Table of Contents

EDA

Growth and Activation 

working = "../../../../School/Graduate 2020-2021/03 - Spring 2021/BADM 577/Illini-Esports-Analysis/"

join = read.csv(paste(working,"guild-activation.csv", sep=""))
join

leave = read.csv(paste(working,"guild-leavers.csv",sep=""))
leave

source = read.csv(paste(working,"guild-joins-by-source.csv",sep=""))
source

A data.frame: 729 × 4
interval_start_timestampnew_memberspct_communicatedpct_opened_channels
<fct><int><dbl><dbl>
2019-03-29T00:00:00+00:002 50.00000 50.00000
2019-03-30T00:00:00+00:006 16.66667 33.33333
2019-03-31T00:00:00+00:008 25.00000 37.50000
2019-04-01T00:00:00+00:009 44.44444 33.33333
2019-04-02T00:00:00+00:002 50.00000100.00000
2019-04-03T00:00:00+00:000 NA NA
2019-04-04T00:00:00+00:002100.00000100.00000
2019-04-05T00:00:00+00:003 33.33333 0.00000
2019-04-06T00:00:00+00:002 0.00000 0.00000
2019-04-07T00:00:00+00:002 0.00000 0.00000
2019-04-08T00:00:00+00:009 33.33333 33.33333
2019-04-09T00:00:00+00:003 33.33333 33.33333
2019-04-10T00:00:00+00:001100.00000100.00000
2019-04-11T00:00:00+00:001 0.00000100.00000
2019-04-12T00:00:00+00:001 0.00000100.00000
2019-04-13T00:00:00+00:001 0.00000100.00000
2019-04-14T00:00:00+00:000 NA NA
2019-04-15T00:00:00+00:000 NA NA
2019-04-16T00:00:00+00:003 66.66667 0.00000
2019-04-17T00:00:00+00:005 0.00000 20.00000
2019-04-18T00:00:00+00:003100.00000 33.33333
2019-04-19T00:00:00+00:003 0.00000 33.33333
2019-04-20T00:00:00+00:000 NA NA
2019-04-21T00:00:00+00:001100.00000100.00000
2019-04-22T00:00:00+00:000 NA NA
2019-04-23T00:00:00+00:001 0.00000 0.00000
2019-04-24T00:00:00+00:003 33.33333 0.00000
2019-04-25T00:00:00+00:003 66.66667 66.66667
2019-04-26T00:00:00+00:003 33.33333 33.33333
2019-04-27T00:00:00+00:001100.00000 0.00000
⋮⋮⋮⋮
2021-02-25T00:00:00+00:00 1 0.00000100.00000
2021-02-26T00:00:00+00:00 540.00000100.00000
2021-02-27T00:00:00+00:00 812.50000100.00000
2021-02-28T00:00:00+00:00 520.00000100.00000
2021-03-01T00:00:00+00:00 2 0.00000 50.00000
2021-03-02T00:00:00+00:00 616.66667 16.66667
2021-03-03T00:00:00+00:00 5 0.00000 40.00000
2021-03-04T00:00:00+00:00 8 0.00000 62.50000
2021-03-05T00:00:00+00:00 333.33333 33.33333
2021-03-06T00:00:00+00:00 3 0.00000 66.66667
2021-03-07T00:00:00+00:00 3 0.00000 33.33333
2021-03-08T00:00:00+00:00 714.28571 42.85714
2021-03-09T00:00:00+00:00 7 0.00000 57.14286
2021-03-10T00:00:00+00:00 5 0.00000 40.00000
2021-03-11T00:00:00+00:00 1 0.00000100.00000
2021-03-12T00:00:00+00:001118.18182 45.45455
2021-03-13T00:00:00+00:00 4 0.00000 50.00000
2021-03-14T00:00:00+00:00 1 0.00000 0.00000
2021-03-15T00:00:00+00:00 1 0.00000 0.00000
2021-03-16T00:00:00+00:00 6 0.00000 83.33333
2021-03-17T00:00:00+00:00 7 0.00000 71.42857
2021-03-18T00:00:00+00:00 1 0.00000 0.00000
2021-03-19T00:00:00+00:00 5 0.00000 80.00000
2021-03-20T00:00:00+00:00 2 0.00000 0.00000
2021-03-21T00:00:00+00:00 633.33333 33.33333
2021-03-22T00:00:00+00:00 520.00000 60.00000
2021-03-23T00:00:00+00:00 1 0.00000 0.00000
2021-03-24T00:00:00+00:00 4 0.00000 50.00000
2021-03-25T00:00:00+00:00 1 0.00000 0.00000
2021-03-26T00:00:00+00:00 4 NA NA
A data.frame: 1104 × 3
interval_start_timestampdays_in_guildleavers
<fct><fct><int>
2019-03-29T00:00:00+00:00'Members for 1 month+' 1
2019-03-30T00:00:00+00:00'Members for 1 month+' 1
2019-03-30T00:00:00+00:00'Members for < 1 month'1
2019-03-31T00:00:00+00:00'Members for 1 month+' 2
2019-03-31T00:00:00+00:00'Members for < 1 month'1
2019-04-01T00:00:00+00:00'Members for 1 month+' 4
2019-04-02T00:00:00+00:00'Members for 1 month+' 1
2019-04-03T00:00:00+00:00'Members for 1 month+' 2
2019-04-03T00:00:00+00:00'Members for < 1 month'2
2019-04-04T00:00:00+00:00'Members for 1 month+' 2
2019-04-04T00:00:00+00:00'Members for < 1 month'2
2019-04-05T00:00:00+00:00'Members for 1 month+' 3
2019-04-06T00:00:00+00:00'Members for 1 month+' 1
2019-04-06T00:00:00+00:00'Members for < 1 month'1
2019-04-07T00:00:00+00:00'Members for 1 month+' 1
2019-04-07T00:00:00+00:00'Members for < 1 month'2
2019-04-08T00:00:00+00:00'Members for 1 month+' 1
2019-04-08T00:00:00+00:00'Members for < 1 month'1
2019-04-09T00:00:00+00:00'Members for 1 month+' 1
2019-04-09T00:00:00+00:00'Members for < 1 month'1
2019-04-10T00:00:00+00:00'Members for 1 month+' 2
2019-04-10T00:00:00+00:00'Members for < 1 month'1
2019-04-11T00:00:00+00:00'Members for 1 month+' 0
2019-04-12T00:00:00+00:00'Members for 1 month+' 1
2019-04-13T00:00:00+00:00'Members for < 1 month'1
2019-04-14T00:00:00+00:00'Members for 1 month+' 2
2019-04-15T00:00:00+00:00'Members for 1 month+' 1
2019-04-15T00:00:00+00:00'Members for < 1 month'1
2019-04-16T00:00:00+00:00'Members for 1 month+' 3
2019-04-16T00:00:00+00:00'Members for < 1 month'1
⋮⋮⋮
2021-03-09T00:00:00+00:00'Members for 1 month+' 2
2021-03-09T00:00:00+00:00'Members for < 1 month'1
2021-03-10T00:00:00+00:00'Members for 1 month+' 2
2021-03-10T00:00:00+00:00'Members for < 1 month'3
2021-03-11T00:00:00+00:00'Members for 1 month+' 2
2021-03-12T00:00:00+00:00'Members for 1 month+' 1
2021-03-12T00:00:00+00:00'Members for < 1 month'5
2021-03-13T00:00:00+00:00'Members for < 1 month'1
2021-03-14T00:00:00+00:00'Members for 1 month+' 1
2021-03-14T00:00:00+00:00'Members for < 1 month'1
2021-03-15T00:00:00+00:00'Members for 1 month+' 2
2021-03-16T00:00:00+00:00'Members for 1 month+' 1
2021-03-16T00:00:00+00:00'Members for < 1 month'3
2021-03-17T00:00:00+00:00'Members for 1 month+' 4
2021-03-17T00:00:00+00:00'Members for < 1 month'2
2021-03-18T00:00:00+00:00'Members for < 1 month'1
2021-03-19T00:00:00+00:00'Members for 1 month+' 2
2021-03-19T00:00:00+00:00'Members for < 1 month'2
2021-03-20T00:00:00+00:00'Members for 1 month+' 5
2021-03-20T00:00:00+00:00'Members for < 1 month'1
2021-03-21T00:00:00+00:00'Members for 1 month+' 1
2021-03-21T00:00:00+00:00'Members for < 1 month'3
2021-03-22T00:00:00+00:00'Members for 1 month+' 1
2021-03-23T00:00:00+00:00'Members for 1 month+' 3
2021-03-23T00:00:00+00:00'Members for < 1 month'1
2021-03-24T00:00:00+00:00'Members for 1 month+' 0
2021-03-25T00:00:00+00:00'Members for 1 month+' 2
2021-03-25T00:00:00+00:00'Members for < 1 month'1
2021-03-26T00:00:00+00:00'Members for 1 month+' 3
2021-03-26T00:00:00+00:00'Members for < 1 month'1
A data.frame: 729 × 4
interval_start_timestampdiscovery_joinsinvitesvanity_joins
<fct><int><int><int>
2019-03-29T00:00:00+00:0000 3
2019-03-30T00:00:00+00:0000 7
2019-03-31T00:00:00+00:0000 8
2019-04-01T00:00:00+00:000011
2019-04-02T00:00:00+00:0000 2
2019-04-03T00:00:00+00:0000 1
2019-04-04T00:00:00+00:0000 3
2019-04-05T00:00:00+00:0000 4
2019-04-06T00:00:00+00:0000 3
2019-04-07T00:00:00+00:0000 2
2019-04-08T00:00:00+00:0000 9
2019-04-09T00:00:00+00:0000 3
2019-04-10T00:00:00+00:0000 1
2019-04-11T00:00:00+00:0000 2
2019-04-12T00:00:00+00:0000 1
2019-04-13T00:00:00+00:0000 1
2019-04-14T00:00:00+00:0000 0
2019-04-15T00:00:00+00:0000 0
2019-04-16T00:00:00+00:0000 7
2019-04-17T00:00:00+00:0000 5
2019-04-18T00:00:00+00:0000 6
2019-04-19T00:00:00+00:0000 3
2019-04-20T00:00:00+00:0000 2
2019-04-21T00:00:00+00:0000 1
2019-04-22T00:00:00+00:0000 1
2019-04-23T00:00:00+00:0000 3
2019-04-24T00:00:00+00:0000 3
2019-04-25T00:00:00+00:0000 3
2019-04-26T00:00:00+00:0000 4
2019-04-27T00:00:00+00:0000 3
⋮⋮⋮⋮
2021-02-25T00:00:00+00:0000 1
2021-02-26T00:00:00+00:0000 6
2021-02-27T00:00:00+00:0000 9
2021-02-28T00:00:00+00:0000 5
2021-03-01T00:00:00+00:0000 3
2021-03-02T00:00:00+00:0000 6
2021-03-03T00:00:00+00:0000 5
2021-03-04T00:00:00+00:0000 8
2021-03-05T00:00:00+00:0000 4
2021-03-06T00:00:00+00:0000 3
2021-03-07T00:00:00+00:0000 4
2021-03-08T00:00:00+00:0000 7
2021-03-09T00:00:00+00:0010 6
2021-03-10T00:00:00+00:0000 5
2021-03-11T00:00:00+00:0000 2
2021-03-12T00:00:00+00:000011
2021-03-13T00:00:00+00:0010 3
2021-03-14T00:00:00+00:0000 1
2021-03-15T00:00:00+00:0000 2
2021-03-16T00:00:00+00:0010 6
2021-03-17T00:00:00+00:0010 9
2021-03-18T00:00:00+00:0000 1
2021-03-19T00:00:00+00:0010 4
2021-03-20T00:00:00+00:0000 2
2021-03-21T00:00:00+00:0000 7
2021-03-22T00:00:00+00:0000 6
2021-03-23T00:00:00+00:0000 1
2021-03-24T00:00:00+00:0000 5
2021-03-25T00:00:00+00:0000 2
2021-03-26T00:00:00+00:0000 4

Historical Engagement 

message = read.csv(paste(working,"guild-message-activity.csv",sep=""))
message

voice = read.csv(paste(working,"guild-voice-activity.csv",sep=""))
voice

communicator = read.csv(paste(working,"guild-communicators.csv",sep=""))
communicator

A data.frame: 729 × 3
interval_start_timestampmessagesmessages_per_communicator
<fct><int><dbl>
2019-03-29T00:00:00+00:00 334 6.301887
2019-03-30T00:00:00+00:00 236 6.210526
2019-03-31T00:00:00+00:00 364 8.088889
2019-04-01T00:00:00+00:00 404 5.386667
2019-04-02T00:00:00+00:00 54311.312500
2019-04-03T00:00:00+00:00 324 7.200000
2019-04-04T00:00:00+00:00 55610.901961
2019-04-05T00:00:00+00:00 273 5.808511
2019-04-06T00:00:00+00:00 335 7.613636
2019-04-07T00:00:00+00:00110222.040000
2019-04-08T00:00:00+00:00 188 4.476190
2019-04-09T00:00:00+00:00 399 8.673913
2019-04-10T00:00:00+00:00 53110.620000
2019-04-11T00:00:00+00:00 68913.000000
2019-04-12T00:00:00+00:00 418 9.086957
2019-04-13T00:00:00+00:00 56613.162791
2019-04-14T00:00:00+00:00 48112.025000
2019-04-15T00:00:00+00:00 65913.180000
2019-04-16T00:00:00+00:00 77912.770492
2019-04-17T00:00:00+00:00 59611.245283
2019-04-18T00:00:00+00:00114315.657534
2019-04-19T00:00:00+00:00 89816.327273
2019-04-20T00:00:00+00:00 331 6.490196
2019-04-21T00:00:00+00:00 47311.000000
2019-04-22T00:00:00+00:00 283 7.256410
2019-04-23T00:00:00+00:00127021.896552
2019-04-24T00:00:00+00:00 74614.346154
2019-04-25T00:00:00+00:00 287 5.519231
2019-04-26T00:00:00+00:00 72811.555556
2019-04-27T00:00:00+00:00 69112.339286
⋮⋮⋮
2021-02-25T00:00:00+00:001383.450000
2021-02-26T00:00:00+00:00 782.437500
2021-02-27T00:00:00+00:00 932.162791
2021-02-28T00:00:00+00:00 461.533333
2021-03-01T00:00:00+00:00 531.766667
2021-03-02T00:00:00+00:00 722.400000
2021-03-03T00:00:00+00:001224.066667
2021-03-04T00:00:00+00:001684.941176
2021-03-05T00:00:00+00:00 742.387097
2021-03-06T00:00:00+00:00 431.482759
2021-03-07T00:00:00+00:00 431.720000
2021-03-08T00:00:00+00:001063.312500
2021-03-09T00:00:00+00:001143.081081
2021-03-10T00:00:00+00:00 832.593750
2021-03-11T00:00:00+00:001092.725000
2021-03-12T00:00:00+00:00 752.027027
2021-03-13T00:00:00+00:001584.647059
2021-03-14T00:00:00+00:00 732.433333
2021-03-15T00:00:00+00:00 732.517241
2021-03-16T00:00:00+00:00 521.575758
2021-03-17T00:00:00+00:00 642.064516
2021-03-18T00:00:00+00:00 652.096774
2021-03-19T00:00:00+00:001823.500000
2021-03-20T00:00:00+00:001212.880952
2021-03-21T00:00:00+00:001573.925000
2021-03-22T00:00:00+00:00 942.410256
2021-03-23T00:00:00+00:00 341.416667
2021-03-24T00:00:00+00:00 511.888889
2021-03-25T00:00:00+00:001202.857143
2021-03-26T00:00:00+00:001223.485714
A data.frame: 729 × 2
interval_start_timestampspeaking_minutes
<fct><int>
2019-03-29T00:00:00+00:000
2019-03-30T00:00:00+00:000
2019-03-31T00:00:00+00:000
2019-04-01T00:00:00+00:000
2019-04-02T00:00:00+00:000
2019-04-03T00:00:00+00:000
2019-04-04T00:00:00+00:000
2019-04-05T00:00:00+00:000
2019-04-06T00:00:00+00:000
2019-04-07T00:00:00+00:000
2019-04-08T00:00:00+00:000
2019-04-09T00:00:00+00:000
2019-04-10T00:00:00+00:000
2019-04-11T00:00:00+00:000
2019-04-12T00:00:00+00:000
2019-04-13T00:00:00+00:000
2019-04-14T00:00:00+00:000
2019-04-15T00:00:00+00:000
2019-04-16T00:00:00+00:000
2019-04-17T00:00:00+00:000
2019-04-18T00:00:00+00:000
2019-04-19T00:00:00+00:000
2019-04-20T00:00:00+00:000
2019-04-21T00:00:00+00:000
2019-04-22T00:00:00+00:000
2019-04-23T00:00:00+00:000
2019-04-24T00:00:00+00:000
2019-04-25T00:00:00+00:000
2019-04-26T00:00:00+00:000
2019-04-27T00:00:00+00:000
⋮⋮
2021-02-25T00:00:00+00:001495
2021-02-26T00:00:00+00:00 913
2021-02-27T00:00:00+00:001118
2021-02-28T00:00:00+00:001354
2021-03-01T00:00:00+00:001269
2021-03-02T00:00:00+00:001200
2021-03-03T00:00:00+00:002031
2021-03-04T00:00:00+00:002293
2021-03-05T00:00:00+00:001124
2021-03-06T00:00:00+00:001398
2021-03-07T00:00:00+00:001460
2021-03-08T00:00:00+00:001834
2021-03-09T00:00:00+00:001523
2021-03-10T00:00:00+00:001119
2021-03-11T00:00:00+00:001878
2021-03-12T00:00:00+00:001429
2021-03-13T00:00:00+00:00 730
2021-03-14T00:00:00+00:00 567
2021-03-15T00:00:00+00:001282
2021-03-16T00:00:00+00:001234
2021-03-17T00:00:00+00:001146
2021-03-18T00:00:00+00:002464
2021-03-19T00:00:00+00:00 840
2021-03-20T00:00:00+00:00 428
2021-03-21T00:00:00+00:00 880
2021-03-22T00:00:00+00:001598
2021-03-23T00:00:00+00:00 873
2021-03-24T00:00:00+00:00 771
2021-03-25T00:00:00+00:001742
2021-03-26T00:00:00+00:001038
A data.frame: 729 × 3
interval_start_timestampvisitorspct_communicated
<fct><int><dbl>
2019-03-29T00:00:00+00:0020625.72816
2019-03-30T00:00:00+00:0018420.65217
2019-03-31T00:00:00+00:0018524.32432
2019-04-01T00:00:00+00:0032822.86585
2019-04-02T00:00:00+00:0014333.56643
2019-04-03T00:00:00+00:0027116.60517
2019-04-04T00:00:00+00:0038113.38583
2019-04-05T00:00:00+00:0019024.73684
2019-04-06T00:00:00+00:0016326.99387
2019-04-07T00:00:00+00:0015931.44654
2019-04-08T00:00:00+00:0016325.76687
2019-04-09T00:00:00+00:0014831.08108
2019-04-10T00:00:00+00:0016330.67485
2019-04-11T00:00:00+00:0013938.12950
2019-04-12T00:00:00+00:0015529.67742
2019-04-13T00:00:00+00:0014330.06993
2019-04-14T00:00:00+00:0014028.57143
2019-04-15T00:00:00+00:0017029.41176
2019-04-16T00:00:00+00:0015040.66667
2019-04-17T00:00:00+00:0015334.64052
2019-04-18T00:00:00+00:0016743.71257
2019-04-19T00:00:00+00:0016233.95062
2019-04-20T00:00:00+00:0033715.13353
2019-04-21T00:00:00+00:0017225.00000
2019-04-22T00:00:00+00:0016224.07407
2019-04-23T00:00:00+00:0016335.58282
2019-04-24T00:00:00+00:0034015.29412
2019-04-25T00:00:00+00:0019626.53061
2019-04-26T00:00:00+00:0037116.98113
2019-04-27T00:00:00+00:0020127.86070
⋮⋮⋮
2021-02-25T00:00:00+00:0017223.255814
2021-02-26T00:00:00+00:0016719.161677
2021-02-27T00:00:00+00:0020820.673077
2021-02-28T00:00:00+00:0016717.964072
2021-03-01T00:00:00+00:0016418.292683
2021-03-02T00:00:00+00:0019915.075377
2021-03-03T00:00:00+00:0016318.404908
2021-03-04T00:00:00+00:0016320.858896
2021-03-05T00:00:00+00:0017917.318436
2021-03-06T00:00:00+00:00304 9.539474
2021-03-07T00:00:00+00:0016215.432099
2021-03-08T00:00:00+00:0023413.675214
2021-03-09T00:00:00+00:0016023.125000
2021-03-10T00:00:00+00:0015620.512821
2021-03-11T00:00:00+00:00553 7.233273
2021-03-12T00:00:00+00:0025314.624506
2021-03-13T00:00:00+00:0023714.345992
2021-03-14T00:00:00+00:0014720.408163
2021-03-15T00:00:00+00:0015418.831169
2021-03-16T00:00:00+00:0015421.428571
2021-03-17T00:00:00+00:0014121.985816
2021-03-18T00:00:00+00:0015320.261438
2021-03-19T00:00:00+00:0026819.402985
2021-03-20T00:00:00+00:00658 6.382979
2021-03-21T00:00:00+00:0017023.529412
2021-03-22T00:00:00+00:0017422.413793
2021-03-23T00:00:00+00:0014316.783217
2021-03-24T00:00:00+00:0015717.197452
2021-03-25T00:00:00+00:0016525.454545
2021-03-26T00:00:00+00:00573 6.108202

Engagement by last 28 days 

text = read.csv(paste(working,"popular-text-channels.csv",sep=""))
text
voice_channel = read.csv(paste(working,"popular-voice-channels.csv",sep=""))
voice_channel

A data.frame: 92 × 6
interval_start_timestampchannel_namechannel_idreaderschattersmessages
<fct><fct><dbl><int><int><int>
2021-03-27T00:00:00+00:00general 2.124359e+1721851264
2021-03-27T00:00:00+00:00hearthstone 2.124361e+17 3 0 0
2021-03-27T00:00:00+00:00overwatch 2.124362e+17 9838794
2021-03-27T00:00:00+00:00lol 2.124362e+17 9731181
2021-03-27T00:00:00+00:00csgo 2.124363e+17 29 4 5
2021-03-27T00:00:00+00:00dota2 2.124364e+17 17 5 11
2021-03-27T00:00:00+00:00announcements 2.124422e+17880 1 4
2021-03-27T00:00:00+00:00other-games 2.127412e+17 46 7 13
2021-03-27T00:00:00+00:00suggestions 2.130108e+17 27 4 5
2021-03-27T00:00:00+00:00memes 2.170801e+17 7111 36
2021-03-27T00:00:00+00:00rocketleague 2.173062e+17 5 0 0
2021-03-27T00:00:00+00:00music_channel 2.182282e+17 20 3 11
2021-03-27T00:00:00+00:00bot-stuff 2.185181e+17 47 9326
2021-03-27T00:00:00+00:00overwatch_info 2.185562e+17154 2 7
2021-03-27T00:00:00+00:00casual-smite 2.187252e+17 1 0 0
2021-03-27T00:00:00+00:00lol_info 2.254194e+17212 4 8
2021-03-27T00:00:00+00:00runescape 2.573993e+17 15 1 7
2021-03-27T00:00:00+00:00dota_info 2.793684e+17 1 0 0
2021-03-27T00:00:00+00:00osu 2.808585e+17 33 4 15
2021-03-27T00:00:00+00:00study_buddies 2.971659e+17 23 8 34
2021-03-27T00:00:00+00:00testing-bots 3.308046e+17 1 0 0
2021-03-27T00:00:00+00:00around-town 3.511549e+17 28 9 16
2021-03-27T00:00:00+00:00console-games 3.515872e+17 1 0 0
2021-03-27T00:00:00+00:00rainbow-6 3.595436e+17 21 4 9
2021-03-27T00:00:00+00:00tech-talk 3.656845e+17 4914 90
2021-03-27T00:00:00+00:00sports 3.675733e+17 4514105
2021-03-27T00:00:00+00:00destiny2 3.731533e+17 18 2 4
2021-03-27T00:00:00+00:00anime 3.733290e+17 7019 74
2021-03-27T00:00:00+00:00smite_info 3.776109e+17 22 1 1
2021-03-27T00:00:00+00:00crowns_feedback3.794238e+17 1 0 0
⋮⋮⋮⋮⋮⋮
2021-03-27T00:00:00+00:00valorant_info 6.958404e+17168 1 5
2021-03-27T00:00:00+00:00valorant_news 6.964060e+17 20 1 3
2021-03-27T00:00:00+00:00valorant_lfg 6.994457e+17 6213 43
2021-03-27T00:00:00+00:00stream-highlights 7.055643e+17 2 0 0
2021-03-27T00:00:00+00:00virtual-reality-info 7.164619e+17 25 0 0
2021-03-27T00:00:00+00:00virtual-reality 7.164626e+17 11 2 7
2021-03-27T00:00:00+00:00competitive-smite 7.226659e+17 10 3 8
2021-03-27T00:00:00+00:00smash-info 7.272015e+17 8 1 2
2021-03-27T00:00:00+00:00minecraft-rules 7.333804e+17 1 0 0
2021-03-27T00:00:00+00:00altdentifier-updates 7.362728e+17 5 0 0
2021-03-27T00:00:00+00:00moderator-only 7.413646e+17 1 0 0
2021-03-27T00:00:00+00:00social-gaming-info 7.505845e+17 37 1 5
2021-03-27T00:00:00+00:00marketplace-listings 7.511623e+17 25 2 2
2021-03-27T00:00:00+00:00bot-updates 7.512931e+17 1 4 6
2021-03-27T00:00:00+00:00yagpdb-bot-logs 7.548220e+17 8 0 0
2021-03-27T00:00:00+00:003v3-lft 7.556002e+17 5 2 2
2021-03-27T00:00:00+00:00tourney-info 7.556008e+17 1 0 0
2021-03-27T00:00:00+00:00partner-servers 7.603847e+17 5 0 0
2021-03-27T00:00:00+00:00read-me-first 7.605702e+17 9 0 0
2021-03-27T00:00:00+00:00genshin-impact 7.638568e+17 53 9159
2021-03-27T00:00:00+00:00shib-logs 7.697164e+17 3 0 0
2021-03-27T00:00:00+00:00server-logs 7.697269e+17 4 0 0
2021-03-27T00:00:00+00:00cloud9-affiliate-discord7.768122e+17 87 1 9
2021-03-27T00:00:00+00:00tournament-screen-shots 7.973465e+17 30 4 10
2021-03-27T00:00:00+00:00alea-3631 8.015882e+17 1 0 0
2021-03-27T00:00:00+00:00hearthstone-news 8.040561e+17 1 0 0
2021-03-27T00:00:00+00:00server-change-log 8.045228e+17 36 1 1
2021-03-27T00:00:00+00:00master-overwatch 8.073712e+17 51 1 9
2021-03-27T00:00:00+00:00team-fortress-2 8.152788e+17 50 4 53
2021-03-27T00:00:00+00:00vc-context 8.224238e+17 43 5 11
A data.frame: 12 × 5
interval_start_timestampchannel_namechannel_idlistenerscommunicators
<fct><fct><dbl><int><int>
2021-03-27T00:00:00+00:00AFK Channel 2.559102e+17 7 0
2021-03-27T00:00:00+00:00Overwatch Oasis 2.617080e+171716
2021-03-27T00:00:00+00:00LoL In-House Lobby2.834215e+17 2 2
2021-03-27T00:00:00+00:00Overwatch Room 1 3.533817e+171716
2021-03-27T00:00:00+00:00General Gaming 5.960341e+171010
2021-03-27T00:00:00+00:00Music Channel 5.960341e+17 2 3
2021-03-27T00:00:00+00:00Overwatch Room 2 6.000934e+171414
2021-03-27T00:00:00+00:00Throwstack Oasis 6.153540e+171414
2021-03-27T00:00:00+00:00Valorant Haven 6.958620e+17 3 3
2021-03-27T00:00:00+00:00Social Gaming 6.960872e+171514
2021-03-27T00:00:00+00:00IE-LIVE 7.687174e+17 1 0
2021-03-27T00:00:00+00:00Apex Oasis 8.093469e+172827

ETL on Growth and Activation

Messing around with date time

Loading the library 

library(lubridate)

Datetime example

I grabbed this example from astrostats.psu. The Berkely Stat Dates page Dates and Times in R was a great reference for the code and values for datetime

Code Value
%d Day of the month (decimal number)
%m Month (decimal number)
%b Month (abbreviated)
%B Month (full name)
%y Year (2 digit)
%Y Year (4 digit) 
dates <- c("02/27/92", "02/27/92", "01/14/92", "02/28/92", "02/01/92")
times <- c("23:03:20", "22:29:56", "01:03:30", "18:21:03", "16:56:26")
x <- paste(dates, times)
strptime(x, "%m/%d/%y %H:%M:%S")
strptime(x, "%m/")

[1] "1992-02-27 23:03:20 CST" "1992-02-27 22:29:56 CST"
[3] "1992-01-14 01:03:30 CST" "1992-02-28 18:21:03 CST"
[5] "1992-02-01 16:56:26 CST"
[1] NA NA NA NA NA

Tests to investigate how to extract date time

These were scuffed tests I used to learn how to extract the date time

  • the variable test made me realize removing +00:00 and replacing it with a Z would make the data in a format that can be read by R
  • the variable test2 was my attempt to try getting it for an entire column
test = "2021-03-27T00:00:00Z"
str(ymd_hms(test))

test2 = join$interval_start_timestamp
#test2
#ymd_hms(join$interval_start_timestamp)
head(strptime(test2, "%Y-%m-%dT%H:%M:%SZ"))

 POSIXct[1:1], format: "2021-03-27"

[1] "2019-03-29 CDT" "2019-03-30 CDT" "2019-03-31 CDT" "2019-04-01 CDT"
[5] "2019-04-02 CDT" "2019-04-03 CDT"

While performing my tests, I struggled understanding format of the date was in, a search of a 2021-03-27T00:00:00+00:00 datatype pointed me to a stack overflow page that helped me learn more about python functions Date Time Formats in Python.

Testing substring removal

  • with a understanding of what I needed to make it possible, I moved on to learn about substring replacement. This took a long time to figure out and understand.

Removing the plus sign

a search of R remove all text after plus sign helped me break through this barrier I found that this answer on stackoverflow was particularly helpful in removing the + sign How to remove + (plus sign) from string in R?. gsub seemed to be the recommend choice among all answers

Removing the rest of zeros

I found the following stackoverflow answer that had a example for how to remove the rest of a string Remove all text before colon. I couldn't remember how to remove everything after the + so the following example from stevencarlislewalker's blog was particularly helpful in refreshing my memory Remove (or replace) everything before or after a specified character in R strings

gsub("\\+.*", 'Z', "2021-03-27T00:00:00+00:00")
'2021-03-27T00:00:00Z'

Removing +00:00Z from the whole column

these were tests I ran to automate this for all the datetime rows.

#join[1,1] = gsub("\\+.*", 'Z', join[1,1])
#join

join[,1] = gsub("\\+.*", 'Z', join[,1])
join

A data.frame: 729 × 4
interval_start_timestampnew_memberspct_communicatedpct_opened_channels
<chr><int><dbl><dbl>
2019-03-29T00:00:00Z2 50.00000 50.00000
2019-03-30T00:00:00Z6 16.66667 33.33333
2019-03-31T00:00:00Z8 25.00000 37.50000
2019-04-01T00:00:00Z9 44.44444 33.33333
2019-04-02T00:00:00Z2 50.00000100.00000
2019-04-03T00:00:00Z0 NA NA
2019-04-04T00:00:00Z2100.00000100.00000
2019-04-05T00:00:00Z3 33.33333 0.00000
2019-04-06T00:00:00Z2 0.00000 0.00000
2019-04-07T00:00:00Z2 0.00000 0.00000
2019-04-08T00:00:00Z9 33.33333 33.33333
2019-04-09T00:00:00Z3 33.33333 33.33333
2019-04-10T00:00:00Z1100.00000100.00000
2019-04-11T00:00:00Z1 0.00000100.00000
2019-04-12T00:00:00Z1 0.00000100.00000
2019-04-13T00:00:00Z1 0.00000100.00000
2019-04-14T00:00:00Z0 NA NA
2019-04-15T00:00:00Z0 NA NA
2019-04-16T00:00:00Z3 66.66667 0.00000
2019-04-17T00:00:00Z5 0.00000 20.00000
2019-04-18T00:00:00Z3100.00000 33.33333
2019-04-19T00:00:00Z3 0.00000 33.33333
2019-04-20T00:00:00Z0 NA NA
2019-04-21T00:00:00Z1100.00000100.00000
2019-04-22T00:00:00Z0 NA NA
2019-04-23T00:00:00Z1 0.00000 0.00000
2019-04-24T00:00:00Z3 33.33333 0.00000
2019-04-25T00:00:00Z3 66.66667 66.66667
2019-04-26T00:00:00Z3 33.33333 33.33333
2019-04-27T00:00:00Z1100.00000 0.00000
⋮⋮⋮⋮
2021-02-25T00:00:00Z 1 0.00000100.00000
2021-02-26T00:00:00Z 540.00000100.00000
2021-02-27T00:00:00Z 812.50000100.00000
2021-02-28T00:00:00Z 520.00000100.00000
2021-03-01T00:00:00Z 2 0.00000 50.00000
2021-03-02T00:00:00Z 616.66667 16.66667
2021-03-03T00:00:00Z 5 0.00000 40.00000
2021-03-04T00:00:00Z 8 0.00000 62.50000
2021-03-05T00:00:00Z 333.33333 33.33333
2021-03-06T00:00:00Z 3 0.00000 66.66667
2021-03-07T00:00:00Z 3 0.00000 33.33333
2021-03-08T00:00:00Z 714.28571 42.85714
2021-03-09T00:00:00Z 7 0.00000 57.14286
2021-03-10T00:00:00Z 5 0.00000 40.00000
2021-03-11T00:00:00Z 1 0.00000100.00000
2021-03-12T00:00:00Z1118.18182 45.45455
2021-03-13T00:00:00Z 4 0.00000 50.00000
2021-03-14T00:00:00Z 1 0.00000 0.00000
2021-03-15T00:00:00Z 1 0.00000 0.00000
2021-03-16T00:00:00Z 6 0.00000 83.33333
2021-03-17T00:00:00Z 7 0.00000 71.42857
2021-03-18T00:00:00Z 1 0.00000 0.00000
2021-03-19T00:00:00Z 5 0.00000 80.00000
2021-03-20T00:00:00Z 2 0.00000 0.00000
2021-03-21T00:00:00Z 633.33333 33.33333
2021-03-22T00:00:00Z 520.00000 60.00000
2021-03-23T00:00:00Z 1 0.00000 0.00000
2021-03-24T00:00:00Z 4 0.00000 50.00000
2021-03-25T00:00:00Z 1 0.00000 0.00000
2021-03-26T00:00:00Z 4 NA NA

split the interval_start_timestamp

Once I got it working on a row, I applied what I learned above to extract the year, month, and day from the initial datetime object Later when I was generating the bar charts, I had issues ordering the data by calendar months, a quick search yielded Sorting months in R I learned that passing months into factor with the levels = month.name would allow me to sort by the months

year = year(as.POSIXlt(join$interval_start_timestamp))

month = factor(months(as.POSIXlt(join$interval_start_timestamp)),levels = month.name)

day = weekdays(as.POSIXlt(join$interval_start_timestamp))

Making the new dataframe

After making the split dataframes, I used a cbind to append the columns to the original dataset and reordered the dataset.

joins = cbind(join, year, month,day)
joins

joins = joins[,c(1,5,6,7,2,3,4)]
joins

A data.frame: 729 × 7
interval_start_timestampnew_memberspct_communicatedpct_opened_channelsyearmonthday
<chr><int><dbl><dbl><dbl><fct><fct>
2019-03-29T00:00:00Z2 50.00000 50.000002019MarchFriday
2019-03-30T00:00:00Z6 16.66667 33.333332019MarchSaturday
2019-03-31T00:00:00Z8 25.00000 37.500002019MarchSunday
2019-04-01T00:00:00Z9 44.44444 33.333332019AprilMonday
2019-04-02T00:00:00Z2 50.00000100.000002019AprilTuesday
2019-04-03T00:00:00Z0 NA NA2019AprilWednesday
2019-04-04T00:00:00Z2100.00000100.000002019AprilThursday
2019-04-05T00:00:00Z3 33.33333 0.000002019AprilFriday
2019-04-06T00:00:00Z2 0.00000 0.000002019AprilSaturday
2019-04-07T00:00:00Z2 0.00000 0.000002019AprilSunday
2019-04-08T00:00:00Z9 33.33333 33.333332019AprilMonday
2019-04-09T00:00:00Z3 33.33333 33.333332019AprilTuesday
2019-04-10T00:00:00Z1100.00000100.000002019AprilWednesday
2019-04-11T00:00:00Z1 0.00000100.000002019AprilThursday
2019-04-12T00:00:00Z1 0.00000100.000002019AprilFriday
2019-04-13T00:00:00Z1 0.00000100.000002019AprilSaturday
2019-04-14T00:00:00Z0 NA NA2019AprilSunday
2019-04-15T00:00:00Z0 NA NA2019AprilMonday
2019-04-16T00:00:00Z3 66.66667 0.000002019AprilTuesday
2019-04-17T00:00:00Z5 0.00000 20.000002019AprilWednesday
2019-04-18T00:00:00Z3100.00000 33.333332019AprilThursday
2019-04-19T00:00:00Z3 0.00000 33.333332019AprilFriday
2019-04-20T00:00:00Z0 NA NA2019AprilSaturday
2019-04-21T00:00:00Z1100.00000100.000002019AprilSunday
2019-04-22T00:00:00Z0 NA NA2019AprilMonday
2019-04-23T00:00:00Z1 0.00000 0.000002019AprilTuesday
2019-04-24T00:00:00Z3 33.33333 0.000002019AprilWednesday
2019-04-25T00:00:00Z3 66.66667 66.666672019AprilThursday
2019-04-26T00:00:00Z3 33.33333 33.333332019AprilFriday
2019-04-27T00:00:00Z1100.00000 0.000002019AprilSaturday
⋮⋮⋮⋮⋮⋮⋮
2021-02-25T00:00:00Z 1 0.00000100.000002021FebruaryThursday
2021-02-26T00:00:00Z 540.00000100.000002021FebruaryFriday
2021-02-27T00:00:00Z 812.50000100.000002021FebruarySaturday
2021-02-28T00:00:00Z 520.00000100.000002021FebruarySunday
2021-03-01T00:00:00Z 2 0.00000 50.000002021March Monday
2021-03-02T00:00:00Z 616.66667 16.666672021March Tuesday
2021-03-03T00:00:00Z 5 0.00000 40.000002021March Wednesday
2021-03-04T00:00:00Z 8 0.00000 62.500002021March Thursday
2021-03-05T00:00:00Z 333.33333 33.333332021March Friday
2021-03-06T00:00:00Z 3 0.00000 66.666672021March Saturday
2021-03-07T00:00:00Z 3 0.00000 33.333332021March Sunday
2021-03-08T00:00:00Z 714.28571 42.857142021March Monday
2021-03-09T00:00:00Z 7 0.00000 57.142862021March Tuesday
2021-03-10T00:00:00Z 5 0.00000 40.000002021March Wednesday
2021-03-11T00:00:00Z 1 0.00000100.000002021March Thursday
2021-03-12T00:00:00Z1118.18182 45.454552021March Friday
2021-03-13T00:00:00Z 4 0.00000 50.000002021March Saturday
2021-03-14T00:00:00Z 1 0.00000 0.000002021March Sunday
2021-03-15T00:00:00Z 1 0.00000 0.000002021March Monday
2021-03-16T00:00:00Z 6 0.00000 83.333332021March Tuesday
2021-03-17T00:00:00Z 7 0.00000 71.428572021March Wednesday
2021-03-18T00:00:00Z 1 0.00000 0.000002021March Thursday
2021-03-19T00:00:00Z 5 0.00000 80.000002021March Friday
2021-03-20T00:00:00Z 2 0.00000 0.000002021March Saturday
2021-03-21T00:00:00Z 633.33333 33.333332021March Sunday
2021-03-22T00:00:00Z 520.00000 60.000002021March Monday
2021-03-23T00:00:00Z 1 0.00000 0.000002021March Tuesday
2021-03-24T00:00:00Z 4 0.00000 50.000002021March Wednesday
2021-03-25T00:00:00Z 1 0.00000 0.000002021March Thursday
2021-03-26T00:00:00Z 4 NA NA2021March Friday
A data.frame: 729 × 7
interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channels
<chr><dbl><fct><fct><int><dbl><dbl>
2019-03-29T00:00:00Z2019MarchFriday 2 50.00000 50.00000
2019-03-30T00:00:00Z2019MarchSaturday 6 16.66667 33.33333
2019-03-31T00:00:00Z2019MarchSunday 8 25.00000 37.50000
2019-04-01T00:00:00Z2019AprilMonday 9 44.44444 33.33333
2019-04-02T00:00:00Z2019AprilTuesday 2 50.00000100.00000
2019-04-03T00:00:00Z2019AprilWednesday0 NA NA
2019-04-04T00:00:00Z2019AprilThursday 2100.00000100.00000
2019-04-05T00:00:00Z2019AprilFriday 3 33.33333 0.00000
2019-04-06T00:00:00Z2019AprilSaturday 2 0.00000 0.00000
2019-04-07T00:00:00Z2019AprilSunday 2 0.00000 0.00000
2019-04-08T00:00:00Z2019AprilMonday 9 33.33333 33.33333
2019-04-09T00:00:00Z2019AprilTuesday 3 33.33333 33.33333
2019-04-10T00:00:00Z2019AprilWednesday1100.00000100.00000
2019-04-11T00:00:00Z2019AprilThursday 1 0.00000100.00000
2019-04-12T00:00:00Z2019AprilFriday 1 0.00000100.00000
2019-04-13T00:00:00Z2019AprilSaturday 1 0.00000100.00000
2019-04-14T00:00:00Z2019AprilSunday 0 NA NA
2019-04-15T00:00:00Z2019AprilMonday 0 NA NA
2019-04-16T00:00:00Z2019AprilTuesday 3 66.66667 0.00000
2019-04-17T00:00:00Z2019AprilWednesday5 0.00000 20.00000
2019-04-18T00:00:00Z2019AprilThursday 3100.00000 33.33333
2019-04-19T00:00:00Z2019AprilFriday 3 0.00000 33.33333
2019-04-20T00:00:00Z2019AprilSaturday 0 NA NA
2019-04-21T00:00:00Z2019AprilSunday 1100.00000100.00000
2019-04-22T00:00:00Z2019AprilMonday 0 NA NA
2019-04-23T00:00:00Z2019AprilTuesday 1 0.00000 0.00000
2019-04-24T00:00:00Z2019AprilWednesday3 33.33333 0.00000
2019-04-25T00:00:00Z2019AprilThursday 3 66.66667 66.66667
2019-04-26T00:00:00Z2019AprilFriday 3 33.33333 33.33333
2019-04-27T00:00:00Z2019AprilSaturday 1100.00000 0.00000
⋮⋮⋮⋮⋮⋮⋮
2021-02-25T00:00:00Z2021FebruaryThursday 1 0.00000100.00000
2021-02-26T00:00:00Z2021FebruaryFriday 540.00000100.00000
2021-02-27T00:00:00Z2021FebruarySaturday 812.50000100.00000
2021-02-28T00:00:00Z2021FebruarySunday 520.00000100.00000
2021-03-01T00:00:00Z2021March Monday 2 0.00000 50.00000
2021-03-02T00:00:00Z2021March Tuesday 616.66667 16.66667
2021-03-03T00:00:00Z2021March Wednesday 5 0.00000 40.00000
2021-03-04T00:00:00Z2021March Thursday 8 0.00000 62.50000
2021-03-05T00:00:00Z2021March Friday 333.33333 33.33333
2021-03-06T00:00:00Z2021March Saturday 3 0.00000 66.66667
2021-03-07T00:00:00Z2021March Sunday 3 0.00000 33.33333
2021-03-08T00:00:00Z2021March Monday 714.28571 42.85714
2021-03-09T00:00:00Z2021March Tuesday 7 0.00000 57.14286
2021-03-10T00:00:00Z2021March Wednesday 5 0.00000 40.00000
2021-03-11T00:00:00Z2021March Thursday 1 0.00000100.00000
2021-03-12T00:00:00Z2021March Friday 1118.18182 45.45455
2021-03-13T00:00:00Z2021March Saturday 4 0.00000 50.00000
2021-03-14T00:00:00Z2021March Sunday 1 0.00000 0.00000
2021-03-15T00:00:00Z2021March Monday 1 0.00000 0.00000
2021-03-16T00:00:00Z2021March Tuesday 6 0.00000 83.33333
2021-03-17T00:00:00Z2021March Wednesday 7 0.00000 71.42857
2021-03-18T00:00:00Z2021March Thursday 1 0.00000 0.00000
2021-03-19T00:00:00Z2021March Friday 5 0.00000 80.00000
2021-03-20T00:00:00Z2021March Saturday 2 0.00000 0.00000
2021-03-21T00:00:00Z2021March Sunday 633.33333 33.33333
2021-03-22T00:00:00Z2021March Monday 520.00000 60.00000
2021-03-23T00:00:00Z2021March Tuesday 1 0.00000 0.00000
2021-03-24T00:00:00Z2021March Wednesday 4 0.00000 50.00000
2021-03-25T00:00:00Z2021March Thursday 1 0.00000 0.00000
2021-03-26T00:00:00Z2021March Friday 4 NA NA

Testing if I could change the months to become a factor 

factor(months(as.POSIXlt(join$interval_start_timestamp)),levels = month.name)[1:20]
<ol class=list-inline>
  • March
  • March
  • March
  • April
  • April
  • April
  • April
  • April
  • April
  • April
  • April
  • April
  • April
  • April
  • April
  • April
  • April
  • April
  • April
  • April
    • </ol>
    <summary style=display:list-item;cursor:pointer> Levels: </summary> <ol class=list-inline>
  • 'January'
  • 'February'
  • 'March'
  • 'April'
  • 'May'
  • 'June'
  • 'July'
  • 'August'
  • 'September'
  • 'October'
  • 'November'
  • 'December'
    • </ol>

    Extracting date time

    run the following cell to extract year, month, day

    Joins extraction 

    # substring replacement
join[,1] = gsub("\\+.*", 'Z', join[,1])

# individual extraction
year = factor(year(as.POSIXlt(join[,1])))
month = factor(months(as.POSIXlt(join[,1])),levels = month.name)
day = weekdays(as.POSIXlt(join[,1]))

# appending new indivually extracted dates
joins = cbind(join, year, month,day)
joins = joins[,c(1,5,6,7,2,3,4)]
joins

    A data.frame: 729 × 7
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channels
    <chr><fct><fct><fct><int><dbl><dbl>
    2019-03-29T00:00:00Z2019MarchFriday 2 50.00000 50.00000
    2019-03-30T00:00:00Z2019MarchSaturday 6 16.66667 33.33333
    2019-03-31T00:00:00Z2019MarchSunday 8 25.00000 37.50000
    2019-04-01T00:00:00Z2019AprilMonday 9 44.44444 33.33333
    2019-04-02T00:00:00Z2019AprilTuesday 2 50.00000100.00000
    2019-04-03T00:00:00Z2019AprilWednesday0 NA NA
    2019-04-04T00:00:00Z2019AprilThursday 2100.00000100.00000
    2019-04-05T00:00:00Z2019AprilFriday 3 33.33333 0.00000
    2019-04-06T00:00:00Z2019AprilSaturday 2 0.00000 0.00000
    2019-04-07T00:00:00Z2019AprilSunday 2 0.00000 0.00000
    2019-04-08T00:00:00Z2019AprilMonday 9 33.33333 33.33333
    2019-04-09T00:00:00Z2019AprilTuesday 3 33.33333 33.33333
    2019-04-10T00:00:00Z2019AprilWednesday1100.00000100.00000
    2019-04-11T00:00:00Z2019AprilThursday 1 0.00000100.00000
    2019-04-12T00:00:00Z2019AprilFriday 1 0.00000100.00000
    2019-04-13T00:00:00Z2019AprilSaturday 1 0.00000100.00000
    2019-04-14T00:00:00Z2019AprilSunday 0 NA NA
    2019-04-15T00:00:00Z2019AprilMonday 0 NA NA
    2019-04-16T00:00:00Z2019AprilTuesday 3 66.66667 0.00000
    2019-04-17T00:00:00Z2019AprilWednesday5 0.00000 20.00000
    2019-04-18T00:00:00Z2019AprilThursday 3100.00000 33.33333
    2019-04-19T00:00:00Z2019AprilFriday 3 0.00000 33.33333
    2019-04-20T00:00:00Z2019AprilSaturday 0 NA NA
    2019-04-21T00:00:00Z2019AprilSunday 1100.00000100.00000
    2019-04-22T00:00:00Z2019AprilMonday 0 NA NA
    2019-04-23T00:00:00Z2019AprilTuesday 1 0.00000 0.00000
    2019-04-24T00:00:00Z2019AprilWednesday3 33.33333 0.00000
    2019-04-25T00:00:00Z2019AprilThursday 3 66.66667 66.66667
    2019-04-26T00:00:00Z2019AprilFriday 3 33.33333 33.33333
    2019-04-27T00:00:00Z2019AprilSaturday 1100.00000 0.00000
    ⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 1 0.00000100.00000
    2021-02-26T00:00:00Z2021FebruaryFriday 540.00000100.00000
    2021-02-27T00:00:00Z2021FebruarySaturday 812.50000100.00000
    2021-02-28T00:00:00Z2021FebruarySunday 520.00000100.00000
    2021-03-01T00:00:00Z2021March Monday 2 0.00000 50.00000
    2021-03-02T00:00:00Z2021March Tuesday 616.66667 16.66667
    2021-03-03T00:00:00Z2021March Wednesday 5 0.00000 40.00000
    2021-03-04T00:00:00Z2021March Thursday 8 0.00000 62.50000
    2021-03-05T00:00:00Z2021March Friday 333.33333 33.33333
    2021-03-06T00:00:00Z2021March Saturday 3 0.00000 66.66667
    2021-03-07T00:00:00Z2021March Sunday 3 0.00000 33.33333
    2021-03-08T00:00:00Z2021March Monday 714.28571 42.85714
    2021-03-09T00:00:00Z2021March Tuesday 7 0.00000 57.14286
    2021-03-10T00:00:00Z2021March Wednesday 5 0.00000 40.00000
    2021-03-11T00:00:00Z2021March Thursday 1 0.00000100.00000
    2021-03-12T00:00:00Z2021March Friday 1118.18182 45.45455
    2021-03-13T00:00:00Z2021March Saturday 4 0.00000 50.00000
    2021-03-14T00:00:00Z2021March Sunday 1 0.00000 0.00000
    2021-03-15T00:00:00Z2021March Monday 1 0.00000 0.00000
    2021-03-16T00:00:00Z2021March Tuesday 6 0.00000 83.33333
    2021-03-17T00:00:00Z2021March Wednesday 7 0.00000 71.42857
    2021-03-18T00:00:00Z2021March Thursday 1 0.00000 0.00000
    2021-03-19T00:00:00Z2021March Friday 5 0.00000 80.00000
    2021-03-20T00:00:00Z2021March Saturday 2 0.00000 0.00000
    2021-03-21T00:00:00Z2021March Sunday 633.33333 33.33333
    2021-03-22T00:00:00Z2021March Monday 520.00000 60.00000
    2021-03-23T00:00:00Z2021March Tuesday 1 0.00000 0.00000
    2021-03-24T00:00:00Z2021March Wednesday 4 0.00000 50.00000
    2021-03-25T00:00:00Z2021March Thursday 1 0.00000 0.00000
    2021-03-26T00:00:00Z2021March Friday 4 NA NA

    Sources extraction 

    # substring replacement
source[,1] = gsub("\\+.*", 'Z', source[,1])

# individual extraction
year = factor(year(as.POSIXlt(source[,1])))
month = factor(months(as.POSIXlt(source[,1])),levels = month.name)
day = weekdays(as.POSIXlt(source[,1]))

# appending new indivually extracted dates
sources = cbind(source, year, month,day)
sources = sources[,c(1,5,6,7,2,3,4)]
sources

    A data.frame: 729 × 7
    interval_start_timestampyearmonthdaydiscovery_joinsinvitesvanity_joins
    <chr><fct><fct><fct><int><int><int>
    2019-03-29T00:00:00Z2019MarchFriday 00 3
    2019-03-30T00:00:00Z2019MarchSaturday 00 7
    2019-03-31T00:00:00Z2019MarchSunday 00 8
    2019-04-01T00:00:00Z2019AprilMonday 0011
    2019-04-02T00:00:00Z2019AprilTuesday 00 2
    2019-04-03T00:00:00Z2019AprilWednesday00 1
    2019-04-04T00:00:00Z2019AprilThursday 00 3
    2019-04-05T00:00:00Z2019AprilFriday 00 4
    2019-04-06T00:00:00Z2019AprilSaturday 00 3
    2019-04-07T00:00:00Z2019AprilSunday 00 2
    2019-04-08T00:00:00Z2019AprilMonday 00 9
    2019-04-09T00:00:00Z2019AprilTuesday 00 3
    2019-04-10T00:00:00Z2019AprilWednesday00 1
    2019-04-11T00:00:00Z2019AprilThursday 00 2
    2019-04-12T00:00:00Z2019AprilFriday 00 1
    2019-04-13T00:00:00Z2019AprilSaturday 00 1
    2019-04-14T00:00:00Z2019AprilSunday 00 0
    2019-04-15T00:00:00Z2019AprilMonday 00 0
    2019-04-16T00:00:00Z2019AprilTuesday 00 7
    2019-04-17T00:00:00Z2019AprilWednesday00 5
    2019-04-18T00:00:00Z2019AprilThursday 00 6
    2019-04-19T00:00:00Z2019AprilFriday 00 3
    2019-04-20T00:00:00Z2019AprilSaturday 00 2
    2019-04-21T00:00:00Z2019AprilSunday 00 1
    2019-04-22T00:00:00Z2019AprilMonday 00 1
    2019-04-23T00:00:00Z2019AprilTuesday 00 3
    2019-04-24T00:00:00Z2019AprilWednesday00 3
    2019-04-25T00:00:00Z2019AprilThursday 00 3
    2019-04-26T00:00:00Z2019AprilFriday 00 4
    2019-04-27T00:00:00Z2019AprilSaturday 00 3
    ⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 00 1
    2021-02-26T00:00:00Z2021FebruaryFriday 00 6
    2021-02-27T00:00:00Z2021FebruarySaturday 00 9
    2021-02-28T00:00:00Z2021FebruarySunday 00 5
    2021-03-01T00:00:00Z2021March Monday 00 3
    2021-03-02T00:00:00Z2021March Tuesday 00 6
    2021-03-03T00:00:00Z2021March Wednesday00 5
    2021-03-04T00:00:00Z2021March Thursday 00 8
    2021-03-05T00:00:00Z2021March Friday 00 4
    2021-03-06T00:00:00Z2021March Saturday 00 3
    2021-03-07T00:00:00Z2021March Sunday 00 4
    2021-03-08T00:00:00Z2021March Monday 00 7
    2021-03-09T00:00:00Z2021March Tuesday 10 6
    2021-03-10T00:00:00Z2021March Wednesday00 5
    2021-03-11T00:00:00Z2021March Thursday 00 2
    2021-03-12T00:00:00Z2021March Friday 0011
    2021-03-13T00:00:00Z2021March Saturday 10 3
    2021-03-14T00:00:00Z2021March Sunday 00 1
    2021-03-15T00:00:00Z2021March Monday 00 2
    2021-03-16T00:00:00Z2021March Tuesday 10 6
    2021-03-17T00:00:00Z2021March Wednesday10 9
    2021-03-18T00:00:00Z2021March Thursday 00 1
    2021-03-19T00:00:00Z2021March Friday 10 4
    2021-03-20T00:00:00Z2021March Saturday 00 2
    2021-03-21T00:00:00Z2021March Sunday 00 7
    2021-03-22T00:00:00Z2021March Monday 00 6
    2021-03-23T00:00:00Z2021March Tuesday 00 1
    2021-03-24T00:00:00Z2021March Wednesday00 5
    2021-03-25T00:00:00Z2021March Thursday 00 2
    2021-03-26T00:00:00Z2021March Friday 00 4

    Leaves extraction 

    # substring replacement
leave[,1] = gsub("\\+.*", 'Z', leave[,1])

# individual extraction
year = factor(year(as.POSIXlt(leave[,1])))
month = factor(months(as.POSIXlt(leave[,1])),levels = month.name)
day = weekdays(as.POSIXlt(leave[,1]))

# appending new indivually extracted dates
leave
leaves = cbind(leave, year, month,day)
leaves
leaves = leaves[,c(1,4,5,6,2,3)]
leaves

    A data.frame: 1104 × 3
    interval_start_timestampdays_in_guildleavers
    <chr><fct><int>
    2019-03-29T00:00:00Z'Members for 1 month+' 1
    2019-03-30T00:00:00Z'Members for 1 month+' 1
    2019-03-30T00:00:00Z'Members for < 1 month'1
    2019-03-31T00:00:00Z'Members for 1 month+' 2
    2019-03-31T00:00:00Z'Members for < 1 month'1
    2019-04-01T00:00:00Z'Members for 1 month+' 4
    2019-04-02T00:00:00Z'Members for 1 month+' 1
    2019-04-03T00:00:00Z'Members for 1 month+' 2
    2019-04-03T00:00:00Z'Members for < 1 month'2
    2019-04-04T00:00:00Z'Members for 1 month+' 2
    2019-04-04T00:00:00Z'Members for < 1 month'2
    2019-04-05T00:00:00Z'Members for 1 month+' 3
    2019-04-06T00:00:00Z'Members for 1 month+' 1
    2019-04-06T00:00:00Z'Members for < 1 month'1
    2019-04-07T00:00:00Z'Members for 1 month+' 1
    2019-04-07T00:00:00Z'Members for < 1 month'2
    2019-04-08T00:00:00Z'Members for 1 month+' 1
    2019-04-08T00:00:00Z'Members for < 1 month'1
    2019-04-09T00:00:00Z'Members for 1 month+' 1
    2019-04-09T00:00:00Z'Members for < 1 month'1
    2019-04-10T00:00:00Z'Members for 1 month+' 2
    2019-04-10T00:00:00Z'Members for < 1 month'1
    2019-04-11T00:00:00Z'Members for 1 month+' 0
    2019-04-12T00:00:00Z'Members for 1 month+' 1
    2019-04-13T00:00:00Z'Members for < 1 month'1
    2019-04-14T00:00:00Z'Members for 1 month+' 2
    2019-04-15T00:00:00Z'Members for 1 month+' 1
    2019-04-15T00:00:00Z'Members for < 1 month'1
    2019-04-16T00:00:00Z'Members for 1 month+' 3
    2019-04-16T00:00:00Z'Members for < 1 month'1
    ⋮⋮⋮
    2021-03-09T00:00:00Z'Members for 1 month+' 2
    2021-03-09T00:00:00Z'Members for < 1 month'1
    2021-03-10T00:00:00Z'Members for 1 month+' 2
    2021-03-10T00:00:00Z'Members for < 1 month'3
    2021-03-11T00:00:00Z'Members for 1 month+' 2
    2021-03-12T00:00:00Z'Members for 1 month+' 1
    2021-03-12T00:00:00Z'Members for < 1 month'5
    2021-03-13T00:00:00Z'Members for < 1 month'1
    2021-03-14T00:00:00Z'Members for 1 month+' 1
    2021-03-14T00:00:00Z'Members for < 1 month'1
    2021-03-15T00:00:00Z'Members for 1 month+' 2
    2021-03-16T00:00:00Z'Members for 1 month+' 1
    2021-03-16T00:00:00Z'Members for < 1 month'3
    2021-03-17T00:00:00Z'Members for 1 month+' 4
    2021-03-17T00:00:00Z'Members for < 1 month'2
    2021-03-18T00:00:00Z'Members for < 1 month'1
    2021-03-19T00:00:00Z'Members for 1 month+' 2
    2021-03-19T00:00:00Z'Members for < 1 month'2
    2021-03-20T00:00:00Z'Members for 1 month+' 5
    2021-03-20T00:00:00Z'Members for < 1 month'1
    2021-03-21T00:00:00Z'Members for 1 month+' 1
    2021-03-21T00:00:00Z'Members for < 1 month'3
    2021-03-22T00:00:00Z'Members for 1 month+' 1
    2021-03-23T00:00:00Z'Members for 1 month+' 3
    2021-03-23T00:00:00Z'Members for < 1 month'1
    2021-03-24T00:00:00Z'Members for 1 month+' 0
    2021-03-25T00:00:00Z'Members for 1 month+' 2
    2021-03-25T00:00:00Z'Members for < 1 month'1
    2021-03-26T00:00:00Z'Members for 1 month+' 3
    2021-03-26T00:00:00Z'Members for < 1 month'1
    A data.frame: 1104 × 6
    interval_start_timestampdays_in_guildleaversyearmonthday
    <chr><fct><int><fct><fct><fct>
    2019-03-29T00:00:00Z'Members for 1 month+' 12019MarchFriday
    2019-03-30T00:00:00Z'Members for 1 month+' 12019MarchSaturday
    2019-03-30T00:00:00Z'Members for < 1 month'12019MarchSaturday
    2019-03-31T00:00:00Z'Members for 1 month+' 22019MarchSunday
    2019-03-31T00:00:00Z'Members for < 1 month'12019March<span style=white-space:pre-wrap>Sunday </span>
    2019-04-01T00:00:00Z'Members for 1 month+' 42019AprilMonday
    2019-04-02T00:00:00Z'Members for 1 month+' 12019AprilTuesday
    2019-04-03T00:00:00Z'Members for 1 month+' 22019AprilWednesday
    2019-04-03T00:00:00Z'Members for < 1 month'22019AprilWednesday
    2019-04-04T00:00:00Z'Members for 1 month+' 22019AprilThursday
    2019-04-04T00:00:00Z'Members for < 1 month'22019AprilThursday
    2019-04-05T00:00:00Z'Members for 1 month+' 32019AprilFriday
    2019-04-06T00:00:00Z'Members for 1 month+' 12019AprilSaturday
    2019-04-06T00:00:00Z'Members for < 1 month'12019AprilSaturday
    2019-04-07T00:00:00Z'Members for 1 month+' 12019AprilSunday
    2019-04-07T00:00:00Z'Members for < 1 month'22019April<span style=white-space:pre-wrap>Sunday </span>
    2019-04-08T00:00:00Z'Members for 1 month+' 12019AprilMonday
    2019-04-08T00:00:00Z'Members for < 1 month'12019April<span style=white-space:pre-wrap>Monday </span>
    2019-04-09T00:00:00Z'Members for 1 month+' 12019AprilTuesday
    2019-04-09T00:00:00Z'Members for < 1 month'12019April<span style=white-space:pre-wrap>Tuesday </span>
    2019-04-10T00:00:00Z'Members for 1 month+' 22019AprilWednesday
    2019-04-10T00:00:00Z'Members for < 1 month'12019AprilWednesday
    2019-04-11T00:00:00Z'Members for 1 month+' 02019AprilThursday
    2019-04-12T00:00:00Z'Members for 1 month+' 12019AprilFriday
    2019-04-13T00:00:00Z'Members for < 1 month'12019AprilSaturday
    2019-04-14T00:00:00Z'Members for 1 month+' 22019AprilSunday
    2019-04-15T00:00:00Z'Members for 1 month+' 12019AprilMonday
    2019-04-15T00:00:00Z'Members for < 1 month'12019April<span style=white-space:pre-wrap>Monday </span>
    2019-04-16T00:00:00Z'Members for 1 month+' 32019AprilTuesday
    2019-04-16T00:00:00Z'Members for < 1 month'12019April<span style=white-space:pre-wrap>Tuesday </span>
    ⋮⋮⋮⋮⋮⋮
    2021-03-09T00:00:00Z'Members for 1 month+' 22021MarchTuesday
    2021-03-09T00:00:00Z'Members for < 1 month'12021March<span style=white-space:pre-wrap>Tuesday </span>
    2021-03-10T00:00:00Z'Members for 1 month+' 22021MarchWednesday
    2021-03-10T00:00:00Z'Members for < 1 month'32021MarchWednesday
    2021-03-11T00:00:00Z'Members for 1 month+' 22021MarchThursday
    2021-03-12T00:00:00Z'Members for 1 month+' 12021MarchFriday
    2021-03-12T00:00:00Z'Members for < 1 month'52021March<span style=white-space:pre-wrap>Friday </span>
    2021-03-13T00:00:00Z'Members for < 1 month'12021MarchSaturday
    2021-03-14T00:00:00Z'Members for 1 month+' 12021MarchSunday
    2021-03-14T00:00:00Z'Members for < 1 month'12021March<span style=white-space:pre-wrap>Sunday </span>
    2021-03-15T00:00:00Z'Members for 1 month+' 22021MarchMonday
    2021-03-16T00:00:00Z'Members for 1 month+' 12021MarchTuesday
    2021-03-16T00:00:00Z'Members for < 1 month'32021March<span style=white-space:pre-wrap>Tuesday </span>
    2021-03-17T00:00:00Z'Members for 1 month+' 42021MarchWednesday
    2021-03-17T00:00:00Z'Members for < 1 month'22021MarchWednesday
    2021-03-18T00:00:00Z'Members for < 1 month'12021MarchThursday
    2021-03-19T00:00:00Z'Members for 1 month+' 22021MarchFriday
    2021-03-19T00:00:00Z'Members for < 1 month'22021March<span style=white-space:pre-wrap>Friday </span>
    2021-03-20T00:00:00Z'Members for 1 month+' 52021MarchSaturday
    2021-03-20T00:00:00Z'Members for < 1 month'12021MarchSaturday
    2021-03-21T00:00:00Z'Members for 1 month+' 12021MarchSunday
    2021-03-21T00:00:00Z'Members for < 1 month'32021March<span style=white-space:pre-wrap>Sunday </span>
    2021-03-22T00:00:00Z'Members for 1 month+' 12021MarchMonday
    2021-03-23T00:00:00Z'Members for 1 month+' 32021MarchTuesday
    2021-03-23T00:00:00Z'Members for < 1 month'12021March<span style=white-space:pre-wrap>Tuesday </span>
    2021-03-24T00:00:00Z'Members for 1 month+' 02021MarchWednesday
    2021-03-25T00:00:00Z'Members for 1 month+' 22021MarchThursday
    2021-03-25T00:00:00Z'Members for < 1 month'12021MarchThursday
    2021-03-26T00:00:00Z'Members for 1 month+' 32021MarchFriday
    2021-03-26T00:00:00Z'Members for < 1 month'12021March<span style=white-space:pre-wrap>Friday </span>
    A data.frame: 1104 × 6
    interval_start_timestampyearmonthdaydays_in_guildleavers
    <chr><fct><fct><fct><fct><int>
    2019-03-29T00:00:00Z2019MarchFriday 'Members for 1 month+' 1
    2019-03-30T00:00:00Z2019MarchSaturday 'Members for 1 month+' 1
    2019-03-30T00:00:00Z2019MarchSaturday 'Members for < 1 month'1
    2019-03-31T00:00:00Z2019MarchSunday 'Members for 1 month+' 2
    2019-03-31T00:00:00Z2019March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1
    2019-04-01T00:00:00Z2019AprilMonday 'Members for 1 month+' 4
    2019-04-02T00:00:00Z2019AprilTuesday 'Members for 1 month+' 1
    2019-04-03T00:00:00Z2019AprilWednesday'Members for 1 month+' 2
    2019-04-03T00:00:00Z2019AprilWednesday'Members for < 1 month'2
    2019-04-04T00:00:00Z2019AprilThursday 'Members for 1 month+' 2
    2019-04-04T00:00:00Z2019AprilThursday 'Members for < 1 month'2
    2019-04-05T00:00:00Z2019AprilFriday 'Members for 1 month+' 3
    2019-04-06T00:00:00Z2019AprilSaturday 'Members for 1 month+' 1
    2019-04-06T00:00:00Z2019AprilSaturday 'Members for < 1 month'1
    2019-04-07T00:00:00Z2019AprilSunday 'Members for 1 month+' 1
    2019-04-07T00:00:00Z2019April<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'2
    2019-04-08T00:00:00Z2019AprilMonday 'Members for 1 month+' 1
    2019-04-08T00:00:00Z2019April<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1
    2019-04-09T00:00:00Z2019AprilTuesday 'Members for 1 month+' 1
    2019-04-09T00:00:00Z2019April<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1
    2019-04-10T00:00:00Z2019AprilWednesday'Members for 1 month+' 2
    2019-04-10T00:00:00Z2019AprilWednesday'Members for < 1 month'1
    2019-04-11T00:00:00Z2019AprilThursday 'Members for 1 month+' 0
    2019-04-12T00:00:00Z2019AprilFriday 'Members for 1 month+' 1
    2019-04-13T00:00:00Z2019AprilSaturday 'Members for < 1 month'1
    2019-04-14T00:00:00Z2019AprilSunday 'Members for 1 month+' 2
    2019-04-15T00:00:00Z2019AprilMonday 'Members for 1 month+' 1
    2019-04-15T00:00:00Z2019April<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1
    2019-04-16T00:00:00Z2019AprilTuesday 'Members for 1 month+' 3
    2019-04-16T00:00:00Z2019April<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1
    ⋮⋮⋮⋮⋮⋮
    2021-03-09T00:00:00Z2021MarchTuesday 'Members for 1 month+' 2
    2021-03-09T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1
    2021-03-10T00:00:00Z2021MarchWednesday'Members for 1 month+' 2
    2021-03-10T00:00:00Z2021MarchWednesday'Members for < 1 month'3
    2021-03-11T00:00:00Z2021MarchThursday 'Members for 1 month+' 2
    2021-03-12T00:00:00Z2021MarchFriday 'Members for 1 month+' 1
    2021-03-12T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'5
    2021-03-13T00:00:00Z2021MarchSaturday 'Members for < 1 month'1
    2021-03-14T00:00:00Z2021MarchSunday 'Members for 1 month+' 1
    2021-03-14T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1
    2021-03-15T00:00:00Z2021MarchMonday 'Members for 1 month+' 2
    2021-03-16T00:00:00Z2021MarchTuesday 'Members for 1 month+' 1
    2021-03-16T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'3
    2021-03-17T00:00:00Z2021MarchWednesday'Members for 1 month+' 4
    2021-03-17T00:00:00Z2021MarchWednesday'Members for < 1 month'2
    2021-03-18T00:00:00Z2021MarchThursday 'Members for < 1 month'1
    2021-03-19T00:00:00Z2021MarchFriday 'Members for 1 month+' 2
    2021-03-19T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'2
    2021-03-20T00:00:00Z2021MarchSaturday 'Members for 1 month+' 5
    2021-03-20T00:00:00Z2021MarchSaturday 'Members for < 1 month'1
    2021-03-21T00:00:00Z2021MarchSunday 'Members for 1 month+' 1
    2021-03-21T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'3
    2021-03-22T00:00:00Z2021MarchMonday 'Members for 1 month+' 1
    2021-03-23T00:00:00Z2021MarchTuesday 'Members for 1 month+' 3
    2021-03-23T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1
    2021-03-24T00:00:00Z2021MarchWednesday'Members for 1 month+' 0
    2021-03-25T00:00:00Z2021MarchThursday 'Members for 1 month+' 2
    2021-03-25T00:00:00Z2021MarchThursday 'Members for < 1 month'1
    2021-03-26T00:00:00Z2021MarchFriday 'Members for 1 month+' 3
    2021-03-26T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1

    Messages extraction 

    # substring replacement
message[,1] = gsub("\\+.*", 'Z', message[,1])

# individual extraction
year = factor(year(as.POSIXlt(message[,1])))
month = factor(months(as.POSIXlt(message[,1])),levels = month.name)
day = weekdays(as.POSIXlt(message[,1]))

# appending new indivually extracted dates
messages = cbind(message, year, month,day)
messages
messages = messages[,c(1,4,5,6,2,3)]
messages

    A data.frame: 729 × 6
    interval_start_timestampmessagesmessages_per_communicatoryearmonthday
    <chr><int><dbl><fct><fct><fct>
    2019-03-29T00:00:00Z 334 6.3018872019MarchFriday
    2019-03-30T00:00:00Z 236 6.2105262019MarchSaturday
    2019-03-31T00:00:00Z 364 8.0888892019MarchSunday
    2019-04-01T00:00:00Z 404 5.3866672019AprilMonday
    2019-04-02T00:00:00Z 54311.3125002019AprilTuesday
    2019-04-03T00:00:00Z 324 7.2000002019AprilWednesday
    2019-04-04T00:00:00Z 55610.9019612019AprilThursday
    2019-04-05T00:00:00Z 273 5.8085112019AprilFriday
    2019-04-06T00:00:00Z 335 7.6136362019AprilSaturday
    2019-04-07T00:00:00Z110222.0400002019AprilSunday
    2019-04-08T00:00:00Z 188 4.4761902019AprilMonday
    2019-04-09T00:00:00Z 399 8.6739132019AprilTuesday
    2019-04-10T00:00:00Z 53110.6200002019AprilWednesday
    2019-04-11T00:00:00Z 68913.0000002019AprilThursday
    2019-04-12T00:00:00Z 418 9.0869572019AprilFriday
    2019-04-13T00:00:00Z 56613.1627912019AprilSaturday
    2019-04-14T00:00:00Z 48112.0250002019AprilSunday
    2019-04-15T00:00:00Z 65913.1800002019AprilMonday
    2019-04-16T00:00:00Z 77912.7704922019AprilTuesday
    2019-04-17T00:00:00Z 59611.2452832019AprilWednesday
    2019-04-18T00:00:00Z114315.6575342019AprilThursday
    2019-04-19T00:00:00Z 89816.3272732019AprilFriday
    2019-04-20T00:00:00Z 331 6.4901962019AprilSaturday
    2019-04-21T00:00:00Z 47311.0000002019AprilSunday
    2019-04-22T00:00:00Z 283 7.2564102019AprilMonday
    2019-04-23T00:00:00Z127021.8965522019AprilTuesday
    2019-04-24T00:00:00Z 74614.3461542019AprilWednesday
    2019-04-25T00:00:00Z 287 5.5192312019AprilThursday
    2019-04-26T00:00:00Z 72811.5555562019AprilFriday
    2019-04-27T00:00:00Z 69112.3392862019AprilSaturday
    ⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z1383.4500002021FebruaryThursday
    2021-02-26T00:00:00Z 782.4375002021FebruaryFriday
    2021-02-27T00:00:00Z 932.1627912021FebruarySaturday
    2021-02-28T00:00:00Z 461.5333332021FebruarySunday
    2021-03-01T00:00:00Z 531.7666672021March Monday
    2021-03-02T00:00:00Z 722.4000002021March Tuesday
    2021-03-03T00:00:00Z1224.0666672021March Wednesday
    2021-03-04T00:00:00Z1684.9411762021March Thursday
    2021-03-05T00:00:00Z 742.3870972021March Friday
    2021-03-06T00:00:00Z 431.4827592021March Saturday
    2021-03-07T00:00:00Z 431.7200002021March Sunday
    2021-03-08T00:00:00Z1063.3125002021March Monday
    2021-03-09T00:00:00Z1143.0810812021March Tuesday
    2021-03-10T00:00:00Z 832.5937502021March Wednesday
    2021-03-11T00:00:00Z1092.7250002021March Thursday
    2021-03-12T00:00:00Z 752.0270272021March Friday
    2021-03-13T00:00:00Z1584.6470592021March Saturday
    2021-03-14T00:00:00Z 732.4333332021March Sunday
    2021-03-15T00:00:00Z 732.5172412021March Monday
    2021-03-16T00:00:00Z 521.5757582021March Tuesday
    2021-03-17T00:00:00Z 642.0645162021March Wednesday
    2021-03-18T00:00:00Z 652.0967742021March Thursday
    2021-03-19T00:00:00Z1823.5000002021March Friday
    2021-03-20T00:00:00Z1212.8809522021March Saturday
    2021-03-21T00:00:00Z1573.9250002021March Sunday
    2021-03-22T00:00:00Z 942.4102562021March Monday
    2021-03-23T00:00:00Z 341.4166672021March Tuesday
    2021-03-24T00:00:00Z 511.8888892021March Wednesday
    2021-03-25T00:00:00Z1202.8571432021March Thursday
    2021-03-26T00:00:00Z1223.4857142021March Friday
    A data.frame: 729 × 6
    interval_start_timestampyearmonthdaymessagesmessages_per_communicator
    <chr><fct><fct><fct><int><dbl>
    2019-03-29T00:00:00Z2019MarchFriday 334 6.301887
    2019-03-30T00:00:00Z2019MarchSaturday 236 6.210526
    2019-03-31T00:00:00Z2019MarchSunday 364 8.088889
    2019-04-01T00:00:00Z2019AprilMonday 404 5.386667
    2019-04-02T00:00:00Z2019AprilTuesday 54311.312500
    2019-04-03T00:00:00Z2019AprilWednesday 324 7.200000
    2019-04-04T00:00:00Z2019AprilThursday 55610.901961
    2019-04-05T00:00:00Z2019AprilFriday 273 5.808511
    2019-04-06T00:00:00Z2019AprilSaturday 335 7.613636
    2019-04-07T00:00:00Z2019AprilSunday 110222.040000
    2019-04-08T00:00:00Z2019AprilMonday 188 4.476190
    2019-04-09T00:00:00Z2019AprilTuesday 399 8.673913
    2019-04-10T00:00:00Z2019AprilWednesday 53110.620000
    2019-04-11T00:00:00Z2019AprilThursday 68913.000000
    2019-04-12T00:00:00Z2019AprilFriday 418 9.086957
    2019-04-13T00:00:00Z2019AprilSaturday 56613.162791
    2019-04-14T00:00:00Z2019AprilSunday 48112.025000
    2019-04-15T00:00:00Z2019AprilMonday 65913.180000
    2019-04-16T00:00:00Z2019AprilTuesday 77912.770492
    2019-04-17T00:00:00Z2019AprilWednesday 59611.245283
    2019-04-18T00:00:00Z2019AprilThursday 114315.657534
    2019-04-19T00:00:00Z2019AprilFriday 89816.327273
    2019-04-20T00:00:00Z2019AprilSaturday 331 6.490196
    2019-04-21T00:00:00Z2019AprilSunday 47311.000000
    2019-04-22T00:00:00Z2019AprilMonday 283 7.256410
    2019-04-23T00:00:00Z2019AprilTuesday 127021.896552
    2019-04-24T00:00:00Z2019AprilWednesday 74614.346154
    2019-04-25T00:00:00Z2019AprilThursday 287 5.519231
    2019-04-26T00:00:00Z2019AprilFriday 72811.555556
    2019-04-27T00:00:00Z2019AprilSaturday 69112.339286
    ⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 1383.450000
    2021-02-26T00:00:00Z2021FebruaryFriday 782.437500
    2021-02-27T00:00:00Z2021FebruarySaturday 932.162791
    2021-02-28T00:00:00Z2021FebruarySunday 461.533333
    2021-03-01T00:00:00Z2021March Monday 531.766667
    2021-03-02T00:00:00Z2021March Tuesday 722.400000
    2021-03-03T00:00:00Z2021March Wednesday1224.066667
    2021-03-04T00:00:00Z2021March Thursday 1684.941176
    2021-03-05T00:00:00Z2021March Friday 742.387097
    2021-03-06T00:00:00Z2021March Saturday 431.482759
    2021-03-07T00:00:00Z2021March Sunday 431.720000
    2021-03-08T00:00:00Z2021March Monday 1063.312500
    2021-03-09T00:00:00Z2021March Tuesday 1143.081081
    2021-03-10T00:00:00Z2021March Wednesday 832.593750
    2021-03-11T00:00:00Z2021March Thursday 1092.725000
    2021-03-12T00:00:00Z2021March Friday 752.027027
    2021-03-13T00:00:00Z2021March Saturday 1584.647059
    2021-03-14T00:00:00Z2021March Sunday 732.433333
    2021-03-15T00:00:00Z2021March Monday 732.517241
    2021-03-16T00:00:00Z2021March Tuesday 521.575758
    2021-03-17T00:00:00Z2021March Wednesday 642.064516
    2021-03-18T00:00:00Z2021March Thursday 652.096774
    2021-03-19T00:00:00Z2021March Friday 1823.500000
    2021-03-20T00:00:00Z2021March Saturday 1212.880952
    2021-03-21T00:00:00Z2021March Sunday 1573.925000
    2021-03-22T00:00:00Z2021March Monday 942.410256
    2021-03-23T00:00:00Z2021March Tuesday 341.416667
    2021-03-24T00:00:00Z2021March Wednesday 511.888889
    2021-03-25T00:00:00Z2021March Thursday 1202.857143
    2021-03-26T00:00:00Z2021March Friday 1223.485714

    Voices extraction 

    # substring replacement
voice[,1] = gsub("\\+.*", 'Z', voice[,1])

# individual extraction
year = factor(year(as.POSIXlt(voice[,1])))
month = factor(months(as.POSIXlt(voice[,1])),levels = month.name)
day = weekdays(as.POSIXlt(voice[,1]))

# appending new indivually extracted dates
voices = cbind(voice, year, month,day)
voices = voices[,c(1,3,4,5,2)]
voices

    A data.frame: 729 × 5
    interval_start_timestampyearmonthdayspeaking_minutes
    <chr><fct><fct><fct><int>
    2019-03-29T00:00:00Z2019MarchFriday 0
    2019-03-30T00:00:00Z2019MarchSaturday 0
    2019-03-31T00:00:00Z2019MarchSunday 0
    2019-04-01T00:00:00Z2019AprilMonday 0
    2019-04-02T00:00:00Z2019AprilTuesday 0
    2019-04-03T00:00:00Z2019AprilWednesday0
    2019-04-04T00:00:00Z2019AprilThursday 0
    2019-04-05T00:00:00Z2019AprilFriday 0
    2019-04-06T00:00:00Z2019AprilSaturday 0
    2019-04-07T00:00:00Z2019AprilSunday 0
    2019-04-08T00:00:00Z2019AprilMonday 0
    2019-04-09T00:00:00Z2019AprilTuesday 0
    2019-04-10T00:00:00Z2019AprilWednesday0
    2019-04-11T00:00:00Z2019AprilThursday 0
    2019-04-12T00:00:00Z2019AprilFriday 0
    2019-04-13T00:00:00Z2019AprilSaturday 0
    2019-04-14T00:00:00Z2019AprilSunday 0
    2019-04-15T00:00:00Z2019AprilMonday 0
    2019-04-16T00:00:00Z2019AprilTuesday 0
    2019-04-17T00:00:00Z2019AprilWednesday0
    2019-04-18T00:00:00Z2019AprilThursday 0
    2019-04-19T00:00:00Z2019AprilFriday 0
    2019-04-20T00:00:00Z2019AprilSaturday 0
    2019-04-21T00:00:00Z2019AprilSunday 0
    2019-04-22T00:00:00Z2019AprilMonday 0
    2019-04-23T00:00:00Z2019AprilTuesday 0
    2019-04-24T00:00:00Z2019AprilWednesday0
    2019-04-25T00:00:00Z2019AprilThursday 0
    2019-04-26T00:00:00Z2019AprilFriday 0
    2019-04-27T00:00:00Z2019AprilSaturday 0
    ⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 1495
    2021-02-26T00:00:00Z2021FebruaryFriday 913
    2021-02-27T00:00:00Z2021FebruarySaturday 1118
    2021-02-28T00:00:00Z2021FebruarySunday 1354
    2021-03-01T00:00:00Z2021March Monday 1269
    2021-03-02T00:00:00Z2021March Tuesday 1200
    2021-03-03T00:00:00Z2021March Wednesday2031
    2021-03-04T00:00:00Z2021March Thursday 2293
    2021-03-05T00:00:00Z2021March Friday 1124
    2021-03-06T00:00:00Z2021March Saturday 1398
    2021-03-07T00:00:00Z2021March Sunday 1460
    2021-03-08T00:00:00Z2021March Monday 1834
    2021-03-09T00:00:00Z2021March Tuesday 1523
    2021-03-10T00:00:00Z2021March Wednesday1119
    2021-03-11T00:00:00Z2021March Thursday 1878
    2021-03-12T00:00:00Z2021March Friday 1429
    2021-03-13T00:00:00Z2021March Saturday 730
    2021-03-14T00:00:00Z2021March Sunday 567
    2021-03-15T00:00:00Z2021March Monday 1282
    2021-03-16T00:00:00Z2021March Tuesday 1234
    2021-03-17T00:00:00Z2021March Wednesday1146
    2021-03-18T00:00:00Z2021March Thursday 2464
    2021-03-19T00:00:00Z2021March Friday 840
    2021-03-20T00:00:00Z2021March Saturday 428
    2021-03-21T00:00:00Z2021March Sunday 880
    2021-03-22T00:00:00Z2021March Monday 1598
    2021-03-23T00:00:00Z2021March Tuesday 873
    2021-03-24T00:00:00Z2021March Wednesday 771
    2021-03-25T00:00:00Z2021March Thursday 1742
    2021-03-26T00:00:00Z2021March Friday 1038

    Communicators extraction 

    # substring replacement
communicator[,1] = gsub("\\+.*", 'Z', communicator[,1])

# individual extraction
year = factor(year(as.POSIXlt(communicator[,1])))
month = factor(months(as.POSIXlt(communicator[,1])),levels = month.name)
day = weekdays(as.POSIXlt(communicator[,1]))
communicator

# appending new individually extracted dates
communicators = cbind(communicator, year, month,day)
communicators = communicators[,c(1,4,5,6,2,3)]
communicators$total_communicated = communicators$visitors * communicators$pct_communicated/100

    A data.frame: 729 × 3
    interval_start_timestampvisitorspct_communicated
    <chr><int><dbl>
    2019-03-29T00:00:00Z20625.72816
    2019-03-30T00:00:00Z18420.65217
    2019-03-31T00:00:00Z18524.32432
    2019-04-01T00:00:00Z32822.86585
    2019-04-02T00:00:00Z14333.56643
    2019-04-03T00:00:00Z27116.60517
    2019-04-04T00:00:00Z38113.38583
    2019-04-05T00:00:00Z19024.73684
    2019-04-06T00:00:00Z16326.99387
    2019-04-07T00:00:00Z15931.44654
    2019-04-08T00:00:00Z16325.76687
    2019-04-09T00:00:00Z14831.08108
    2019-04-10T00:00:00Z16330.67485
    2019-04-11T00:00:00Z13938.12950
    2019-04-12T00:00:00Z15529.67742
    2019-04-13T00:00:00Z14330.06993
    2019-04-14T00:00:00Z14028.57143
    2019-04-15T00:00:00Z17029.41176
    2019-04-16T00:00:00Z15040.66667
    2019-04-17T00:00:00Z15334.64052
    2019-04-18T00:00:00Z16743.71257
    2019-04-19T00:00:00Z16233.95062
    2019-04-20T00:00:00Z33715.13353
    2019-04-21T00:00:00Z17225.00000
    2019-04-22T00:00:00Z16224.07407
    2019-04-23T00:00:00Z16335.58282
    2019-04-24T00:00:00Z34015.29412
    2019-04-25T00:00:00Z19626.53061
    2019-04-26T00:00:00Z37116.98113
    2019-04-27T00:00:00Z20127.86070
    ⋮⋮⋮
    2021-02-25T00:00:00Z17223.255814
    2021-02-26T00:00:00Z16719.161677
    2021-02-27T00:00:00Z20820.673077
    2021-02-28T00:00:00Z16717.964072
    2021-03-01T00:00:00Z16418.292683
    2021-03-02T00:00:00Z19915.075377
    2021-03-03T00:00:00Z16318.404908
    2021-03-04T00:00:00Z16320.858896
    2021-03-05T00:00:00Z17917.318436
    2021-03-06T00:00:00Z304 9.539474
    2021-03-07T00:00:00Z16215.432099
    2021-03-08T00:00:00Z23413.675214
    2021-03-09T00:00:00Z16023.125000
    2021-03-10T00:00:00Z15620.512821
    2021-03-11T00:00:00Z553 7.233273
    2021-03-12T00:00:00Z25314.624506
    2021-03-13T00:00:00Z23714.345992
    2021-03-14T00:00:00Z14720.408163
    2021-03-15T00:00:00Z15418.831169
    2021-03-16T00:00:00Z15421.428571
    2021-03-17T00:00:00Z14121.985816
    2021-03-18T00:00:00Z15320.261438
    2021-03-19T00:00:00Z26819.402985
    2021-03-20T00:00:00Z658 6.382979
    2021-03-21T00:00:00Z17023.529412
    2021-03-22T00:00:00Z17422.413793
    2021-03-23T00:00:00Z14316.783217
    2021-03-24T00:00:00Z15717.197452
    2021-03-25T00:00:00Z16525.454545
    2021-03-26T00:00:00Z573 6.108202

    Identifying Covid vs Normal Time Periods

    The following modifications are my attempts to identify covid years for our analysis, I could edit the csv, but I decided to explore R to practice etl for larger datasets. The Fall 2017 STAT 200 course page on Regression With Factor Variables was particularly helpful as a reference when I was trying to have R use Covid as the default factor instead of Normal, having Covid as the default factor will be important when I generate the linear models and interpret the outputs. I would also recommend reading the berkley stats page on "Factors in R" to get a deeper understanding of how to convert factors with dates

    I could have applied the relevel() to the as.factor line as seen in this stack overflow answer How to force R to use a specified factor level as reference in a regression?, but I realized it was much easier to read/run the code in my head line by line than to pass into multiple functions

    # marking covid and non covid months
joins$year_type = as.double(joins$year)
joins$year_type[joins$year_type == 1 ] <- "Normal"
joins$year_type[joins$year_type == 2] <- "Covid"
joins$year_type[joins$year_type == 3] <- "Covid"
joins$year_type = as.factor(joins$year_type)
joins$year_type = relevel(joins$year_type, ref = 2)
head(joins)

leaves$year_type = as.double(leaves$year)
leaves$year_type[leaves$year_type == 1 ] <- "Normal"
leaves$year_type[leaves$year_type ==2] <- "Covid"
leaves$year_type[leaves$year_type ==3] <- "Covid"
leaves$year_type = as.factor(leaves$year_type)
leaves$year_type = relevel(leaves$year_type, ref = 2)
head(leaves)

sources$year_type = as.double(sources$year)
sources$year_type[sources$year_type == 1 ] <- "Normal"
sources$year_type[sources$year_type ==2] <- "Covid"
sources$year_type[sources$year_type ==3] <- "Covid"
sources$year_type = as.factor(sources$year_type)
sources$year_type = relevel(sources$year_type, ref = 2)
head(sources)

messages$year_type = as.double(messages$year)
messages$year_type[messages$year_type == 1 ] <- "Normal"
messages$year_type[messages$year_type ==2] <- "Covid"
messages$year_type[messages$year_type ==3] <- "Covid"
messages$year_type = as.factor(messages$year_type)
messages$year_type = relevel(messages$year_type, ref = 2)
head(messages)

voices$year_type = as.double(voices$year)
voices$year_type[voices$year_type == 1 ] <- "Normal"
voices$year_type[voices$year_type ==2] <- "Covid"
voices$year_type[voices$year_type ==3] <- "Covid"
voices$year_type = as.factor(voices$year_type)
voices$year_type = relevel(voices$year_type, ref = 2)
head(voices)

communicators$year_type = as.double(communicators$year)
communicators$year_type[communicators$year_type == 1 ] <- "Normal"
communicators$year_type[communicators$year_type ==2] <- "Covid"
communicators$year_type[communicators$year_type ==3] <- "Covid"
communicators$year_type = as.factor(communicators$year_type)
communicators$year_type = relevel(communicators$year_type, ref = 2)
head(communicators)

    A data.frame: 6 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 250.00000 50.00000Normal
    22019-03-30T00:00:00Z2019MarchSaturday 616.66667 33.33333Normal
    32019-03-31T00:00:00Z2019MarchSunday 825.00000 37.50000Normal
    42019-04-01T00:00:00Z2019AprilMonday 944.44444 33.33333Normal
    52019-04-02T00:00:00Z2019AprilTuesday 250.00000100.00000Normal
    62019-04-03T00:00:00Z2019AprilWednesday0 NA NANormal
    A data.frame: 6 × 7
    interval_start_timestampyearmonthdaydays_in_guildleaversyear_type
    <chr><fct><fct><fct><fct><int><fct>
    12019-03-29T00:00:00Z2019MarchFriday 'Members for 1 month+' 1Normal
    22019-03-30T00:00:00Z2019MarchSaturday'Members for 1 month+' 1Normal
    32019-03-30T00:00:00Z2019MarchSaturday'Members for < 1 month'1Normal
    42019-03-31T00:00:00Z2019MarchSunday 'Members for 1 month+' 2Normal
    52019-03-31T00:00:00Z2019March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Normal
    62019-04-01T00:00:00Z2019AprilMonday 'Members for 1 month+' 4Normal
    A data.frame: 6 × 8
    interval_start_timestampyearmonthdaydiscovery_joinsinvitesvanity_joinsyear_type
    <chr><fct><fct><fct><int><int><int><fct>
    12019-03-29T00:00:00Z2019MarchFriday 00 3Normal
    22019-03-30T00:00:00Z2019MarchSaturday 00 7Normal
    32019-03-31T00:00:00Z2019MarchSunday 00 8Normal
    42019-04-01T00:00:00Z2019AprilMonday 0011Normal
    52019-04-02T00:00:00Z2019AprilTuesday 00 2Normal
    62019-04-03T00:00:00Z2019AprilWednesday00 1Normal
    A data.frame: 6 × 7
    interval_start_timestampyearmonthdaymessagesmessages_per_communicatoryear_type
    <chr><fct><fct><fct><int><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 334 6.301887Normal
    22019-03-30T00:00:00Z2019MarchSaturday 236 6.210526Normal
    32019-03-31T00:00:00Z2019MarchSunday 364 8.088889Normal
    42019-04-01T00:00:00Z2019AprilMonday 404 5.386667Normal
    52019-04-02T00:00:00Z2019AprilTuesday 54311.312500Normal
    62019-04-03T00:00:00Z2019AprilWednesday324 7.200000Normal
    A data.frame: 6 × 6
    interval_start_timestampyearmonthdayspeaking_minutesyear_type
    <chr><fct><fct><fct><int><fct>
    12019-03-29T00:00:00Z2019MarchFriday 0Normal
    22019-03-30T00:00:00Z2019MarchSaturday 0Normal
    32019-03-31T00:00:00Z2019MarchSunday 0Normal
    42019-04-01T00:00:00Z2019AprilMonday 0Normal
    52019-04-02T00:00:00Z2019AprilTuesday 0Normal
    62019-04-03T00:00:00Z2019AprilWednesday0Normal
    A data.frame: 6 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 20625.7281653Normal
    22019-03-30T00:00:00Z2019MarchSaturday 18420.6521738Normal
    32019-03-31T00:00:00Z2019MarchSunday 18524.3243245Normal
    42019-04-01T00:00:00Z2019AprilMonday 32822.8658575Normal
    52019-04-02T00:00:00Z2019AprilTuesday 14333.5664348Normal
    62019-04-03T00:00:00Z2019AprilWednesday27116.6051745Normal

    Data Needed For Investigation

    The following cells are the final processed data that will be used for analysis

    Historical data 

    head(joins)
head(leaves)
head(sources)
head(messages)
head(voices)
head(communicators)
    A data.frame: 6 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 250.00000 50.00000Normal
    22019-03-30T00:00:00Z2019MarchSaturday 616.66667 33.33333Normal
    32019-03-31T00:00:00Z2019MarchSunday 825.00000 37.50000Normal
    42019-04-01T00:00:00Z2019AprilMonday 944.44444 33.33333Normal
    52019-04-02T00:00:00Z2019AprilTuesday 250.00000100.00000Normal
    62019-04-03T00:00:00Z2019AprilWednesday0 NA NANormal
    A data.frame: 6 × 7
    interval_start_timestampyearmonthdaydays_in_guildleaversyear_type
    <chr><fct><fct><fct><fct><int><fct>
    12019-03-29T00:00:00Z2019MarchFriday 'Members for 1 month+' 1Normal
    22019-03-30T00:00:00Z2019MarchSaturday'Members for 1 month+' 1Normal
    32019-03-30T00:00:00Z2019MarchSaturday'Members for < 1 month'1Normal
    42019-03-31T00:00:00Z2019MarchSunday 'Members for 1 month+' 2Normal
    52019-03-31T00:00:00Z2019March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Normal
    62019-04-01T00:00:00Z2019AprilMonday 'Members for 1 month+' 4Normal
    A data.frame: 6 × 8
    interval_start_timestampyearmonthdaydiscovery_joinsinvitesvanity_joinsyear_type
    <chr><fct><fct><fct><int><int><int><fct>
    12019-03-29T00:00:00Z2019MarchFriday 00 3Normal
    22019-03-30T00:00:00Z2019MarchSaturday 00 7Normal
    32019-03-31T00:00:00Z2019MarchSunday 00 8Normal
    42019-04-01T00:00:00Z2019AprilMonday 0011Normal
    52019-04-02T00:00:00Z2019AprilTuesday 00 2Normal
    62019-04-03T00:00:00Z2019AprilWednesday00 1Normal
    A data.frame: 6 × 7
    interval_start_timestampyearmonthdaymessagesmessages_per_communicatoryear_type
    <chr><fct><fct><fct><int><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 334 6.301887Normal
    22019-03-30T00:00:00Z2019MarchSaturday 236 6.210526Normal
    32019-03-31T00:00:00Z2019MarchSunday 364 8.088889Normal
    42019-04-01T00:00:00Z2019AprilMonday 404 5.386667Normal
    52019-04-02T00:00:00Z2019AprilTuesday 54311.312500Normal
    62019-04-03T00:00:00Z2019AprilWednesday324 7.200000Normal
    A data.frame: 6 × 6
    interval_start_timestampyearmonthdayspeaking_minutesyear_type
    <chr><fct><fct><fct><int><fct>
    12019-03-29T00:00:00Z2019MarchFriday 0Normal
    22019-03-30T00:00:00Z2019MarchSaturday 0Normal
    32019-03-31T00:00:00Z2019MarchSunday 0Normal
    42019-04-01T00:00:00Z2019AprilMonday 0Normal
    52019-04-02T00:00:00Z2019AprilTuesday 0Normal
    62019-04-03T00:00:00Z2019AprilWednesday0Normal
    A data.frame: 6 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 20625.7281653Normal
    22019-03-30T00:00:00Z2019MarchSaturday 18420.6521738Normal
    32019-03-31T00:00:00Z2019MarchSunday 18524.3243245Normal
    42019-04-01T00:00:00Z2019AprilMonday 32822.8658575Normal
    52019-04-02T00:00:00Z2019AprilTuesday 14333.5664348Normal
    62019-04-03T00:00:00Z2019AprilWednesday27116.6051745Normal

    Last 28 days 

    head(text)
head(voice)
    A data.frame: 6 × 6
    interval_start_timestampchannel_namechannel_idreaderschattersmessages
    <fct><fct><dbl><int><int><int>
    12021-03-27T00:00:00+00:00general 2.124359e+1721851264
    22021-03-27T00:00:00+00:00hearthstone2.124361e+17 3 0 0
    32021-03-27T00:00:00+00:00overwatch 2.124362e+17 9838794
    42021-03-27T00:00:00+00:00lol 2.124362e+17 9731181
    52021-03-27T00:00:00+00:00csgo 2.124363e+17 29 4 5
    62021-03-27T00:00:00+00:00dota2 2.124364e+17 17 5 11
    A data.frame: 6 × 2
    interval_start_timestampspeaking_minutes
    <chr><int>
    12019-03-29T00:00:00Z0
    22019-03-30T00:00:00Z0
    32019-03-31T00:00:00Z0
    42019-04-01T00:00:00Z0
    52019-04-02T00:00:00Z0
    62019-04-03T00:00:00Z0

    Data Aggregation

    subsetting by year

    Originally I planned on aggregating by the year for my bar charts, but when I read through some more examples of aggregates, I found a better method in "Aggregating by category"

    joins.2019 = subset(joins, year == 2019)
joins.2020 = subset(joins, year == 2020)
joins.2021 = subset(joins, year == 2021)

leaves.2019 = subset(leaves, year == 2019)
leaves.2020 = subset(leaves, year == 2020)
leaves.2021 = subset(leaves, year == 2021)

sources.2019 = subset(sources, year == 2019)
sources.2020 = subset(sources, year == 2020)
sources.2021 = subset(sources, year == 2021)

comm.2019 = subset(communicators, year == 2019)
comm.2020 = subset(communicators, year == 2020)
comm.2021 = subset(communicators, year == 2021)

    Aggregating by year

    2019 

    joins.2019
leaves.2019
sources.2019
comm.2019

    A data.frame: 278 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 2 50.00000 50.00000Normal
    22019-03-30T00:00:00Z2019MarchSaturday 6 16.66667 33.33333Normal
    32019-03-31T00:00:00Z2019MarchSunday 8 25.00000 37.50000Normal
    42019-04-01T00:00:00Z2019AprilMonday 9 44.44444 33.33333Normal
    52019-04-02T00:00:00Z2019AprilTuesday 2 50.00000100.00000Normal
    62019-04-03T00:00:00Z2019AprilWednesday0 NA NANormal
    72019-04-04T00:00:00Z2019AprilThursday 2100.00000100.00000Normal
    82019-04-05T00:00:00Z2019AprilFriday 3 33.33333 0.00000Normal
    92019-04-06T00:00:00Z2019AprilSaturday 2 0.00000 0.00000Normal
    102019-04-07T00:00:00Z2019AprilSunday 2 0.00000 0.00000Normal
    112019-04-08T00:00:00Z2019AprilMonday 9 33.33333 33.33333Normal
    122019-04-09T00:00:00Z2019AprilTuesday 3 33.33333 33.33333Normal
    132019-04-10T00:00:00Z2019AprilWednesday1100.00000100.00000Normal
    142019-04-11T00:00:00Z2019AprilThursday 1 0.00000100.00000Normal
    152019-04-12T00:00:00Z2019AprilFriday 1 0.00000100.00000Normal
    162019-04-13T00:00:00Z2019AprilSaturday 1 0.00000100.00000Normal
    172019-04-14T00:00:00Z2019AprilSunday 0 NA NANormal
    182019-04-15T00:00:00Z2019AprilMonday 0 NA NANormal
    192019-04-16T00:00:00Z2019AprilTuesday 3 66.66667 0.00000Normal
    202019-04-17T00:00:00Z2019AprilWednesday5 0.00000 20.00000Normal
    212019-04-18T00:00:00Z2019AprilThursday 3100.00000 33.33333Normal
    222019-04-19T00:00:00Z2019AprilFriday 3 0.00000 33.33333Normal
    232019-04-20T00:00:00Z2019AprilSaturday 0 NA NANormal
    242019-04-21T00:00:00Z2019AprilSunday 1100.00000100.00000Normal
    252019-04-22T00:00:00Z2019AprilMonday 0 NA NANormal
    262019-04-23T00:00:00Z2019AprilTuesday 1 0.00000 0.00000Normal
    272019-04-24T00:00:00Z2019AprilWednesday3 33.33333 0.00000Normal
    282019-04-25T00:00:00Z2019AprilThursday 3 66.66667 66.66667Normal
    292019-04-26T00:00:00Z2019AprilFriday 3 33.33333 33.33333Normal
    302019-04-27T00:00:00Z2019AprilSaturday 1100.00000 0.00000Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    2492019-12-02T00:00:00Z2019DecemberMonday 2 0.00000 0.00000Normal
    2502019-12-03T00:00:00Z2019DecemberTuesday 2 0.00000 50.00000Normal
    2512019-12-04T00:00:00Z2019DecemberWednesday3 33.33333 66.66667Normal
    2522019-12-05T00:00:00Z2019DecemberThursday 5 0.00000 20.00000Normal
    2532019-12-06T00:00:00Z2019DecemberFriday 2 50.00000 50.00000Normal
    2542019-12-07T00:00:00Z2019DecemberSaturday 1100.00000 0.00000Normal
    2552019-12-08T00:00:00Z2019DecemberSunday 3 33.33333 33.33333Normal
    2562019-12-09T00:00:00Z2019DecemberMonday 2 50.00000 50.00000Normal
    2572019-12-10T00:00:00Z2019DecemberTuesday 1 0.00000100.00000Normal
    2582019-12-11T00:00:00Z2019DecemberWednesday3 66.66667100.00000Normal
    2592019-12-12T00:00:00Z2019DecemberThursday 1 0.00000 0.00000Normal
    2602019-12-13T00:00:00Z2019DecemberFriday 0 NA NANormal
    2612019-12-14T00:00:00Z2019DecemberSaturday 1 0.00000100.00000Normal
    2622019-12-15T00:00:00Z2019DecemberSunday 1100.00000 0.00000Normal
    2632019-12-16T00:00:00Z2019DecemberMonday 1 0.00000100.00000Normal
    2642019-12-17T00:00:00Z2019DecemberTuesday 1 0.00000100.00000Normal
    2652019-12-18T00:00:00Z2019DecemberWednesday6 0.00000 50.00000Normal
    2662019-12-19T00:00:00Z2019DecemberThursday 1 0.00000 0.00000Normal
    2672019-12-20T00:00:00Z2019DecemberFriday 0 NA NANormal
    2682019-12-21T00:00:00Z2019DecemberSaturday 2 50.00000 50.00000Normal
    2692019-12-22T00:00:00Z2019DecemberSunday 0 NA NANormal
    2702019-12-23T00:00:00Z2019DecemberMonday 0 NA NANormal
    2712019-12-24T00:00:00Z2019DecemberTuesday 0 NA NANormal
    2722019-12-25T00:00:00Z2019DecemberWednesday1 0.00000 0.00000Normal
    2732019-12-26T00:00:00Z2019DecemberThursday 0 NA NANormal
    2742019-12-27T00:00:00Z2019DecemberFriday 1 0.00000 0.00000Normal
    2752019-12-28T00:00:00Z2019DecemberSaturday 1100.00000 0.00000Normal
    2762019-12-29T00:00:00Z2019DecemberSunday 1 0.00000 0.00000Normal
    2772019-12-30T00:00:00Z2019DecemberMonday 0 NA NANormal
    2782019-12-31T00:00:00Z2019DecemberTuesday 0 NA NANormal
    A data.frame: 401 × 7
    interval_start_timestampyearmonthdaydays_in_guildleaversyear_type
    <chr><fct><fct><fct><fct><int><fct>
    12019-03-29T00:00:00Z2019MarchFriday 'Members for 1 month+' 1Normal
    22019-03-30T00:00:00Z2019MarchSaturday 'Members for 1 month+' 1Normal
    32019-03-30T00:00:00Z2019MarchSaturday 'Members for < 1 month'1Normal
    42019-03-31T00:00:00Z2019MarchSunday 'Members for 1 month+' 2Normal
    52019-03-31T00:00:00Z2019March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Normal
    62019-04-01T00:00:00Z2019AprilMonday 'Members for 1 month+' 4Normal
    72019-04-02T00:00:00Z2019AprilTuesday 'Members for 1 month+' 1Normal
    82019-04-03T00:00:00Z2019AprilWednesday'Members for 1 month+' 2Normal
    92019-04-03T00:00:00Z2019AprilWednesday'Members for < 1 month'2Normal
    102019-04-04T00:00:00Z2019AprilThursday 'Members for 1 month+' 2Normal
    112019-04-04T00:00:00Z2019AprilThursday 'Members for < 1 month'2Normal
    122019-04-05T00:00:00Z2019AprilFriday 'Members for 1 month+' 3Normal
    132019-04-06T00:00:00Z2019AprilSaturday 'Members for 1 month+' 1Normal
    142019-04-06T00:00:00Z2019AprilSaturday 'Members for < 1 month'1Normal
    152019-04-07T00:00:00Z2019AprilSunday 'Members for 1 month+' 1Normal
    162019-04-07T00:00:00Z2019April<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'2Normal
    172019-04-08T00:00:00Z2019AprilMonday 'Members for 1 month+' 1Normal
    182019-04-08T00:00:00Z2019April<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Normal
    192019-04-09T00:00:00Z2019AprilTuesday 'Members for 1 month+' 1Normal
    202019-04-09T00:00:00Z2019April<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Normal
    212019-04-10T00:00:00Z2019AprilWednesday'Members for 1 month+' 2Normal
    222019-04-10T00:00:00Z2019AprilWednesday'Members for < 1 month'1Normal
    232019-04-11T00:00:00Z2019AprilThursday 'Members for 1 month+' 0Normal
    242019-04-12T00:00:00Z2019AprilFriday 'Members for 1 month+' 1Normal
    252019-04-13T00:00:00Z2019AprilSaturday 'Members for < 1 month'1Normal
    262019-04-14T00:00:00Z2019AprilSunday 'Members for 1 month+' 2Normal
    272019-04-15T00:00:00Z2019AprilMonday 'Members for 1 month+' 1Normal
    282019-04-15T00:00:00Z2019April<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Normal
    292019-04-16T00:00:00Z2019AprilTuesday 'Members for 1 month+' 3Normal
    302019-04-16T00:00:00Z2019April<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮
    3722019-12-06T00:00:00Z2019DecemberFriday 'Members for 1 month+' 0Normal
    3732019-12-07T00:00:00Z2019DecemberSaturday 'Members for 1 month+' 4Normal
    3742019-12-08T00:00:00Z2019DecemberSunday 'Members for 1 month+' 4Normal
    3752019-12-09T00:00:00Z2019DecemberMonday 'Members for 1 month+' 0Normal
    3762019-12-10T00:00:00Z2019DecemberTuesday 'Members for 1 month+' 1Normal
    3772019-12-11T00:00:00Z2019DecemberWednesday'Members for 1 month+' 0Normal
    3782019-12-12T00:00:00Z2019DecemberThursday 'Members for 1 month+' 1Normal
    3792019-12-13T00:00:00Z2019DecemberFriday 'Members for 1 month+' 2Normal
    3802019-12-14T00:00:00Z2019DecemberSaturday 'Members for 1 month+' 0Normal
    3812019-12-15T00:00:00Z2019DecemberSunday 'Members for 1 month+' 0Normal
    3822019-12-16T00:00:00Z2019DecemberMonday 'Members for 1 month+' 2Normal
    3832019-12-16T00:00:00Z2019December<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Normal
    3842019-12-17T00:00:00Z2019DecemberTuesday 'Members for 1 month+' 3Normal
    3852019-12-18T00:00:00Z2019DecemberWednesday'Members for 1 month+' 2Normal
    3862019-12-19T00:00:00Z2019DecemberThursday 'Members for 1 month+' 1Normal
    3872019-12-20T00:00:00Z2019DecemberFriday 'Members for 1 month+' 0Normal
    3882019-12-21T00:00:00Z2019DecemberSaturday 'Members for 1 month+' 2Normal
    3892019-12-21T00:00:00Z2019DecemberSaturday 'Members for < 1 month'1Normal
    3902019-12-22T00:00:00Z2019DecemberSunday 'Members for 1 month+' 1Normal
    3912019-12-22T00:00:00Z2019December<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Normal
    3922019-12-23T00:00:00Z2019DecemberMonday 'Members for 1 month+' 1Normal
    3932019-12-24T00:00:00Z2019DecemberTuesday 'Members for 1 month+' 1Normal
    3942019-12-25T00:00:00Z2019DecemberWednesday'Members for 1 month+' 1Normal
    3952019-12-26T00:00:00Z2019DecemberThursday 'Members for 1 month+' 1Normal
    3962019-12-27T00:00:00Z2019DecemberFriday 'Members for 1 month+' 0Normal
    3972019-12-28T00:00:00Z2019DecemberSaturday 'Members for 1 month+' 0Normal
    3982019-12-29T00:00:00Z2019DecemberSunday 'Members for 1 month+' 2Normal
    3992019-12-29T00:00:00Z2019December<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Normal
    4002019-12-30T00:00:00Z2019DecemberMonday 'Members for 1 month+' 1Normal
    4012019-12-31T00:00:00Z2019DecemberTuesday 'Members for 1 month+' 2Normal
    A data.frame: 278 × 8
    interval_start_timestampyearmonthdaydiscovery_joinsinvitesvanity_joinsyear_type
    <chr><fct><fct><fct><int><int><int><fct>
    12019-03-29T00:00:00Z2019MarchFriday 00 3Normal
    22019-03-30T00:00:00Z2019MarchSaturday 00 7Normal
    32019-03-31T00:00:00Z2019MarchSunday 00 8Normal
    42019-04-01T00:00:00Z2019AprilMonday 0011Normal
    52019-04-02T00:00:00Z2019AprilTuesday 00 2Normal
    62019-04-03T00:00:00Z2019AprilWednesday00 1Normal
    72019-04-04T00:00:00Z2019AprilThursday 00 3Normal
    82019-04-05T00:00:00Z2019AprilFriday 00 4Normal
    92019-04-06T00:00:00Z2019AprilSaturday 00 3Normal
    102019-04-07T00:00:00Z2019AprilSunday 00 2Normal
    112019-04-08T00:00:00Z2019AprilMonday 00 9Normal
    122019-04-09T00:00:00Z2019AprilTuesday 00 3Normal
    132019-04-10T00:00:00Z2019AprilWednesday00 1Normal
    142019-04-11T00:00:00Z2019AprilThursday 00 2Normal
    152019-04-12T00:00:00Z2019AprilFriday 00 1Normal
    162019-04-13T00:00:00Z2019AprilSaturday 00 1Normal
    172019-04-14T00:00:00Z2019AprilSunday 00 0Normal
    182019-04-15T00:00:00Z2019AprilMonday 00 0Normal
    192019-04-16T00:00:00Z2019AprilTuesday 00 7Normal
    202019-04-17T00:00:00Z2019AprilWednesday00 5Normal
    212019-04-18T00:00:00Z2019AprilThursday 00 6Normal
    222019-04-19T00:00:00Z2019AprilFriday 00 3Normal
    232019-04-20T00:00:00Z2019AprilSaturday 00 2Normal
    242019-04-21T00:00:00Z2019AprilSunday 00 1Normal
    252019-04-22T00:00:00Z2019AprilMonday 00 1Normal
    262019-04-23T00:00:00Z2019AprilTuesday 00 3Normal
    272019-04-24T00:00:00Z2019AprilWednesday00 3Normal
    282019-04-25T00:00:00Z2019AprilThursday 00 3Normal
    292019-04-26T00:00:00Z2019AprilFriday 00 4Normal
    302019-04-27T00:00:00Z2019AprilSaturday 00 3Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    2492019-12-02T00:00:00Z2019DecemberMonday 002Normal
    2502019-12-03T00:00:00Z2019DecemberTuesday 002Normal
    2512019-12-04T00:00:00Z2019DecemberWednesday003Normal
    2522019-12-05T00:00:00Z2019DecemberThursday 005Normal
    2532019-12-06T00:00:00Z2019DecemberFriday 002Normal
    2542019-12-07T00:00:00Z2019DecemberSaturday 001Normal
    2552019-12-08T00:00:00Z2019DecemberSunday 004Normal
    2562019-12-09T00:00:00Z2019DecemberMonday 002Normal
    2572019-12-10T00:00:00Z2019DecemberTuesday 001Normal
    2582019-12-11T00:00:00Z2019DecemberWednesday003Normal
    2592019-12-12T00:00:00Z2019DecemberThursday 002Normal
    2602019-12-13T00:00:00Z2019DecemberFriday 000Normal
    2612019-12-14T00:00:00Z2019DecemberSaturday 001Normal
    2622019-12-15T00:00:00Z2019DecemberSunday 001Normal
    2632019-12-16T00:00:00Z2019DecemberMonday 001Normal
    2642019-12-17T00:00:00Z2019DecemberTuesday 001Normal
    2652019-12-18T00:00:00Z2019DecemberWednesday006Normal
    2662019-12-19T00:00:00Z2019DecemberThursday 002Normal
    2672019-12-20T00:00:00Z2019DecemberFriday 000Normal
    2682019-12-21T00:00:00Z2019DecemberSaturday 004Normal
    2692019-12-22T00:00:00Z2019DecemberSunday 001Normal
    2702019-12-23T00:00:00Z2019DecemberMonday 000Normal
    2712019-12-24T00:00:00Z2019DecemberTuesday 000Normal
    2722019-12-25T00:00:00Z2019DecemberWednesday001Normal
    2732019-12-26T00:00:00Z2019DecemberThursday 000Normal
    2742019-12-27T00:00:00Z2019DecemberFriday 001Normal
    2752019-12-28T00:00:00Z2019DecemberSaturday 001Normal
    2762019-12-29T00:00:00Z2019DecemberSunday 001Normal
    2772019-12-30T00:00:00Z2019DecemberMonday 000Normal
    2782019-12-31T00:00:00Z2019DecemberTuesday 000Normal
    A data.frame: 278 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 20625.7281653Normal
    22019-03-30T00:00:00Z2019MarchSaturday 18420.6521738Normal
    32019-03-31T00:00:00Z2019MarchSunday 18524.3243245Normal
    42019-04-01T00:00:00Z2019AprilMonday 32822.8658575Normal
    52019-04-02T00:00:00Z2019AprilTuesday 14333.5664348Normal
    62019-04-03T00:00:00Z2019AprilWednesday27116.6051745Normal
    72019-04-04T00:00:00Z2019AprilThursday 38113.3858351Normal
    82019-04-05T00:00:00Z2019AprilFriday 19024.7368447Normal
    92019-04-06T00:00:00Z2019AprilSaturday 16326.9938744Normal
    102019-04-07T00:00:00Z2019AprilSunday 15931.4465450Normal
    112019-04-08T00:00:00Z2019AprilMonday 16325.7668742Normal
    122019-04-09T00:00:00Z2019AprilTuesday 14831.0810846Normal
    132019-04-10T00:00:00Z2019AprilWednesday16330.6748550Normal
    142019-04-11T00:00:00Z2019AprilThursday 13938.1295053Normal
    152019-04-12T00:00:00Z2019AprilFriday 15529.6774246Normal
    162019-04-13T00:00:00Z2019AprilSaturday 14330.0699343Normal
    172019-04-14T00:00:00Z2019AprilSunday 14028.5714340Normal
    182019-04-15T00:00:00Z2019AprilMonday 17029.4117650Normal
    192019-04-16T00:00:00Z2019AprilTuesday 15040.6666761Normal
    202019-04-17T00:00:00Z2019AprilWednesday15334.6405253Normal
    212019-04-18T00:00:00Z2019AprilThursday 16743.7125773Normal
    222019-04-19T00:00:00Z2019AprilFriday 16233.9506255Normal
    232019-04-20T00:00:00Z2019AprilSaturday 33715.1335351Normal
    242019-04-21T00:00:00Z2019AprilSunday 17225.0000043Normal
    252019-04-22T00:00:00Z2019AprilMonday 16224.0740739Normal
    262019-04-23T00:00:00Z2019AprilTuesday 16335.5828258Normal
    272019-04-24T00:00:00Z2019AprilWednesday34015.2941252Normal
    282019-04-25T00:00:00Z2019AprilThursday 19626.5306152Normal
    292019-04-26T00:00:00Z2019AprilFriday 37116.9811363Normal
    302019-04-27T00:00:00Z2019AprilSaturday 20127.8607056Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    2492019-12-02T00:00:00Z2019DecemberMonday 15530.9677448Normal
    2502019-12-03T00:00:00Z2019DecemberTuesday 17027.0588246Normal
    2512019-12-04T00:00:00Z2019DecemberWednesday42910.4895145Normal
    2522019-12-05T00:00:00Z2019DecemberThursday 24714.9797637Normal
    2532019-12-06T00:00:00Z2019DecemberFriday 43216.4351971Normal
    2542019-12-07T00:00:00Z2019DecemberSaturday 44313.3182859Normal
    2552019-12-08T00:00:00Z2019DecemberSunday 43213.6574159Normal
    2562019-12-09T00:00:00Z2019DecemberMonday 21722.1198248Normal
    2572019-12-10T00:00:00Z2019DecemberTuesday 16629.5180749Normal
    2582019-12-11T00:00:00Z2019DecemberWednesday16229.6296348Normal
    2592019-12-12T00:00:00Z2019DecemberThursday 41214.3203959Normal
    2602019-12-13T00:00:00Z2019DecemberFriday 17721.4689338Normal
    2612019-12-14T00:00:00Z2019DecemberSaturday 18821.2766040Normal
    2622019-12-15T00:00:00Z2019DecemberSunday 16927.8106547Normal
    2632019-12-16T00:00:00Z2019DecemberMonday 13628.6764739Normal
    2642019-12-17T00:00:00Z2019DecemberTuesday 13332.3308343Normal
    2652019-12-18T00:00:00Z2019DecemberWednesday12721.2598427Normal
    2662019-12-19T00:00:00Z2019DecemberThursday 12325.2032531Normal
    2672019-12-20T00:00:00Z2019DecemberFriday 14419.4444428Normal
    2682019-12-21T00:00:00Z2019DecemberSaturday 12520.8000026Normal
    2692019-12-22T00:00:00Z2019DecemberSunday 11718.8034222Normal
    2702019-12-23T00:00:00Z2019DecemberMonday 11624.1379328Normal
    2712019-12-24T00:00:00Z2019DecemberTuesday 10824.0740726Normal
    2722019-12-25T00:00:00Z2019DecemberWednesday10626.4150928Normal
    2732019-12-26T00:00:00Z2019DecemberThursday 11026.3636429Normal
    2742019-12-27T00:00:00Z2019DecemberFriday 9631.2500030Normal
    2752019-12-28T00:00:00Z2019DecemberSaturday 9118.6813217Normal
    2762019-12-29T00:00:00Z2019DecemberSunday 9021.1111119Normal
    2772019-12-30T00:00:00Z2019DecemberMonday 10825.9259328Normal
    2782019-12-31T00:00:00Z2019DecemberTuesday 10026.0000026Normal

    2020 

    joins.2020
leaves.2020
sources.2020
comm.2020

    A data.frame: 366 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    2792020-01-01T00:00:00Z2020JanuaryWednesday 0 NA NACovid
    2802020-01-02T00:00:00Z2020JanuaryThursday 1 0.00000100.00000Covid
    2812020-01-03T00:00:00Z2020JanuaryFriday 2 0.00000 50.00000Covid
    2822020-01-04T00:00:00Z2020JanuarySaturday 0 NA NACovid
    2832020-01-05T00:00:00Z2020JanuarySunday 0 NA NACovid
    2842020-01-06T00:00:00Z2020JanuaryMonday 3 0.00000 0.00000Covid
    2852020-01-07T00:00:00Z2020JanuaryTuesday 1 0.00000100.00000Covid
    2862020-01-08T00:00:00Z2020JanuaryWednesday 2 0.00000 50.00000Covid
    2872020-01-09T00:00:00Z2020JanuaryThursday 3 33.33333 33.33333Covid
    2882020-01-10T00:00:00Z2020JanuaryFriday 2 0.00000 0.00000Covid
    2892020-01-11T00:00:00Z2020JanuarySaturday 0 NA NACovid
    2902020-01-12T00:00:00Z2020JanuarySunday 2 0.00000100.00000Covid
    2912020-01-13T00:00:00Z2020JanuaryMonday 2100.00000100.00000Covid
    2922020-01-14T00:00:00Z2020JanuaryTuesday 7 14.28571 57.14286Covid
    2932020-01-15T00:00:00Z2020JanuaryWednesday 4 0.00000 25.00000Covid
    2942020-01-16T00:00:00Z2020JanuaryThursday 3 33.33333100.00000Covid
    2952020-01-17T00:00:00Z2020JanuaryFriday 1 0.00000 0.00000Covid
    2962020-01-18T00:00:00Z2020JanuarySaturday 3 0.00000100.00000Covid
    2972020-01-19T00:00:00Z2020JanuarySunday 2 0.00000 50.00000Covid
    2982020-01-20T00:00:00Z2020JanuaryMonday 2 50.00000100.00000Covid
    2992020-01-21T00:00:00Z2020JanuaryTuesday 4 25.00000 75.00000Covid
    3002020-01-22T00:00:00Z2020JanuaryWednesday 3 0.00000 0.00000Covid
    3012020-01-23T00:00:00Z2020JanuaryThursday 19 15.78947 21.05263Covid
    3022020-01-24T00:00:00Z2020JanuaryFriday 0 NA NACovid
    3032020-01-25T00:00:00Z2020JanuarySaturday 3 33.33333 33.33333Covid
    3042020-01-26T00:00:00Z2020JanuarySunday 3 0.00000100.00000Covid
    3052020-01-27T00:00:00Z2020JanuaryMonday 3 0.00000 66.66667Covid
    3062020-01-28T00:00:00Z2020JanuaryTuesday 2 0.00000100.00000Covid
    3072020-01-29T00:00:00Z2020JanuaryWednesday 5 40.00000 80.00000Covid
    3082020-01-30T00:00:00Z2020JanuaryThursday 1 0.00000100.00000Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    6152020-12-02T00:00:00Z2020DecemberWednesday250.00000100.00000Covid
    6162020-12-03T00:00:00Z2020DecemberThursday 2 0.00000 50.00000Covid
    6172020-12-04T00:00:00Z2020DecemberFriday 540.00000 80.00000Covid
    6182020-12-05T00:00:00Z2020DecemberSaturday 425.00000 25.00000Covid
    6192020-12-06T00:00:00Z2020DecemberSunday 3 0.00000 0.00000Covid
    6202020-12-07T00:00:00Z2020DecemberMonday 1 0.00000100.00000Covid
    6212020-12-08T00:00:00Z2020DecemberTuesday 1 0.00000100.00000Covid
    6222020-12-09T00:00:00Z2020DecemberWednesday1 0.00000 0.00000Covid
    6232020-12-10T00:00:00Z2020DecemberThursday 1 0.00000100.00000Covid
    6242020-12-11T00:00:00Z2020DecemberFriday 1 0.00000100.00000Covid
    6252020-12-12T00:00:00Z2020DecemberSaturday 3 0.00000 66.66667Covid
    6262020-12-13T00:00:00Z2020DecemberSunday 5 0.00000 20.00000Covid
    6272020-12-14T00:00:00Z2020DecemberMonday 3 0.00000 66.66667Covid
    6282020-12-15T00:00:00Z2020DecemberTuesday 250.00000100.00000Covid
    6292020-12-16T00:00:00Z2020DecemberWednesday450.00000 75.00000Covid
    6302020-12-17T00:00:00Z2020DecemberThursday 0 NA NACovid
    6312020-12-18T00:00:00Z2020DecemberFriday 250.00000 50.00000Covid
    6322020-12-19T00:00:00Z2020DecemberSaturday 0 NA NACovid
    6332020-12-20T00:00:00Z2020DecemberSunday 911.11111 55.55556Covid
    6342020-12-21T00:00:00Z2020DecemberMonday 250.00000 50.00000Covid
    6352020-12-22T00:00:00Z2020DecemberTuesday 3 0.00000 33.33333Covid
    6362020-12-23T00:00:00Z2020DecemberWednesday0 NA NACovid
    6372020-12-24T00:00:00Z2020DecemberThursday 0 NA NACovid
    6382020-12-25T00:00:00Z2020DecemberFriday 2 0.00000 0.00000Covid
    6392020-12-26T00:00:00Z2020DecemberSaturday 333.33333100.00000Covid
    6402020-12-27T00:00:00Z2020DecemberSunday 0 NA NACovid
    6412020-12-28T00:00:00Z2020DecemberMonday 1 0.00000 0.00000Covid
    6422020-12-29T00:00:00Z2020DecemberTuesday 3 0.00000 33.33333Covid
    6432020-12-30T00:00:00Z2020DecemberWednesday1 0.00000 0.00000Covid
    6442020-12-31T00:00:00Z2020DecemberThursday 3 0.00000 33.33333Covid
    A data.frame: 568 × 7
    interval_start_timestampyearmonthdaydays_in_guildleaversyear_type
    <chr><fct><fct><fct><fct><int><fct>
    4022020-01-01T00:00:00Z2020JanuaryWednesday'Members for 1 month+' 0Covid
    4032020-01-02T00:00:00Z2020JanuaryThursday 'Members for 1 month+' 0Covid
    4042020-01-03T00:00:00Z2020JanuaryFriday 'Members for 1 month+' 2Covid
    4052020-01-03T00:00:00Z2020January<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1Covid
    4062020-01-04T00:00:00Z2020JanuarySaturday 'Members for 1 month+' 2Covid
    4072020-01-04T00:00:00Z2020JanuarySaturday 'Members for < 1 month'1Covid
    4082020-01-05T00:00:00Z2020JanuarySunday 'Members for 1 month+' 1Covid
    4092020-01-06T00:00:00Z2020January<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Covid
    4102020-01-07T00:00:00Z2020JanuaryTuesday 'Members for 1 month+' 3Covid
    4112020-01-08T00:00:00Z2020JanuaryWednesday'Members for 1 month+' 1Covid
    4122020-01-08T00:00:00Z2020JanuaryWednesday'Members for < 1 month'1Covid
    4132020-01-09T00:00:00Z2020JanuaryThursday 'Members for 1 month+' 2Covid
    4142020-01-09T00:00:00Z2020JanuaryThursday 'Members for < 1 month'1Covid
    4152020-01-10T00:00:00Z2020JanuaryFriday 'Members for 1 month+' 2Covid
    4162020-01-11T00:00:00Z2020JanuarySaturday 'Members for 1 month+' 0Covid
    4172020-01-12T00:00:00Z2020JanuarySunday 'Members for 1 month+' 2Covid
    4182020-01-13T00:00:00Z2020JanuaryMonday 'Members for 1 month+' 4Covid
    4192020-01-14T00:00:00Z2020JanuaryTuesday 'Members for 1 month+' 3Covid
    4202020-01-14T00:00:00Z2020January<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    4212020-01-15T00:00:00Z2020JanuaryWednesday'Members for < 1 month'1Covid
    4222020-01-16T00:00:00Z2020JanuaryThursday 'Members for 1 month+' 3Covid
    4232020-01-16T00:00:00Z2020JanuaryThursday 'Members for < 1 month'1Covid
    4242020-01-17T00:00:00Z2020JanuaryFriday 'Members for 1 month+' 2Covid
    4252020-01-17T00:00:00Z2020January<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1Covid
    4262020-01-18T00:00:00Z2020JanuarySaturday 'Members for 1 month+' 2Covid
    4272020-01-19T00:00:00Z2020JanuarySunday 'Members for 1 month+' 2Covid
    4282020-01-20T00:00:00Z2020JanuaryMonday 'Members for 1 month+' 0Covid
    4292020-01-21T00:00:00Z2020JanuaryTuesday 'Members for 1 month+' 7Covid
    4302020-01-22T00:00:00Z2020JanuaryWednesday'Members for 1 month+' 3Covid
    4312020-01-23T00:00:00Z2020JanuaryThursday 'Members for 1 month+' 1Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮
    9402020-12-11T00:00:00Z2020December<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1Covid
    9412020-12-12T00:00:00Z2020DecemberSaturday 'Members for 1 month+' 1Covid
    9422020-12-12T00:00:00Z2020DecemberSaturday 'Members for < 1 month'1Covid
    9432020-12-13T00:00:00Z2020December<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'2Covid
    9442020-12-14T00:00:00Z2020DecemberMonday 'Members for 1 month+' 2Covid
    9452020-12-14T00:00:00Z2020December<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Covid
    9462020-12-15T00:00:00Z2020DecemberTuesday 'Members for 1 month+' 0Covid
    9472020-12-16T00:00:00Z2020DecemberWednesday'Members for 1 month+' 1Covid
    9482020-12-16T00:00:00Z2020DecemberWednesday'Members for < 1 month'1Covid
    9492020-12-17T00:00:00Z2020DecemberThursday 'Members for 1 month+' 2Covid
    9502020-12-18T00:00:00Z2020DecemberFriday 'Members for 1 month+' 0Covid
    9512020-12-19T00:00:00Z2020DecemberSaturday 'Members for 1 month+' 2Covid
    9522020-12-19T00:00:00Z2020DecemberSaturday 'Members for < 1 month'1Covid
    9532020-12-20T00:00:00Z2020DecemberSunday 'Members for 1 month+' 7Covid
    9542020-12-20T00:00:00Z2020December<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'2Covid
    9552020-12-21T00:00:00Z2020DecemberMonday 'Members for 1 month+' 1Covid
    9562020-12-22T00:00:00Z2020DecemberTuesday 'Members for 1 month+' 1Covid
    9572020-12-22T00:00:00Z2020December<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    9582020-12-23T00:00:00Z2020DecemberWednesday'Members for 1 month+' 3Covid
    9592020-12-24T00:00:00Z2020DecemberThursday 'Members for 1 month+' 0Covid
    9602020-12-25T00:00:00Z2020DecemberFriday 'Members for 1 month+' 7Covid
    9612020-12-25T00:00:00Z2020December<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'2Covid
    9622020-12-26T00:00:00Z2020DecemberSaturday 'Members for 1 month+' 1Covid
    9632020-12-26T00:00:00Z2020DecemberSaturday 'Members for < 1 month'1Covid
    9642020-12-27T00:00:00Z2020DecemberSunday 'Members for 1 month+' 4Covid
    9652020-12-28T00:00:00Z2020DecemberMonday 'Members for 1 month+' 2Covid
    9662020-12-29T00:00:00Z2020DecemberTuesday 'Members for 1 month+' 3Covid
    9672020-12-29T00:00:00Z2020December<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    9682020-12-30T00:00:00Z2020DecemberWednesday'Members for 1 month+' 4Covid
    9692020-12-31T00:00:00Z2020DecemberThursday 'Members for 1 month+' 2Covid
    A data.frame: 366 × 8
    interval_start_timestampyearmonthdaydiscovery_joinsinvitesvanity_joinsyear_type
    <chr><fct><fct><fct><int><int><int><fct>
    2792020-01-01T00:00:00Z2020JanuaryWednesday00 0Covid
    2802020-01-02T00:00:00Z2020JanuaryThursday 00 1Covid
    2812020-01-03T00:00:00Z2020JanuaryFriday 00 2Covid
    2822020-01-04T00:00:00Z2020JanuarySaturday 00 0Covid
    2832020-01-05T00:00:00Z2020JanuarySunday 00 0Covid
    2842020-01-06T00:00:00Z2020JanuaryMonday 00 3Covid
    2852020-01-07T00:00:00Z2020JanuaryTuesday 00 3Covid
    2862020-01-08T00:00:00Z2020JanuaryWednesday00 4Covid
    2872020-01-09T00:00:00Z2020JanuaryThursday 00 3Covid
    2882020-01-10T00:00:00Z2020JanuaryFriday 00 3Covid
    2892020-01-11T00:00:00Z2020JanuarySaturday 00 0Covid
    2902020-01-12T00:00:00Z2020JanuarySunday 00 2Covid
    2912020-01-13T00:00:00Z2020JanuaryMonday 00 3Covid
    2922020-01-14T00:00:00Z2020JanuaryTuesday 00 8Covid
    2932020-01-15T00:00:00Z2020JanuaryWednesday00 4Covid
    2942020-01-16T00:00:00Z2020JanuaryThursday 00 5Covid
    2952020-01-17T00:00:00Z2020JanuaryFriday 00 2Covid
    2962020-01-18T00:00:00Z2020JanuarySaturday 00 4Covid
    2972020-01-19T00:00:00Z2020JanuarySunday 00 3Covid
    2982020-01-20T00:00:00Z2020JanuaryMonday 00 4Covid
    2992020-01-21T00:00:00Z2020JanuaryTuesday 00 4Covid
    3002020-01-22T00:00:00Z2020JanuaryWednesday00 4Covid
    3012020-01-23T00:00:00Z2020JanuaryThursday 0021Covid
    3022020-01-24T00:00:00Z2020JanuaryFriday 00 1Covid
    3032020-01-25T00:00:00Z2020JanuarySaturday 00 4Covid
    3042020-01-26T00:00:00Z2020JanuarySunday 00 3Covid
    3052020-01-27T00:00:00Z2020JanuaryMonday 00 4Covid
    3062020-01-28T00:00:00Z2020JanuaryTuesday 00 2Covid
    3072020-01-29T00:00:00Z2020JanuaryWednesday00 5Covid
    3082020-01-30T00:00:00Z2020JanuaryThursday 00 1Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    6152020-12-02T00:00:00Z2020DecemberWednesday004Covid
    6162020-12-03T00:00:00Z2020DecemberThursday 101Covid
    6172020-12-04T00:00:00Z2020DecemberFriday 005Covid
    6182020-12-05T00:00:00Z2020DecemberSaturday 005Covid
    6192020-12-06T00:00:00Z2020DecemberSunday 003Covid
    6202020-12-07T00:00:00Z2020DecemberMonday 001Covid
    6212020-12-08T00:00:00Z2020DecemberTuesday 001Covid
    6222020-12-09T00:00:00Z2020DecemberWednesday002Covid
    6232020-12-10T00:00:00Z2020DecemberThursday 001Covid
    6242020-12-11T00:00:00Z2020DecemberFriday 001Covid
    6252020-12-12T00:00:00Z2020DecemberSaturday 003Covid
    6262020-12-13T00:00:00Z2020DecemberSunday 204Covid
    6272020-12-14T00:00:00Z2020DecemberMonday 004Covid
    6282020-12-15T00:00:00Z2020DecemberTuesday 003Covid
    6292020-12-16T00:00:00Z2020DecemberWednesday103Covid
    6302020-12-17T00:00:00Z2020DecemberThursday 000Covid
    6312020-12-18T00:00:00Z2020DecemberFriday 002Covid
    6322020-12-19T00:00:00Z2020DecemberSaturday 003Covid
    6332020-12-20T00:00:00Z2020DecemberSunday 009Covid
    6342020-12-21T00:00:00Z2020DecemberMonday 003Covid
    6352020-12-22T00:00:00Z2020DecemberTuesday 003Covid
    6362020-12-23T00:00:00Z2020DecemberWednesday000Covid
    6372020-12-24T00:00:00Z2020DecemberThursday 000Covid
    6382020-12-25T00:00:00Z2020DecemberFriday 002Covid
    6392020-12-26T00:00:00Z2020DecemberSaturday 004Covid
    6402020-12-27T00:00:00Z2020DecemberSunday 000Covid
    6412020-12-28T00:00:00Z2020DecemberMonday 001Covid
    6422020-12-29T00:00:00Z2020DecemberTuesday 102Covid
    6432020-12-30T00:00:00Z2020DecemberWednesday002Covid
    6442020-12-31T00:00:00Z2020DecemberThursday 003Covid
    A data.frame: 366 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    2792020-01-01T00:00:00Z2020JanuaryWednesday10625.47169827Covid
    2802020-01-02T00:00:00Z2020JanuaryThursday 10522.85714324Covid
    2812020-01-03T00:00:00Z2020JanuaryFriday 10425.00000026Covid
    2822020-01-04T00:00:00Z2020JanuarySaturday 10326.21359227Covid
    2832020-01-05T00:00:00Z2020JanuarySunday 9323.65591422Covid
    2842020-01-06T00:00:00Z2020JanuaryMonday 10217.64705918Covid
    2852020-01-07T00:00:00Z2020JanuaryTuesday 10126.73267327Covid
    2862020-01-08T00:00:00Z2020JanuaryWednesday10926.60550529Covid
    2872020-01-09T00:00:00Z2020JanuaryThursday 11024.54545527Covid
    2882020-01-10T00:00:00Z2020JanuaryFriday 10119.80198020Covid
    2892020-01-11T00:00:00Z2020JanuarySaturday 9627.08333326Covid
    2902020-01-12T00:00:00Z2020JanuarySunday 12127.27272733Covid
    2912020-01-13T00:00:00Z2020JanuaryMonday 11422.80701826Covid
    2922020-01-14T00:00:00Z2020JanuaryTuesday 11229.46428633Covid
    2932020-01-15T00:00:00Z2020JanuaryWednesday11729.05982934Covid
    2942020-01-16T00:00:00Z2020JanuaryThursday 13435.82089648Covid
    2952020-01-17T00:00:00Z2020JanuaryFriday 12428.22580635Covid
    2962020-01-18T00:00:00Z2020JanuarySaturday 392 7.14285728Covid
    2972020-01-19T00:00:00Z2020JanuarySunday 391 5.88235323Covid
    2982020-01-20T00:00:00Z2020JanuaryMonday 17121.05263236Covid
    2992020-01-21T00:00:00Z2020JanuaryTuesday 433 8.77598238Covid
    3002020-01-22T00:00:00Z2020JanuaryWednesday24218.59504145Covid
    3012020-01-23T00:00:00Z2020JanuaryThursday 19229.16666756Covid
    3022020-01-24T00:00:00Z2020JanuaryFriday 24820.56451651Covid
    3032020-01-25T00:00:00Z2020JanuarySaturday 41014.39024459Covid
    3042020-01-26T00:00:00Z2020JanuarySunday 19114.65968628Covid
    3052020-01-27T00:00:00Z2020JanuaryMonday 15425.32467539Covid
    3062020-01-28T00:00:00Z2020JanuaryTuesday 16625.90361443Covid
    3072020-01-29T00:00:00Z2020JanuaryWednesday50512.87128765Covid
    3082020-01-30T00:00:00Z2020JanuaryThursday 44410.36036046Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    6152020-12-02T00:00:00Z2020DecemberWednesday15916.98113227Covid
    6162020-12-03T00:00:00Z2020DecemberThursday 26614.28571438Covid
    6172020-12-04T00:00:00Z2020DecemberFriday 19321.76165842Covid
    6182020-12-05T00:00:00Z2020DecemberSaturday 15726.11465041Covid
    6192020-12-06T00:00:00Z2020DecemberSunday 15118.54304628Covid
    6202020-12-07T00:00:00Z2020DecemberMonday 15018.00000027Covid
    6212020-12-08T00:00:00Z2020DecemberTuesday 546 5.67765631Covid
    6222020-12-09T00:00:00Z2020DecemberWednesday15715.28662424Covid
    6232020-12-10T00:00:00Z2020DecemberThursday 13522.96296331Covid
    6242020-12-11T00:00:00Z2020DecemberFriday 16717.96407230Covid
    6252020-12-12T00:00:00Z2020DecemberSaturday 25011.20000028Covid
    6262020-12-13T00:00:00Z2020DecemberSunday 13716.78832123Covid
    6272020-12-14T00:00:00Z2020DecemberMonday 12023.33333328Covid
    6282020-12-15T00:00:00Z2020DecemberTuesday 12624.60317531Covid
    6292020-12-16T00:00:00Z2020DecemberWednesday24217.76859543Covid
    6302020-12-17T00:00:00Z2020DecemberThursday 16822.61904838Covid
    6312020-12-18T00:00:00Z2020DecemberFriday 13813.04347818Covid
    6322020-12-19T00:00:00Z2020DecemberSaturday 263 9.12547524Covid
    6332020-12-20T00:00:00Z2020DecemberSunday 258 9.68992225Covid
    6342020-12-21T00:00:00Z2020DecemberMonday 13013.07692317Covid
    6352020-12-22T00:00:00Z2020DecemberTuesday 13613.23529418Covid
    6362020-12-23T00:00:00Z2020DecemberWednesday12016.66666720Covid
    6372020-12-24T00:00:00Z2020DecemberThursday 10726.16822428Covid
    6382020-12-25T00:00:00Z2020DecemberFriday 550 3.81818221Covid
    6392020-12-26T00:00:00Z2020DecemberSaturday 14912.75167819Covid
    6402020-12-27T00:00:00Z2020DecemberSunday 14114.89361721Covid
    6412020-12-28T00:00:00Z2020DecemberMonday 11622.41379326Covid
    6422020-12-29T00:00:00Z2020DecemberTuesday 11426.31578930Covid
    6432020-12-30T00:00:00Z2020DecemberWednesday12518.40000023Covid
    6442020-12-31T00:00:00Z2020DecemberThursday 15621.79487234Covid

    2021 

    joins.2021
leaves.2021
sources.2021
comm.2021

    A data.frame: 85 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    6452021-01-01T00:00:00Z2021JanuaryFriday 520.00000 40.00000Covid
    6462021-01-02T00:00:00Z2021JanuarySaturday 2 0.00000100.00000Covid
    6472021-01-03T00:00:00Z2021JanuarySunday 2 0.00000 50.00000Covid
    6482021-01-04T00:00:00Z2021JanuaryMonday 0 NA NACovid
    6492021-01-05T00:00:00Z2021JanuaryTuesday 2 0.00000 50.00000Covid
    6502021-01-06T00:00:00Z2021JanuaryWednesday 1 0.00000100.00000Covid
    6512021-01-07T00:00:00Z2021JanuaryThursday 250.00000 50.00000Covid
    6522021-01-08T00:00:00Z2021JanuaryFriday 1631.25000 68.75000Covid
    6532021-01-09T00:00:00Z2021JanuarySaturday 3 0.00000 0.00000Covid
    6542021-01-10T00:00:00Z2021JanuarySunday 333.33333 66.66667Covid
    6552021-01-11T00:00:00Z2021JanuaryMonday 2 0.00000 50.00000Covid
    6562021-01-12T00:00:00Z2021JanuaryTuesday 2 0.00000 50.00000Covid
    6572021-01-13T00:00:00Z2021JanuaryWednesday 4 0.00000 75.00000Covid
    6582021-01-14T00:00:00Z2021JanuaryThursday 1 0.00000100.00000Covid
    6592021-01-15T00:00:00Z2021JanuaryFriday 580.00000100.00000Covid
    6602021-01-16T00:00:00Z2021JanuarySaturday 2 0.00000 50.00000Covid
    6612021-01-17T00:00:00Z2021JanuarySunday 2 0.00000100.00000Covid
    6622021-01-18T00:00:00Z2021JanuaryMonday 366.66667100.00000Covid
    6632021-01-19T00:00:00Z2021JanuaryTuesday 1 0.00000 0.00000Covid
    6642021-01-20T00:00:00Z2021JanuaryWednesday 250.00000 50.00000Covid
    6652021-01-21T00:00:00Z2021JanuaryThursday 8 0.00000 25.00000Covid
    6662021-01-22T00:00:00Z2021JanuaryFriday 1 0.00000100.00000Covid
    6672021-01-23T00:00:00Z2021JanuarySaturday 1 0.00000100.00000Covid
    6682021-01-24T00:00:00Z2021JanuarySunday 4 0.00000 75.00000Covid
    6692021-01-25T00:00:00Z2021JanuaryMonday 1421.42857 57.14286Covid
    6702021-01-26T00:00:00Z2021JanuaryTuesday 2 0.00000 50.00000Covid
    6712021-01-27T00:00:00Z2021JanuaryWednesday 633.33333 83.33333Covid
    6722021-01-28T00:00:00Z2021JanuaryThursday 5 0.00000 20.00000Covid
    6732021-01-29T00:00:00Z2021JanuaryFriday 616.66667 66.66667Covid
    6742021-01-30T00:00:00Z2021JanuarySaturday 250.00000100.00000Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    7002021-02-25T00:00:00Z2021FebruaryThursday 1 0.00000100.00000Covid
    7012021-02-26T00:00:00Z2021FebruaryFriday 540.00000100.00000Covid
    7022021-02-27T00:00:00Z2021FebruarySaturday 812.50000100.00000Covid
    7032021-02-28T00:00:00Z2021FebruarySunday 520.00000100.00000Covid
    7042021-03-01T00:00:00Z2021March Monday 2 0.00000 50.00000Covid
    7052021-03-02T00:00:00Z2021March Tuesday 616.66667 16.66667Covid
    7062021-03-03T00:00:00Z2021March Wednesday 5 0.00000 40.00000Covid
    7072021-03-04T00:00:00Z2021March Thursday 8 0.00000 62.50000Covid
    7082021-03-05T00:00:00Z2021March Friday 333.33333 33.33333Covid
    7092021-03-06T00:00:00Z2021March Saturday 3 0.00000 66.66667Covid
    7102021-03-07T00:00:00Z2021March Sunday 3 0.00000 33.33333Covid
    7112021-03-08T00:00:00Z2021March Monday 714.28571 42.85714Covid
    7122021-03-09T00:00:00Z2021March Tuesday 7 0.00000 57.14286Covid
    7132021-03-10T00:00:00Z2021March Wednesday 5 0.00000 40.00000Covid
    7142021-03-11T00:00:00Z2021March Thursday 1 0.00000100.00000Covid
    7152021-03-12T00:00:00Z2021March Friday 1118.18182 45.45455Covid
    7162021-03-13T00:00:00Z2021March Saturday 4 0.00000 50.00000Covid
    7172021-03-14T00:00:00Z2021March Sunday 1 0.00000 0.00000Covid
    7182021-03-15T00:00:00Z2021March Monday 1 0.00000 0.00000Covid
    7192021-03-16T00:00:00Z2021March Tuesday 6 0.00000 83.33333Covid
    7202021-03-17T00:00:00Z2021March Wednesday 7 0.00000 71.42857Covid
    7212021-03-18T00:00:00Z2021March Thursday 1 0.00000 0.00000Covid
    7222021-03-19T00:00:00Z2021March Friday 5 0.00000 80.00000Covid
    7232021-03-20T00:00:00Z2021March Saturday 2 0.00000 0.00000Covid
    7242021-03-21T00:00:00Z2021March Sunday 633.33333 33.33333Covid
    7252021-03-22T00:00:00Z2021March Monday 520.00000 60.00000Covid
    7262021-03-23T00:00:00Z2021March Tuesday 1 0.00000 0.00000Covid
    7272021-03-24T00:00:00Z2021March Wednesday 4 0.00000 50.00000Covid
    7282021-03-25T00:00:00Z2021March Thursday 1 0.00000 0.00000Covid
    7292021-03-26T00:00:00Z2021March Friday 4 NA NACovid
    A data.frame: 135 × 7
    interval_start_timestampyearmonthdaydays_in_guildleaversyear_type
    <chr><fct><fct><fct><fct><int><fct>
    9702021-01-01T00:00:00Z2021JanuaryFriday 'Members for 1 month+' 4Covid
    9712021-01-01T00:00:00Z2021January<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'2Covid
    9722021-01-02T00:00:00Z2021JanuarySaturday 'Members for 1 month+' 2Covid
    9732021-01-02T00:00:00Z2021JanuarySaturday 'Members for < 1 month'2Covid
    9742021-01-03T00:00:00Z2021JanuarySunday 'Members for 1 month+' 1Covid
    9752021-01-03T00:00:00Z2021January<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Covid
    9762021-01-04T00:00:00Z2021JanuaryMonday 'Members for 1 month+' 2Covid
    9772021-01-05T00:00:00Z2021JanuaryTuesday 'Members for 1 month+' 4Covid
    9782021-01-06T00:00:00Z2021JanuaryWednesday'Members for 1 month+' 2Covid
    9792021-01-07T00:00:00Z2021JanuaryThursday 'Members for 1 month+' 4Covid
    9802021-01-07T00:00:00Z2021JanuaryThursday 'Members for < 1 month'1Covid
    9812021-01-08T00:00:00Z2021JanuaryFriday 'Members for 1 month+' 5Covid
    9822021-01-08T00:00:00Z2021January<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'3Covid
    9832021-01-09T00:00:00Z2021JanuarySaturday 'Members for 1 month+' 2Covid
    9842021-01-09T00:00:00Z2021JanuarySaturday 'Members for < 1 month'2Covid
    9852021-01-10T00:00:00Z2021JanuarySunday 'Members for 1 month+' 1Covid
    9862021-01-11T00:00:00Z2021JanuaryMonday 'Members for 1 month+' 2Covid
    9872021-01-12T00:00:00Z2021JanuaryTuesday 'Members for 1 month+' 1Covid
    9882021-01-13T00:00:00Z2021JanuaryWednesday'Members for 1 month+' 3Covid
    9892021-01-13T00:00:00Z2021JanuaryWednesday'Members for < 1 month'1Covid
    9902021-01-14T00:00:00Z2021JanuaryThursday 'Members for 1 month+' 2Covid
    9912021-01-15T00:00:00Z2021JanuaryFriday 'Members for 1 month+' 2Covid
    9922021-01-16T00:00:00Z2021JanuarySaturday 'Members for 1 month+' 4Covid
    9932021-01-17T00:00:00Z2021JanuarySunday 'Members for 1 month+' 0Covid
    9942021-01-18T00:00:00Z2021January<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Covid
    9952021-01-19T00:00:00Z2021JanuaryTuesday 'Members for 1 month+' 3Covid
    9962021-01-19T00:00:00Z2021January<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    9972021-01-20T00:00:00Z2021JanuaryWednesday'Members for 1 month+' 3Covid
    9982021-01-20T00:00:00Z2021JanuaryWednesday'Members for < 1 month'1Covid
    9992021-01-21T00:00:00Z2021JanuaryThursday 'Members for 1 month+' 1Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮
    10752021-03-09T00:00:00Z2021MarchTuesday 'Members for 1 month+' 2Covid
    10762021-03-09T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    10772021-03-10T00:00:00Z2021MarchWednesday'Members for 1 month+' 2Covid
    10782021-03-10T00:00:00Z2021MarchWednesday'Members for < 1 month'3Covid
    10792021-03-11T00:00:00Z2021MarchThursday 'Members for 1 month+' 2Covid
    10802021-03-12T00:00:00Z2021MarchFriday 'Members for 1 month+' 1Covid
    10812021-03-12T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'5Covid
    10822021-03-13T00:00:00Z2021MarchSaturday 'Members for < 1 month'1Covid
    10832021-03-14T00:00:00Z2021MarchSunday 'Members for 1 month+' 1Covid
    10842021-03-14T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Covid
    10852021-03-15T00:00:00Z2021MarchMonday 'Members for 1 month+' 2Covid
    10862021-03-16T00:00:00Z2021MarchTuesday 'Members for 1 month+' 1Covid
    10872021-03-16T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'3Covid
    10882021-03-17T00:00:00Z2021MarchWednesday'Members for 1 month+' 4Covid
    10892021-03-17T00:00:00Z2021MarchWednesday'Members for < 1 month'2Covid
    10902021-03-18T00:00:00Z2021MarchThursday 'Members for < 1 month'1Covid
    10912021-03-19T00:00:00Z2021MarchFriday 'Members for 1 month+' 2Covid
    10922021-03-19T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'2Covid
    10932021-03-20T00:00:00Z2021MarchSaturday 'Members for 1 month+' 5Covid
    10942021-03-20T00:00:00Z2021MarchSaturday 'Members for < 1 month'1Covid
    10952021-03-21T00:00:00Z2021MarchSunday 'Members for 1 month+' 1Covid
    10962021-03-21T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'3Covid
    10972021-03-22T00:00:00Z2021MarchMonday 'Members for 1 month+' 1Covid
    10982021-03-23T00:00:00Z2021MarchTuesday 'Members for 1 month+' 3Covid
    10992021-03-23T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    11002021-03-24T00:00:00Z2021MarchWednesday'Members for 1 month+' 0Covid
    11012021-03-25T00:00:00Z2021MarchThursday 'Members for 1 month+' 2Covid
    11022021-03-25T00:00:00Z2021MarchThursday 'Members for < 1 month'1Covid
    11032021-03-26T00:00:00Z2021MarchFriday 'Members for 1 month+' 3Covid
    11042021-03-26T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1Covid
    A data.frame: 85 × 8
    interval_start_timestampyearmonthdaydiscovery_joinsinvitesvanity_joinsyear_type
    <chr><fct><fct><fct><int><int><int><fct>
    6452021-01-01T00:00:00Z2021JanuaryFriday 00 6Covid
    6462021-01-02T00:00:00Z2021JanuarySaturday 00 2Covid
    6472021-01-03T00:00:00Z2021JanuarySunday 10 1Covid
    6482021-01-04T00:00:00Z2021JanuaryMonday 00 0Covid
    6492021-01-05T00:00:00Z2021JanuaryTuesday 00 2Covid
    6502021-01-06T00:00:00Z2021JanuaryWednesday00 1Covid
    6512021-01-07T00:00:00Z2021JanuaryThursday 00 2Covid
    6522021-01-08T00:00:00Z2021JanuaryFriday 0016Covid
    6532021-01-09T00:00:00Z2021JanuarySaturday 00 4Covid
    6542021-01-10T00:00:00Z2021JanuarySunday 00 3Covid
    6552021-01-11T00:00:00Z2021JanuaryMonday 00 2Covid
    6562021-01-12T00:00:00Z2021JanuaryTuesday 00 2Covid
    6572021-01-13T00:00:00Z2021JanuaryWednesday00 4Covid
    6582021-01-14T00:00:00Z2021JanuaryThursday 00 1Covid
    6592021-01-15T00:00:00Z2021JanuaryFriday 00 5Covid
    6602021-01-16T00:00:00Z2021JanuarySaturday 00 2Covid
    6612021-01-17T00:00:00Z2021JanuarySunday 00 3Covid
    6622021-01-18T00:00:00Z2021JanuaryMonday 00 3Covid
    6632021-01-19T00:00:00Z2021JanuaryTuesday 00 2Covid
    6642021-01-20T00:00:00Z2021JanuaryWednesday00 2Covid
    6652021-01-21T00:00:00Z2021JanuaryThursday 00 9Covid
    6662021-01-22T00:00:00Z2021JanuaryFriday 00 1Covid
    6672021-01-23T00:00:00Z2021JanuarySaturday 00 4Covid
    6682021-01-24T00:00:00Z2021JanuarySunday 00 4Covid
    6692021-01-25T00:00:00Z2021JanuaryMonday 0014Covid
    6702021-01-26T00:00:00Z2021JanuaryTuesday 00 5Covid
    6712021-01-27T00:00:00Z2021JanuaryWednesday00 6Covid
    6722021-01-28T00:00:00Z2021JanuaryThursday 00 5Covid
    6732021-01-29T00:00:00Z2021JanuaryFriday 10 5Covid
    6742021-01-30T00:00:00Z2021JanuarySaturday 00 2Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    7002021-02-25T00:00:00Z2021FebruaryThursday 00 1Covid
    7012021-02-26T00:00:00Z2021FebruaryFriday 00 6Covid
    7022021-02-27T00:00:00Z2021FebruarySaturday 00 9Covid
    7032021-02-28T00:00:00Z2021FebruarySunday 00 5Covid
    7042021-03-01T00:00:00Z2021March Monday 00 3Covid
    7052021-03-02T00:00:00Z2021March Tuesday 00 6Covid
    7062021-03-03T00:00:00Z2021March Wednesday00 5Covid
    7072021-03-04T00:00:00Z2021March Thursday 00 8Covid
    7082021-03-05T00:00:00Z2021March Friday 00 4Covid
    7092021-03-06T00:00:00Z2021March Saturday 00 3Covid
    7102021-03-07T00:00:00Z2021March Sunday 00 4Covid
    7112021-03-08T00:00:00Z2021March Monday 00 7Covid
    7122021-03-09T00:00:00Z2021March Tuesday 10 6Covid
    7132021-03-10T00:00:00Z2021March Wednesday00 5Covid
    7142021-03-11T00:00:00Z2021March Thursday 00 2Covid
    7152021-03-12T00:00:00Z2021March Friday 0011Covid
    7162021-03-13T00:00:00Z2021March Saturday 10 3Covid
    7172021-03-14T00:00:00Z2021March Sunday 00 1Covid
    7182021-03-15T00:00:00Z2021March Monday 00 2Covid
    7192021-03-16T00:00:00Z2021March Tuesday 10 6Covid
    7202021-03-17T00:00:00Z2021March Wednesday10 9Covid
    7212021-03-18T00:00:00Z2021March Thursday 00 1Covid
    7222021-03-19T00:00:00Z2021March Friday 10 4Covid
    7232021-03-20T00:00:00Z2021March Saturday 00 2Covid
    7242021-03-21T00:00:00Z2021March Sunday 00 7Covid
    7252021-03-22T00:00:00Z2021March Monday 00 6Covid
    7262021-03-23T00:00:00Z2021March Tuesday 00 1Covid
    7272021-03-24T00:00:00Z2021March Wednesday00 5Covid
    7282021-03-25T00:00:00Z2021March Thursday 00 2Covid
    7292021-03-26T00:00:00Z2021March Friday 00 4Covid
    A data.frame: 85 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    6452021-01-01T00:00:00Z2021JanuaryFriday 312 9.29487229Covid
    6462021-01-02T00:00:00Z2021JanuarySaturday 17417.24137930Covid
    6472021-01-03T00:00:00Z2021JanuarySunday 13218.93939425Covid
    6482021-01-04T00:00:00Z2021JanuaryMonday 11221.42857124Covid
    6492021-01-05T00:00:00Z2021JanuaryTuesday 14412.50000018Covid
    6502021-01-06T00:00:00Z2021JanuaryWednesday368 7.06521726Covid
    6512021-01-07T00:00:00Z2021JanuaryThursday 31513.01587341Covid
    6522021-01-08T00:00:00Z2021JanuaryFriday 27416.78832146Covid
    6532021-01-09T00:00:00Z2021JanuarySaturday 24810.48387126Covid
    6542021-01-10T00:00:00Z2021JanuarySunday 14918.79194628Covid
    6552021-01-11T00:00:00Z2021JanuaryMonday 22516.88888938Covid
    6562021-01-12T00:00:00Z2021JanuaryTuesday 15017.33333326Covid
    6572021-01-13T00:00:00Z2021JanuaryWednesday15218.42105328Covid
    6582021-01-14T00:00:00Z2021JanuaryThursday 14415.27777822Covid
    6592021-01-15T00:00:00Z2021JanuaryFriday 14827.02702740Covid
    6602021-01-16T00:00:00Z2021JanuarySaturday 12319.51219524Covid
    6612021-01-17T00:00:00Z2021JanuarySunday 12913.17829517Covid
    6622021-01-18T00:00:00Z2021JanuaryMonday 13623.52941232Covid
    6632021-01-19T00:00:00Z2021JanuaryTuesday 13320.30075227Covid
    6642021-01-20T00:00:00Z2021JanuaryWednesday13619.85294127Covid
    6652021-01-21T00:00:00Z2021JanuaryThursday 12723.62204730Covid
    6662021-01-22T00:00:00Z2021JanuaryFriday 19219.27083337Covid
    6672021-01-23T00:00:00Z2021JanuarySaturday 13919.42446027Covid
    6682021-01-24T00:00:00Z2021JanuarySunday 15315.68627524Covid
    6692021-01-25T00:00:00Z2021JanuaryMonday 27615.21739142Covid
    6702021-01-26T00:00:00Z2021JanuaryTuesday 18419.02173935Covid
    6712021-01-27T00:00:00Z2021JanuaryWednesday18224.72527545Covid
    6722021-01-28T00:00:00Z2021JanuaryThursday 605 6.28099238Covid
    6732021-01-29T00:00:00Z2021JanuaryFriday 26113.40996235Covid
    6742021-01-30T00:00:00Z2021JanuarySaturday 20120.39801041Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    7002021-02-25T00:00:00Z2021FebruaryThursday 17223.25581440Covid
    7012021-02-26T00:00:00Z2021FebruaryFriday 16719.16167732Covid
    7022021-02-27T00:00:00Z2021FebruarySaturday 20820.67307743Covid
    7032021-02-28T00:00:00Z2021FebruarySunday 16717.96407230Covid
    7042021-03-01T00:00:00Z2021March Monday 16418.29268330Covid
    7052021-03-02T00:00:00Z2021March Tuesday 19915.07537730Covid
    7062021-03-03T00:00:00Z2021March Wednesday16318.40490830Covid
    7072021-03-04T00:00:00Z2021March Thursday 16320.85889634Covid
    7082021-03-05T00:00:00Z2021March Friday 17917.31843631Covid
    7092021-03-06T00:00:00Z2021March Saturday 304 9.53947429Covid
    7102021-03-07T00:00:00Z2021March Sunday 16215.43209925Covid
    7112021-03-08T00:00:00Z2021March Monday 23413.67521432Covid
    7122021-03-09T00:00:00Z2021March Tuesday 16023.12500037Covid
    7132021-03-10T00:00:00Z2021March Wednesday15620.51282132Covid
    7142021-03-11T00:00:00Z2021March Thursday 553 7.23327340Covid
    7152021-03-12T00:00:00Z2021March Friday 25314.62450637Covid
    7162021-03-13T00:00:00Z2021March Saturday 23714.34599234Covid
    7172021-03-14T00:00:00Z2021March Sunday 14720.40816330Covid
    7182021-03-15T00:00:00Z2021March Monday 15418.83116929Covid
    7192021-03-16T00:00:00Z2021March Tuesday 15421.42857133Covid
    7202021-03-17T00:00:00Z2021March Wednesday14121.98581631Covid
    7212021-03-18T00:00:00Z2021March Thursday 15320.26143831Covid
    7222021-03-19T00:00:00Z2021March Friday 26819.40298552Covid
    7232021-03-20T00:00:00Z2021March Saturday 658 6.38297942Covid
    7242021-03-21T00:00:00Z2021March Sunday 17023.52941240Covid
    7252021-03-22T00:00:00Z2021March Monday 17422.41379339Covid
    7262021-03-23T00:00:00Z2021March Tuesday 14316.78321724Covid
    7272021-03-24T00:00:00Z2021March Wednesday15717.19745227Covid
    7282021-03-25T00:00:00Z2021March Thursday 16525.45454542Covid
    7292021-03-26T00:00:00Z2021March Friday 573 6.10820235Covid

    Aggregating by month

    2019 

    head(joins.2019)
head(leaves.2019)
head(comm.2019)

agg_joins.2019 = aggregate(joins.2019$new_members, list(joins.2019$month), sum)
colnames(agg_joins.2019) <- c("Months", "Total New Members")
agg_leaves.2019 = aggregate(leaves.2019$leavers, list(leaves.2019$month), sum)
colnames(agg_leaves.2019) <- c("Months", "Total Leavers")
agg_comm.2019 = aggregate(comm.2019$total_communicated, list(comm.2019$month), sum)
colnames(agg_comm.2019) <- c("Months", "Total Communicated")
    A data.frame: 6 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 250.00000 50.00000Normal
    22019-03-30T00:00:00Z2019MarchSaturday 616.66667 33.33333Normal
    32019-03-31T00:00:00Z2019MarchSunday 825.00000 37.50000Normal
    42019-04-01T00:00:00Z2019AprilMonday 944.44444 33.33333Normal
    52019-04-02T00:00:00Z2019AprilTuesday 250.00000100.00000Normal
    62019-04-03T00:00:00Z2019AprilWednesday0 NA NANormal
    A data.frame: 6 × 7
    interval_start_timestampyearmonthdaydays_in_guildleaversyear_type
    <chr><fct><fct><fct><fct><int><fct>
    12019-03-29T00:00:00Z2019MarchFriday 'Members for 1 month+' 1Normal
    22019-03-30T00:00:00Z2019MarchSaturday'Members for 1 month+' 1Normal
    32019-03-30T00:00:00Z2019MarchSaturday'Members for < 1 month'1Normal
    42019-03-31T00:00:00Z2019MarchSunday 'Members for 1 month+' 2Normal
    52019-03-31T00:00:00Z2019March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Normal
    62019-04-01T00:00:00Z2019AprilMonday 'Members for 1 month+' 4Normal
    A data.frame: 6 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 20625.7281653Normal
    22019-03-30T00:00:00Z2019MarchSaturday 18420.6521738Normal
    32019-03-31T00:00:00Z2019MarchSunday 18524.3243245Normal
    42019-04-01T00:00:00Z2019AprilMonday 32822.8658575Normal
    52019-04-02T00:00:00Z2019AprilTuesday 14333.5664348Normal
    62019-04-03T00:00:00Z2019AprilWednesday27116.6051745Normal

    2020 

    joins.2020
leaves.2020
comm.2020

agg_joins.2020 = aggregate(joins.2020$new_members, list(joins.2020$month), sum)
colnames(agg_joins.2020) <- c("Months", "Total New Members")
agg_leaves.2020 = aggregate(leaves.2020$leavers, list(leaves.2020$month), sum)
colnames(agg_leaves.2020) <- c("Months", "Total Leavers")
agg_comm.2020 = aggregate(comm.2020$total_communicated, list(comm.2020$month), sum)
colnames(agg_comm.2020) <- c("Months", "Total Communicated")

    A data.frame: 366 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    2792020-01-01T00:00:00Z2020JanuaryWednesday 0 NA NACovid
    2802020-01-02T00:00:00Z2020JanuaryThursday 1 0.00000100.00000Covid
    2812020-01-03T00:00:00Z2020JanuaryFriday 2 0.00000 50.00000Covid
    2822020-01-04T00:00:00Z2020JanuarySaturday 0 NA NACovid
    2832020-01-05T00:00:00Z2020JanuarySunday 0 NA NACovid
    2842020-01-06T00:00:00Z2020JanuaryMonday 3 0.00000 0.00000Covid
    2852020-01-07T00:00:00Z2020JanuaryTuesday 1 0.00000100.00000Covid
    2862020-01-08T00:00:00Z2020JanuaryWednesday 2 0.00000 50.00000Covid
    2872020-01-09T00:00:00Z2020JanuaryThursday 3 33.33333 33.33333Covid
    2882020-01-10T00:00:00Z2020JanuaryFriday 2 0.00000 0.00000Covid
    2892020-01-11T00:00:00Z2020JanuarySaturday 0 NA NACovid
    2902020-01-12T00:00:00Z2020JanuarySunday 2 0.00000100.00000Covid
    2912020-01-13T00:00:00Z2020JanuaryMonday 2100.00000100.00000Covid
    2922020-01-14T00:00:00Z2020JanuaryTuesday 7 14.28571 57.14286Covid
    2932020-01-15T00:00:00Z2020JanuaryWednesday 4 0.00000 25.00000Covid
    2942020-01-16T00:00:00Z2020JanuaryThursday 3 33.33333100.00000Covid
    2952020-01-17T00:00:00Z2020JanuaryFriday 1 0.00000 0.00000Covid
    2962020-01-18T00:00:00Z2020JanuarySaturday 3 0.00000100.00000Covid
    2972020-01-19T00:00:00Z2020JanuarySunday 2 0.00000 50.00000Covid
    2982020-01-20T00:00:00Z2020JanuaryMonday 2 50.00000100.00000Covid
    2992020-01-21T00:00:00Z2020JanuaryTuesday 4 25.00000 75.00000Covid
    3002020-01-22T00:00:00Z2020JanuaryWednesday 3 0.00000 0.00000Covid
    3012020-01-23T00:00:00Z2020JanuaryThursday 19 15.78947 21.05263Covid
    3022020-01-24T00:00:00Z2020JanuaryFriday 0 NA NACovid
    3032020-01-25T00:00:00Z2020JanuarySaturday 3 33.33333 33.33333Covid
    3042020-01-26T00:00:00Z2020JanuarySunday 3 0.00000100.00000Covid
    3052020-01-27T00:00:00Z2020JanuaryMonday 3 0.00000 66.66667Covid
    3062020-01-28T00:00:00Z2020JanuaryTuesday 2 0.00000100.00000Covid
    3072020-01-29T00:00:00Z2020JanuaryWednesday 5 40.00000 80.00000Covid
    3082020-01-30T00:00:00Z2020JanuaryThursday 1 0.00000100.00000Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    6152020-12-02T00:00:00Z2020DecemberWednesday250.00000100.00000Covid
    6162020-12-03T00:00:00Z2020DecemberThursday 2 0.00000 50.00000Covid
    6172020-12-04T00:00:00Z2020DecemberFriday 540.00000 80.00000Covid
    6182020-12-05T00:00:00Z2020DecemberSaturday 425.00000 25.00000Covid
    6192020-12-06T00:00:00Z2020DecemberSunday 3 0.00000 0.00000Covid
    6202020-12-07T00:00:00Z2020DecemberMonday 1 0.00000100.00000Covid
    6212020-12-08T00:00:00Z2020DecemberTuesday 1 0.00000100.00000Covid
    6222020-12-09T00:00:00Z2020DecemberWednesday1 0.00000 0.00000Covid
    6232020-12-10T00:00:00Z2020DecemberThursday 1 0.00000100.00000Covid
    6242020-12-11T00:00:00Z2020DecemberFriday 1 0.00000100.00000Covid
    6252020-12-12T00:00:00Z2020DecemberSaturday 3 0.00000 66.66667Covid
    6262020-12-13T00:00:00Z2020DecemberSunday 5 0.00000 20.00000Covid
    6272020-12-14T00:00:00Z2020DecemberMonday 3 0.00000 66.66667Covid
    6282020-12-15T00:00:00Z2020DecemberTuesday 250.00000100.00000Covid
    6292020-12-16T00:00:00Z2020DecemberWednesday450.00000 75.00000Covid
    6302020-12-17T00:00:00Z2020DecemberThursday 0 NA NACovid
    6312020-12-18T00:00:00Z2020DecemberFriday 250.00000 50.00000Covid
    6322020-12-19T00:00:00Z2020DecemberSaturday 0 NA NACovid
    6332020-12-20T00:00:00Z2020DecemberSunday 911.11111 55.55556Covid
    6342020-12-21T00:00:00Z2020DecemberMonday 250.00000 50.00000Covid
    6352020-12-22T00:00:00Z2020DecemberTuesday 3 0.00000 33.33333Covid
    6362020-12-23T00:00:00Z2020DecemberWednesday0 NA NACovid
    6372020-12-24T00:00:00Z2020DecemberThursday 0 NA NACovid
    6382020-12-25T00:00:00Z2020DecemberFriday 2 0.00000 0.00000Covid
    6392020-12-26T00:00:00Z2020DecemberSaturday 333.33333100.00000Covid
    6402020-12-27T00:00:00Z2020DecemberSunday 0 NA NACovid
    6412020-12-28T00:00:00Z2020DecemberMonday 1 0.00000 0.00000Covid
    6422020-12-29T00:00:00Z2020DecemberTuesday 3 0.00000 33.33333Covid
    6432020-12-30T00:00:00Z2020DecemberWednesday1 0.00000 0.00000Covid
    6442020-12-31T00:00:00Z2020DecemberThursday 3 0.00000 33.33333Covid
    A data.frame: 568 × 7
    interval_start_timestampyearmonthdaydays_in_guildleaversyear_type
    <chr><fct><fct><fct><fct><int><fct>
    4022020-01-01T00:00:00Z2020JanuaryWednesday'Members for 1 month+' 0Covid
    4032020-01-02T00:00:00Z2020JanuaryThursday 'Members for 1 month+' 0Covid
    4042020-01-03T00:00:00Z2020JanuaryFriday 'Members for 1 month+' 2Covid
    4052020-01-03T00:00:00Z2020January<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1Covid
    4062020-01-04T00:00:00Z2020JanuarySaturday 'Members for 1 month+' 2Covid
    4072020-01-04T00:00:00Z2020JanuarySaturday 'Members for < 1 month'1Covid
    4082020-01-05T00:00:00Z2020JanuarySunday 'Members for 1 month+' 1Covid
    4092020-01-06T00:00:00Z2020January<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Covid
    4102020-01-07T00:00:00Z2020JanuaryTuesday 'Members for 1 month+' 3Covid
    4112020-01-08T00:00:00Z2020JanuaryWednesday'Members for 1 month+' 1Covid
    4122020-01-08T00:00:00Z2020JanuaryWednesday'Members for < 1 month'1Covid
    4132020-01-09T00:00:00Z2020JanuaryThursday 'Members for 1 month+' 2Covid
    4142020-01-09T00:00:00Z2020JanuaryThursday 'Members for < 1 month'1Covid
    4152020-01-10T00:00:00Z2020JanuaryFriday 'Members for 1 month+' 2Covid
    4162020-01-11T00:00:00Z2020JanuarySaturday 'Members for 1 month+' 0Covid
    4172020-01-12T00:00:00Z2020JanuarySunday 'Members for 1 month+' 2Covid
    4182020-01-13T00:00:00Z2020JanuaryMonday 'Members for 1 month+' 4Covid
    4192020-01-14T00:00:00Z2020JanuaryTuesday 'Members for 1 month+' 3Covid
    4202020-01-14T00:00:00Z2020January<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    4212020-01-15T00:00:00Z2020JanuaryWednesday'Members for < 1 month'1Covid
    4222020-01-16T00:00:00Z2020JanuaryThursday 'Members for 1 month+' 3Covid
    4232020-01-16T00:00:00Z2020JanuaryThursday 'Members for < 1 month'1Covid
    4242020-01-17T00:00:00Z2020JanuaryFriday 'Members for 1 month+' 2Covid
    4252020-01-17T00:00:00Z2020January<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1Covid
    4262020-01-18T00:00:00Z2020JanuarySaturday 'Members for 1 month+' 2Covid
    4272020-01-19T00:00:00Z2020JanuarySunday 'Members for 1 month+' 2Covid
    4282020-01-20T00:00:00Z2020JanuaryMonday 'Members for 1 month+' 0Covid
    4292020-01-21T00:00:00Z2020JanuaryTuesday 'Members for 1 month+' 7Covid
    4302020-01-22T00:00:00Z2020JanuaryWednesday'Members for 1 month+' 3Covid
    4312020-01-23T00:00:00Z2020JanuaryThursday 'Members for 1 month+' 1Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮
    9402020-12-11T00:00:00Z2020December<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1Covid
    9412020-12-12T00:00:00Z2020DecemberSaturday 'Members for 1 month+' 1Covid
    9422020-12-12T00:00:00Z2020DecemberSaturday 'Members for < 1 month'1Covid
    9432020-12-13T00:00:00Z2020December<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'2Covid
    9442020-12-14T00:00:00Z2020DecemberMonday 'Members for 1 month+' 2Covid
    9452020-12-14T00:00:00Z2020December<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Covid
    9462020-12-15T00:00:00Z2020DecemberTuesday 'Members for 1 month+' 0Covid
    9472020-12-16T00:00:00Z2020DecemberWednesday'Members for 1 month+' 1Covid
    9482020-12-16T00:00:00Z2020DecemberWednesday'Members for < 1 month'1Covid
    9492020-12-17T00:00:00Z2020DecemberThursday 'Members for 1 month+' 2Covid
    9502020-12-18T00:00:00Z2020DecemberFriday 'Members for 1 month+' 0Covid
    9512020-12-19T00:00:00Z2020DecemberSaturday 'Members for 1 month+' 2Covid
    9522020-12-19T00:00:00Z2020DecemberSaturday 'Members for < 1 month'1Covid
    9532020-12-20T00:00:00Z2020DecemberSunday 'Members for 1 month+' 7Covid
    9542020-12-20T00:00:00Z2020December<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'2Covid
    9552020-12-21T00:00:00Z2020DecemberMonday 'Members for 1 month+' 1Covid
    9562020-12-22T00:00:00Z2020DecemberTuesday 'Members for 1 month+' 1Covid
    9572020-12-22T00:00:00Z2020December<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    9582020-12-23T00:00:00Z2020DecemberWednesday'Members for 1 month+' 3Covid
    9592020-12-24T00:00:00Z2020DecemberThursday 'Members for 1 month+' 0Covid
    9602020-12-25T00:00:00Z2020DecemberFriday 'Members for 1 month+' 7Covid
    9612020-12-25T00:00:00Z2020December<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'2Covid
    9622020-12-26T00:00:00Z2020DecemberSaturday 'Members for 1 month+' 1Covid
    9632020-12-26T00:00:00Z2020DecemberSaturday 'Members for < 1 month'1Covid
    9642020-12-27T00:00:00Z2020DecemberSunday 'Members for 1 month+' 4Covid
    9652020-12-28T00:00:00Z2020DecemberMonday 'Members for 1 month+' 2Covid
    9662020-12-29T00:00:00Z2020DecemberTuesday 'Members for 1 month+' 3Covid
    9672020-12-29T00:00:00Z2020December<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    9682020-12-30T00:00:00Z2020DecemberWednesday'Members for 1 month+' 4Covid
    9692020-12-31T00:00:00Z2020DecemberThursday 'Members for 1 month+' 2Covid
    A data.frame: 366 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    2792020-01-01T00:00:00Z2020JanuaryWednesday10625.47169827Covid
    2802020-01-02T00:00:00Z2020JanuaryThursday 10522.85714324Covid
    2812020-01-03T00:00:00Z2020JanuaryFriday 10425.00000026Covid
    2822020-01-04T00:00:00Z2020JanuarySaturday 10326.21359227Covid
    2832020-01-05T00:00:00Z2020JanuarySunday 9323.65591422Covid
    2842020-01-06T00:00:00Z2020JanuaryMonday 10217.64705918Covid
    2852020-01-07T00:00:00Z2020JanuaryTuesday 10126.73267327Covid
    2862020-01-08T00:00:00Z2020JanuaryWednesday10926.60550529Covid
    2872020-01-09T00:00:00Z2020JanuaryThursday 11024.54545527Covid
    2882020-01-10T00:00:00Z2020JanuaryFriday 10119.80198020Covid
    2892020-01-11T00:00:00Z2020JanuarySaturday 9627.08333326Covid
    2902020-01-12T00:00:00Z2020JanuarySunday 12127.27272733Covid
    2912020-01-13T00:00:00Z2020JanuaryMonday 11422.80701826Covid
    2922020-01-14T00:00:00Z2020JanuaryTuesday 11229.46428633Covid
    2932020-01-15T00:00:00Z2020JanuaryWednesday11729.05982934Covid
    2942020-01-16T00:00:00Z2020JanuaryThursday 13435.82089648Covid
    2952020-01-17T00:00:00Z2020JanuaryFriday 12428.22580635Covid
    2962020-01-18T00:00:00Z2020JanuarySaturday 392 7.14285728Covid
    2972020-01-19T00:00:00Z2020JanuarySunday 391 5.88235323Covid
    2982020-01-20T00:00:00Z2020JanuaryMonday 17121.05263236Covid
    2992020-01-21T00:00:00Z2020JanuaryTuesday 433 8.77598238Covid
    3002020-01-22T00:00:00Z2020JanuaryWednesday24218.59504145Covid
    3012020-01-23T00:00:00Z2020JanuaryThursday 19229.16666756Covid
    3022020-01-24T00:00:00Z2020JanuaryFriday 24820.56451651Covid
    3032020-01-25T00:00:00Z2020JanuarySaturday 41014.39024459Covid
    3042020-01-26T00:00:00Z2020JanuarySunday 19114.65968628Covid
    3052020-01-27T00:00:00Z2020JanuaryMonday 15425.32467539Covid
    3062020-01-28T00:00:00Z2020JanuaryTuesday 16625.90361443Covid
    3072020-01-29T00:00:00Z2020JanuaryWednesday50512.87128765Covid
    3082020-01-30T00:00:00Z2020JanuaryThursday 44410.36036046Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    6152020-12-02T00:00:00Z2020DecemberWednesday15916.98113227Covid
    6162020-12-03T00:00:00Z2020DecemberThursday 26614.28571438Covid
    6172020-12-04T00:00:00Z2020DecemberFriday 19321.76165842Covid
    6182020-12-05T00:00:00Z2020DecemberSaturday 15726.11465041Covid
    6192020-12-06T00:00:00Z2020DecemberSunday 15118.54304628Covid
    6202020-12-07T00:00:00Z2020DecemberMonday 15018.00000027Covid
    6212020-12-08T00:00:00Z2020DecemberTuesday 546 5.67765631Covid
    6222020-12-09T00:00:00Z2020DecemberWednesday15715.28662424Covid
    6232020-12-10T00:00:00Z2020DecemberThursday 13522.96296331Covid
    6242020-12-11T00:00:00Z2020DecemberFriday 16717.96407230Covid
    6252020-12-12T00:00:00Z2020DecemberSaturday 25011.20000028Covid
    6262020-12-13T00:00:00Z2020DecemberSunday 13716.78832123Covid
    6272020-12-14T00:00:00Z2020DecemberMonday 12023.33333328Covid
    6282020-12-15T00:00:00Z2020DecemberTuesday 12624.60317531Covid
    6292020-12-16T00:00:00Z2020DecemberWednesday24217.76859543Covid
    6302020-12-17T00:00:00Z2020DecemberThursday 16822.61904838Covid
    6312020-12-18T00:00:00Z2020DecemberFriday 13813.04347818Covid
    6322020-12-19T00:00:00Z2020DecemberSaturday 263 9.12547524Covid
    6332020-12-20T00:00:00Z2020DecemberSunday 258 9.68992225Covid
    6342020-12-21T00:00:00Z2020DecemberMonday 13013.07692317Covid
    6352020-12-22T00:00:00Z2020DecemberTuesday 13613.23529418Covid
    6362020-12-23T00:00:00Z2020DecemberWednesday12016.66666720Covid
    6372020-12-24T00:00:00Z2020DecemberThursday 10726.16822428Covid
    6382020-12-25T00:00:00Z2020DecemberFriday 550 3.81818221Covid
    6392020-12-26T00:00:00Z2020DecemberSaturday 14912.75167819Covid
    6402020-12-27T00:00:00Z2020DecemberSunday 14114.89361721Covid
    6412020-12-28T00:00:00Z2020DecemberMonday 11622.41379326Covid
    6422020-12-29T00:00:00Z2020DecemberTuesday 11426.31578930Covid
    6432020-12-30T00:00:00Z2020DecemberWednesday12518.40000023Covid
    6442020-12-31T00:00:00Z2020DecemberThursday 15621.79487234Covid

    2021 

    joins.2021
leaves.2021
comm.2021

agg_joins.2021 = aggregate(joins.2021$new_members, list(joins.2021$month), sum)
colnames(agg_joins.2021) <- c("Months", "Total New Members")
agg_leaves.2021 = aggregate(leaves.2021$leavers, list(leaves.2021$month), sum)
colnames(agg_leaves.2021) <- c("Months", "Total Leavers")
agg_comm.2021 = aggregate(comm.2021$total_communicated, list(comm.2021$month), sum)
colnames(agg_comm.2021) <- c("Months", "Total Communicated")

    A data.frame: 85 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    6452021-01-01T00:00:00Z2021JanuaryFriday 520.00000 40.00000Covid
    6462021-01-02T00:00:00Z2021JanuarySaturday 2 0.00000100.00000Covid
    6472021-01-03T00:00:00Z2021JanuarySunday 2 0.00000 50.00000Covid
    6482021-01-04T00:00:00Z2021JanuaryMonday 0 NA NACovid
    6492021-01-05T00:00:00Z2021JanuaryTuesday 2 0.00000 50.00000Covid
    6502021-01-06T00:00:00Z2021JanuaryWednesday 1 0.00000100.00000Covid
    6512021-01-07T00:00:00Z2021JanuaryThursday 250.00000 50.00000Covid
    6522021-01-08T00:00:00Z2021JanuaryFriday 1631.25000 68.75000Covid
    6532021-01-09T00:00:00Z2021JanuarySaturday 3 0.00000 0.00000Covid
    6542021-01-10T00:00:00Z2021JanuarySunday 333.33333 66.66667Covid
    6552021-01-11T00:00:00Z2021JanuaryMonday 2 0.00000 50.00000Covid
    6562021-01-12T00:00:00Z2021JanuaryTuesday 2 0.00000 50.00000Covid
    6572021-01-13T00:00:00Z2021JanuaryWednesday 4 0.00000 75.00000Covid
    6582021-01-14T00:00:00Z2021JanuaryThursday 1 0.00000100.00000Covid
    6592021-01-15T00:00:00Z2021JanuaryFriday 580.00000100.00000Covid
    6602021-01-16T00:00:00Z2021JanuarySaturday 2 0.00000 50.00000Covid
    6612021-01-17T00:00:00Z2021JanuarySunday 2 0.00000100.00000Covid
    6622021-01-18T00:00:00Z2021JanuaryMonday 366.66667100.00000Covid
    6632021-01-19T00:00:00Z2021JanuaryTuesday 1 0.00000 0.00000Covid
    6642021-01-20T00:00:00Z2021JanuaryWednesday 250.00000 50.00000Covid
    6652021-01-21T00:00:00Z2021JanuaryThursday 8 0.00000 25.00000Covid
    6662021-01-22T00:00:00Z2021JanuaryFriday 1 0.00000100.00000Covid
    6672021-01-23T00:00:00Z2021JanuarySaturday 1 0.00000100.00000Covid
    6682021-01-24T00:00:00Z2021JanuarySunday 4 0.00000 75.00000Covid
    6692021-01-25T00:00:00Z2021JanuaryMonday 1421.42857 57.14286Covid
    6702021-01-26T00:00:00Z2021JanuaryTuesday 2 0.00000 50.00000Covid
    6712021-01-27T00:00:00Z2021JanuaryWednesday 633.33333 83.33333Covid
    6722021-01-28T00:00:00Z2021JanuaryThursday 5 0.00000 20.00000Covid
    6732021-01-29T00:00:00Z2021JanuaryFriday 616.66667 66.66667Covid
    6742021-01-30T00:00:00Z2021JanuarySaturday 250.00000100.00000Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    7002021-02-25T00:00:00Z2021FebruaryThursday 1 0.00000100.00000Covid
    7012021-02-26T00:00:00Z2021FebruaryFriday 540.00000100.00000Covid
    7022021-02-27T00:00:00Z2021FebruarySaturday 812.50000100.00000Covid
    7032021-02-28T00:00:00Z2021FebruarySunday 520.00000100.00000Covid
    7042021-03-01T00:00:00Z2021March Monday 2 0.00000 50.00000Covid
    7052021-03-02T00:00:00Z2021March Tuesday 616.66667 16.66667Covid
    7062021-03-03T00:00:00Z2021March Wednesday 5 0.00000 40.00000Covid
    7072021-03-04T00:00:00Z2021March Thursday 8 0.00000 62.50000Covid
    7082021-03-05T00:00:00Z2021March Friday 333.33333 33.33333Covid
    7092021-03-06T00:00:00Z2021March Saturday 3 0.00000 66.66667Covid
    7102021-03-07T00:00:00Z2021March Sunday 3 0.00000 33.33333Covid
    7112021-03-08T00:00:00Z2021March Monday 714.28571 42.85714Covid
    7122021-03-09T00:00:00Z2021March Tuesday 7 0.00000 57.14286Covid
    7132021-03-10T00:00:00Z2021March Wednesday 5 0.00000 40.00000Covid
    7142021-03-11T00:00:00Z2021March Thursday 1 0.00000100.00000Covid
    7152021-03-12T00:00:00Z2021March Friday 1118.18182 45.45455Covid
    7162021-03-13T00:00:00Z2021March Saturday 4 0.00000 50.00000Covid
    7172021-03-14T00:00:00Z2021March Sunday 1 0.00000 0.00000Covid
    7182021-03-15T00:00:00Z2021March Monday 1 0.00000 0.00000Covid
    7192021-03-16T00:00:00Z2021March Tuesday 6 0.00000 83.33333Covid
    7202021-03-17T00:00:00Z2021March Wednesday 7 0.00000 71.42857Covid
    7212021-03-18T00:00:00Z2021March Thursday 1 0.00000 0.00000Covid
    7222021-03-19T00:00:00Z2021March Friday 5 0.00000 80.00000Covid
    7232021-03-20T00:00:00Z2021March Saturday 2 0.00000 0.00000Covid
    7242021-03-21T00:00:00Z2021March Sunday 633.33333 33.33333Covid
    7252021-03-22T00:00:00Z2021March Monday 520.00000 60.00000Covid
    7262021-03-23T00:00:00Z2021March Tuesday 1 0.00000 0.00000Covid
    7272021-03-24T00:00:00Z2021March Wednesday 4 0.00000 50.00000Covid
    7282021-03-25T00:00:00Z2021March Thursday 1 0.00000 0.00000Covid
    7292021-03-26T00:00:00Z2021March Friday 4 NA NACovid
    A data.frame: 135 × 7
    interval_start_timestampyearmonthdaydays_in_guildleaversyear_type
    <chr><fct><fct><fct><fct><int><fct>
    9702021-01-01T00:00:00Z2021JanuaryFriday 'Members for 1 month+' 4Covid
    9712021-01-01T00:00:00Z2021January<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'2Covid
    9722021-01-02T00:00:00Z2021JanuarySaturday 'Members for 1 month+' 2Covid
    9732021-01-02T00:00:00Z2021JanuarySaturday 'Members for < 1 month'2Covid
    9742021-01-03T00:00:00Z2021JanuarySunday 'Members for 1 month+' 1Covid
    9752021-01-03T00:00:00Z2021January<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Covid
    9762021-01-04T00:00:00Z2021JanuaryMonday 'Members for 1 month+' 2Covid
    9772021-01-05T00:00:00Z2021JanuaryTuesday 'Members for 1 month+' 4Covid
    9782021-01-06T00:00:00Z2021JanuaryWednesday'Members for 1 month+' 2Covid
    9792021-01-07T00:00:00Z2021JanuaryThursday 'Members for 1 month+' 4Covid
    9802021-01-07T00:00:00Z2021JanuaryThursday 'Members for < 1 month'1Covid
    9812021-01-08T00:00:00Z2021JanuaryFriday 'Members for 1 month+' 5Covid
    9822021-01-08T00:00:00Z2021January<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'3Covid
    9832021-01-09T00:00:00Z2021JanuarySaturday 'Members for 1 month+' 2Covid
    9842021-01-09T00:00:00Z2021JanuarySaturday 'Members for < 1 month'2Covid
    9852021-01-10T00:00:00Z2021JanuarySunday 'Members for 1 month+' 1Covid
    9862021-01-11T00:00:00Z2021JanuaryMonday 'Members for 1 month+' 2Covid
    9872021-01-12T00:00:00Z2021JanuaryTuesday 'Members for 1 month+' 1Covid
    9882021-01-13T00:00:00Z2021JanuaryWednesday'Members for 1 month+' 3Covid
    9892021-01-13T00:00:00Z2021JanuaryWednesday'Members for < 1 month'1Covid
    9902021-01-14T00:00:00Z2021JanuaryThursday 'Members for 1 month+' 2Covid
    9912021-01-15T00:00:00Z2021JanuaryFriday 'Members for 1 month+' 2Covid
    9922021-01-16T00:00:00Z2021JanuarySaturday 'Members for 1 month+' 4Covid
    9932021-01-17T00:00:00Z2021JanuarySunday 'Members for 1 month+' 0Covid
    9942021-01-18T00:00:00Z2021January<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Covid
    9952021-01-19T00:00:00Z2021JanuaryTuesday 'Members for 1 month+' 3Covid
    9962021-01-19T00:00:00Z2021January<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    9972021-01-20T00:00:00Z2021JanuaryWednesday'Members for 1 month+' 3Covid
    9982021-01-20T00:00:00Z2021JanuaryWednesday'Members for < 1 month'1Covid
    9992021-01-21T00:00:00Z2021JanuaryThursday 'Members for 1 month+' 1Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮
    10752021-03-09T00:00:00Z2021MarchTuesday 'Members for 1 month+' 2Covid
    10762021-03-09T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    10772021-03-10T00:00:00Z2021MarchWednesday'Members for 1 month+' 2Covid
    10782021-03-10T00:00:00Z2021MarchWednesday'Members for < 1 month'3Covid
    10792021-03-11T00:00:00Z2021MarchThursday 'Members for 1 month+' 2Covid
    10802021-03-12T00:00:00Z2021MarchFriday 'Members for 1 month+' 1Covid
    10812021-03-12T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'5Covid
    10822021-03-13T00:00:00Z2021MarchSaturday 'Members for < 1 month'1Covid
    10832021-03-14T00:00:00Z2021MarchSunday 'Members for 1 month+' 1Covid
    10842021-03-14T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Covid
    10852021-03-15T00:00:00Z2021MarchMonday 'Members for 1 month+' 2Covid
    10862021-03-16T00:00:00Z2021MarchTuesday 'Members for 1 month+' 1Covid
    10872021-03-16T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'3Covid
    10882021-03-17T00:00:00Z2021MarchWednesday'Members for 1 month+' 4Covid
    10892021-03-17T00:00:00Z2021MarchWednesday'Members for < 1 month'2Covid
    10902021-03-18T00:00:00Z2021MarchThursday 'Members for < 1 month'1Covid
    10912021-03-19T00:00:00Z2021MarchFriday 'Members for 1 month+' 2Covid
    10922021-03-19T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'2Covid
    10932021-03-20T00:00:00Z2021MarchSaturday 'Members for 1 month+' 5Covid
    10942021-03-20T00:00:00Z2021MarchSaturday 'Members for < 1 month'1Covid
    10952021-03-21T00:00:00Z2021MarchSunday 'Members for 1 month+' 1Covid
    10962021-03-21T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'3Covid
    10972021-03-22T00:00:00Z2021MarchMonday 'Members for 1 month+' 1Covid
    10982021-03-23T00:00:00Z2021MarchTuesday 'Members for 1 month+' 3Covid
    10992021-03-23T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    11002021-03-24T00:00:00Z2021MarchWednesday'Members for 1 month+' 0Covid
    11012021-03-25T00:00:00Z2021MarchThursday 'Members for 1 month+' 2Covid
    11022021-03-25T00:00:00Z2021MarchThursday 'Members for < 1 month'1Covid
    11032021-03-26T00:00:00Z2021MarchFriday 'Members for 1 month+' 3Covid
    11042021-03-26T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1Covid
    A data.frame: 85 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    6452021-01-01T00:00:00Z2021JanuaryFriday 312 9.29487229Covid
    6462021-01-02T00:00:00Z2021JanuarySaturday 17417.24137930Covid
    6472021-01-03T00:00:00Z2021JanuarySunday 13218.93939425Covid
    6482021-01-04T00:00:00Z2021JanuaryMonday 11221.42857124Covid
    6492021-01-05T00:00:00Z2021JanuaryTuesday 14412.50000018Covid
    6502021-01-06T00:00:00Z2021JanuaryWednesday368 7.06521726Covid
    6512021-01-07T00:00:00Z2021JanuaryThursday 31513.01587341Covid
    6522021-01-08T00:00:00Z2021JanuaryFriday 27416.78832146Covid
    6532021-01-09T00:00:00Z2021JanuarySaturday 24810.48387126Covid
    6542021-01-10T00:00:00Z2021JanuarySunday 14918.79194628Covid
    6552021-01-11T00:00:00Z2021JanuaryMonday 22516.88888938Covid
    6562021-01-12T00:00:00Z2021JanuaryTuesday 15017.33333326Covid
    6572021-01-13T00:00:00Z2021JanuaryWednesday15218.42105328Covid
    6582021-01-14T00:00:00Z2021JanuaryThursday 14415.27777822Covid
    6592021-01-15T00:00:00Z2021JanuaryFriday 14827.02702740Covid
    6602021-01-16T00:00:00Z2021JanuarySaturday 12319.51219524Covid
    6612021-01-17T00:00:00Z2021JanuarySunday 12913.17829517Covid
    6622021-01-18T00:00:00Z2021JanuaryMonday 13623.52941232Covid
    6632021-01-19T00:00:00Z2021JanuaryTuesday 13320.30075227Covid
    6642021-01-20T00:00:00Z2021JanuaryWednesday13619.85294127Covid
    6652021-01-21T00:00:00Z2021JanuaryThursday 12723.62204730Covid
    6662021-01-22T00:00:00Z2021JanuaryFriday 19219.27083337Covid
    6672021-01-23T00:00:00Z2021JanuarySaturday 13919.42446027Covid
    6682021-01-24T00:00:00Z2021JanuarySunday 15315.68627524Covid
    6692021-01-25T00:00:00Z2021JanuaryMonday 27615.21739142Covid
    6702021-01-26T00:00:00Z2021JanuaryTuesday 18419.02173935Covid
    6712021-01-27T00:00:00Z2021JanuaryWednesday18224.72527545Covid
    6722021-01-28T00:00:00Z2021JanuaryThursday 605 6.28099238Covid
    6732021-01-29T00:00:00Z2021JanuaryFriday 26113.40996235Covid
    6742021-01-30T00:00:00Z2021JanuarySaturday 20120.39801041Covid
    ⋮⋮⋮⋮⋮⋮⋮⋮⋮
    7002021-02-25T00:00:00Z2021FebruaryThursday 17223.25581440Covid
    7012021-02-26T00:00:00Z2021FebruaryFriday 16719.16167732Covid
    7022021-02-27T00:00:00Z2021FebruarySaturday 20820.67307743Covid
    7032021-02-28T00:00:00Z2021FebruarySunday 16717.96407230Covid
    7042021-03-01T00:00:00Z2021March Monday 16418.29268330Covid
    7052021-03-02T00:00:00Z2021March Tuesday 19915.07537730Covid
    7062021-03-03T00:00:00Z2021March Wednesday16318.40490830Covid
    7072021-03-04T00:00:00Z2021March Thursday 16320.85889634Covid
    7082021-03-05T00:00:00Z2021March Friday 17917.31843631Covid
    7092021-03-06T00:00:00Z2021March Saturday 304 9.53947429Covid
    7102021-03-07T00:00:00Z2021March Sunday 16215.43209925Covid
    7112021-03-08T00:00:00Z2021March Monday 23413.67521432Covid
    7122021-03-09T00:00:00Z2021March Tuesday 16023.12500037Covid
    7132021-03-10T00:00:00Z2021March Wednesday15620.51282132Covid
    7142021-03-11T00:00:00Z2021March Thursday 553 7.23327340Covid
    7152021-03-12T00:00:00Z2021March Friday 25314.62450637Covid
    7162021-03-13T00:00:00Z2021March Saturday 23714.34599234Covid
    7172021-03-14T00:00:00Z2021March Sunday 14720.40816330Covid
    7182021-03-15T00:00:00Z2021March Monday 15418.83116929Covid
    7192021-03-16T00:00:00Z2021March Tuesday 15421.42857133Covid
    7202021-03-17T00:00:00Z2021March Wednesday14121.98581631Covid
    7212021-03-18T00:00:00Z2021March Thursday 15320.26143831Covid
    7222021-03-19T00:00:00Z2021March Friday 26819.40298552Covid
    7232021-03-20T00:00:00Z2021March Saturday 658 6.38297942Covid
    7242021-03-21T00:00:00Z2021March Sunday 17023.52941240Covid
    7252021-03-22T00:00:00Z2021March Monday 17422.41379339Covid
    7262021-03-23T00:00:00Z2021March Tuesday 14316.78321724Covid
    7272021-03-24T00:00:00Z2021March Wednesday15717.19745227Covid
    7282021-03-25T00:00:00Z2021March Thursday 16525.45454542Covid
    7292021-03-26T00:00:00Z2021March Friday 573 6.10820235Covid

    Testing aggregations

    This section includes my initial tests for data aggregation. In the next section I learned a easier to read method to aggregate multiple variables.

    communicators
median_comm = aggregate(communicators$visitors, list(communicators$month), sum)
median_comm[order(median_comm$x),]

    A data.frame: 729 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    2019-03-29T00:00:00Z2019MarchFriday 20625.7281653Normal
    2019-03-30T00:00:00Z2019MarchSaturday 18420.6521738Normal
    2019-03-31T00:00:00Z2019MarchSunday 18524.3243245Normal
    2019-04-01T00:00:00Z2019AprilMonday 32822.8658575Normal
    2019-04-02T00:00:00Z2019AprilTuesday 14333.5664348Normal
    2019-04-03T00:00:00Z2019AprilWednesday27116.6051745Normal
    2019-04-04T00:00:00Z2019AprilThursday 38113.3858351Normal
    2019-04-05T00:00:00Z2019AprilFriday 19024.7368447Normal
    2019-04-06T00:00:00Z2019AprilSaturday 16326.9938744Normal
    2019-04-07T00:00:00Z2019AprilSunday 15931.4465450Normal
    2019-04-08T00:00:00Z2019AprilMonday 16325.7668742Normal
    2019-04-09T00:00:00Z2019AprilTuesday 14831.0810846Normal
    2019-04-10T00:00:00Z2019AprilWednesday16330.6748550Normal
    2019-04-11T00:00:00Z2019AprilThursday 13938.1295053Normal
    2019-04-12T00:00:00Z2019AprilFriday 15529.6774246Normal
    2019-04-13T00:00:00Z2019AprilSaturday 14330.0699343Normal
    2019-04-14T00:00:00Z2019AprilSunday 14028.5714340Normal
    2019-04-15T00:00:00Z2019AprilMonday 17029.4117650Normal
    2019-04-16T00:00:00Z2019AprilTuesday 15040.6666761Normal
    2019-04-17T00:00:00Z2019AprilWednesday15334.6405253Normal
    2019-04-18T00:00:00Z2019AprilThursday 16743.7125773Normal
    2019-04-19T00:00:00Z2019AprilFriday 16233.9506255Normal
    2019-04-20T00:00:00Z2019AprilSaturday 33715.1335351Normal
    2019-04-21T00:00:00Z2019AprilSunday 17225.0000043Normal
    2019-04-22T00:00:00Z2019AprilMonday 16224.0740739Normal
    2019-04-23T00:00:00Z2019AprilTuesday 16335.5828258Normal
    2019-04-24T00:00:00Z2019AprilWednesday34015.2941252Normal
    2019-04-25T00:00:00Z2019AprilThursday 19626.5306152Normal
    2019-04-26T00:00:00Z2019AprilFriday 37116.9811363Normal
    2019-04-27T00:00:00Z2019AprilSaturday 20127.8607056Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 17223.25581440Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 16719.16167732Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 20820.67307743Covid
    2021-02-28T00:00:00Z2021FebruarySunday 16717.96407230Covid
    2021-03-01T00:00:00Z2021March Monday 16418.29268330Covid
    2021-03-02T00:00:00Z2021March Tuesday 19915.07537730Covid
    2021-03-03T00:00:00Z2021March Wednesday16318.40490830Covid
    2021-03-04T00:00:00Z2021March Thursday 16320.85889634Covid
    2021-03-05T00:00:00Z2021March Friday 17917.31843631Covid
    2021-03-06T00:00:00Z2021March Saturday 304 9.53947429Covid
    2021-03-07T00:00:00Z2021March Sunday 16215.43209925Covid
    2021-03-08T00:00:00Z2021March Monday 23413.67521432Covid
    2021-03-09T00:00:00Z2021March Tuesday 16023.12500037Covid
    2021-03-10T00:00:00Z2021March Wednesday15620.51282132Covid
    2021-03-11T00:00:00Z2021March Thursday 553 7.23327340Covid
    2021-03-12T00:00:00Z2021March Friday 25314.62450637Covid
    2021-03-13T00:00:00Z2021March Saturday 23714.34599234Covid
    2021-03-14T00:00:00Z2021March Sunday 14720.40816330Covid
    2021-03-15T00:00:00Z2021March Monday 15418.83116929Covid
    2021-03-16T00:00:00Z2021March Tuesday 15421.42857133Covid
    2021-03-17T00:00:00Z2021March Wednesday14121.98581631Covid
    2021-03-18T00:00:00Z2021March Thursday 15320.26143831Covid
    2021-03-19T00:00:00Z2021March Friday 26819.40298552Covid
    2021-03-20T00:00:00Z2021March Saturday 658 6.38297942Covid
    2021-03-21T00:00:00Z2021March Sunday 17023.52941240Covid
    2021-03-22T00:00:00Z2021March Monday 17422.41379339Covid
    2021-03-23T00:00:00Z2021March Tuesday 14316.78321724Covid
    2021-03-24T00:00:00Z2021March Wednesday15717.19745227Covid
    2021-03-25T00:00:00Z2021March Thursday 16525.45454542Covid
    2021-03-26T00:00:00Z2021March Friday 573 6.10820235Covid
    A data.frame: 12 × 2
    Group.1x
    <fct><int>
    6June 10342
    5May 10814
    4April 11595
    12December 11671
    1January 12220
    7July 12230
    2February 12236
    3March 12848
    8August 15664
    11November 16734
    10October 17617
    9September22230

    Aggregating by category

    As mentioned in the subsetting by year section, upon reading some examples for aggregating in R, I found that there was a method to aggregate by multiple columns. The following article "Aggregate in R" was particularly helpful as it had sample code with useful outputs. The second option of using R linear model notation is a bit more intuitive than the first suggestion.

    aggregate(df_2$weight, by = list(df_2$feed, df_2$cat_var), FUN = sum)
# Equivalent to:
aggregate(weight ~ feed + cat_var, data = df_2, FUN = sum)

    Joins 

    head(joins)
agg_joins = aggregate(new_members ~ month + year, data = joins, FUN = sum)
head(agg_joins)
    A data.frame: 6 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 250.00000 50.00000Normal
    22019-03-30T00:00:00Z2019MarchSaturday 616.66667 33.33333Normal
    32019-03-31T00:00:00Z2019MarchSunday 825.00000 37.50000Normal
    42019-04-01T00:00:00Z2019AprilMonday 944.44444 33.33333Normal
    52019-04-02T00:00:00Z2019AprilTuesday 250.00000100.00000Normal
    62019-04-03T00:00:00Z2019AprilWednesday0 NA NANormal
    A data.frame: 6 × 3
    monthyearnew_members
    <fct><fct><int>
    1March 2019 16
    2April 2019 69
    3May 2019 54
    4June 2019 54
    5July 2019 37
    6August2019256

    Leaves 

    leaves
agg_leaves = aggregate(leavers ~ month + year, data = leaves, FUN = sum)
agg_leaves

    A data.frame: 1104 × 7
    interval_start_timestampyearmonthdaydays_in_guildleaversyear_type
    <chr><fct><fct><fct><fct><int><fct>
    2019-03-29T00:00:00Z2019MarchFriday 'Members for 1 month+' 1Normal
    2019-03-30T00:00:00Z2019MarchSaturday 'Members for 1 month+' 1Normal
    2019-03-30T00:00:00Z2019MarchSaturday 'Members for < 1 month'1Normal
    2019-03-31T00:00:00Z2019MarchSunday 'Members for 1 month+' 2Normal
    2019-03-31T00:00:00Z2019March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Normal
    2019-04-01T00:00:00Z2019AprilMonday 'Members for 1 month+' 4Normal
    2019-04-02T00:00:00Z2019AprilTuesday 'Members for 1 month+' 1Normal
    2019-04-03T00:00:00Z2019AprilWednesday'Members for 1 month+' 2Normal
    2019-04-03T00:00:00Z2019AprilWednesday'Members for < 1 month'2Normal
    2019-04-04T00:00:00Z2019AprilThursday 'Members for 1 month+' 2Normal
    2019-04-04T00:00:00Z2019AprilThursday 'Members for < 1 month'2Normal
    2019-04-05T00:00:00Z2019AprilFriday 'Members for 1 month+' 3Normal
    2019-04-06T00:00:00Z2019AprilSaturday 'Members for 1 month+' 1Normal
    2019-04-06T00:00:00Z2019AprilSaturday 'Members for < 1 month'1Normal
    2019-04-07T00:00:00Z2019AprilSunday 'Members for 1 month+' 1Normal
    2019-04-07T00:00:00Z2019April<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'2Normal
    2019-04-08T00:00:00Z2019AprilMonday 'Members for 1 month+' 1Normal
    2019-04-08T00:00:00Z2019April<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Normal
    2019-04-09T00:00:00Z2019AprilTuesday 'Members for 1 month+' 1Normal
    2019-04-09T00:00:00Z2019April<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Normal
    2019-04-10T00:00:00Z2019AprilWednesday'Members for 1 month+' 2Normal
    2019-04-10T00:00:00Z2019AprilWednesday'Members for < 1 month'1Normal
    2019-04-11T00:00:00Z2019AprilThursday 'Members for 1 month+' 0Normal
    2019-04-12T00:00:00Z2019AprilFriday 'Members for 1 month+' 1Normal
    2019-04-13T00:00:00Z2019AprilSaturday 'Members for < 1 month'1Normal
    2019-04-14T00:00:00Z2019AprilSunday 'Members for 1 month+' 2Normal
    2019-04-15T00:00:00Z2019AprilMonday 'Members for 1 month+' 1Normal
    2019-04-15T00:00:00Z2019April<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Normal
    2019-04-16T00:00:00Z2019AprilTuesday 'Members for 1 month+' 3Normal
    2019-04-16T00:00:00Z2019April<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Normal
    ⋮⋮⋮⋮⋮⋮⋮
    2021-03-09T00:00:00Z2021MarchTuesday 'Members for 1 month+' 2Covid
    2021-03-09T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    2021-03-10T00:00:00Z2021MarchWednesday'Members for 1 month+' 2Covid
    2021-03-10T00:00:00Z2021MarchWednesday'Members for < 1 month'3Covid
    2021-03-11T00:00:00Z2021MarchThursday 'Members for 1 month+' 2Covid
    2021-03-12T00:00:00Z2021MarchFriday 'Members for 1 month+' 1Covid
    2021-03-12T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'5Covid
    2021-03-13T00:00:00Z2021MarchSaturday 'Members for < 1 month'1Covid
    2021-03-14T00:00:00Z2021MarchSunday 'Members for 1 month+' 1Covid
    2021-03-14T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Covid
    2021-03-15T00:00:00Z2021MarchMonday 'Members for 1 month+' 2Covid
    2021-03-16T00:00:00Z2021MarchTuesday 'Members for 1 month+' 1Covid
    2021-03-16T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'3Covid
    2021-03-17T00:00:00Z2021MarchWednesday'Members for 1 month+' 4Covid
    2021-03-17T00:00:00Z2021MarchWednesday'Members for < 1 month'2Covid
    2021-03-18T00:00:00Z2021MarchThursday 'Members for < 1 month'1Covid
    2021-03-19T00:00:00Z2021MarchFriday 'Members for 1 month+' 2Covid
    2021-03-19T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'2Covid
    2021-03-20T00:00:00Z2021MarchSaturday 'Members for 1 month+' 5Covid
    2021-03-20T00:00:00Z2021MarchSaturday 'Members for < 1 month'1Covid
    2021-03-21T00:00:00Z2021MarchSunday 'Members for 1 month+' 1Covid
    2021-03-21T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'3Covid
    2021-03-22T00:00:00Z2021MarchMonday 'Members for 1 month+' 1Covid
    2021-03-23T00:00:00Z2021MarchTuesday 'Members for 1 month+' 3Covid
    2021-03-23T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    2021-03-24T00:00:00Z2021MarchWednesday'Members for 1 month+' 0Covid
    2021-03-25T00:00:00Z2021MarchThursday 'Members for 1 month+' 2Covid
    2021-03-25T00:00:00Z2021MarchThursday 'Members for < 1 month'1Covid
    2021-03-26T00:00:00Z2021MarchFriday 'Members for 1 month+' 3Covid
    2021-03-26T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1Covid
    A data.frame: 25 × 3
    monthyearleavers
    <fct><fct><int>
    March 2019 6
    April 2019 75
    May 2019 54
    June 2019 45
    July 2019 47
    August 2019 66
    September2019 90
    October 2019 60
    November 2019118
    December 2019 43
    January 2020 66
    February 2020 82
    March 2020 73
    April 2020 95
    May 2020 72
    June 2020 82
    July 2020 90
    August 2020127
    September2020132
    October 2020100
    November 2020 91
    December 2020 83
    January 2021 93
    February 2021 88
    March 2021 78

    Experimental 3d agg

    I was curious to see what would happen if I were to add another dimension of days_in_guild. I ended up not using it as it would be hard to visualize with a chart.

    leaves
agg_leaves = aggregate(leavers ~ month + year + days_in_guild, data = leaves, FUN = sum)
agg_leaves

    A data.frame: 1104 × 7
    interval_start_timestampyearmonthdaydays_in_guildleaversyear_type
    <chr><fct><fct><fct><fct><int><fct>
    2019-03-29T00:00:00Z2019MarchFriday 'Members for 1 month+' 1Normal
    2019-03-30T00:00:00Z2019MarchSaturday 'Members for 1 month+' 1Normal
    2019-03-30T00:00:00Z2019MarchSaturday 'Members for < 1 month'1Normal
    2019-03-31T00:00:00Z2019MarchSunday 'Members for 1 month+' 2Normal
    2019-03-31T00:00:00Z2019March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Normal
    2019-04-01T00:00:00Z2019AprilMonday 'Members for 1 month+' 4Normal
    2019-04-02T00:00:00Z2019AprilTuesday 'Members for 1 month+' 1Normal
    2019-04-03T00:00:00Z2019AprilWednesday'Members for 1 month+' 2Normal
    2019-04-03T00:00:00Z2019AprilWednesday'Members for < 1 month'2Normal
    2019-04-04T00:00:00Z2019AprilThursday 'Members for 1 month+' 2Normal
    2019-04-04T00:00:00Z2019AprilThursday 'Members for < 1 month'2Normal
    2019-04-05T00:00:00Z2019AprilFriday 'Members for 1 month+' 3Normal
    2019-04-06T00:00:00Z2019AprilSaturday 'Members for 1 month+' 1Normal
    2019-04-06T00:00:00Z2019AprilSaturday 'Members for < 1 month'1Normal
    2019-04-07T00:00:00Z2019AprilSunday 'Members for 1 month+' 1Normal
    2019-04-07T00:00:00Z2019April<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'2Normal
    2019-04-08T00:00:00Z2019AprilMonday 'Members for 1 month+' 1Normal
    2019-04-08T00:00:00Z2019April<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Normal
    2019-04-09T00:00:00Z2019AprilTuesday 'Members for 1 month+' 1Normal
    2019-04-09T00:00:00Z2019April<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Normal
    2019-04-10T00:00:00Z2019AprilWednesday'Members for 1 month+' 2Normal
    2019-04-10T00:00:00Z2019AprilWednesday'Members for < 1 month'1Normal
    2019-04-11T00:00:00Z2019AprilThursday 'Members for 1 month+' 0Normal
    2019-04-12T00:00:00Z2019AprilFriday 'Members for 1 month+' 1Normal
    2019-04-13T00:00:00Z2019AprilSaturday 'Members for < 1 month'1Normal
    2019-04-14T00:00:00Z2019AprilSunday 'Members for 1 month+' 2Normal
    2019-04-15T00:00:00Z2019AprilMonday 'Members for 1 month+' 1Normal
    2019-04-15T00:00:00Z2019April<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Normal
    2019-04-16T00:00:00Z2019AprilTuesday 'Members for 1 month+' 3Normal
    2019-04-16T00:00:00Z2019April<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Normal
    ⋮⋮⋮⋮⋮⋮⋮
    2021-03-09T00:00:00Z2021MarchTuesday 'Members for 1 month+' 2Covid
    2021-03-09T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    2021-03-10T00:00:00Z2021MarchWednesday'Members for 1 month+' 2Covid
    2021-03-10T00:00:00Z2021MarchWednesday'Members for < 1 month'3Covid
    2021-03-11T00:00:00Z2021MarchThursday 'Members for 1 month+' 2Covid
    2021-03-12T00:00:00Z2021MarchFriday 'Members for 1 month+' 1Covid
    2021-03-12T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'5Covid
    2021-03-13T00:00:00Z2021MarchSaturday 'Members for < 1 month'1Covid
    2021-03-14T00:00:00Z2021MarchSunday 'Members for 1 month+' 1Covid
    2021-03-14T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Covid
    2021-03-15T00:00:00Z2021MarchMonday 'Members for 1 month+' 2Covid
    2021-03-16T00:00:00Z2021MarchTuesday 'Members for 1 month+' 1Covid
    2021-03-16T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'3Covid
    2021-03-17T00:00:00Z2021MarchWednesday'Members for 1 month+' 4Covid
    2021-03-17T00:00:00Z2021MarchWednesday'Members for < 1 month'2Covid
    2021-03-18T00:00:00Z2021MarchThursday 'Members for < 1 month'1Covid
    2021-03-19T00:00:00Z2021MarchFriday 'Members for 1 month+' 2Covid
    2021-03-19T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'2Covid
    2021-03-20T00:00:00Z2021MarchSaturday 'Members for 1 month+' 5Covid
    2021-03-20T00:00:00Z2021MarchSaturday 'Members for < 1 month'1Covid
    2021-03-21T00:00:00Z2021MarchSunday 'Members for 1 month+' 1Covid
    2021-03-21T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'3Covid
    2021-03-22T00:00:00Z2021MarchMonday 'Members for 1 month+' 1Covid
    2021-03-23T00:00:00Z2021MarchTuesday 'Members for 1 month+' 3Covid
    2021-03-23T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    2021-03-24T00:00:00Z2021MarchWednesday'Members for 1 month+' 0Covid
    2021-03-25T00:00:00Z2021MarchThursday 'Members for 1 month+' 2Covid
    2021-03-25T00:00:00Z2021MarchThursday 'Members for < 1 month'1Covid
    2021-03-26T00:00:00Z2021MarchFriday 'Members for 1 month+' 3Covid
    2021-03-26T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1Covid
    A data.frame: 50 × 4
    monthyeardays_in_guildleavers
    <fct><fct><fct><int>
    <span style=white-space:pre-wrap>March </span>2019'Members for < 1 month' 2
    <span style=white-space:pre-wrap>April </span>2019'Members for < 1 month'27
    <span style=white-space:pre-wrap>May </span>2019'Members for < 1 month'18
    <span style=white-space:pre-wrap>June </span>2019'Members for < 1 month'12
    <span style=white-space:pre-wrap>July </span>2019'Members for < 1 month'11
    <span style=white-space:pre-wrap>August </span>2019'Members for < 1 month'23
    September2019'Members for < 1 month'34
    <span style=white-space:pre-wrap>October </span>2019'Members for < 1 month'31
    November 2019'Members for < 1 month'65
    December 2019'Members for < 1 month' 7
    <span style=white-space:pre-wrap>January </span>2020'Members for < 1 month'17
    February 2020'Members for < 1 month'32
    <span style=white-space:pre-wrap>March </span>2020'Members for < 1 month'20
    <span style=white-space:pre-wrap>April </span>2020'Members for < 1 month'20
    <span style=white-space:pre-wrap>May </span>2020'Members for < 1 month'16
    <span style=white-space:pre-wrap>June </span>2020'Members for < 1 month'28
    <span style=white-space:pre-wrap>July </span>2020'Members for < 1 month'28
    <span style=white-space:pre-wrap>August </span>2020'Members for < 1 month'61
    September2020'Members for < 1 month'68
    <span style=white-space:pre-wrap>October </span>2020'Members for < 1 month'42
    November 2020'Members for < 1 month'35
    December 2020'Members for < 1 month'20
    <span style=white-space:pre-wrap>January </span>2021'Members for < 1 month'26
    February 2021'Members for < 1 month'40
    <span style=white-space:pre-wrap>March </span>2021'Members for < 1 month'32
    March 2019'Members for 1 month+' 4
    April 2019'Members for 1 month+' 48
    May 2019'Members for 1 month+' 36
    June 2019'Members for 1 month+' 33
    July 2019'Members for 1 month+' 36
    August 2019'Members for 1 month+' 43
    September2019'Members for 1 month+' 56
    October 2019'Members for 1 month+' 29
    November 2019'Members for 1 month+' 53
    December 2019'Members for 1 month+' 36
    January 2020'Members for 1 month+' 49
    February 2020'Members for 1 month+' 50
    March 2020'Members for 1 month+' 53
    April 2020'Members for 1 month+' 75
    May 2020'Members for 1 month+' 56
    June 2020'Members for 1 month+' 54
    July 2020'Members for 1 month+' 62
    August 2020'Members for 1 month+' 66
    September2020'Members for 1 month+' 64
    October 2020'Members for 1 month+' 58
    November 2020'Members for 1 month+' 56
    December 2020'Members for 1 month+' 63
    January 2021'Members for 1 month+' 67
    February 2021'Members for 1 month+' 48
    March 2021'Members for 1 month+' 46

    Sources

    I tried aggregating the various sources. Our group later realized we could get the same data from another file. So this ended up being unused.

    sources
agg_sources = aggregate(discovery_joins + invites + vanity_joins ~ month + year, data = sources, FUN = sum)
agg_sources

    A data.frame: 729 × 8
    interval_start_timestampyearmonthdaydiscovery_joinsinvitesvanity_joinsyear_type
    <chr><fct><fct><fct><int><int><int><fct>
    2019-03-29T00:00:00Z2019MarchFriday 00 3Normal
    2019-03-30T00:00:00Z2019MarchSaturday 00 7Normal
    2019-03-31T00:00:00Z2019MarchSunday 00 8Normal
    2019-04-01T00:00:00Z2019AprilMonday 0011Normal
    2019-04-02T00:00:00Z2019AprilTuesday 00 2Normal
    2019-04-03T00:00:00Z2019AprilWednesday00 1Normal
    2019-04-04T00:00:00Z2019AprilThursday 00 3Normal
    2019-04-05T00:00:00Z2019AprilFriday 00 4Normal
    2019-04-06T00:00:00Z2019AprilSaturday 00 3Normal
    2019-04-07T00:00:00Z2019AprilSunday 00 2Normal
    2019-04-08T00:00:00Z2019AprilMonday 00 9Normal
    2019-04-09T00:00:00Z2019AprilTuesday 00 3Normal
    2019-04-10T00:00:00Z2019AprilWednesday00 1Normal
    2019-04-11T00:00:00Z2019AprilThursday 00 2Normal
    2019-04-12T00:00:00Z2019AprilFriday 00 1Normal
    2019-04-13T00:00:00Z2019AprilSaturday 00 1Normal
    2019-04-14T00:00:00Z2019AprilSunday 00 0Normal
    2019-04-15T00:00:00Z2019AprilMonday 00 0Normal
    2019-04-16T00:00:00Z2019AprilTuesday 00 7Normal
    2019-04-17T00:00:00Z2019AprilWednesday00 5Normal
    2019-04-18T00:00:00Z2019AprilThursday 00 6Normal
    2019-04-19T00:00:00Z2019AprilFriday 00 3Normal
    2019-04-20T00:00:00Z2019AprilSaturday 00 2Normal
    2019-04-21T00:00:00Z2019AprilSunday 00 1Normal
    2019-04-22T00:00:00Z2019AprilMonday 00 1Normal
    2019-04-23T00:00:00Z2019AprilTuesday 00 3Normal
    2019-04-24T00:00:00Z2019AprilWednesday00 3Normal
    2019-04-25T00:00:00Z2019AprilThursday 00 3Normal
    2019-04-26T00:00:00Z2019AprilFriday 00 4Normal
    2019-04-27T00:00:00Z2019AprilSaturday 00 3Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 00 1Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 00 6Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 00 9Covid
    2021-02-28T00:00:00Z2021FebruarySunday 00 5Covid
    2021-03-01T00:00:00Z2021March Monday 00 3Covid
    2021-03-02T00:00:00Z2021March Tuesday 00 6Covid
    2021-03-03T00:00:00Z2021March Wednesday00 5Covid
    2021-03-04T00:00:00Z2021March Thursday 00 8Covid
    2021-03-05T00:00:00Z2021March Friday 00 4Covid
    2021-03-06T00:00:00Z2021March Saturday 00 3Covid
    2021-03-07T00:00:00Z2021March Sunday 00 4Covid
    2021-03-08T00:00:00Z2021March Monday 00 7Covid
    2021-03-09T00:00:00Z2021March Tuesday 10 6Covid
    2021-03-10T00:00:00Z2021March Wednesday00 5Covid
    2021-03-11T00:00:00Z2021March Thursday 00 2Covid
    2021-03-12T00:00:00Z2021March Friday 0011Covid
    2021-03-13T00:00:00Z2021March Saturday 10 3Covid
    2021-03-14T00:00:00Z2021March Sunday 00 1Covid
    2021-03-15T00:00:00Z2021March Monday 00 2Covid
    2021-03-16T00:00:00Z2021March Tuesday 10 6Covid
    2021-03-17T00:00:00Z2021March Wednesday10 9Covid
    2021-03-18T00:00:00Z2021March Thursday 00 1Covid
    2021-03-19T00:00:00Z2021March Friday 10 4Covid
    2021-03-20T00:00:00Z2021March Saturday 00 2Covid
    2021-03-21T00:00:00Z2021March Sunday 00 7Covid
    2021-03-22T00:00:00Z2021March Monday 00 6Covid
    2021-03-23T00:00:00Z2021March Tuesday 00 1Covid
    2021-03-24T00:00:00Z2021March Wednesday00 5Covid
    2021-03-25T00:00:00Z2021March Thursday 00 2Covid
    2021-03-26T00:00:00Z2021March Friday 00 4Covid
    A data.frame: 25 × 3
    monthyeardiscovery_joins + invites + vanity_joins
    <fct><fct><int>
    March 2019 18
    April 2019 92
    May 2019 64
    June 2019 58
    July 2019 46
    August 2019273
    September2019196
    October 2019119
    November 2019190
    December 2019 49
    January 2020106
    February 2020 79
    March 2020 74
    April 2020134
    May 2020 96
    June 2020 85
    July 2020125
    August 2020345
    September2020260
    October 2020214
    November 2020143
    December 2020 82
    January 2021126
    February 2021147
    March 2021122

    Communicators 

    communicators
agg_comms = aggregate(total_communicated ~ month + year, data = communicators, FUN = sum)
agg_comms

    A data.frame: 729 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    2019-03-29T00:00:00Z2019MarchFriday 20625.7281653Normal
    2019-03-30T00:00:00Z2019MarchSaturday 18420.6521738Normal
    2019-03-31T00:00:00Z2019MarchSunday 18524.3243245Normal
    2019-04-01T00:00:00Z2019AprilMonday 32822.8658575Normal
    2019-04-02T00:00:00Z2019AprilTuesday 14333.5664348Normal
    2019-04-03T00:00:00Z2019AprilWednesday27116.6051745Normal
    2019-04-04T00:00:00Z2019AprilThursday 38113.3858351Normal
    2019-04-05T00:00:00Z2019AprilFriday 19024.7368447Normal
    2019-04-06T00:00:00Z2019AprilSaturday 16326.9938744Normal
    2019-04-07T00:00:00Z2019AprilSunday 15931.4465450Normal
    2019-04-08T00:00:00Z2019AprilMonday 16325.7668742Normal
    2019-04-09T00:00:00Z2019AprilTuesday 14831.0810846Normal
    2019-04-10T00:00:00Z2019AprilWednesday16330.6748550Normal
    2019-04-11T00:00:00Z2019AprilThursday 13938.1295053Normal
    2019-04-12T00:00:00Z2019AprilFriday 15529.6774246Normal
    2019-04-13T00:00:00Z2019AprilSaturday 14330.0699343Normal
    2019-04-14T00:00:00Z2019AprilSunday 14028.5714340Normal
    2019-04-15T00:00:00Z2019AprilMonday 17029.4117650Normal
    2019-04-16T00:00:00Z2019AprilTuesday 15040.6666761Normal
    2019-04-17T00:00:00Z2019AprilWednesday15334.6405253Normal
    2019-04-18T00:00:00Z2019AprilThursday 16743.7125773Normal
    2019-04-19T00:00:00Z2019AprilFriday 16233.9506255Normal
    2019-04-20T00:00:00Z2019AprilSaturday 33715.1335351Normal
    2019-04-21T00:00:00Z2019AprilSunday 17225.0000043Normal
    2019-04-22T00:00:00Z2019AprilMonday 16224.0740739Normal
    2019-04-23T00:00:00Z2019AprilTuesday 16335.5828258Normal
    2019-04-24T00:00:00Z2019AprilWednesday34015.2941252Normal
    2019-04-25T00:00:00Z2019AprilThursday 19626.5306152Normal
    2019-04-26T00:00:00Z2019AprilFriday 37116.9811363Normal
    2019-04-27T00:00:00Z2019AprilSaturday 20127.8607056Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 17223.25581440Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 16719.16167732Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 20820.67307743Covid
    2021-02-28T00:00:00Z2021FebruarySunday 16717.96407230Covid
    2021-03-01T00:00:00Z2021March Monday 16418.29268330Covid
    2021-03-02T00:00:00Z2021March Tuesday 19915.07537730Covid
    2021-03-03T00:00:00Z2021March Wednesday16318.40490830Covid
    2021-03-04T00:00:00Z2021March Thursday 16320.85889634Covid
    2021-03-05T00:00:00Z2021March Friday 17917.31843631Covid
    2021-03-06T00:00:00Z2021March Saturday 304 9.53947429Covid
    2021-03-07T00:00:00Z2021March Sunday 16215.43209925Covid
    2021-03-08T00:00:00Z2021March Monday 23413.67521432Covid
    2021-03-09T00:00:00Z2021March Tuesday 16023.12500037Covid
    2021-03-10T00:00:00Z2021March Wednesday15620.51282132Covid
    2021-03-11T00:00:00Z2021March Thursday 553 7.23327340Covid
    2021-03-12T00:00:00Z2021March Friday 25314.62450637Covid
    2021-03-13T00:00:00Z2021March Saturday 23714.34599234Covid
    2021-03-14T00:00:00Z2021March Sunday 14720.40816330Covid
    2021-03-15T00:00:00Z2021March Monday 15418.83116929Covid
    2021-03-16T00:00:00Z2021March Tuesday 15421.42857133Covid
    2021-03-17T00:00:00Z2021March Wednesday14121.98581631Covid
    2021-03-18T00:00:00Z2021March Thursday 15320.26143831Covid
    2021-03-19T00:00:00Z2021March Friday 26819.40298552Covid
    2021-03-20T00:00:00Z2021March Saturday 658 6.38297942Covid
    2021-03-21T00:00:00Z2021March Sunday 17023.52941240Covid
    2021-03-22T00:00:00Z2021March Monday 17422.41379339Covid
    2021-03-23T00:00:00Z2021March Tuesday 14316.78321724Covid
    2021-03-24T00:00:00Z2021March Wednesday15717.19745227Covid
    2021-03-25T00:00:00Z2021March Thursday 16525.45454542Covid
    2021-03-26T00:00:00Z2021March Friday 573 6.10820235Covid
    A data.frame: 25 × 3
    monthyeartotal_communicated
    <fct><fct><dbl>
    March 2019 136
    April 20191531
    May 20191238
    June 20191094
    July 20191150
    August 20191760
    September20192588
    October 20192168
    November 20191861
    December 20191184
    January 20201094
    February 20201232
    March 20201174
    April 20201186
    May 20201077
    June 20201139
    July 20201071
    August 20201859
    September20202175
    October 20201602
    November 20201165
    December 2020 864
    January 2021 968
    February 2021 948
    March 2021 876

    Visualizations

    I realized that using R's base plots were not going to make the cut. I recall that when I was searching for graphing solutions on a different project, I found an appealing graph solution with ggplots. At the time I was using python, so ggplot wasn't a library supported. In another class, the professor introduced ggplots. I could have used excel to generate the plots, but I wanted a learning opportunity to try ggplot on something that wasn't homework or classwork. I knew I needed a stacked bar chart as I needed to compare the changes across the months and years.

    After a search on the web, I found the following guide "How to Create and Customize Bar Plot Using ggplot2 Package in R- One Zero Blog" on the towards data science medium to be particularly helpful, as there was sample code with outputs. I used the sample code from section on bar labels on a stack bar plot as a base and made modifications to fit my data.

    all joins

    To make it easier for me to input the parameters and give me a sanity check for my graphs, I loaded all the aggregate data.

    library(ggplot2)

head(joins)
head(agg_joins.2019)
head(agg_joins.2020)
head(agg_joins.2021)
head(agg_joins)

    A data.frame: 6 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    12019-03-29T00:00:00Z2019MarchFriday 250.00000 50.00000Normal
    22019-03-30T00:00:00Z2019MarchSaturday 616.66667 33.33333Normal
    32019-03-31T00:00:00Z2019MarchSunday 825.00000 37.50000Normal
    42019-04-01T00:00:00Z2019AprilMonday 944.44444 33.33333Normal
    52019-04-02T00:00:00Z2019AprilTuesday 250.00000100.00000Normal
    62019-04-03T00:00:00Z2019AprilWednesday0 NA NANormal
    A data.frame: 6 × 2
    MonthsTotal New Members
    <fct><int>
    1March 16
    2April 69
    3May 54
    4June 54
    5July 37
    6August256
    A data.frame: 6 × 2
    MonthsTotal New Members
    <fct><int>
    1January 86
    2February 61
    3March 63
    4April 123
    5May 84
    6June 74
    A data.frame: 3 × 2
    MonthsTotal New Members
    <fct><int>
    1January 113
    2February137
    3March 109
    A data.frame: 6 × 3
    monthyearnew_members
    <fct><fct><int>
    1March 2019 16
    2April 2019 69
    3May 2019 54
    4June 2019 54
    5July 2019 37
    6August2019256

    I started by substituting the sample parameters with my own dataset. I quickly realized that the graph had some issues on the x axis. The month names were overlapping.

    all_joins = ggplot(data = agg_joins, mapping = aes(x = month, y = new_members, fill = year)) + xlab("Month") + ylab("Total New Members") + geom_col()+
            geom_text(aes(label=new_members), position = position_stack(vjust= 0.5),
            colour = "black", size = 5)
all_joins = all_joins + labs(title = "New Member Joins Across the Year")
all_joins

    After searching the web, I found a great stack overflow answer How to maintain size of ggplot with long labels that ultimately influenced the final graphs.

    all_joins = ggplot(data = agg_joins, mapping = aes(x = month, y = new_members, fill = year)) + xlab("Month") + ylab("Total New Members") + geom_col()+
            geom_text(aes(label=new_members), position = position_stack(vjust= 0.5),
            colour = "black", size = 5) + coord_flip()
all_joins = all_joins + labs(title = "New Member Joins Across the Year")
all_joins

    When I first made the graphs, the order of the x axis was backwards from a normal year. For the presentation I used the version above, but when I came back for the final report and final write up, I decided to search for a solution. I knew previously that coord_flip() was the cause of the initial reversed order. Searching ggplot coord_flip() change order of x axis+change+order+of+x+axis&t=ffab&ia=web) found the answer I was looking for. The following answer from Reversed order after coord_flip in R was had the solution I was looking for. I learned that I could use a limits parameter to change the order, as passing scale_x_discrete() with out any parameters wouldn't change my graph.

    Ultimately this is the final version of the graph. For the report, I scaled the horizontal dimension to be 1920 and had the aspect ratio fixed.

    all_joins = ggplot(data = agg_joins, mapping = aes(x = month, y = new_members, fill = year)) + xlab("Month") + ylab("Total New Members") + geom_col()+
            geom_text(aes(label=new_members), position = position_stack(vjust= 0.5),
            colour = "black", size = 5) + coord_flip() + scale_x_discrete(limits = rev(levels(agg_joins$month)))
all_joins = all_joins + labs(title = "New Member Joins Across the Year")
all_joins

    All leaves

    I decided to also make a graph for leaves, but it was ultimately scrapped because our analysis was more focused in the new user changes. Perhaps we can return to analyze the leaves

    leaves
agg_leaves.2019
agg_leaves.2020
agg_leaves.2021
agg_leaves

    A data.frame: 1104 × 7
    interval_start_timestampyearmonthdaydays_in_guildleaversyear_type
    <chr><fct><fct><fct><fct><int><fct>
    2019-03-29T00:00:00Z2019MarchFriday 'Members for 1 month+' 1Normal
    2019-03-30T00:00:00Z2019MarchSaturday 'Members for 1 month+' 1Normal
    2019-03-30T00:00:00Z2019MarchSaturday 'Members for < 1 month'1Normal
    2019-03-31T00:00:00Z2019MarchSunday 'Members for 1 month+' 2Normal
    2019-03-31T00:00:00Z2019March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Normal
    2019-04-01T00:00:00Z2019AprilMonday 'Members for 1 month+' 4Normal
    2019-04-02T00:00:00Z2019AprilTuesday 'Members for 1 month+' 1Normal
    2019-04-03T00:00:00Z2019AprilWednesday'Members for 1 month+' 2Normal
    2019-04-03T00:00:00Z2019AprilWednesday'Members for < 1 month'2Normal
    2019-04-04T00:00:00Z2019AprilThursday 'Members for 1 month+' 2Normal
    2019-04-04T00:00:00Z2019AprilThursday 'Members for < 1 month'2Normal
    2019-04-05T00:00:00Z2019AprilFriday 'Members for 1 month+' 3Normal
    2019-04-06T00:00:00Z2019AprilSaturday 'Members for 1 month+' 1Normal
    2019-04-06T00:00:00Z2019AprilSaturday 'Members for < 1 month'1Normal
    2019-04-07T00:00:00Z2019AprilSunday 'Members for 1 month+' 1Normal
    2019-04-07T00:00:00Z2019April<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'2Normal
    2019-04-08T00:00:00Z2019AprilMonday 'Members for 1 month+' 1Normal
    2019-04-08T00:00:00Z2019April<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Normal
    2019-04-09T00:00:00Z2019AprilTuesday 'Members for 1 month+' 1Normal
    2019-04-09T00:00:00Z2019April<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Normal
    2019-04-10T00:00:00Z2019AprilWednesday'Members for 1 month+' 2Normal
    2019-04-10T00:00:00Z2019AprilWednesday'Members for < 1 month'1Normal
    2019-04-11T00:00:00Z2019AprilThursday 'Members for 1 month+' 0Normal
    2019-04-12T00:00:00Z2019AprilFriday 'Members for 1 month+' 1Normal
    2019-04-13T00:00:00Z2019AprilSaturday 'Members for < 1 month'1Normal
    2019-04-14T00:00:00Z2019AprilSunday 'Members for 1 month+' 2Normal
    2019-04-15T00:00:00Z2019AprilMonday 'Members for 1 month+' 1Normal
    2019-04-15T00:00:00Z2019April<span style=white-space:pre-wrap>Monday </span>'Members for < 1 month'1Normal
    2019-04-16T00:00:00Z2019AprilTuesday 'Members for 1 month+' 3Normal
    2019-04-16T00:00:00Z2019April<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Normal
    ⋮⋮⋮⋮⋮⋮⋮
    2021-03-09T00:00:00Z2021MarchTuesday 'Members for 1 month+' 2Covid
    2021-03-09T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    2021-03-10T00:00:00Z2021MarchWednesday'Members for 1 month+' 2Covid
    2021-03-10T00:00:00Z2021MarchWednesday'Members for < 1 month'3Covid
    2021-03-11T00:00:00Z2021MarchThursday 'Members for 1 month+' 2Covid
    2021-03-12T00:00:00Z2021MarchFriday 'Members for 1 month+' 1Covid
    2021-03-12T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'5Covid
    2021-03-13T00:00:00Z2021MarchSaturday 'Members for < 1 month'1Covid
    2021-03-14T00:00:00Z2021MarchSunday 'Members for 1 month+' 1Covid
    2021-03-14T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'1Covid
    2021-03-15T00:00:00Z2021MarchMonday 'Members for 1 month+' 2Covid
    2021-03-16T00:00:00Z2021MarchTuesday 'Members for 1 month+' 1Covid
    2021-03-16T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'3Covid
    2021-03-17T00:00:00Z2021MarchWednesday'Members for 1 month+' 4Covid
    2021-03-17T00:00:00Z2021MarchWednesday'Members for < 1 month'2Covid
    2021-03-18T00:00:00Z2021MarchThursday 'Members for < 1 month'1Covid
    2021-03-19T00:00:00Z2021MarchFriday 'Members for 1 month+' 2Covid
    2021-03-19T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'2Covid
    2021-03-20T00:00:00Z2021MarchSaturday 'Members for 1 month+' 5Covid
    2021-03-20T00:00:00Z2021MarchSaturday 'Members for < 1 month'1Covid
    2021-03-21T00:00:00Z2021MarchSunday 'Members for 1 month+' 1Covid
    2021-03-21T00:00:00Z2021March<span style=white-space:pre-wrap>Sunday </span>'Members for < 1 month'3Covid
    2021-03-22T00:00:00Z2021MarchMonday 'Members for 1 month+' 1Covid
    2021-03-23T00:00:00Z2021MarchTuesday 'Members for 1 month+' 3Covid
    2021-03-23T00:00:00Z2021March<span style=white-space:pre-wrap>Tuesday </span>'Members for < 1 month'1Covid
    2021-03-24T00:00:00Z2021MarchWednesday'Members for 1 month+' 0Covid
    2021-03-25T00:00:00Z2021MarchThursday 'Members for 1 month+' 2Covid
    2021-03-25T00:00:00Z2021MarchThursday 'Members for < 1 month'1Covid
    2021-03-26T00:00:00Z2021MarchFriday 'Members for 1 month+' 3Covid
    2021-03-26T00:00:00Z2021March<span style=white-space:pre-wrap>Friday </span>'Members for < 1 month'1Covid
    A data.frame: 10 × 2
    MonthsTotal Leavers
    <fct><int>
    March 6
    April 75
    May 54
    June 45
    July 47
    August 66
    September 90
    October 60
    November 118
    December 43
    A data.frame: 12 × 2
    MonthsTotal Leavers
    <fct><int>
    January 66
    February 82
    March 73
    April 95
    May 72
    June 82
    July 90
    August 127
    September132
    October 100
    November 91
    December 83
    A data.frame: 3 × 2
    MonthsTotal Leavers
    <fct><int>
    January 93
    February88
    March 78
    A data.frame: 25 × 3
    monthyearleavers
    <fct><fct><int>
    March 2019 6
    April 2019 75
    May 2019 54
    June 2019 45
    July 2019 47
    August 2019 66
    September2019 90
    October 2019 60
    November 2019118
    December 2019 43
    January 2020 66
    February 2020 82
    March 2020 73
    April 2020 95
    May 2020 72
    June 2020 82
    July 2020 90
    August 2020127
    September2020132
    October 2020100
    November 2020 91
    December 2020 83
    January 2021 93
    February 2021 88
    March 2021 78
     

    all_leaves = ggplot(data = agg_leaves, mapping = aes(x = month, y = leavers, fill = year)) + xlab("Month") + ylab("Total Leaves") + geom_col()+
             geom_text(aes(label=leavers), position = position_stack(vjust= 0.5),
             colour = "black", size = 5) + coord_flip() + scale_x_discrete(limits = rev(levels(agg_leaves$month)))
all_leaves = all_leaves + labs(title = "Member Leaves Across the Year")

all_leaves

    All communicators 

    communicators

agg_comm.2019
agg_comm.2020
agg_comm.2021
agg_comms

    A data.frame: 729 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    2019-03-29T00:00:00Z2019MarchFriday 20625.7281653Normal
    2019-03-30T00:00:00Z2019MarchSaturday 18420.6521738Normal
    2019-03-31T00:00:00Z2019MarchSunday 18524.3243245Normal
    2019-04-01T00:00:00Z2019AprilMonday 32822.8658575Normal
    2019-04-02T00:00:00Z2019AprilTuesday 14333.5664348Normal
    2019-04-03T00:00:00Z2019AprilWednesday27116.6051745Normal
    2019-04-04T00:00:00Z2019AprilThursday 38113.3858351Normal
    2019-04-05T00:00:00Z2019AprilFriday 19024.7368447Normal
    2019-04-06T00:00:00Z2019AprilSaturday 16326.9938744Normal
    2019-04-07T00:00:00Z2019AprilSunday 15931.4465450Normal
    2019-04-08T00:00:00Z2019AprilMonday 16325.7668742Normal
    2019-04-09T00:00:00Z2019AprilTuesday 14831.0810846Normal
    2019-04-10T00:00:00Z2019AprilWednesday16330.6748550Normal
    2019-04-11T00:00:00Z2019AprilThursday 13938.1295053Normal
    2019-04-12T00:00:00Z2019AprilFriday 15529.6774246Normal
    2019-04-13T00:00:00Z2019AprilSaturday 14330.0699343Normal
    2019-04-14T00:00:00Z2019AprilSunday 14028.5714340Normal
    2019-04-15T00:00:00Z2019AprilMonday 17029.4117650Normal
    2019-04-16T00:00:00Z2019AprilTuesday 15040.6666761Normal
    2019-04-17T00:00:00Z2019AprilWednesday15334.6405253Normal
    2019-04-18T00:00:00Z2019AprilThursday 16743.7125773Normal
    2019-04-19T00:00:00Z2019AprilFriday 16233.9506255Normal
    2019-04-20T00:00:00Z2019AprilSaturday 33715.1335351Normal
    2019-04-21T00:00:00Z2019AprilSunday 17225.0000043Normal
    2019-04-22T00:00:00Z2019AprilMonday 16224.0740739Normal
    2019-04-23T00:00:00Z2019AprilTuesday 16335.5828258Normal
    2019-04-24T00:00:00Z2019AprilWednesday34015.2941252Normal
    2019-04-25T00:00:00Z2019AprilThursday 19626.5306152Normal
    2019-04-26T00:00:00Z2019AprilFriday 37116.9811363Normal
    2019-04-27T00:00:00Z2019AprilSaturday 20127.8607056Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 17223.25581440Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 16719.16167732Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 20820.67307743Covid
    2021-02-28T00:00:00Z2021FebruarySunday 16717.96407230Covid
    2021-03-01T00:00:00Z2021March Monday 16418.29268330Covid
    2021-03-02T00:00:00Z2021March Tuesday 19915.07537730Covid
    2021-03-03T00:00:00Z2021March Wednesday16318.40490830Covid
    2021-03-04T00:00:00Z2021March Thursday 16320.85889634Covid
    2021-03-05T00:00:00Z2021March Friday 17917.31843631Covid
    2021-03-06T00:00:00Z2021March Saturday 304 9.53947429Covid
    2021-03-07T00:00:00Z2021March Sunday 16215.43209925Covid
    2021-03-08T00:00:00Z2021March Monday 23413.67521432Covid
    2021-03-09T00:00:00Z2021March Tuesday 16023.12500037Covid
    2021-03-10T00:00:00Z2021March Wednesday15620.51282132Covid
    2021-03-11T00:00:00Z2021March Thursday 553 7.23327340Covid
    2021-03-12T00:00:00Z2021March Friday 25314.62450637Covid
    2021-03-13T00:00:00Z2021March Saturday 23714.34599234Covid
    2021-03-14T00:00:00Z2021March Sunday 14720.40816330Covid
    2021-03-15T00:00:00Z2021March Monday 15418.83116929Covid
    2021-03-16T00:00:00Z2021March Tuesday 15421.42857133Covid
    2021-03-17T00:00:00Z2021March Wednesday14121.98581631Covid
    2021-03-18T00:00:00Z2021March Thursday 15320.26143831Covid
    2021-03-19T00:00:00Z2021March Friday 26819.40298552Covid
    2021-03-20T00:00:00Z2021March Saturday 658 6.38297942Covid
    2021-03-21T00:00:00Z2021March Sunday 17023.52941240Covid
    2021-03-22T00:00:00Z2021March Monday 17422.41379339Covid
    2021-03-23T00:00:00Z2021March Tuesday 14316.78321724Covid
    2021-03-24T00:00:00Z2021March Wednesday15717.19745227Covid
    2021-03-25T00:00:00Z2021March Thursday 16525.45454542Covid
    2021-03-26T00:00:00Z2021March Friday 573 6.10820235Covid
    A data.frame: 10 × 2
    MonthsTotal Communicated
    <fct><dbl>
    March 136
    April 1531
    May 1238
    June 1094
    July 1150
    August 1760
    September2588
    October 2168
    November 1861
    December 1184
    A data.frame: 12 × 2
    MonthsTotal Communicated
    <fct><dbl>
    January 1094
    February 1232
    March 1174
    April 1186
    May 1077
    June 1139
    July 1071
    August 1859
    September2175
    October 1602
    November 1165
    December 864
    A data.frame: 3 × 2
    MonthsTotal Communicated
    <fct><dbl>
    January 968
    February948
    March 876
    A data.frame: 25 × 3
    monthyeartotal_communicated
    <fct><fct><dbl>
    March 2019 136
    April 20191531
    May 20191238
    June 20191094
    July 20191150
    August 20191760
    September20192588
    October 20192168
    November 20191861
    December 20191184
    January 20201094
    February 20201232
    March 20201174
    April 20201186
    May 20201077
    June 20201139
    July 20201071
    August 20201859
    September20202175
    October 20201602
    November 20201165
    December 2020 864
    January 2021 968
    February 2021 948
    March 2021 876
     

    all_comms = ggplot(data = agg_comms, mapping = aes(x = month, y = total_communicated, fill = year)) + xlab("Month") + ylab("Total Members Communicated") +
            geom_col()+ geom_text(aes(label=total_communicated), position = position_stack(vjust= 0.5),
            colour = "black", size = 5) + coord_flip() + scale_x_discrete(limits = rev(levels(agg_comms$month)))
all_comms = all_comms + labs(title = "All Communicating Members")
all_comms

    Multiple Models Excluding Effect of Year

    This section contains the code for generating linear models for the other variables we were interested in. I followed my professor's notes for setting up the parameters. For fun I decided to experiment with the messages dataset, as it included an additional variable of messages_per_communicator which gives a bit more granularity in comparing between individuals and aggregates for messages.

    New members linear model 

    joins

    A data.frame: 729 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    2019-03-29T00:00:00Z2019MarchFriday 2 50.00000 50.00000Normal
    2019-03-30T00:00:00Z2019MarchSaturday 6 16.66667 33.33333Normal
    2019-03-31T00:00:00Z2019MarchSunday 8 25.00000 37.50000Normal
    2019-04-01T00:00:00Z2019AprilMonday 9 44.44444 33.33333Normal
    2019-04-02T00:00:00Z2019AprilTuesday 2 50.00000100.00000Normal
    2019-04-03T00:00:00Z2019AprilWednesday0 NA NANormal
    2019-04-04T00:00:00Z2019AprilThursday 2100.00000100.00000Normal
    2019-04-05T00:00:00Z2019AprilFriday 3 33.33333 0.00000Normal
    2019-04-06T00:00:00Z2019AprilSaturday 2 0.00000 0.00000Normal
    2019-04-07T00:00:00Z2019AprilSunday 2 0.00000 0.00000Normal
    2019-04-08T00:00:00Z2019AprilMonday 9 33.33333 33.33333Normal
    2019-04-09T00:00:00Z2019AprilTuesday 3 33.33333 33.33333Normal
    2019-04-10T00:00:00Z2019AprilWednesday1100.00000100.00000Normal
    2019-04-11T00:00:00Z2019AprilThursday 1 0.00000100.00000Normal
    2019-04-12T00:00:00Z2019AprilFriday 1 0.00000100.00000Normal
    2019-04-13T00:00:00Z2019AprilSaturday 1 0.00000100.00000Normal
    2019-04-14T00:00:00Z2019AprilSunday 0 NA NANormal
    2019-04-15T00:00:00Z2019AprilMonday 0 NA NANormal
    2019-04-16T00:00:00Z2019AprilTuesday 3 66.66667 0.00000Normal
    2019-04-17T00:00:00Z2019AprilWednesday5 0.00000 20.00000Normal
    2019-04-18T00:00:00Z2019AprilThursday 3100.00000 33.33333Normal
    2019-04-19T00:00:00Z2019AprilFriday 3 0.00000 33.33333Normal
    2019-04-20T00:00:00Z2019AprilSaturday 0 NA NANormal
    2019-04-21T00:00:00Z2019AprilSunday 1100.00000100.00000Normal
    2019-04-22T00:00:00Z2019AprilMonday 0 NA NANormal
    2019-04-23T00:00:00Z2019AprilTuesday 1 0.00000 0.00000Normal
    2019-04-24T00:00:00Z2019AprilWednesday3 33.33333 0.00000Normal
    2019-04-25T00:00:00Z2019AprilThursday 3 66.66667 66.66667Normal
    2019-04-26T00:00:00Z2019AprilFriday 3 33.33333 33.33333Normal
    2019-04-27T00:00:00Z2019AprilSaturday 1100.00000 0.00000Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 1 0.00000100.00000Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 540.00000100.00000Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 812.50000100.00000Covid
    2021-02-28T00:00:00Z2021FebruarySunday 520.00000100.00000Covid
    2021-03-01T00:00:00Z2021March Monday 2 0.00000 50.00000Covid
    2021-03-02T00:00:00Z2021March Tuesday 616.66667 16.66667Covid
    2021-03-03T00:00:00Z2021March Wednesday 5 0.00000 40.00000Covid
    2021-03-04T00:00:00Z2021March Thursday 8 0.00000 62.50000Covid
    2021-03-05T00:00:00Z2021March Friday 333.33333 33.33333Covid
    2021-03-06T00:00:00Z2021March Saturday 3 0.00000 66.66667Covid
    2021-03-07T00:00:00Z2021March Sunday 3 0.00000 33.33333Covid
    2021-03-08T00:00:00Z2021March Monday 714.28571 42.85714Covid
    2021-03-09T00:00:00Z2021March Tuesday 7 0.00000 57.14286Covid
    2021-03-10T00:00:00Z2021March Wednesday 5 0.00000 40.00000Covid
    2021-03-11T00:00:00Z2021March Thursday 1 0.00000100.00000Covid
    2021-03-12T00:00:00Z2021March Friday 1118.18182 45.45455Covid
    2021-03-13T00:00:00Z2021March Saturday 4 0.00000 50.00000Covid
    2021-03-14T00:00:00Z2021March Sunday 1 0.00000 0.00000Covid
    2021-03-15T00:00:00Z2021March Monday 1 0.00000 0.00000Covid
    2021-03-16T00:00:00Z2021March Tuesday 6 0.00000 83.33333Covid
    2021-03-17T00:00:00Z2021March Wednesday 7 0.00000 71.42857Covid
    2021-03-18T00:00:00Z2021March Thursday 1 0.00000 0.00000Covid
    2021-03-19T00:00:00Z2021March Friday 5 0.00000 80.00000Covid
    2021-03-20T00:00:00Z2021March Saturday 2 0.00000 0.00000Covid
    2021-03-21T00:00:00Z2021March Sunday 633.33333 33.33333Covid
    2021-03-22T00:00:00Z2021March Monday 520.00000 60.00000Covid
    2021-03-23T00:00:00Z2021March Tuesday 1 0.00000 0.00000Covid
    2021-03-24T00:00:00Z2021March Wednesday 4 0.00000 50.00000Covid
    2021-03-25T00:00:00Z2021March Thursday 1 0.00000 0.00000Covid
    2021-03-26T00:00:00Z2021March Friday 4 NA NACovid
     

    joins_lm = lm(new_members ~ month + year_type, data = joins)
print(summary(joins_lm))

    Call:
lm(formula = new_members ~ month + year_type, data = joins)

Residuals:
   Min     1Q Median     3Q    Max 
-8.759 -2.195 -0.612  0.808 85.469 

Coefficients:
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)     1.98132    0.80555   2.460  0.01414 *  
monthFebruary   0.26401    0.96935   0.272  0.78543    
monthMarch     -0.01493    0.95690  -0.016  0.98756    
monthApril      0.60450    0.98228   0.615  0.53848    
monthMay       -0.36969    0.97461  -0.379  0.70456    
monthJune      -0.46217    0.98228  -0.471  0.63814    
monthJuly      -0.30518    0.97461  -0.313  0.75428    
monthAugust     6.54966    0.97461   6.720 3.70e-11 ***
monthSeptember  4.28783    0.98228   4.365 1.46e-05 ***
monthOctober    2.22708    0.97461   2.285  0.02260 *  
monthNovember   2.25450    0.98228   2.295  0.02201 *  
monthDecember  -0.78905    0.97461  -0.810  0.41844    
year_typeCovid  1.22836    0.44590   2.755  0.00602 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 5.283 on 716 degrees of freedom
Multiple R-squared:  0.1475,	Adjusted R-squared:  0.1332 
F-statistic: 10.32 on 12 and 716 DF,  p-value: < 2.2e-16

    Total messages linear model 

    messages

    A data.frame: 729 × 7
    interval_start_timestampyearmonthdaymessagesmessages_per_communicatoryear_type
    <chr><fct><fct><fct><int><dbl><fct>
    2019-03-29T00:00:00Z2019MarchFriday 334 6.301887Normal
    2019-03-30T00:00:00Z2019MarchSaturday 236 6.210526Normal
    2019-03-31T00:00:00Z2019MarchSunday 364 8.088889Normal
    2019-04-01T00:00:00Z2019AprilMonday 404 5.386667Normal
    2019-04-02T00:00:00Z2019AprilTuesday 54311.312500Normal
    2019-04-03T00:00:00Z2019AprilWednesday 324 7.200000Normal
    2019-04-04T00:00:00Z2019AprilThursday 55610.901961Normal
    2019-04-05T00:00:00Z2019AprilFriday 273 5.808511Normal
    2019-04-06T00:00:00Z2019AprilSaturday 335 7.613636Normal
    2019-04-07T00:00:00Z2019AprilSunday 110222.040000Normal
    2019-04-08T00:00:00Z2019AprilMonday 188 4.476190Normal
    2019-04-09T00:00:00Z2019AprilTuesday 399 8.673913Normal
    2019-04-10T00:00:00Z2019AprilWednesday 53110.620000Normal
    2019-04-11T00:00:00Z2019AprilThursday 68913.000000Normal
    2019-04-12T00:00:00Z2019AprilFriday 418 9.086957Normal
    2019-04-13T00:00:00Z2019AprilSaturday 56613.162791Normal
    2019-04-14T00:00:00Z2019AprilSunday 48112.025000Normal
    2019-04-15T00:00:00Z2019AprilMonday 65913.180000Normal
    2019-04-16T00:00:00Z2019AprilTuesday 77912.770492Normal
    2019-04-17T00:00:00Z2019AprilWednesday 59611.245283Normal
    2019-04-18T00:00:00Z2019AprilThursday 114315.657534Normal
    2019-04-19T00:00:00Z2019AprilFriday 89816.327273Normal
    2019-04-20T00:00:00Z2019AprilSaturday 331 6.490196Normal
    2019-04-21T00:00:00Z2019AprilSunday 47311.000000Normal
    2019-04-22T00:00:00Z2019AprilMonday 283 7.256410Normal
    2019-04-23T00:00:00Z2019AprilTuesday 127021.896552Normal
    2019-04-24T00:00:00Z2019AprilWednesday 74614.346154Normal
    2019-04-25T00:00:00Z2019AprilThursday 287 5.519231Normal
    2019-04-26T00:00:00Z2019AprilFriday 72811.555556Normal
    2019-04-27T00:00:00Z2019AprilSaturday 69112.339286Normal
    ⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 1383.450000Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 782.437500Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 932.162791Covid
    2021-02-28T00:00:00Z2021FebruarySunday 461.533333Covid
    2021-03-01T00:00:00Z2021March Monday 531.766667Covid
    2021-03-02T00:00:00Z2021March Tuesday 722.400000Covid
    2021-03-03T00:00:00Z2021March Wednesday1224.066667Covid
    2021-03-04T00:00:00Z2021March Thursday 1684.941176Covid
    2021-03-05T00:00:00Z2021March Friday 742.387097Covid
    2021-03-06T00:00:00Z2021March Saturday 431.482759Covid
    2021-03-07T00:00:00Z2021March Sunday 431.720000Covid
    2021-03-08T00:00:00Z2021March Monday 1063.312500Covid
    2021-03-09T00:00:00Z2021March Tuesday 1143.081081Covid
    2021-03-10T00:00:00Z2021March Wednesday 832.593750Covid
    2021-03-11T00:00:00Z2021March Thursday 1092.725000Covid
    2021-03-12T00:00:00Z2021March Friday 752.027027Covid
    2021-03-13T00:00:00Z2021March Saturday 1584.647059Covid
    2021-03-14T00:00:00Z2021March Sunday 732.433333Covid
    2021-03-15T00:00:00Z2021March Monday 732.517241Covid
    2021-03-16T00:00:00Z2021March Tuesday 521.575758Covid
    2021-03-17T00:00:00Z2021March Wednesday 642.064516Covid
    2021-03-18T00:00:00Z2021March Thursday 652.096774Covid
    2021-03-19T00:00:00Z2021March Friday 1823.500000Covid
    2021-03-20T00:00:00Z2021March Saturday 1212.880952Covid
    2021-03-21T00:00:00Z2021March Sunday 1573.925000Covid
    2021-03-22T00:00:00Z2021March Monday 942.410256Covid
    2021-03-23T00:00:00Z2021March Tuesday 341.416667Covid
    2021-03-24T00:00:00Z2021March Wednesday 511.888889Covid
    2021-03-25T00:00:00Z2021March Thursday 1202.857143Covid
    2021-03-26T00:00:00Z2021March Friday 1223.485714Covid
     

    messages_lm = lm(messages ~ month + year_type, data = messages)
print(summary(messages_lm))

    Call:
lm(formula = messages ~ month + year_type, data = messages)

Residuals:
    Min      1Q  Median      3Q     Max 
-533.72 -131.98  -34.98   68.19 2435.80 

Coefficients:
                Estimate Std. Error t value Pr(>|t|)    
(Intercept)     370.7838    37.3808   9.919  < 2e-16 ***
monthFebruary     0.7405    44.9820   0.016  0.98687    
monthMarch       19.0476    44.4043   0.429  0.66808    
monthApril      153.6371    45.5819   3.371  0.00079 ***
monthMay         24.6162    45.2261   0.544  0.58641    
monthJune       -73.9795    45.5819  -1.623  0.10503    
monthJuly       -42.4322    45.2261  -0.938  0.34845    
monthAugust     210.2452    45.2261   4.649 3.98e-06 ***
monthSeptember  433.9371    45.5819   9.520  < 2e-16 ***
monthOctober    261.9549    45.2261   5.792 1.04e-08 ***
monthNovember   109.9371    45.5819   2.412  0.01612 *  
monthDecember   -79.8354    45.2261  -1.765  0.07795 .  
year_typeCovid -193.5419    20.6915  -9.354  < 2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 245.1 on 716 degrees of freedom
Multiple R-squared:  0.369,	Adjusted R-squared:  0.3584 
F-statistic: 34.89 on 12 and 716 DF,  p-value: < 2.2e-16

    Messages experiments

    Including messages_per_communicator in full model 

    messages

    A data.frame: 729 × 7
    interval_start_timestampyearmonthdaymessagesmessages_per_communicatoryear_type
    <chr><fct><fct><fct><int><dbl><fct>
    2019-03-29T00:00:00Z2019MarchFriday 334 6.301887Normal
    2019-03-30T00:00:00Z2019MarchSaturday 236 6.210526Normal
    2019-03-31T00:00:00Z2019MarchSunday 364 8.088889Normal
    2019-04-01T00:00:00Z2019AprilMonday 404 5.386667Normal
    2019-04-02T00:00:00Z2019AprilTuesday 54311.312500Normal
    2019-04-03T00:00:00Z2019AprilWednesday 324 7.200000Normal
    2019-04-04T00:00:00Z2019AprilThursday 55610.901961Normal
    2019-04-05T00:00:00Z2019AprilFriday 273 5.808511Normal
    2019-04-06T00:00:00Z2019AprilSaturday 335 7.613636Normal
    2019-04-07T00:00:00Z2019AprilSunday 110222.040000Normal
    2019-04-08T00:00:00Z2019AprilMonday 188 4.476190Normal
    2019-04-09T00:00:00Z2019AprilTuesday 399 8.673913Normal
    2019-04-10T00:00:00Z2019AprilWednesday 53110.620000Normal
    2019-04-11T00:00:00Z2019AprilThursday 68913.000000Normal
    2019-04-12T00:00:00Z2019AprilFriday 418 9.086957Normal
    2019-04-13T00:00:00Z2019AprilSaturday 56613.162791Normal
    2019-04-14T00:00:00Z2019AprilSunday 48112.025000Normal
    2019-04-15T00:00:00Z2019AprilMonday 65913.180000Normal
    2019-04-16T00:00:00Z2019AprilTuesday 77912.770492Normal
    2019-04-17T00:00:00Z2019AprilWednesday 59611.245283Normal
    2019-04-18T00:00:00Z2019AprilThursday 114315.657534Normal
    2019-04-19T00:00:00Z2019AprilFriday 89816.327273Normal
    2019-04-20T00:00:00Z2019AprilSaturday 331 6.490196Normal
    2019-04-21T00:00:00Z2019AprilSunday 47311.000000Normal
    2019-04-22T00:00:00Z2019AprilMonday 283 7.256410Normal
    2019-04-23T00:00:00Z2019AprilTuesday 127021.896552Normal
    2019-04-24T00:00:00Z2019AprilWednesday 74614.346154Normal
    2019-04-25T00:00:00Z2019AprilThursday 287 5.519231Normal
    2019-04-26T00:00:00Z2019AprilFriday 72811.555556Normal
    2019-04-27T00:00:00Z2019AprilSaturday 69112.339286Normal
    ⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 1383.450000Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 782.437500Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 932.162791Covid
    2021-02-28T00:00:00Z2021FebruarySunday 461.533333Covid
    2021-03-01T00:00:00Z2021March Monday 531.766667Covid
    2021-03-02T00:00:00Z2021March Tuesday 722.400000Covid
    2021-03-03T00:00:00Z2021March Wednesday1224.066667Covid
    2021-03-04T00:00:00Z2021March Thursday 1684.941176Covid
    2021-03-05T00:00:00Z2021March Friday 742.387097Covid
    2021-03-06T00:00:00Z2021March Saturday 431.482759Covid
    2021-03-07T00:00:00Z2021March Sunday 431.720000Covid
    2021-03-08T00:00:00Z2021March Monday 1063.312500Covid
    2021-03-09T00:00:00Z2021March Tuesday 1143.081081Covid
    2021-03-10T00:00:00Z2021March Wednesday 832.593750Covid
    2021-03-11T00:00:00Z2021March Thursday 1092.725000Covid
    2021-03-12T00:00:00Z2021March Friday 752.027027Covid
    2021-03-13T00:00:00Z2021March Saturday 1584.647059Covid
    2021-03-14T00:00:00Z2021March Sunday 732.433333Covid
    2021-03-15T00:00:00Z2021March Monday 732.517241Covid
    2021-03-16T00:00:00Z2021March Tuesday 521.575758Covid
    2021-03-17T00:00:00Z2021March Wednesday 642.064516Covid
    2021-03-18T00:00:00Z2021March Thursday 652.096774Covid
    2021-03-19T00:00:00Z2021March Friday 1823.500000Covid
    2021-03-20T00:00:00Z2021March Saturday 1212.880952Covid
    2021-03-21T00:00:00Z2021March Sunday 1573.925000Covid
    2021-03-22T00:00:00Z2021March Monday 942.410256Covid
    2021-03-23T00:00:00Z2021March Tuesday 341.416667Covid
    2021-03-24T00:00:00Z2021March Wednesday 511.888889Covid
    2021-03-25T00:00:00Z2021March Thursday 1202.857143Covid
    2021-03-26T00:00:00Z2021March Friday 1223.485714Covid
     

    messages_lm1 = lm(messages ~ month + year_type + messages_per_communicator, data = messages)
print(summary(messages_lm1))

    Call:
lm(formula = messages ~ month + year_type + messages_per_communicator, 
    data = messages)

Residuals:
    Min      1Q  Median      3Q     Max 
-794.57  -58.66    1.20   50.09 1112.68 

Coefficients:
                          Estimate Std. Error t value Pr(>|t|)    
(Intercept)                -80.219     22.265  -3.603 0.000337 ***
monthFebruary               44.936     23.694   1.896 0.058298 .  
monthMarch                  13.590     23.369   0.582 0.561041    
monthApril                  12.429     24.209   0.513 0.607821    
monthMay                   -37.842     23.845  -1.587 0.112952    
monthJune                   -2.577     24.045  -0.107 0.914678    
monthJuly                  -33.459     23.802  -1.406 0.160241    
monthAugust                128.790     23.875   5.394 9.36e-08 ***
monthSeptember             311.849     24.154  12.911  < 2e-16 ***
monthOctober               187.593     23.863   7.861 1.40e-14 ***
monthNovember              101.338     23.989   4.224 2.71e-05 ***
monthDecember              -12.940     23.851  -0.543 0.587613    
year_typeCovid             -36.598     11.478  -3.189 0.001492 ** 
messages_per_communicator   55.895      1.292  43.247  < 2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 129 on 715 degrees of freedom
Multiple R-squared:  0.8255,	Adjusted R-squared:  0.8223 
F-statistic: 260.2 on 13 and 715 DF,  p-value: < 2.2e-16

    Including messages_per_communicator in full model 

    messages

    A data.frame: 729 × 7
    interval_start_timestampyearmonthdaymessagesmessages_per_communicatoryear_type
    <chr><fct><fct><fct><int><dbl><fct>
    2019-03-29T00:00:00Z2019MarchFriday 334 6.301887Normal
    2019-03-30T00:00:00Z2019MarchSaturday 236 6.210526Normal
    2019-03-31T00:00:00Z2019MarchSunday 364 8.088889Normal
    2019-04-01T00:00:00Z2019AprilMonday 404 5.386667Normal
    2019-04-02T00:00:00Z2019AprilTuesday 54311.312500Normal
    2019-04-03T00:00:00Z2019AprilWednesday 324 7.200000Normal
    2019-04-04T00:00:00Z2019AprilThursday 55610.901961Normal
    2019-04-05T00:00:00Z2019AprilFriday 273 5.808511Normal
    2019-04-06T00:00:00Z2019AprilSaturday 335 7.613636Normal
    2019-04-07T00:00:00Z2019AprilSunday 110222.040000Normal
    2019-04-08T00:00:00Z2019AprilMonday 188 4.476190Normal
    2019-04-09T00:00:00Z2019AprilTuesday 399 8.673913Normal
    2019-04-10T00:00:00Z2019AprilWednesday 53110.620000Normal
    2019-04-11T00:00:00Z2019AprilThursday 68913.000000Normal
    2019-04-12T00:00:00Z2019AprilFriday 418 9.086957Normal
    2019-04-13T00:00:00Z2019AprilSaturday 56613.162791Normal
    2019-04-14T00:00:00Z2019AprilSunday 48112.025000Normal
    2019-04-15T00:00:00Z2019AprilMonday 65913.180000Normal
    2019-04-16T00:00:00Z2019AprilTuesday 77912.770492Normal
    2019-04-17T00:00:00Z2019AprilWednesday 59611.245283Normal
    2019-04-18T00:00:00Z2019AprilThursday 114315.657534Normal
    2019-04-19T00:00:00Z2019AprilFriday 89816.327273Normal
    2019-04-20T00:00:00Z2019AprilSaturday 331 6.490196Normal
    2019-04-21T00:00:00Z2019AprilSunday 47311.000000Normal
    2019-04-22T00:00:00Z2019AprilMonday 283 7.256410Normal
    2019-04-23T00:00:00Z2019AprilTuesday 127021.896552Normal
    2019-04-24T00:00:00Z2019AprilWednesday 74614.346154Normal
    2019-04-25T00:00:00Z2019AprilThursday 287 5.519231Normal
    2019-04-26T00:00:00Z2019AprilFriday 72811.555556Normal
    2019-04-27T00:00:00Z2019AprilSaturday 69112.339286Normal
    ⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 1383.450000Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 782.437500Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 932.162791Covid
    2021-02-28T00:00:00Z2021FebruarySunday 461.533333Covid
    2021-03-01T00:00:00Z2021March Monday 531.766667Covid
    2021-03-02T00:00:00Z2021March Tuesday 722.400000Covid
    2021-03-03T00:00:00Z2021March Wednesday1224.066667Covid
    2021-03-04T00:00:00Z2021March Thursday 1684.941176Covid
    2021-03-05T00:00:00Z2021March Friday 742.387097Covid
    2021-03-06T00:00:00Z2021March Saturday 431.482759Covid
    2021-03-07T00:00:00Z2021March Sunday 431.720000Covid
    2021-03-08T00:00:00Z2021March Monday 1063.312500Covid
    2021-03-09T00:00:00Z2021March Tuesday 1143.081081Covid
    2021-03-10T00:00:00Z2021March Wednesday 832.593750Covid
    2021-03-11T00:00:00Z2021March Thursday 1092.725000Covid
    2021-03-12T00:00:00Z2021March Friday 752.027027Covid
    2021-03-13T00:00:00Z2021March Saturday 1584.647059Covid
    2021-03-14T00:00:00Z2021March Sunday 732.433333Covid
    2021-03-15T00:00:00Z2021March Monday 732.517241Covid
    2021-03-16T00:00:00Z2021March Tuesday 521.575758Covid
    2021-03-17T00:00:00Z2021March Wednesday 642.064516Covid
    2021-03-18T00:00:00Z2021March Thursday 652.096774Covid
    2021-03-19T00:00:00Z2021March Friday 1823.500000Covid
    2021-03-20T00:00:00Z2021March Saturday 1212.880952Covid
    2021-03-21T00:00:00Z2021March Sunday 1573.925000Covid
    2021-03-22T00:00:00Z2021March Monday 942.410256Covid
    2021-03-23T00:00:00Z2021March Tuesday 341.416667Covid
    2021-03-24T00:00:00Z2021March Wednesday 511.888889Covid
    2021-03-25T00:00:00Z2021March Thursday 1202.857143Covid
    2021-03-26T00:00:00Z2021March Friday 1223.485714Covid
     

    messages_lm2 = lm(messages_per_communicator ~ month + year_type, data = messages)
print(summary(messages_lm2))

    Call:
lm(formula = messages_per_communicator ~ month + year_type, data = messages)

Residuals:
    Min      1Q  Median      3Q     Max 
-7.5431 -2.2972 -0.7784  1.2309 28.5756 

Coefficients:
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)     8.06881    0.56882  14.185  < 2e-16 ***
monthFebruary  -0.79070    0.68449  -1.155  0.24841    
monthMarch      0.09763    0.67570   0.144  0.88515    
monthApril      2.52633    0.69362   3.642  0.00029 ***
monthMay        1.11743    0.68821   1.624  0.10489    
monthJune      -1.27745    0.69362  -1.842  0.06593 .  
monthJuly      -0.16054    0.68821  -0.233  0.81561    
monthAugust     1.45731    0.68821   2.118  0.03456 *  
monthSeptember  2.18426    0.69362   3.149  0.00171 ** 
monthOctober    1.33040    0.68821   1.933  0.05361 .  
monthNovember   0.15385    0.69362   0.222  0.82452    
monthDecember  -1.19681    0.68821  -1.739  0.08246 .  
year_typeCovid -2.80785    0.31486  -8.918  < 2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 3.73 on 716 degrees of freedom
Multiple R-squared:  0.2164,	Adjusted R-squared:  0.2033 
F-statistic: 16.48 on 12 and 716 DF,  p-value: < 2.2e-16

    Voices linear model 

    voices

    A data.frame: 729 × 6
    interval_start_timestampyearmonthdayspeaking_minutesyear_type
    <chr><fct><fct><fct><int><fct>
    2019-03-29T00:00:00Z2019MarchFriday 0Normal
    2019-03-30T00:00:00Z2019MarchSaturday 0Normal
    2019-03-31T00:00:00Z2019MarchSunday 0Normal
    2019-04-01T00:00:00Z2019AprilMonday 0Normal
    2019-04-02T00:00:00Z2019AprilTuesday 0Normal
    2019-04-03T00:00:00Z2019AprilWednesday0Normal
    2019-04-04T00:00:00Z2019AprilThursday 0Normal
    2019-04-05T00:00:00Z2019AprilFriday 0Normal
    2019-04-06T00:00:00Z2019AprilSaturday 0Normal
    2019-04-07T00:00:00Z2019AprilSunday 0Normal
    2019-04-08T00:00:00Z2019AprilMonday 0Normal
    2019-04-09T00:00:00Z2019AprilTuesday 0Normal
    2019-04-10T00:00:00Z2019AprilWednesday0Normal
    2019-04-11T00:00:00Z2019AprilThursday 0Normal
    2019-04-12T00:00:00Z2019AprilFriday 0Normal
    2019-04-13T00:00:00Z2019AprilSaturday 0Normal
    2019-04-14T00:00:00Z2019AprilSunday 0Normal
    2019-04-15T00:00:00Z2019AprilMonday 0Normal
    2019-04-16T00:00:00Z2019AprilTuesday 0Normal
    2019-04-17T00:00:00Z2019AprilWednesday0Normal
    2019-04-18T00:00:00Z2019AprilThursday 0Normal
    2019-04-19T00:00:00Z2019AprilFriday 0Normal
    2019-04-20T00:00:00Z2019AprilSaturday 0Normal
    2019-04-21T00:00:00Z2019AprilSunday 0Normal
    2019-04-22T00:00:00Z2019AprilMonday 0Normal
    2019-04-23T00:00:00Z2019AprilTuesday 0Normal
    2019-04-24T00:00:00Z2019AprilWednesday0Normal
    2019-04-25T00:00:00Z2019AprilThursday 0Normal
    2019-04-26T00:00:00Z2019AprilFriday 0Normal
    2019-04-27T00:00:00Z2019AprilSaturday 0Normal
    ⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 1495Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 913Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 1118Covid
    2021-02-28T00:00:00Z2021FebruarySunday 1354Covid
    2021-03-01T00:00:00Z2021March Monday 1269Covid
    2021-03-02T00:00:00Z2021March Tuesday 1200Covid
    2021-03-03T00:00:00Z2021March Wednesday2031Covid
    2021-03-04T00:00:00Z2021March Thursday 2293Covid
    2021-03-05T00:00:00Z2021March Friday 1124Covid
    2021-03-06T00:00:00Z2021March Saturday 1398Covid
    2021-03-07T00:00:00Z2021March Sunday 1460Covid
    2021-03-08T00:00:00Z2021March Monday 1834Covid
    2021-03-09T00:00:00Z2021March Tuesday 1523Covid
    2021-03-10T00:00:00Z2021March Wednesday1119Covid
    2021-03-11T00:00:00Z2021March Thursday 1878Covid
    2021-03-12T00:00:00Z2021March Friday 1429Covid
    2021-03-13T00:00:00Z2021March Saturday 730Covid
    2021-03-14T00:00:00Z2021March Sunday 567Covid
    2021-03-15T00:00:00Z2021March Monday 1282Covid
    2021-03-16T00:00:00Z2021March Tuesday 1234Covid
    2021-03-17T00:00:00Z2021March Wednesday1146Covid
    2021-03-18T00:00:00Z2021March Thursday 2464Covid
    2021-03-19T00:00:00Z2021March Friday 840Covid
    2021-03-20T00:00:00Z2021March Saturday 428Covid
    2021-03-21T00:00:00Z2021March Sunday 880Covid
    2021-03-22T00:00:00Z2021March Monday 1598Covid
    2021-03-23T00:00:00Z2021March Tuesday 873Covid
    2021-03-24T00:00:00Z2021March Wednesday 771Covid
    2021-03-25T00:00:00Z2021March Thursday 1742Covid
    2021-03-26T00:00:00Z2021March Friday 1038Covid
     

    voices_lm = lm(speaking_minutes ~ month + year_type, data = voices)
print(summary(voices_lm))

    Call:
lm(formula = speaking_minutes ~ month + year_type, data = voices)

Residuals:
    Min      1Q  Median      3Q     Max 
-928.94 -287.96  -21.33  150.04 2268.59 

Coefficients:
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)      238.42      68.62   3.475 0.000542 ***
monthFebruary     53.85      82.57   0.652 0.514493    
monthMarch       261.27      81.51   3.205 0.001409 ** 
monthApril      -217.09      83.67  -2.595 0.009665 ** 
monthMay        -269.06      83.02  -3.241 0.001246 ** 
monthJune       -225.25      83.67  -2.692 0.007265 ** 
monthJuly       -265.07      83.02  -3.193 0.001470 ** 
monthAugust      142.77      83.02   1.720 0.085914 .  
monthSeptember   474.25      83.67   5.668 2.09e-08 ***
monthOctober     463.99      83.02   5.589 3.25e-08 ***
monthNovember    256.21      83.67   3.062 0.002280 ** 
monthDecember     -9.41      83.02  -0.113 0.909785    
year_typeCovid   216.28      37.98   5.694 1.81e-08 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 450 on 716 degrees of freedom
Multiple R-squared:  0.2877,	Adjusted R-squared:  0.2757 
F-statistic:  24.1 on 12 and 716 DF,  p-value: < 2.2e-16

    Communicators linear model 

    communicators

    A data.frame: 729 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    2019-03-29T00:00:00Z2019MarchFriday 20625.7281653Normal
    2019-03-30T00:00:00Z2019MarchSaturday 18420.6521738Normal
    2019-03-31T00:00:00Z2019MarchSunday 18524.3243245Normal
    2019-04-01T00:00:00Z2019AprilMonday 32822.8658575Normal
    2019-04-02T00:00:00Z2019AprilTuesday 14333.5664348Normal
    2019-04-03T00:00:00Z2019AprilWednesday27116.6051745Normal
    2019-04-04T00:00:00Z2019AprilThursday 38113.3858351Normal
    2019-04-05T00:00:00Z2019AprilFriday 19024.7368447Normal
    2019-04-06T00:00:00Z2019AprilSaturday 16326.9938744Normal
    2019-04-07T00:00:00Z2019AprilSunday 15931.4465450Normal
    2019-04-08T00:00:00Z2019AprilMonday 16325.7668742Normal
    2019-04-09T00:00:00Z2019AprilTuesday 14831.0810846Normal
    2019-04-10T00:00:00Z2019AprilWednesday16330.6748550Normal
    2019-04-11T00:00:00Z2019AprilThursday 13938.1295053Normal
    2019-04-12T00:00:00Z2019AprilFriday 15529.6774246Normal
    2019-04-13T00:00:00Z2019AprilSaturday 14330.0699343Normal
    2019-04-14T00:00:00Z2019AprilSunday 14028.5714340Normal
    2019-04-15T00:00:00Z2019AprilMonday 17029.4117650Normal
    2019-04-16T00:00:00Z2019AprilTuesday 15040.6666761Normal
    2019-04-17T00:00:00Z2019AprilWednesday15334.6405253Normal
    2019-04-18T00:00:00Z2019AprilThursday 16743.7125773Normal
    2019-04-19T00:00:00Z2019AprilFriday 16233.9506255Normal
    2019-04-20T00:00:00Z2019AprilSaturday 33715.1335351Normal
    2019-04-21T00:00:00Z2019AprilSunday 17225.0000043Normal
    2019-04-22T00:00:00Z2019AprilMonday 16224.0740739Normal
    2019-04-23T00:00:00Z2019AprilTuesday 16335.5828258Normal
    2019-04-24T00:00:00Z2019AprilWednesday34015.2941252Normal
    2019-04-25T00:00:00Z2019AprilThursday 19626.5306152Normal
    2019-04-26T00:00:00Z2019AprilFriday 37116.9811363Normal
    2019-04-27T00:00:00Z2019AprilSaturday 20127.8607056Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 17223.25581440Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 16719.16167732Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 20820.67307743Covid
    2021-02-28T00:00:00Z2021FebruarySunday 16717.96407230Covid
    2021-03-01T00:00:00Z2021March Monday 16418.29268330Covid
    2021-03-02T00:00:00Z2021March Tuesday 19915.07537730Covid
    2021-03-03T00:00:00Z2021March Wednesday16318.40490830Covid
    2021-03-04T00:00:00Z2021March Thursday 16320.85889634Covid
    2021-03-05T00:00:00Z2021March Friday 17917.31843631Covid
    2021-03-06T00:00:00Z2021March Saturday 304 9.53947429Covid
    2021-03-07T00:00:00Z2021March Sunday 16215.43209925Covid
    2021-03-08T00:00:00Z2021March Monday 23413.67521432Covid
    2021-03-09T00:00:00Z2021March Tuesday 16023.12500037Covid
    2021-03-10T00:00:00Z2021March Wednesday15620.51282132Covid
    2021-03-11T00:00:00Z2021March Thursday 553 7.23327340Covid
    2021-03-12T00:00:00Z2021March Friday 25314.62450637Covid
    2021-03-13T00:00:00Z2021March Saturday 23714.34599234Covid
    2021-03-14T00:00:00Z2021March Sunday 14720.40816330Covid
    2021-03-15T00:00:00Z2021March Monday 15418.83116929Covid
    2021-03-16T00:00:00Z2021March Tuesday 15421.42857133Covid
    2021-03-17T00:00:00Z2021March Wednesday14121.98581631Covid
    2021-03-18T00:00:00Z2021March Thursday 15320.26143831Covid
    2021-03-19T00:00:00Z2021March Friday 26819.40298552Covid
    2021-03-20T00:00:00Z2021March Saturday 658 6.38297942Covid
    2021-03-21T00:00:00Z2021March Sunday 17023.52941240Covid
    2021-03-22T00:00:00Z2021March Monday 17422.41379339Covid
    2021-03-23T00:00:00Z2021March Tuesday 14316.78321724Covid
    2021-03-24T00:00:00Z2021March Wednesday15717.19745227Covid
    2021-03-25T00:00:00Z2021March Thursday 16525.45454542Covid
    2021-03-26T00:00:00Z2021March Friday 573 6.10820235Covid
     

    communicators_lm = lm(total_communicated ~ month + year_type, data = communicators)
print(summary(communicators_lm))

    Call:
lm(formula = total_communicated ~ month + year_type, data = communicators)

Residuals:
    Min      1Q  Median      3Q     Max 
-39.805  -7.258  -1.258   5.628  77.195 

Coefficients:
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)     42.1266     1.9689  21.396  < 2e-16 ***
monthFebruary    4.9875     2.3693   2.105  0.03563 *  
monthMarch       2.7318     2.3388   1.168  0.24318    
monthApril       7.5910     2.4009   3.162  0.00163 ** 
monthMay        -0.3536     2.3821  -0.148  0.88203    
monthJune       -0.4757     2.4009  -0.198  0.84300    
monthJuly       -1.8698     2.3821  -0.785  0.43277    
monthAugust     20.6786     2.3821   8.681  < 2e-16 ***
monthSeptember  41.6910     2.4009  17.365  < 2e-16 ***
monthOctober    23.1141     2.3821   9.703  < 2e-16 ***
monthNovember   12.7410     2.4009   5.307 1.49e-07 ***
monthDecember   -4.6601     2.3821  -1.956  0.05082 .  
year_typeCovid  -8.8685     1.0899  -8.137 1.79e-15 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 12.91 on 716 degrees of freedom
Multiple R-squared:  0.552,	Adjusted R-squared:  0.5445 
F-statistic: 73.53 on 12 and 716 DF,  p-value: < 2.2e-16

    Testing Year Effect

    After our group presented our project, our professor was concerned that there was confounding variables that the anova test had not factored in. Thus for our final report, we generated multiple regression models

    New members multiple regression model 

    joins

    A data.frame: 729 × 8
    interval_start_timestampyearmonthdaynew_memberspct_communicatedpct_opened_channelsyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    2019-03-29T00:00:00Z2019MarchFriday 2 50.00000 50.00000Normal
    2019-03-30T00:00:00Z2019MarchSaturday 6 16.66667 33.33333Normal
    2019-03-31T00:00:00Z2019MarchSunday 8 25.00000 37.50000Normal
    2019-04-01T00:00:00Z2019AprilMonday 9 44.44444 33.33333Normal
    2019-04-02T00:00:00Z2019AprilTuesday 2 50.00000100.00000Normal
    2019-04-03T00:00:00Z2019AprilWednesday0 NA NANormal
    2019-04-04T00:00:00Z2019AprilThursday 2100.00000100.00000Normal
    2019-04-05T00:00:00Z2019AprilFriday 3 33.33333 0.00000Normal
    2019-04-06T00:00:00Z2019AprilSaturday 2 0.00000 0.00000Normal
    2019-04-07T00:00:00Z2019AprilSunday 2 0.00000 0.00000Normal
    2019-04-08T00:00:00Z2019AprilMonday 9 33.33333 33.33333Normal
    2019-04-09T00:00:00Z2019AprilTuesday 3 33.33333 33.33333Normal
    2019-04-10T00:00:00Z2019AprilWednesday1100.00000100.00000Normal
    2019-04-11T00:00:00Z2019AprilThursday 1 0.00000100.00000Normal
    2019-04-12T00:00:00Z2019AprilFriday 1 0.00000100.00000Normal
    2019-04-13T00:00:00Z2019AprilSaturday 1 0.00000100.00000Normal
    2019-04-14T00:00:00Z2019AprilSunday 0 NA NANormal
    2019-04-15T00:00:00Z2019AprilMonday 0 NA NANormal
    2019-04-16T00:00:00Z2019AprilTuesday 3 66.66667 0.00000Normal
    2019-04-17T00:00:00Z2019AprilWednesday5 0.00000 20.00000Normal
    2019-04-18T00:00:00Z2019AprilThursday 3100.00000 33.33333Normal
    2019-04-19T00:00:00Z2019AprilFriday 3 0.00000 33.33333Normal
    2019-04-20T00:00:00Z2019AprilSaturday 0 NA NANormal
    2019-04-21T00:00:00Z2019AprilSunday 1100.00000100.00000Normal
    2019-04-22T00:00:00Z2019AprilMonday 0 NA NANormal
    2019-04-23T00:00:00Z2019AprilTuesday 1 0.00000 0.00000Normal
    2019-04-24T00:00:00Z2019AprilWednesday3 33.33333 0.00000Normal
    2019-04-25T00:00:00Z2019AprilThursday 3 66.66667 66.66667Normal
    2019-04-26T00:00:00Z2019AprilFriday 3 33.33333 33.33333Normal
    2019-04-27T00:00:00Z2019AprilSaturday 1100.00000 0.00000Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 1 0.00000100.00000Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 540.00000100.00000Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 812.50000100.00000Covid
    2021-02-28T00:00:00Z2021FebruarySunday 520.00000100.00000Covid
    2021-03-01T00:00:00Z2021March Monday 2 0.00000 50.00000Covid
    2021-03-02T00:00:00Z2021March Tuesday 616.66667 16.66667Covid
    2021-03-03T00:00:00Z2021March Wednesday 5 0.00000 40.00000Covid
    2021-03-04T00:00:00Z2021March Thursday 8 0.00000 62.50000Covid
    2021-03-05T00:00:00Z2021March Friday 333.33333 33.33333Covid
    2021-03-06T00:00:00Z2021March Saturday 3 0.00000 66.66667Covid
    2021-03-07T00:00:00Z2021March Sunday 3 0.00000 33.33333Covid
    2021-03-08T00:00:00Z2021March Monday 714.28571 42.85714Covid
    2021-03-09T00:00:00Z2021March Tuesday 7 0.00000 57.14286Covid
    2021-03-10T00:00:00Z2021March Wednesday 5 0.00000 40.00000Covid
    2021-03-11T00:00:00Z2021March Thursday 1 0.00000100.00000Covid
    2021-03-12T00:00:00Z2021March Friday 1118.18182 45.45455Covid
    2021-03-13T00:00:00Z2021March Saturday 4 0.00000 50.00000Covid
    2021-03-14T00:00:00Z2021March Sunday 1 0.00000 0.00000Covid
    2021-03-15T00:00:00Z2021March Monday 1 0.00000 0.00000Covid
    2021-03-16T00:00:00Z2021March Tuesday 6 0.00000 83.33333Covid
    2021-03-17T00:00:00Z2021March Wednesday 7 0.00000 71.42857Covid
    2021-03-18T00:00:00Z2021March Thursday 1 0.00000 0.00000Covid
    2021-03-19T00:00:00Z2021March Friday 5 0.00000 80.00000Covid
    2021-03-20T00:00:00Z2021March Saturday 2 0.00000 0.00000Covid
    2021-03-21T00:00:00Z2021March Sunday 633.33333 33.33333Covid
    2021-03-22T00:00:00Z2021March Monday 520.00000 60.00000Covid
    2021-03-23T00:00:00Z2021March Tuesday 1 0.00000 0.00000Covid
    2021-03-24T00:00:00Z2021March Wednesday 4 0.00000 50.00000Covid
    2021-03-25T00:00:00Z2021March Thursday 1 0.00000 0.00000Covid
    2021-03-26T00:00:00Z2021March Friday 4 NA NACovid
     

    joins_lm = lm(new_members ~ month + year + year_type, data = joins)
print(summary(joins_lm))

    Call:
lm(formula = new_members ~ month + year + year_type, data = joins)

Residuals:
   Min     1Q Median     3Q    Max 
-8.751 -2.100 -0.594  0.789 85.461 

Coefficients: (1 not defined because of singularities)
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)     1.10756    0.89191   1.242 0.214722    
monthFebruary   0.27963    0.96663   0.289 0.772452    
monthMarch      0.10295    0.95562   0.108 0.914240    
monthApril      1.48651    1.05476   1.409 0.159174    
monthMay        0.51231    1.04767   0.489 0.624990    
monthJune       0.41984    1.05476   0.398 0.690719    
monthJuly       0.57683    1.04767   0.551 0.582092    
monthAugust     7.43167    1.04767   7.094 3.15e-12 ***
monthSeptember  5.16984    1.05476   4.901 1.18e-06 ***
monthOctober    3.10909    1.04767   2.968 0.003101 ** 
monthNovember   3.13651    1.05476   2.974 0.003042 ** 
monthDecember   0.09296    1.04767   0.089 0.929323    
year2020        1.21187    0.44469   2.725 0.006584 ** 
year2021        2.99237    0.90010   3.324 0.000931 ***
year_typeCovid       NA         NA      NA       NA    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 5.268 on 715 degrees of freedom
Multiple R-squared:  0.1535,	Adjusted R-squared:  0.1381 
F-statistic: 9.971 on 13 and 715 DF,  p-value: < 2.2e-16

    Total messages multiple regression model 

    messages

    A data.frame: 729 × 7
    interval_start_timestampyearmonthdaymessagesmessages_per_communicatoryear_type
    <chr><fct><fct><fct><int><dbl><fct>
    2019-03-29T00:00:00Z2019MarchFriday 334 6.301887Normal
    2019-03-30T00:00:00Z2019MarchSaturday 236 6.210526Normal
    2019-03-31T00:00:00Z2019MarchSunday 364 8.088889Normal
    2019-04-01T00:00:00Z2019AprilMonday 404 5.386667Normal
    2019-04-02T00:00:00Z2019AprilTuesday 54311.312500Normal
    2019-04-03T00:00:00Z2019AprilWednesday 324 7.200000Normal
    2019-04-04T00:00:00Z2019AprilThursday 55610.901961Normal
    2019-04-05T00:00:00Z2019AprilFriday 273 5.808511Normal
    2019-04-06T00:00:00Z2019AprilSaturday 335 7.613636Normal
    2019-04-07T00:00:00Z2019AprilSunday 110222.040000Normal
    2019-04-08T00:00:00Z2019AprilMonday 188 4.476190Normal
    2019-04-09T00:00:00Z2019AprilTuesday 399 8.673913Normal
    2019-04-10T00:00:00Z2019AprilWednesday 53110.620000Normal
    2019-04-11T00:00:00Z2019AprilThursday 68913.000000Normal
    2019-04-12T00:00:00Z2019AprilFriday 418 9.086957Normal
    2019-04-13T00:00:00Z2019AprilSaturday 56613.162791Normal
    2019-04-14T00:00:00Z2019AprilSunday 48112.025000Normal
    2019-04-15T00:00:00Z2019AprilMonday 65913.180000Normal
    2019-04-16T00:00:00Z2019AprilTuesday 77912.770492Normal
    2019-04-17T00:00:00Z2019AprilWednesday 59611.245283Normal
    2019-04-18T00:00:00Z2019AprilThursday 114315.657534Normal
    2019-04-19T00:00:00Z2019AprilFriday 89816.327273Normal
    2019-04-20T00:00:00Z2019AprilSaturday 331 6.490196Normal
    2019-04-21T00:00:00Z2019AprilSunday 47311.000000Normal
    2019-04-22T00:00:00Z2019AprilMonday 283 7.256410Normal
    2019-04-23T00:00:00Z2019AprilTuesday 127021.896552Normal
    2019-04-24T00:00:00Z2019AprilWednesday 74614.346154Normal
    2019-04-25T00:00:00Z2019AprilThursday 287 5.519231Normal
    2019-04-26T00:00:00Z2019AprilFriday 72811.555556Normal
    2019-04-27T00:00:00Z2019AprilSaturday 69112.339286Normal
    ⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 1383.450000Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 782.437500Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 932.162791Covid
    2021-02-28T00:00:00Z2021FebruarySunday 461.533333Covid
    2021-03-01T00:00:00Z2021March Monday 531.766667Covid
    2021-03-02T00:00:00Z2021March Tuesday 722.400000Covid
    2021-03-03T00:00:00Z2021March Wednesday1224.066667Covid
    2021-03-04T00:00:00Z2021March Thursday 1684.941176Covid
    2021-03-05T00:00:00Z2021March Friday 742.387097Covid
    2021-03-06T00:00:00Z2021March Saturday 431.482759Covid
    2021-03-07T00:00:00Z2021March Sunday 431.720000Covid
    2021-03-08T00:00:00Z2021March Monday 1063.312500Covid
    2021-03-09T00:00:00Z2021March Tuesday 1143.081081Covid
    2021-03-10T00:00:00Z2021March Wednesday 832.593750Covid
    2021-03-11T00:00:00Z2021March Thursday 1092.725000Covid
    2021-03-12T00:00:00Z2021March Friday 752.027027Covid
    2021-03-13T00:00:00Z2021March Saturday 1584.647059Covid
    2021-03-14T00:00:00Z2021March Sunday 732.433333Covid
    2021-03-15T00:00:00Z2021March Monday 732.517241Covid
    2021-03-16T00:00:00Z2021March Tuesday 521.575758Covid
    2021-03-17T00:00:00Z2021March Wednesday 642.064516Covid
    2021-03-18T00:00:00Z2021March Thursday 652.096774Covid
    2021-03-19T00:00:00Z2021March Friday 1823.500000Covid
    2021-03-20T00:00:00Z2021March Saturday 1212.880952Covid
    2021-03-21T00:00:00Z2021March Sunday 1573.925000Covid
    2021-03-22T00:00:00Z2021March Monday 942.410256Covid
    2021-03-23T00:00:00Z2021March Tuesday 341.416667Covid
    2021-03-24T00:00:00Z2021March Wednesday 511.888889Covid
    2021-03-25T00:00:00Z2021March Thursday 1202.857143Covid
    2021-03-26T00:00:00Z2021March Friday 1223.485714Covid
     

    messages_lm = lm(messages ~ month + year +  year_type, data = messages)
print(summary(messages_lm))

    Call:
lm(formula = messages ~ month + year + year_type, data = messages)

Residuals:
    Min      1Q  Median      3Q     Max 
-533.05 -127.07  -32.48   66.92 2435.13 

Coefficients: (1 not defined because of singularities)
                Estimate Std. Error t value Pr(>|t|)    
(Intercept)     441.7623    41.0836  10.753  < 2e-16 ***
monthFebruary    -0.5282    44.5253  -0.012  0.99054    
monthMarch        9.4722    44.0183   0.215  0.82968    
monthApril       81.9887    48.5851   1.688  0.09194 .  
monthMay        -47.0322    48.2583  -0.975  0.33009    
monthJune      -145.6279    48.5851  -2.997  0.00282 ** 
monthJuly      -114.0806    48.2583  -2.364  0.01835 *  
monthAugust     138.5968    48.2583   2.872  0.00420 ** 
monthSeptember  362.2887    48.5851   7.457 2.57e-13 ***
monthOctober    190.3065    48.2583   3.943 8.82e-05 ***
monthNovember    38.2887    48.5851   0.788  0.43091    
monthDecember  -151.4838    48.2583  -3.139  0.00176 ** 
year2020       -192.2022    20.4837  -9.383  < 2e-16 ***
year2021       -336.8387    41.4610  -8.124 1.98e-15 ***
year_typeCovid        NA         NA      NA       NA    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 242.6 on 715 degrees of freedom
Multiple R-squared:  0.3827,	Adjusted R-squared:  0.3714 
F-statistic: 34.09 on 13 and 715 DF,  p-value: < 2.2e-16

    Voices multiple regression model 

    voices

    A data.frame: 729 × 6
    interval_start_timestampyearmonthdayspeaking_minutesyear_type
    <chr><fct><fct><fct><int><fct>
    2019-03-29T00:00:00Z2019MarchFriday 0Normal
    2019-03-30T00:00:00Z2019MarchSaturday 0Normal
    2019-03-31T00:00:00Z2019MarchSunday 0Normal
    2019-04-01T00:00:00Z2019AprilMonday 0Normal
    2019-04-02T00:00:00Z2019AprilTuesday 0Normal
    2019-04-03T00:00:00Z2019AprilWednesday0Normal
    2019-04-04T00:00:00Z2019AprilThursday 0Normal
    2019-04-05T00:00:00Z2019AprilFriday 0Normal
    2019-04-06T00:00:00Z2019AprilSaturday 0Normal
    2019-04-07T00:00:00Z2019AprilSunday 0Normal
    2019-04-08T00:00:00Z2019AprilMonday 0Normal
    2019-04-09T00:00:00Z2019AprilTuesday 0Normal
    2019-04-10T00:00:00Z2019AprilWednesday0Normal
    2019-04-11T00:00:00Z2019AprilThursday 0Normal
    2019-04-12T00:00:00Z2019AprilFriday 0Normal
    2019-04-13T00:00:00Z2019AprilSaturday 0Normal
    2019-04-14T00:00:00Z2019AprilSunday 0Normal
    2019-04-15T00:00:00Z2019AprilMonday 0Normal
    2019-04-16T00:00:00Z2019AprilTuesday 0Normal
    2019-04-17T00:00:00Z2019AprilWednesday0Normal
    2019-04-18T00:00:00Z2019AprilThursday 0Normal
    2019-04-19T00:00:00Z2019AprilFriday 0Normal
    2019-04-20T00:00:00Z2019AprilSaturday 0Normal
    2019-04-21T00:00:00Z2019AprilSunday 0Normal
    2019-04-22T00:00:00Z2019AprilMonday 0Normal
    2019-04-23T00:00:00Z2019AprilTuesday 0Normal
    2019-04-24T00:00:00Z2019AprilWednesday0Normal
    2019-04-25T00:00:00Z2019AprilThursday 0Normal
    2019-04-26T00:00:00Z2019AprilFriday 0Normal
    2019-04-27T00:00:00Z2019AprilSaturday 0Normal
    ⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 1495Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 913Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 1118Covid
    2021-02-28T00:00:00Z2021FebruarySunday 1354Covid
    2021-03-01T00:00:00Z2021March Monday 1269Covid
    2021-03-02T00:00:00Z2021March Tuesday 1200Covid
    2021-03-03T00:00:00Z2021March Wednesday2031Covid
    2021-03-04T00:00:00Z2021March Thursday 2293Covid
    2021-03-05T00:00:00Z2021March Friday 1124Covid
    2021-03-06T00:00:00Z2021March Saturday 1398Covid
    2021-03-07T00:00:00Z2021March Sunday 1460Covid
    2021-03-08T00:00:00Z2021March Monday 1834Covid
    2021-03-09T00:00:00Z2021March Tuesday 1523Covid
    2021-03-10T00:00:00Z2021March Wednesday1119Covid
    2021-03-11T00:00:00Z2021March Thursday 1878Covid
    2021-03-12T00:00:00Z2021March Friday 1429Covid
    2021-03-13T00:00:00Z2021March Saturday 730Covid
    2021-03-14T00:00:00Z2021March Sunday 567Covid
    2021-03-15T00:00:00Z2021March Monday 1282Covid
    2021-03-16T00:00:00Z2021March Tuesday 1234Covid
    2021-03-17T00:00:00Z2021March Wednesday1146Covid
    2021-03-18T00:00:00Z2021March Thursday 2464Covid
    2021-03-19T00:00:00Z2021March Friday 840Covid
    2021-03-20T00:00:00Z2021March Saturday 428Covid
    2021-03-21T00:00:00Z2021March Sunday 880Covid
    2021-03-22T00:00:00Z2021March Monday 1598Covid
    2021-03-23T00:00:00Z2021March Tuesday 873Covid
    2021-03-24T00:00:00Z2021March Wednesday 771Covid
    2021-03-25T00:00:00Z2021March Thursday 1742Covid
    2021-03-26T00:00:00Z2021March Friday 1038Covid
     

    voices_lm = lm(speaking_minutes ~ month + year + year_type, data = voices)
summary(voices_lm)

    Call:
lm(formula = speaking_minutes ~ month + year + year_type, data = voices)

Residuals:
    Min      1Q  Median      3Q     Max 
-925.30 -193.30  -24.96  135.36 2264.95 

Coefficients: (1 not defined because of singularities)
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)     -146.89      68.66  -2.139   0.0327 *  
monthFebruary     60.74      74.41   0.816   0.4146    
monthMarch       313.25      73.56   4.258 2.33e-05 ***
monthApril       171.85      81.19   2.117   0.0346 *  
monthMay         119.88      80.65   1.487   0.1376    
monthJune        163.68      81.19   2.016   0.0442 *  
monthJuly        123.87      80.65   1.536   0.1250    
monthAugust      531.71      80.65   6.593 8.37e-11 ***
monthSeptember   863.18      81.19  10.631  < 2e-16 ***
monthOctober     852.93      80.65  10.576  < 2e-16 ***
monthNovember    645.15      81.19   7.946 7.50e-15 ***
monthDecember    379.53      80.65   4.706 3.03e-06 ***
year2020         209.00      34.23   6.106 1.68e-09 ***
year2021         994.15      69.29  14.348  < 2e-16 ***
year_typeCovid       NA         NA      NA       NA    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 405.5 on 715 degrees of freedom
Multiple R-squared:  0.4224,	Adjusted R-squared:  0.4119 
F-statistic: 40.22 on 13 and 715 DF,  p-value: < 2.2e-16

    Communicators multiple regression model 

    communicators

    A data.frame: 729 × 8
    interval_start_timestampyearmonthdayvisitorspct_communicatedtotal_communicatedyear_type
    <chr><fct><fct><fct><int><dbl><dbl><fct>
    2019-03-29T00:00:00Z2019MarchFriday 20625.7281653Normal
    2019-03-30T00:00:00Z2019MarchSaturday 18420.6521738Normal
    2019-03-31T00:00:00Z2019MarchSunday 18524.3243245Normal
    2019-04-01T00:00:00Z2019AprilMonday 32822.8658575Normal
    2019-04-02T00:00:00Z2019AprilTuesday 14333.5664348Normal
    2019-04-03T00:00:00Z2019AprilWednesday27116.6051745Normal
    2019-04-04T00:00:00Z2019AprilThursday 38113.3858351Normal
    2019-04-05T00:00:00Z2019AprilFriday 19024.7368447Normal
    2019-04-06T00:00:00Z2019AprilSaturday 16326.9938744Normal
    2019-04-07T00:00:00Z2019AprilSunday 15931.4465450Normal
    2019-04-08T00:00:00Z2019AprilMonday 16325.7668742Normal
    2019-04-09T00:00:00Z2019AprilTuesday 14831.0810846Normal
    2019-04-10T00:00:00Z2019AprilWednesday16330.6748550Normal
    2019-04-11T00:00:00Z2019AprilThursday 13938.1295053Normal
    2019-04-12T00:00:00Z2019AprilFriday 15529.6774246Normal
    2019-04-13T00:00:00Z2019AprilSaturday 14330.0699343Normal
    2019-04-14T00:00:00Z2019AprilSunday 14028.5714340Normal
    2019-04-15T00:00:00Z2019AprilMonday 17029.4117650Normal
    2019-04-16T00:00:00Z2019AprilTuesday 15040.6666761Normal
    2019-04-17T00:00:00Z2019AprilWednesday15334.6405253Normal
    2019-04-18T00:00:00Z2019AprilThursday 16743.7125773Normal
    2019-04-19T00:00:00Z2019AprilFriday 16233.9506255Normal
    2019-04-20T00:00:00Z2019AprilSaturday 33715.1335351Normal
    2019-04-21T00:00:00Z2019AprilSunday 17225.0000043Normal
    2019-04-22T00:00:00Z2019AprilMonday 16224.0740739Normal
    2019-04-23T00:00:00Z2019AprilTuesday 16335.5828258Normal
    2019-04-24T00:00:00Z2019AprilWednesday34015.2941252Normal
    2019-04-25T00:00:00Z2019AprilThursday 19626.5306152Normal
    2019-04-26T00:00:00Z2019AprilFriday 37116.9811363Normal
    2019-04-27T00:00:00Z2019AprilSaturday 20127.8607056Normal
    ⋮⋮⋮⋮⋮⋮⋮⋮
    2021-02-25T00:00:00Z2021FebruaryThursday 17223.25581440Covid
    2021-02-26T00:00:00Z2021FebruaryFriday 16719.16167732Covid
    2021-02-27T00:00:00Z2021FebruarySaturday 20820.67307743Covid
    2021-02-28T00:00:00Z2021FebruarySunday 16717.96407230Covid
    2021-03-01T00:00:00Z2021March Monday 16418.29268330Covid
    2021-03-02T00:00:00Z2021March Tuesday 19915.07537730Covid
    2021-03-03T00:00:00Z2021March Wednesday16318.40490830Covid
    2021-03-04T00:00:00Z2021March Thursday 16320.85889634Covid
    2021-03-05T00:00:00Z2021March Friday 17917.31843631Covid
    2021-03-06T00:00:00Z2021March Saturday 304 9.53947429Covid
    2021-03-07T00:00:00Z2021March Sunday 16215.43209925Covid
    2021-03-08T00:00:00Z2021March Monday 23413.67521432Covid
    2021-03-09T00:00:00Z2021March Tuesday 16023.12500037Covid
    2021-03-10T00:00:00Z2021March Wednesday15620.51282132Covid
    2021-03-11T00:00:00Z2021March Thursday 553 7.23327340Covid
    2021-03-12T00:00:00Z2021March Friday 25314.62450637Covid
    2021-03-13T00:00:00Z2021March Saturday 23714.34599234Covid
    2021-03-14T00:00:00Z2021March Sunday 14720.40816330Covid
    2021-03-15T00:00:00Z2021March Monday 15418.83116929Covid
    2021-03-16T00:00:00Z2021March Tuesday 15421.42857133Covid
    2021-03-17T00:00:00Z2021March Wednesday14121.98581631Covid
    2021-03-18T00:00:00Z2021March Thursday 15320.26143831Covid
    2021-03-19T00:00:00Z2021March Friday 26819.40298552Covid
    2021-03-20T00:00:00Z2021March Saturday 658 6.38297942Covid
    2021-03-21T00:00:00Z2021March Sunday 17023.52941240Covid
    2021-03-22T00:00:00Z2021March Monday 17422.41379339Covid
    2021-03-23T00:00:00Z2021March Tuesday 14316.78321724Covid
    2021-03-24T00:00:00Z2021March Wednesday15717.19745227Covid
    2021-03-25T00:00:00Z2021March Thursday 16525.45454542Covid
    2021-03-26T00:00:00Z2021March Friday 573 6.10820235Covid
     

    communicators_lm = lm(total_communicated ~ month + year + year_type, data = communicators)
summary(communicators_lm)

    Call:
lm(formula = total_communicated ~ month + year + year_type, data = communicators)

Residuals:
    Min      1Q  Median      3Q     Max 
-39.780  -7.398  -1.624   6.070  77.220 

Coefficients: (1 not defined because of singularities)
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)      44.837      2.175  20.612  < 2e-16 ***
monthFebruary     4.939      2.357   2.095  0.03652 *  
monthMarch        2.366      2.331   1.015  0.31033    
monthApril        4.855      2.572   1.887  0.05953 .  
monthMay         -3.090      2.555  -1.209  0.22696    
monthJune        -3.212      2.572  -1.249  0.21223    
monthJuly        -4.606      2.555  -1.803  0.07187 .  
monthAugust      17.942      2.555   7.022 5.09e-12 ***
monthSeptember   38.955      2.572  15.143  < 2e-16 ***
monthOctober     20.378      2.555   7.975 6.03e-15 ***
monthNovember    10.005      2.572   3.889  0.00011 ***
monthDecember    -7.396      2.555  -2.895  0.00391 ** 
year2020         -8.817      1.085  -8.130 1.89e-15 ***
year2021        -14.341      2.195  -6.533 1.23e-10 ***
year_typeCovid       NA         NA      NA       NA    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 12.85 on 715 degrees of freedom
Multiple R-squared:  0.5571,	Adjusted R-squared:  0.5491 
F-statistic: 69.19 on 13 and 715 DF,  p-value: < 2.2e-16