adding characteristic tests with outcomes
This commit is contained in:
mjgaughan
parent
586e46641d
commit
8b887a6af5
878
R/.Rhistory
878
R/.Rhistory
@ -1,442 +1,3 @@
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time_plot <- all_actions_data |>
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ggplot(aes(x=week_offset, y=log1p_count, color=factor(document_type))) +
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geom_smooth() +
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geom_vline(x=0)+
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theme_bw() +
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theme(legend.position = "top")
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time_plot
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time_plot <- all_actions_data |>
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ggplot(aes(x=week_offset, y=log1p_count, color=factor(document_type))) +
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geom_smooth() +
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geom_vline(x=0)+
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theme_bw() +
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theme(legend.position = "top")
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time_plot <- all_actions_data |>
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ggplot(aes(x=week_offset, y=log1p_count, color=factor(document_type))) +
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geom_smooth() +
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geom_vline(0)+
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theme_bw() +
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theme(legend.position = "top")
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time_plot
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time_plot <- all_actions_data |>
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ggplot(aes(x=week_offset, y=log1p_count, color=factor(document_type))) +
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geom_smooth() +
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geom_vline(xintercept = 0)+
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theme_bw() +
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theme(legend.position = "top")
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time_plot
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#looking at event gap
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document_event_gap <- ggplot(all_actions_data, aes(x=event_gap, group=as.factor(document_type))) +
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geom_density(aes(color = as.factor(document_type), fill=as.factor(document_type)), alpha=0.2, position="identity") +
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theme_bw()
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document_event_gap
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#looking at event gap
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document_event_gap <- ggplot(all_actions_data, aes(x=scale(event_gap), group=as.factor(document_type))) +
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geom_density(aes(color = as.factor(document_type), fill=as.factor(document_type)), alpha=0.2, position="identity") +
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theme_bw()
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document_event_gap
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#looking at event gap
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mean(all_actions_readme_data$event_gap)
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sd(all_actions_readme_data$event_gap)
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mean(all_actions_contrib_data$event_gap)
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sd(all_actions_contrib_data$event_gap)
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mode(all_actions_contrib_data$event_gap)
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mean(all_actions_contrib_data$event_gap)
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library(tidyverse)
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contrib_df <- read_csv("../final_data/deb_contrib_did.csv")
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readme_df <- read_csv("../final_data/deb_readme_did.csv")
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hist(readme_df$event_gap)
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hist(readme_df$event_gap)
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mean(readme_df$event_gap)
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sd(readme_df$event_gap)
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min(readme_df$event_gap)
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count(readme_df$event_gap < 0)
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length(readme_df$event_gap < 0)
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table(readme_df$event_gap)
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table(contrib_df$event_gap)
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sum(readme_df$event_gap < 0)
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table(readme_df$event_gap)
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delta <- as.POSIXct(readme_df$event_date) - as.POSIXct(readme_df$first_commit_dt) -
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delta <- as.POSIXct(readme_df$event_date) - as.POSIXct(readme_df$first_commit_dt)
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delta <- as.POSIXct(readme_df$event_date) - as.POSIXct(readme_df$first_commit_dt)
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readme_df$asposixctED <- as.POSIXct(readme_df$event_date)
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View(readme_df)
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readme_df$asposixctFC <- as.POSIXct(readme_df$first_commit_dt)
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readme_df$new_delta <- readme_df$asposixctED - readme_df$asposixctFC
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View(readme_df)
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readme_df$new_delta <- as.numeric(readme_df$asposixctED - readme_df$asposixctFC, units="days")
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View(readme_df)
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readme_df$new_delta <- readme_df$asposixctED - readme_df$asposixctFC, units="days"
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readme_df$new_delta <- readme_df$asposixctED - readme_df$asposixctFC
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contrib_df <- read_csv("../final_data/deb_contrib_did.csv")
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readme_df <- read_csv("../final_data/deb_readme_did.csv")
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contrib_df <- contrib_df |>
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filter(event_gap >= 0)
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readme_df <- readme_df |>
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filter(event_gap >= 0)
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readme_df <- read_csv("../final_data/deb_readme_did.csv")
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sum(readme_df$event_gap < 0)
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sum(contrib_df$event_gap < 0)
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contrib_df <- read_csv("../final_data/deb_contrib_did.csv")
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sum(contrib_df$event_gap < 0)
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as.POSIXct(2016-02-20 02:31:00)-as.POSIXct(2009-02-06 16:31:05)
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as.POSIXct("2016-02-20 02:31:00")-as.POSIXct("2009-02-06 16:31:05")
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as.POSIXct("2016-11-29 13:34:52")-as.POSIXct("2014-07-11 08:36:39")
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as.POSIXct("2017-02-04 21:15:52")-as.POSIXct("2009-04-23 17:11:15")
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as.POSIXct("2019-01-17 23:15:08")-as.POSIXct("2007-11-28 09:50:01")
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contrib_df <- read_csv("../final_data/deb_contrib_did.csv")
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sum(contrib_df$event_gap < 0)
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as.POSIXct("2019-07-31 17:38:52")-as.POSIXct("2019-07-31 13:38:52")
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as.numeric(as.POSIXct("2019-07-31 17:38:52")-as.POSIXct("2019-07-31 13:38:52"), unit=days)
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as.numeric(as.POSIXct("2019-07-31 17:38:52")-as.POSIXct("2019-07-31 13:38:52"), unit="days")
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as.numeric(as.POSIXct("1998-08-13 15:43:39")-as.POSIXct("1998-08-13 11:43:39"), unit="days")
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as.numeric(as.POSIXct("2009-05-08 15:26:27")-as.POSIXct("2009-02-05 19:06:44"), unit="days")
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readme_df <- read_csv("../final_data/deb_readme_did.csv")
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results <- as.numeric(as.POSIXct(readme_df$event_date) - as.POSIXct(readme_df$first_commit_dt), unit="days")
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min(results)
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L1 <- as.POSIXct(c(
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"2019-07-31 17:38:52", "1998-08-13 15:43:39", "2009-05-08 15:26:27",
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"2011-03-22 14:02:38", "2009-10-09 09:54:44", "2009-04-29 23:16:59",
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"2009-08-15 08:12:16", "2014-07-11 19:14:56", "2008-10-21 14:00:00",
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"2016-08-15 21:55:21", "2000-06-18 14:00:37", "2000-11-05 00:12:44",
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"2009-04-23 21:23:12", "2010-09-19 12:36:20", "2007-11-28 14:50:01",
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"2013-08-09 18:25:49", "2005-05-07 21:52:07", "2004-01-27 19:53:06",
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"2015-11-16 04:44:13", "2014-06-11 23:19:07", "2008-04-15 05:23:34",
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"2015-02-08 10:08:15", "2008-06-20 10:52:21"
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))
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# L2 (provided list of ordered datetime values)
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L2 <- as.POSIXct(c(
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"2019-07-31 13:38:52", "1998-08-13 11:43:39", "2009-02-05 19:06:44",
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"2011-01-27 10:48:48", "2009-10-09 05:54:44", "2009-04-29 19:16:59",
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"2009-08-15 04:12:16", "2014-07-11 08:36:39", "2008-10-21 10:00:00",
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"2016-04-14 14:41:36", "2000-06-18 10:00:37", "2000-11-04 19:12:44",
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"2009-04-23 17:11:15", "2010-09-15 20:20:35", "2007-11-28 09:50:01",
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"2013-08-09 14:25:49", "2005-05-01 18:31:26", "2004-01-27 14:53:06",
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"2015-10-09 02:31:15", "2014-06-13 22:35:34", "2008-04-15 01:23:34",
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"2010-03-07 00:58:08", "2008-06-20 06:30:10"
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))
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# Calculate differences in days
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differences <- as.numeric(L2 - L1, units = "days")
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# Print the resulting differences
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print(differences)
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as.numeric(as.POSIXct("2011-03-22 14:02:38
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")-as.POSIXct("2011-01-27 10:48:48"), unit="days")
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as.numeric(as.POSIXct("2009-10-09 09:54:44
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")-as.POSIXct("2009-10-09 05:54:44
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"), unit="days")
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as.numeric(as.POSIXct("2009-04-29 23:16:59
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")-as.POSIXct("2009-04-29 19:16:59
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"), unit="days")
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as.numeric(as.POSIXct("2009-08-15 08:12:16
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")-as.POSIXct("2009-08-15 04:12:16
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"), unit="days")
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as.numeric(as.POSIXct("2014-07-11 19:14:56
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")-as.POSIXct("2014-07-11 08:36:39
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"), unit="days")
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as.numeric(as.POSIXct("2008-10-21 14:00:00
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")-as.POSIXct("2008-10-21 10:00:00
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"), unit="days")
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as.numeric(as.POSIXct("2016-08-15 21:55:21
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")-as.POSIXct("2016-04-14 14:41:36
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"), unit="days")
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as.numeric(as.POSIXct("2000-06-18 14:00:37
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")-as.POSIXct("2000-06-18 10:00:37
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"), unit="days")
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as.numeric(as.POSIXct("2000-11-05 00:12:44
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")-as.POSIXct("2000-11-04 19:12:44
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"), unit="days")
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as.numeric(as.POSIXct("2009-04-23 21:23:12
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")-as.POSIXct("2009-04-23 17:11:15
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"), unit="days")
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as.numeric(as.POSIXct("2010-09-19 12:36:20
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")-as.POSIXct("2010-09-15 20:20:35
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"), unit="days")
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as.numeric(as.POSIXct("2007-11-28 14:50:01
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")-as.POSIXct("2007-11-28 09:50:01
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"), unit="days")
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as.numeric(as.POSIXct("2013-08-09 18:25:49
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")-as.POSIXct("2013-08-09 14:25:49
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"), unit="days")
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as.numeric(as.POSIXct("2005-05-07 21:52:07
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")-as.POSIXct("2005-05-01 18:31:26
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"), unit="days")
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as.numeric(as.POSIXct("2004-01-27 19:53:06
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")-as.POSIXct("2004-01-27 14:53:06
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"), unit="days")
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as.numeric(as.POSIXct("2015-11-16 04:44:13
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")-as.POSIXct("2015-10-09 02:31:15
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"), unit="days")
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as.numeric(as.POSIXct("2014-06-11 23:19:07
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")-as.POSIXct("2014-06-13 22:35:34
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"), unit="days")
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as.numeric(as.POSIXct("2014-06-11 23:19:07
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")-as.POSIXct("2014-06-13 22:35:34
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"), unit="days")
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as.numeric(as.POSIXct("2008-04-15 05:23:34
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")-as.POSIXct("2008-04-15 01:23:34
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"), unit="days")
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as.numeric(as.POSIXct("2015-02-08 10:08:15
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")-as.POSIXct("2010-03-07 00:58:08
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"), unit="days")
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as.numeric(as.POSIXct("2008-06-20 10:52:21
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")-as.POSIXct("2008-06-20 06:30:10
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"), unit="days")
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as.numeric(as.POSIXct("2001-06-22 17:39:29
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")-as.POSIXct("2001-06-22 13:39:29
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"), unit="days")
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as.numeric(as.POSIXct("2013-05-15 12:13:50
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")-as.POSIXct("2013-05-15 08:13:50
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"), unit="days")
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as.numeric(as.POSIXct("2015-12-10 12:31:14
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")-as.POSIXct("2015-12-10 07:31:14
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"), unit="days")
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as.numeric(as.POSIXct("2013-02-07 15:58:18
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")-as.POSIXct("2013-02-07 10:58:18
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"), unit="days")
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as.numeric(as.POSIXct("2013-06-05 15:19:59
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")-as.POSIXct("2013-06-05 11:19:59
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"), unit="days")
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as.numeric(as.POSIXct("2016-02-24 21:54:34
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")-as.POSIXct("2016-02-24 16:54:34
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"), unit="days")
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as.numeric(as.POSIXct("2013-09-09 16:52:04
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")-as.POSIXct("2013-08-08 20:07:23
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"), unit="days")
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#all_gmodel <- glmer.nb(log1p_count ~ D * week_offset + scaled_project_age + scaled_event_gap + (D * week_offset | upstream_vcs_link),
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# control=glmerControl(optimizer="bobyqa",
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# optCtrl=list(maxfun=2e5)), nAGQ=0, data=all_actions_data)
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all_gmodel <- readRDS("0710_contrib_all.rda")
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"), unit="days")
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#all_gmodel <- glmer.nb(log1p_count ~ D * week_offset + scaled_project_age + scaled_event_gap + (D * week_offset | upstream_vcs_link),
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# control=glmerControl(optimizer="bobyqa",
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# optCtrl=list(maxfun=2e5)), nAGQ=0, data=all_actions_data)
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all_gmodel <- readRDS("0710_contrib_all.rda")
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summary(all_gmodel)
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as.numeric(as.POSIXct("2014-09-28 09:39:20
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")-as.POSIXct("2014-09-28 03:41:27
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"), unit="days")
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as.numeric(as.POSIXct("2011-08-27 03:10:24
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")-as.POSIXct("2011-08-26 23:10:24
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"), unit="days")
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as.numeric(as.POSIXct("2011-05-31 21:58:54
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")-as.POSIXct("2011-05-31 18:00:13
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"), unit="days")
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as.numeric(as.POSIXct("2015-11-10 20:33:50
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")-as.POSIXct("2015-11-10 15:33:50
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"), unit="days")
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as.numeric(as.POSIXct("2019-12-02 10:59:23
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")-as.POSIXct("2019-12-02 05:59:23
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"), unit="days")
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as.numeric(as.POSIXct("2019-12-02 11:00:24
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")-as.POSIXct("2019-12-02 06:00:24
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"), unit="days")
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as.numeric(as.POSIXct("2014-10-15 07:41:16
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")-as.POSIXct("2014-09-20 06:22:40
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"), unit="days")
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as.numeric(as.POSIXct("2015-05-13 13:28:36
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")-as.POSIXct("2015-05-13 09:28:36
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"), unit="days")
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as.numeric(as.POSIXct("2017-06-23 09:04:49
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")-as.POSIXct("2017-06-23 05:04:49
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"), unit="days")
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as.numeric(as.POSIXct("2015-09-22 16:31:10
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")-as.POSIXct("2015-09-01 14:47:44
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"), unit="days")
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as.numeric(as.POSIXct("2011-08-11 19:19:12
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")-as.POSIXct("2011-07-05 16:09:48
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"), unit="days")
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as.numeric(as.POSIXct("2017-02-02 11:34:37
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")-as.POSIXct("2017-02-01 05:48:49
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"), unit="days")
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as.numeric(as.POSIXct("1988-08-07 21:49:56
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")-as.POSIXct("1988-06-05 13:51:08
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"), unit="days")
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as.numeric(as.POSIXct("2013-01-26 21:18:26
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")-as.POSIXct("2013-01-26 16:18:26
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"), unit="days")
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as.numeric(as.POSIXct("2010-07-24 20:27:20
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")-as.POSIXct("2010-07-24 16:27:20
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"), unit="days")
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as.numeric(as.POSIXct("2008-04-20 04:45:51
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")-as.POSIXct("2008-02-23 06:53:28
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"), unit="days")
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as.numeric(as.POSIXct("2014-07-15 11:41:30
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")-as.POSIXct("2014-01-28 15:47:41
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"), unit="days")
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as.numeric(as.POSIXct("2019-05-28 14:40:24
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||||
")-as.POSIXct("2019-05-28 10:29:07
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"), unit="days")
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as.numeric(as.POSIXct("2009-02-03 09:41:14
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")-as.POSIXct("2009-02-01 17:37:33
|
||||
"), unit="days")
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as.numeric(as.POSIXct("2011-08-24 09:46:11
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")-as.POSIXct("2010-07-24 17:09:50
|
||||
"), unit="days")
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as.numeric(as.POSIXct("2017-03-29 07:30:12
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||||
")-as.POSIXct("2017-03-28 20:24:14
|
||||
"), unit="days")
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as.numeric(as.POSIXct("2013-04-04 21:58:36
|
||||
")-as.POSIXct("2013-04-04 17:58:36
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2018-02-06 08:23:27
|
||||
")-as.POSIXct("2018-02-04 20:54:04
|
||||
"), unit="days")
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as.numeric(as.POSIXct("2017-07-08 09:55:34
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||||
")-as.POSIXct("2017-07-08 05:30:53
|
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"), unit="days")
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as.numeric(as.POSIXct("2014-02-08 21:43:05
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")-as.POSIXct("2014-02-08 16:43:05
|
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"), unit="days")
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as.numeric(as.POSIXct("2012-12-06 20:08:36
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")-as.POSIXct("2012-12-06 15:08:36
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"), unit="days")
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as.numeric(as.POSIXct("2006-01-20 16:13:23
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")-as.POSIXct("2006-01-20 11:13:23
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"), unit="days")
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as.numeric(as.POSIXct("2009-04-25 13:02:20
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||||
")-as.POSIXct("2009-04-25 09:02:20
|
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"), unit="days")
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as.numeric(as.POSIXct("2015-11-06 19:02:05
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||||
")-as.POSIXct("2015-11-06 14:02:05
|
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"), unit="days")
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as.numeric(as.POSIXct("2015-09-07 03:35:11
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||||
")-as.POSIXct("2015-09-06 23:30:43
|
||||
"), unit="days")
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as.numeric(as.POSIXct("2010-07-15 09:55:52
|
||||
")-as.POSIXct("2010-07-15 05:55:52
|
||||
"), unit="days")
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||||
as.numeric(as.POSIXct("2007-09-21 09:19:24
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||||
")-as.POSIXct("2007-09-21 05:02:27
|
||||
"), unit="days")
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||||
as.numeric(as.POSIXct("2013-05-28 18:52:41
|
||||
")-as.POSIXct("2007-04-01 16:01:20
|
||||
"), unit="days")
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||||
as.numeric(as.POSIXct("2013-05-02 23:54:17
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||||
")-as.POSIXct("2013-05-02 19:54:17
|
||||
"), unit="days")
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||||
as.numeric(as.POSIXct("2013-04-02 17:43:49
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||||
")-as.POSIXct("2013-04-02 13:43:49
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2011-04-03 11:15:21
|
||||
")-as.POSIXct("2011-04-03 07:15:21
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2018-09-03 14:19:31
|
||||
")-as.POSIXct("2018-09-03 10:19:31
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2008-10-31 18:50:55
|
||||
")-as.POSIXct("2008-10-21 10:34:54
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2012-03-31 21:02:17
|
||||
")-as.POSIXct("2012-03-31 17:02:17
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2014-04-15 08:31:16
|
||||
")-as.POSIXct("2014-04-15 04:31:16
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2013-08-30 08:25:52
|
||||
")-as.POSIXct("2013-08-30 04:25:52
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2012-06-28 12:02:58
|
||||
")-as.POSIXct("2012-06-28 04:41:05
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2012-03-12 11:32:41
|
||||
")-as.POSIXct("2012-03-08 07:32:06
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2012-07-14 19:06:01
|
||||
")-as.POSIXct("2012-07-14 15:06:01
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2012-09-23 03:41:35
|
||||
")-as.POSIXct("2012-09-22 23:41:35
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2012-11-04 22:57:59
|
||||
")-as.POSIXct("2012-11-04 09:36:27
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2015-04-02 12:37:04
|
||||
")-as.POSIXct("2014-02-17 09:19:10
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2011-09-23 05:37:51
|
||||
")-as.POSIXct("2007-03-09 11:17:14
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2014-05-10 14:17:37
|
||||
")-as.POSIXct("2014-03-15 09:47:58
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2013-09-09 01:53:53
|
||||
")-as.POSIXct("2013-09-08 21:53:53
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2015-06-30 20:49:36
|
||||
")-as.POSIXct("2015-06-30 16:49:36
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2011-02-02 11:56:48
|
||||
")-as.POSIXct("2011-02-02 05:57:37
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2011-02-02 11:56:48
|
||||
")-as.POSIXct("2011-11-04 09:43:27
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2011-11-04 13:43:27
|
||||
")-as.POSIXct("2011-11-04 09:43:27
|
||||
"), unit="days")
|
||||
as.numeric(as.POSIXct("2009-01-22 01:08:05
|
||||
")-as.POSIXct("2007-03-23 16:50:26
|
||||
"), unit="days")
|
||||
contrib_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
contrib_df <- contrib_df |>
|
||||
filter(event_gap >= 0)
|
||||
readme_df <- readme_df |>
|
||||
filter(event_gap >= 0)
|
||||
hist(readme_df$event_gap)
|
||||
mean(readme_df$event_gap)
|
||||
sd(readme_df$event_gap)
|
||||
median(readme_df$event_gap)
|
||||
max(readme_df$event_gap)
|
||||
13871.64 / 365
|
||||
true_gap <- c()
|
||||
for (i in len(readme_df$event_date)){
|
||||
delta <- as.numeric(as.POSIXct(readme_df$event_date[i,])-as.POSIXct(readme_df$first_commit_dt[i,]), unit="days")
|
||||
true_gap <- c(true_gap, delta)
|
||||
}
|
||||
for (i in length(readme_df$event_date)){
|
||||
delta <- as.numeric(as.POSIXct(readme_df$event_date[i,])-as.POSIXct(readme_df$first_commit_dt[i,]), unit="days")
|
||||
true_gap <- c(true_gap, delta)
|
||||
}
|
||||
delta <- as.numeric(as.POSIXct(readme_df$event_date[i])-as.POSIXct(readme_df$first_commit_dt[i]), unit="days")
|
||||
for (i in length(readme_df$event_date)){
|
||||
delta <- as.numeric(as.POSIXct(readme_df$event_date[i])-as.POSIXct(readme_df$first_commit_dt[i]), unit="days")
|
||||
true_gap <- c(true_gap, delta)
|
||||
}
|
||||
true_gap
|
||||
for (i in length(readme_df$event_date)){
|
||||
delta <- as.numeric(as.POSIXct(readme_df$event_date[i])-as.POSIXct(readme_df$first_commit_dt[i]), unit="days")
|
||||
true_gap <- c(true_gap, delta)
|
||||
}
|
||||
true_gap
|
||||
length(readme_df$event_date)
|
||||
true_gap <- c()
|
||||
for (i in length(readme_df$event_date)){
|
||||
delta <- as.numeric(as.POSIXct(readme_df$event_date[i])-as.POSIXct(readme_df$first_commit_dt[i]), unit="days")
|
||||
true_gap <- c(true_gap, delta)
|
||||
}
|
||||
true_gap
|
||||
length(readme_df$event_date)
|
||||
true_gap <- c()
|
||||
for (i in 1:length(readme_df$event_date)){
|
||||
delta <- as.numeric(as.POSIXct(readme_df$event_date[i])-as.POSIXct(readme_df$first_commit_dt[i]), unit="days")
|
||||
true_gap <- c(true_gap, delta)
|
||||
}
|
||||
true_gap
|
||||
library(tidyverse)
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
readme_df <- readme_df |>
|
||||
filter(event_gap >= 0)
|
||||
hist(readme_df$event_gap)
|
||||
median(readme_df$event_gap)
|
||||
sd(readme_df$event_gap)
|
||||
max(readme_df$event_gap)
|
||||
table(readme_df$event_gap)
|
||||
contrib_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
contrib_df <- contrib_df |>
|
||||
filter(event_gap >= 0)
|
||||
median(readme_df$event_gap)
|
||||
sd(readme_df$event_gap)
|
||||
hist(contrib_df$event_gap)
|
||||
median(contrib_df$event_gap)
|
||||
1786.431 / 265
|
||||
@ -510,3 +71,442 @@ contrib_g
|
||||
library(gridExtra)
|
||||
grid.arrange(contrib_g, readme_g, nrow = 1)
|
||||
source("~/Desktop/git/24_deb_gov/R/contribRDDAnalysis.R")
|
||||
source("~/Desktop/git/24_deb_gov/R/documentReadabilityAnalysis.R")
|
||||
contrib_pop_df <- read_csv("../final_data/deb_contrib_pop_change.csv")
|
||||
contrib_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
View(contrib_pop_df)
|
||||
contrib_readability_df <- read_csv('../text_analysis/dwo_readability_contributing.csv')
|
||||
View(contrib_readability_df)
|
||||
View(contrib_pop_df)
|
||||
View(contrib_readability_df)
|
||||
View(contrib_pop_df)
|
||||
View(contrib_readability_df)
|
||||
View(contrib_pop_df)
|
||||
View(contrib_pop_df)
|
||||
View(contrib_df)
|
||||
View(contrib_pop_df)
|
||||
View(contrib_readability_df)
|
||||
View(contrib_pop_df)
|
||||
#concat dataframes into central data
|
||||
contrib_df_total <- contrib_pop_df |>
|
||||
mutate(project_name = str_split(upstream_vcs_link, pattern="/")[-1])
|
||||
View(contrib_pop_df)
|
||||
View(contrib_readability_df)
|
||||
View(contrib_readability_df)
|
||||
contrib_df_total <- contrib_readability_df |>
|
||||
mutate(project_name = str_split(filename, pattern="_")[-2])
|
||||
View(contrib_readability_df)
|
||||
contrib_df_total <- contrib_readability_df |>
|
||||
mutate(project_name = str_split(filename, pattern="_"))
|
||||
View(contrib_df_total)
|
||||
contrib_df_total <- contrib_readability_df |>
|
||||
mutate(project_name = str_split(filename, pattern="_")[0])
|
||||
contrib_df_total <- contrib_readability_df |>
|
||||
mutate(project_name = str_split(filename, pattern="_")[1])
|
||||
View(contrib_df_total)
|
||||
contrib_df_total <- contrib_readability_df |>
|
||||
mutate(project_name = str_split(filename, pattern="_")[1] |>
|
||||
sapply("[[", 1))
|
||||
View(contrib_df_total)
|
||||
contrib_df_total <- contrib_readability_df |>
|
||||
mutate(project_name = str_split(filename, pattern="_"))
|
||||
View(contrib_df_total)
|
||||
contrib_df_total <- contrib_readability_df |>
|
||||
mutate(project_name_array = str_split(filename, pattern="_")) |>
|
||||
mutate(projes_name = project_name_array[1])
|
||||
View(contrib_df_total)
|
||||
View(contrib_readability_df)
|
||||
View(contrib_pop_df)
|
||||
#concat dataframes into central data
|
||||
contrib_pop_df <- contrib_pop_df %>%
|
||||
mutate(first_element = map_chr(upstream_vcs_link, ~ {
|
||||
parts <- str_split(.x, pattern = "/")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
parts[1] # Extract the first element after splitting
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
View(contrib_pop_df)
|
||||
contrib_df_total <- contrib_readability_df |>
|
||||
mutate(project_name = map_chr(filename, ~ {
|
||||
parts <- str_split(.x, pattern = "_")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
parts[1]
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
contrib_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
contrib_pop_df <- read_csv("../final_data/deb_contrib_pop_change.csv")
|
||||
contrib_readability_df <- read_csv('../text_analysis/dwo_readability_contributing.csv')
|
||||
contrib_df_total <- contrib_readability_df |>
|
||||
mutate(project_name = map_chr(filename, ~ {
|
||||
parts <- str_split(.x, pattern = "_")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
parts[1]
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
View(contrib_df_total)
|
||||
contrib_pop_df <- contrib_pop_df |>
|
||||
mutate(project_name = map_chr(upstream_vcs_link, ~ {
|
||||
parts <- str_split(.x, pattern = "/")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
parts[-1]
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
parts[length(parts)]
|
||||
contrib_pop_df <- contrib_pop_df |>
|
||||
mutate(project_name = map_chr(upstream_vcs_link, ~ {
|
||||
parts <- str_split(.x, pattern = "/")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
parts[length(parts)]
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
View(contrib_pop_df)
|
||||
source("~/Desktop/git/24_deb_gov/R/docChar_outcomes.R")
|
||||
source("~/Desktop/git/24_deb_gov/R/docChar_outcomes.R")
|
||||
contrib_total_df <- contrib_pop_df |>
|
||||
left_join(contrib_readability_df, by="project_name")
|
||||
View(contrib_total_df)
|
||||
# test regressions
|
||||
lm1 <- glm.nb(after_contrib_new ~ word_count, data = contrib_total_df)
|
||||
# test regressions
|
||||
library(MASS)
|
||||
lm1 <- glm.nb(after_contrib_new ~ word_count, data = contrib_total_df)
|
||||
summary(lm1)
|
||||
View(contrib_total_df)
|
||||
contrib_total_df <- contrib_pop_df |>
|
||||
join(contrib_readability_df, by="project_name")
|
||||
View(contrib_total_df)
|
||||
View(contrib_readability_df)
|
||||
qqnorm(residuals(lm1))
|
||||
source("~/Desktop/git/24_deb_gov/R/docChar_outcomes.R")
|
||||
lm1 <- glm.nb(after_contrib_new ~ linsear_write, data = contrib_total_df)
|
||||
lm1 <- glm.nb(after_contrib_new ~ linsear, data = contrib_total_df)
|
||||
View(contrib_total_df)
|
||||
lm1 <- glm.nb(after_contrib_new ~ linsear_write_formula, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(after_contrib_new ~ reading_time, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(after_contrib_new ~ flesch_reading_ease, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
contrib_readability_df <- contrib_readability_df |>
|
||||
mutate(project_name = map_chr(filename, ~ {
|
||||
parts <- str_split(.x, pattern = "_")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
head(parts, -1)
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
parts[1] + parts[2]
|
||||
contrib_readability_df <- contrib_readability_df |>
|
||||
mutate(project_name = map_chr(filename, ~ {
|
||||
parts <- str_split(.x, pattern = "_")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
parts[1] + parts[2]
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
contrib_readability_df <- contrib_readability_df |>
|
||||
mutate(project_name = map_chr(filename, ~ {
|
||||
parts <- str_split(.x, pattern = "_")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
paste(head(parts, -1), collapse="")
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
View(contrib_readability_df)
|
||||
#libraries
|
||||
library(stringr)
|
||||
contrib_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
contrib_pop_df <- read_csv("../final_data/deb_contrib_pop_change.csv")
|
||||
contrib_readability_df <- read_csv('../text_analysis/dwo_readability_contributing.csv')
|
||||
contrib_pop_df <- contrib_pop_df |>
|
||||
mutate(project_name = map_chr(upstream_vcs_link, ~ {
|
||||
parts <- str_split(.x, pattern = "/")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
parts[length(parts)]
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
contrib_readability_df <- contrib_readability_df |>
|
||||
mutate(project_name = map_chr(filename, ~ {
|
||||
parts <- str_split(.x, pattern = "_")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
paste(head(parts, -1), collapse="_")
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
contrib_total_df <- contrib_pop_df |>
|
||||
join(contrib_readability_df, by="project_name")
|
||||
View(contrib_total_df)
|
||||
# test regressions
|
||||
library(MASS)
|
||||
lm1 <- glm.nb(after_contrib_new ~ flesch_reading_ease, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(after_contrib_new ~ flesch_reading_ease + age_in_days, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
View(contrib_df)
|
||||
source("~/Desktop/git/24_deb_gov/R/contrib_docChar_outcomes.R")
|
||||
View(windowed_data)
|
||||
View(windowed_data)
|
||||
summed_data <- windowed_data |>
|
||||
group_by(upstream_vcs_link) |>
|
||||
summarize(total_ct_after_all = sum(ct_after_all))
|
||||
summed_data <- windowed_data |>
|
||||
filter(window="ct_after_all") |>
|
||||
group_by(upstream_vcs_link) |>
|
||||
summarize(total_ct_after_all = sum(count))
|
||||
summed_data <- windowed_data |>
|
||||
filter(window=="ct_after_all") |>
|
||||
group_by(upstream_vcs_link) |>
|
||||
summarize(total_ct_after_all = sum(count))
|
||||
View(summed_data)
|
||||
summed_data <- windowed_data |>
|
||||
filter(window=="ct_after_all") |>
|
||||
group_by(upstream_vcs_link) |>
|
||||
mutate(total_ct_after_all = sum(count))
|
||||
View(summed_data)
|
||||
summed_data <- windowed_data |>
|
||||
filter(window=="ct_after_all") |>
|
||||
group_by(upstream_vcs_link) |>
|
||||
summarize(total_ct_after_all = sum(count)) |> ungroup()
|
||||
View(summed_data)
|
||||
View(windowed_data)
|
||||
summed_data <- windowed_data |>
|
||||
filter(window=="ct_after_all") |>
|
||||
group_by(upstream_vcs_link) |>
|
||||
summarise_at(vars(count), list(name=sum))
|
||||
View(summed_data)
|
||||
summed_data <- windowed_data |>
|
||||
filter(D==1) |>
|
||||
group_by(upstream_vcs_link) |>
|
||||
summarise_at(vars(count), list(summed_count=sum))
|
||||
View(summed_data)
|
||||
source("~/Desktop/git/24_deb_gov/R/contrib_docChar_outcomes.R")
|
||||
contrib_total_df <- contrib_total_df|>
|
||||
join(summed_data, by=upstream_vcs_link)
|
||||
contrib_total_df <- contrib_pop_df |>
|
||||
join(contrib_readability_df, by="project_name")
|
||||
View(contrib_total_df)
|
||||
contrib_total_df <- contrib_total_df|>
|
||||
join(summed_data, by=upstream_vcs_link)
|
||||
View(summed_data)
|
||||
contrib_total_df <- contrib_total_df|>
|
||||
join(summed_data, by="upstream_vcs_link")
|
||||
View(contrib_total_df)
|
||||
View(contrib_df)
|
||||
source("~/Desktop/git/24_deb_gov/R/contrib_docChar_outcomes.R")
|
||||
#outcome variable that is number of commits by number of new contributors
|
||||
contrib_total_df$commit_by_contrib = contrib_total_df$summed_count * contrib_total_df$after_contrib_new
|
||||
# test regressions
|
||||
library(MASS)
|
||||
lm1 <- glm.nb(after_contrib_new ~ flesch_reading_ease + age_in_days, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(commit_by_contrib ~ flesch_reading_ease + age_in_days, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
View(contrib_total_df)
|
||||
lm1 <- glm.nb(commit_by_contrib ~ word_count, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
contrib_total_df$scaled_outcome = scale(contrib_total_df$commit_by_contrib)
|
||||
lm1 <- glm.nb(scaled_outcome ~ word_count + flesch_kincaid, data = contrib_total_df)
|
||||
lm1 <- glm.nb(scaled_outcome ~ word_count + flesch_kincaid_grade, data = contrib_total_df)
|
||||
contrib_total_df$logged_outcome = log1p(contrib_total_df$commit_by_contrib)
|
||||
# test regressions
|
||||
library(MASS)
|
||||
lm1 <- glm.nb(scaled_outcome ~ word_count + flesch_kincaid_grade, data = contrib_total_df)
|
||||
lm1 <- glm.nb(logged_outcome ~ word_count + flesch_kincaid_grade, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(logged_outcome ~ word_count + flesch_kincaid_grade + linsear_write_formula, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
contrib_total_df$scaled_outcome = scale(contrib_total_df$commit_by_contrib)
|
||||
# test regressions
|
||||
library(MASS)
|
||||
lm1 <- lm(scaled_outcome ~ word_count + flesch_kincaid_grade + linsear_write_formula, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(logged_outcome ~ word_count + flesch_kincaid_grade + linsear_write_formula, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(logged_outcome ~ word_count + flesch_kincaid_grade + linsear_write_formula + mcalpine_eflaw, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(logged_outcome ~ word_count + flesch_kincaid_grade + linsear_write_formula + mcalpine_eflaw + dale_chall_readability_score, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(logged_outcome ~ word_count + dale_chall_readability_score, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(logged_outcome ~ word_count + reading_time, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(commit_by_contrib ~ word_count + reading_time, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(commit_by_contrib ~ word_count + flesch_kincaid_grade, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
#libraries
|
||||
library(stringr)
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
readme_pop_df <- read_csv("../final_data/deb_readme_pop_change.csv")
|
||||
readme_readability_df <- read_csv('../text_analysis/dwo_readability_readmeuting.csv')
|
||||
source("~/Desktop/git/24_deb_gov/R/readme_docChar_outcomes.R")
|
||||
source("~/Desktop/git/24_deb_gov/R/readme_docChar_outcomes.R")
|
||||
lm1 <- glm.nb(commit_by_readme ~ word_count + flesch_kincaid_grade, data = readme_total_df)
|
||||
View(readme_readability_df)
|
||||
readme_readability_df <- readme_readability_df |>
|
||||
mutate(project_name = map_chr(filename, ~ {
|
||||
parts <- str_split(.x, pattern = "_")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
paste(head(parts, -1), collapse="_")
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
readme_total_df <- readme_pop_df |>
|
||||
join(readme_readability_df, by="project_name")
|
||||
readme_total_df <- readme_total_df|>
|
||||
join(summed_data, by="upstream_vcs_link")
|
||||
#outcome variable that is number of commits by number of new readmeutors
|
||||
readme_total_df$commit_by_readme = readme_total_df$summed_count * readme_total_df$after_readme_new
|
||||
readme_total_df$logged_outcome = log(readme_total_df$commit_by_readme)
|
||||
View(readme_total_df)
|
||||
View(readme_total_df)
|
||||
#outcome variable that is number of commits by number of new readmeutors
|
||||
readme_total_df$commit_by_readme = readme_total_df$summed_count * readme_total_df$after_readme_new
|
||||
View(readme_total_df)
|
||||
View(readme_readability_df)
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/agateau/yokadi/issues/new", "project_name"] = "yokadi"
|
||||
View(readme_pop_df)
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/SciRuby/rb-gsl/issues/new", "project_name"] = "rb-gsl"
|
||||
source("~/Desktop/git/24_deb_gov/R/readme_docChar_outcomes.R")
|
||||
readme_readability_df <- readme_readability_df |>
|
||||
mutate(project_name = map_chr(filename, ~ {
|
||||
parts <- str_split(.x, pattern = "_")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
paste(head(parts, -1), collapse="_")
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
readme_readability_df[readme_readability_df['filename'] == "yder_README_8md.html", "project_name"] = "yder"
|
||||
readme_readability_df[readme_readability_df['filename'] == "pg_filedump.git_README.pg_filedump", "project_name"] = "pg_filedump.git"
|
||||
readme_readability_df[readme_readability_df['filename'] == "openvas_UPGRADE_README", "project_name"] = "openvas"
|
||||
readme_readability_df[readme_readability_df['filename'] == "hyphen.git_README_hyph_en_US.txt", "project_name"] = "hyphen.git"
|
||||
readme_readability_df[readme_readability_df['filename'] == "cycle.git_README_ru.html", "project_name"] = "cycle.git"
|
||||
readme_readability_df[readme_readability_df['filename'] == "diffuse.git_README_ru", "project_name"] = "diffuse.git"
|
||||
readme_readability_df[readme_readability_df['filename'] == "CheMPS2_README_8md_source.html", "project_name"] = "CheMPS2"
|
||||
readme_readability_df[readme_readability_df['filename'] == "sleuthkit_README_win32.txt", "project_name"] = "sleuthkit"
|
||||
readme_readability_df[readme_readability_df['filename'] == "Lmod_README_lua_modulefiles.txt", "project_name"] = "Lmod"
|
||||
readme_readability_df[readme_readability_df['filename'] == "engauge_debian_README_for_osx", "project_name"] = "engauge_debian"
|
||||
readme_total_df <- readme_pop_df |>
|
||||
join(readme_readability_df, by="project_name")
|
||||
readme_total_df <- readme_total_df|>
|
||||
join(summed_data, by="upstream_vcs_link")
|
||||
#outcome variable that is number of commits by number of new readmeutors
|
||||
readme_total_df$commit_by_readme = readme_total_df$summed_count * readme_total_df$after_readme_new
|
||||
View(readme_total_df)
|
||||
readme_total_df$logged_outcome = log(readme_total_df$commit_by_readme)
|
||||
#outcome variable that is number of commits by number of new readmeutors
|
||||
readme_total_df$commit_by_readme = readme_total_df$summed_count * readme_total_df$after_readme_new
|
||||
#outcome variable that is number of commits by number of new readmeutors
|
||||
readme_total_df$commit_by_contrib = readme_total_df$summed_count * readme_total_df$after_readme_new
|
||||
#outcome variable that is number of commits by number of new readmeutors
|
||||
readme_total_df$commit_by_contrib = NA
|
||||
readme_total_df$commit_by_contrib = readme_total_df$summed_count * readme_total_df$after_readme_new
|
||||
View(readme_total_df)
|
||||
View(readme_total_df)
|
||||
readme_total_df$commit_by_contrib = readme_total_df$summed_count * readme_total_df$after_contrib_new
|
||||
lm1 <- glm.nb(commit_by_contrib ~ word_count + flesch_kincaid_grade, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
readme_total_df$logged_outcome = log(readme_total_df$commit_by_readme)
|
||||
readme_total_df$logged_outcome = log(readme_total_df$commit_by_contrib)
|
||||
lm1 <- glm.nb(commit_by_contrib ~ word_count + flesch_kincaid_grade, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(summed_count ~ word_count + flesch_kincaid_grade, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(commit_by_contrib ~ word_count + flesch_kincaid_grade, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(after_contrib_new ~ word_count + flesch_kincaid_grade, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(after_contrib_new ~ word_count + reading_time, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(commit_by_contrib ~ word_count + reading_time, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(reading_time ~ word_count , data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
View(readme_total_df)
|
||||
lm1 <- glm.nb(reading_time ~ flesch_reading_ease , data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(flesch_reading_ease ~ reading_time , data = readme_total_df)
|
||||
lm1 <- glm.nb(commit_by_contrib ~ reading_time , data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(commit_by_contrib ~ reading_time + linsear_write_formula , data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
readme_total_df$commit_by_contrib = readme_total_df$summed_count * (readme_total_df$after_contrib_new + 1)
|
||||
readme_total_df$logged_outcome = log(readme_total_df$commit_by_contrib)
|
||||
lm1 <- glm.nb(commit_by_contrib ~ reading_time + linsear_write_formula , data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
readme_total_df$logged_outcome = log1p(readme_total_df$commit_by_contrib)
|
||||
lm1 <- glm.nb(logged_outcome ~ reading_time + linsear_write_formula , data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(logged_outcome ~ reading_time + linsear_write_formula + flesch_reading_ease, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(logged_outcome ~ reading_time + linsear_write_formula + flesch_reading_ease + mcalpine_eflaw, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(summed_count~ reading_time + linsear_write_formula + flesch_reading_ease + mcalpine_eflaw, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(summed_count~ reading_time + linsear_write_formula + flesch_reading_ease + mcalpine_eflaw + word_count, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(logged_outcome~ reading_time + linsear_write_formula + flesch_reading_ease + mcalpine_eflaw + word_count, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
source("~/Desktop/git/24_deb_gov/R/contrib_docChar_outcomes.R")
|
||||
lm1 <- glm.nb(logged_outcome~ reading_time + linsear_write_formula + flesch_reading_ease + mcalpine_eflaw + word_count, data = contrib_total_df)
|
||||
contrib_total_df$logged_outcome = log1p(contrib_total_df$commit_by_contrib)
|
||||
lm1 <- glm.nb(logged_outcome ~ reading_time + linsear_write_formula + flesch_reading_ease + mcalpine_eflaw + word_count, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
lm1 <- glm.nb(summed_count ~ reading_time + linsear_write_formula + flesch_reading_ease + mcalpine_eflaw + word_count, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
|
||||
BIN
R/0715_readability_plots.png
Normal file
BIN
R/0715_readability_plots.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 196 KiB |
@ -3,8 +3,6 @@ library(plyr)
|
||||
#get the contrib data instead
|
||||
try(setwd(dirname(rstudioapi::getActiveDocumentContext()$path)))
|
||||
contrib_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
contrib_df <- contrib_df |>
|
||||
filter(event_gap >= 0)
|
||||
#some preprocessing and expansion
|
||||
col_order <- c("upstream_vcs_link", "age_in_days", "first_commit", "first_commit_dt", "event_gap", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
contrib_df <- contrib_df[,col_order]
|
||||
|
||||
77
R/contrib_docChar_outcomes.R
Normal file
77
R/contrib_docChar_outcomes.R
Normal file
@ -0,0 +1,77 @@
|
||||
#libraries
|
||||
library(stringr)
|
||||
contrib_df <- read_csv("../final_data/deb_contrib_did.csv")
|
||||
contrib_pop_df <- read_csv("../final_data/deb_contrib_pop_change.csv")
|
||||
contrib_readability_df <- read_csv('../text_analysis/dwo_readability_contributing.csv')
|
||||
#get the contribution count
|
||||
#some preprocessing and expansion
|
||||
col_order <- c("upstream_vcs_link", "age_in_days", "first_commit", "first_commit_dt", "event_gap", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
contrib_df <- contrib_df[,col_order]
|
||||
contrib_df$ct_before_all <- str_split(gsub("[][]","", contrib_df$before_all_ct), ", ")
|
||||
contrib_df$ct_after_all <- str_split(gsub("[][]","", contrib_df$after_all_ct), ", ")
|
||||
contrib_df$ct_before_mrg <- str_split(gsub("[][]","", contrib_df$before_mrg_ct), ", ")
|
||||
contrib_df$ct_after_mrg <- str_split(gsub("[][]","", contrib_df$after_mrg_ct), ", ")
|
||||
drop <- c("before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct")
|
||||
contrib_df = contrib_df[,!(names(contrib_df) %in% drop)]
|
||||
# 2 some expansion needs to happens for each project
|
||||
expand_timeseries <- function(project_row) {
|
||||
longer <- project_row |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
longer$count <- as.numeric(longer$count)
|
||||
#longer <- longer[which(longer$observation_type == "all"),]
|
||||
return(longer)
|
||||
}
|
||||
expanded_data <- expand_timeseries(contrib_df[1,])
|
||||
for (i in 2:nrow(contrib_df)){
|
||||
expanded_data <- rbind(expanded_data, expand_timeseries(contrib_df[i,]))
|
||||
}
|
||||
#filter out the windows of time that we're looking at
|
||||
window_num <- 8
|
||||
windowed_data <- expanded_data |>
|
||||
filter(week >= (27 - window_num) & week <= (27 + window_num)) |>
|
||||
mutate(D = ifelse(week > 27, 1, 0))
|
||||
|
||||
summed_data <- windowed_data |>
|
||||
filter(D==1) |>
|
||||
group_by(upstream_vcs_link) |>
|
||||
summarise_at(vars(count), list(summed_count=sum))
|
||||
|
||||
#concat dataframes into central data
|
||||
contrib_pop_df <- contrib_pop_df |>
|
||||
mutate(project_name = map_chr(upstream_vcs_link, ~ {
|
||||
parts <- str_split(.x, pattern = "/")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
parts[length(parts)]
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
|
||||
contrib_readability_df <- contrib_readability_df |>
|
||||
mutate(project_name = map_chr(filename, ~ {
|
||||
parts <- str_split(.x, pattern = "_")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
paste(head(parts, -1), collapse="_")
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
|
||||
contrib_total_df <- contrib_pop_df |>
|
||||
join(contrib_readability_df, by="project_name")
|
||||
|
||||
contrib_total_df <- contrib_total_df|>
|
||||
join(summed_data, by="upstream_vcs_link")
|
||||
#outcome variable that is number of commits by number of new contributors
|
||||
contrib_total_df$commit_by_contrib = contrib_total_df$summed_count * contrib_total_df$after_contrib_new
|
||||
contrib_total_df$logged_outcome = log1p(contrib_total_df$commit_by_contrib)
|
||||
# test regressions
|
||||
library(MASS)
|
||||
lm1 <- glm.nb(summed_count ~ reading_time + linsear_write_formula + flesch_reading_ease + mcalpine_eflaw + word_count, data = contrib_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
101
R/readme_docChar_outcomes.R
Normal file
101
R/readme_docChar_outcomes.R
Normal file
@ -0,0 +1,101 @@
|
||||
#libraries
|
||||
library(stringr)
|
||||
readme_df <- read_csv("../final_data/deb_readme_did.csv")
|
||||
readme_pop_df <- read_csv("../final_data/deb_readme_pop_change.csv")
|
||||
readme_readability_df <- read_csv('../text_analysis/dwo_readability_readme.csv')
|
||||
#get the readmeution count
|
||||
#some preprocessing and expansion
|
||||
col_order <- c("upstream_vcs_link", "age_in_days", "first_commit", "first_commit_dt", "event_gap", "event_date", "event_hash", "before_all_ct", "after_all_ct", "before_mrg_ct", "after_mrg_ct", "before_auth_new", "after_auth_new", "before_commit_new", "after_commit_new")
|
||||
readme_df <- readme_df[,col_order]
|
||||
readme_df$ct_before_all <- str_split(gsub("[][]","", readme_df$before_all_ct), ", ")
|
||||
readme_df$ct_after_all <- str_split(gsub("[][]","", readme_df$after_all_ct), ", ")
|
||||
readme_df$ct_before_mrg <- str_split(gsub("[][]","", readme_df$before_mrg_ct), ", ")
|
||||
readme_df$ct_after_mrg <- str_split(gsub("[][]","", readme_df$after_mrg_ct), ", ")
|
||||
drop <- c("before_all_ct", "before_mrg_ct", "after_all_ct", "after_mrg_ct")
|
||||
readme_df = readme_df[,!(names(readme_df) %in% drop)]
|
||||
# 2 some expansion needs to happens for each project
|
||||
expand_timeseries <- function(project_row) {
|
||||
longer <- project_row |>
|
||||
pivot_longer(cols = starts_with("ct"),
|
||||
names_to = "window",
|
||||
values_to = "count") |>
|
||||
unnest(count)
|
||||
longer$observation_type <- gsub("^.*_", "", longer$window)
|
||||
longer <- ddply(longer, "observation_type", transform, week=seq(from=0, by=1, length.out=length(observation_type)))
|
||||
longer$count <- as.numeric(longer$count)
|
||||
#longer <- longer[which(longer$observation_type == "all"),]
|
||||
return(longer)
|
||||
}
|
||||
expanded_data <- expand_timeseries(readme_df[1,])
|
||||
for (i in 2:nrow(readme_df)){
|
||||
expanded_data <- rbind(expanded_data, expand_timeseries(readme_df[i,]))
|
||||
}
|
||||
#filter out the windows of time that we're looking at
|
||||
window_num <- 8
|
||||
windowed_data <- expanded_data |>
|
||||
filter(week >= (27 - window_num) & week <= (27 + window_num)) |>
|
||||
mutate(D = ifelse(week > 27, 1, 0))
|
||||
|
||||
summed_data <- windowed_data |>
|
||||
filter(D==1) |>
|
||||
group_by(upstream_vcs_link) |>
|
||||
summarise_at(vars(count), list(summed_count=sum))
|
||||
|
||||
#concat dataframes into central data
|
||||
readme_pop_df <- readme_pop_df |>
|
||||
mutate(project_name = map_chr(upstream_vcs_link, ~ {
|
||||
parts <- str_split(.x, pattern = "/")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
parts[length(parts)]
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/agateau/yokadi/issues/new", "project_name"] = "yokadi"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "http://github.com/voloko/twitter-stream/issues/new", "project_name"] = "twitter-stream"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/ai/autoprefixer-rails/issues/new", "project_name"] = "autoprefixer-rails"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/aquasync/ruby-ole/issues/new", "project_name"] = "ruby-ole"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/bluemonk/ipaddress/issues/new", "project_name"] = "ipaddress"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/ccocchi/rabl-rails/issues/new", "project_name"] = "rabl-rails"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/dejan/espeak-ruby/issues/new", "project_name"] = "espeak-ruby"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/hadley/plyr/issues/new", "project_name"] = "plyr"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/jfelchner/ruby-progressbar/issues/new", "project_name"] = "ruby-progressbar"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/sargon/trayer-srg/issues/new", "project_name"] = "trayer-srg"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/SciRuby/rb-gsl/issues/new", "project_name"] = "rb-gsl"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/solvespace/solvespace/issues/new", "project_name"] = "solvespace"
|
||||
readme_pop_df[readme_pop_df['upstream_vcs_link'] == "https://github.com/walling/unorm/issues/new", "project_name"] = "unorm"
|
||||
|
||||
readme_readability_df <- readme_readability_df |>
|
||||
mutate(project_name = map_chr(filename, ~ {
|
||||
parts <- str_split(.x, pattern = "_")[[1]]
|
||||
if (length(parts) >= 1) {
|
||||
paste(head(parts, -1), collapse="_")
|
||||
} else {
|
||||
NA_character_
|
||||
}
|
||||
}))
|
||||
readme_readability_df[readme_readability_df['filename'] == "yder_README_8md.html", "project_name"] = "yder"
|
||||
readme_readability_df[readme_readability_df['filename'] == "pg_filedump.git_README.pg_filedump", "project_name"] = "pg_filedump.git"
|
||||
readme_readability_df[readme_readability_df['filename'] == "openvas_UPGRADE_README", "project_name"] = "openvas"
|
||||
readme_readability_df[readme_readability_df['filename'] == "hyphen.git_README_hyph_en_US.txt", "project_name"] = "hyphen.git"
|
||||
readme_readability_df[readme_readability_df['filename'] == "cycle.git_README_ru.html", "project_name"] = "cycle.git"
|
||||
readme_readability_df[readme_readability_df['filename'] == "diffuse.git_README_ru", "project_name"] = "diffuse.git"
|
||||
readme_readability_df[readme_readability_df['filename'] == "CheMPS2_README_8md_source.html", "project_name"] = "CheMPS2"
|
||||
readme_readability_df[readme_readability_df['filename'] == "sleuthkit_README_win32.txt", "project_name"] = "sleuthkit"
|
||||
readme_readability_df[readme_readability_df['filename'] == "Lmod_README_lua_modulefiles.txt", "project_name"] = "Lmod"
|
||||
readme_readability_df[readme_readability_df['filename'] == "engauge_debian_README_for_osx", "project_name"] = "engauge_debian"
|
||||
|
||||
readme_total_df <- readme_pop_df |>
|
||||
join(readme_readability_df, by="project_name")
|
||||
|
||||
readme_total_df <- readme_total_df|>
|
||||
join(summed_data, by="upstream_vcs_link")
|
||||
#outcome variable that is number of commits by number of new readmeutors
|
||||
readme_total_df$commit_by_contrib = NA
|
||||
readme_total_df$commit_by_contrib = readme_total_df$summed_count * (readme_total_df$after_contrib_new + 1)
|
||||
readme_total_df$logged_outcome = log1p(readme_total_df$commit_by_contrib)
|
||||
# test regressions
|
||||
library(MASS)
|
||||
lm1 <- glm.nb(logged_outcome~ reading_time + linsear_write_formula + flesch_reading_ease + mcalpine_eflaw + word_count, data = readme_total_df)
|
||||
qqnorm(residuals(lm1))
|
||||
summary(lm1)
|
||||
Loading…
Reference in New Issue
Block a user