95 lines
2.8 KiB
R
95 lines
2.8 KiB
R
library(tidyverse)
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library(jsonlite)
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library(lubridate)
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## TODO: get the within-case seniority
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main_csv <-"~/analysis_data/100725_bivariate_data.csv"
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main_df <- read.csv(main_csv, header = TRUE)
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#task_df <- main_df |>
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# filter(comment_type == "task_description")
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main_df <- main_df |>
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mutate(new_priority_score = ifelse(priority_score == 90, NA, priority_score))
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library(ggdist)
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ggplot(main_df, aes(x = week_index, y = n_comments, fill = isAuthorWMF)) +
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facet_grid(~source) +
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geom_dots(side = "both", layout = "hex", stackratio = 0.92) +
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scale_fill_viridis_d() +
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xlim(-130, 15) +
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theme_minimal() +
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labs(
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title = "PCs for Task Descriptions (Faceted by Source and Phase)",
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x = "week_index",
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y = "Priority_Score",
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fill = "isAuthorWMF?"
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)
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library(ggplot2)
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ggplot(main_df, aes(y = new_priority_score, x = resolution_outcome, fill = isAuthorWMF)) +
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facet_grid(source~phase) +
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stat_histinterval()+
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theme_minimal() +
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labs(
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title = "Histogram of triaged priority scores by task outcome and affiliation (faceted by source and phase)",
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x = "on-time resolution (wide release date +90 days)",
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y = "priority score (post-triage)",
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fill = "isTaskAuthorWMF?"
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)
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main_df %>%
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count(phase, source, resolution_outcome, isAuthorWMF) %>%
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ggplot(aes(
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y = resolution_outcome,
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x = isAuthorWMF,
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fill = n,
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label = n
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)) +
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facet_grid(source ~ phase) +
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geom_tile() +
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geom_text(size = 5, color = "white") +
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scale_fill_viridis_c() +
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theme_minimal() +
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labs(
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title = "Count of Tasks by on-time resolution",
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x = "isTaskAuthorWMF?",
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y = "on-time resolution (wide release date +90 days)",
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fill = "count of tasks"
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)
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ggplot(main_df, aes(y = resolution_outcome, x = week_index, fill = isAuthorWMF)) +
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facet_grid(~source) +
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stat_dots(position = "dodgejust", quantiles = 100, color = NA) +
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theme_minimal() +
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labs(
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title = "centile (1/100) distribution dot plot of tasks (faceted by source)",
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x = "week_index of task filed",
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y = "on-time resolution (wide release date +90 days) ",
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fill = "isTaskAuthorWMF?"
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)
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ggplot(main_df, aes(y = priority_score, x = week_index, color = resolution_outcome)) +
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facet_grid(~source) +
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geom_point() +
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geom_smooth() +
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theme_minimal() +
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labs(
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title = "week_index x priority_score(faceted by source)",
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x = "week_index of task filed",
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y = "triaged priority score",
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color = "on-time resolution (wide release date +90 days)"
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)
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ggplot(main_df, aes(y = priority_score, x = median_gerrit_reviewers, color = isAuthorWMF)) +
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facet_grid(~source) +
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geom_point() +
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theme_minimal() +
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labs(
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title = "gerrit reviewers x priority_score(faceted by source)",
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x = "median # of gerrit reviewers for linked PRs",
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y = "triaged priority score",
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color = "isAuthorWMF?"
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)
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