74 lines
1.6 KiB
R
74 lines
1.6 KiB
R
library(tidyverse)
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#library(dsl)
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library(dplyr)
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dsl_csv <-"~/dsl/110925_DSL_df_adac.csv"
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dsl_df <- read.csv(dsl_csv, header = TRUE)
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outcome_summary <- dsl_df |>
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group_by(source, isAuthorWMF)|>
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summarise(
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total_sum = sum(!is.na(resolution_outcome)),
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count_resolution_outcome = sum(resolution_outcome),
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success_prop = count_resolution_outcome / total_sum,
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median_ttr_days = median(TTR, na.rm = TRUE) / 24,
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median_comments_before_resolution = median(n_comments_before)
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)
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library(ggplot2)
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library(ggdist)
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ggplot(
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dsl_df,
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aes(
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x=n_comments_before,
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color=source,
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fill=source
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)
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) +
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facet_grid(~isAuthorWMF) +
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stat_halfeye() +
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theme_minimal()
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dsl_df <- dsl_df |>
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mutate(priority = factor(priority,
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levels = c("Unbreak Now!", "High", "Medium", "Low", "Lowest", "Needs Triage")))
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ggplot(dsl_df,
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aes(
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fill=resolution_outcome,
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x=priority
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)) +
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facet_grid(~source) +
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geom_bar() +
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theme_minimal()
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signed_power <- function(x, p) {
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sign(x) * abs(x) ^ p
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}
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signed_log <- function(x) sign(x) * log1p(abs(x))
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dsl_df <- dsl_df |>
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mutate(
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sp_med_pc3_adac = signed_power(median_PC3_adac, 0.2),
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sp_med_pc4_adac = signed_power(median_PC4_adac, 0.2),
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sl_med_pc4_adac = signed_log(median_PC4_adac),
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sl_med_pc3_adac = signed_log(median_PC3_adac)
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)
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ggplot(dsl_df, aes(
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y= log1p(TTR/24),
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x=sl_med_pc4_adac,
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shape=isAuthorWMF,
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color=isAuthorWMF
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)) +
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facet_grid(~source) +
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theme_minimal() +
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geom_smooth(method="loess", span=0.5) +
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geom_point() +
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scale_color_viridis_d()
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