46 lines
1.3 KiB
R
46 lines
1.3 KiB
R
library(tidyverse)
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library(dplyr)
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library(lubridate)
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library(rdd)
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readme_df_filepath <- "/mmfs1/gscratch/comdata/users/mjilg/govdoc-cr-data/final_data/metadata/final_0207_README_weekly_count_data.csv"
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df = read.csv(readme_df_filepath, header = TRUE)
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#filtered_df <- df |>
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# filter(!project_id == "letsencrypt_letsencrypt")
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#output_filepath <-"/mmfs1/gscratch/comdata/users/mjilg/govdoc-cr-data/final_data/README_weekly_count_data.csv"
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#write.csv(filtered_df, output_filepath, row.names = FALSE)
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#EDA
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var(df$commit_count) # 207.7579
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mean(df$commit_count) # 4.31725
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median(df$commit_count) # 0
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mean(df$age) # 5074.828
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mean(df$age_at_commit) # 533.7488
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median(df$age) # 4876
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median(df$age_at_commit) # 0 days
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# scale and log-transform
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df$scaled_age <- scale(df$age)
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df$scaled_age_at_commit <- scale(df$age_at_commit)
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df$log1p_count <- log1p(df$commit_count)
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#getting IK Bandwidth
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get_optimal_bandwidth <- function(df){
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bw <- tryCatch({
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IKbandwidth(df$relative_week, df$log1p_count, cutpoint = 0, verbose = FALSE, kernel = "triangular")
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}, error = function(e) {
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NA
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})
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}
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mean_optimal_bandwidth <- df %>%
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group_by(project_id) %>%
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summarise(optimal_bandwidth = get_optimal_bandwidth(cur_data())) %>%
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drop_na(optimal_bandwidth) |>
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summarise(mean_optimal_bandwidth = mean(optimal_bandwidth))
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#Mean Optimal Bandwidth: 5.471781
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