редактировать рецепт: Как провести сравнительный анализ поведения на поле цифровой дидактики (R)

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Датасет [[Digida2026]] - собран и размещен на [[GitHub]] * https://raw.githubusercontent.com/patarakin/stat-data/refs/heads/main/datasets/csv/users7_activity_with_categories.csv <syntaxhighlight lang="R" line> getwd() library(tidyverse) library(ggplot2) students <- read_csv("https://raw.githubusercontent.com/patarakin/stat-data/refs/heads/main/datasets/csv/users7_activity_with_categories.csv", show_col_types = FALSE) # rm(students) students # --- Pipe students |> head() ###-- Select students %>% select(username, n_total_edits, days_active, edits_articles, n_files_uploaded, discipline) ###-- Select + Filter students %>% select(username, n_total_edits, days_active, edits_articles, n_files_uploaded, discipline) %>% filter(n_total_edits > 10) %>% filter(days_active < 2) ### --- Select + Mutate ## - edit_per_day -активность в день # pct_articles - активность на страницах (0), а не в пространстве обсуждений students %>% select(username, n_total_edits, days_active, edits_articles, n_files_uploaded, discipline) %>% mutate( edit_per_day = round(n_total_edits / days_active, 2), pct_articles = round(edits_articles / n_total_edits * 100, 1) ) ### + Groupby students %>% select(username, n_total_edits, days_active, edits_articles, n_files_uploaded, discipline) %>% mutate( edit_per_day = round(n_total_edits / days_active, 2), pct_articles = round(edits_articles / n_total_edits * 100, 1) ) %>% group_by(discipline) #--- Groupby + Summarize students %>% select(username, n_total_edits, days_active, edits_articles, n_files_uploaded, discipline) %>% mutate( edit_per_day = round(n_total_edits / days_active, 2), pct_articles = round(edits_articles / n_total_edits * 100, 1) ) %>% filter(days_active > 0) %>% group_by(discipline) %>% summarise( n_students = n(), mean_edits = round(mean(n_total_edits), 1), mean_edit_per_day = round(mean(edit_per_day), 2), total_files = sum(n_files_uploaded), mean_pct_articles = round(mean(pct_articles), 1), .groups = "drop" ) %>% arrange(desc(n_students)) #-------------------- students_analysis <- students %>% select(username, n_total_edits, days_active, edits_articles, n_files_uploaded, discipline) %>% filter(days_active > 0) %>% mutate( edit_per_day = round(n_total_edits / days_active, 2), pct_articles = round(edits_articles / n_total_edits * 100, 1) ) ## glimpse(students_analysis) unique(students_analysis$discipline) summary(students_analysis$edit_per_day) p <- ggplot(students_analysis, aes(x = discipline, y = edit_per_day)) + geom_boxplot() print(p) p <- ggplot(students_analysis, aes(x = discipline, y = edit_per_day)) + geom_boxplot() print(p) students_analysis <- students %>% select(discipline, n_total_edits, days_active) %>% filter(days_active > 0) %>% mutate( edit_per_day = n_total_edits / days_active ) ggplot(students_analysis, aes(x = discipline, y = edit_per_day)) + geom_boxplot() ## ggplot students_analysis %>% ggplot(aes(x = discipline, y = edit_per_day, fill = discipline)) + geom_boxplot() + labs( title = "Edit frequency per day by discipline", x = "Discipline", y = "Edits per day" ) + theme_minimal() + theme(axis.text.x = element_text(angle = 45, hjust = 1)) </syntaxhighlight> [[Файл:Pipe Digida2026.png|600px]] == Основные глаголы преобразования данных == {{Шаблон:TidyR}} ---- [[Категория:Lesson]]

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