251 lines
9.0 KiB
R
251 lines
9.0 KiB
R
# Script to calculate absolute differences between time intervals in eohi2.csv
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# Compares present vs past/future, and 5-year vs 10-year intervals
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# Load necessary library
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library(dplyr)
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setwd("C:/Users/irina/Documents/DND/EOHI/eohi2")
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# Read the data (with check.names=FALSE to preserve original column names)
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# na.strings=NULL keeps empty cells as empty strings instead of converting to NA
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df <- read.csv("eohi2.csv", stringsAsFactors = FALSE, check.names = FALSE, na.strings = NULL)
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# Define the 15 item names (same order for all time periods)
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items <- c(
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"pref_read", "pref_music", "pref_TV", "pref_nap", "pref_travel",
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"pers_extravert", "pers_critical", "pers_dependable", "pers_anxious", "pers_complex",
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"val_obey", "val_trad", "val_opinion", "val_performance", "val_justice"
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)
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# Note: present uses lowercase "tv", others use uppercase "TV"
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items_present <- c(
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"pref_read", "pref_music", "pref_tv", "pref_nap", "pref_travel",
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"pers_extravert", "pers_critical", "pers_dependable", "pers_anxious", "pers_complex",
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"val_obey", "val_trad", "val_opinion", "val_performance", "val_justice"
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)
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# Define all source columns (75 total)
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source_cols <- c(
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paste0("present_", items_present),
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paste0("past_5_", items),
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paste0("past_10_", items),
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paste0("fut_5_", items),
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paste0("fut_10_", items)
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)
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# Define all target columns (90 total = 6 calculation types × 15 items)
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target_NPast_5 <- paste0("NPast_5_", items)
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target_NPast_10 <- paste0("NPast_10_", items)
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target_NFut_5 <- paste0("NFut_5_", items)
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target_NFut_10 <- paste0("NFut_10_", items)
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target_5_10past <- paste0("5.10past_", items)
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target_5_10fut <- paste0("5.10fut_", items)
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target_cols <- c(
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target_NPast_5,
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target_NPast_10,
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target_NFut_5,
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target_NFut_10,
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target_5_10past,
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target_5_10fut
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)
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# ============= TROUBLESHOOTING: CHECK COLUMN EXISTENCE =============
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cat("\n=== COLUMN EXISTENCE CHECK ===\n\n")
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# Get actual column names from dataframe (trimmed)
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df_cols <- trimws(names(df))
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# Check Source columns
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missing_source <- source_cols[!source_cols %in% df_cols]
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existing_source <- source_cols[source_cols %in% df_cols]
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cat("Source Columns:\n")
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cat(" Expected: 75 columns\n")
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cat(" Found:", length(existing_source), "columns\n")
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cat(" Missing:", length(missing_source), "columns\n")
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if (length(missing_source) > 0 && length(missing_source) <= 10) {
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cat("\n Missing source columns:\n")
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for (col in missing_source) {
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cat(" -", col, "\n")
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}
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} else if (length(missing_source) > 10) {
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cat("\n Too many missing to list individually (", length(missing_source), "missing)\n")
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}
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cat("\n=== END CHECK ===\n\n")
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# Stop if critical columns are missing
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if (length(missing_source) > 30) {
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stop("ERROR: Too many source columns missing! Please check column names in CSV file.")
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}
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cat("Proceeding with processing...\n\n")
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# ============= CALCULATE DIFFERENCES =============
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cat("Calculating time interval differences...\n")
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# Convert source columns to numeric
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for (col in source_cols) {
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if (col %in% names(df)) {
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df[[col]] <- as.numeric(df[[col]])
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}
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}
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# Helper function to calculate absolute difference
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calc_abs_diff <- function(col1, col2) {
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val1 <- if (col1 %in% names(df)) df[[col1]] else NA
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val2 <- if (col2 %in% names(df)) df[[col2]] else NA
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abs(val1 - val2)
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}
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# Calculate NPast_5: |present - past_5|
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cat(" Calculating NPast_5 differences (present vs past 5 years)...\n")
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for (i in 1:15) {
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target <- target_NPast_5[i]
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source1 <- paste0("present_", items_present[i])
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source2 <- paste0("past_5_", items[i])
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df[[target]] <- calc_abs_diff(source1, source2)
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}
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# Calculate NPast_10: |present - past_10|
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cat(" Calculating NPast_10 differences (present vs past 10 years)...\n")
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for (i in 1:15) {
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target <- target_NPast_10[i]
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source1 <- paste0("present_", items_present[i])
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source2 <- paste0("past_10_", items[i])
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df[[target]] <- calc_abs_diff(source1, source2)
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}
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# Calculate NFut_5: |present - fut_5|
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cat(" Calculating NFut_5 differences (present vs future 5 years)...\n")
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for (i in 1:15) {
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target <- target_NFut_5[i]
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source1 <- paste0("present_", items_present[i])
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source2 <- paste0("fut_5_", items[i])
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df[[target]] <- calc_abs_diff(source1, source2)
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}
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# Calculate NFut_10: |present - fut_10|
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cat(" Calculating NFut_10 differences (present vs future 10 years)...\n")
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for (i in 1:15) {
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target <- target_NFut_10[i]
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source1 <- paste0("present_", items_present[i])
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source2 <- paste0("fut_10_", items[i])
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df[[target]] <- calc_abs_diff(source1, source2)
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}
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# Calculate 5.10past: |past_5 - past_10|
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cat(" Calculating 5.10past differences (past 5 vs past 10 years)...\n")
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for (i in 1:15) {
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target <- target_5_10past[i]
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source1 <- paste0("past_5_", items[i])
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source2 <- paste0("past_10_", items[i])
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df[[target]] <- calc_abs_diff(source1, source2)
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}
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# Calculate 5.10fut: |fut_5 - fut_10|
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cat(" Calculating 5.10fut differences (future 5 vs future 10 years)...\n")
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for (i in 1:15) {
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target <- target_5_10fut[i]
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source1 <- paste0("fut_5_", items[i])
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source2 <- paste0("fut_10_", items[i])
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df[[target]] <- calc_abs_diff(source1, source2)
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}
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cat("\n=== CALCULATION COMPLETE ===\n")
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cat(" 90 difference columns created.\n\n")
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# ============= QUALITY ASSURANCE: RANDOM ROW CHECK =============
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# This function can be run multiple times to check different random rows
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qa_check_random_row <- function() {
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# Pick a random row
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random_row <- sample(1:nrow(df), 1)
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cat("\n========================================\n")
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cat("QA CHECK: Random Row #", random_row, "\n")
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cat("========================================\n\n")
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# Sample one calculation from each type (item 1: pref_read)
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test_item_idx <- 1
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calculations <- list(
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list(name = "NPast_5", target = target_NPast_5[test_item_idx],
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source1 = paste0("present_", items_present[test_item_idx]),
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source2 = paste0("past_5_", items[test_item_idx]),
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desc = "|present - past_5|"),
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list(name = "NPast_10", target = target_NPast_10[test_item_idx],
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source1 = paste0("present_", items_present[test_item_idx]),
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source2 = paste0("past_10_", items[test_item_idx]),
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desc = "|present - past_10|"),
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list(name = "NFut_5", target = target_NFut_5[test_item_idx],
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source1 = paste0("present_", items_present[test_item_idx]),
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source2 = paste0("fut_5_", items[test_item_idx]),
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desc = "|present - fut_5|"),
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list(name = "NFut_10", target = target_NFut_10[test_item_idx],
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source1 = paste0("present_", items_present[test_item_idx]),
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source2 = paste0("fut_10_", items[test_item_idx]),
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desc = "|present - fut_10|"),
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list(name = "5.10past", target = target_5_10past[test_item_idx],
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source1 = paste0("past_5_", items[test_item_idx]),
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source2 = paste0("past_10_", items[test_item_idx]),
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desc = "|past_5 - past_10|"),
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list(name = "5.10fut", target = target_5_10fut[test_item_idx],
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source1 = paste0("fut_5_", items[test_item_idx]),
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source2 = paste0("fut_10_", items[test_item_idx]),
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desc = "|fut_5 - fut_10|")
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)
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cat("Checking sample item: pref_read\n\n")
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for (calc in calculations) {
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cat(sprintf("--- %s ---\n", calc$name))
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cat(sprintf("Formula: %s\n", calc$desc))
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val1 <- if (calc$source1 %in% names(df)) df[random_row, calc$source1] else NA
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val2 <- if (calc$source2 %in% names(df)) df[random_row, calc$source2] else NA
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target_val <- df[random_row, calc$target]
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cat(sprintf(" %s: %s\n", calc$source1, ifelse(is.na(val1), "NA", as.character(val1))))
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cat(sprintf(" %s: %s\n", calc$source2, ifelse(is.na(val2), "NA", as.character(val2))))
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if (!is.na(val1) && !is.na(val2)) {
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expected_diff <- abs(val1 - val2)
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cat(sprintf("\n Calculation: |%.5f - %.5f| = %.5f\n", val1, val2, expected_diff))
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cat(sprintf(" Target (%s): %.5f\n", calc$target, target_val))
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cat(sprintf(" Match: %s\n", ifelse(abs(expected_diff - target_val) < 0.0001, "YES ✓", "NO ✗")))
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} else {
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cat(" Cannot calculate (missing values)\n")
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}
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cat("\n")
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}
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cat("========================================\n")
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cat("END QA CHECK\n")
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cat("========================================\n\n")
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}
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# Run QA check on first random row
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cat("\n\n")
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qa_check_random_row()
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# Instructions for running additional checks
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cat("\n")
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cat("*** TO CHECK ANOTHER RANDOM ROW ***\n")
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cat("Run this command in R console:\n")
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cat(" qa_check_random_row()\n")
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cat("\n")
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# Save the modified dataframe back to CSV
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# na="" writes NA values as empty cells instead of "NA" text
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# COMMENTED OUT FOR REVIEW - Uncomment when ready to save
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# write.csv(df, "eohi2.csv", row.names = FALSE, na = "")
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cat("\n*** WRITE TO FILE IS COMMENTED OUT ***\n")
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cat("Review the output above, then uncomment line 243 to save changes.\n")
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cat("\nProcessing complete! 90 difference columns calculated (not yet saved to file).\n")
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