40 lines
1.5 KiB
R
40 lines
1.5 KiB
R
library(dplyr)
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setwd("/home/ladmin/Documents/DND/EOHI/eohi3/dataREVIEW-JAN21")
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# Read the data (with check.names=FALSE to preserve original column names)
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# Keep empty cells as empty strings, not NA
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# Only convert the literal string "NA" to NA, not empty strings
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df <- read.csv("eohi3_raw.csv", stringsAsFactors = FALSE, check.names = FALSE, na.strings = "NA")
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# Populate citizenship column from taq_cit_1 and taq_cit_2
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# If both have values, set to "Both"
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# Otherwise, use the value from whichever column has a value
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# Empty values remain as empty strings (not NA)
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# Ensure citizenship column exists, initialize with empty strings if needed
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if (!"citizenship" %in% names(df)) {
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df$citizenship <- ""
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}
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# Convert NA to empty string for taq_cit columns to ensure consistent handling
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df$taq_cit_1[is.na(df$taq_cit_1)] <- ""
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df$taq_cit_2[is.na(df$taq_cit_2)] <- ""
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# Populate citizenship based on taq_cit_1 and taq_cit_2 using base R
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# Check if both have values (non-empty)
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both_have_values <- df$taq_cit_1 != "" & df$taq_cit_2 != ""
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# Check if only taq_cit_1 has a value
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only_cit1 <- df$taq_cit_1 != "" & df$taq_cit_2 == ""
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# Check if only taq_cit_2 has a value
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only_cit2 <- df$taq_cit_2 != "" & df$taq_cit_1 == ""
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# Assign values
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df$citizenship[both_have_values] <- "Both"
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df$citizenship[only_cit1] <- df$taq_cit_1[only_cit1]
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df$citizenship[only_cit2] <- df$taq_cit_2[only_cit2]
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# For rows where neither has a value, citizenship keeps its original value (may be empty string)
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write.csv(df, "eohi3_raw.csv", row.names = FALSE, na = "", quote = TRUE)
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