Improving Performance and Readability of Proportion Calculations with Data Tables
Based on your request, here is a revised version of your code with improvements for performance and readability:
# Calculate proportions for each column except "area_ha"
myColumns <- setdiff(colnames(df)[-1], "area_ha")
for (name in myColumns) {
# Use dcast to spread the data into columns and sum across rows
tempdf <- data.table::dcast(df, id ~ name, fun = sum)
# Calculate proportions by dividing by row sums and multiplying by 100
tempdf[, name := tempdf[name] / rowSums(tempdf[, name], na.rm = TRUE) * 100]
# Merge the temporary data frame with df_fin using the id column
df_fin <- left_join(df_fin, tempdf, by = "id")
}
This code first defines a list of columns (myColumns) that do not include area_ha. It then iterates over each column in this list. For each column, it uses the dcast function from the data.table package to spread the data into new columns and sums across rows. After calculating the proportions for these new columns, it merges the temporary data frame (tempdf) with df_fin using the id column.
The key improvements in this code are:
- It uses
setdiffto definemyColumns, which is more concise than listing each column individually. - It uses a
forloop to iterate over the columns, which makes it easier to add or remove columns from the calculation without modifying the code. - It uses the
left_joinfunction instead ofright_jointo ensure that all observations are preserved in the final data frame.
Note: Make sure you have the data.table package installed. If not, install it with install.packages("data.table").
Last modified on 2024-01-16