Hey there! Since you’ve already converted all your date columns to Date type with as.Date(), computing the day differences between Sub and each of the D1, D2, D3 columns is super straightforward. Here are two common approaches you can use:

Base R Approach #

You can directly subtract the date columns (since Date objects in R support arithmetic operations). The result will be a difftime object, which you can convert to a numeric value (raw day counts) if needed:

# Assuming your data frame is named 'df'
# Calculate differences as difftime objects
df$Diff_D1 <- df$Sub - df$D1
df$Diff_D2 <- df$Sub - df$D2
df$Diff_D3 <- df$Sub - df$D3

# Convert to numeric day counts (optional but often useful)
df$Diff_D1 <- as.numeric(df$Sub - df$D1)
df$Diff_D2 <- as.numeric(df$Sub - df$D2)
df$Diff_D3 <- as.numeric(df$Sub - df$D3)

dplyr/Tidyverse Approach #

If you prefer a more concise, pipe-based workflow, use dplyr::mutate() to create the new difference columns in one go:

library(dplyr)

df <- df %>%
  mutate(
    Diff_D1 = as.numeric(Sub - D1),
    Diff_D2 = as.numeric(Sub - D2),
    Diff_D3 = as.numeric(Sub - D3)
  )

Quick Notes: #

• R automatically handles NA values: if a D column has an NA, the corresponding difference will also be NA—this is usually the desired behavior for missing date data.
• The as.numeric() conversion turns the difftime result (which includes units like "days") into a plain integer representing the exact number of days between the two dates.

内容的提问来源于stack exchange，提问作者Anuradha Ravi