请求协助：在data.frame中重复指定变量行并填充缺失值

Hey there! Let's work through your data wrangling task together. I'll walk you through two common approaches—using the tidyverse suite and base R—to get your desired output.

First, let's define a sample version of your input data to make this concrete:

# Sample input data frame
original_df <- data.frame(
  var1 = c("A", "B", "C"),
  var2 = c(10, 20, 30),
  var3 = c(NA, 5, NA)
)

Approach 1: Using Tidyverse (dplyr + tidyr) #

This method is intuitive and produces clean, readable code. We'll first fill missing var3 values with 0, then repeat each row 3 times (which keeps var3 tied to its original row while duplicating var1 and var2):

library(dplyr)
library(tidyr)

# Process the data
target_df <- original_df %>%
  # Replace NA in var3 with 0 (coalesce is a cleaner alternative to ifelse here)
  mutate(var3 = coalesce(var3, 0)) %>%
  # Repeat each row 3 times
  uncount(3)

# View the result
target_df

Approach 2: Using Base R #

If you prefer not to load external packages, this base R method achieves the same result:

# Step 1: Fill NA in var3 with 0
original_df$var3[is.na(original_df$var3)] <- 0

# Step 2: Repeat var1/var2 3 times per row, and match with var3
target_df <- data.frame(
  var1 = rep(original_df$var1, each = 3),
  var2 = rep(original_df$var2, each = 3),
  var3 = rep(original_df$var3, each = 3)
)

# View the result
target_df

Expected Output #

Both methods will produce this final data frame:

var1 var2 var3
1    A   10    0
2    A   10    0
3    A   10    0
4    B   20    5
5    B   20    5
6    B   20    5
7    C   30    0
8    C   30    0
9    C   30    0

内容的提问来源于stack exchange，提问作者chermen