在列表中执行ifelse()：将符号*替换为0、.替换为1

Hey there! I see you need to replace the * and . symbols in your data structure using R's ifelse() function. Let's walk through how to do this properly.

First, let's clarify: the structure you provided is actually a data frame (not a simple list) in R. Here's how you can use ifelse() to swap * for 0 and . for 1, while keeping other values (like "4", "5", "a") unchanged:

Step 1: Assign your data to a variable #

First, let's make sure we have your data stored properly:

# Store your original data frame
my_df <- structure(
  list(
    `1` = c("4", "*", ".", ".", "*", ".", ".", "*", "*", ".", "*", ".", ".", ".", ".", ".", "."),
    `2` = c("5", ".", ".", ".", ".", ".", "*", ".", ".", ".", "*", ".", ".", ".", ".", "*", ".", "*", ".", ".", "*", "*", "*", "*", "*", "."),
    `3` = c("4", ".", ".", ".", ".", "*", ".", ".", "*", ".", ".", "a", "*", ".", "*", ".", ".")
  ),
  .Names = c("1", "2", "3")
)

Step 2: Use lapply() + ifelse() to process each column #

We'll loop through every column in the data frame, and apply ifelse() to replace the symbols:

# Process each column with nested ifelse()
processed_df <- as.data.frame(
  lapply(my_df, function(column) {
    # First replace * with 0, then . with 1, keep others as-is
    ifelse(column == "*", 0, ifelse(column == ".", 1, column))
  })
)

Step 3: Check the result #

If you print processed_df, you'll see all * are now 0, all . are 1, and values like "4", "5", "a" stay the same.

How this works: #

• lapply(my_df, function(column): This iterates over each column in your data frame, passing one column at a time to the function.
• Nested ifelse(): We first check if the value is *—if yes, replace with 0. If not, check if it's .—replace with 1. Any other value is left unchanged.
• as.data.frame(): Converts the list output from lapply() back into a data frame (since lapply() returns a list by default).

内容的提问来源于stack exchange，提问作者user8248672