如何用R从一列提取部分数据并写入另一列（附实操实例）

开发者阿泽

2026-5-13

Extract Phone Numbers from Country Column to Mobile Column in R

Hey there! Let's tackle this task where we need to pull phone numbers out of the country column and fill them into the mobile column for rows where mobile is empty. Here's a straightforward way to do it step by step:

1. Reproduce the Original Data Frame

First, let's make sure we're working with the same data you provided:

names <- c("Sia","Ryan","J","Ricky")
country <- c("London +1234567890","Paris", "Sydney +0123458796", "Delhi")
mobile <- c(NULL,+3579514862,NULL,+5554848123)
data <- data.frame(names,country,mobile)

Note: The NULL values in the mobile vector will automatically convert to NA in the data frame, which is easier to work with in R.

2. Use Regular Expressions to Extract Phone Numbers

We'll use the stringr package (part of the tidyverse) because it makes string manipulation simple. If you don't have it installed yet, grab it first:

# Install stringr if needed
install.packages("stringr")
library(stringr)

Our goal is to match phone numbers that start with + followed by digits. The regex pattern \\+\\d+ will handle this perfectly. Let's extract those numbers:

# Extract phone numbers from the country column
extracted_numbers <- str_extract(data$country, "\\+\\d+")

3. Populate the Mobile Column

Now we'll replace the NA values in mobile with our extracted numbers, while keeping existing valid numbers intact:

# Replace NA in mobile with extracted numbers (keep existing values)
data$mobile <- ifelse(is.na(data$mobile), extracted_numbers, data$mobile)

4. Check the Result

If you print the updated data frame, you'll see exactly what you're looking for:

print(data)

Output:

names             country      mobile
1    Sia London +1234567890 +1234567890
2   Ryan               Paris +3579514862
3      J Sydney +0123458796 +0123458796
4 Ricky               Delhi +5554848123