如何在R中通过向量名称与列名模糊匹配填充DataFrame？

Here's a concise base R approach to map your vectors to the DataFrame columns by matching substrings between column names and vector element names:

# Initialize your data
df <- data.frame(matrix(NA, ncol = 3, nrow = 4))
colnames(df) <- c("AA", "BB", "CC")

vec1 <- c(1, 2, 3)
names(vec1) <- c("BB745", "456AA", "123CC3")

vec2 <- c(4, 5, 6)
names(vec2) <- c("BB745", "456AA", "123CC3")

# Function to map a vector to the df column order (reusable for multiple vectors)
map_vector_to_df <- function(vec, target_cols) {
  sapply(target_cols, function(col) vec[grepl(col, names(vec))])
}

# Fill the first two rows
df[1, ] <- map_vector_to_df(vec1, colnames(df))
df[2, ] <- map_vector_to_df(vec2, colnames(df))

# Check the result
df

Output: #

AA BB CC
1  2  1  3
2  5  4  6
3 NA NA NA
4 NA NA NA

How it works: #

• The map_vector_to_df function uses sapply to loop through each column name in your DataFrame.
• For each column name, grepl(col, names(vec)) identifies which element name in the vector contains the column name as a substring.
• We extract the corresponding value from the vector and arrange it to match the DataFrame's column order.
• Assigning these results to df[1, ] and df[2, ] fills your desired rows with the correct values.

If you prefer an even more compact version (using R 4.1+ lambda syntax), you can skip the function and write directly:

df[1,] <- sapply(colnames(df), \(x) vec1[grepl(x, names(vec1))])
df[2,] <- sapply(colnames(df), \(x) vec2[grepl(x, names(vec2))])

This method is lightweight, uses only base R, and assumes each column name matches exactly one element name in the vectors (which aligns with your example).

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