如何处理数据框中含向量的value列并计算各word的均值？

First, let's recreate your data frame in R (assuming the value column is stored as character strings):

# Create the sample data frame
df <- data.frame(
  word = c("a", "b", "c", "d", "e", "f"),
  value = c("3", "c(1, 10, 15, 17)", "8", "c(2,9)", "c(3, 7, 8, 12, 16, 17, 19)", "6"),
  stringsAsFactors = FALSE
)

Step 1: Convert value column to numeric vectors #

Use lapply() to evaluate each string as an R expression, turning them into actual numeric vectors:

# Convert character strings to numeric vectors
df$value <- lapply(df$value, function(x) eval(parse(text = x)))

Now, the value column contains numeric vectors (scalars for single values, multi-element vectors for the c(...) entries).

Step 2: Calculate the mean for each word #

Use sapply() to compute the mean of each vector in the value column:

# Compute mean for each row
df$mean <- sapply(df$value, mean)

Final Result #

Your data frame will now include the mean for each word:

print(df)
#   word                     value      mean
# 1    a                         3  3.000000
# 2    b           1, 10, 15, 17  10.750000
# 3    c                         8  8.000000
# 4    d                     2, 9  5.500000
# 5    e 3, 7, 8, 12, 16, 17, 19  11.714286
# 6    f                         6  6.000000

Notes #

• This approach assumes all entries in the value column are valid R numeric expressions (either single numbers or c(...) vectors). If there are invalid entries, add error handling with tryCatch() to avoid crashes.
• eval(parse(...)) works here because your entries follow valid R syntax, but avoid using this with untrusted input as it can execute arbitrary code.

内容的提问来源于stack exchange，提问作者user21390049