R语言中如何将tapply生成的Class数组转换为数据帧？

Hey Luis, let's work through this problem step by step! I see a couple of small issues in your current code, plus we can make this way more efficient instead of manually binding each year's data.

First, let's fix your existing code #

The main problems are:

• A typo in your table() call (missing a closing parenthesis)
• Incorrect indexing for the 2015 entry (you used a["2015", "1st Qu."] instead of the list-style a[["2015"]][["1st Qu."]])
• A variable name mismatch when setting column names (you referenced losstroke but your data frame is xdata)

Here's the corrected version of your original code:

# Fix the table call first (add closing parenthesis)
table(Data$year, useNA=c("always"))

# Your tapply code is fine
a <- tapply(Data$x, Data$year, summary)

# Correct the indexing and variable name
xdata <- as.data.frame(rbind(
  x2014 <- c(2014, a[["2014"]][["1st Qu."]], a[["2014"]][["Median"]], a[["2014"]][["3rd Qu."]]),
  x2015 <- c(2015, a[["2015"]][["1st Qu."]], a[["2015"]][["Median"]], a[["2015"]][["3rd Qu."]]),
  x2016 <- c(2016, a[["2016"]][["1st Qu."]], a[["2016"]][["Median"]], a[["2016"]][["3rd Qu."]])
))
colnames(xdata) <- c("Year", "Q1", "Median", "Q3")
rm(a, x2014, x2015, x2016)

A better, automated approach (no manual binding!) #

Manually writing out each year isn't scalable if you add more years later. Instead, we can convert that a list directly into a data frame:

Using base R:

# Convert the list of summaries into a data frame
summary_df <- as.data.frame(do.call(rbind, a))
# Add the Year column using the list's names
summary_df$Year <- rownames(summary_df)
# Extract only the columns we need and rename them
final_df <- summary_df[, c("Year", "1st Qu.", "Median", "3rd Qu.")]
colnames(final_df) <- c("Year", "Q1", "Median", "Q3")
# Optional: Convert Year to numeric if needed
final_df$Year <- as.numeric(final_df$Year)

Using dplyr (tidyverse style, even cleaner):

If you're open to using the dplyr package, we can skip the tapply step entirely and summarize directly from your original Data frame—this is more readable and less error-prone:

library(dplyr)

final_df <- Data %>%
  group_by(year) %>%
  summarize(
    Q1 = quantile(x, 0.25, na.rm = TRUE), # Add na.rm=TRUE if you have missing values
    Median = median(x, na.rm = TRUE),
    Q3 = quantile(x, 0.75, na.rm = TRUE)
  )

Why your original code broke #

When you use tapply() with summary, it returns a named list (not a matrix or data frame). Each element of the list is a named numeric vector containing the summary stats for one year. That means you can't use matrix-style indexing like a["2015", "1st Qu."]—you have to use list indexing: a[["2015"]] to get the 2015 summary vector, then [["1st Qu."]] to pull the specific stat from that vector.

内容的提问来源于stack exchange，提问作者Luis Labán