使用R语言将多行转单列：DataFrame-1转换为目标DataFrame-2

Hey there! Let's sort out this DataFrame reshaping task in R. Since you need to convert DataFrame-1 to your target DataFrame-2 (turning multi-row data into a single column), I’ll walk you through two common scenarios and the simplest ways to pull this off using both tidyverse tools and base R.

Scenario 1: Convert wide-format columns into a single long column #

This is the classic "wide to long" reshaping—say you have multiple columns of data, and you want all their rows stacked into one single column.

Example DataFrame-1 (wide format):

df1 <- data.frame(
  Category = c("Group A", "Group B", "Group C"),
  Metric1 = c(10, 20, 30),
  Metric2 = c(15, 25, 35),
  Metric3 = c(12, 22, 32)
)

Target DataFrame-2 (single column):

df2 <- data.frame(
  AllValues = c(10, 15, 12, 20, 25, 22, 30, 35, 32)
)

How to do it:

Using tidyr::pivot_longer() (tidyverse, most flexible):

library(tidyr)

# If you don't need to keep the Category column:
df2 <- df1 %>%
  pivot_longer(
    cols = everything(),  # Grab all columns
    names_to = NULL,      # We don't care about original column names
    values_to = "AllValues"  # Name for our new single column
  )

# If you want to keep the Category and sort by it first:
df2 <- df1 %>%
  pivot_longer(
    cols = starts_with("Metric"),  # Only select the Metric columns
    names_to = NULL,
    values_to = "AllValues"
  ) %>%
  arrange(Category)

Using base R stack() (quick for simple cases):

# Works if all columns are the same data type
df2 <- data.frame(AllValues = stack(df1)$values)

Scenario 2: Combine multiple rows per group into a single cell in one column #

If your goal is to aggregate rows from the same group into a single string entry in a column (e.g., merging all values for a single ID into one cell), here's how:

Example DataFrame-1 (grouped rows):

df1 <- data.frame(
  ID = c(1, 1, 1, 2, 2),
  Item = c("Apple", "Banana", "Cherry", "Date", "Elderberry")
)

Target DataFrame-2 (aggregated single column):

df2 <- data.frame(
  ID = c(1, 2),
  CombinedItems = c("Apple, Banana, Cherry", "Date, Elderberry")
)

How to do it:

Using dplyr + tidyr (tidyverse):

library(dplyr)

df2 <- df1 %>%
  group_by(ID) %>%
  summarise(
    CombinedItems = paste(Item, collapse = ", ")  # Use any delimiter you want
  ) %>%
  ungroup()

Using base R aggregate():

df2 <- aggregate(Item ~ ID, data = df1, FUN = function(x) paste(x, collapse = ", "))

Just adjust the column names (like Metric, ID, Item) to match your actual DataFrame-1 structure, and you’ll get exactly the DataFrame-2 you need.

内容的提问来源于stack exchange，提问作者userRC