求助：如何将R语言DataFrame转换为指定格式表格

Hey there! Let's figure out how to reshape your data into that wide-format table you want. You've got a long-format dataset where each row is a respondent's score for their major, and you want to flip it so Majors are columns, Respondents are rows, and the cells hold the corresponding score values. Here are three solid ways to do this in R:

1. Using tidyr::pivot_wider (Tidyverse Recommended) #

This is the most intuitive and flexible method if you're using the tidyverse toolkit. First, make sure you have the package installed, then run this:

# Load the tidyverse package (includes tidyr)
library(tidyverse)

# Your original data setup
Respond<-as.factor(c(1,2,3,4,5,6,7,8,9,10,11,12)) 
Major<-as.factor(c("AD","B","E","AD","B","AD","B","E","AD", "E","AD","E")) 
score<-c(2.5,0.5,2,3,2,2,1,1,1,0.5,3,1.5) 
data<-data.frame(Respond,Major,score)

# Reshape to wide format
wide_data <- data %>%
  pivot_wider(names_from = Major,  # Use Major values as column names
              values_from = score) # Fill cells with score values

# Check the result
print(wide_data)

2. Using reshape2::dcast #

If you prefer the older reshape2 package (still widely used), this works too:

# Load reshape2
library(reshape2)

# Reshape with dcast
wide_data_dcast <- dcast(data, Respond ~ Major, value.var = "score")

print(wide_data_dcast)

The formula Respond ~ Major tells R: "Use Respond values as rows, Major values as columns, and fill with the 'score' variable."

3. Base R reshape Function #

No extra packages needed here—just use R's built-in reshape tool:

# Reshape with base R
wide_data_base <- reshape(data, 
                          idvar = "Respond",  # Identify rows by Respondent
                          timevar = "Major",  # Use Major to create columns
                          direction = "wide") # Switch to wide format

# Clean up column names (remove the "score." prefix)
colnames(wide_data_base) <- gsub("score\\.", "", colnames(wide_data_base))

print(wide_data_base)

All three methods will give you the exact table structure you're looking for. The pivot_wider method is especially nice because it plays well with other tidyverse functions if you need to do more data cleaning or analysis later.

内容的提问来源于stack exchange，提问作者Daeyoon