How to Merge Multiple CSV Files in R (Step-by-Step Example)

You can use the following basic syntax to import and merge multiple CSV files located in the same folder into R:

df <- list.files(path='C:/my/path/to/files') %>% 
  lapply(read_csv) %>% 
  bind_rows

The following step-by-step example shows how to use this syntax in practice.

Step 1: Create & Export Multiple Data Frames

First, we’ll use the following code to create and export three data frames to CSV files:

#create three data frames
df1 <- data.frame(points=c(4, 5, 5, 6, 8, 9),
                  assists=c(3, 2, 4, 4, 6, 3))

df2 <- data.frame(points=c(2, 10, 14, 15),
                  assists=c(3, 2, 9, 3))

df3 <- data.frame(points=c(6, 8, 9),
                  assists=c(10, 6, 4))

#export all three data frames to CSV files
write.csv(df1, 'C:/Users/bob/Documents/my_data_files/df1.csv', row.names=FALSE)
write.csv(df2, 'C:/Users/bob/Documents/my_data_files/df2.csv', row.names=FALSE)
write.csv(df3, 'C:/Users/bob/Documents/my_data_files/df3.csv', row.names=FALSE)

I can navigate to this folder and see that the three CSV files were successfully exported:

Step 2: Import & Merge Multiple CSV Files

Next, we’ll use the following code to import and merge all three CSV files into one data frame in R:

library(dplyr)
library(readr)

#import and merge all three CSV files into one data frame
df <- list.files(path='C:/Users/bob/Documents/my_data_files') %>% 
  lapply(read_csv) %>% 
  bind_rows 

#view resulting data frame
df

# A tibble: 13 x 2
   points assists
       
 1      4       3
 2      5       2
 3      5       4
 4      6       4
 5      8       6
 6      9       3
 7      2       3
 8     10       2
 9     14       9
10     15       3
11      6      10
12      8       6
13      9       4

Notice that all three CSV files have been successfully merged into one data frame.

We can see that the resulting data frame has 13 rows and 2 columns.

Note: If the data frames do not have matching column names, R will still merge all of the data frames and simply fill in missing values with NA values.