have a list of large csv dfs in R, all data frames have a common "ID" column. How can I merge all dfs matching ID's and also include rows that dont?

Question

I would like to merge all data frames in a list. All dfs have different columns but have "ID" column in common. I would like to merge all dfs on ID but also include IDs that dont match as well. I figure I would have to do an outer merge but am not sure. Can anyone please help with this please? I would like one master csv file with all ID's in the dfs and merge all the ones that overlap.

library("readr")
library("dplyr")
library("plyr")
library("readxl")
library("data.table")

getwd()
setwd("./Users/Desktop/CTRI")
ctri_data <- list.files(path = "/Users/Desktop/CTRI",
                        pattern = "*.csv",              
                        recursive = TRUE,  
                        full.names = TRUE)  


# Read all csv files in the folder and create a list of dataframes
df.list <- lapply(ctri_data , read.csv)

Try `Reduce(function(...) merge(..., all = TRUE, by = "ID"), df.list)` — akrun, May 02 '22 at 23:03
sorry could you clarify what should be entered for the "..." — mwc201, May 02 '22 at 23:15
It is 3 dots representing for variadic elements. You dont have to enter anything — akrun, May 03 '22 at 16:13

have a list of large csv dfs in R, all data frames have a common "ID" column. How can I merge all dfs matching ID's and also include rows that dont?

0 Answers0