Get the number of rows and columns of a multiple CSV file - r

Question

Is there any way to get information about the number of rows and columns of a multiple CSV file in R and save it in a CSV file? Here is my R code:
#Library
if (!require("tidyverse")) install.packages("tidyverse")
if (!require("fs")) install.packages("fs")
#Mentioning Files Location
file_paths <- fs::dir_ls("C:\\Users\\Desktop\\FileCount\\Test")
file_paths[[2]]
#Reading Multiple CSV Files
file_paths %>%
map(function(path)
{
read_csv(path,col_names = FALSE)
})
#Counting Number of Rows
lapply(X = file_paths, FUN = function(x) {
length(count.fields(x))
})
#Counting Number of Columns
lapply(X = file_paths, FUN = function(x) {
length(ncol(x))
})
#Saving CSV File
write.csv(file_paths,"C:\\Users\\Desktop\\FileCount\\Test\\FileName.csv", row.names = FALSE)
Couple of things are not working:
Number of Columns of a multiple CSV file
When I am saving the file, I want to save Filename, number of rows and number of columns. See attached image.
How the output looks like:
Attached some CSV Files for testing: Here
Any help appreciated.

Answer 1

Welcome on SO! Using the tidyverse and data.table, here's a way to do it:
Note: All the .csv files are in my TestStack directory, but you can change it with your own directory (C:/Users/Desktop/FileCount/Test).
Code:
library(tidyverse)
csv.file <- list.files("TestStack") # Directory with your .csv files
data.frame.output <- data.frame(number_of_cols = NA,
number_of_rows = NA,
name_of_csv = NA) #The df to be written
MyF <- function(x){
csv.read.file <- data.table::fread(
paste("TestStack", x, sep = "/")
)
number.of.cols <- ncol(csv.read.file)
number.of.rows <- nrow(csv.read.file)
data.frame.output <<- add_row(data.frame.output,
number_of_cols = number.of.cols,
number_of_rows = number.of.rows,
name_of_csv = str_remove_all(x,".csv")) %>%
filter(!is.na(name_of_csv))
}
map(csv.file, MyF)
Output:
number_of_cols number_of_rows name_of_csv
1 3 2150 CH_com
2 2 34968 epci_com_20
3 3 732 g1g4
4 7 161905 RP
I have this output because my TestStack had 4 files named CH_com.csv, epci_com_20.csv,...
You can then write the object data.frame.output to a .csv as you wanted: data.table::fwrite(data.frame.output, file = "Output.csv")

Answer 2

files_map <- "test"
files <- list.files(files_map)
library(data.table)
output <- data.table::rbindlist(
lapply(files, function(file) {
dt <- data.table::fread(paste(files_map, file, sep = "/"))
list("number_of_cols" = ncol(dt), "number_of_rows" = nrow(dt), "name_of_csv" = file)
})
)
data.table::fwrite(output, file = "Filename.csv")
Or with map and a seperate function to do the tasks, but without using an empty table first and update it with a global assignment. I see this happen a lot on apply functions, while it is not needed at all.
myF <- function(file) {
dt <- data.table::fread(paste(files_map, file, sep = "/"))
data.frame("number_of_cols" = ncol(dt), "number_of_rows" = nrow(dt), "name_of_csv" = file)
}
output <- do.call(rbind, map(files, myF))