Writing Multiple Data Frames into .CSV Files Using R

Writing multiple data frames into .csv files using R

Here's a self-contained example along the lines of Richard's comment, but uses the names of the dataframes in the list as filenames for the CSV files:

# Create a list of n data frames

n <- 10

my_list <- lapply(1:n, function(i)  data.frame(x = rnorm(10), y = rnorm(10)) )

# name the data frames

names(my_list) <- letters[1:n]

# save each new data frame as an individual .csv file based on its name

lapply(1:length(my_list), function(i) write.csv(my_list[[i]], 
                                      file = paste0(names(my_list[i]), ".csv"),
                                      row.names = FALSE))

Export multiple data frames into .csv files using R

Iterate over the data frame names. We assume all names start with d and are of length 3. Modify the pattern if not or directly set nms if you know them. We also make a second check that the names are data frames but you can omit that check if you are sure that there are no objects that are not data frames and have a name matching the pattern.

nms <- ls(pattern = "^d..$")
for(nm in nms) {
  X <- get(nm)
  if (is.data.frame(X)) {
    filename <- paste0(nm, ".csv")
    message("writing out ", filename)
    write.csv(X, file = filename, row.names = FALSE)
  }
}

Write different data frame in one .csv file with R

write.csv just calls write.table under the hood, with appropriate arguments. So you can achieve what you want with 3 calls to write.table.

write.table(df1, "filename.csv", col.names=TRUE, sep=",")
write.table(df2, "filename.csv", col.names=FALSE, sep=",", append=TRUE)
write.table(df3, "filename.csv", col.names=FALSE, sep=",", append=TRUE)

Actually, you could avoid the whole issue by combining your data frames into a single df with rbind, then calling write.csv once.

write.csv(rbind(df1, d32, df3), "filename.csv")

How to write multiple .csv files from a list of data frames into a new folder with the original filename?

Given that points_calculated is a list of data.frames, and the names(points_calculated) are the filename you want, you can do the following:

library(purrr)
points_calculated %>%
  iwalk(
    ~ readr::write_csv(.x, file = paste("./ExperimentFolder/PointsFolder", .y))
  )
)

imap() will iterate over your list, and perform the function after ~. .x is the element of the list (the data.frame), and .y is it's name.

Write multiple data frames to csv-file using purrr::map

map() and walk() both work, but walk() doesn't print anything, whereas map() will.

Invisible output

list(iris = iris, mtcars = mtcars) %>%
  names(.) %>%
  walk(~ write_csv(dfs[[.]], paste0("data-raw/", ., ".csv")))

Prints output to console

list(iris = iris, mtcars = mtcars) %>%
  names(.) %>%
  map(~ write_csv(dfs[[.]], paste0("data-raw/", ., ".csv")))

Write data frame to multiple csv's in R

# Split dataframe by city
split_df <- split(df, list(df$city))

# Write out separate CSV for each city
for (city in names(split_df)) {
    write.csv(split_df[[city]], paste0(city, ".csv"))
}

Saving multiple data-frames to single csv file using Shiny downloadHandler

Other options:

1. Write an Excel workbook with one sheet per
   dataframe
2. Zip together multiple csv
   files

Here's a sample of both options using four dataframes from the R Datasets Package.

library(shiny)
library(xlsx)

shinyApp(
    ui = fluidPage(
        downloadButton("downloadExcelSheet", "Download Excel Workbook with Multiple Sheets"),
        downloadButton("downloadZippedCSV", "Download zipped csv files")
    ),
    server = function(input, output) { 

        #### Write an Excel workbook with one sheet per dataframe ####
        output$downloadExcelSheet <- downloadHandler(
            filename = function() {
                "excelWorkbook.xlsx"
            },
            content = function(file) {
                # write workbook and first sheet
                write.xlsx(mtcars, file, sheetName = "mtcars", append = FALSE)

                # add other sheets for each dataframe
                listOtherFiles <- list(iris = iris, 
                                       airquality = airquality, 
                                       sleep = sleep)
                for(i in 1:length(listOtherFiles)) {
                    write.xlsx(listOtherFiles[i], file, 
                               sheetName = names(listOtherFiles)[i], append = TRUE)
                }
            }
        )

        #### Zip together multiple csv files ####
        output$downloadZippedCSV <- downloadHandler(
            filename = function() {
                "zippedCSV.zip"
            },
            content = function(file) {
                # go to temp dir to avoid permission issues
                owd <- setwd(tempdir())
                on.exit(setwd(owd))

                # create list of dataframes and NULL value to store fileNames
                listDataFrames <- list(mtcars = mtcars, 
                                       iris = iris,
                                       airquality = airquality,
                                       sleep = sleep)
                allFileNames <- NULL

                # loop through each dataframe
                for(i in 1:length(listDataFrames)) {
                    # write each dataframe as csv and save fileName
                    fileName <- paste0(names(listDataFrames)[i], ".csv")
                    write.csv(listDataFrames[1], fileName)
                    allFileNames <- c(fileName, allFileNames)
                }

                # write the zip file
                zip(file, allFileNames) 

            }
        )
    }
)

How to export multiple .csv-files?

ls() has pattern argument to get the object name based on specific pattern in the data. You may try -

my_list <- ls(pattern = '^data')

purrr::imap(mget(my_list),
             ~write.csv(.x, sprintf('data_%s.csv', .y), row.names = FALSE))

To keep it completely in base R -

tmp <- mget(my_list)
Map(function(x, y) write.csv(x, y, row.names = FALSE), tmp, 
                   sprintf('data_%s.csv', names(tmp)))

where mget returns a named list of dataframes.

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