Import and export data to CSV

In R you can import your data from external data sources. One of the most popular scenario is when you want to analyze data from a .csv file. I will describe this use case below.

Import data from a file

To import data from a .csv file to R use read_csv from readr which is a part of tidyverse.

For example, if you want to import data from a file named file_to_import.csv in your working directory and save it in a data frame named df, use:

library(tidyverse)
df <- read_csv('file_to_import.csv')

Sometimes you need some extra options like header or separator.

If you don't want to import first line of your file, use col_names = FALSE option.

Also if you have column separator other than comma , use delim';' option - you can declare your separator in this place.

Example of the code with options mentioned above:

df <- read_csv('file_to_import.csv', col_names = FALSE, delim = ';')

Where is my working directory?

To check the working directory type in the R console:

getwd()

[1] "/Users/michal"

Export data

After having conducted the analysis you may want to save the results in a file to use it in some other tools. To do this you need the write_csv function.

If you want to save data from a data frame called ga.data you can use the following code:

write_csv(ga.data, "exported_data.csv")

As a result R will export data to the .csv file. You can open it in every text editor or spreadsheet (i.e. Microsoft Excel). The other use case is to upload data as custom dimension or campaign cost data to Google Analytics.

Where can I find saved file?

Your saved .csv file is in your working directory.