You have imported and transformed data. It resides within your R environment as a data frame. Now you will need to provide it to marketing. The following are two common ways to export data from R into a file for use elsewhere in an organization:
Writing data to a CSV file
Writing data to a tab-delimited text file
These methods are similar, but they produce different results. Knowing about them and their differences will help you decide the format you would like to use.
CSV files are common among data applications. Other data applications, such as Excel, can read these types of file. CSV files are also useful because database systems can typically import them into their environment, just as you imported a CSV into the R environment. The
write.csv() function is used to write a data frame to a CSV file. In this example, the input parameters include
report and the name of the output file,
write.csv(report, "revenue_report.csv", row.names = FALSE)
You also used a
row.names = FALSE parameter. Very often, your dataset will not contain row names. This parameter prevents R from adding a column of numerical identifiers to the CSV file. There are many other parameters you can use with
write.csv(). Learn more about them by typing
?write.csv in the R console.
There may be times when you would like to have your data read by a data application that does not import CSV files. Recall that in the Extracting data from sources section, that
read.csv() had a more flexible counterpart,
write.table() function provides you with greater flexibility on how the final file is composed:
write.table(report, "revenue_report.txt", row.names = FALSE, sep = "\t")
write.table() function uses a syntax that is very similar to
write.csv(). You see the addition of
sep = "\t". This tells R to separate data with the tab character when creating the text file. There are many other parameters you can use with
write.table(). Learn more about them by typing
?write.table in the R console.