April 2018
Beginner
238 pages
7h 13m
English
So, we made sure we had access to the file where we could have downloaded to a local space, if necessary.
We were able to verify the file is as expected using Excel (or some other spreadsheet product). We could have loaded into a text file editor as well, but the display would not have shown the column layouts inherently.
We then used a built-in command to read the file into a data format of use. In this case, the R command was read.csv and the data format was a DataFrame. We changed the column names and removed unused columns to conform to our needs.
A further option available for read.csv (and supported in other languages) is to ignore records containing NA values. There are many datasets available that have this condition—some ...