Selecting DataFrame rows and columns simultaneously

Directly using the indexing operator is the correct method to select one or more columns from a DataFrame. However, it does not allow you to select both rows and columns simultaneously. To select rows and columns simultaneously, you will need to pass both valid row and column selections separated by a comma to either the .iloc or .loc indexers.

 

Getting ready

The generic form to select rows and columns will look like the following code:

>>> df.iloc[rows, columns]
>>> df.loc[rows, columns]

The rows and columnsvariables may be scalar values, lists, slice objects, or boolean sequences.

Note

Passing a boolean sequence to the indexers is covered in Chapter 11, Boolean Indexing.

In this recipe, each step shows a simultaneous row and column selection using .iloc and its exact replication using .loc.

How to do it...

1. Read in the college dataset, and set the index as the institution name. Select the first three rows and the first four columns...