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