Numerical Computing with Python

How to do it...

1. Read in the college dataset, create a separate DataFrame with STABBR as the index, and check whether the index is sorted:

>>> college = pd.read_csv('data/college.csv')>>> college2 = college.set_index('STABBR')>>> college2.index.is_monotonicFalse

2. Sort the index from college2 and store it as another object:

>>> college3 = college2.sort_index()>>> college3.index.is_monotonicTrue

3. Time the selection of the state of Texas (TX) from all three DataFrames:

>>> %timeit college[college['STABBR'] == 'TX']1.43 ms ± 53.5 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)>>> %timeit college2.loc['TX']526 µs ± 6.67 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)>>> %timeit college3.loc['TX']183 µs ± 3.67 µs per loop ...