Numerical Computing with Python

How to do it...

1. Read in the flights dataset, and output the first five rows:

>>> flights = pd.read_csv('data/flights.csv')>>> flights.head()

2. If we want to find the distribution of airlines over a range of distances, we need to place the values of the DIST column into discrete bins. Let's use the pandas cut function to split the data into five bins:

>>> bins = [-np.inf, 200, 500, 1000, 2000, np.inf]>>> cuts = pd.cut(flights['DIST'], bins=bins)>>> cuts.head()0 (500.0, 1000.0] 1 (1000.0, 2000.0] 2 (500.0, 1000.0] 3 (1000.0, 2000.0] 4 (1000.0, 2000.0] Name: DIST, dtype: category Categories (5, interval[float64]): [(-inf, 200.0] < (200.0, 500.0] ...