Learning IPython for Interactive Computing and Data Visualization - Second Edition

Computing with NumPy arrays

We now get to the substance of array programming with NumPy. We will perform manipulations and computations on ndarrays.

Let's first import NumPy, pandas, matplotlib, and seaborn:

In [1]: import numpy as np
        import pandas as pd
        import matplotlib.pyplot as plt
        import seaborn as sns
        %matplotlib inline

We load the NYC taxi dataset with pandas:

In [2]: data = pd.read_csv('../chapter2/data/nyc_data.csv',
                           parse_dates=['pickup_datetime',
                                        'dropoff_datetime'])

We get the pickup and dropoff locations of the taxi rides as ndarrays, using the .values attribute of pandas DataFrames:

In [3]: pickup = data[['pickup_longitude', 'pickup_latitude']].values
        dropoff = data[['dropoff_longitude',
                        'dropoff_latitude']].values
 pickup ...