Solution 13.1

Perform the following steps to complete the activity:

1. For this activity, you will need the pandas library, the matplotlib.pyplot library, and the sklearn.linear_model.LinearRegression module. Load them in the first cell of the notebook:

   import pandas as pd
   import matplotlib.pyplot as plt
   from sklearn.linear_model import LinearRegression

2. Read in the bike_share.csv data from the Datasets directory and list the first five rows using .head():

   rental_data = pd.read_csv('../Datasets/bike_share.csv')
   rental_data.head()

This produces the following:

Figure 15.72 – The first five rows of the bike_share data

3. You need to create a datetime index. Begin by creating a column that combines the date and hour strings into a datetime-like string, and then convert that string to a datetime, storing the result in a column. Finally, set the index to the new column, so there is a datetime index:

   rental_data['date_time&apos...