Activity 13.01 – Creating a time series model

In this activity, as a data analyst for a bike-share startup, you are provided with a dataset that has hourly unit rentals for a bike-share business. You are tasked to create a very simple model to predict the rentals one week in advance. Here, you will use linear regression from scikit-learn, which you saw in Chapter 11, Data Modeling –Regression:

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 few rows:

Figure 13.25 – The bike_share.csv data

3. You need to create a datetime index. Construct a new datetime-valued column as a combination of the date and the hour and...