4. Autoregression

Activity 4.01: Autoregression Model Based on Periodic Data

1. Import the necessary packages, classes, and libraries.

   Note

   This activity will work on an earlier version of pandas, ensure that you downgrade the version of pandas using the command:

   pip install pandas==0.24.2

   The code is as follows:

   import pandas as pd
   import numpy as np
   from statsmodels.tsa.ar_model import AR
   from statsmodels.graphics.tsaplots import plot_acf
   import matplotlib.pyplot as plt

2. Load the data and convert the Date column to datetime:

   df = pd.read_csv('../Datasets/austin_weather.csv')
   df.Date = pd.to_datetime(df.Date)
   print(df.head())
   print(df.tail())

   The output for df.head() should look as follows:

   Figure 4.22: Output for df.head()

   The output for df.tail() should look as follows:

   Figure 4.23: Output for df.tail()

3. Plot the complete set of average temperature values (df.TempAvgF) with Date on the x axis:

   fig, ax = plt.subplots(figsize = (10, 7))
   ax.scatter(df.Date, df.TempAvgF)
   plt...