ARIMA Models Identification: Correlograms in Python Videos

Last Update: June 21, 2022

My online video tutorials are hosted at YouTube channel.

For learning this concept, you can view my online video tutorials: ARIMA Models Identification: Correlograms in Python (Spyder) and ARIMA Models Identification: Correlograms in Python (Jupyter).

Videos Code

1. Packages

import pandas as pd
import statsmodels.api as sm
import statsmodels.graphics.tsaplots as tsp
import matplotlib.pyplot as plt

2. Data

mdata_obj = sm.datasets.get_rdataset(dataname="AirPassengers",
                                     package="datasets",
                                     cache=True)
mdata = mdata_obj.data
mdata = pd.DataFrame(data=mdata["value"]).set_index(
    pd.date_range(start="1949", end="1961", freq="M"))
print(mdata.head())
print(mdata_obj.__doc__)

Ranges Delimiting

tdata = mdata[:"1958-12-31"]
fdata = mdata["1959-01-01":]

Chart

plt.plot(tdata)
plt.ylabel("Air Passengers")
plt.xlabel("Year")
plt.show()

3. ARIMA Models Identification

Correlograms

tsp.plot_acf(x=tdata, lags=24, alpha=0.05)
plt.show()

tsp.plot_pacf(x=tdata, lags=24, alpha=0.05)
plt.show()