Using Pandas Autocorrelation Plot - how to limit x-axis to make it more readable?

Question

I am using python 3.7.

I am performing time series forecasting using an ARIMA model. I am assessing the properties of my data for ARIMA using an Autocorrelation Plot - specifically using autocorrelation_plot from pandas.plotting.

My data has 50,000 records or so, making the plot extremely busy and hard to pick out any specific trends. Is there a way to limit the x-axis to bring the first few hundred lags more into focus?

I can't share the actual plot, but my code is as follow:

import pandas as pd
from pandas.plotting import autocorrelation_plot

#Import Data
time_series_2619 = pd.read_csv("Consumption/2619.csv", parse_dates=['Date/Time'], index_col = ['Date/Time'])['Recording']

#Auto Correlation Plot
autocorrelation_plot(time_series_2619)

I couldn't find anything in the documentation.

Answer 1

autocorrelation_plot returns a matplotlib.axis object. Hence, you can simply use the set_xlim() method to limit the x-axis:

ax = autocorrelation_plot(time_series_2619)
ax.set_xlim([0, 500])

Answer 2

Alternatively, you can use the plot_acf() function and specify the lags.

# import the plotting functions for act and pacf  
from statsmodels.graphics.tsaplots import plot_acf, plot_pacf
plot_acf(df1['Thousands of Passengers'], lags=40);