Trusted answers to developer questions
What is a pandas autocorrelation plot in Python?
Fouzia BashirOverview
Autocorrelation plots are specifically used to check the randomness between data points of a dataset. In time series analysis, correlation is computed parallel to each data point at varying time lags to determine their relationship.
pandas.plotting.autocorrelation_plot()
Syntax
pandas.plotting.autocorrelation_plot(series, ax=None, **kwargs)
Parameters
series: It should be a time series instance.ax: It shows matplotlib axis object. Its default value isNone.**kwargs: These are keyword arguments.
Return value
It returns a matplotlib.axis.Axes object.
Example
In this example, we draw an autocorrelation plot on randomly generated data points.
# importing libraries
import pandas as pd
import matplotlib.pyplot as plot
import numpy as np
# creating a sample space of 500 values
data = np.linspace(-10, np.pi*5, num=500)
# creating a series of random values
_series = pd.Series(np.cos(data) * np.random.rand(500))
# generate autocorrelation plot
pd.plotting.autocorrelation_plot(_series)
# save above generated graph as PNG file in output directory
plot.savefig("output/graph.png")Explanation
- Lines 2–4: We load the
pandas,matplotlib, andnumpylibraries. - Line 6: We invoke
np.linspace()to generate500sample values between-10andnp.pi * 5. - Line 8: We generate a
_seriesseries of random numbers. - Line 10: The
pd.plotting.autocorrelation_plot()method generates an autocorrelation plot of the above-created series of random numbers. - Line 12: We save the graph in the output directory as a
PNG Portable Network Graphics
RELATED TAGS
python
CONTRIBUTOR
Fouzia BashirRELATED COURSES
View all Courses
Keep Exploring
Related Courses
