Matplotlib.pyplot.acorr() in Python

Syntax: matplotlib.pyplot.acorr(x, *, data=None, **kwargs) Parameters: This method accept the following parameters that are described below:

• x: This parameter is a sequence of scalar.
• detrend: This parameter is an optional parameter. Its default value is mlab.detrend_none
• normed: This parameter is also an optional parameter and contains the bool value. Its default value is True
• usevlines: This parameter is also an optional parameter and contains the bool value. Its default value is True
• maxlags: This parameter is also an optional parameter and contains the integer value. Its default value is 10
• linestyle: This parameter is also an optional parameter and used for plotting the data points, only when usevlines is False.
• marker: This parameter is also an optional parameter and contains the string. Its default value is 'o'

Returns: This method returns the following:

• lags:This method returns the lag vector
• c:This method returns the auto correlation vector.
• line : Added LineCollection if usevlines is True, otherwise add Line2D.
• b: This method returns the horizontal line at 0 if usevlines is True, otherwise None.

The resultant is (lags, c, line, b).

# Implementation of matplotlib.pyplot.acorr()
# function

import matplotlib.pyplot as plt
import numpy as np

# Time series data
geeks = np.array([24.40, 110.25, 20.05, 22.00,
                  61.90, 7.80, 15.00, 22.80, 
                  34.90, 57.30])

# Plot autocorrelation
plt.acorr(geeks, maxlags = 9)

# Add labels to autocorrelation plot
plt.title("Autocorrelation of Geeksforgeeks' Users data")
plt.xlabel('X-axis')
plt.ylabel('Y-axis')

# Display the autocorrelation plot
plt.show()

# Implementation of matplotlib.pyplot.acorr() 
# function

import matplotlib.pyplot as plt
import numpy as np


# Fixing random state for reproducibility
np.random.seed(10**7)

geeks = np.random.randn(51 )

plt.title("Autocorrelation Example")
plt.acorr(geeks, usevlines = True, 
          normed = True, maxlags = 50, 
          lw = 2)

plt.grid(True)
plt.show()