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Matplotlib.axes.Axes.acorr() in Python

Matplotlib is a library in Python and it is numerical ā€“ mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

matplotlib.axes.Axes.acorr() Function

The Axes.acorr() function in axes module of matplotlib library is used to plot the autocorrelation of x.

Syntax: Axes.acorr(self, 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 ā€˜oā€™

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).

Below examples illustrate the matplotlib.axes.Axes.acorr() function in matplotlib.axes:

Example 1:




# Implementation of matplotlib function
Ā Ā Ā 
import matplotlib.pyplot as plt
import numpy as np
Ā Ā Ā 
# Time series data
neveropen = np.array([24.40, 110.25, 20.05,
Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā 22.00, 61.90, 7.80,Ā 
Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā 15.00, 22.80, 34.90,Ā 
Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā 57.30])
Ā Ā Ā 
# Plot autocorrelation
fig, ax = plt.subplots()
ax.acorr(neveropen, maxlags = 9)
Ā Ā Ā 
# Add labels to autocorrelation
# plotax.xlabel('X-axis')
ax.set_ylabel('Y-axis')
Ā Ā 
ax.set_title('matplotlib.axes.Axes.acorr() Example')
Ā Ā 
plt.show()


Output:

Example 2:




# Implementation of matplotlib function
import matplotlib.pyplot as plt
import numpy as np
Ā Ā Ā 
Ā Ā Ā 
# Fixing random state for reproducibility
np.random.seed(10**7)
neveropen = np.random.randn(100)
Ā Ā 
fig, ax = plt.subplots()
ax.acorr(neveropen, usevlines = True, normed = True,
Ā Ā Ā Ā Ā Ā Ā Ā Ā maxlags = 80, lw = 3)
ax.grid(True)
Ā Ā 
ax.set_title('matplotlib.axes.Axes.acorr() Example')
Ā Ā 
plt.show()


Output:

Thapelo Manthata
Iā€™m a desktop support specialist transitioning into a SharePoint developer role by day and Software Engineering student by night. My superpowers include customer service, coding, the Microsoft office 365 suite including SharePoint and power platform.
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