.corrcoef()

In NumPy, the .corrcoef() method computes the Pearson correlation coefficient of two specified arrays and returns an array as the result.

Syntax

numpy.corrcoef(x, y=None, rowvar=True, dtype=None)

• x: The first array to be used for computing the Pearson correlation coefficient.
• y (Optional): The second array to be used for computing the Pearson correlation coefficient.
• rowvar (Optional): If True (default), then each row represents a variable and each column contains an observation. If False, then the roles are reversed.
• dtype (Optional): Specifies the return data type.

Example

The following example demonstrates the usage of the .corrcoef() method:

# Importing the NumPy library
import numpy as np

# Defining two arrays
arr1 = np.array([6, 21, 37])
arr2 = np.array([1, 25, 51])

# Using the .corrcoef() method
res = np.corrcoef(arr1, arr2)

# Printing the result
print(res)

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The above code produces the following output:

[[1.         0.99999002]
 [0.99999002 1.        ]]

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Codebyte Example

Run the following codebyte example to understand the use of the .corrcoef() method:

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