pandas.DataFrame.corr() function | How to calculate correlation in pandas
pandas.DataFrame.corr(): This function compute pairwise correlation of columns, excluding NA/null values.
Syntax: DataFrame.corr(method=’pearson’, min_periods=1)
Parameters:
method : {‘pearson’, ‘kendall’, ‘spearman’} or callable
pearson : standard correlation coefficient
kendall : Kendall Tau correlation coefficient
spearman : Spearman rank correlation
callable: callable with input two 1d ndarrays
and returning a float .. versionadded:: 0.24.0
min_periods : int, optional
Minimum number of observations required per pair of columns to have a valid result. Currently only available for pearson and spearman correlation
Returns:
y : DataFrame
pandas.DataFrame.corr() function example:
import pandas as pd
df = pd.DataFrame({'A': [5, 2], 'B': [4, 8]})
print("Pearson correlation",df.corr(method='pearson'))
print("kendall correlation",df.corr(method='kendall'))
print("spearman correlation",df.corr(method='spearman'))
Output:
Pearson correlation A B A 1.0 -1.0 B -1.0 1.0 kendall correlation A B A 1.0 -1.0 B -1.0 1.0 spearman correlation A B A 1.0 -1.0 B -1.0 1.0
