pandas.Series.corr
- Series.corr(other, method='pearson', min_periods=None)[source]
-
Compute correlation with other Series, excluding missing values.
- Parameters
-
- other:Series
-
Series with which to compute the correlation.
- method:{‘pearson’, ‘kendall’, ‘spearman’} or callable
-
Method used to compute correlation:
pearson : Standard correlation coefficient
kendall : Kendall Tau correlation coefficient
spearman : Spearman rank correlation
callable: Callable with input two 1d ndarrays and returning a float.
Warning
Note that the returned matrix from corr will have 1 along the diagonals and will be symmetric regardless of the callable’s behavior.
- min_periods:int, optional
-
Minimum number of observations needed to have a valid result.
- Returns
-
- float
-
Correlation with other.
See also
DataFrame.corr
-
Compute pairwise correlation between columns.
DataFrame.corrwith
-
Compute pairwise correlation with another DataFrame or Series.
Examples
>>> def histogram_intersection(a, b): ... v = np.minimum(a, b).sum().round(decimals=1) ... return v >>> s1 = pd.Series([.2, .0, .6, .2]) >>> s2 = pd.Series([.3, .6, .0, .1]) >>> s1.corr(s2, method=histogram_intersection) 0.3
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/1.3.4/reference/api/pandas.Series.corr.html