pandas.Series.corr¶

Series.corr(other, method='pearson', min_periods=None)[source]¶

Compute correlation with other Series, excluding missing values.

Parameters

otherSeries

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_periodsint, 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

pandas.Series.copy

pandas.Series.count