Login Register

Series.corr()

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

Compute correlation with other Series, excluding missing values

Parameters:

other : Series

method : {?pearson?, ?kendall?, ?spearman?}

pearson : standard correlation coefficient
kendall : Kendall Tau correlation coefficient
spearman : Spearman rank correlation

min_periods : int, optional

Minimum number of observations needed to have a valid result

Returns:

correlation : float

Links:

http://pandas.pydata.org/pandas-docs/version/0.19.2/generated/pandas.Series.corr.html

doc_Pandas

2017-01-12 04:53:30

Comments

Leave a Comment

Please login to continue.

Popular Articles

Rolling.corr() Rolling.corr(other=None, pairwise=None, **kwargs) [source] rolling sample correlation Parameters: other : Series, DataFrame, or ndarray, optiona

Expanding.corr() Expanding.corr(other=None, pairwise=None, **kwargs) [source] expanding sample correlation Parameters: other : Series, DataFrame, or ndarray, opt

DataFrameGroupBy.corr() DataFrameGroupBy.corr(method='pearson', min_periods=1) Compute pairwise correlation of columns, excluding NA/null values Parameters: method : {?

EWM.corr() EWM.corr(other=None, pairwise=None, **kwargs) [source] exponential weighted sample correlation Parameters: other : Series, DataFrame, or ndarray

DataFrame.corr() DataFrame.corr(method='pearson', min_periods=1) [source] Compute pairwise correlation of columns, excluding NA/null values Parameters: method :