databricks.koalas.Series.corr¶
-
Series.corr(other, method='pearson') → float[source]¶ Compute correlation with other Series, excluding missing values.
- Parameters
- otherSeries
- method{‘pearson’, ‘spearman’}
pearson : standard correlation coefficient
spearman : Spearman rank correlation
- Returns
- correlationfloat
Notes
There are behavior differences between Koalas and pandas.
the method argument only accepts ‘pearson’, ‘spearman’
the data should not contain NaNs. Koalas will return an error.
Koalas doesn’t support the following argument(s).
min_periods argument is not supported
Examples
>>> df = ks.DataFrame({'s1': [.2, .0, .6, .2], ... 's2': [.3, .6, .0, .1]}) >>> s1 = df.s1 >>> s2 = df.s2 >>> s1.corr(s2, method='pearson') -0.851064...
>>> s1.corr(s2, method='spearman') -0.948683...