From 0eb0940f64ba556935f5847166f135d68a824e15 Mon Sep 17 00:00:00 2001 From: jackgoldsmith4 Date: Fri, 27 May 2022 09:55:22 -0400 Subject: [PATCH 1/3] add to corr docs --- pandas/core/series.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/pandas/core/series.py b/pandas/core/series.py index d1514a3872800..a6c7c55ef556f 100644 --- a/pandas/core/series.py +++ b/pandas/core/series.py @@ -2541,6 +2541,8 @@ def quantile(self, q=0.5, interpolation="linear"): def corr(self, other, method="pearson", min_periods=None) -> float: """ Compute correlation with `other` Series, excluding missing values. + The two `Series` objects are not required to be the same length and will be + aligned internally before the correlation function is applied. Parameters ---------- From 401acf764d3594c7967eed73f7a45715caeff292 Mon Sep 17 00:00:00 2001 From: jackgoldsmith4 Date: Fri, 27 May 2022 09:56:19 -0400 Subject: [PATCH 2/3] add to cov docs --- pandas/core/series.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/pandas/core/series.py b/pandas/core/series.py index a6c7c55ef556f..443537d60393a 100644 --- a/pandas/core/series.py +++ b/pandas/core/series.py @@ -2615,6 +2615,8 @@ def cov( ) -> float: """ Compute covariance with Series, excluding missing values. + The two `Series` objects are not required to be the same length and + will be aligned internally before the covariaance is calculated. Parameters ---------- From f5bba4db3214a5819bb9dbd662b94bba23abf430 Mon Sep 17 00:00:00 2001 From: jackgoldsmith4 Date: Fri, 27 May 2022 09:58:42 -0400 Subject: [PATCH 3/3] fix typo --- pandas/core/series.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/pandas/core/series.py b/pandas/core/series.py index 443537d60393a..e938acd11ba70 100644 --- a/pandas/core/series.py +++ b/pandas/core/series.py @@ -2616,7 +2616,7 @@ def cov( """ Compute covariance with Series, excluding missing values. The two `Series` objects are not required to be the same length and - will be aligned internally before the covariaance is calculated. + will be aligned internally before the covariance is calculated. Parameters ----------