From 867d6efb7da9a979cde03debe0de16321c5f37dc Mon Sep 17 00:00:00 2001 From: regmibijay Date: Tue, 27 Apr 2021 17:29:58 +0200 Subject: [PATCH 1/2] improved dataframe example to avoid confusion --- pandas/core/frame.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pandas/core/frame.py b/pandas/core/frame.py index 7f970a72cb12c..994abac199366 100644 --- a/pandas/core/frame.py +++ b/pandas/core/frame.py @@ -9827,10 +9827,10 @@ def nunique(self, axis: Axis = 0, dropna: bool = True) -> Series: Examples -------- - >>> df = pd.DataFrame({'A': [1, 2, 3], 'B': [1, 1, 1]}) + >>> df = pd.DataFrame({'A': [4, 5, 6], 'B': [4, 1, 1]}) >>> df.nunique() A 3 - B 1 + B 2 dtype: int64 >>> df.nunique(axis=1) From 9a2a6aa200f44971b047b7816433d56df1598296 Mon Sep 17 00:00:00 2001 From: regmibijay Date: Thu, 29 Apr 2021 14:12:11 +0200 Subject: [PATCH 2/2] simplified explaination of nunique --- pandas/core/frame.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pandas/core/frame.py b/pandas/core/frame.py index 994abac199366..129dbe52c5885 100644 --- a/pandas/core/frame.py +++ b/pandas/core/frame.py @@ -9803,9 +9803,9 @@ def _get_data() -> DataFrame: def nunique(self, axis: Axis = 0, dropna: bool = True) -> Series: """ - Count distinct observations over requested axis. + Count number of distinct elements in specified axis. - Return Series with number of distinct observations. Can ignore NaN + Return Series with number of distinct elements. Can ignore NaN values. Parameters