From ebe32befc5242bc3f0eedc5ae37335c9f196b991 Mon Sep 17 00:00:00 2001 From: Paul Reidy Date: Thu, 12 Oct 2017 23:17:50 +0100 Subject: [PATCH] DOC: Adding examples to update docstring (#16812) --- pandas/core/frame.py | 36 ++++++++++++++++++++++++++++++++++++ pandas/core/series.py | 32 ++++++++++++++++++++++++++++++++ 2 files changed, 68 insertions(+) diff --git a/pandas/core/frame.py b/pandas/core/frame.py index c7e8c0da75e2c..21849dbd59d7f 100644 --- a/pandas/core/frame.py +++ b/pandas/core/frame.py @@ -4154,6 +4154,42 @@ def update(self, other, join='left', overwrite=True, filter_func=None, raise_conflict : boolean If True, will raise an error if the DataFrame and other both contain data in the same place. + + Examples + -------- + >>> df = pd.DataFrame({'A': ['a', 'b', 'c'], + 'B': [1, 2, 3]}) + >>> new_df = pd.DataFrame({'B': ['d', 'e', 'f'], + 'C': ['g', 'h', 'i']}) + >>> df.update(new_df) + >>> df + A B + 0 a d + 1 b e + 2 c f + >>> df = pd.DataFrame({'A': ['a', 'b', 'c'], + 'B': [1, 2, 3]}) + >>> new_column = pd.Series(['d', 'e', 'f'], name='B') + >>> df.update(new_column) + >>> df + A B + 0 a d + 1 b e + 2 c f + + If ``other`` contains NaNs the corresponding values are not updated + in the original dataframe. + + >>> df = pd.DataFrame({'A': ['a', 'b', 'c'], + 'B': [1, 2, 3]}) + >>> new_df = pd.DataFrame({'B': ['d', np.nan, 'f']}) + >>> df.update(new_df) + >>> df + A B + 0 a d + 1 b 2 + 2 c f + """ import pandas.core.computation.expressions as expressions # TODO: Support other joins diff --git a/pandas/core/series.py b/pandas/core/series.py index 8499f8b55d2d0..e8668a38b6b2a 100644 --- a/pandas/core/series.py +++ b/pandas/core/series.py @@ -1780,6 +1780,38 @@ def update(self, other): Parameters ---------- other : Series + + Examples + -------- + >>> s = pd.Series(['a', 'b', 'c', 'd']) + >>> s.update(pd.Series([1, 2, 3, 4])) + >>> s + 0 1 + 1 2 + 2 3 + 3 4 + dtype: object + + >>> s = pd.Series(['a', 'b', 'c', 'd']) + >>> s.update(pd.Series([1, 4], index=[0, 3])) + >>> s + 0 1 + 1 b + 2 c + 3 4 + dtype: object + + If ``other`` contains NaNs the corresponding values are not updated + in the original Series. + + >>> s = pd.Series(['a', 'b', 'c', 'd']) + >>> s.update(pd.Series([1, 2, np.nan, 4])) + >>> s + 0 1 + 1 2 + 2 c + 3 4 + dtype: object """ other = other.reindex_like(self) mask = notna(other)