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DOC: Fixing EX01 - Added examples #54242

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Jul 24, 2023
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DOC: Fixing EX01 - Added examples #54242

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3 changes: 0 additions & 3 deletions ci/code_checks.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -85,8 +85,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.util.hash_array \
pandas.util.hash_pandas_object \
pandas_object \
pandas.api.interchange.from_dataframe \
pandas.DatetimeIndex.snap \
pandas.api.indexers.BaseIndexer \
pandas.api.indexers.VariableOffsetWindowIndexer \
pandas.api.extensions.ExtensionDtype \
Expand All @@ -102,7 +100,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
pandas.api.extensions.ExtensionArray._values_for_factorize \
pandas.api.extensions.ExtensionArray.interpolate \
pandas.api.extensions.ExtensionArray.ravel \
pandas.DataFrame.__dataframe__
RET=$(($RET + $?)) ; echo $MSG "DONE"

fi
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16 changes: 16 additions & 0 deletions pandas/core/frame.py
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Expand Up @@ -912,6 +912,22 @@ def __dataframe__(

`nan_as_null` currently has no effect; once support for nullable extension
dtypes is added, this value should be propagated to columns.

Examples
--------
>>> df_not_necessarily_pandas = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
>>> interchange_object = df_not_necessarily_pandas.__dataframe__()
>>> interchange_object.column_names()
Index(['A', 'B'], dtype='object')
>>> df_pandas = (pd.api.interchange.from_dataframe
... (interchange_object.select_columns_by_name(['A'])))
>>> df_pandas
A
0 1
1 2

These methods (``column_names``, ``select_columns_by_name``) should work
for any dataframe library which implements the interchange protocol.
"""

from pandas.core.interchange.dataframe import PandasDataFrameXchg
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11 changes: 11 additions & 0 deletions pandas/core/indexes/datetimes.py
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Expand Up @@ -487,6 +487,17 @@ def snap(self, freq: Frequency = "S") -> DatetimeIndex:
Returns
-------
DatetimeIndex

Examples
--------
>>> idx = pd.DatetimeIndex(['2023-01-01', '2023-01-02',
... '2023-02-01', '2023-02-02'])
>>> idx
DatetimeIndex(['2023-01-01', '2023-01-02', '2023-02-01', '2023-02-02'],
dtype='datetime64[ns]', freq=None)
>>> idx.snap('MS')
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just when I thought I'd seen all the methods

DatetimeIndex(['2023-01-01', '2023-01-01', '2023-02-01', '2023-02-01'],
dtype='datetime64[ns]', freq=None)
"""
# Superdumb, punting on any optimizing
freq = to_offset(freq)
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16 changes: 16 additions & 0 deletions pandas/core/interchange/from_dataframe.py
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Expand Up @@ -44,6 +44,22 @@ def from_dataframe(df, allow_copy: bool = True) -> pd.DataFrame:
Returns
-------
pd.DataFrame

Examples
--------
>>> df_not_necessarily_pandas = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
>>> interchange_object = df_not_necessarily_pandas.__dataframe__()
>>> interchange_object.column_names()
Index(['A', 'B'], dtype='object')
>>> df_pandas = (pd.api.interchange.from_dataframe
... (interchange_object.select_columns_by_name(['A'])))
>>> df_pandas
A
0 1
1 2

These methods (``column_names``, ``select_columns_by_name``) should work
for any dataframe library which implements the interchange protocol.
"""
if isinstance(df, pd.DataFrame):
return df
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