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Merge pull request #19804 from arsenelupin14/fix-doctest-19716
TST: Enable doctest for dataframes.rst (#19716)
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‎docs/table/dataframes.rst‎

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.. doctest-skip-all
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.. _df_narwhals:
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Interfacing with DataFrames
@@ -39,26 +37,40 @@ Basic Multi-Backend Example
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.. EXAMPLE START: Using Generic Multi-Backend Methods
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Create a table and convert to different DataFrame backends::
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Create a table and convert to different DataFrame backends:
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>>> from astropy.table import Table
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>>> t = Table()
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>>> t['a'] = [1, 2, 3, 4]
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>>> t['b'] = ['a', 'b', 'c', 'd']
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# Convert to pandas DataFrame
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Convert to pandas DataFrame:
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.. doctest-requires:: pandas
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>>> df_pandas = t.to_df("pandas")
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.. doctest-requires:: pandas>=3.0
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>>> type(df_pandas)
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<class 'pandas.core.frame.DataFrame'>
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<class 'pandas.DataFrame'>
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Convert to polars DataFrame:
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.. doctest-requires:: polars
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# Convert to polars DataFrame
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>>> df_polars = t.to_df("polars")
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>>> type(df_polars)
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<class 'polars.dataframe.frame.DataFrame'>
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Create a table from any supported DataFrame::
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Create a table from any supported DataFrame:
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.. doctest-requires:: pandas
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>>> t2 = Table.from_df(df_pandas) # From pandas
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.. doctest-requires:: polars
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>>> t3 = Table.from_df(df_polars) # From polars
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.. EXAMPLE END
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>>> t['a'] = [1, 2, 3, 4]
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>>> t['b'] = ['a', 'b', 'c', 'd']
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Convert to a pandas DataFrame using the pandas-specific method::
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Convert to a pandas DataFrame using the pandas-specific method:
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.. doctest-requires:: pandas
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>>> df = t.to_pandas()
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>>> df
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1 2 b
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2 3 c
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3 4 d
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.. doctest-requires:: pandas>=3.0
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>>> type(df)
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<class 'pandas.core.frame.DataFrame'>
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<class 'pandas.DataFrame'>
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Create a table from a pandas DataFrame::
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Create a table from a pandas DataFrame:
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.. doctest-requires:: pandas
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>>> t2 = Table.from_pandas(df)
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>>> t2
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<Table length=4>
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a b
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int64 string8
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----- -------
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1 a
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2 b
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3 c
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4 d
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a b
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int64 str1
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----- ----
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1 a
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2 b
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3 c
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4 d
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.. EXAMPLE END
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Pandas Index Support
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--------------------
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The pandas-specific methods provide full support for DataFrame indexing, which is a unique pandas feature::
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The pandas-specific methods provide full support for DataFrame indexing, which is a unique pandas feature:
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>>> from astropy.time import Time
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>>> tm = Time([1998, 2002], format="jyear")
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>>> x = [1, 2]
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>>> t = Table([tm, x], names=["tm", "x"])
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# Use a column as the DataFrame index
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Use a column as the DataFrame index:
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.. doctest-requires:: pandas
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>>> df = t.to_pandas(index="tm")
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>>> df.index.name
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'tm'
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# Convert back including the index as a column
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Convert back including the index as a column:
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.. doctest-requires:: pandas
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>>> t_back = Table.from_pandas(df, index=True)
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>>> t_back.colnames
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['tm', 'x']
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Pandas Excel Support
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--------------------
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Read an Excel file into a table by utilizing the pandas backend::
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Read an Excel file into a table by utilizing the pandas backend:
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.. doctest-skip::
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>>> t = Table.from_pandas(pandas.read_excel("myexceltable.xlsx"))
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-- 2.0 b 2021-01-02 00:00:00.000 2.0,5.0 2.0
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3 -- c 2021-01-03 00:00:00.000 3.0,6.0 3.0
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Convert using the pandas-specific method::
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Convert using the pandas-specific method:
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.. doctest-requires:: pandas
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>>> df_pandas = t.to_pandas()
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>>> df_pandas
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1 <NA> 2.0 b 2021-01-02 2.0 5.0 2.0
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2 3 NaN c 2021-01-03 3.0 6.0 3.0
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Convert using the generic method to pandas::
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Convert using the generic method to pandas:
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.. doctest-requires:: pandas
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>>> df_generic = t.to_df("pandas")
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>>> # Results are identical to df_pandas
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Convert to polars using the generic method::
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Convert to polars using the generic method:
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.. doctest-requires:: polars
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>>> df_polars = t.to_df("polars")
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>>> df_polars
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│ 3 ┆ null ┆ c ┆ 2021-01-03 00:00:00 ┆ 3.0 ┆ 6.0 ┆ 3.0 │
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└──────┴──────┴──────┴─────────────────────┴───────┴────────┴─────┘
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Convert back to tables::
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Convert back to tables:
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.. doctest-requires:: pandas
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>>> t_from_pandas = QTable.from_pandas(df_pandas) # Using pandas-specific method
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>>> t_from_generic = QTable.from_df(df_pandas) # Using generic method
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.. doctest-requires:: polars
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>>> t_from_polars = QTable.from_df(df_polars) # From polars DataFrame
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Note the data transformations that occurred:

‎docs/table/pandas.rst‎

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.. doctest-skip-all
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.. _pandas:
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Interfacing with the Pandas Package

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