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Update multiple instances of dtype_backend parameter description to…
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… make them all consistent (#54104)

update dtype_backend description instances so that they are all the same
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@tpaxman
tpaxman authored Jul 13, 2023
1 parent 0511c49 commit 4b27e94
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Showing 14 changed files with 140 additions and 119 deletions.
13 changes: 9 additions & 4 deletions pandas/core/dtypes/cast.py
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Expand Up @@ -1004,11 +1004,16 @@ def convert_dtypes(
infer_objects : bool, defaults False
Whether to also infer objects to float/int if possible. Is only hit if the
object array contains pd.NA.
dtype_backend : str, default "numpy_nullable"
Nullable dtype implementation to use.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* "numpy_nullable" returns numpy-backed nullable types
* "pyarrow" returns pyarrow-backed nullable types using ``ArrowDtype``
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
Returns
-------
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15 changes: 8 additions & 7 deletions pandas/core/generic.py
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Expand Up @@ -6737,13 +6737,14 @@ def convert_dtypes(
dtypes if the floats can be faithfully casted to integers.
.. versionadded:: 1.2.0
dtype_backend : {"numpy_nullable", "pyarrow"}, default "numpy_nullable"
Which dtype_backend to use, e.g. whether a DataFrame should use nullable
dtypes for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
The dtype_backends are still experimential.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
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15 changes: 8 additions & 7 deletions pandas/core/tools/numeric.py
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Original file line number Diff line number Diff line change
Expand Up @@ -88,13 +88,14 @@ def to_numeric(
the dtype it is to be cast to, so if none of the dtypes
checked satisfy that specification, no downcasting will be
performed on the data.
dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
The dtype_backends are still experimential.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
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15 changes: 8 additions & 7 deletions pandas/io/clipboards.py
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Expand Up @@ -37,13 +37,14 @@ def read_clipboard(
A string or regex delimiter. The default of ``'\\s+'`` denotes
one or more whitespace characters.
dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g., whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when ``'numpy_nullable'`` is set, pyarrow is used for all
dtypes if ``'pyarrow'`` is set.
The dtype_backends are still experimental.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
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15 changes: 8 additions & 7 deletions pandas/io/excel/_base.py
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Expand Up @@ -286,13 +286,14 @@
.. versionadded:: 1.2.0
dtype_backend : {{"numpy_nullable", "pyarrow"}}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
The dtype_backends are still experimential.
dtype_backend : {{'numpy_nullable', 'pyarrow'}}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
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15 changes: 8 additions & 7 deletions pandas/io/feather_format.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,13 +89,14 @@ def read_feather(
.. versionadded:: 1.2.0
dtype_backend : {{"numpy_nullable", "pyarrow"}}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
The dtype_backends are still experimential.
dtype_backend : {{'numpy_nullable', 'pyarrow'}}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
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15 changes: 8 additions & 7 deletions pandas/io/html.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1121,13 +1121,14 @@ def read_html(
.. versionadded:: 1.5.0
dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
The dtype_backends are still experimential.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
Expand Down
15 changes: 8 additions & 7 deletions pandas/io/json/_json.py
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Original file line number Diff line number Diff line change
Expand Up @@ -662,13 +662,14 @@ def read_json(
.. versionadded:: 1.2.0
dtype_backend : {{"numpy_nullable", "pyarrow"}}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
The dtype_backends are still experimential.
dtype_backend : {{'numpy_nullable', 'pyarrow'}}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
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15 changes: 8 additions & 7 deletions pandas/io/orc.py
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Original file line number Diff line number Diff line change
Expand Up @@ -63,13 +63,14 @@ def read_orc(
Output always follows the ordering of the file and not the columns list.
This mirrors the original behaviour of
:external+pyarrow:py:meth:`pyarrow.orc.ORCFile.read`.
dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
The dtype_backends are still experimential.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
Expand Down
15 changes: 8 additions & 7 deletions pandas/io/parquet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -533,13 +533,14 @@ def read_parquet(
.. deprecated:: 2.0
dtype_backend : {{"numpy_nullable", "pyarrow"}}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
The dtype_backends are still experimential.
dtype_backend : {{'numpy_nullable', 'pyarrow'}}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
Expand Down
29 changes: 15 additions & 14 deletions pandas/io/parsers/readers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -416,14 +416,14 @@
.. versionadded:: 1.2
dtype_backend : {{'numpy_nullable', 'pyarrow'}}, defaults to NumPy backed DataFrame
Back-end data type to use for the :class:`~pandas.DataFrame`. For
``'numpy_nullable'``, have NumPy arrays, nullable ``dtypes`` are used for all
``dtypes`` that have a
nullable implementation when ``'numpy_nullable'`` is set, pyarrow is used for all
dtypes if ``'pyarrow'`` is set.
dtype_backend : {{'numpy_nullable', 'pyarrow'}}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
The ``dtype_backends`` are still experimental.
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
Expand Down Expand Up @@ -1319,13 +1319,14 @@ def read_fwf(
infer_nrows : int, default 100
The number of rows to consider when letting the parser determine the
`colspecs`.
dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
The dtype_backends are still experimential.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
Expand Down
13 changes: 7 additions & 6 deletions pandas/io/spss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,13 +36,14 @@ def read_spss(
Return a subset of the columns. If None, return all columns.
convert_categoricals : bool, default is True
Convert categorical columns into pd.Categorical.
dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
The dtype_backends are still experimential.
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
Expand Down
54 changes: 29 additions & 25 deletions pandas/io/sql.py
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Original file line number Diff line number Diff line change
Expand Up @@ -305,13 +305,14 @@ def read_sql_table(
chunksize : int, default None
If specified, returns an iterator where `chunksize` is the number of
rows to include in each chunk.
dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
The dtype_backends are still experimential.
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
Expand Down Expand Up @@ -443,13 +444,14 @@ def read_sql_query(
{‘a’: np.float64, ‘b’: np.int32, ‘c’: ‘Int64’}.
.. versionadded:: 1.3.0
dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
The dtype_backends are still experimential.
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
Expand Down Expand Up @@ -576,13 +578,14 @@ def read_sql(
chunksize : int, default None
If specified, return an iterator where `chunksize` is the
number of rows to include in each chunk.
dtype_backend : {"numpy_nullable", "pyarrow"}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
The dtype_backends are still experimential.
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
dtype : Type name or dict of columns
Expand Down Expand Up @@ -1631,13 +1634,14 @@ def read_table(
chunksize : int, default None
If specified, return an iterator where `chunksize` is the number
of rows to include in each chunk.
dtype_backend : {{"numpy_nullable", "pyarrow"}}, defaults to NumPy dtypes
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
The dtype_backends are still experimential.
dtype_backend : {'numpy_nullable', 'pyarrow'}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
Expand Down
15 changes: 8 additions & 7 deletions pandas/io/xml.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -1014,13 +1014,14 @@ def read_xml(
{storage_options}
dtype_backend : {{"numpy_nullable", "pyarrow"}}, defaults to NumPy backed DataFrames
Which dtype_backend to use, e.g. whether a DataFrame should have NumPy
arrays, nullable dtypes are used for all dtypes that have a nullable
implementation when "numpy_nullable" is set, pyarrow is used for all
dtypes if "pyarrow" is set.
The dtype_backends are still experimential.
dtype_backend : {{'numpy_nullable', 'pyarrow'}}, default 'numpy_nullable'
Back-end data type applied to the resultant :class:`DataFrame`
(still experimental). Behaviour is as follows:
* ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
(default).
* ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
DataFrame.
.. versionadded:: 2.0
Expand Down

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