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DOC: list supported float dtypes I #50738

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DOC: list supported float dtypes I
natmokval Jan 13, 2023
7f6f544
DOC: list supported float dtypes II
natmokval Jan 26, 2023
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DOC: list supported float dtypes III
natmokval Jan 28, 2023
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63 changes: 36 additions & 27 deletions doc/source/user_guide/basics.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -2050,33 +2050,42 @@ The following table lists all of pandas extension types. For methods requiring `
arguments, strings can be specified as indicated. See the respective
documentation sections for more on each type.

+-------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| Kind of Data | Data Type | Scalar | Array | String Aliases |
+=================================================+===============+===========+========+===========+===============================+========================================+
| :ref:`tz-aware datetime <timeseries.timezone>` | :class:`DatetimeTZDtype` | :class:`Timestamp` | :class:`arrays.DatetimeArray` | ``'datetime64[ns, <tz>]'`` |
| | | | | |
+-------------------------------------------------+---------------+-----------+--------------------+-------------------------------+----------------------------------------+
| :ref:`Categorical <categorical>` | :class:`CategoricalDtype` | (none) | :class:`Categorical` | ``'category'`` |
+-------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`period (time spans) <timeseries.periods>` | :class:`PeriodDtype` | :class:`Period` | :class:`arrays.PeriodArray` | ``'period[<freq>]'``, |
| | | | ``'Period[<freq>]'`` | |
+-------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`sparse <sparse>` | :class:`SparseDtype` | (none) | :class:`arrays.SparseArray` | ``'Sparse'``, ``'Sparse[int]'``, |
| | | | | ``'Sparse[float]'`` |
+-------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`intervals <advanced.intervalindex>` | :class:`IntervalDtype` | :class:`Interval` | :class:`arrays.IntervalArray` | ``'interval'``, ``'Interval'``, |
| | | | | ``'Interval[<numpy_dtype>]'``, |
| | | | | ``'Interval[datetime64[ns, <tz>]]'``, |
| | | | | ``'Interval[timedelta64[<freq>]]'`` |
+-------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`nullable integer <integer_na>` | :class:`Int64Dtype`, ... | (none) | :class:`arrays.IntegerArray` | ``'Int8'``, ``'Int16'``, ``'Int32'``, |
| | | | | ``'Int64'``, ``'UInt8'``, ``'UInt16'``,|
| | | | | ``'UInt32'``, ``'UInt64'`` |
+-------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`Strings <text>` | :class:`StringDtype` | :class:`str` | :class:`arrays.StringArray` | ``'string'`` |
+-------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`Boolean (with NA) <api.arrays.bool>` | :class:`BooleanDtype` | :class:`bool` | :class:`arrays.BooleanArray` | ``'boolean'`` |
+-------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
+---------------------------------------------------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
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Could you post a screenshot of how this looks? It's somewhat hard to see what changed from the diff

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so, the issue is fixed? Right ! or can i still push my changes? I am new in open source

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Yes, if interested in contributing you can find an issue that hasn't been assigned yet or doesn't have an open pull request

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Ok, thank you. So on an issue only one person can pull a request at one time?

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Yes

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Ok thanks mroeschke

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dtypes_pandas

This is a screenshot of that part of the table.
As Marco said, there is no need to add NumPy integer and NumPy float to the table of pandas extension types. I corrected the table and left only "nullable float" under "nullable integer" (without the rest). This implies that we shouldn’t resize the table.

| Kind of Data | Data Type | Scalar | Array | String Aliases |
+=============================================================================================+===============+===========+========+===========+===============================+========================================+
| :ref:`tz-aware datetime <timeseries.timezone>` | :class:`DatetimeTZDtype` | :class:`Timestamp` | :class:`arrays.DatetimeArray` | ``'datetime64[ns, <tz>]'`` |
| | | | | |
+---------------------------------------------------------------------------------------------+---------------+-----------+--------------------+-------------------------------+----------------------------------------+
| :ref:`Categorical <categorical>` | :class:`CategoricalDtype` | (none) | :class:`Categorical` | ``'category'`` |
+---------------------------------------------------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`period (time spans) <timeseries.periods>` | :class:`PeriodDtype` | :class:`Period` | :class:`arrays.PeriodArray` | ``'period[<freq>]'``, |
| | | | ``'Period[<freq>]'`` | |
+---------------------------------------------------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`sparse <sparse>` | :class:`SparseDtype` | (none) | :class:`arrays.SparseArray` | ``'Sparse'``, ``'Sparse[int]'``, |
| | | | | ``'Sparse[float]'`` |
+---------------------------------------------------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`intervals <advanced.intervalindex>` | :class:`IntervalDtype` | :class:`Interval` | :class:`arrays.IntervalArray` | ``'interval'``, ``'Interval'``, |
| | | | | ``'Interval[<numpy_dtype>]'``, |
| | | | | ``'Interval[datetime64[ns, <tz>]]'``, |
| | | | | ``'Interval[timedelta64[<freq>]]'`` |
+---------------------------------------------------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`nullable integer <integer_na>` | :class:`Int64Dtype`, ... | (none) | :class:`arrays.IntegerArray` | ``'Int8'``, ``'Int16'``, ``'Int32'``, |
| | | | | ``'Int64'``, ``'UInt8'``, ``'UInt16'``,|
| | | | | ``'UInt32'``, ``'UInt64'`` |
+---------------------------------------------------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| `NumPy integer <https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.integer>`_ | :class:`numpy.integer` | :class:`int` | :class:`arrays.IntegerArray` | ``'int8'``, ``'int16'``, ``'int32'``, |
| | | | | ``'int64'``, ``'uint8'``, ``'uint16'``,|
| | | | | ``'uint32'``, ``'uint64'`` |
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I don't think this needs adding, as this table says

The following table lists all of pandas extension types

All that needs adding is "nullable float" under "nullable integer"

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Thank you, @MarcoGorelli . As you suggested, I added "nullable float" to the table and removed integer and float.

I noticed that there is no link to “nullable float”
Wouldn’t be useful to have a description and examples for “nullable float”, as we have for “nullable integer”

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yeah, maybe - currently there's no user guide page on nullable floats, but perhaps there should be

+---------------------------------------------------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| ``nullable float`` | :class:`Float64Dtype`, ...| (none) | :class:`arrays.FloatingArray` | ``'Float32'``, ``'Float64'`` |
+---------------------------------------------------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| `NumPy float <https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.floating>`_ | :class:`numpy.floating` | :class:`float` | :class:`arrays.FloatingArray` | ``'float16'``, ``'float32'``, |
| | | | | ``'float64'`` |
+---------------------------------------------------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`Strings <text>` | :class:`StringDtype` | :class:`str` | :class:`arrays.StringArray` | ``'string'`` |
+---------------------------------------------------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| :ref:`Boolean (with NA) <api.arrays.bool>` | :class:`BooleanDtype` | :class:`bool` | :class:`arrays.BooleanArray` | ``'boolean'`` |
+---------------------------------------------------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+

pandas has two ways to store strings.

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2 changes: 1 addition & 1 deletion pandas/core/tools/numeric.py
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Expand Up @@ -70,7 +70,7 @@ def to_numeric(

- 'integer' or 'signed': smallest signed int dtype (min.: np.int8)
- 'unsigned': smallest unsigned int dtype (min.: np.uint8)
- 'float': smallest float dtype (min.: np.float32)
- 'float': float dtype (min.: np.float32), float16 is not supported.
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TBH I think this one's clear enough as it is - if it says min: np.float32, then that already implies float16 not being supported

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This is a good point. After re-consideration, I agree.

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let's revert this change


As this behaviour is separate from the core conversion to
numeric values, any errors raised during the downcasting
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