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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
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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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56 changes: 29 additions & 27 deletions doc/source/user_guide/basics.rst
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Expand Up @@ -2050,33 +2050,35 @@ 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'`` |
+-------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
+--------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| Kind of Data | Data Type | Scalar | Array | String Aliases |
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looks like this has gone forward by one space 😄 any chance you could bring it back to where it was, to minimise the diff?

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Thank you, @MarcoGorelli . I was wondering why my diff was so unreadable. I deleted one space, now it looks nicer 😄.

Also, I reverted line 73 as you suggested.

+==================================================+===============+===========+========+===========+===============================+========================================+
| :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'`` |
+--------------------------------------------------+---------------------------+--------------------+-------------------------------+----------------------------------------+
| ``nullable float`` | :class:`Float64Dtype`, ...| (none) | :class:`arrays.FloatingArray` | ``'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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