zhuwenxing opened a new issue, #45105:
URL: https://github.com/apache/arrow/issues/45105
### Describe the bug, including details regarding any error messages,
version, and platform.
```
@classmethod
def from_pandas(cls, cls_1, df, Schema_schema=None, preserve_index=None,
nthreads=None, columns=None, bool_safe=True): # real signature unknown;
restored from __doc__
"""
Table.from_pandas(cls, df, Schema schema=None, preserve_index=None,
nthreads=None, columns=None, bool safe=True)
Convert pandas.DataFrame to an Arrow Table.
The column types in the resulting Arrow Table are inferred
from the
dtypes of the pandas.Series in the DataFrame. In the case of
non-object
Series, the NumPy dtype is translated to its Arrow
equivalent. In the
case of `object`, we need to guess the datatype by looking
at the
Python objects in this Series.
Be aware that Series of the `object` dtype don't carry enough
information to always lead to a meaningful Arrow type. In
the case that
we cannot infer a type, e.g. because the DataFrame is of
length 0 or
the Series only contains None/nan objects, the type is set to
null. This behavior can be avoided by constructing an
explicit schema
and passing it to this function.
Parameters
----------
df : pandas.DataFrame
schema : pyarrow.Schema, optional
The expected schema of the Arrow Table. This can be used
to
indicate the type of columns if we cannot infer it
automatically.
If passed, the output will have exactly this schema.
Columns
specified in the schema that are not found in the
DataFrame columns
or its index will raise an error. Additional columns or
index
levels in the DataFrame which are not specified in the
schema will
be ignored.
preserve_index : bool, optional
Whether to store the index as an additional column in
the resulting
``Table``. The default of None will store the index as a
column,
except for RangeIndex which is stored as metadata only.
Use
``preserve_index=True`` to force it to be stored as a
column.
nthreads : int, default None
If greater than 1, convert columns to Arrow in parallel
using
indicated number of threads. By default, this follows
:func:`pyarrow.cpu_count` (may use up to system CPU
count threads).
columns : list, optional
List of column to be converted. If None, use all columns.
safe : bool, default True
Check for overflows or other unsafe conversions.
Returns
-------
Table
Examples
--------
>>> import pyarrow as pa
>>> import pandas as pd
>>> df = pd.DataFrame({'n_legs': [2, 4, 5, 100],
... 'animals': ["Flamingo", "Horse",
"Brittle stars", "Centipede"]})
>>> pa.Table.from_pandas(df)
pyarrow.Table
n_legs: int64
animals: string
----
n_legs: [[2,4,5,100]]
animals: [["Flamingo","Horse","Brittle stars","Centipede"]]
"""
pass
```
### Component(s)
Python
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