Attempt to infer better dtypes for object columns.
Attempts soft conversion of object-dtyped columns, leaving non-object and unconvertible columns unchanged. The inference rules are the same as during normal Series/DataFrame construction.
Whether to make a copy for non-object or non-inferable columns or Series.
Note
The copy keyword will change behavior in pandas 3.0. Copy-on-Write will be enabled by default, which means that all methods with a copy keyword will use a lazy copy mechanism to defer the copy and ignore the copy keyword. The copy keyword will be removed in a future version of pandas.
You can already get the future behavior and improvements through enabling copy on write pd.options.mode.copy_on_write = True
See also
to_datetimeConvert argument to datetime.
to_timedeltaConvert argument to timedelta.
to_numericConvert argument to numeric type.
convert_dtypesConvert argument to best possible dtype.
Examples
>>> df = pd.DataFrame({"A": ["a", 1, 2, 3]})
>>> df = df.iloc[1:]
>>> df
A
1 1
2 2
3 3
>>> df.dtypes
A object
dtype: object
>>> df.infer_objects().dtypes
A int64
dtype: object
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/2.3.0/reference/api/pandas.Series.infer_objects.html