pandas.DataFrame.infer_objects#
- DataFrame.infer_objects(copy=None)[source]#
- 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. - Parameters:
- copybool, default True
- 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
 
- Returns:
- same type as input object
 
 - See also - to_datetime
- Convert argument to datetime. 
- to_timedelta
- Convert argument to timedelta. 
- to_numeric
- Convert argument to numeric type. 
- convert_dtypes
- Convert 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