pandas.core.window.expanding.Expanding.min#
- Expanding.min(numeric_only=False, engine=None, engine_kwargs=None)[source]#
Calculate the expanding minimum.
- Parameters:
- numeric_onlybool, default False
Include only float, int, boolean columns.
Added in version 1.5.0.
- enginestr, default None
'cython'
: Runs the operation through C-extensions from cython.'numba'
: Runs the operation through JIT compiled code from numba.None
: Defaults to'cython'
or globally settingcompute.use_numba
Added in version 1.3.0.
- engine_kwargsdict, default None
For
'cython'
engine, there are no acceptedengine_kwargs
For
'numba'
engine, the engine can acceptnopython
,nogil
andparallel
dictionary keys. The values must either beTrue
orFalse
. The defaultengine_kwargs
for the'numba'
engine is{'nopython': True, 'nogil': False, 'parallel': False}
Added in version 1.3.0.
- Returns:
- Series or DataFrame
Return type is the same as the original object with
np.float64
dtype.
See also
pandas.Series.expanding
Calling expanding with Series data.
pandas.DataFrame.expanding
Calling expanding with DataFrames.
pandas.Series.min
Aggregating min for Series.
pandas.DataFrame.min
Aggregating min for DataFrame.
Notes
See Numba engine and Numba (JIT compilation) for extended documentation and performance considerations for the Numba engine.
Examples
>>> ser = pd.Series([2, 3, 4, 1], index=['a', 'b', 'c', 'd']) >>> ser.expanding().min() a 2.0 b 2.0 c 2.0 d 1.0 dtype: float64