Expanding.
std
Calculate expanding standard deviation.
Normalized by N-1 by default. This can be changed using the ddof argument.
Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements.
N - ddof
N
For NumPy compatibility. No additional arguments are used.
Returns the same object type as the caller of the expanding calculation.
See also
Series.expanding
Calling object with Series data.
DataFrame.expanding
Calling object with DataFrames.
Series.std
Equivalent method for Series.
DataFrame.std
Equivalent method for DataFrame.
numpy.std
Equivalent method for Numpy array.
Notes
The default ddof of 1 used in Series.std is different than the default ddof of 0 in numpy.std.
A minimum of one period is required for the rolling calculation.
Examples
>>> s = pd.Series([5, 5, 6, 7, 5, 5, 5]) >>> s.rolling(3).std() 0 NaN 1 NaN 2 0.577350 3 1.000000 4 1.000000 5 1.154701 6 0.000000 dtype: float64
>>> s.expanding(3).std() 0 NaN 1 NaN 2 0.577350 3 0.957427 4 0.894427 5 0.836660 6 0.786796 dtype: float64