pandas.Series.std

Series.std(*, axis=None, skipna=True, ddof=1, numeric_only=False, **kwargs)

Return sample standard deviation.

Normalized by N-1 by default. This can be changed using the ddof argument.

Parameters:

axis{index (0)}

This parameter is unused and defaults to 0.

skipnabool, default True

Exclude NA/null values. If Series is NA, the result will be NA.

ddofint, default 1

Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements.

numeric_onlybool, default False

Not implemented for Series.

**kwargs

Additional keywords have no effect but might be accepted for compatibility with NumPy.

Returns:

scalar

Standard deviation over all values in the Series.

See also

numpy.std

Compute the standard deviation along the specified axis.

Series.var

Return unbiased variance over requested axis.

Series.sem

Return unbiased standard error of the mean over requested axis.

Series.mean

Return the mean of the values over the requested axis.

Series.median

Return the median of the values over the requested axis.

Series.mode

Return the mode(s) of the Series.

Examples

>>> s = pd.Series([1, 2, 3])
>>> s.std()
1.0

Alternatively, ddof=0 can be set to normalize by $N$ instead of $N-1$:

>>> s.std(ddof=0)
0.816496580927726