Truth.var#
missionbio.demultiplex.dna.truth.Truth.var
- Truth.var(axis=None, skipna=True, level=None, ddof=1, numeric_only=None, **kwargs)#
Return unbiased variance over requested axis.
Normalized by N-1 by default. This can be changed using the ddof argument.
- Parameters:
- axis{index (0), columns (1)}
For Series this parameter is unused and defaults to 0.
- skipnabool, default True
Exclude NA/null values. If an entire row/column is NA, the result will be NA.
- levelint or level name, default None
If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series.
Deprecated since version 1.3.0: The level keyword is deprecated. Use groupby instead.
- 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 None
Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.
Deprecated since version 1.5.0: Specifying
numeric_only=None
is deprecated. The default value will beFalse
in a future version of pandas.
- Returns:
- Series or DataFrame (if level specified)
Examples
>>> df = pd.DataFrame({'person_id': [0, 1, 2, 3], ... 'age': [21, 25, 62, 43], ... 'height': [1.61, 1.87, 1.49, 2.01]} ... ).set_index('person_id') >>> df age height person_id 0 21 1.61 1 25 1.87 2 62 1.49 3 43 2.01
>>> df.var() age 352.916667 height 0.056367
Alternatively,
ddof=0
can be set to normalize by N instead of N-1:>>> df.var(ddof=0) age 264.687500 height 0.042275
< Class Truth