bigframes.pandas.DataFrame.var#

DataFrame.var(axis:str|int=0,*,numeric_only:bool=False)→Series[source]#

Return unbiased variance over requested axis.

Normalized by N-1 by default.

Examples:

>>>df=bpd.DataFrame({"A":[1,3],"B":[2,4]})>>>df    A       B0   1       21   3       4[2 rows x 2 columns]

Calculating the variance of each column (the default behavior without an explicit axis parameter).

>>>df.var()A    2.0B    2.0dtype: Float64

Calculating the variance of each row.

>>>df.var(axis=1)0    0.51    0.5dtype: Float64

Parameters:

• axis ({index (0),columns (1)}) – Axis for the function to be applied on.For Series this parameter is unused and defaults to 0.

• numeric_only (bool. default False) – Default False. Include only float, int, boolean columns.

Returns:

Series with unbiased variance over requested axis.

Return type:

bigframes.pandas.Series