var() – Variance Function in python pandas is used to calculate variance of a given set of numbers, Variance of a data frame, Variance of column or column wise variance in pandas python and Variance of rows or row wise variance in pandas python, let’s see an example of each. We need to use the package name “statistics” in calculation of variance. In this tutorial we will learn,
- How to find the variance of a given set of numbers
- How to find variance of a dataframe in pandas python
- How to find the variance of a column in pandas dataframe
- How to find row wise variance of a pandas dataframe
Syntax of variance Function in python
Parameters :
axis : {rows (0), columns (1)}
skipna : Exclude NA/null values when computing the result
level : If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series
ddof : Delta Degrees of Freedom. The divisor used in calculations is N – ddof, where N represents the number of elements.
numeric_only : Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.
Variance Function in Python pandas
Simple variance function is shown below
# calculate variance import numpy as np print(np.var([1,9,5,6,8,7])) print(np.var([4,-11,-5,16,5,7,9]))
output:
8.97881103594
Variance of a dataframe in pandas python:
Create dataframe
import pandas as pd
import numpy as np
#Create a DataFrame
d = {
'Name':['Alisa','Bobby','Cathrine','Madonna','Rocky','Sebastian','Jaqluine',
'Rahul','David','Andrew','Ajay','Teresa'],
'Score1':[62,47,55,74,31,77,85,63,42,32,71,57],
'Score2':[89,87,67,55,47,72,76,79,44,92,99,69],
'Score3':[56,86,77,45,73,62,74,89,71,67,97,68]}
df = pd.DataFrame(d)
print df
So the resultant dataframe will be
Variance of the dataframe in pandas python:
# variance of the dataframe df.var()
will calculate the variance of the dataframe across columns so the output will be
Score2 311.636364
Score3 206.083333
dtype: float64
Column variance of the dataframe in pandas:
# column variance of the dataframe df.var(axis=0)
axis=0 argument calculates the column wise variance of the dataframe so the result will be
Score2 311.636364
Score3 206.083333
dtype: float64
Row variance of the dataframe in pandas:
# Row variance of the dataframe df.var(axis=1)
axis=1 argument calculates the row wise variance of the dataframe so the result will be
Calculate the variance of the specific Column in pandas
# variance of the specific column df.loc[:,"Score1"].var()
the above code calculates the variance of the “Score1” column so the result will be
