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How to calculate the measure of dispersion for a data set using python?

Description

To calculate the measure of dispersion for a sample data set in python.

Process

Range:

   Difference between the largest and smallest values.

   It takes largest and smallest value from the data set.

   It uses only the data less than 6 in a data set.

Variance:

   Variance measures how far a data set is spread out.

   The average squared deviation of values from the mean.

Standard Deviation

   It takes all data from the data set.

   We can use standard deviation, if the data in a data set are more than 6.

   Standard Deviation is the square root of variance.

Sample Code

#import pandas library

import pandas as pd

#load the data from CSV file

data=pd.read_csv(‘/home/soft27/

/Sathish/Pythonfiles/Employee.csv’)

#creating the Data Frame

df=pd.DataFrame(data)

print(“Actual data from the CSV file:”)

print(df)

#Calculate the variance

print(“The variance is:”)

print(df.var())

#calculate the standard deviation

print(“The standard deviation is:”)

print(df.std())

Screenshots
Calculate the measure of dispersion for a data set using python
import pandas as pd
Calculate the variance