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Pandas Data Series: Create the mean and standard deviation of the data of a given Series


Write a Pandas program to create the mean and standard deviation of the data of a given Series.

Sample Solution :

Python Code :

import pandas as pd
s = pd.Series(data = [1,2,3,4,5,6,7,8,9,5,3])
print("Original Data Series:")
print(s)
print("Mean of the said Data Series:")
print(s.mean())
print("Standard deviation of the said Data Series:")
print(s.std())

Sample Output:

Original Data Series:
0     1
1     2
2     3
3     4
4     5
5     6
6     7
7     8
8     9
9     5
10    3
dtype: int64
Mean of the said Data Series:
4.818181818181818
Standard deviation of the said Data Series:
2.522624895547565                 

Explanation:

In the above code –

s = pd.Series(data = [1,2,3,4,5,6,7,8,9,5,3]): This line creates a Pandas Series object 's' containing a sequence of 11 integer values.print(s.mean()): This line calculates the mean of the values in the Pandas Series object 's' using the .mean() method and prints the result.

print(s.std()): This line calculates the standard deviation of the values in the Pandas Series object 's' using the .std() method and prints the result. The standard deviation is a measure of the spread of the data and is calculated by taking the square root of the average of the squared differences from the mean.

Python-Pandas Code Editor:

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