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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