How do you calculate the standard deviation of a column titled “Age” in the pandas DataFrame df?A.df['Age'].std()B.df[Age].std()C.df['Age'].stdD.df[Age].std

The correct way to calculate the standard deviation of a column titled “Age” in the pandas DataFrame df is A. df['Age'].std(). Here is the step by step process:

1. Import the pandas library:

import pandas as pd

2. Create or load your DataFrame. For example, if you have a DataFrame named df, it might look something like this:

df = pd.DataFrame({'Age': [23, 29, 21, 25, 22, 26, 24, 23, 25, 24]})

3. Use the std() function on the 'Age' column of the DataFrame:

std_dev = df['Age'].std()

4. Print the standard deviation:

print(std_dev)

This will give you the standard deviation of the ages in the DataFrame. The std() function calculates the standard deviation, which is a measure of the amount of variation or dispersion of a set of values.