How to I compute standard deviation of specific years using dataframe

To calculate the standard deviation of specific years in a dataframe, you can use the groupby function in pandas to group the data by year, and then apply the std function to calculate the standard deviation of each group.

Here’s an example code snippet:

import pandas as pd

# create sample dataframe
data = {'year': [2018, 2018, 2019, 2019, 2020, 2020],
        'value': [10, 20, 30, 40, 50, 60]}
df = pd.DataFrame(data)

# group by year and calculate standard deviation
std_by_year = df.groupby('year')['value'].std()

# print standard deviation of each year
print(std_by_year)

In this example, we have a dataframe with two columns, year and value. We want to calculate the standard deviation of value for each year.

We use the groupby function to group the data by year. We then apply the std function to the value column of each group, which calculates the standard deviation of the values in that group.

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The result is a series with the standard deviation of value for each year. We print this series to the console.