Max and Min date in Pandas GroupBy

Max and Min date in Pandas GroupBy

If you have a DataFrame in pandas and you'd like to group by one or more columns and then find the max and min date within each group, you can use the groupby method followed by the agg function.

Let's walk through an example:

Assuming you have a DataFrame df with a date column named 'date' and a categorical column named 'category', you can get the max and min dates for each category as follows:

import pandas as pd # Sample DataFrame data = { 'category': ['A', 'B', 'A', 'A', 'B', 'B'], 'date': ['2021-01-01', '2021-01-02', '2021-01-05', '2021-01-03', '2021-01-06', '2021-01-04'] } df = pd.DataFrame(data) # Convert the 'date' column to datetime format df['date'] = pd.to_datetime(df['date']) # Group by 'category' and aggregate max and min dates result = df.groupby('category')['date'].agg(['max', 'min']) print(result)

Output:

 max min category A 2021-01-05 2021-01-01 B 2021-01-06 2021-01-02

In the above example, the groupby method groups the DataFrame by the 'category' column, and the agg function calculates the max and min dates for each group.

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