pandas groupby multicolumns

To group by multiple columns in pandas, you can pass a list of column names to the groupby() method. Here's an example:

import pandas as pd

# create a sample dataframe
data = {'group': ['A', 'A', 'B', 'B', 'B'], 
        'year': [2018, 2018, 2019, 2019, 2020], 
        'value': [10, 15, 20, 25, 30]}
df = pd.DataFrame(data)

# group by 'group' and 'year' columns and calculate the sum of 'value'
grouped = df.groupby(['group', 'year'])['value'].sum()

print(grouped)

Output:

group  year
A      2018    25
B      2019    45
       2020    30
Name: value, dtype: int64

In this example, we grouped the dataframe by the 'group' and 'year' columns and calculated the sum of the 'value' column for each group. The resulting object is a pandas series with a hierarchical index, where the first level corresponds to the 'group' column and the second level corresponds to the 'year' column.