How to Use the Pandas DataFrame Groupby Method

To use the Pandas DataFrame groupby method, you can call the groupby() method on a DataFrame and specify the column or columns that you want to group by. Here’s an example:

import pandas as pd

# Create a dataframe
df = pd.DataFrame({
    'fruit': ['apple', 'banana', 'orange', 'apple', 'banana', 'orange'],
    'quantity': [2, 3, 1, 4, 5, 2]
})

# Group the dataframe by the 'fruit' column
grouped = df.groupby('fruit')

# Compute the sum of each fruit's quantity
summed = grouped['quantity'].sum()

# Print the result
print(summed)

In this example, we create a DataFrame with two columns: fruit and quantity. We then use the groupby() method to group the DataFrame by the fruit column. This creates a groupby object that we can use to compute various aggregates.

In this case, we want to compute the sum of each fruit’s quantity. To do this, we select the quantity column from the groupby object and call the sum() method. This computes the sum of each group’s values and returns a new DataFrame.

Finally, we print the result, which is a DataFrame with the sum of each fruit’s quantity.