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How to Group Variables in Python to Calculate Count, Average, and Sum

Group Variables in Python

Condition for Grouping Variables in Python to Calculate Count, Average, and Sum

  • Description:
    In Python, grouping variables to calculate counts, averages, or sums can be done using the pandas library.

    Specifically, the groupby() function is used to group data based on certain variables, and then you can perform various aggregation operations like count(), mean(), and sum() on each group.

    Steps: 1. Import Pandas Library
    2. Create a DataFrame
    3. Apply groupby()
    4. Apply Aggregation Functions
Step-by-Step Process
  • Import Pandas Library:
    First, you need to import the pandas library, which provides the groupby() function.
  • Create a DataFrame:
    A DataFrame holds your data, and this is where you can apply the grouping.
  • Apply groupby():
    Use groupby() to group your data based on a specific column or columns.
  • Apply Aggregation Functions:
    After grouping, you can apply aggregation functions such as count(), mean(), sum(), etc., to the groups.
Sample Source Code
  • # Code for Grouping Variables

    import pandas as pd

    data = {
    'Store': ['A', 'B', 'A', 'C', 'B', 'C', 'A'],
    'Sales': [250, 150, 300, 400, 100, 350, 500],
    'Quantity': [3, 2, 4, 5, 2, 3, 6]
    }

    df = pd.DataFrame(data)

    # Group by 'Store' and calculate count, average (mean), and sum for 'Sales' and 'Quantity'
    grouped = df.groupby('Store').agg(
    Sales_Count=('Sales', 'count'),
    Sales_Avg=('Sales', 'mean'),
    Sales_Sum=('Sales', 'sum'),
    Quantity_Sum=('Quantity', 'sum')
    )

    print(grouped)
Screenshots
  • Group Variables in Python

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