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Aggregating columns

You need to clean and analyze your stock data to understand high-value inventory patterns. Raw inventory data often includes irrelevant items and needs organization by category. Clean the data by filtering for expensive items (over $5), then calculate accurate totals, and organize by category. This cleaned and summarized view helps identify which departments have the most investment in premium products.

Este exercício faz parte do curso

Cleaning Data in Java

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Instruções do exercício

  • Find expensive items (Unit_Price > $5.00).
  • Calculate the total Stock_Quantity for each category.
  • Group results by Category.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

import static tech.tablesaw.aggregate.AggregateFunctions.sum;

import tech.tablesaw.api.Table;
import tech.tablesaw.selection.Selection;

public class GroceryDataAggregation {
    public static void main(String[] args) {
        Table inventory = Table.read().csv("grocery_inventory.csv");

        Table quantityByCategory = inventory
                // Find expensive items (price > $5.00)
                .where(inventory.doubleColumn("Unit_Price").____(5.0))
                // Calculate total stock for each category
                .____("Stock_Quantity", ____)
                // Group results by product category
                .____("Category");

        System.out.println("Total quantity by category:");
        System.out.println(quantityByCategory.first(5));
    }
}
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