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Analyzing missing and unique values

As a grocery inventory analyst, you need to assess data quality in your new inventory tracking system. Before analyzing stock levels and pricing, you need to check for missing data and verify product categorization. Load the inventory data, examine each column for completeness, and analyze category distributions. Some sample data is shown below.

Product_Name Category Date_Received Stock_Quantity Unit_Price
Bell Pepper Fruits & Vegetables 3/1/24 46 4.6
Vegetable Oil Oils & Fats 4/1/24 51 2
Parmesan Cheese Dairy 4/1/24 38 12

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Cet exercice fait partie du cours

Cleaning Data in Java

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Instructions

  • Extract the column from inventory and count missing values in the column.
  • Count the inventory by unique categories.

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

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

        for (String colName : inventory.columnNames()) {
            // Extract the column and count missing values in the column
            int missing = inventory.____(colName).____();
            System.out.println(colName + " missing values: " + missing);
        }

        // Count the inventory by unique categories
        Table catCounts = ____.____("Category");
        System.out.println("\nCategory distribution:");
        System.out.println(catCounts);
    }
}
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