Working with column types

You're building a product catalog for a tech training startup. Before creating courses, you need to analyze the product pricing-understanding the price range helps determine which products to prioritize. Working with typed columns like DoubleColumn gives you access to statistical methods that generic columns don't provide.

The Table and DoubleColumn classes have been imported for you.

This exercise is part of the course

Importing Data in Java

Exercise instructions

Read "products.csv" into the products table.
Access the "Price" column and store it in prices.
Print the mean price.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

public class ProductCatalog {
    public static void main(String[] args) {
    	try {
          // Load products.csv into the products table
          Table products = Table.____().csv("____");

		  // Access the Price column and store it in prices
          DoubleColumn ____ = products.doubleColumn("____");
          
          // Print the mean price
          System.out.println("Price Stats - Min: $" + prices.min() +
                  ", Max: $" + prices.max() +
                  ", Mean: $" + prices.____());

          System.out.println(products.first(5));
        } catch (Exception e) {
            System.err.println("Error reading CSV files: " + e.getMessage());
        }
    }
}

Edit and Run Code

This exercise is part of the course

Importing Data in Java

IntermediateSkill Level

4.9+

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Kickstart your journey into data handling with Java! In this first chapter, you'll learn how to read, validate, and manage data using Java I/O Streams and then dive into the powerful Tablesaw library to easily create, explore, and manipulate data tables, the perfect foundation for modern data analysis in Java.

Exercise 1: Understanding Data Import Fundamentals Exercise 2: Creating basic file readers Exercise 3: Implementing data validation Exercise 4: Java I/O Streams overview Exercise 5: Reading files with BufferedReader Exercise 6: Writing files with BufferedWriter Exercise 7: Stream chaining Exercise 8: Introduction to Tablesaw Exercise 9: Creating a table Exercise 10: Exploring table metadata Exercise 11: Modifying table structure

In this second chapter, we will move on to covering CSV processing in Tablesaw. Initially, you will learn to read and write CSV files with varying formats, and then we move on to modifying tables, adding and removing columns, filtering tables and manipulating the data within tables for data cleaning and processing.

Exercise 1: CSV processing with Tablesaw Exercise 2: Reading CSV files Exercise 3: Handling CSV parsing options Exercise 4: Writing formatted CSV files Exercise 5: Data structures in Tablesaw Exercise 6: Working with column types

Current Exercise

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Complete your Java data journey by mastering transformation patterns that allow you to modify columns, process rows, and summarize datasets into meaningful insights. You’ll also work with JSON data, from simple files to complex, nested structures - preparing you to handle modern APIs and configuration files.

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