Congratulations!

1. Congratulations!

Congratulations! You've made it to the end of this course.

2. Chapter 1 summary

In Chapter 1, you learned how to work with Java's built-in I/O classes like File, Path, and Files. We explored streams, and we introduced Tablesaw. You also performed basic table operations in Tablesaw.

3. Chapter 2 summary

Chapter 2 focused on Tablesaw mastery. You learned CSV processing, data structures, and powerful filtering with methods like where() and select(). Advanced techniques included computed columns and conditional transformations.

4. Chapter 3 summary

Our final chapter covered advanced processing. You learned transformation patterns with .map() and .forEach(), mastered JSON handling from basics to complex nested structures, and developed custom parsing solutions for unique scenarios.

5. Summary

This diagram shows the complete data processing workflow we've covered in the course. Raw data from CSV and JSON files flows through ingestion, validation, and transformation stages into the Tablesaw Processing Engine. The engine then powers various operations - filtering, aggregation, parsing, and column operations, which feed into analytics and reports. This pipeline demonstrates how to handle complex, multi-format data efficiently in real-world applications.

6. Further learning

This has only scratched the surface of what is possible with both Tablesaw and Java. DataCamp has a number of other courses available for Java, some of which will build on the knowledge from this course! The best way to improve is to practice, so keep practicing your skills with personal projects, and you will find that your skills continue to improve.

7. Thank you!

Thank you for taking this course, and congratulations on completing it!

Create Your Free Account

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.

This exercise is part of the course

Importing Data in Java

IntermediateSkill Level

5.0+

Start Course for Free

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 Exercise 7: Table filtering Exercise 8: Table queries Exercise 9: Data manipulation and analysis Exercise 10: Initial data exploration Exercise 11: Department analysis Exercise 12: Advanced Data Manipulation Techniques Exercise 13: Data cleaning and enhancement Exercise 14: Advanced filtering and analysis

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.

Exercise 1: Data Transformation Patterns Exercise 2: Employee salary analysis Exercise 3: Total compensation calculator Exercise 4: Department summary statistics Exercise 5: JSON Data Basics with Tablesaw Exercise 6: Loading JSON files Exercise 7: JSON data analysis Exercise 8: JSON validation Exercise 9: Complex JSON Processing Exercise 10: Importing nested data Exercise 11: Merging nested data Exercise 12: Handling missing JSON values Exercise 13: Congratulations!

Current Exercise