# Using Effcient Sorting Algorithms in Java to Arrange Tax Data

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In this Guided Project, you will:

Learn how to analyze a sorting algorithm and choose the best one for the situation

Discover how to implement industry standard algorithms that depend on fundamentals of Java

2 hours
Intermediate
Split-screen video
English
Desktop only

By the end of this project, you will learn how to create an application that sorts Missouri Tax Data into ascending order using a variety of critical sorting algorithms. We will learn how to process a real life data set, and see the difference between various sorting algorithms in memory and time usage. In addition, we will learn how to analyze a sorting algorithm and how to design a readable implementation. Finally, we will cover what circumstance are ideal for each type of sorting algorithm. After completing this project, students will be able to move to more advanced algorithms and data structures. Sorting algorithms are essential to the creation of powerful and efficient programs, for almost any circumstance when we need to arrange the data for our user in a certain order. Doing this can make it significantly faster for a human, or even computer, to parse and understand this data to make business decisions. We will explore how each of these sorting methods are different and how to implement them. We will also briefly cover how to access these methods using built-in Java functions. In this course we will cover bubble sort, insertion sort, merge sort, selection sort, and quicksort. These five sorting techniques span a variety of efficiencies and use cases in real life. They also all are easy to implement with knowledge of arrays, recursion, and loops in Java.

### Skills you will develop

Mathematical OptimizationAlgorithm DesignJavaComputer ProgrammingSorting

## Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

1. Learners will be introduced to the overall structure of the program and understand how we will be importing the data set.

2. Students will learn how to find and interpret the Big-Oh complexity of an algorithm

3. Students will discover situations where bubble sort is ideal, and learn how to implement bubble sort in Java with the dataset.

4. Students will discover situations where insertion sort is ideal, and learn how to implement insertion sort in Java with the dataset.

5. Students will discover situations where selection sort is ideal, and learn how to implement selection sort in Java with the dataset.

6. Students will discover situations where mergesort is ideal, and learn how to implement mergesort in Java with the dataset.

7. Students will discover situations where quicksort is ideal, and learn how to implement quicksort in Java with the dataset.

## How Guided Projects work

In a split-screen video, your instructor guides you step-by-step

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