Survey Data Analyzer

This project is a Java-based application designed to analyze survey data related to life quality and demographic information. It features a custom hash table implementation to efficiently store and manage survey responses, enabling fast retrieval and comprehensive analysis. The project highlights proficiency in data structures, file I/O, object-oriented programming, and data analysis, making it a strong addition to a professional portfolio.

Table of Contents

• Features
• Technologies Used
• Installation and Setup
• Usage
• Project Structure
• Contributing
• License
• Contact

Features

• Custom Hash Table Implementation:
  • Uses integer keys (response IDs) and Response objects as values.
  • Implements linear probing for collision resolution.
  • Supports dynamic resizing based on a load factor of 0.5.
  • Provides methods for insertion, search, deletion, and printing the table.
• Data Parsing:
  • Reads tab-separated survey data from a file (responses.txt) and populates the hash table.
• Demographic Analysis:
  • Distributions for gender, age group, residence, education level, income source, marital status, and smoking status.
• Life Quality Analysis:
  • Calculates average life quality scores overall and segmented by demographic factors (e.g., gender, age, residence).
  • Analyzes life quality based on mixed conditions (e.g., marital status and residence) and specific survey responses.
• Additional Insights:
  • Identifies the most common treatments, symptoms, and affected life aspects using sorting algorithms.
• Testing:
  • Includes a test suite (Tests.java) to verify the accuracy of analysis methods against expected results.

Technologies Used

• Java: Built with standard Java (JDK 8 or higher), leveraging its object-oriented capabilities and core libraries for file handling and data processing.

Installation and Setup

Follow these steps to set up and run the project locally:

1. Prerequisites:

   • Install Java Development Kit (JDK) 8 or higher on your system.

2. Clone the Repository:

   git clone https://github.com/yourusername/survey-data-analyzer.git

3. Navigate to the Project Directory:

cd survey-data-analyzer

4. Prepare the Survey Data File:

• Place the responses.txt file in the src directory. This file should contain tab-separated survey responses (see ReadFile.java for the expected format).

5. Compile the Java Files:

• Navigate to the src directory (if applicable):

cd src

• Compile all Java files:

javac *.java

6. Run the Application:
   • Execute the Tests class to run the analysis and tests:

   java Tests

Usage

• Input: The program reads survey data from responses.txt in the src directory. Each line represents a response with fields like ID, gender, age, and survey answers (tab-separated).
• Output: Running java Tests executes a suite of tests that invoke analysis methods and print results to the console, comparing them against expected values for validation.
• Customization: Modify Tests.java to explore different analyses or adapt ReadFile.java to handle alternative file formats or paths.

Example Command:

java Tests

This runs the predefined tests, displaying whether each analysis matches the expected output.

Project Structure

• CustomHashTable.java:
  • Implements a hash table with linear probing and dynamic resizing.
  • Supports insertion, search, deletion, and printing of entries.
• ReadFile.java:
  • Reads and parses responses.txt, creating Response objects and inserting them into the hash table.
• Response.java:
  • Encapsulates a single survey response with demographic data and survey answers.
  • Computes a Quality score based on specific survey questions.
• SurveyDataAnalyzer.java:
• Contains methods for demographic and life quality analysis, including distribution counts and averages.
• Identifies common treatments, symptoms, and life aspects using insertion sort.
• TestResponse.java:
  • A simple test class to demonstrate Response object creation and printing.
• Tests.java:
• Main entry point with a test suite to validate analysis methods against expected results.

License

This project is licensed under the MIT License.

Contact

For inquiries or further discussion, reach out to me at akiliu1116@gmail.com