jpujolf95/video_game_project

Video_Game

Video_Game_Project

Video_Game

Game Rating Analysis Project

Table of Contents

1. Introduction
2. Project Overview
3. Data Collection
4. Data Preprocessing
5. Exploratory Data Analysis
6. Modeling
7. Usage

1. Introduction

This project aims to analyze how different categories, tags and gaming magazine reviews influence the rating scores of games given by users. By exploring and modeling this data, we hope to gain valuable insights into what factors contribute to higher or lower user ratings for video games.

2. Project Overview

In this project, we will follow these main steps:

1. Data Collection: Obtain video game data from various sources including publisher, year of release, user ratings, game categories, and tags.

2. Data Preprocessing: Clean and prepare the data for analysis.

3. Exploratory Data Analysis (EDA): Explore the data to understand the distribution of ratings across different categories and tags.

4. Modeling: Build a predictive model.

5. Evaluation: Evaluate the model's performance and interpret the results to draw meaningful conclusions.

3. Data Collection

The data for this project has been collected from publicly available datasets from Kaggle. We will focus on obtaining information about game ratings, categories, and user-assigned tags.

4. Data Preprocessing

Before conducting any analysis, I have preprocessed the data to ensure its quality and reliability. This step will involve handling missing values, removing duplicates, and dropping any columns that are deemed irrelevant for the analysis.

5. Exploratory Data Analysis (EDA)

In the EDA phase, we will visualize and analyze the data to identify patterns and trends in game ratings.

6. Modeling

To predict the user rating of games we will build a suitable machine learning model taking into consideration publishers, categories, tags on game ratings.

7. Usage

To use or reproduce this project:

1. Clone the repository to your local machine.
2. Ensure you have the required dependencies and libraries installed (details in requirements.txt).
3. Run the data collection and preprocessing scripts.
4. Execute the Jupyter notebooks for EDA and modeling.
5. Explore the results and conclusions obtained from the analysis.

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Thank you for your interest in the Game Rating Analysis project. If you have any questions or suggestions, please don't hesitate to reach out to me. Happy gaming!