iswojciechowska / ih_final_bootcamp_project

FINAL PROJECT FOR IRONHACK

Project Overview

This repository presents my final project for IronHack, focusing on a comprehensive analysis of YouTube trends in Germany. Divided into two parts, the project provides insights into viewer behavior, sentiment in comments, and includes a predictive model for video views.

Part 1: YouTube German Trends Analysis

Explore YouTube trends in Germany, unraveling key aspects such as video popularity, viewer engagement, and sentiment analysis. The analysis aims to uncover patterns and trends within the dynamics of YouTube content in the German market.

Project Highlights

• Notebooks:

  • Part_1/YouTube_German_Trends_Analysis.ipynb: In-depth analysis of YouTube trends.
  • Part_1/YouTube_Analysis_Tool.ipynb: Python script for efficient YouTube video analysis.

• Datasets:

  • Part_1/DE_category_id.json: File containing category names.
  • `Part_1/link to dataset in Notebook.

• Presentation:

  • Part_1/presentation.pdf: Presentation Slides - Summarized insights and key findings.

Part 2:

Includes analysis of 20 biggest news publishers on Youtube - mainly in SQL.

Additional Analysis and Visualizations

Visualizations on Tableau for additional insights. Link to Tableau Visualizations

Why Analyze YouTube Trends?

Analyzing YouTube trends can provide valuable insights for various purposes:

• Business Strategy: Understanding what content resonates with the audience can inform marketing and content strategies.

• Cultural Insights: Examining trends sheds light on cultural preferences, providing a snapshot of societal interests.

• Predictive Modeling: Building models to predict video views can offer a glimpse into future trends and audience engagement.

How to Use

1. Clone the repository.
2. Navigate to the respective part's folder (Part_1 or Part_2).
3. Follow the instructions in each part for specific details on running the code and analysis.