YouTube Global Statistics Analytics

A Data Visualization project through an interactive web application, analyzing global YouTube trends by dynamic data filtering and interactive insights.

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Source Code available in the repository
Github handle: swetapati22
Project: YouTube Global Statistics Analytics
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Source Code: Click here
Deployed App: Click here
Demo Video: Watch Demo
Dataset Link: View Dataset

Overview

A Data Visualization, interactive web application project using Plotly, Preswald, Python, and Pandas to analyze global YouTube trends across categories, creators, and countries. Enabling dynamic exploration through interactive insights using Global YouTube Statistics 2023 dataset.

The application features six interactive visualizations and a dynamic slider filter to enhance interactivity.

Tech Stack

  • Preswald – For interactive UI & visualization.
  • Pandas – Data manipulation & filtering.
  • Plotly – Graphical visualizations (bar charts, line graphs, maps, heatmaps).
  • Python – Backend scripting.
  • Git & GitHub – Version control & collaboration.

Dataset Details

  • Dataset: Global YouTube Statistics 2023:
  • Dataset Source: Kaggle

Global Filter - Slider for Views Threshold

Before visualizing data, the app includes a slider filter that allows users to set a minimum threshold for video views.
This ensures dynamic exploration based on user preferences.

views_threshold = slider("Minimum Views (Converted to Billion)", min_val=0, max_val=max_views, default=0.5)

Once a threshold is selected, the six different visualizations are displayed.

Visualizations

1. Views by Category (Bar Chart)

Graph Type: 📊 Bar Chart (Categorical Comparison)

  • Displays total YouTube video views for different content categories.
  • Users can identify top-performing categories.

Analytical Insights:

  • Most popular category: Music, accumulating 2928.88 billion views, highlighting its massive audience engagement.
  • Least popular categories: Travel & Events, Movies, Nonprofits & Activism – indicating niche audiences with smaller but dedicated followings.

2. Top YouTubers by Views (Bar Chart)

Graph Type: 📊 Bar Chart (Ranked List)

  • Highlights top YouTubers based on total video views.

Analytical Insights:

  • Most-watched YouTuber: T-Series, amassing 228.00 billion views, demonstrating a strong and consistent audience reach.
  • The distribution of views indicates category dominance, where Entertainment, Music, and Gaming outperform niche educational or specialized content.

3. YouTube Views by Country (Choropleth Map)

Graph Type: 🌍 Choropleth Map (Geographical Data Representation)

  • Displays YouTube viewership per country.

Analytical Insights:

  • Country with highest YouTube engagement: United States, leading with 3557.44 billion views, showcasing its massive audience and content consumption.
  • Lowest engagement regions: Peru, Finland, Andorra – potentially due to smaller population sizes, lower internet penetration, or niche content interests.

Graph Type: 🔥 Heatmap (Regional Comparison)

  • Illustrates how YouTube content categories perform across different countries.

Analytical Insights:

  • United States has the highest YouTube views globally with 3557.44 billion views, with Music as the most-watched category, accumulating 1012.12 billion views.
  • Least-watched categories globally: Travel & Events, Movies, Nonprofits & Activism – suggesting these categories cater to niche audiences rather than mass engagement.

Graph Type: 📈 Line Chart (Time Series Analysis)

  • Tracks YouTube creators trending in the last 30 days.

Analytical Insights:

  • Most trending YouTuber: ıııııııı KIMPRO, accumulating 3.4 billion views in the past 30 days.
  • Largest drop in engagement: ArianaGrandeVevo, indicating a potential decline in engagement or reduced content uploads.

6. Subscribers vs Uploads Growth (Multi-Line Chart)

Graph Type: 📈 Multi-Line Chart (Trend Comparison)

  • Analyzes the relationship between content uploads & subscriber growth.

Analytical Insights:

  • Category with highest subscriber growth: Film & Animation, reaching 86.90 million subscribers, demonstrating strong audience engagement.
  • Category with lowest subscriber growth: Travel & Events, with only 12.50 million subscribers, suggesting that more uploads do not necessarily translate to higher subscriber gain.
  • Not all categories grow equally – quality content matters more than quantity in some cases.

How to Run the Project

1. Install Preswald

pip install preswald

2. Initialize Project

preswald init my_example_project
cd my_example_project

3. Download Dataset

Place the dataset in the data/ folder inside the project.

4. Run Locally

preswald run

5. Deploy to Structured Cloud

preswald deploy --target structured --github <your-github-username> --api-key <structured-api-key> hello.py

Replace <your-github-username> and <structured-api-key> with your credentials.

Major Takeaways:

  • YouTube trends vary significantly by category, creator, and region.
  • Trending creators fluctuate frequently, requiring continuous audience engagement.

  • Content quality > Upload quantity for some categories.

    This interactive dashboard provides valuable insights for content creators, analysts, and marketers to understand global YouTube trends dynamically.