Valentius Kryptix

Introduction

In this project, I explored the Netflix Titles dataset to understand what type of content dominates the platform. As a Data Science Intern at Valentius Kryptix, my goal was to convert raw data into meaningful visuals.

The dataset contains over 8000+ titles with details like Type, Director, Cast, Country, Release Year and Rating.

Tools Used

• Python (Pandas, Matplotlib, Seaborn)
• Power BI for Interactive Dashboard
• Dataset: Netflix Movies and TV Shows from Kaggle

Key Visualizations & Insights

1. Movies vs TV Shows

I analyzed the distribution of content types.
Insight: Netflix has almost 70% Movies and 30% TV Shows. This shows Netflix focuses more on movie content. USA is the biggest contributor.

2. Top 10 Countries Producing Content

Using a bar chart analysis, I found which countries produce most content.
Insight: USA is the top content producer with 2800+ titles, followed by India with 900+ titles and UK with 600+ titles. India being in Top 3 is a proud moment!

3. Content Added Over the Years

I plotted content added each year from 2015 to 2021.
Insight: Content addition peaked in 2019-2020 with around 1900 titles each year. After that, growth became stable, showing Netflix’s content strategy matured.

4. My Power BI Dashboard

Finally, I built an interactive Power BI dashboard with filters for Type, Rating and Country. It helps anyone explore Netflix data easily with slicers and dynamic charts.

Conclusion

This visualization task helped me understand the power of storytelling with data. We can see clear trends – like US dominance, movie-heavy library, and the rise of Indian content on Netflix.

This was a great learning experience as part of my internship at Valentius Kryptix.

Author: Sadhana Mang, Data Science Intern, Pune