Netflix data set

This coding challenge was one i completed in my spare time 

Overview of the Netflix Dataset Project

The dataset captures a wide range of metadata about movies and TV shows available on Netflix, including title, content type, rating, release year, country of origin, duration, and genre categories. After cleaning and preparing the data in Python, the refined dataset becomes a strong foundation for analysis. It allows you to explore how Netflix’s global catalogue has evolved over time, identify regional content patterns, and understand the platform’s distribution of genres and formats. These insights help reveal broader trends in Netflix’s programming strategy and international reach.

Tools and resources used:

Python (Google Colab)

• Used for full data‑cleaning workflow

• Libraries: pandas, numpy, datetime

• Tasks included:

• Inspecting and understanding the raw dataset

• Removing unnecessary columns

• Handling missing values

• Converting and standardising date fields

• Extracting primary country of origin

• Creating custom age‑group classifications

• Exporting a clean CSV for visualisation

Tableau

• Used to build interactive dashboards

• Visualised:

• Content ratings distribution

• Release‑year trends

• Global title distribution

• Ratings by country

• Genre patterns

• Enabled deeper insight into how Netflix’s catalogue is structured and how it has evolved over time

GitHub

• Stores the full project code, cleaned dataset, and documentation

• Provides version control and a public portfolio record of your workflow

Google Sites

• Hosts the project write‑up and dashboards

• Presents the analysis in a polished, accessible format for viewers

These screenshots are snippets of my completed work on the Netflix Dataset. To see the complete data set, have a look at my github page below:

Github Link: OwenMasterson/Python-Tableau_Netflix