Netflix Content Strategy Analysis Project Project Overview This project analyzes Netflix's content strategy by exploring the dataset of Netflix releases in 2023. The objective is to derive meaningful insights, identify trends, and evaluate how different factors (e.g., content type, language, release date) impact viewership. The project also includes an exploration of seasonality, day-of-week trends, and potential correlations with holidays.
Dataset File Name: netflix_content_2023.csv Description: Contains information about Netflix's 2023 content releases, including: Title Content Type (e.g., Movie, TV Show) Language Indicator Release Date Hours Viewed (in billions)
Project Goals Analyze viewership patterns: Compare Movies and TV Shows. Examine trends based on language, release month, and seasons. Identify top-performing content: Find titles with the highest viewership. Understand temporal trends: Analyze release patterns by month and weekday. Explore viewership impact near significant holidays. Build insights for future strategies: Suggest optimal release times and focus areas based on data.
Pipeline Workflow
- Data Preprocessing Convert Hours Viewed into numerical format. Parse Release Date and extract: Release Month Release Day Release Season (Winter, Spring, Summer, Fall) Map content releases near significant holidays.
- Data Analysis and Visualization Content Trends: Analyze total viewership hours for Movies vs. TV Shows. Language-based Viewership: Identify the most popular languages. Seasonality: Visualize viewership across months and seasons. Day-of-Week Patterns: Evaluate the impact of weekday releases on viewership. Holiday Impact: Highlight content released near significant holidays and their viewership.
- Outputs Top-Performing Content: A table showing the top 5 titles based on viewership. Visualizations: Bar plots, line graphs, and dual-axis plots for trends and comparisons. Summary Insights: Recommendations for optimal release strategies.
Project Files File/Folder Description netflix_content_2023.csv Dataset of Netflix's 2023 releases. netflix_analysis.py Python script containing all code. README.md Documentation for the project (this file). outputs/ Folder containing generated visualizations.
Dependencies Python 3.7+ Libraries: pandas numpy matplotlib seaborn calendar datetime Install the required packages using:
View generated visualizations and insights in the outputs/ folder.
Key Visualizations Total Viewership by Content Type: Highlights which type (Movies or TV Shows) generates more hours viewed. Viewership by Language: Shows the most popular languages for Netflix releases. Monthly Viewership Trends: Line chart for trends across months. Seasonal Viewership: Bar plot of total hours viewed by season. Content Released vs. Viewership by Month: Dual-axis chart for release volume and viewership trends. Future Enhancements Automate data updates and integrate with Netflix’s live API (if available). Implement machine learning models to predict the viewership of future content. Develop a dashboard for interactive data exploration.