This project analyzes Netflix's content release strategy to understand how the platform schedules and releases its shows and movies. By examining patterns in release dates, genres, and viewer engagement, this analysis provides insights into Netflix's approach to maximizing viewership and retaining subscribers.
- Identify trends in Netflix's content release schedule.
- Analyze the relationship between release dates and viewer engagement.
- Explore how different genres are prioritized in the release strategy.
- Provide recommendations for optimizing content release schedules.
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Data Collection:
- Gathered data on Netflix releases, including titles, genres, release dates, and viewer ratings.
- Used publicly available datasets and web scraping techniques to collect relevant information.
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Data Cleaning:
- Handled missing values, duplicates, and inconsistencies in the dataset.
- Standardized date formats and categorized genres for analysis.
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Data Analysis:
- Performed exploratory data analysis (EDA) to identify trends and patterns.
- Used visualizations to analyze the distribution of releases over time and across genres.
- Investigated the correlation between release dates and viewer engagement metrics.
- Python: For data cleaning, analysis, and visualization.
- Pandas: For data manipulation and analysis.
- Matplotlib/Seaborn: For creating visualizations.
- Jupyter Notebook: For interactive coding and documentation.
- Web Scraping: For collecting data from online sources.