Netflix Dashboard

Netflix Content Exploration Project Overview

In this project, I conducted a comprehensive analysis of Netflix's content library using a dataset spanning from 1925 to 2020, sourced from GitHub. The primary aim was to uncover insights and trends related to genre distribution, ratings, release years, and overall content strategies. The findings offer a deeper understanding of Netflix’s content offerings, user preferences, and growth patterns over time.

1. Data Import and Preparation

Dataset:

The dataset contained detailed information on Netflix’s shows and movies, including:

• Titles: Names of movies and TV shows.
• Genres: Categories such as Drama, Comedy, Thriller, Documentary, etc.
• Release Years: The year each title was added to Netflix.
• Ratings: User ratings, often categorized by TV rating systems (e.g., TV-MA, TV-14, PG).
• Descriptions: Brief summaries or keywords related to the titles.

Data Cleaning:

• Missing Values: Handled any missing or null data through mean imputation for numeric values or deletion of incomplete rows.
• Duplicates: Identified and removed duplicate entries to ensure each title was unique.
• Standardization: Ensured consistent formats for fields such as dates and ratings to facilitate easier analysis.

2. Exploratory Data Analysis (EDA)

Dataset Overview:

The dataset was explored to understand its structure and identify key columns for further analysis:

• Genres: To identify the variety and frequency of genres available.
• Release Year: To analyze trends in Netflix’s content release strategy over the years.
• Ratings: To examine user preferences and the distribution of content ratings across genres.

Basic Visualizations:

• Bar Charts: Displayed the number of titles by genre and by release year. This helped identify dominant genres like Drama and Comedy.
• Pie Charts: Illustrated the proportion of TV Shows vs. Movies, offering insights into Netflix’s content strategy. For instance, the Distribution of Content Types revealed:
  • TV Shows: 32%
  • Movies: 68%
• Histograms: Analyzed the distribution of ratings across the content library, highlighting the spread and concentration of ratings.

3. Visual Dashboard Creation

The project integrated Excel's dashboard capabilities to create an interactive and dynamic exploration environment.

Charts:

• Bar Charts: Compared the number of titles by genre, release year, and other categories.
• Pie Charts: Visualized the proportion of ratings (e.g., number of titles rated TV-MA, TV-14) and content types (TV Shows vs. Movies).
• Line Charts: Analyzed Netflix’s content release trends over time, revealing growth patterns in the number of releases each year.

Interactivity:

• Pivot Tables: Allowed dynamic filtering and drilling down into specific aspects of the data (e.g., viewing top-rated Drama movies or recent TV shows).
• Map Visualization: Helped analyze the geographic distribution of Netflix content across different countries or regions, revealing regional content preferences.

4. Key Insights and Trends

Genre Distribution:

• Top Genres: The Documentary, Stand-Up Comedy, and Drama genres were the most prevalent across Netflix’s library.
  • Documentaries and Stand-Up Comedy have grown significantly over the years, indicating Netflix's push towards original and niche content.

Ratings Analysis:

• Top 3 Ratings:
  • TV-MA: The most common rating, often assigned to adult content (movies and TV shows).
  • TV-14: A significant portion of the content falls under this rating, appealing to a younger audience.
  • TV-PG: Also highly represented, particularly in family-friendly or children’s programming.

Country Insights:

• Top Country: The United States had the highest total of titles, with 2,032 movies and TV shows available on the platform. This reinforces the notion that Netflix's core content base is heavily influenced by the U.S. market.

5. Results and Findings

This Excel-based project provided several key takeaways:

• Content Dominance: Documentaries, Stand-Up Comedy, and Dramas dominate the Netflix library, with these genres frequently appearing in top content lists.
• Ratings Distribution: Netflix features a diverse range of ratings. The most common ratings are TV-MA, TV-14, and TV-PG, indicating a broad appeal across various age groups and audience segments.
• Geographic Distribution: The United States is the top producer of Netflix content, with a total of 2,032 movies and TV shows. This highlights the central role the U.S. plays in Netflix’s content acquisition and production strategy.

6. Conclusion

This analysis of Netflix’s content library, using Excel for data cleaning, exploration, and visualization, revealed several insights into Netflix’s content strategy and user preferences. The interactive dashboard allowed for dynamic and personalized exploration, helping to identify trends in genre popularity, ratings distribution, and geographic content availability.