This project involves a comprehensive analysis of Netflix's movies and TV shows data using SQL. The goal is to extract valuable insights and answer various business questions based on the dataset. The following README provides a detailed account of the project's objectives, business problems, solutions, findings, and conclusions.
- Analyze the distribution of content types (movies vs TV shows).
- Identify the most common ratings for movies and TV shows.
- List and analyze content based on release years, countries, and durations.
- Explore and categorize content based on specific criteria and keywords.
The data for this project is sourced from the Kaggle dataset:
- Dataset Link: Movies Dataset
DROP TABLE IF EXISTS netflix;
CREATE TABLE netflix
(
show_id VARCHAR(5),
type VARCHAR(10),
title VARCHAR(250),
director VARCHAR(550),
casts VARCHAR(1050),
country VARCHAR(550),
date_added VARCHAR(55),
release_year INT,
rating VARCHAR(15),
duration VARCHAR(15),
listed_in VARCHAR(250),
description VARCHAR(550)
);
SELECT
type,
COUNT(*)
FROM netflix
GROUP BY 1;
Objective: Determine the distribution of content types on Netflix.
WITH RatingCounts AS (
SELECT
type,
rating,
COUNT(*) AS rating_count
FROM netflix
GROUP BY type, rating
),
RankedRatings AS (
SELECT
type,
rating,
rating_count,
RANK() OVER (PARTITION BY type ORDER BY rating_count DESC) AS rank
FROM RatingCounts
)
SELECT
type,
rating AS most_frequent_rating
FROM RankedRatings
WHERE rank = 1;
Objective: Identify the most frequently occurring rating for each type of content.
SELECT *
FROM netflix
WHERE release_year = 2020;
Objective: Retrieve all movies released in a specific year.
SELECT *
FROM
(
SELECT
UNNEST(STRING_TO_ARRAY(country, ',')) AS country,
COUNT(*) AS total_content
FROM netflix
GROUP BY 1
) AS t1
WHERE country IS NOT NULL
ORDER BY total_content DESC
LIMIT 5;
Objective: Identify the top 5 countries with the highest number of content items.
SELECT
*
FROM netflix
WHERE type = 'Movie'
ORDER BY SPLIT_PART(duration, ' ', 1)::INT DESC;
Objective: Find the movie with the longest duration.
SELECT *
FROM netflix
WHERE TO_DATE(date_added, 'Month DD, YYYY') >= CURRENT_DATE - INTERVAL '5 years';
Objective: Retrieve content added to Netflix in the last 5 years.
SELECT *
FROM (
SELECT
*,
UNNEST(STRING_TO_ARRAY(director, ',')) AS director_name
FROM netflix
) AS t
WHERE director_name = 'Rajiv Chilaka';
Objective: List all content directed by 'Rajiv Chilaka'.
SELECT *
FROM netflix
WHERE type = 'TV Show'
AND SPLIT_PART(duration, ' ', 1)::INT > 5;
Objective: Identify TV shows with more than 5 seasons.
SELECT
UNNEST(STRING_TO_ARRAY(listed_in, ',')) AS genre,
COUNT(*) AS total_content
FROM netflix
GROUP BY 1;
Objective: Count the number of content items in each genre.
return top 5 year with highest avg content release!
SELECT
country,
release_year,
COUNT(show_id) AS total_release,
ROUND(
COUNT(show_id)::numeric /
(SELECT COUNT(show_id) FROM netflix WHERE country = 'India')::numeric * 100, 2
) AS avg_release
FROM netflix
WHERE country = 'India'
GROUP BY country, release_year
ORDER BY avg_release DESC
LIMIT 5;
Objective: Calculate and rank years by the average number of content releases by India.
SELECT *
FROM netflix
WHERE listed_in LIKE '%Documentaries';
Objective: Retrieve all movies classified as documentaries.
SELECT *
FROM netflix
WHERE director IS NULL;
Objective: List content that does not have a director.
SELECT *
FROM netflix
WHERE casts LIKE '%Salman Khan%'
AND release_year > EXTRACT(YEAR FROM CURRENT_DATE) - 10;
Objective: Count the number of movies featuring 'Salman Khan' in the last 10 years.
SELECT
UNNEST(STRING_TO_ARRAY(casts, ',')) AS actor,
COUNT(*)
FROM netflix
WHERE country = 'India'
GROUP BY actor
ORDER BY COUNT(*) DESC
LIMIT 10;
Objective: Identify the top 10 actors with the most appearances in Indian-produced movies.
SELECT
category,
COUNT(*) AS content_count
FROM (
SELECT
CASE
WHEN description ILIKE '%kill%' OR description ILIKE '%violence%' THEN 'Bad'
ELSE 'Good'
END AS category
FROM netflix
) AS categorized_content
GROUP BY category;
Objective: Categorize content as 'Bad' if it contains 'kill' or 'violence' and 'Good' otherwise. Count the number of items in each category.
- Content Distribution: The dataset contains a diverse range of movies and TV shows with varying ratings and genres.
- Common Ratings: Insights into the most common ratings provide an understanding of the content's target audience.
- Geographical Insights: The top countries and the average content releases by India highlight regional content distribution.
- Content Categorization: Categorizing content based on specific keywords helps in understanding the nature of content available on Netflix.
This analysis provides a comprehensive view of Netflix's content and can help inform content strategy and decision-making.