Dive into trends in Netflix movie durations and discover whether movies are getting shorter over the years.
This project is from DataCamp and is part of the Data Scientist with Python career track.
Netflix Movies and TV Shows from Kaggle.
It provides a comprehensive analysis of the Netflix movies dataset. It includes data cleaning, data visualization, and data manipulation. The dataset is from Kaggle, it contains information about movies and TV shows available on Netflix as of 2019. The dataset is available in the repository.
Netflix, originally a DVD rental service, has grown into a global streaming giant with over 200 million subscribers. We aim to explore a fundamental question: Are the average durations of movies on Netflix declining? This analysis investigates the potential decline and its correlation with non-feature film genres.
Here's how we tackle the problem:
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Data Preparation, we start by importing necessary libraries and creating a DataFrame from provided data.
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Visualizing Movie Duration, using Matplotlib and Seaborn, we visualize trends in movie durations from 2011 to 2020, helping you identify any changes.
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Impact of Non-Feature Films, we investigate if non-feature film genres (e.g., documentaries, stand-up) have influenced the decline in movie durations by filtering and visualizing relevant data.
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Genre Distribution, visualize the distribution of movie genres on Netflix.
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Country of Origin, explore the countries producing the most content on Netflix.
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Movie Duration Distribution, investigate the spread of movie durations across the dataset.
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Release Year Trends by Genre, identify trends in genre popularity over time.
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Seasonal Trends in Movie Releases, discover seasonal trends in movie releases.
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Movie Duration by Genre, visualize the distribution of movie durations for different genres.
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Top Directors with the Most Movies, find the directors with the most movies on Netflix.
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Movie Duration Over the Years (Average), calculate and visualize the average movie duration over the years.