This project is an exploratory data analysis of the Netflix Movies and TV Shows dataset. The goal of the project is to uncover patterns and trends in the data, and to draw insights from the analysis. The dataset contains information about various movies and TV shows available on Netflix, including their titles, genres, release years, and more.
- pandas
- numpy
- matplotlib
- seaborn
You can download the dataset here: https://www.kaggle.com/datasets/shivamb/netflix-shows
In this phase, the data is cleaned and preprocessed to remove any missing or invalid values. This involves:
- Removing duplicates
- Handling missing values
- Standardizing the data types
- Removing unwanted columns
- Renaming columns
In this phase, the cleaned data is analyzed to gain insights in the Netflix Platform. This involves:
- Which type of content is released.
- Which country is producing more netflix content
- Which directors have directed more netflix content
- On which genre are more movies/tv shows listed
- On each year how many movies/tv shows is produced
- Ratings of the movies/tv shows
With description given of the movies/tv-show Sentimental Analysis can be done and can suggest and categorize the movies/tv-shows.