Netflix Movies and TV Shows


This EDA is based on a dataset that contains movies and tv shows available on Netflix. The file has 12 columns and 7787 rows. Some columns, including director, cast, country, date_added, and rating, had null columns and needed to be replaced. Since the columns with null values are either categorical or ordinal, I gave unknown for the director, cast, country; and for the others, I replaced the values with mode, which gave the most common value.Through my exploration, I was able to create visualizations that show the top directors, the amount of tv shows created relative to movies, how much content has been released over time, the countries that release the most content, and the amount of each rating.

Data Visualizations

The first visualization is a bar chart showing the top 5 directors based on the amount of content they have produced.

The pie chart displays the percentage of tv shows produced versus movies. From the graph, it is clear that the majority of Netflix’s content is movies.

The graph shows the amount of new content that Netflix has released over the years. It is clear that the number of movies and tv shows released has drastically increased overtime, reaching a peak around 2018.

This horizontal bar chart is a simplified version of the previous graph. It only displays the amount of new tv shows and movies released within the past 10 years, making it easier to see the exact quantity.

The bar chart shows the top 5 countries that have produced the most content. It is clear that the United States releases the majority of tv shows and movies for Netflix.

The horizontal bar chart displays the amount each rating has been used for Netflix’s content. Based on the graph, it is obvious that TV-14 and TV-MA are the most common ratings.

This side-by-side bar chart also shows the amount of content released throughout the past 10 years; however, it breaks it up between tv shows and movies. Through this visualization, it’s easier to differentiate between the number of movies produced relative to tv shows.



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