This repository includes a project generated during Global AI Hub Python Bootcamp.
In this project, I was asked to analyse a dataset obtained from Kaggle.
https://www.kaggle.com/datasets/luiscorter/netflix-original-films-imdb-scores
Requirements of the project:
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In which language were the long-running films created according to the data set? Make a visualization.
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Find and visualize the IMDB values of the movies shot in the "Documentary" genre between January 2019 and June 2020.
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Which genre has the highest IMDB score among movies shot in English?
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What is the average "runtime" of movies shot in "Hindi"?
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How many categories does the "Genre" Column have and what are these categories? Express it visually.
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Find the 3 most used languages in the movies in the data set.
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What are the top 10 movies with the highest IMDB score?
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What is the correlation between IMDB score and "Runtime"? Examine and visualize.
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What are the top 10 "Genre" with the highest IMDB Score? Visualize it.
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What are the top 10 movies with the highest "Runtime"? Visualize it.
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In which year was the most movies released? Visualize it.
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Which language movies have the lowest average IMBD rating? Visualize it.
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Which year has the greatest total runtime?
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What is the "Genre" in which each language is used the most?
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Is there any outlier data in the data set? Please explain.