Skip to content

mtahiraslan/Data_Analysis_and_Visualization_Netflix

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 

Repository files navigation

Data Analysis and Visualization on Netflix Dataset

In this project, which was developed using the Netflix-Original-Films-Imdb-Scores data set available on Kaggle, data analyzes and data visualizations were made using Python language on Jupyter Notebook.

Dataset: https://www.kaggle.com/datasets/luiscorter/netflix-original-films-imdb-scores

In the Python bootcamp, basically the answers to the following questions were sought and included in the project.
● In which language were the long-run movies created according to the dataset?
● Find and visualize the IMDB values of movies shot in the 'Documentary' genre between January 2019 and June 2020.
● Which genre has the highest IMDB rating among movies shot in English?
● What is the average 'runtime' of movies shot in 'Hindi'?
● How many categories does the 'Genre' Column have and what are these categories?
● Find the 3 most used languages in the movies in the data set.
● What are the top 10 movies with the highest IMDB rating?
● What is the correlation between IMDB score and 'Runtime'?
● Which are the top 10 'Genre' with the highest IMDB Score?
● What are the top 10 movies with the highest 'Runtime'?
● In which year was the most movies released?
● Which language movies have the lowest average IMBD ratings?
● Which year has the greatest total runtime?
● What is the "Genre" where each language is used the most?
● Is there outlier data in the data set? Please explain.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published