This repository created for the Global AI Hub Python Bootcamp projects

• Project 1 contains a imaginary math class takes students name,surname,id,point as an input and after that put the points in a logic and calculate the student pass or failed and store all the data in a dict after that, transforms that dict to a dataframe and excell file.
• Project 2 contains a kaggle netflix dataset and some operations on that dataset operations are

  • Based on the dataset which languages are used for the long movies, visualize.

  • Find and visualize the IMDB values of the 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 those categories? Express it visually.

  • Find the 3 most used languages in the movies in the data set.

  • Top 10 movies with the highest IMDB rating?

  • What is the correlation between IMDB score and 'Runtime'? Examine and visualize.

  • Which are the top 10 'Genre' with the highest IMDB Score? Visualize it.

  • What are the top 10 movies with the highest 'runtime'? Visualize it.

  • In which year was the most movies released? Visualize it.

  • Which language movies have the lowest average IMBD ratings? Visualize it.

  • Which year has the greatest total runtime?

  • What is the "Genre" where each language is used the most?

  • Is there any outlier data in the data set? Please explain.

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