Description : We scrap the data from the wellknow website IMDB, whish is the bigest movie database from our banchmark. From IMDB we get : 21 attributes compose by :
names
years
imdb_ratings
metascores
votes
categories
mv_pages
genre1
genre2
genre3
stars1
stars2
stars3
rank
nb_oscar
win
nom
runtime
budget
gross
After cleaning those data and place them in a pandas dataframe. We also decided to add one other features, the director from "Themoviedb" API which is kind of conected to IMDB (same movie id). To finish we analyse the entire data by using machine learning in order to find correlation betweenn attributes. The 2 different machine learning algothme that we use are, Linear Regression and Decision Tree Regressor from SKlearn.
- Alexadre Bensimon
- Jules Enguehard
- Victor Henrio
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
You need to clone the entire project on your device by doing this command :
* git clone https://github.com/Alex-bensimon/Projet_DataScienceTools.git
And then execute the main file by execute this command :
* main()
A menu should appear on your consol. You can now follow the instructions to discover all the functionalities implemented.
You need to insatll Python version 2 at least to run beautifulsoup4
We use all those library :
- BeautifulSoup
- Urllib
- Pandas
- Numpy
- Matplotlib.pyplot
- seaborn
- time
- warning
- requests
- sklearn
A step by step series of examples that tell you how to get a development env running
Say what the step will be
Give the example
And repeat
until finished
End with an example of getting some data out of the system or using it for a little demo
Explain how to run the automated tests for this system
Explain what these tests test and why
Give an example
Explain what these tests test and why
Give an example
Python 3.7.6
This project is licensed under the MIT License
- We thank Remi Ferreira for his high quality courses and his impressive green background. We also thank him for sharing his knowledge and his passion with us.