Data Analysis Examining trends in the carpooling industry

Posted on Jan 11, 2019

Project GitHub | LinkedIn:   Niki   Moritz   Hao-Wei   Matthew   Oren

The skills we demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

Background

As part of my web-scraping project at the NYC Data Science Academy, I have decided to examine the Carpooling industry, an industry which is transforming the transportation sector. I am particularly interested in some of the factors that determine the pricing of a carpooling ride. I have proceeded with web-scraping BlaBla Car, one of the leaders in the european carpooling industry. BlaBla Car's philosophy is that carpooling with strangers breaks the ice and creates new friendships- which explains the name BlaBla.

Screenshot 2019-01-11 16.18.46.png

Web-Scraping

I used selenium to extract information for rides based in Paris  with destinations that include over 10 french and european cities. Information scraped includes ride price,driver picture , gender of driver, vehicle type and ID verification.

Screenshot 2019-01-11 16.27.00.png

Link to the python code: https://github.com/karimhzaatary/Blabla_car

 

About Author

karim El Zaatari

Data Scientist and mechanical engineering graduate with a demonstrated record of leadership & problem solving. My data science projects span over various topics including air pollution, carpooling,house pricing and machine learning in horse racing.
View all posts by karim El Zaatari >

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