Data Science Project from Scratch - Part 2 (Data Collection)
This is part two of the new Data Science Project from Scratch Series. In this video I go through how to setup a github repo and collect data for your own data science project.
github repo for this project: https://github.com/PlayingNumbers/ds_...
How to set up data science environment: • How to Set Up Your Data Science Environmen...
Chrome Driver Link: https://chromedriver.chromium.org/
Data collection can be a tedious and frustrating process, but you don't necessarily have to start from scratch. You should search github to see if someone has already built a web scraper for the website you are looking at. You should also check to see if the website has an open API.
For this project, I found someone who had written a glassdoor web scraper and I was able to version it for our purposes. The code and the article that I used are linked here:
Code: https://github.com/arapfaik/scraping-...
Article: https://towardsdatascience.com/seleni...
This web scraper was written in python with the selinium package.
This is an iterative process, so in this video you will see how I go about debugging my code and making it work.
Stay tuned for part 3 where I go through and clean up the data that we collected to make it usable for our EDA and model building.
After we scrape the data, I save the code to github.
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