Swappa Scraper (After-market Price Tracker for smartphones)

A python program to fetch subscriptions from mail, pull the swappa listings (new and old), scrape them and do perform exploratory data analysis.

What it helps with?

The after-market data can be used to understand the selling distribution and market trends before making a purchase

Tools & Libraries Used

1. Python GMAIL API - To read mails from GMAIL and fetch the listings for swappa
2. Scrapy - To scrape data from swappa
3. Tableau - To draw the visualization/EDA
4. Google Viz - To draw visualization for the web (WIP)

End Result

Data Info - 3000 listings (records)

Which phone sells the most? (With median price sold in comparison to the prices not sold)

iPhone 8 has 319 listings out of 3000 total. (Roughly 10% of total phones)

---

Selling distribution of iPhone X (Sold vs Unsold)

For iPhone X, 400-470 price bin contains most of the phone which are listed as well as sold. One can see that prices above $570 are not being sold.

---

Where are most sellers from?

New Jersey and Texas has the most sellers

Code

In folder v1, run the scripts in below order

1. mail.py (Uses GMAIL API). If you have data skip this file
2. s1.py (You need to have scrapy for this)
3. merge.py