This project is to exercise some skills in web scrapping using python.
The Coffee&Cookies Books Club is a startup in the UK that wants to build a subscription-based book club for lovers of coffee and books.
Coffee&Cookies picks only hard-to-find and greatly-rated books. The company packs them with a unique reading guide and a wellness set including exotic varieties of coffee and specialty candies.
Their market research showed that the customers keeps their subscription for longer when they receive a mix of casual and business books, from the following categories:
- Classics
- Science Fiction
- Humor
- Business
Coffee&Cookies needs to decide what books to deliver next to their subscribers, and required me search for a dataset including the following info:
- Book name
- Price in GBP
- Customer Rating
- Stock availability
The customer asked for the raw information as it will be used later for further analysis.
- *.csv file with the information
A table will be created containing the following information:
| Columns | Description |
|---|---|
| scrap_date | the date the scrapping was held |
| book_title | the title of the book |
| book_category | the book's category page |
| book_upc | a unique universal identifier for each title |
| book_price | price excl. tax |
| book_stars | rating from 1 to 5 |
| book_in_stock | is it available? |
| nr_available | how many books are in stock |
Tools used:
- Jupyter Notebook
- Python 3.9
- BeautifulSoup4
- Pandas
- Requests
STEP 01: use a browser to understand the tags structure for the website, and find where the data we need is embedded within the code.
STEP 02: scrap the catalogue pages to get a dataset of titles available (urls) with their respective categories.
STEP 03: use the list of urls created in step 02 to access the books pages to scrap for the remaining information needed.
STEP 04: join create a table with the scrapped data.
STEP 05: transform and clean the data, and export it to *.csv and deliver it to Coffee&Cookies.
I will use https://books.toscrape.com as a source for the data. It is a website made for scrapping and can be used free of charge.
- Add Pagination feature for categories that have more than 20 books. The ones requested by Coffee&Cookies didn't, but it would be nice to have it ready.
- Add an interactive filter to select the categories.
- Send this to production for a better usage, possibly using streamlit and heroku.