This dataset contains:

• more than 55,000 clothing items from digikala.com
• name, price, discount, rating, url and a list of the url for all of each item's images.

1. raw_Data: Contains everything except image urls.
2. clean_Data: Contains everything.
3. clean_reduced_Data: Contains only names, urls, and image urls.

1. 'category product scraper.py' searches the input category in the website and extracts the name, price, discount, rating and url of each item.
2. 'preprocess_clean.ipynb' uses the csv files in the 'raw_Data' folder and finds the image links for each record of the csv file.
3. 'Single product image scraper.py' extracts the image links of the input (have to be set by hand) link.
4. 'preprocess_reduce.ipynb' uses the csv files in the 'clean_Data' folder and drops the price, discount and rating columns.