The purpose of this project is to practice the process of Data Cleaning in Python. I used the libraries Pandas, NumPy, Os and Re.

The raw data, is in the folder data, and it was extracted from the spanish website "www.pccomponentes.com" using Power Automate. The data includes all the Laptops in sale on 25th June 2023. The data columns are as follows:

• Laptop: Raw data, including all the carachteristics for each laptop.

• New Price: If there is discounted price, it's included in this column.

• Old Price: If there is discounted price, the old price it's in this column.

• Price: The price is here when there isn't any discount.

• Old Price 2: Sometimes, the price is included here.

• Status: Here we see the status of the laptop. However, the only interesting value is reacondicionado. If not, it's new.

In LaptopsDataCleaning.ipynb it's all the process of data cleaning, and the final result is the file laptops.csv