• Following the extraction of data through web scraping, my initial data preparation in Excel involved employing the "Text to Columns" feature, eliminating commas, and subsequently removing empty rows and irrelevant columns.

• The Power Query Editor played a pivotal role in this undertaking. I adjusted the data type of the listing price to a whole number, addressing the presence of currency symbols. Additionally, I excluded a column indicating "no rating," considering that all cars lacked ratings. For listing location, I focused exclusively on city names, disregarding town addresses. Notably, I resolved formatting issues where the vehicle type, kilometers, and transmission columns presented challenges, particularly with new cars lacking kilometer data and the misplacement of transmission details.

• Pivot tables were then generated using the refined dataset. The analysis aimed to uncover patterns such as the expected higher prices for new cars, lower mileage, and the intriguing finding that demo cars, despite common perception, were not consistently cheaper than brand-new ones.

• Further insights revealed a trend wherein manual cars tended to be more affordable, likely attributed to the rising popularity and costliness of automatic transmissions. Notably, the Chery Tiggo 8 emerged as a luxury car, even in its base model, maintaining a higher price point. For first-time buyers, the Tiggo 4 was recommended, supported by condition formatting indicating that the Pro Urban 1.5 variant exhibited a lower average listing price.