Context

Who are the Top 100 TikTokers from Pakistan? Who to follow? how many followers they have? How many videos they have uploaded? This dataset answer all of these questions

Content

Top 100 TikTokers from Pakistan. The dataset contains their TikTok IDs, Names, Number of videos and Followers Count

Inspiration

Can you help us understand what contents our youth is consuming and how many hours we spend on TikTok as a Nation?

👨‍💻 Author: Azhar Saleem

"https://github.com/azharsaleem18" target="_blank"> https://img.shields.io/badge/GitHub-Profile-blue?style=for-the-badge&logo=github" alt="GitHub Profile"> "https://www.kaggle.com/azharsaleem" target="_blank"> https://img.shields.io/badge/Kaggle-Profile-blue?style=for-the-badge&logo=kaggle" alt="Kaggle Profile"> "https://www.linkedin.com/in/azhar-saleem/" target="_blank"> https://img.shields.io/badge/LinkedIn-Profile-blue?style=for-the-badge&logo=linkedin" alt="LinkedIn Profile">
"https://www.youtube.com/@AzharSaleem19" target="_blank"> https://img.shields.io/badge/YouTube-Profile-red?style=for-the-badge&logo=youtube" alt="YouTube Profile"> "https://www.facebook.com/azhar.saleem1472/" target="_blank"> https://img.shields.io/badge/Facebook-Profile-blue?style=for-the-badge&logo=facebook" alt="Facebook Profile"> "https://www.tiktok.com/@azhar_saleem18" target="_blank"> https://img.shields.io/badge/TikTok-Profile-blue?style=for-the-badge&logo=tiktok" alt="TikTok Profile">
"https://twitter.com/azhar_saleem18" target="_blank"> https://img.shields.io/badge/Twitter-Profile-blue?style=for-the-badge&logo=twitter" alt="Twitter Profile"> "https://www.instagram.com/azhar_saleem18/" target="_blank"> https://img.shields.io/badge/Instagram-Profile-blue?style=for-the-badge&logo=instagram" alt="Instagram Profile"> "mailto:azharsaleem6@gmail.com"> https://img.shields.io/badge/Email-Contact%20Me-red?style=for-the-badge&logo=gmail" alt="Email Contact">

Dataset Description

This dataset represents a comprehensive collection of vehicle listings from PakWheels.com, Pakistan's largest automobile website, as of 2024. It includes detailed information about various aspects of vehicles available for sale across Pakistan, including their prices, models, mileage, engine capacity, and age. This data offers a snapshot of the current automobile market in Pakistan, providing insights into vehicle valuation trends, consumer preferences, and market dynamics.

The dataset is designed for anyone interested in the Pakistani automobile market, whether they are buyers, sellers, car enthusiasts, analysts, or researchers. It provides a foundational dataset for a wide range of analytical and predictive tasks.

Columns Description

1. url: The URL of the vehicle listing on PakWheels.com. This can be used to reference the original listing for more detailed information or verification.
2. title: The title of the listing, which typically includes the make, model, and year of the vehicle.
3. price: The listed price of the vehicle in Pakistani Rupees. This is crucial for market analysis and price prediction models.
4. city: The city in Pakistan where the vehicle is located, useful for regional market analysis.
5. model: The manufacturing year of the vehicle. This is often a determinant of price depreciation.
6. mileage: The total mileage of the vehicle in kilometers, which affects the vehicle’s condition and price.
7. fuel_type: Type of fuel the vehicle uses (e.g., Petrol, Diesel, Hybrid), important for segment analysis based on fuel economy and environmental impact.
8. transmission: The type of transmission (e.g., Automatic, Manual), which influences the driving experience and market value.
9. registered: The city in which the vehicle is registered. This can impact the resale value and legality of the sale.
10. color: The color of the vehicle, which can be a factor in buyer preference.
11. assembly: Whether the vehicle was locally assembled or imported, affecting taxes, duties, and price.
12. engine_capacity: The engine capacity of the vehicle in cubic centimeters (cc), which is a key indicator of performance.
13. post_date: The date the listing was posted, useful for tracking market trends over time.
14. price_category: Categorical representation of the vehicle's price range (e.g., Low, Medium, High).
15. mileage_category: Categorical assessment of the vehicle's mileage (e.g., Low, Medium, High).
16. post_day_of_week: The day of the week the listing was posted, which might influence how quickly a vehicle sells.
17. vehicle_age: The age of the vehicle calculated from the model year to the current year, affecting depreciation and market value.

Usage and Potential Applications in Data Analysis

Market Analysis

• Pricing Trends: Analyze how the prices of vehicles change based on age, mileage, and other factors. This can help in un...