Project overview
In this project, you’ll take on the role of a data analyst working for a used car classifieds service. You’ll work with a scraped dataset of used car listings from eBay Kleinanzeigen, a section of the German eBay website. The goal is to clean the data and analyze the included used car listings.
This project will allow you to apply a variety of data cleaning and exploration techniques using Python’s pandas library. You’ll develop skills in identifying and handling missing values, converting data types, filtering and grouping data, and performing aggregations to extract insights. These practical data wrangling and analysis skills are essential for working with real-world datasets.
Objective: Clean and analyze a used car listings dataset to gain insights into pricing and mileage trends across different car brands.
Key skill required
To complete this project, it's recommended to build these foundational skills in Python
- Working with NumPy arrays and performing vectorized operations
- Selecting data using Boolean indexing in NumPy and pandas
- Exploring and analyzing data using the pandas library
- Cleaning and preparing data for analysis using pandas
Projects steps
Step 1: Introduction
Step 2: Cleaning Column Names
Step 3: Initial Exploration and Cleaning
Step 4: Exploring the Odometer and Price Columns
Step 5: Exploring the Date Columns
Step 6: Dealing with Incorrect Registration Year Data
Step 7: Exploring Price by Brand
Step 8: Storing Aggregate Data in a DataFrame
Step 9: Next Steps
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