Exploring eBay Car Sales Data
- Guided Project
- 2.6 hours
- Beginner
- Python
Practice data cleaning and exploration using pandas to analyze a dataset of used cars from eBay Kleinanzeigen.
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.
What You'll Learn
- ✓ Clean a dataset on your own
- ✓ Employ new pandas methods
- ✓ Present your analysis to support your code
Before You Start
- ✓ 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
Project Steps
9 steps
- 1 Introduction
- 2 Cleaning Column Names
- 3 Initial Exploration and Cleaning
- 4 Exploring the Odometer and Price Columns
- 5 Exploring the Date Columns
- 6 Dealing with Incorrect Registration Year Data
- 7 Exploring Price by Brand
- 8 Storing Aggregate Data in a DataFrame
- 9 Next Steps
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