This project was made as an assignment for Practicum100 Data Analysis course for mastering Exploratory Data Analysis.

The goal of this project is to find out which features of a vehicle influence its price the most by analyzing the data from ads published on the site of Crankshaft List every day. We have data for 2 years period, from 2018 to 2019.

Project structure:

1. General information. Taking a look at the data and determining first anomalities in data for the next step.
2. Data preprocessing. Further look into the data and preprocessing found anomalities (missing values, duplicates, mismatches etc). Additionally we'll make calculations needed for the analysis.
3. Exploratory Data Analysis. We'll check our features of interest from statistical point of view to determine whether the data is suitable for analysis, identifying outlierts etc, while studying the data in detail.
4. Overall conclusion and advice for business.

Additionally:

• The project was made in Jupyter Notebook, so to run it you should have Anaconda installed. It has a Table of Contents for easier navigation.

• The data for the project is additionally accesable by the link to Google Drive in the notebook itself. When downloaded, it has to be stored in the same folder with the notebook.

This project was created by Mila Lunacharska, in October 2021.