Real Estate Market Analysis with Python
Investigating Property Transactions and Customer Satisfaction advanced
With Elitsa Kaloyanova
Project type: Career Track
Duration: 18 Hours
Background: The real estate market is a complex and dynamic entity of great interest for professionals in the field, investors, policymakers, and data analysts that wish to thoroughly understand the market conditions and customer behavior and make informed decisions. In our Real Estate Market Analysis with Python project, the client—a leading company in the industry—has collected data on properties and their customers and wishes you to help them with the real estate analysis.
Project Objective: This Real Estate Market Analysis with Python project aims for you to preprocess, analyze, and visualize the real estate property data, thereby generating meaningful insights about property transactions and customer profiles.
For this Real Estate Market Analysis with Python project, you’ll need Python v.3 and Jupyter Notebook installed.
You’ll need to have the following Python libraries installed:
- seaborn (optional)
The data in this Real Estate Market Analysis with Python project is divided into two main tables. The first dataset contains details about the properties, including ID, building details, sale date, etc. The second dataset comprises customer details, such as customer ID, entity, name, surname, and more.
- 2 Project files
- Guided and unguided instructions
- Part 1: Data Preprocessing
- Part 2: Descriptive Statistics
- Part 3: Data Analysis
- Part 4: Data Visualization
- Part 5: Data Interpretation