🏡 Nashville Housing Storyline
A Visual Exploration of Real Estate Trends in Nashville, TN
📌 Note: The dataset used in this project was pre-cleaned using my dedicated SQL workflow here:
👉 Nashville_SQL_Cleaning_Project
📍 Overview
This project uncovers housing market patterns in Nashville using Python-based visualizations. By analyzing over 48,000 property records, we dive into how sale price is influenced by property age, land use type, and structural value — turning raw real estate data into compelling visual narratives.
📦 Dataset
The data contains residential transactions from the Nashville area, including:
- Property age and sale price
- Land use classification
- Building and land value
- Owner and parcel information
🎯 Project Goals
- Clean and prepare large-scale real estate data
- Engineer insightful features like PropertyAge and BuildingToLandRatio
- Visualize market dynamics using Matplotlib and Seaborn
- Communicate insights through visually polished storytelling
📊 Key Insights
- Newer properties consistently command higher sale prices, especially within Residential categories.
- Vacant and underutilized land clusters around lower sale values.
- A high Building-to-Land Ratio often signals premium development — but outliers exist.
- Most transactions occur under $500K, with price skew driven by a handful of luxury parcels.
📚 What’s Inside
| File | Description |
|---|---|
Nashville_Housing_Cleaning.ipynb |
Full cleaning script with transformations |
images.PNG |
exported figures (PNG) |
README.md |
Project overview and documentation |
🧰 Tools Used
- pandas & numpy for data wrangling
- matplotlib & seaborn for custom plotting
- Optional exports via kaleido and plotly
- Notebook executed in VS Code
📸 Sample Visuals
- Scatter Plot — Sale Price vs Property Age by Land Use
- Line Plot — Average Sale Price Trends by Year
- Bar Chart — Total Number of Property Sales per Year These visuals support key takeaways and uncover pricing patterns across property types and time.
🚀 How to View
- Clone the repository
- Open the notebook in VS Code or Jupyter
- Run the notebook step by step
- Explore insights and visual narratives
📬 Author
Salma Mohammed
GitHub Profile
LinkedIn