chicago-rent-analysis

Software Used

• Python (version 3.9 or higher)

Python Packages Required

The following packages must be installed:

• pandas
• matplotlib
• numpy

Platform

This project was developed and tested on macOS.
It should also run on Windows or Linux with the same Python setup.

Section 2: Map of the Documentation

Project Folder Structure:

chicago-rent-analysis/
│
├── DATA/
│   ├── Business_Licenses_Chicago.csv
│   ├── cleaned_chicago_dataset.csv
│   └── Zillow_Rent_Prices.csv
│
├── SCRIPTS/
│   ├── data_cleaning.py
│   ├── eda.py
│   ├── panel_regression.py
│   └── run_pipeline.sh
│
├── OUTPUT/
│   ├── business_openings_distribution.png
│   ├── business_vs_rent_growth.png
│   ├── rent_and_business_monthly_XXXXX.png
│   ├── rent_data_availability.png
│   └── rent_growth_distribution.png
│
├── README.md
└── LICENSE

Section 3: Instructions for Reproducing Results

Step 1: Clone the Repository

git clone https://github.com/purplemorgy/chicago-rent-analysis
cd chicago-rent-analysis

---

Step 2: Install Git LFS (Required for Data Files)

This project uses Git Large File Storage (LFS) to manage large .csv datasets.
Without Git LFS, the data files will not download correctly.

Install Git LFS

Mac (Homebrew):

brew install git-lfs

windows download from https://git-lfs.com/

Linux

sudo apt install git-lfs

Initializing Git LFS

git lfs install

Download Dataset files

git lfs pull

Step 3: Run the pipeline

This project includes a pipeline script that automatically:

• Creates a virtual environment

• Installs required Python packages

• Runs data cleaning

• Generates EDA plots

• Runs panel regression models and prints interpretations

bash run_pipeline.sh