Analysis of health conditions across US counties and health outcomes forecasting 📈

In this project we analyzed data from US Census, CDC, and other sources, and build a machine learning model to predict health outcomes across US counties.

The project consists of three main parts, which are:

1. Data collection, preprocessing
2. Exploratory Data Analysis (EDA)
3. Machine learning model building

▪️ Case_Study.ipynb contains jupyter notebook file with the project itself.

▪️ sunshine_data_scraper.py contains python code for scraping average annual sunshine data by state (across US).

▪️ Health_outomes_slides.pdf is a document with the presentation slides for this project.

To reproduce the same working enviroment, please follow these steps:

1. Clone the repository to desired location on your machine

git clone link-to-the-repo

2. Create conda enviroment with the correct python version and activate it

conda create --name myenv python=3.9
conda activate myenv

3. Install ipykernel package and enable your enviroment to show up in the list of available kernels in jupyter notebook

conda install ipykernel
python -m ipykernel install --user --name myenv --display-name "myenv"

4. Install required packages

conda install pandas==1.3.5

conda install openpyxl==3.0.10

conda install nbformat==5.7.0

conda install seaborn==0.12.2

conda install scipy==1.10.0

conda install scikit-learn==1.2.2

conda install yellowbrick==1.5

5. Install PLotly from the sourse

conda install -c https://conda.anaconda.org/plotly plotly

6. Open jupyter notebook from the same directory

jupyter notebook

7. Change the Kernel to "myenv" using Menu bar.

Now you can run the notebook cells.

⚠️ Some visualizations may not be displayed properly when you open the notebook in Jupyter. If that is the case, I reccommend you to open it in Google Colab via following link:

Link to Google Colab notebook: Health outcomes analysis in USA notebook

Link to presentation slides: Canva Slides