This is a fork of Glycemic Index Visualisation by Mandar Gite
The glycemic_index_analysis.py script contains the following functionality:
Accesses data from a webpage using Pandas.
- Cleans the data by resetting the index, deleting rows without glycemic index values, and removing the first and last rows of the dataframe.
- Creates several plots using Matplotlib and Seaborn:
- Bar plot of the top 10 foods with the highest glycemic index values.
- Bar plot of the bottom 10 foods with the lowest glycemic index values.
- Scatter plot of the glycemic index vs. glycemic load for all foods.
- Bar plot of the top and bottom two fruits by glycemic index.
- Python 3.6 or higher
- Pandas Python library for data manipulation and analysis
- Seaborn Python data visualization library for creating attractive and informative statistical graphics
- Matplotlib Python library for creating static, animated, and interactive visualizations in various formats
- Jypyter Notebook Open-source web application that allows you to create and share documents containing live code, equations, visualizations, and narrative text
Clone this repository into a folder of your choice:
git clone github.com/generallynonsensical/glycemic_index_visualisation
then
cd glycemic_index_visualisation
Create a Python Virtual Environment in the folder:
python3 -m venv .venv
then
Source .venv/bin/activate
Install Pandas Seaborn Matplotlib and Jupyter using pip:
pip install pandas seaborn matplotlib notebook
From terminal, in project directory, run:
jupiter notebook
Jupyter Notebook is then opened in browser at http://localhost:8888
Feel free to fork this repository and submit pull requests if you have any suggestions or improvements.
This project is licensed under the MIT License.