Potable water is defined as water that is suitable for human consumption (i.e., water that can be used for drinking or cooking). The term implies that the water is drinkable as well as safe. Here we our predicting the water potability i.e Water is Good for human resources or not potable.
This repository creates a Data Web App about safe water for human consumption by using Streamlit Python Package. More specifically, it allows its users to change the values of the nine predictor variables:
- pH
- Hardness
- Solids
- Chloramines
- Sulfate
- Conductivity
- Organic_carbon
- Trihalomethanes
- Turbidity
Trains a Random Forest Classifier model and, finally, observe the prediction of the trained model.
The imported csv file contains water quality metrics for 3276 different water bodies.
- First, we create a virtual Python environment called my_venv
python3 -m venv my_venv
- Then, we activate the virtual environment
source path_to_your_virtual_environment/bin/activate
- After getting to the virtual environment's file, install prerequisite packages
wget https://raw.githubusercontent.com/Mridul-Sharma01/Water_Potability/main/requirements.txt
and
pip install -r requirements.txt
- Dowload and unzip contents from Github repo
Dowload and unzip contents from https://github.com/Mridul-Sharma01/Water_Potablity/archive/refs/heads/main.zip
- Launch the app
streamlit run app.py
Package | Version |
---|---|
streamlit | 1.10.0 |
pandas | 1.4.2 |
sci-kit learn | 1.1.1 |
numpy | 1.9.2 |