This project calculates an "energy score" based on input data such as physical activity, nutrition, sleep quality, and mental stress levels. The energy score helps users understand their overall health and well-being.
There are two different approaches to calculate the energy score in this repository. Below are the steps to run each approach.
This approach calculates the energy score using basic parameters such as steps, exercise minutes, average heart rate, and stress level. It uses a single set of input data for the calculation.
- Clone the repository to your local machine:
git clone https://github.com/NishanthGowda007/EnergyScoreSystem.git
2.Navigate to the project folder: cd EnergyScoreSystem
3.Run the Python script for Approach 1: python approach1.py
In this approach, the energy score is calculated for each row of health data from a CSV file. This method processes a dataset that includes multiple health records and saves the energy score results to a new CSV file.
- Clone the repository to your local machine:
git clone https://github.com/NishanthGowda007/EnergyScoreSystem.git
2.Prepare a CSV file (synthetic_health_data1.csv) with health data, including columns such as steps, exercise_minutes, heart_rate_avg, stress_level, total_sleep_time, sleep_efficiency, protein, carbohydrates, and fat.
3.Place the CSV file in the project directory.
4.Navigate to the project folder: cd EnergyScoreSystem
5.Run the Python script for Approach 2: python approach2.py
6.The energy score for each row in the dataset will be calculated and saved in a new file called energy_scores_output.csv.