This repository includes Active Energy Burned for Kim Wolf. Data obtained from Apple Health for Code Kentucky Python project - July 2022.
While learning Python through the Code Kentucky program, I was tasked with creating a project to demonstrate my data analysis skills. I chose to export and analyze select data from my Apple Health app in hopes to discover trends.
Version 1.0 - Date 7/21/2022
Hi 👋, I'm Kim Wolf - A life-long learner currently tackling Python through the Code Kentucky program.
🔭 I’m currently working on a project to analyze my health data, including Apple Watch stand hours, exercise time, heart rate, stand time, step count and walking heart rate average for the last two (2) years (time period June 1, 2020 through May 31, 2022).
🌱 I am currently learning Python.
💬 Ask me about my health goals - they are ever changing, but always striving to move the needle.
📫 How to reach me: kim41051@yahoo.com
👨💻 My current project is available in Github at https://github.com/KimBug29/AppleDataKW.git.
GENERAL USAGE NOTES: To view this project, the user must first install Anaconda with Jupyter Notebooks. Also pip install numpy and pandas.
The objective of this Python project is to obtain Apple health data for a two year time period and import as a csv file. Several tools will then be used to analyze the data for displaying graphs including: minimum, median and maximum stats. All work will be done by Kim Wolf. Version 1.0 - Date 7/21/2022 Version 1.0 is a data analysis of health information with the following project requirements:
- Project is specifically named and uploaded in GitHub with a minimum of 5 separate commits
- Gitignore is included to keep any secrets/passwords out of the GitHub repository
- A README file with at least one paragraph explaining the project
- Relevant packages to be installed to run the project include: Anaconda with Jupyter Notebooks Coding was performed using: Visual Studio Code Python v2022.8.0 - Python extension for Visual Studio Code Jupyter v2022.5.1001601848 - Jupyter extension for Visual Studio Code Pylint v2022.2.0 - Pylint extension for Visual Studio Code Python 3.10.2
- Data used within this project includes one export file(in csv format) of my health data, including Apple Watch stand hours, exercise time, heart rate, stand time, step count and walking heart rate average for the last two (2) years (time period June 1, 2020 through May 31, 2022). File name: Export_ActiveEnergyBurned.csv
Features include:
- Feature 1 - Read data in from a local csv file. Data exported from Apple Health app, then saved and imported as .csv file File imported using Pandas
- Feature 2 - Manipulate and clean my data - use custom functions to round all data to whole numbers of either minutes, hours or count
- Feature 3 - Analyze my data - Perform a minimum of 5 basic calculations with Pandas (or possibly custom functions) to find min, med and max and count/minutes of active energy burned - calories, basal energy burned - calories, exercise time, heart rate - count/min, resting heart rate - count/min.
- Feature 4 - Visualize my data - Make a minimum of 2 basic plots with matplotlib to provide a visual representation of the data. Plots include barh, scatter, line, and summary of multiple data in subplot.
- Feature 5 - Interpret my data and graphical output by using markdown cells in Jupyter Notebook. Each section contains an interpretation.
Contact information regarding this analysis: Developer: Kim Wolf Email: kim41051@yahoo.com
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