Tidepool Data Science Project Template

Creating a new repository from this template

You can create a new repository from this template manually by going here.

Step by step directions from github are located here.

The purpose of this project is to [___].

This phase of the project will be done when [___].

(Add a short paragraph with some details, Why?, How?, Link to Jira and/or Confluence) In order to learn [], we did [].

Install Miniconda. CAUTION for python virtual env users: Anaconda will automatically update your .bash_profile so that conda is launched automatically when you open a terminal. You can deactivate with the command conda deactivate or you can edit your bash_profile.
If you are new to Anaconda check out their getting started docs.
If you want the pre-commit githooks to install automatically, then following these directions.
Clone this repo (for help see this tutorial).
In a terminal, navigate to the directory where you cloned this repo.
Run conda update -n base -c defaults conda to update to the latest version of conda
Run conda env create -f conda-environment.yml --name [input-your-env-name-here]. This will download all of the package dependencies and install them in a conda (python) virtual environment. (Insert your conda env name in the brackets. Do not include the brackets)
Run conda env list to get a list of conda environments and select the environment that was created from the environmental.yml file (hint: environment name is at the top of the file)
Run conda activate <conda-env-name> or source activate <conda-env-name> to start the environment.
If you did not setup your global git-template to automatically install the pre-commit githooks, then run pre-commit install to enable the githooks.
Run deactivate to stop the environment.

Raw Data is being kept [here](Repo folder containing raw data) within this repo. (If using offline data mention that and how they may obtain the data from the froup)
Data processing/transformation scripts are being kept [here](Repo folder containing data processing scripts/notebooks)
(Finishing filling out this list)

All are welcome to contribute to this project.
Naming convention for notebooks is [short_description]-[initials]-[date_created]-[version], e.g. initial_data_exploration-jqp-2020-04-25-v-0-1-0.ipynb. A short _ delimited description, the creator's initials, date of creation, and a version number,
Naming convention for data files, figures, and tables is [PHI (if applicable)]-[short_description]-[date created or downloaded]-[code_version], e.g. raw_project_data_from_mnist-2020-04-25-v-0-1-0.csv, or project_data_figure-2020-04-25-v-0-1-0.png.

NOTE: PHI data is never stored in github and the .gitignore file includes this requirement as well.