Jeff's Data Analysis Toolchain

Installing Dependencies

You will need access to these commands on the command line:

• conda (Anaconda or Miniconda with Python 3)
• git (conda install git or git-scm.com)

Download this source code, either manually through GitHub or using git:

git clone https://github.com/jpgill86/analysis.git

On the command line, navigate to the top-level directory:

cd analysis

Create a new conda environment:

conda env create -f environment.yml -n analysis

or update an existing one:

conda env update -f environment.yml -n analysis

Instead of analysis, you could use any environment name you like, but the scripts in the scripts directory assume this is your environment name.

Getting Started

Activate your conda environment and launch Jupyter notebook:

conda activate analysis
jupyter notebook

Using the Jupyter file browser, navigate to the notebooks directory and select a Jupyter notebook file (*.ipynb) to begin a session.

The launch-notebooks script located under scripts can run these commands and navigate to the correct directory for you.

Notes

When creating a new conda environment, you may use one of the files in the snapshots directory instead of environment.yml to create an exact replica of an environment created using that file on a particular date (these files were created using conda env export, with git commands pointing to specific commits added manually). This is useful for tracking down bugs or reproducing old results exactly when external package updates create unexpected changes in output. Using old environment snapshots may result in installing old versions of packages when newer versions would work just as well, so try environment.yml first.