Abstract¶
Setup overview and detail.
A brief guide to setting up the software to visualize data. The summary workflow is
Install conda or miniconda
Create a virtual environment:
Download required packages including git
Download Visual Studio Code (or another IDE)
Sign up for Github
Conda and Virtual Environment¶
Install conda by downloading miniconda or anaconda appropriate for your os. Miniconda is the lighter version of anaconda. The latter comes with a desktop user interface, miniconda does not.
Open a terminal you should see something like
(base) $
Enter the following command in your terminal (use whatever simple name you want, here we’re using ‘geo’):
(base) $ conda create -n geo python
If you want, specify the python version, usually safest to use the previous version:
(base) $ conda create -n geo python=3.13
Hit enter or Y to create the environment. Once installed, check the new env exists by entering
(base) $ conda env list
Then activate the new env
(base) $ conda activate geo
The terminal will change and look something like
(geo) $
Install the base packages into the new env:
(geo) $ pip install -r requirements.txt
Awesome, you just used the terminal to create new env and install software. Not so bad, was it?
Install VS Code & Extensions¶
Visual Studio Code is a powerful open-source code editor. There are other integrated development environments (IDEs) such as Pycharm or Spyder (comes with Anaconda), so choose the one that’s best for you. Note that if you only use R, RStudio comes with an integrated terminal and IDE so you can solely work within RStudio. If you use multiple languages, however, VS Code is fantastic, used by many (so it makes tutorials and learning new packages or languages easier), and it has many plugins to make it easy to use.
Visual Studio Code has great documentation and setup tutorials so that we won’t explore those here. Download VS Code for your OS and open it. On the left-hand pane, there is an icon with 4 squares for extensions. Click on that to open it and install and activate the following extensions (use the search box at the top of the extension pane to find each extension):
Bracket Pair Color DLW
autoDocstring
Code Spell Checker
CodeSnap
GitHub Actions, GitHub Pull Requests, and GitHub Repositories
GitLens
Highlight Matching Tag
indent-rainbows
Jupyter
Prettier
Python
Optional extensions include github copilot (requires a subscription) and chatgpt (requires a subscription for some versions). I highly recommend considering copilot as the chat and autocomplete, for it often suggests code that works or can help you resolve errors in your code when searches or your own editing don’t work. It will also greatly speed up the process of producing code and seems to be improving rapidly. Copilot is free to students and possibly free through select nonprofit organizations.
No you’re ready to use script and notebooks interactively.