Bio data scripts & code samples related to the IOOS code sprint Biological Data Session.
Each subdirectory is focuses on a particular problem/question.
The subdirectories may contain R DESCRIPTION and/or python requirements.txt files to help with installing dependencies.
Subdirectories can also contain their own README files.
There are no hard rules here; it's just a quick and easy place to drop your scripts/examples.
If you're munging through data in Python, you might want to consider using a virtual environment to install your dependencies in.
On a Mac or Linux machine, you can quickly create a virtual environment with the commands below.
$ python3 -m venv env
$ source env/bin/activate # activate the environment
$ pip install -U pip # upgrade pip version
$ pip install -r requirements.txt
If you're installing and using jupyter notebooks this way, you'll also want to ensure that
the user is specified so your installed packages are found properly:
python -m ipykernel install --user
Now, you should be ready to fire up Python and start exploring!
The install.sh (and install_*.sh) files in the root dir are helpers which comb through the subdirs and try to install all dependencies.
They aren't pretty.
Highlights:
- data_to_dwc : Abby's example data transformations
- obis_subset : Pull data out of OBIS using robis then make some plots in R & in python.