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First commit of new jupyterbook
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‎.gitignore

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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pip-wheel-metadata/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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.python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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.vscode/
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*.DS_Store
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_build/
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_thumbnails/
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content/pages/communications.md
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content/pages/contributing.md
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content/pages/code_of_conduct.md
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content/notebooks_gallery/

‎README.md

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# Project Pythia Foundations
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This is the source repository for the Project Pythia Foundations content collection.
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The book is powered by [Jupyter Book](https://jupyterbook.org/intro.html).

‎_config.yml

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# Book settings
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# Learn more at https://jupyterbook.org/customize/config.html
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title: Project Pythia Foundations
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author: The Project Pythia community
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logo: images/ProjectPythia_Logo_Final-01-Blue.png
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# Force re-execution of notebooks on each build.
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# See https://jupyterbook.org/content/execute.html
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execute:
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execute_notebooks: force
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# Define the name of the latex output file for PDF builds
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latex:
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latex_documents:
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targetname: book.tex
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# Add a bibtex file so that we can create citations
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bibtex_bibfiles:
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- references.bib
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# Information about where the book exists on the web
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repository:
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url: https://foundations.projectpythia.org # Online location of your book
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#path_to_book: docs # Optional path to your book, relative to the repository root
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branch: main # Which branch of the repository should be used when creating links (optional)
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# Add GitHub buttons to your book
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# See https://jupyterbook.org/customize/config.html#add-a-link-to-your-repository
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html:
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use_issues_button: true
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use_repository_button: true

‎_toc.yml

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# Table of content
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# Learn more at https://jupyterbook.org/customize/toc.html
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#
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- file: landing-page
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- part: Preamble
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chapters:
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- file: preamble/how-to-use
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- file: preamble/how-to-contribute
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- part: Foundational skills
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chapters:
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- file: foundations/overview
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- file: foundations/basic-python
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- file: foundations/jupyter
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- file: foundations/markdown
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- file: foundations/conda
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- file: foundations/version-control
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sections:
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- file: foundations/git
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- file: foundations/github
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- part: Core Scientific Python packages
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chapters:
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- file: core/overview
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- file: core/numpy
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- file: core/matplotlib
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- file: core/cartopy
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- file: core/datetime
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- file: core/pandas
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- file: core/data-formats
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- file: core/xarray

‎core/cartopy.md

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# Cartopy
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```{note}
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This content is under construction!
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```
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This section will contain tutorials on plotting map with [cartopy](https://scitools.org.uk/cartopy/docs/latest/). It will be cross-referenced with tutorials on [xarray](xarray) and [matplotlib](matplotlib).

‎core/data-formats.md

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# Data Formats
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```{note}
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This content is under construction!
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```
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This section will contain tutorials on how to interact in Python with data file formats in widespread use in the geosciences, such as NetCDF.

‎core/datetime.md

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# Datetime
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```{note}
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This content is under construction!
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```
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This section will contain tutorials on dealing with times and calendars in scientific Python, including use of the [datetime](https://docs.python.org/3/library/datetime.html) library.

‎core/matplotlib.md

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# Matplotlib
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```{note}
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This content is under construction!
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```
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This section will contain tutorials on basic plotting with [matplotlib](https://matplotlib.org).

‎core/numpy.md

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# Numpy
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```{note}
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This content is under construction!
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```
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This section will contain tutorials on array computing with [numpy](https://numpy.org).

‎core/overview.md

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# Overview
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This section will contain cross-referenced tutorial material for several packages in the Scientific Python ecosystem that are in wide use across the Geosciences.
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## Packages
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- [Numpy](numpy): Core package for array computing, the workhorse of the Scientific Python stack
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- [matplotlib](matplotlib): Basic plotting
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- [cartopy](cartopy): Plotting on map projections
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- [datetime](datetime): Dealing with time and calendar data
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- [pandas](pandas): Working with labeled tabular data
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- [Data formats](data-formats): Working with common geoscience data formats
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- [xarray](xarray): Working with gridded and labeled N-dimensional data

‎core/pandas.md

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# Pandas
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```{note}
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This content is under construction!
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```
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This section will contain tutorials on using [pandas](https://pandas.pydata.org) for labeled tabular data.

‎core/xarray.md

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# Xarray
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```{note}
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This content is under construction!
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```
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This section will contain tutorials on using [xarray](http://xarray.pydata.org/en/stable/) for analysis of gridded N-dimensional datasets.

‎foundations/basic-python.md

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# Basic Python Syntax
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```{note}
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This content is under construction!
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```

‎foundations/conda.md

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# Using the conda package manager
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```{note}
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This content is under construction!
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```

‎foundations/git.md

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# Basic version control with git
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```{note}
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This content is under construction!
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```

‎foundations/github.md

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# Getting started with GitHub
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```{note}
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This content is under construction!
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```

‎foundations/jupyter.md

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# Computing with Jupyter
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```{note}
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This content is under construction!
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```

‎foundations/markdown.md

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# Markdown
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```{note}
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This content is under construction!
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```

‎foundations/overview.md

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# Overview
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This section will contain cross-referenced tutorial material for foundational computing skills that are needed to work effectively with the open-source Scientific Python stack.
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## Topics
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- [Basic Python Syntax](basic-python): Getting started with Python
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- [Computing with Jupyter](jupyter): An introduction to Jupyter environments for interactive, reproducible computing
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- [Markdown](markdown): The simple, human-readable text language used extensively in Jupyter notebooks, GitHub discussions, and elsewhere.
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- [Using the conda package manager](conda): Set up self-contained Python environments on your own machines.
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- [Version control with git and GitHub](version-control): Getting started with version control and collaboration tools

‎foundations/version-control.md

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# Version Control with git and GitHub
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```{note}
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This content is under construction!
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```

‎images/ProjectPythia_Logo_Final-01-Blue-NoText.svg

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‎images/ProjectPythia_Logo_Final-01-Blue.ico

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‎images/ProjectPythia_Logo_Final-01-Blue.png

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