Housekeeping + clean up sidebar (#190)

1. Move acknowledgments to intro.md.
2. Move domain specific tutorial links to "Keep Exploring"
3. Add Pythia material to "Keep Exploring"
4. Add CONTRIBUTING.md
5. Redirect SciPy 2022 link to Fundamental Learning Path
6. Reorganize with Data Tidying and Learning Path subheadings

Closes #49
Closes #81
Closes #176
Closes #179

Author: dcherian

CONTRIBUTING.md

@@ -1,18 +1,22 @@
-## Contributing
+# Contributing Guide
 
-This repository is a great opportunity to start contributing to Xarray.
+This tutorial repository is a great opportunity to start contributing to Xarray.
 
-- Report bugs, request features or submit feedback as a [GitHub Issue](https://docs.github.com/en/issues/tracking-your-work-with-issues/about-issues). First check existing issues: https://github.com/xarray-contrib/xarray-tutorial/issues !
+- Report bugs, request features or submit feedback as a [GitHub Issue](https://docs.github.com/en/issues/tracking-your-work-with-issues/about-issues). First check existing [issues](https://github.com/xarray-contrib/xarray-tutorial/issues) !
 
 - Make fixes, add content or improvements using [GitHub Pull Requests](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/about-pull-requests), the sections below go over this process in more detail:
 
+```{seealso}
+The Project Pythia Foundations material on  [Github](https://foundations.projectpythia.org/foundations/getting-started-github.html) and Github workflows is a great place to start if you are new to this.
+```
+
 ## Content Guidelines
 
 Please note that examples submitted to this repository should follow these
 guidelines:
 
 1. Run top-to-bottom without intervention from the user
-1. Not require external data sources that may disappear over time (external data sources that are highly unlikely to disappear are fine)
+1. Not require external data sources that may disappear over time (external data sources that are highly unlikely to disappear are fine). Small datasets for tutorial purposes can be added [here](https://github.com/pydata/xarray-data/) if necessary.
 1. Not be resource intensive, and should run within 2GB of memory
 1. Be clear and contain enough prose to explain the topic at hand
 1. Be concise and limited to one or two topics, such that a reader can get through the example within a few minutes of reading
@@ -31,7 +35,7 @@ cd xarray-tutorial
 
 You'll need `conda` or `mamba`, which can be installed from https://github.com/conda-forge/miniforge
 
-We also use [conda-lock](https://conda-incubator.github.io/conda-lock/) to ensure we have reproducible environments across different operating systems
+We also use [conda-lock](https://conda.github.io/conda-lock/) to ensure we have reproducible environments across different operating systems
 
 We also use [pre-commit hooks](https://pre-commit.com) to run styling and other checks before committing code.
 

README.md

@@ -33,3 +33,7 @@ jupyter lab
 ## Contributing
 
 Contributions are welcome and greatly appreciated! See our [CONTRIBUTING.md](./CONTRIBUTING.md) document.
+
+## Acknowledgements
+
+This website is the result of many contributions from the Xarray community! We're very grateful for everyone's volunteered effort as well as [sponsored development](https://xarray.dev/#sponsors). Funding for SciPy 2022, SciPy 2023 tutorial materialdevelopment specifically was supported by NASA's Open Source Tools, Frameworks, and Libraries Program (award 80NSSC22K0345).

_config.yml

@@ -19,7 +19,8 @@ parse:
   # https://jupyterbook.org/content/content-blocks.html?highlight=myst%20substitution#define-substitutions-for-your-whole-book
   # https://jupyterbook.org/content/content-blocks.html#using-substitutions-in-links
   myst_substitutions:
-    xarray_docs: https://xarray.dev
+    xarray_homepage: https://xarray.dev
+    xarray_docs: https://docs.xarray.dev
     xarray_repo: https://github.com/pydata/xarray
     xarray_forum: https://github.com/pydata/xarray/discussions
   myst_enable_extensions:
@@ -68,6 +69,7 @@ sphinx:
     - sphinxext.rediraffe
     - sphinx_exercise
   config:
+    language: en # accessibility
     # application/vnd.holoviews_load.v0+json, application/vnd.holoviews_exec.v0+json
     suppress_warnings: ['mystnb.unknown_mime_type', 'misc.highlighting_failure']
     notfound_context:
@@ -76,5 +78,6 @@ sphinx:
 
     rediraffe_redirects:
       scipy-tutorial/00_overview.ipynb: overview/get-started.md
+      workshops/scipy2022/README.md: overview/fundamental-path/README.md
 
     bibtex_reference_style: author_year # or label, super, \supercite

_toc.yml

@@ -6,7 +6,9 @@ parts:
     chapters:
       - file: overview/get-started.md
       - file: overview/xarray-in-45-min
-      - file: overview/fundamental-path/README.md
+      - file: overview/learning-paths.md
+        sections:
+          - file: overview/fundamental-path/README.md
 
   - caption: Fundamentals
     chapters:
@@ -39,7 +41,9 @@ parts:
       - file: intermediate/xarray_ecosystem
       - file: intermediate/hvplot
       - file: intermediate/cmip6-cloud
-      - file: data_cleaning/ice_velocity.ipynb
+      - file: data_cleaning/data_cleaning.md
+        sections:
+          - file: data_cleaning/ice_velocity
 
   - caption: Advanced
     chapters:
@@ -81,16 +85,8 @@ parts:
           - file: workshops/online-tutorial-series/02_indexing
           - file: workshops/online-tutorial-series/03_computation
 
-  - caption: Domain Specific
-    chapters:
-      - url: https://anopheles-genomic-surveillance.github.io/workshop-5/module-1-xarray.html
-        title: Genomics
-      - url: https://predictablynoisy.com/posts/2019/2019-10-22-xarray-neuro/
-        title: Electrophysiology
-
   - caption: Reference
     chapters:
+      - file: CONTRIBUTING
       - file: reference/resources
       - file: reference/glossary
-      - file: reference/bibliography
-      - file: reference/acknowledgements

data_cleaning/data_cleaning.md

@@ -0,0 +1,5 @@
+# Data Tidying
+
+```{tableofcontents}
+
+```

images/alignment_schematic.png

@@ -35,4 +35,16 @@ Ask questions on the Xarray Discussion Forum
 
 ````
 
+## Citation
+
 ✏️ To cite this material, you can use the recommended [Xarray citation](https://docs.xarray.dev/en/stable/getting-started-guide/faq.html#how-should-i-cite-xarray): {cite:p}`hoyerhamman2017`, {cite:p}`xarray_v202230`.
+
+## Acknowledgements
+
+This website is the result of many contributions from the Xarray community! We're very grateful for everyone's volunteered effort as well as [sponsored development](https://xarray.dev/#sponsors). Funding for SciPy 2022, SciPy 2023 tutorial material development specifically was supported by NASA's Open Source Tools, Frameworks, and Libraries Program (award 80NSSC22K0345).
+
+## Bibliography
+
+```{bibliography}
+:style: plain
+```

images/broadcasting.png

@@ -1,4 +1,4 @@
-# Fundamental Learning Path
+# Fundamentals Learning Path
 
 This syllabus comes from Scipy 2022 tutorial workshop.
 This path covers fundamental Xarray concepts with

images/broadcasting_schematic.png

@@ -0,0 +1,11 @@
+# Learning Paths
+
+Learning Paths are guided tours through the material on the site.
+These paths were originally built for in-person tutorials at the SciPy conference.
+They are useful if you would like to work through the material in an organized manner.
+
+Follow the links below to try out each path.
+
+```{tableofcontents}
+
+```

images/logo.png

@@ -5,7 +5,14 @@ demonstrate real-world applications of Xarray in a variety of use cases. These
 need not be explored in any particular sequence, instead they are meant to
 provide a sampling of what Xarray can be used for.
 
-## Weather/Climate Model Data
+```{seealso}
+1. The [Xarray blog](https://xarray.dev/blog) has a number of user stories showcasing Xarray in
+many scientific domains.
+2. [Project Pythia Foundations](https://foundations.projectpythia.org/) is a great collection of
+material on Xarray and related packages.
+```
+
+## Weather and Climate
 
 1. [Global Mean Surface Temperature from CMIP6](https://gallery.pangeo.io/repos/pangeo-gallery/cmip6/):
    Start with `global_mean_surface_temp.ipynb` then feel free to explore the
@@ -14,14 +21,21 @@ provide a sampling of what Xarray can be used for.
 1. [National Water Model Streamflow Analysis](https://gallery.pangeo.io/repos/rsignell-usgs/esip-gallery/):
    Start with `02_National_Water_Model.ipynb` then feel free to explore the rest
    of the notebooks.
-
-## Satellite Data
-
-1. [Planetary Computer Examples](https://github.com/microsoft/PlanetaryComputerExamples)
+1. The [Project Pythia Cookbooks](https://cookbooks.projectpythia.org/) are a great collection of
+   resources showcasing use of Xarray with real world datasets.
+1. [Examples using the Microsoft Planetary Computer](https://github.com/microsoft/PlanetaryComputerExamples)
 
 ## Bayesian Statistical Modeling
 
 1. [Xarray and PyMC3](https://mybinder.org/v2/gh/pymc-devs/pymc3/main?filepath=%2Fdocs%2Fsource%2Fnotebooks):
    Start with `multilevel_modeling.ipynb` then feel free to explore the rest of
    the notebooks. Also checkout [Arviz](https://arviz-devs.github.io/arviz/)
    which uses Xarray as its data model.
+
+## Genomics
+
+1. [From "data analysis for genomic surveillance of African malaria vectors" ](https://anopheles-genomic-surveillance.github.io/workshop-5/module-1-xarray.html)
+
+## Electrophysiology
+
+1.  ["Analyzing intracranial electrophysiology data with xarray"](https://chrisholdgraf.com/blog/2019/2019-10-22-xarray-neuro/)