diff --git a/_preview/451/.buildinfo b/_preview/451/.buildinfo
index d33b098e..8cd5f538 100644
--- a/_preview/451/.buildinfo
+++ b/_preview/451/.buildinfo
@@ -1,4 +1,4 @@
# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: c6223f73990e6194ad3eb736a6f744bd
+config: ca6d3a49520e6989a968258d09adada5
tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/_preview/451/_images/NSF-Unidata_lockup_horizontal_2023.png b/_preview/451/_images/NSF-Unidata_lockup_horizontal_2023.png
new file mode 100644
index 00000000..740c01fa
Binary files /dev/null and b/_preview/451/_images/NSF-Unidata_lockup_horizontal_2023.png differ
diff --git a/_preview/451/_sources/cookbook-guide.md b/_preview/451/_sources/cookbook-guide.md
index ff0395fc..713cd3fd 100644
--- a/_preview/451/_sources/cookbook-guide.md
+++ b/_preview/451/_sources/cookbook-guide.md
@@ -258,9 +258,12 @@ As always, reach out to a Pythia team member for help with any of these steps!
### Initiate the Cookbook review process
-Your Cookbook will be assigned a Cookbook advocate from the Project Pythia maintenance team.
+If you haven't already, now is a great time to [contact the Project Pythia team](https://discourse.pangeo.io/c/education/project-pythia/60) to let them know about your new Cookbook. You will be assigned a Cookbook advocate from the Pythia maintenance team.
They will open an issue on your Cookbook repository with the [Cookbook Checklist](cookbook-tasklist.md) for you to document your completion of the above process, plus a few more GitHub-specific steps.
Once you complete this process, your Cookbook will be ready for review and publication!
+
+### Submit your Cookbook to the Gallery
+
Click the button below to request addition of your Cookbook to the [Project Pythia Cookbook Gallery](https://cookbooks.projectpythia.org).
diff --git a/_preview/451/_sources/cookbook-tasklist.md b/_preview/451/_sources/cookbook-tasklist.md
index d9313a21..367abe65 100644
--- a/_preview/451/_sources/cookbook-tasklist.md
+++ b/_preview/451/_sources/cookbook-tasklist.md
@@ -9,7 +9,7 @@ Once we've marked this entire checklist, [click here to open an issue on Project
---
- [ ] **Confirm you’ve followed the entire Project Pythia [Cookbook Guide](https://projectpythia.org/cookbook-guide.html)**.
-Take note especially of the **Develop your cookbook**, **Authorship and the CITATION.cff file**, **Gallery tags**, and **Generate a DOI** sections. **Save the step of making a “release” of your cookbook as the last step of this checklist.**
+Take note especially of the [Develop your cookbook](https://projectpythia.org/cookbook-guide.html#develop-your-cookbook), [Authorship and the CITATION.cff file](https://projectpythia.org/cookbook-guide.html#authorship-and-the-citation-cff-file), and [Gallery tags](https://projectpythia.org/cookbook-guide.html#gallery-tags) sections. **Save the [Generate a DOI](https://projectpythia.org/cookbook-guide.html#generate-a-doi) step as the last step of this checklist.**
- [ ] **Confirm that the individual notebooks within your Cookbook adhere to the [notebook template](https://github.com/ProjectPythia/cookbook-template/blob/main/notebooks/notebook-template.ipynb)**.
If the template does not fit your Cookbook’s needs, that’s fine too! Simply let us know here in this issue.
- [ ] **Finalize your Cookbook repository name.**
@@ -40,7 +40,7 @@ This can be seen in individual Pull Requests as green checkmarks ✅ for importa
- trigger-link-check will fail if links in your content can not be resolved. We can help ignore links that are broken even if they work on manual clicks.
- Code errors in your notebooks themselves
- [ ] **Identify a Maintainer team via GitHub handle(s) in this thread.**
-This can be one or more people with availability to check in on this Cookbook, issue fixes to broken content, or with a vision for the future development of the Cookbook.
+This can be one or more people with availability to check in on this Cookbook, issue fixes to broken content, or with a vision for the future development of the Cookbook. This is typically (but not necessarily) one of the primary authors of the Cookbook.
- [ ] **Finally, release your Cookbook!**
- On the right-hand sidebar for your Cookbook repository, click “Create a new release”. If you don’t see this button, you may need to click on the “Releases” header first and “Create” or “Draft” a new release.
![GitHub Repository sidebar section titled "Releases"](https://raw.githubusercontent.com/ProjectPythia/projectpythia.github.io/main/portal/_static/images/4-releases.png "Releases")
diff --git a/_preview/451/_sources/index.md b/_preview/451/_sources/index.md
index 99dbdfc9..6b1cd91a 100644
--- a/_preview/451/_sources/index.md
+++ b/_preview/451/_sources/index.md
@@ -9,9 +9,8 @@
An education and training hub for the geoscientific Python community
-
- Project Pythia is hosting a Cookbook Cook-Off June 11-14, 2024.
- Learn more here.
+
+ Donate to support Project Pythia!
[Project Pythia](about) is the education working group for [Pangeo](https://pangeo.io)
diff --git a/_preview/451/_sources/posts/fundraiser.md b/_preview/451/_sources/posts/fundraiser.md
new file mode 100644
index 00000000..68850e75
--- /dev/null
+++ b/_preview/451/_sources/posts/fundraiser.md
@@ -0,0 +1,39 @@
+---
+blogpost: true
+date: Jun 28, 2023
+author: Julia kent
+tags: fundraiser
+---
+
+# Donate to Support Project Pythia!
+
+## You can make an impact on our community!
+By donating to support Project Pythia you are investing in an important educational resource for the entire geoscience community, from students to late career. Project Pythia is an education working group helping geoscientists make sense of huge volumes of numerical scientific data using tools that facilitate open, reproducible science, and building an inclusive community of practice around these goals. Project Pythia is a home for Python-centered learning resources that are open-source, community-owned, geoscience-focused, and high-quality.
+
+Donations contribute to outreach and community engagement activities, such as participant support at our annual hackathons.
+
+## Friends of the National Center
+Friends of the National Center is the fundraising arm of the University Corporation for Atmospheric Research (UCAR), which manages the National Science Foundation National Center for Atmospheric Research. UCAR is a non-profit organization, so all donations to Project Pythia are tax-deductible to the fullest extent allowed by law.
+
+We accept donations through the following ways:
+**Online** – Click the Donate Button on the right (we accept credit cards, Paypal and ApplePay).
+**Check** – Mail your check made out to UCAR and send it to:
+UCAR – Friends of the National Center
+Attn: Sarah Swanson
+PO BOX 3000
+Boulder, CO 80307
+Please include in the memo: Donation for Project Pythia
+**Stock gifts, ACH Transfers, etc.** – Please reach out to Friends of the National Center at info@friendsofthenationalcenter.org
+
+
+
+
+
+
diff --git a/_preview/451/_sources/resource-gallery.md b/_preview/451/_sources/resource-gallery.md
index 15e6d85e..d5fd01af 100644
--- a/_preview/451/_sources/resource-gallery.md
+++ b/_preview/451/_sources/resource-gallery.md
@@ -14,7 +14,7 @@ Resource Gallery
:::{dropdown} affiliation
A tutorial for getting started with Python aimed at scientists with experience in at least one other coding language. Designed to teach you Python, not package specific syntax.
Introduction to Python for Atmospheric Science and Meteorology. Unidata is working to create a collection of online training materials focused on the use of Python in the atmospheric sciences. While our examples and scenarios may feature Unidata tools and data technologies, our aim is to present a generic ... more
Introduction to Python for Atmospheric Science and Meteorology. Unidata is working to create a collection of online training materials focused on the use of Python in the atmospheric sciences. While our examples and scenarios may feature Unidata tools and data technologies, our aim is to present a generic set of freely available tools that are generally useful to scientists, educators, and students in the geosciences, broadly defined.
-
Jupyter notebooks are a great way to have code, output, images, video, and other information in one place. Notebooks are an ideal tool for the student, research scientist, and even software developer. In this lesson we will go over the basic features of Jupyter notebooks and how to use them.
-
Author: Ryan Abernathey, Kerry Key Affiliation: Lamont-Doherty Earth Observatory
+
Author: Kerry Key, Ryan Abernathey Affiliation: Lamont-Doherty Earth Observatory
This book grew out of a course developed at Columbia University called Research Computing in Earth Science. It was written mostly by Ryan Abernathey, with significant contributions from Kerry Key. By separating the book from the class, we hope to create an open-source community resource for python education ... more
@@ -164,7 +100,7 @@ Resource Gallery
An Introduction to Earth and Environmental Data Science
-Author: Ryan Abernathey, Kerry Key
+Author: Kerry Key, Ryan Abernathey
Affiliation: Lamont-Doherty Earth Observatory
This book grew out of a course developed at Columbia University called Research Computing in Earth Science. It was written mostly by Ryan Abernathey, with significant contributions from Kerry Key. By separating the book from the class, we hope to create an open-source community resource for python education in the Earth and Environmental Sciences.
@@ -644,7 +580,7 @@ Resource Gallery
The examples below show GeoCAT-comp functions being utilized in real-world use cases. They also demonstrate how GeoCAT-comp can be used to make plots with Matplotlib (using Cartopy) and PyNGL (work in progress).
MetPy is a modern meteorological open-source toolkit for Python. It is a maintained project of Unidata to serve the academic meteorological community. MetPy consists of three major areas of functionality: plots, calculations, and file i/o.
-
Unidata Numpy tutorial that covers how to create an array of ‘data’, perform basic calculations on this data using python math functions, and slice and index the array.
-
Siphon is a collection of Python utilities for downloading data from remote data services. Much of Siphon’s current functionality focuses on access to data hosted on a THREDDS Data Server. It also provides clients to a variety of simple web services.
An overview on Siphon from the Unidata Python Workshop that: uses Siphon to access a THREDDS catalog, filters data, and uses Siphon to perform remote data access.
-
Examples of how wrf-python can be used to make plots with matplotlib (with basemap and cartopy) and PyNGL. None of these examples make use of xarray’s builtin plotting functions, since additional work is most likely needed to extend xarray in order to work correctly.
@@ -1518,31 +1354,6 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
-:::{grid-item-card}
-:shadow: md
-:class-footer: card-footer
-:class-card: tagged-card tutorial xarray
-
-
An introduction to Xarray through the Unidata Python Workshop that asks, "What is XArray and how does XArray fit in with Numpy and Pandas?"" by creating a DataArray, openning netCDF data using XArray, and subsetting the data.
-
-
-
-
-
-+++
-
-Tutorial
-Xarray
-
-:::
-
-
-
:::{grid-item-card}
:shadow: md
:class-footer: card-footer
@@ -1551,7 +1362,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Project Pythia, Julia Kent Affiliation:NCAR
+
Author: Project Pythia, Julia Kent Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers setting up a work environment and opening a .txt file. The content to follow along with this video is hosted on the Xdev Python Tutorial website.
@@ -1799,7 +1610,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Project Pythia, Julia Kent Affiliation:NCAR
+
Author: Project Pythia, Julia Kent Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers creating a data dictionary. The content to follow along with this video is hosted on the Xdev Python Tutorial website.
@@ -1827,7 +1638,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Project Pythia, Julia Kent Affiliation:NCAR
+
Author: Project Pythia, Julia Kent Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers how to write and call functions in Python. The content to follow along with this video is hosted on the Xdev Python Tutorial website.
@@ -1855,7 +1666,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Project Pythia, Julia Kent Affiliation:NCAR
+
Author: Project Pythia, Julia Kent Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers how to create and call modules and packages. The content to follow along with this video is hosted on the Xdev Python Tutorial website.
@@ -1883,7 +1694,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Project Pythia, Julia Kent Affiliation:NCAR
+
Author: Project Pythia, Julia Kent Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers how to use your first external buil-in package, `math`, and how to publish your package. The content to follow along with this video is hosted on the Xdev Python Tutorial website.
@@ -1911,7 +1722,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Project Pythia, A Kootz Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `numpy`. The content to follow along with this video is hosted on this Numpy Google Collab.
@@ -1967,7 +1778,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Recording from the Python Tutorial Seminar Series introducing the Python Package `matplotlib`. The content to follow along with this video is hosted on this Matplotlib Tutorial GitHub Repository.
@@ -1996,7 +1807,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Recording from the Python Tutorial Seminar Series introducing the Python Package `cartopy`. The content to follow along with this video is hosted in this Cartopy Tutorial GitHub Repository.
@@ -2053,7 +1864,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Project Pythia, Kevin Paul Affiliation:NCAR
+
Author: Project Pythia, Kevin Paul Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the tools Git and GitHub. The content to follow along with this tutorial is hosted in this Git and GitHub Demo GitHub Repository.
@@ -2081,7 +1892,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Max Grover, Project Pythia, Drew Camron Affiliation:NCAR
+
Author: Project Pythia, Max Grover, Drew Camron Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `pandas`. The content to follow along with this video is hosted in this Pandas Tutorial GitHub Repository.
@@ -2109,7 +1920,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Anderson Banihirwe, Project Pythia Affiliation:NCAR
+
Author: Project Pythia, Anderson Banihirwe Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `xarray`. This is the first lesson of a two part series. The content to follow along with this video is hosted in this Xarray Tutorial GitHub Repository.
@@ -2137,7 +1948,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Anderson Banihirwe, Project Pythia Affiliation:NCAR
+
Author: Project Pythia, Anderson Banihirwe Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `xarray`. This is the second lesson of a two part series. The content to follow along with this video is hosted in this Xarray Tutorial GitHub Repository.
@@ -2165,7 +1976,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Anderson Banihirwe, Project Pythia Affiliation:NCAR
+
Author: Project Pythia, Anderson Banihirwe Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `dask`. This is the first lesson of a two part series. The content to follow along with this video is hosted in this Xarray Tutorial GitHub Repository.
@@ -2193,7 +2004,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Anderson Banihirwe, Project Pythia Affiliation:NCAR
+
Author: Project Pythia, Anderson Banihirwe Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `dask`. This is the second lesson of a two part series. The content to follow along with this video is hosted in this Xarray Tutorial GitHub Repository.
@@ -2221,7 +2032,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Recording from the Python Tutorial Seminar Series introducing advanced plotting techniques and highlighting tools developed by GeoCAT. The content to follow along with this video is hosted in this Plotting with GeoCat GitHub Repository.
@@ -2250,7 +2061,7 @@ Xarray is inspired by and borrows heavily from pandas, the popular data analysis
Author: Project Pythia, A Kootz Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing `geocat-comp`. The content to follow along with this video is hosted in this GeoCat-Comp GitHub Repository.
diff --git a/_preview/451/_static/images/logos/NSF-Unidata_lockup_horizontal_2023.png b/_preview/451/_static/images/logos/NSF-Unidata_lockup_horizontal_2023.png
new file mode 100644
index 00000000..740c01fa
Binary files /dev/null and b/_preview/451/_static/images/logos/NSF-Unidata_lockup_horizontal_2023.png differ
diff --git a/_preview/451/about.html b/_preview/451/about.html
index 0ae2a77b..752875e4 100644
--- a/_preview/451/about.html
+++ b/_preview/451/about.html
@@ -70,7 +70,7 @@
-
+
@@ -826,7 +826,7 @@
By donating to support Project Pythia you are investing in an important educational resource for the entire geoscience community, from students to late career. Project Pythia is an education working group helping geoscientists make sense of huge volumes of numerical scientific data using tools that facilitate open, reproducible science, and building an inclusive community of practice around these goals. Project Pythia is a home for Python-centered learning resources that are open-source, community-owned, geoscience-focused, and high-quality.
By donating to support Project Pythia you are investing in an important educational resource for the entire geoscience community, from students to late career. Project Pythia is an education working group helping geoscientists make sense of huge volumes of numerical scientific data using tools that facilitate open, reproducible science, and building an inclusive community of practice around these goals. Project Pythia is a home for Python-centered learning resources that are open-source, community-owned, geoscience-focused, and high-quality.
By donating to support Project Pythia you are investing in an important educational resource for the entire geoscience community, from students to late career. Project Pythia is an education working group helping geoscientists make sense of huge volumes of numerical scientific data using tools that facilitate open, reproducible science, and building an inclusive community of practice around these goals. Project Pythia is a home for Python-centered learning resources that are open-source, community-owned, geoscience-focused, and high-quality.
By donating to support Project Pythia you are investing in an important educational resource for the entire geoscience community, from students to late career. Project Pythia is an education working group helping geoscientists make sense of huge volumes of numerical scientific data using tools that facilitate open, reproducible science, and building an inclusive community of practice around these goals. Project Pythia is a home for Python-centered learning resources that are open-source, community-owned, geoscience-focused, and high-quality.
Your Cookbook will be assigned a Cookbook advocate from the Project Pythia maintenance team.
+
If you haven’t already, now is a great time to contact the Project Pythia team to let them know about your new Cookbook. You will be assigned a Cookbook advocate from the Pythia maintenance team.
They will open an issue on your Cookbook repository with the Cookbook Checklist for you to document your completion of the above process, plus a few more GitHub-specific steps.
-Once you complete this process, your Cookbook will be ready for review and publication!
-Click the button below to request addition of your Cookbook to the Project Pythia Cookbook Gallery.
+Once you complete this process, your Cookbook will be ready for review and publication!
+
+
+
**Confirm you’ve followed the entire Project Pythia [Cookbook Guide](https://projectpythia.org/cookbook-guide.html)**.
-Take note especially of the **Develop your cookbook**, **Authorship and the CITATION.cff file**, **Gallery tags**, and **Generate a DOI** sections. **Save the step of making a “release” of your cookbook as the last step of this checklist.**
+Take note especially of the [Develop your cookbook](https://projectpythia.org/cookbook-guide.html#develop-your-cookbook), [Authorship and the CITATION.cff file](https://projectpythia.org/cookbook-guide.html#authorship-and-the-citation-cff-file), and [Gallery tags](https://projectpythia.org/cookbook-guide.html#gallery-tags) sections. **Save the [Generate a DOI](https://projectpythia.org/cookbook-guide.html#generate-a-doi) step as the last step of this checklist.**- [ ]**Confirm that the individual notebooks within your Cookbook adhere to the [notebook template](https://github.com/ProjectPythia/cookbook-template/blob/main/notebooks/notebook-template.ipynb)**.
If the template does not fit your Cookbook’s needs, that’s fine too! Simply let us know here in this issue.
- [ ]**Finalize your Cookbook repository name.**
@@ -434,7 +434,7 @@
By donating to support Project Pythia you are investing in an important educational resource for the entire geoscience community, from students to late career. Project Pythia is an education working group helping geoscientists make sense of huge volumes of numerical scientific data using tools that facilitate open, reproducible science, and building an inclusive community of practice around these goals. Project Pythia is a home for Python-centered learning resources that are open-source, community-owned, geoscience-focused, and high-quality.
+
Donations contribute to outreach and community engagement activities, such as participant support at our annual hackathons.
+
+
+
Friends of the National Center
+
Friends of the National Center is the fundraising arm of the University Corporation for Atmospheric Research (UCAR), which manages the National Science Foundation National Center for Atmospheric Research. UCAR is a non-profit organization, so all donations to Project Pythia are tax-deductible to the fullest extent allowed by law.
+
We accept donations through the following ways:
+Online – Click the Donate Button on the right (we accept credit cards, Paypal and ApplePay).
+Check – Mail your check made out to UCAR and send it to:
+UCAR – Friends of the National Center
+Attn: Sarah Swanson
+PO BOX 3000
+Boulder, CO 80307
+Please include in the memo: Donation for Project Pythia
+Stock gifts, ACH Transfers, etc. – Please reach out to Friends of the National Center at info@friendsofthenationalcenter.org
A tutorial for getting started with Python aimed at scientists with experience in at least one other coding language. Designed to teach you Python, not package specific syntax.
Introduction to Python for Atmospheric Science and Meteorology. Unidata is working to create a collection of online training materials focused on the use of Python in the atmospheric sciences. While our examples and scenarios may feature Unidata tools and data technologies, our aim is to present a generic ... more
Introduction to Python for Atmospheric Science and Meteorology. Unidata is working to create a collection of online training materials focused on the use of Python in the atmospheric sciences. While our examples and scenarios may feature Unidata tools and data technologies, our aim is to present a generic set of freely available tools that are generally useful to scientists, educators, and students in the geosciences, broadly defined.
-
Jupyter notebooks are a great way to have code, output, images, video, and other information in one place. Notebooks are an ideal tool for the student, research scientist, and even software developer. In this lesson we will go over the basic features of Jupyter notebooks and how to use them.
-
Author: Ryan Abernathey, Kerry Key Affiliation: Lamont-Doherty Earth Observatory
+
Author: Kerry Key, Ryan Abernathey Affiliation: Lamont-Doherty Earth Observatory
This book grew out of a course developed at Columbia University called Research Computing in Earth Science. It was written mostly by Ryan Abernathey, with significant contributions from Kerry Key. By separating the book from the class, we hope to create an open-source community resource for python education ... more
@@ -363,7 +312,7 @@
Unidata Python Training
An Introduction to Earth and Environmental Data Science
-Author: Ryan Abernathey, Kerry Key
+Author: Kerry Key, Ryan Abernathey
Affiliation: Lamont-Doherty Earth Observatory
This book grew out of a course developed at Columbia University called Research Computing in Earth Science. It was written mostly by Ryan Abernathey, with significant contributions from Kerry Key. By separating the book from the class, we hope to create an open-source community resource for python education in the Earth and Environmental Sciences.
@@ -734,7 +683,7 @@
The examples below show GeoCAT-comp functions being utilized in real-world use cases. They also demonstrate how GeoCAT-comp can be used to make plots with Matplotlib (using Cartopy) and PyNGL (work in progress).
MetPy is a modern meteorological open-source toolkit for Python. It is a maintained project of Unidata to serve the academic meteorological community. MetPy consists of three major areas of functionality: plots, calculations, and file i/o.
-
Unidata Numpy tutorial that covers how to create an array of ‘data’, perform basic calculations on this data using python math functions, and slice and index the array.
-
Siphon is a collection of Python utilities for downloading data from remote data services. Much of Siphon’s current functionality focuses on access to data hosted on a THREDDS Data Server. It also provides clients to a variety of simple web services.
An overview on Siphon from the Unidata Python Workshop that: uses Siphon to access a THREDDS catalog, filters data, and uses Siphon to perform remote data access.
-
Examples of how wrf-python can be used to make plots with matplotlib (with basemap and cartopy) and PyNGL. None of these examples make use of xarray’s builtin plotting functions, since additional work is most likely needed to extend xarray in order to work correctly.
An introduction to Xarray through the Unidata Python Workshop that asks, "What is XArray and how does XArray fit in with Numpy and Pandas?"" by creating a DataArray, openning netCDF data using XArray, and subsetting the data.
-
Author: Project Pythia, Julia Kent Affiliation:NCAR
+
Author: Project Pythia, Julia Kent Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers setting up a work environment and opening a .txt file. The content to follow along with this video is hosted on the Xdev Python Tutorial website.
Author: Project Pythia, Julia Kent Affiliation:NCAR
+
Author: Project Pythia, Julia Kent Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers creating a data dictionary. The content to follow along with this video is hosted on the Xdev Python Tutorial website.
Author: Project Pythia, Julia Kent Affiliation:NCAR
+
Author: Project Pythia, Julia Kent Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers how to write and call functions in Python. The content to follow along with this video is hosted on the Xdev Python Tutorial website.
Author: Project Pythia, Julia Kent Affiliation:NCAR
+
Author: Project Pythia, Julia Kent Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers how to create and call modules and packages. The content to follow along with this video is hosted on the Xdev Python Tutorial website.
Author: Project Pythia, Julia Kent Affiliation:NCAR
+
Author: Project Pythia, Julia Kent Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers how to use your first external buil-in package, `math`, and how to publish your package. The content to follow along with this video is hosted on the Xdev Python Tutorial website.
Author: Project Pythia, A Kootz Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `numpy`. The content to follow along with this video is hosted on this Numpy Google Collab.
Recording from the Python Tutorial Seminar Series introducing the Python Package `matplotlib`. The content to follow along with this video is hosted on this Matplotlib Tutorial GitHub Repository.
Recording from the Python Tutorial Seminar Series introducing the Python Package `cartopy`. The content to follow along with this video is hosted in this Cartopy Tutorial GitHub Repository.
Author: Project Pythia, Kevin Paul Affiliation:NCAR
+
Author: Project Pythia, Kevin Paul Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the tools Git and GitHub. The content to follow along with this tutorial is hosted in this Git and GitHub Demo GitHub Repository.
Author: Max Grover, Project Pythia, Drew Camron Affiliation:NCAR
+
Author: Project Pythia, Max Grover, Drew Camron Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `pandas`. The content to follow along with this video is hosted in this Pandas Tutorial GitHub Repository.
Author: Anderson Banihirwe, Project Pythia Affiliation:NCAR
+
Author: Project Pythia, Anderson Banihirwe Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `xarray`. This is the first lesson of a two part series. The content to follow along with this video is hosted in this Xarray Tutorial GitHub Repository.
Author: Anderson Banihirwe, Project Pythia Affiliation:NCAR
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Author: Project Pythia, Anderson Banihirwe Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `xarray`. This is the second lesson of a two part series. The content to follow along with this video is hosted in this Xarray Tutorial GitHub Repository.
Author: Anderson Banihirwe, Project Pythia Affiliation:NCAR
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Author: Project Pythia, Anderson Banihirwe Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `dask`. This is the first lesson of a two part series. The content to follow along with this video is hosted in this Xarray Tutorial GitHub Repository.
Author: Anderson Banihirwe, Project Pythia Affiliation:NCAR
+
Author: Project Pythia, Anderson Banihirwe Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing the Python Package `dask`. This is the second lesson of a two part series. The content to follow along with this video is hosted in this Xarray Tutorial GitHub Repository.
Recording from the Python Tutorial Seminar Series introducing advanced plotting techniques and highlighting tools developed by GeoCAT. The content to follow along with this video is hosted in this Plotting with GeoCat GitHub Repository.
Author: Project Pythia, A Kootz Affiliation:NSF NCAR
Recording from the Python Tutorial Seminar Series introducing `geocat-comp`. The content to follow along with this video is hosted in this GeoCat-Comp GitHub Repository.
@@ -2357,10 +2211,10 @@
Climatematch Academy
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@@ -2410,7 +2264,7 @@
Contribute
By the Project Pythia Community.
- Last updated on 9 August 2024.
+ Last updated on 6 September 2024.