|
5 | 5 | "id": "0", |
6 | 6 | "metadata": {}, |
7 | 7 | "source": [ |
8 | | - "<img src=\"../../images/scipy2024.png\" align=\"right\" width=\"20%\">\n", |
| 8 | + "# SciPy 2024\n", |
9 | 9 | "\n", |
| 10 | + "## Welcome to the Xarray SciPy 2024 Tutorial! \n", |
10 | 11 | "\n", |
11 | | - "# Welcome to the Xarray SciPy 2024 Tutorial! \n", |
| 12 | + "<img src=\"https://images.squarespace-cdn.com/content/v1/6596dfc539fa52603ef8b8d4/277ecf67-8dd4-401f-a74c-df3574adf1d1/SCIPY-2024-no-textArtboard%2B1%403x.png?format=1500w\" align=\"right\" width=\"20%\">\n", |
12 | 13 | "\n", |
13 | 14 | "**Xarray**: *Friendly, Interactive, and Scalable Scientific Data Analysis*\n", |
14 | 15 | "\n", |
15 | 16 | "July 8, 13:30–17:30 (US/Pacific), Room 317\n", |
16 | 17 | "\n", |
17 | | - "This *4-hour* workshop will explore content from [the Xarray tutorial](https://tutorial.xarray.dev), which contains a comprehensive collection of hands-on tutorial Jupyter Notebooks. We won't cover it all today, but instead will review a curated set of examples that will prepare you for increasingly complex real-world data analysis tasks!\n", |
| 18 | + "This *4-hour* workshop will explore content from [the Xarray tutorial](https://tutorial.xarray.dev), which contains a comprehensive collection of hands-on tutorial Jupyter Notebooks. We will review a curated set of examples that will prepare you for increasingly complex real-world data analysis tasks!\n", |
18 | 19 | "\n", |
19 | | - "## *Draft* Schedule \n", |
| 20 | + ":::{admonition} Learning Goals\n", |
| 21 | + "- Orient yourself to Xarray resources to continue on your Xarray journey!\n", |
| 22 | + "- Effectively use Xarray’s multidimensional indexing and computational patterns\n", |
| 23 | + "- Understand how Xarray can wrap other array types in the scientific Python ecosystem\n", |
| 24 | + "- Learn how to leverage Xarray’s powerful backend and extension capabilities to customize workflows and open a variety of scientific datasets\n", |
| 25 | + ":::\n", |
| 26 | + "\n", |
| 27 | + "## Schedule \n", |
20 | 28 | "\n", |
21 | 29 | "*Times in US/Pacific Timezone (Tacoma, WA)\n", |
22 | 30 | "\n", |
|
27 | 35 | "| Introduction and Setup | 1:30 (10 min) | --- | \n", |
28 | 36 | "| Xarray Data Model, Backends, Extensions | 1:40 (40 min) | [Quick Introduction to Indexing](../../fundamentals/02.1_indexing_Basic.ipynb) <br> [Boolean Indexing & Masking](../../intermediate/indexing/boolean-masking-indexing.ipynb) | \n", |
29 | 37 | "| *10 minute Break* \n", |
30 | | - "| Computational Patterns | 2:30 (50 min) | [Computation Patterns](../../intermediate/01-high-level-computation-patterns.ipynb) | \n", |
| 38 | + "| Computational Patterns | 2:30 (50 min) | [Advanced Indexing](../../intermediate/indexing/advanced-indexing.ipynb) <br> [Computation Patterns](../../intermediate/01-high-level-computation-patterns.ipynb) <br> | \n", |
31 | 39 | "| *10 minute Break* | \n", |
32 | | - "| Wrapping other arrays | 3:30 (50 min) | [Xarray and Dask](../../intermediate/xarray_and_dask.ipynb) | \n", |
| 40 | + "| Wrapping other arrays | 3:30 (50 min) | [The Xarray Ecosystem](../../intermediate/xarray_ecosystem.ipynb) <br> [Accessors](../../advanced/accessors/01_accessor_examples.ipynb) <br> [Backends](../../advanced/backends/1.Backend_without_Lazy_Loading.ipynb) <br> | \n", |
33 | 41 | "| *10 minute Break* | \n", |
34 | | - "| Synthesis, Explore your data! | 4:30 (30 min) <br> <br> <br> 5:00 (30 min) | Apply what you've learned, let's work together with your own data |\n", |
35 | | - "| | **End 5:30** | |\n", |
| 42 | + "| Synthesis, Explore your data! | 4:30 (50 min) <br> | [Data Tidying](../../intermediate/data_cleaning/05.1_intro.md) <br> |\n", |
| 43 | + "| | End 5:30 | |\n", |
| 44 | + "\n", |
| 45 | + "\n", |
| 46 | + "### Tutorial Setup\n", |
| 47 | + "\n", |
| 48 | + "We recommend using a preconfigured GitHub Codespace for this tutorial. This section describes how to access and manage a GitHub Codespace.\n", |
| 49 | + "\n", |
| 50 | + ":::{note}\n", |
| 51 | + "If you prefer to work on your own computer, refer to instructions in the [Getting Started Section](../../overview/get-started.md)\n", |
| 52 | + ":::\n", |
| 53 | + "\n", |
| 54 | + "This tutorial is available to run within [Github Codespaces](https://github.com/features/codespaces) - \"a development environment that's hosted in the cloud\" - with the conda environment specification in the [`conda-lock.yml`](../../conda/conda-lock.yml) file.\n", |
| 55 | + "\n", |
| 56 | + "[](https://github.com/codespaces/new/xarray-contrib/xarray-tutorial/tree/main?devcontainer_path=.devcontainer%2Fscipy2024%2Fdevcontainer.json)\n", |
| 57 | + "\n", |
| 58 | + "☝️ Click the button above to go to options window to launch a Github Codespace.\n", |
| 59 | + "\n", |
| 60 | + "GitHub currently gives every user [120 vCPU-hours per month for free](https://docs.github.com/en/billing/managing-billing-for-github-codespaces/about-billing-for-github-codespaces#monthly-included-storage-and-core-hours-for-personal-accounts), beyond that you must pay. **So be sure to explicitly stop your Codespace when you are done by going to this page (https://github.com/codespaces).**\n", |
| 61 | + "\n", |
| 62 | + "Once your Codespace is launched, the following happens:\n", |
| 63 | + "\n", |
| 64 | + "- [Visual Studio Code](https://code.visualstudio.com/) Interface will open up within your browser.\n", |
| 65 | + "- A built in terminal will open and it will execute `jupyter lab` automatically.\n", |
| 66 | + "- Once you see a url to click within the terminal, simply `cmd + click` the given url.\n", |
| 67 | + "- This will open up another tab in your browser, leading to a [Jupyter Lab](https://jupyterlab.readthedocs.io/en/latest/) Interface.\n", |
| 68 | + "\n", |
36 | 69 | "\n", |
37 | 70 | "\n", |
38 | 71 | "## Thanks for attending!\n", |
39 | 72 | "\n", |
40 | | - "Please continue to explore the subfolders in the JupyterLab File Browser for additional tutorial notebooks to run, or read the rendered notebooks at [https://tutorial.xarray.dev](https://tutorial.xarray.dev)" |
| 73 | + "Please continue to explore the subfolders in the JupyterLab File Browser for additional tutorial notebooks to run, or read the rendered notebooks at [https://tutorial.xarray.dev](https://tutorial.xarray.dev)\n", |
| 74 | + "\n", |
| 75 | + "### SciPy 2024 Organized by:\n", |
| 76 | + "\n", |
| 77 | + "- Scott Henderson (Univ. Washington)\n", |
| 78 | + "- Jessica Scheick (Univ. New Hampshire)\n", |
| 79 | + "- Negin Sobhani (National Center for Atmospheric Research)\n", |
| 80 | + "- Tom Nicholas [C]worthy\n", |
| 81 | + "- Max Jones (CarbonPlan)\n", |
| 82 | + "- Wietze Suijker (Space Intelligence)" |
41 | 83 | ] |
42 | | - }, |
43 | | - { |
44 | | - "cell_type": "markdown", |
45 | | - "id": "1", |
46 | | - "metadata": {}, |
47 | | - "source": [] |
48 | 84 | } |
49 | 85 | ], |
50 | 86 | "metadata": { |
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