|
10 | 10 | }, |
11 | 11 | { |
12 | 12 | "cell_type": "markdown", |
13 | | - "id": "6a1dcd59-5bd5-4e1a-93d3-8e0850aacc9e", |
| 13 | + "id": "5e524b05-f463-4727-b212-93bf1450930e", |
| 14 | + "metadata": {}, |
| 15 | + "source": [ |
| 16 | + "## Outline" |
| 17 | + ] |
| 18 | + }, |
| 19 | + { |
| 20 | + "cell_type": "markdown", |
| 21 | + "id": "7abd406b-717c-4c46-a821-21788826f655", |
14 | 22 | "metadata": {}, |
15 | 23 | "source": [ |
16 | | - "## Outline\n", |
17 | | - "\n", |
18 | 24 | "* Aggregate gridded data based on vector regions (e.g. neighborhoods)\n", |
19 | 25 | " * Not straightforward to do in Python\n", |
20 | | - " * Design:\n", |
21 | | - " * Start in a Notebook, prepared with Maryam’s expertise\n", |
22 | | - " * Loading GeoPandas, tools for Zonal Statistics\n", |
23 | | - " * Programmatically create .jGIS document, add input data sources and output data sources.\n", |
24 | | - " * Demonstrate collaboration of JGIS alongside Notebook. Annotation, ad layer from catalog, etc." |
| 26 | + "* Design:\n", |
| 27 | + " * Start in a Notebook, prepared with Maryam’s expertise\n", |
| 28 | + " * Loading GeoPandas, tools for Zonal Statistics\n", |
| 29 | + " * Programmatically create .jGIS document, add input data sources and output data sources.\n", |
| 30 | + " * Demonstrate collaboration of JGIS alongside Notebook. Annotation, ad layer from catalog, etc." |
| 31 | + ] |
| 32 | + }, |
| 33 | + { |
| 34 | + "cell_type": "markdown", |
| 35 | + "id": "941c869f-4726-4363-ac71-95440a475386", |
| 36 | + "metadata": { |
| 37 | + "jp-MarkdownHeadingCollapsed": true |
| 38 | + }, |
| 39 | + "source": [ |
| 40 | + "## From geopythontutorials.com" |
25 | 41 | ] |
26 | 42 | }, |
27 | 43 | { |
|
47 | 63 | "id": "0b259e2b-0758-430d-ba4e-d48184395473", |
48 | 64 | "metadata": {}, |
49 | 65 | "source": [ |
50 | | - "## From geopythontutorials.com\n", |
51 | | - "\n", |
52 | 66 | "https://www.geopythontutorials.com/notebooks/xarray_zonal_stats.html?utm_source=chatgpt.com\n", |
53 | 67 | "\n", |
54 | 68 | "New dependencies\n", |
|
246 | 260 | { |
247 | 261 | "cell_type": "markdown", |
248 | 262 | "id": "8d63cc59-78cd-4639-9c96-f6ac3e0dd208", |
249 | | - "metadata": {}, |
| 263 | + "metadata": { |
| 264 | + "jp-MarkdownHeadingCollapsed": true |
| 265 | + }, |
250 | 266 | "source": [ |
251 | 267 | "## From Carl's class" |
252 | 268 | ] |
|
47625 | 47641 | "\n", |
47626 | 47642 | "https://espm-288.carlboettiger.info/tutorials/python/spatial-4.html" |
47627 | 47643 | ] |
| 47644 | + }, |
| 47645 | + { |
| 47646 | + "cell_type": "code", |
| 47647 | + "execution_count": null, |
| 47648 | + "id": "a169692a-2674-4c4e-ab88-50ba908083d2", |
| 47649 | + "metadata": {}, |
| 47650 | + "outputs": [], |
| 47651 | + "source": [] |
47628 | 47652 | } |
47629 | 47653 | ], |
47630 | 47654 | "metadata": { |
|
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