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Merged
mnfienen merged 1 commit into from
Sep 24, 2025
Merged

formatting geopandas for the html layout version #185

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22 changes: 20 additions & 2 deletions notebooks/part0_python_intro/09_a_Geopandas.ipynb
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Expand Up @@ -678,7 +678,8 @@
"id": "50525a00",
"metadata": {},
"source": [
"### How about some spatial joins?"
"## How about some spatial joins?\n",
"***"
]
},
{
Expand Down Expand Up @@ -824,6 +825,7 @@
"metadata": {},
"source": [
"## TEST YOUR SKILLS #1\n",
"***\n",
"Using the `bounds` geodataframe you just made, write a function to visualize predicate behaviors.\n",
"- your function should accept a left geodataframe, a right geodataframe, and a string for the predicate\n",
"- your function should plot:\n",
Expand Down Expand Up @@ -994,7 +996,11 @@
"id": "e63a1ab3",
"metadata": {},
"source": [
"### As we've seen, spatial joins are powerful, but they really only gather data from multiple collections. What if we want to actually calculate the amount of overlap among shapes? Or create new shapes based on intersection or not intersection of shapes? [`overlay`](https://geopandas.org/en/stable/docs/user_guide/set_operations.html?highlight=overlay) does these things."
"## Overlays\n",
"***\n",
"### As we've seen, spatial joins are powerful, but they really only gather data from multiple collections. What if we want to actually calculate the amount of overlap among shapes? Or create new shapes based on intersection or not intersection of shapes?\n",
"\n",
"### [overlay](https://geopandas.org/en/stable/docs/user_guide/set_operations.html?highlight=overlay) does these things."
]
},
{
Expand All @@ -1016,6 +1022,17 @@
"inters.plot()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3b39f0f7-2e68-4840-b8fc-d53e3a3d1b3f",
"metadata": {},
"outputs": [],
"source": [
"inters = bounds.overlay(isthmus, how='intersection')\n",
"inters.plot()"
]
},
{
"cell_type": "code",
"execution_count": null,
Expand Down Expand Up @@ -1105,6 +1122,7 @@
"metadata": {},
"source": [
"## TEST YOUR SKILLS _OPTIONAL_\n",
"***\n",
"We have an Excel file that contains a crosswalk between SPECIES number as provided and species name. Can we bring that into our dataset and evaluate some conclusions about tree species by neighborhood?\n",
"- start with the `trees_with_hoods` GeoDataFrame\n",
"- load up and join the data from datapath / 'Madison_Tree_Species_Lookup.xlsx'\n",
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12 changes: 0 additions & 12 deletions notebooks/part0_python_intro/10a_Rasterio_intro.ipynb
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Expand Up @@ -815,18 +815,6 @@
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.2"
}
},
"nbformat": 4,
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