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brendancolbrendancol
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tested and cleared all notebooks
1 parent 4129ea2 commit 5f35823

13 files changed

Lines changed: 745 additions & 424 deletions

‎examples/Pathfinding_Austin_Road_Network.ipynb‎

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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:31.469085Z",
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"iopub.status.busy": "2026-01-23T19:13:31.468977Z",
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"iopub.status.idle": "2026-01-23T19:13:32.421379Z",
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"shell.execute_reply": "2026-01-23T19:13:32.420650Z"
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}
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},
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"outputs": [],
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"source": [
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"import datashader as ds\n",
@@ -62,12 +69,17 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:32.423409Z",
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"iopub.status.busy": "2026-01-23T19:13:32.422938Z",
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"iopub.status.idle": "2026-01-23T19:13:34.034515Z",
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"shell.execute_reply": "2026-01-23T19:13:34.033712Z"
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}
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},
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"outputs": [],
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"source": [
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"streets = geopandas.read_file(\n",
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" \"data/geo_export_9c395dda-0b29-41ec-89b4-a51a898f7104.shp\"\n",
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")\n",
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"streets = geopandas.read_file(\"../xrspatial-examples/data/geo_export_9c395dda-0b29-41ec-89b4-a51a898f7104.shp\")\n",
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"streets = streets.to_crs(\"EPSG:4326\")\n",
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"streets = streets.explode(\"geometry\").reset_index(drop=True)\n",
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"streets_spd = spatialpandas.GeoDataFrame(streets, geometry=\"geometry\")"
@@ -92,7 +104,14 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:34.036027Z",
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"iopub.status.busy": "2026-01-23T19:13:34.035787Z",
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"iopub.status.idle": "2026-01-23T19:13:34.054300Z",
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"shell.execute_reply": "2026-01-23T19:13:34.053635Z"
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}
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},
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"outputs": [],
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"source": [
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"xmin, ymin, xmax, ymax = (\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:34.072052Z",
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"iopub.status.busy": "2026-01-23T19:13:34.071884Z",
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"iopub.status.idle": "2026-01-23T19:13:36.136717Z",
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"shell.execute_reply": "2026-01-23T19:13:36.136054Z"
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}
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},
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"outputs": [],
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"source": [
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"H, W = 600, 800\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:36.137998Z",
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"iopub.status.busy": "2026-01-23T19:13:36.137876Z",
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"iopub.status.idle": "2026-01-23T19:13:37.131601Z",
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"shell.execute_reply": "2026-01-23T19:13:37.131064Z"
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}
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},
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"outputs": [],
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"source": [
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"# find the path from start to goal,\n",
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"path_shaded = dynspread(shade(path_agg, cmap=[\"green\"]), threshold=1, max_px=1)\n",
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"set_background(stack(street_shaded, path_shaded, start_shaded, goal_shaded), \"black\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "python"
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.14.2"
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}
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},
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"nbformat": 4,

‎examples/pharmacy-deserts.ipynb‎

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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:12:53.231018Z",
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"iopub.status.busy": "2026-01-23T19:12:53.230906Z",
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"iopub.status.idle": "2026-01-23T19:12:54.153805Z",
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}
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},
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"outputs": [],
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"source": [
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"import datashader as ds\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:12:54.155318Z",
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"iopub.status.busy": "2026-01-23T19:12:54.155027Z",
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"iopub.status.idle": "2026-01-23T19:12:54.308338Z",
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"shell.execute_reply": "2026-01-23T19:12:54.307765Z"
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}
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},
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"outputs": [],
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"source": [
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"# Load Pharmacies and add out x, y fields based on CalcLocation\n",
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"pharmacy_df = pd.read_csv(\"./xrspatial-examples/data/facilities.csv\")\n",
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"pharmacy_df = pd.read_csv(\"../xrspatial-examples/data/facilities.csv\")\n",
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"coords = pharmacy_df[\"CalcLocation\"].str.split(\",\", expand=True)\n",
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"pharmacy_df[\"y\"] = np.array(coords[0], dtype=\"float64\")\n",
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"pharmacy_df[\"x\"] = np.array(coords[1], dtype=\"float64\")\n",
@@ -82,7 +96,14 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:12:54.325729Z",
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"iopub.status.busy": "2026-01-23T19:12:54.325568Z",
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"iopub.status.idle": "2026-01-23T19:13:07.768006Z",
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}
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},
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"outputs": [],
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"source": [
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"# Load Census Block Groups and Calculate Percent over 65 years-old\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:07.769550Z",
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"iopub.status.busy": "2026-01-23T19:13:07.769287Z",
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"iopub.status.idle": "2026-01-23T19:13:08.942658Z",
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},
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"outputs": [],
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"source": [
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"# Load Census County and Calculate Percent over 65 years-old\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:08.944030Z",
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"iopub.status.busy": "2026-01-23T19:13:08.943925Z",
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"iopub.status.idle": "2026-01-23T19:13:12.446986Z",
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"shell.execute_reply": "2026-01-23T19:13:12.446334Z"
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}
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},
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"outputs": [],
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"source": [
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"x_range = (-124.848974, -66.885444)\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:12.448188Z",
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"iopub.status.busy": "2026-01-23T19:13:12.448083Z",
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"iopub.status.idle": "2026-01-23T19:13:15.042708Z",
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"shell.execute_reply": "2026-01-23T19:13:15.042222Z"
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}
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},
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"outputs": [],
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"source": [
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"pharmacy_raster = cvs.points(pharmacy_df, \"x\", \"y\")\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:15.044150Z",
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"iopub.status.busy": "2026-01-23T19:13:15.044043Z",
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"iopub.status.idle": "2026-01-23T19:13:23.087968Z",
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"shell.execute_reply": "2026-01-23T19:13:23.087515Z"
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}
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},
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"age_raster = cvs.polygons(\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:23.090108Z",
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"iopub.status.busy": "2026-01-23T19:13:23.090002Z",
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"iopub.status.idle": "2026-01-23T19:13:23.469051Z",
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"shell.execute_reply": "2026-01-23T19:13:23.468423Z"
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}
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},
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"outputs": [],
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"source": [
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"pharmacy_deserts = binary(proximity_classifed, [3])\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:23.470503Z",
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"iopub.status.busy": "2026-01-23T19:13:23.470395Z",
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"iopub.status.idle": "2026-01-23T19:13:25.284662Z",
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},
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"from datashader.colors import Set1\n",
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{
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:25.286041Z",
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"iopub.status.busy": "2026-01-23T19:13:25.285949Z",
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"iopub.status.idle": "2026-01-23T19:13:25.470420Z",
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"shell.execute_reply": "2026-01-23T19:13:25.469864Z"
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},
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"source": [
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"from xrspatial import zonal_stats\n",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:25.471583Z",
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"iopub.status.busy": "2026-01-23T19:13:25.471478Z",
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"iopub.status.idle": "2026-01-23T19:13:25.593109Z",
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"shell.execute_reply": "2026-01-23T19:13:25.592471Z"
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}
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},
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"cols = [\"pharmacy_desert_mean\", \"NAME\", \"STATE_FIPS\", \"geometry\"]\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:25.594252Z",
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"iopub.status.busy": "2026-01-23T19:13:25.594151Z",
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"iopub.status.idle": "2026-01-23T19:13:28.338669Z",
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"shell.execute_reply": "2026-01-23T19:13:28.337777Z"
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},
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"source": [
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"from xrspatial import hillshade\n",
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{
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-23T19:13:28.340196Z",
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"iopub.status.busy": "2026-01-23T19:13:28.340077Z",
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"iopub.status.idle": "2026-01-23T19:13:28.571855Z",
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},
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"img = stack(\n",
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")\n",
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"set_background(img, \"black\")"
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},
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"cell_type": "code",
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"execution_count": null,
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"name": "python"
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.14.2"
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}
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},
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"nbformat": 4,

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