feat: Add an example for Geohash Layer #1242
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Check failure on line 1 in examples/geohash-layer.ipynb
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| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
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Member
There was a problem hiding this comment. Similar to other examples like https://github.com/developmentseed/lonboard/blob/main/examples/data-filter-extension.ipynb, could you create the example notebook with Assuming you have Then you can copy in the markdown instructional cell: 
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| "id": "geohash-intro", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "This example aggregates public NYC 311 requests into geohash cells and renders their density with `GeohashLayer`. Brighter cells received fewer reports; darker red cells received more.\n", | ||
| "\n", | ||
| "The data comes from [NYC Open Data's 311 Service Requests dataset](https://data.cityofnewyork.us/Social-Services/311-Service-Requests-from-2010-to-Present/erm2-nwe9/about_data)." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "geohash-dependencies", | ||
| "metadata": { | ||
| "jupyter": { | ||
| "source_hidden": true | ||
| } | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "# /// script\n", | ||
| "# requires-python = \">=3.12\"\n", | ||
| "# dependencies = [\n", | ||
| "# \"geohash2\",\n", | ||
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Member
There was a problem hiding this comment. geohash2 is 10 years old: https://github.com/dbarthe/geohash/ Can we use another more modern geohash library like https://pypi.org/project/pygeohash/? |
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| "# \"lonboard\",\n", | ||
| "# \"matplotlib\",\n", | ||
| "# \"palettable\",\n", | ||
| "# \"pandas\",\n", | ||
| "# \"pyarrow\",\n", | ||
| "# \"requests\",\n", | ||
| "# ]\n", | ||
| "# ///" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 6, | ||
| "id": "geohash-imports", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import geohash2\n", | ||
| "import pandas as pd\n", | ||
| "import requests\n", | ||
| "from matplotlib.colors import LogNorm\n", | ||
| "from palettable.colorbrewer.sequential import YlOrRd_9\n", | ||
| "\n", | ||
| "from lonboard import GeohashLayer, Map\n", | ||
| "from lonboard.basemap import CartoStyle, MaplibreBasemap\n", | ||
| "from lonboard.colormap import apply_continuous_cmap\n", | ||
| "from lonboard.view_state import MapViewState" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "geohash-download-note", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Download and aggregate the data" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 7, | ||
| "id": "geohash-aggregate", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/html": [ | ||
| "<div>\n", | ||
| "<style scoped>\n", | ||
| " .dataframe tbody tr th:only-of-type {\n", | ||
| " vertical-align: middle;\n", | ||
| " }\n", | ||
| "\n", | ||
| " .dataframe tbody tr th {\n", | ||
| " vertical-align: top;\n", | ||
| " }\n", | ||
| "\n", | ||
| " .dataframe thead th {\n", | ||
| " text-align: right;\n", | ||
| " }\n", | ||
| "</style>\n", | ||
| "<table border=\"1\" class=\"dataframe\">\n", | ||
| " <thead>\n", | ||
| " <tr style=\"text-align: right;\">\n", | ||
| " <th></th>\n", | ||
| " <th>geohash</th>\n", | ||
| " <th>request_count</th>\n", | ||
| " <th>primary_borough</th>\n", | ||
| " <th>top_complaint</th>\n", | ||
| " <th>top_complaint_count</th>\n", | ||
| " </tr>\n", | ||
| " </thead>\n", | ||
| " <tbody>\n", | ||
| " <tr>\n", | ||
| " <th>0</th>\n", | ||
| " <td>dr5nqr</td>\n", | ||
| " <td>1</td>\n", | ||
| " <td>STATEN ISLAND</td>\n", | ||
| " <td>Noise - Commercial</td>\n", | ||
| " <td>1</td>\n", | ||
| " </tr>\n", | ||
| " <tr>\n", | ||
| " <th>1</th>\n", | ||
| " <td>dr5nqw</td>\n", | ||
| " <td>1</td>\n", | ||
| " <td>STATEN ISLAND</td>\n", | ||
| " <td>Noise - Residential</td>\n", | ||
| " <td>1</td>\n", | ||
| " </tr>\n", | ||
| " <tr>\n", | ||
| " <th>2</th>\n", | ||
| " <td>dr5nqx</td>\n", | ||
| " <td>1</td>\n", | ||
| " <td>STATEN ISLAND</td>\n", | ||
| " <td>Illegal Parking</td>\n", | ||
| " <td>1</td>\n", | ||
| " </tr>\n", | ||
| " <tr>\n", | ||
| " <th>3</th>\n", | ||
| " <td>dr5nqz</td>\n", | ||
| " <td>1</td>\n", | ||
| " <td>STATEN ISLAND</td>\n", | ||
| " <td>Damaged Tree</td>\n", | ||
| " <td>1</td>\n", | ||
| " </tr>\n", | ||
| " <tr>\n", | ||
| " <th>4</th>\n", | ||
| " <td>dr5nw9</td>\n", | ||
| " <td>1</td>\n", | ||
| " <td>STATEN ISLAND</td>\n", | ||
| " <td>Building/Use</td>\n", | ||
| " <td>1</td>\n", | ||
| " </tr>\n", | ||
| " </tbody>\n", | ||
| "</table>\n", | ||
| "</div>" | ||
| ], | ||
| "text/plain": [ | ||
| " geohash request_count primary_borough top_complaint \\\n", | ||
| "0 dr5nqr 1 STATEN ISLAND Noise - Commercial \n", | ||
| "1 dr5nqw 1 STATEN ISLAND Noise - Residential \n", | ||
| "2 dr5nqx 1 STATEN ISLAND Illegal Parking \n", | ||
| "3 dr5nqz 1 STATEN ISLAND Damaged Tree \n", | ||
| "4 dr5nw9 1 STATEN ISLAND Building/Use \n", | ||
| "\n", | ||
| " top_complaint_count \n", | ||
| "0 1 \n", | ||
| "1 1 \n", | ||
| "2 1 \n", | ||
| "3 1 \n", | ||
| "4 1 " | ||
| ] | ||
| }, | ||
| "execution_count": 7, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "API_URL = \"https://data.cityofnewyork.us/resource/erm2-nwe9.json\"\n", | ||
| "PARAMS = {\n", | ||
| " \"$select\": \"latitude, longitude, complaint_type, borough\",\n", | ||
| " \"$where\": (\n", | ||
| " \"created_date >= '2025-01-01T00:00:00' AND \"\n", | ||
| " \"created_date < '2025-01-08T00:00:00' AND \"\n", | ||
| " \"latitude IS NOT NULL AND longitude IS NOT NULL\"\n", | ||
| " ),\n", | ||
| " \"$order\": \"created_date ASC\",\n", | ||
| " \"$limit\": 10_000,\n", | ||
| "}\n", | ||
| "\n", | ||
| "try:\n", | ||
| " response = requests.get(API_URL, params=PARAMS, timeout=30)\n", | ||
| " response.raise_for_status()\n", | ||
| "except requests.RequestException as exc:\n", | ||
| " raise RuntimeError(\"Unable to download NYC 311 data. Please try again later.\") from exc\n", | ||
| "\n", | ||
| "requests_df = pd.DataFrame(response.json())\n", | ||
| "if requests_df.empty:\n", | ||
| " raise RuntimeError(\"The NYC 311 query returned no requests.\")\n", | ||
| "\n", | ||
| "requests_df = requests_df.astype({\"latitude\": \"float64\", \"longitude\": \"float64\"})\n", | ||
| "requests_df[\"geohash\"] = [\n", | ||
| " geohash2.encode(latitude, longitude, precision=6)\n", | ||
| " for latitude, longitude in zip(requests_df[\"latitude\"], requests_df[\"longitude\"], strict=True)\n", | ||
| "]\n", | ||
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Comment on lines
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Member
There was a problem hiding this comment. It would be nice if the geohash library provided a vectorized API, so that we could nudge people towards a faster approach. But this is fine. |
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| "def aggregate_cell_data(df):\n", | ||
| " top_complaint = df[\"complaint_type\"].mode()[0] if not df[\"complaint_type\"].empty else \"N/A\"\n", | ||
| " return pd.Series({\n", | ||
| " \"request_count\": len(df),\n", | ||
| " \"primary_borough\": df[\"borough\"].mode()[0] if \"borough\" in df.columns else \"Unspecified\",\n", | ||
| " \"top_complaint\": top_complaint,\n", | ||
| " \"top_complaint_count\": (df[\"complaint_type\"] == top_complaint).sum(),\n", | ||
| " })\n", | ||
| "\n", | ||
| "cells = requests_df.groupby(\"geohash\", as_index=False).apply(aggregate_cell_data)\n", | ||
| "cells.head()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "geohash-render-note", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Explore neighborhood-scale demand\n", | ||
| "\n", | ||
| "Hover over a cell to inspect its geohash and request count." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "id": "geohash-render", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "application/vnd.jupyter.widget-view+json": { | ||
| "model_id": "bc8ae637553b4e1b87cf53bd3ef192e6", | ||
| "version_major": 2, | ||
| "version_minor": 0 | ||
| }, | ||
| "text/plain": [ | ||
| "VBox(children=(<lonboard._map.Map object at 0x118b095b0>, VBox(children=(ErrorOutput(), ErrorOutput(), ErrorOu…" | ||
| ] | ||
| }, | ||
| "execution_count": 8, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "color_scale = LogNorm(\n", | ||
| " vmin=cells[\"request_count\"].min(),\n", | ||
| " vmax=cells[\"request_count\"].max(),\n", | ||
| ")\n", | ||
| "\n", | ||
| "layer = GeohashLayer.from_pandas(\n", | ||
| " cells,\n", | ||
| " get_geohash=cells[\"geohash\"],\n", | ||
| " get_fill_color=apply_continuous_cmap(\n", | ||
| " color_scale(cells[\"request_count\"]), YlOrRd_9, alpha=0.88\n", | ||
| " ),\n", | ||
| " get_line_color=[35, 12, 8, 160],\n", | ||
| " line_width_min_pixels=0.75,\n", | ||
| " pickable=True,\n", | ||
| ")\n", | ||
| "\n", | ||
| "map_ = Map(\n", | ||
| " layer,\n", | ||
| " basemap=MaplibreBasemap(style=CartoStyle.DarkMatter),\n", | ||
| " view_state=MapViewState(longitude=-73.96, latitude=40.73, zoom=10),\n", | ||
| " height=700,\n", | ||
| " show_tooltip=True,\n", | ||
| " show_side_panel=False,\n", | ||
| " picking_radius=5,\n", | ||
| ")\n", | ||
| "map_" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "lonboard (3.12.x)", | ||
| "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": "3.12.13" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } | ||
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CI is failing on some formatting and linting on this notebook