Docs refactor work: Add Earth Engine Python quickstart

PiperOrigin-RevId: 665453734

guides/linked/generated/quickstart_python.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Get started with Earth Engine for Python\n",
+    "\n",
+    "Project: /earth-engine/_project.yaml Book: /earth-engine/_book.yaml"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#@title Copyright 2024 The Earth Engine Community Authors { display-mode: \"form\" }\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "# https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This quickstart will give you an interactive introduction to visualizing and\n",
+    "analyzing geospatial data with the Earth Engine Python interface.\n",
+    "\n",
+    "## Before you begin\n",
+    "\n",
+    "[Register or create](https://code.earthengine.google.com/register) a Google Cloud Project. You'll be prompted to complete the following steps: \n",
+    "\n",
+    "  * Select the project's purpose: commercial or noncommercial.\n",
+    "  * If the purpose is noncommercial, select a project type.\n",
+    "  * Create a new Google Cloud project or select an existing project.\n",
+    "  * If the purpose is commercial, verify or set up billing for your project.\n",
+    "  * Confirm your project information.  \n",
+    "\n",
+    "**Note:** If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can [delete the project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects), removing all resources owned by the project. \n",
+    "\n",
+    "## Notebook setup\n",
+    "\n",
+    "**1.** Import the Earth Engine and geemap libraries."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ee\n",
+    "import geemap.core as geemap"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**2.** Authenticate and initialize the Earth Engine service. Follow the\n",
+    "resulting prompts to complete authentication. Be sure to replace PROJECT_ID\n",
+    "with the name of the project you set up for this quickstart."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ee.Authenticate()\n",
+    "ee.Initialize(project='PROJECT_ID')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Add raster data to a map\n",
+    "\n",
+    "**1.** Load climate data for a given period and display its metadata."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "jan_2023_climate = (\n",
+    "    ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY_AGGR')\n",
+    "    .filterDate('2023-01', '2023-02')\n",
+    "    .first()\n",
+    ")\n",
+    "jan_2023_climate"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**2.** Instantiate a map object and add the temperature band as a layer with\n",
+    "specific visualization properties. Display the map."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m = geemap.Map(center=[30, 0], zoom=2)\n",
+    "\n",
+    "vis_params = {\n",
+    "    'bands': ['temperature_2m'],\n",
+    "    'min': 229,\n",
+    "    'max': 304,\n",
+    "    'palette': 'inferno',\n",
+    "}\n",
+    "m.add_layer(jan_2023_climate, vis_params, 'Temperature (K)')\n",
+    "m"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Add vector data to a map\n",
+    "\n",
+    "**1.** Create a vector data object with points for three cities."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cities = ee.FeatureCollection([\n",
+    "    ee.Feature(ee.Geometry.Point(10.75, 59.91), {'city': 'Oslo'}),\n",
+    "    ee.Feature(ee.Geometry.Point(-118.24, 34.05), {'city': 'Los Angeles'}),\n",
+    "    ee.Feature(ee.Geometry.Point(103.83, 1.33), {'city': 'Singapore'}),\n",
+    "])\n",
+    "cities"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**2.** Add the city locations to the map and redisplay it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "m.add_layer(cities, name='Cities')\n",
+    "m"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Extract and chart data\n",
+    "\n",
+    "**1.** Import the Altair charting library."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install -q --upgrade altair\n",
+    "import altair as alt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**2.** Extract the climate data for the three cities as a pandas DataFrame."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "city_climates = jan_2023_climate.reduceRegions(cities, ee.Reducer.first())\n",
+    "\n",
+    "city_climates_dataframe = ee.data.computeFeatures(\n",
+    "    {'expression': city_climates, 'fileFormat': 'PANDAS_DATAFRAME'}\n",
+    ")\n",
+    "city_climates_dataframe"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**3.** Plot the temperature for the cities as a bar chart."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "alt.Chart(city_climates_dataframe).mark_bar(size=100).encode(\n",
+    "    alt.X('city:N', sort='y', axis=alt.Axis(labelAngle=0), title='City'),\n",
+    "    alt.Y('temperature_2m:Q', title='Temperature (K)'),\n",
+    "    tooltip=[\n",
+    "        alt.Tooltip('city:N', title='City'),\n",
+    "        alt.Tooltip('temperature_2m:Q', title='Temperature (K)'),\n",
+    "    ],\n",
+    ").properties(title='January 2023 temperature for selected cities', width=500)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## What's next\n",
+    "\n",
+    "  * Learn about analyzing data with Earth Engine's [objects and methods](https://developers.google.com/earth-engine/guides/objects_methods_overview).\n",
+    "  * Learn about Earth Engine's [processing environments](https://developers.google.com/earth-engine/guides/processing_environments).\n",
+    "  * Learn about Earth Engine's [machine learning capabilities](https://developers.google.com/earth-engine/guides/machine-learning).\n",
+    "  * Learn how to [export your computation results to BigQuery](https://developers.google.com/earth-engine/guides/exporting_to_bigquery)."
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "name": "Get started with Earth Engine for Python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

samples/python/guides/quickstart.py

@@ -0,0 +1,86 @@
+# Copyright 2024 The Google Earth Engine Community Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Google Earth Engine Developer's Guide examples for 'Python quickstart'."""
+
+# [START earthengine__quickstart__imports]
+import ee
+import geemap.core as geemap
+# [END earthengine__quickstart__imports]
+
+# [START earthengine__quickstart__auth]
+ee.Authenticate()
+ee.Initialize(project='PROJECT_ID')
+# [END earthengine__quickstart__auth]
+
+# [START earthengine__quickstart__image_load]
+jan_2023_climate = (
+    ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY_AGGR')
+    .filterDate('2023-01', '2023-02')
+    .first()
+)
+jan_2023_climate
+# [END earthengine__quickstart__image_load]
+
+# [START earthengine__quickstart__image_display]
+m = geemap.Map(center=[30, 0], zoom=2)
+
+vis_params = {
+    'bands': ['temperature_2m'],
+    'min': 229,
+    'max': 304,
+    'palette': 'inferno',
+}
+m.add_layer(jan_2023_climate, vis_params, 'Temperature (K)')
+m
+# [END earthengine__quickstart__image_display]
+
+# [START earthengine__quickstart__fc_create]
+cities = ee.FeatureCollection([
+    ee.Feature(ee.Geometry.Point(10.75, 59.91), {'city': 'Oslo'}),
+    ee.Feature(ee.Geometry.Point(-118.24, 34.05), {'city': 'Los Angeles'}),
+    ee.Feature(ee.Geometry.Point(103.83, 1.33), {'city': 'Singapore'}),
+])
+cities
+# [END earthengine__quickstart__fc_create]
+
+# [START earthengine__quickstart__fc_display]
+m.add_layer(cities, name='Cities')
+m
+# [END earthengine__quickstart__fc_display]
+
+# [START earthengine__quickstart__import_altair]
+%pip install -q --upgrade altair
+import altair as alt
+# [END earthengine__quickstart__import_altair]
+
+# [START earthengine__quickstart__extract_data]
+city_climates = jan_2023_climate.reduceRegions(cities, ee.Reducer.first())
+
+city_climates_dataframe = ee.data.computeFeatures(
+    {'expression': city_climates, 'fileFormat': 'PANDAS_DATAFRAME'}
+)
+city_climates_dataframe
+# [END earthengine__quickstart__extract_data]
+
+# [START earthengine__quickstart__plot_data]
+alt.Chart(city_climates_dataframe).mark_bar(size=100).encode(
+    alt.X('city:N', sort='y', axis=alt.Axis(labelAngle=0), title='City'),
+    alt.Y('temperature_2m:Q', title='Temperature (K)'),
+    tooltip=[
+        alt.Tooltip('city:N', title='City'),
+        alt.Tooltip('temperature_2m:Q', title='Temperature (K)'),
+    ],
+).properties(title='January 2023 temperature for selected cities', width=500)
+# [END earthengine__quickstart__plot_data]