diff --git "a/sandbox.ipynb" "b/sandbox.ipynb" new file mode 100644--- /dev/null +++ "b/sandbox.ipynb" @@ -0,0 +1,2142 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 145, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import ee\n", + "import geemap\n", + "import geopandas as gpd\n", + "from shapely.ops import transform\n", + "ee.Initialize()" + ] + }, + { + "cell_type": "code", + "execution_count": 146, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "gdf = gpd.read_file(\"/home/patel_zeel/Mean_NDVI/golvada he 10 2023-24.kml\")\n", + "gdf = gdf.to_crs(epsg=4326)\n", + "def poly_3d_to_2d(shape):\n", + " if shape.has_z:\n", + " return transform(lambda x, y, z: (x, y), shape)\n", + " else:\n", + " return shape\n", + "gdf['geometry'] = gdf['geometry'].apply(poly_3d_to_2d)\n", + "gdf = gdf.to_crs(epsg=4326)\n", + "first_item = gdf.iloc[0:1]\n", + "ee_object = geemap.gdf_to_ee(first_item)" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of images in the collection: 2\n" + ] + } + ], + "source": [ + "dataset = ee.ImageCollection('LANDSAT/LC08/C02/T1_TOA').filterBounds(ee_object).filterDate('2023-01-01', '2023-01-31')\n", + "true_color_432 = dataset.select(['B4', 'B3', 'B2'])\n", + "print(\"Number of images in the collection: \", true_color_432.size().getInfo())" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Image ID: LC08_148044_20230115\n", + "New Image ID: LC08_148044_20230115\n" + ] + } + ], + "source": [ + "# pick the second image in the collection\n", + "image = dataset.toList(true_color_432.size()).get(1)\n", + "image = ee.Image(image)\n", + "# print image id\n", + "print(\"Image ID: \", image.id().getInfo())\n", + "# replace id with \"anonymous\"\n", + "image = image.set('id', 'anonymous')\n", + "# print new image id\n", + "print(\"New Image ID: \", image.id().getInfo())" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Computing statistics ...\n", + "Generating URL ...\n", + "Downloading data from https://earthengine.googleapis.com/v1/projects/815228341823/tables/8a81a210a87d3b3a27187b606616f13c-f5c9d2fc785b6f388b63270382c578e4:getFeatures\n", + "Please wait ...\n", + "Data downloaded to /home/patel_zeel/Mean_NDVI/zonal_stats.csv\n" + ] + } + ], + "source": [ + "features = geemap.zonal_stats(dataset.qualityMosaic(\"B4\").select(\"B4\"), ee_object, statistics_type='mean', scale=10)" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'20210125'" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import re\n", + "\n", + "re.findall(r\"LC08_\\d+_(\\d+)_NDVI\", \"LC08_148043_20210125_NDVI\")[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
<ee.image.Image object at 0x7fd10c62b820>
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset.qualityMosaic('NDVI')" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "'2023-01-01'" + ] + }, + "execution_count": 116, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "start = '2023-01-01'\n", + "start.format(\"YYYY-MM\")" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['2023-01-01', '2023-02-01', '2023-03-01', '2023-04-01', '2023-05-01', '2023-06-01', '2023-07-01', '2023-08-01', '2023-09-01', '2023-10-01', '2023-11-01', '2023-12-01', '2024-01-01']\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "start_date = '2023-01'\n", + "end_date = '2024-01'\n", + "\n", + "# get 1st day of each month\n", + "dates = pd.date_range(start_date, end_date, freq='MS').strftime(\"%Y-%m-%d\").tolist()\n", + "print(dates)" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[0;31mSignature:\u001b[0m\n", + "\u001b[0mgeemap\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzonal_stats\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0min_value_raster\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0min_zone_vector\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mout_file_path\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mstat_type\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'MEAN'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mscale\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mcrs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mtile_scale\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1.0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mreturn_fc\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mverbose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m300\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mproxies\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mSource:\u001b[0m \n", + "\u001b[0;32mdef\u001b[0m \u001b[0mzonal_stats\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0min_value_raster\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0min_zone_vector\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mout_file_path\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mstat_type\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"MEAN\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mscale\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mcrs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mtile_scale\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1.0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mreturn_fc\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mverbose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m300\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mproxies\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m\"\"\"Summarizes the values of a raster within the zones of another dataset and exports the results as a csv, shp, json, kml, or kmz.\u001b[0m\n", + "\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m Args:\u001b[0m\n", + "\u001b[0;34m in_value_raster (object): An ee.Image or ee.ImageCollection that contains the values on which to calculate a statistic.\u001b[0m\n", + "\u001b[0;34m in_zone_vector (object): An ee.FeatureCollection that defines the zones.\u001b[0m\n", + "\u001b[0;34m out_file_path (str): Output file path that will contain the summary of the values in each zone. The file type can be: csv, shp, json, kml, kmz\u001b[0m\n", + "\u001b[0;34m stat_type (str, optional): Statistical type to be calculated. Defaults to 'MEAN'. For 'HIST', you can provide three parameters: max_buckets, min_bucket_width, and max_raw. For 'FIXED_HIST', you must provide three parameters: hist_min, hist_max, and hist_steps.\u001b[0m\n", + "\u001b[0;34m scale (float, optional): A nominal scale in meters of the projection to work in. Defaults to None.\u001b[0m\n", + "\u001b[0;34m crs (str, optional): The projection to work in. If unspecified, the projection of the image's first band is used. If specified in addition to scale, rescaled to the specified scale. Defaults to None.\u001b[0m\n", + "\u001b[0;34m tile_scale (float, optional): A scaling factor used to reduce aggregation tile size; using a larger tileScale (e.g. 2 or 4) may enable computations that run out of memory with the default. Defaults to 1.0.\u001b[0m\n", + "\u001b[0;34m verbose (bool, optional): Whether to print descriptive text when the programming is running. Default to True.\u001b[0m\n", + "\u001b[0;34m return_fc (bool, optional): Whether to return the results as an ee.FeatureCollection. Defaults to False.\u001b[0m\n", + "\u001b[0;34m timeout (int, optional): Timeout in seconds. Default to 300.\u001b[0m\n", + "\u001b[0;34m proxies (dict, optional): A dictionary of proxy servers to use for the request. Default to None.\u001b[0m\n", + "\u001b[0;34m \"\"\"\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0min_value_raster\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mee\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mImageCollection\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0min_value_raster\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0min_value_raster\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtoBands\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0min_value_raster\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mee\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mImage\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"The input raster must be an ee.Image.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0min_zone_vector\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mee\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mFeatureCollection\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"The input zone data must be an ee.FeatureCollection.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mout_file_path\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mout_file_path\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetcwd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"zonal_stats.csv\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m\"statistics_type\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mstat_type\u001b[0m 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histogram\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;31m# The maximum number of buckets to use when building a histogram; will be rounded up to a power of 2.\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mmax_buckets\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;31m# The minimum histogram bucket width, or null to allow any power of 2.\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mmin_bucket_width\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;31m# The number of values to accumulate before building the initial histogram.\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mmax_raw\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mhist_min\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1.0\u001b[0m \u001b[0;31m# The lower (inclusive) bound of the first bucket.\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mhist_max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m100.0\u001b[0m \u001b[0;31m# The upper (exclusive) bound of the last bucket.\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mhist_steps\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m10\u001b[0m \u001b[0;31m# The number of buckets to use.\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;34m\"max_buckets\"\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mmax_buckets\u001b[0m \u001b[0;34m=\u001b[0m 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parameters: hist_min, hist_max, and hist_steps.\"\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mallowed_statistics\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m\"COUNT\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mee\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mReducer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcount\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m\"MEAN\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mee\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mReducer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m\"MEAN_UNWEIGHTED\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mee\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mReducer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munweighted\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m\"MAXIMUM\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mee\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mReducer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m\"MEDIAN\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mee\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mReducer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmedian\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m 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\u001b[0min_value_raster\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreduceRegions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mcollection\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0min_zone_vector\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mreducer\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mreducer\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mscale\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mscale\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mcrs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcrs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mtileScale\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtile_scale\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mif\u001b[0m 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"\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mleft\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'DataFrame | Series'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mright\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'DataFrame | Series'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mhow\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'MergeHow'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'inner'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mon\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'IndexLabel | None'\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mleft_on\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m'IndexLabel | None'\u001b[0m \u001b[0;34m=\u001b[0m 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"Merge DataFrame or named Series objects with a database-style join.\n", + "\n", + "A named Series object is treated as a DataFrame with a single named column.\n", + "\n", + "The join is done on columns or indexes. If joining columns on\n", + "columns, the DataFrame indexes *will be ignored*. Otherwise if joining indexes\n", + "on indexes or indexes on a column or columns, the index will be passed on.\n", + "When performing a cross merge, no column specifications to merge on are\n", + "allowed.\n", + "\n", + ".. warning::\n", + "\n", + " If both key columns contain rows where the key is a null value, those\n", + " rows will be matched against each other. This is different from usual SQL\n", + " join behaviour and can lead to unexpected results.\n", + "\n", + "Parameters\n", + "----------\n", + "left : DataFrame or named Series\n", + "right : DataFrame or named Series\n", + " Object to merge with.\n", + "how : {'left', 'right', 'outer', 'inner', 'cross'}, default 'inner'\n", + " Type of merge to be performed.\n", + "\n", + " * left: use only keys from left frame, similar to a SQL left outer join;\n", + " preserve key order.\n", + " * right: use only keys from right frame, similar to a SQL right outer join;\n", + " preserve key order.\n", + " * outer: use union of keys from both frames, similar to a SQL full outer\n", + " join; sort keys lexicographically.\n", + " * inner: use intersection of keys from both frames, similar to a SQL inner\n", + " join; preserve the order of the left keys.\n", + " * cross: creates the cartesian product from both frames, preserves the order\n", + " of the left keys.\n", + "\n", + " .. versionadded:: 1.2.0\n", + "\n", + "on : label or list\n", + " Column or index level names to join on. These must be found in both\n", + " DataFrames. If `on` is None and not merging on indexes then this defaults\n", + " to the intersection of the columns in both DataFrames.\n", + "left_on : label or list, or array-like\n", + " Column or index level names to join on in the left DataFrame. Can also\n", + " be an array or list of arrays of the length of the left DataFrame.\n", + " These arrays are treated as if they are columns.\n", + "right_on : label or list, or array-like\n", + " Column or index level names to join on in the right DataFrame. Can also\n", + " be an array or list of arrays of the length of the right DataFrame.\n", + " These arrays are treated as if they are columns.\n", + "left_index : bool, default False\n", + " Use the index from the left DataFrame as the join key(s). If it is a\n", + " MultiIndex, the number of keys in the other DataFrame (either the index\n", + " or a number of columns) must match the number of levels.\n", + "right_index : bool, default False\n", + " Use the index from the right DataFrame as the join key. Same caveats as\n", + " left_index.\n", + "sort : bool, default False\n", + " Sort the join keys lexicographically in the result DataFrame. If False,\n", + " the order of the join keys depends on the join type (how keyword).\n", + "suffixes : list-like, default is (\"_x\", \"_y\")\n", + " A length-2 sequence where each element is optionally a string\n", + " indicating the suffix to add to overlapping column names in\n", + " `left` and `right` respectively. Pass a value of `None` instead\n", + " of a string to indicate that the column name from `left` or\n", + " `right` should be left as-is, with no suffix. At least one of the\n", + " values must not be None.\n", + "copy : bool, default True\n", + " If False, avoid copy if possible.\n", + "indicator : bool or str, default False\n", + " If True, adds a column to the output DataFrame called \"_merge\" with\n", + " information on the source of each row. The column can be given a different\n", + " name by providing a string argument. The column will have a Categorical\n", + " type with the value of \"left_only\" for observations whose merge key only\n", + " appears in the left DataFrame, \"right_only\" for observations\n", + " whose merge key only appears in the right DataFrame, and \"both\"\n", + " if the observation's merge key is found in both DataFrames.\n", + "\n", + "validate : str, optional\n", + " If specified, checks if merge is of specified type.\n", + "\n", + " * \"one_to_one\" or \"1:1\": check if merge keys are unique in both\n", + " left and right datasets.\n", + " * \"one_to_many\" or \"1:m\": check if merge keys are unique in left\n", + " dataset.\n", + " * \"many_to_one\" or \"m:1\": check if merge keys are unique in right\n", + " dataset.\n", + " * \"many_to_many\" or \"m:m\": allowed, but does not result in checks.\n", + "\n", + "Returns\n", + "-------\n", + "DataFrame\n", + " A DataFrame of the two merged objects.\n", + "\n", + "See Also\n", + "--------\n", + "merge_ordered : Merge with optional filling/interpolation.\n", + "merge_asof : Merge on nearest keys.\n", + "DataFrame.join : Similar method using indices.\n", + "\n", + "Examples\n", + "--------\n", + ">>> df1 = pd.DataFrame({'lkey': ['foo', 'bar', 'baz', 'foo'],\n", + "... 'value': [1, 2, 3, 5]})\n", + ">>> df2 = pd.DataFrame({'rkey': ['foo', 'bar', 'baz', 'foo'],\n", + "... 'value': [5, 6, 7, 8]})\n", + ">>> df1\n", + " lkey value\n", + "0 foo 1\n", + "1 bar 2\n", + "2 baz 3\n", + "3 foo 5\n", + ">>> df2\n", + " rkey value\n", + "0 foo 5\n", + "1 bar 6\n", + "2 baz 7\n", + "3 foo 8\n", + "\n", + "Merge df1 and df2 on the lkey and rkey columns. The value columns have\n", + "the default suffixes, _x and _y, appended.\n", + "\n", + ">>> df1.merge(df2, left_on='lkey', right_on='rkey')\n", + " lkey value_x rkey value_y\n", + "0 foo 1 foo 5\n", + "1 foo 1 foo 8\n", + "2 foo 5 foo 5\n", + "3 foo 5 foo 8\n", + "4 bar 2 bar 6\n", + "5 baz 3 baz 7\n", + "\n", + "Merge DataFrames df1 and df2 with specified left and right suffixes\n", + "appended to any overlapping columns.\n", + "\n", + ">>> df1.merge(df2, left_on='lkey', right_on='rkey',\n", + "... suffixes=('_left', '_right'))\n", + " lkey value_left rkey value_right\n", + "0 foo 1 foo 5\n", + "1 foo 1 foo 8\n", + "2 foo 5 foo 5\n", + "3 foo 5 foo 8\n", + "4 bar 2 bar 6\n", + "5 baz 3 baz 7\n", + "\n", + "Merge DataFrames df1 and df2, but raise an exception if the DataFrames have\n", + "any overlapping columns.\n", + "\n", + ">>> df1.merge(df2, left_on='lkey', right_on='rkey', suffixes=(False, False))\n", + "Traceback (most recent call last):\n", + "...\n", + "ValueError: columns overlap but no suffix specified:\n", + " Index(['value'], dtype='object')\n", + "\n", + ">>> df1 = pd.DataFrame({'a': ['foo', 'bar'], 'b': [1, 2]})\n", + ">>> df2 = pd.DataFrame({'a': ['foo', 'baz'], 'c': [3, 4]})\n", + ">>> df1\n", + " a b\n", + "0 foo 1\n", + "1 bar 2\n", + ">>> df2\n", + " a c\n", + "0 foo 3\n", + "1 baz 4\n", + "\n", + ">>> df1.merge(df2, how='inner', on='a')\n", + " a b c\n", + "0 foo 1 3\n", + "\n", + ">>> df1.merge(df2, how='left', on='a')\n", + " a b c\n", + "0 foo 1 3.0\n", + "1 bar 2 NaN\n", + "\n", + ">>> df1 = pd.DataFrame({'left': ['foo', 'bar']})\n", + ">>> df2 = pd.DataFrame({'right': [7, 8]})\n", + ">>> df1\n", + " left\n", + "0 foo\n", + "1 bar\n", + ">>> df2\n", + " right\n", + "0 7\n", + "1 8\n", + "\n", + ">>> df1.merge(df2, how='cross')\n", + " left right\n", + "0 foo 7\n", + "1 foo 8\n", + "2 bar 7\n", + "3 bar 8\n", + "\u001b[0;31mSource:\u001b[0m \n", + "\u001b[0;34m@\u001b[0m\u001b[0mSubstitution\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"\\nleft : DataFrame or named Series\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;34m@\u001b[0m\u001b[0mAppender\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_merge_doc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindents\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;32mdef\u001b[0m \u001b[0mmerge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mleft\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mDataFrame\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0mSeries\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mright\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mDataFrame\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0mSeries\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mhow\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mMergeHow\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"inner\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mon\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mIndexLabel\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mleft_on\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mIndexLabel\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mright_on\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mIndexLabel\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mleft_index\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mbool\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mright_index\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mbool\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0msort\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mbool\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0msuffixes\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mSuffixes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"_x\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"_y\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mbool\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mindicator\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0mbool\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mvalidate\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mDataFrame\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mleft_df\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_validate_operand\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mleft\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mright_df\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_validate_operand\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mright\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mhow\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"cross\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0m_cross_merge\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mleft_df\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mright_df\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mon\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mon\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mleft_on\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mleft_on\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m 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\u001b[0mvalidate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalidate\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mop\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_MergeOperation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mleft_df\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mright_df\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mhow\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mhow\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mon\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mon\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mleft_on\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mleft_on\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mright_on\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mright_on\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mleft_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mleft_index\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mright_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mright_index\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0msort\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msort\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0msuffixes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msuffixes\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mindicator\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindicator\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0mvalidate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalidate\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n", + "\u001b[0;34m\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_result\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mFile:\u001b[0m /opt/anaconda3/envs/zeel_py310/lib/python3.10/site-packages/pandas/core/reshape/merge.py\n", + "\u001b[0;31mType:\u001b[0m function" + ] + } + ], + "source": [ + "pd.merge??" + ] + }, + { + "cell_type": "code", + "execution_count": 163, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " 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      • CLOUD_COVER_LAND:0.04
      • COLLECTION_CATEGORY:T1
      • COLLECTION_NUMBER:2
      • DATA_SOURCE_ELEVATION:GLS2000
      • DATA_SOURCE_TIRS_STRAY_LIGHT_CORRECTION:TIRS
      • DATE_ACQUIRED:2023-01-15
      • DATE_PRODUCT_GENERATED:1675122294000
      • DATUM:WGS84
      • EARTH_SUN_DISTANCE:0.9836383
      • ELLIPSOID:WGS84
      • GEOMETRIC_RMSE_MODEL:7.591
      • GEOMETRIC_RMSE_MODEL_X:5.31
      • GEOMETRIC_RMSE_MODEL_Y:5.425
      • GEOMETRIC_RMSE_VERIFY:4.289
      • GRID_CELL_SIZE_PANCHROMATIC:15
      • GRID_CELL_SIZE_REFLECTIVE:30
      • GRID_CELL_SIZE_THERMAL:30
      • GROUND_CONTROL_POINTS_MODEL:685
      • GROUND_CONTROL_POINTS_VERIFY:186
      • GROUND_CONTROL_POINTS_VERSION:5
      • IMAGE_QUALITY_OLI:9
      • IMAGE_QUALITY_TIRS:9
      • K1_CONSTANT_BAND_10:774.8853
      • K1_CONSTANT_BAND_11:480.8883
      • K2_CONSTANT_BAND_10:1321.0789
      • K2_CONSTANT_BAND_11:1201.1442
      • LANDSAT_PRODUCT_ID:LC08_L1TP_148044_20230115_20230130_02_T1
      • LANDSAT_SCENE_ID:LC81480442023015LGN00
      • MAP_PROJECTION:UTM
      • NADIR_OFFNADIR:NADIR
      • ORIENTATION:NORTH_UP
      • PANCHROMATIC_LINES:15661
      • PANCHROMATIC_SAMPLES:15341
      • PROCESSING_LEVEL:L1TP
      • PROCESSING_SOFTWARE_VERSION:LPGS_16.2.0
      • RADIANCE_ADD_BAND_1:-64.88466
      • RADIANCE_ADD_BAND_10:0.1
      • RADIANCE_ADD_BAND_11:0.1
      • RADIANCE_ADD_BAND_2:-66.44268
      • RADIANCE_ADD_BAND_3:-61.22636
      • RADIANCE_ADD_BAND_4:-51.62952
      • RADIANCE_ADD_BAND_5:-31.59469
      • RADIANCE_ADD_BAND_6:-7.85731
      • RADIANCE_ADD_BAND_7:-2.64833
      • RADIANCE_ADD_BAND_8:-58.4304
      • RADIANCE_ADD_BAND_9:-12.34792
      • RADIANCE_MULT_BAND_1:0.012977
      • RADIANCE_MULT_BAND_10:0.0003342
      • RADIANCE_MULT_BAND_11:0.0003342
      • RADIANCE_MULT_BAND_2:0.013289
      • RADIANCE_MULT_BAND_3:0.012245
      • RADIANCE_MULT_BAND_4:0.010326
      • RADIANCE_MULT_BAND_5:0.0063189
      • RADIANCE_MULT_BAND_6:0.0015715
      • RADIANCE_MULT_BAND_7:0.00052967
      • RADIANCE_MULT_BAND_8:0.011686
      • RADIANCE_MULT_BAND_9:0.0024696
      • REFLECTANCE_ADD_BAND_1:-0.1
      • REFLECTANCE_ADD_BAND_2:-0.1
      • REFLECTANCE_ADD_BAND_3:-0.1
      • REFLECTANCE_ADD_BAND_4:-0.1
      • REFLECTANCE_ADD_BAND_5:-0.1
      • REFLECTANCE_ADD_BAND_6:-0.1
      • REFLECTANCE_ADD_BAND_7:-0.1
      • REFLECTANCE_ADD_BAND_8:-0.1
      • REFLECTANCE_ADD_BAND_9:-0.1
      • REFLECTANCE_MULT_BAND_1:2e-05
      • REFLECTANCE_MULT_BAND_2:2e-05
      • REFLECTANCE_MULT_BAND_3:2e-05
      • REFLECTANCE_MULT_BAND_4:2e-05
      • REFLECTANCE_MULT_BAND_5:2e-05
      • REFLECTANCE_MULT_BAND_6:2e-05
      • REFLECTANCE_MULT_BAND_7:2e-05
      • REFLECTANCE_MULT_BAND_8:2e-05
      • REFLECTANCE_MULT_BAND_9:2e-05
      • REFLECTIVE_LINES:7831
      • REFLECTIVE_SAMPLES:7671
      • REQUEST_ID:1631847_00022
      • RESAMPLING_OPTION:CUBIC_CONVOLUTION
      • ROLL_ANGLE:-0.001
      • SATURATION_BAND_1:N
      • SATURATION_BAND_2:N
      • SATURATION_BAND_3:N
      • SATURATION_BAND_4:N
      • SATURATION_BAND_5:N
      • SATURATION_BAND_6:N
      • SATURATION_BAND_7:Y
      • SATURATION_BAND_8:N
      • SATURATION_BAND_9:N
      • SCENE_CENTER_TIME:05:33:07.2544160Z
      • SENSOR_ID:OLI_TIRS
      • SPACECRAFT_ID:LANDSAT_8
      • STATION_ID:LGN
      • SUN_AZIMUTH:148.67360104
      • SUN_ELEVATION:39.17034349
      • TARGET_WRS_PATH:148
      • TARGET_WRS_ROW:44
      • THERMAL_LINES:7831
      • THERMAL_SAMPLES:7671
      • TIRS_SSM_MODEL:FINAL
      • TIRS_SSM_POSITION_STATUS:ESTIMATED
      • TRUNCATION_OLI:UPPER
      • UTM_ZONE:43
      • WRS_PATH:148
      • WRS_ROW:44
      • WRS_TYPE:2
      • system:asset_size:1223935931
        • type:LinearRing
            • 0:72.31883641964504
            • 1:22.52056460806495
            • 0:72.29786773945534
            • 1:22.42936978641094
            • 0:72.29790667636928
            • 1:22.42736139148
            • 0:72.30336790848062
            • 1:22.426188648118245
            • 0:72.91869001515637
            • 1:22.30172835792067
            • 0:73.56730118878409
            • 1:22.167716185850985
            • 0:74.09737210807053
            • 1:22.056060171921665
            • 0:74.0993441010931
            • 1:22.056071041671355
            • 0:74.10397180462448
            • 1:22.07490056623611
            • 0:74.1329028941469
            • 1:22.19375917371582
            • 0:74.338430292183
            • 1:23.033751135411748
            • 0:74.47374505900434
            • 1:23.582190648182443
            • 0:74.52477957148619
            • 1:23.788055785032157
            • 0:74.52361975586437
            • 1:23.788584893320223
            • 0:73.58117794062672
            • 1:23.982739409188408
            • 0:72.7016330176871
            • 1:24.15813876032298
            • 0:72.69921791350811
            • 1:24.158102347091965
            • 0:72.60125718541295
            • 1:23.739508350574084
            • 0:72.50666704989243
            • 1:23.333219126751594
            • 0:72.41253287124782
            • 1:22.926903337749174
            • 0:72.31883641964504
            • 1:22.52056460806495
      • system:index:LC08_148044_20230115
      • system:time_end:1673760787254
      • system:time_start:1673760787254
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 163, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "first_item\n", + "ee_object = geemap.gdf_to_ee(first_item)\n", + "image = dataset.toList(true_color_432.size()).get(1)\n", + "image = ee.Image(image)\n", + "image" + ] + }, + { + "cell_type": "code", + "execution_count": 232, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d5625c7aabcf4d92a42515ca045ef758", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Map(center=[27.0, 72.0], controls=(WidgetControl(options=['position', 'transparent_bg'], widget=SearchDataGUI(…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import geemap\n", + "Map = geemap.Map(center=(27.0, 72.0), zoom=17)\n", + "\n", + "wmts_url = \"https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/MapServer/WMTS/1.0.0\"\n", + "\n", + "Map.add_tile_layer(\"https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/default028mm/MapServer/tile/56450/{z}/{y}/{x}\")\n", + "Map" + ] + }, + { + "cell_type": "code", + "execution_count": 249, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 249, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import geemap.foliumap as geemap\n", + "Map = geemap.Map(center=(27.0, 72.0), zoom=17)\n", + "\n", + "wmts_url = \"https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/MapServer/WMTS/1.0.0\"\n", + "\n", + "Map.add_tile_layer(\"https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/56450/{z}/{y}/{x}\")\n", + "Map" + ] + }, + { + "cell_type": "code", + "execution_count": 268, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ad7f77aad13a49ce9cc3518d296d1138", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Map(center=[27.0, 72.0], controls=(ZoomControl(options=['position', 'zoom_in_text', 'zoom_in_title', 'zoom_out…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import leafmap\n", + "Map = leafmap.Map(center=(27.0, 72.0), zoom=17)\n", + "Map.split_map(\"https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/10/{z}/{y}/{x}\", \"https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/56450/{z}/{y}/{x}\")\n", + "Map" + ] + }, + { + "cell_type": "code", + "execution_count": 277, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "67487913ce194912975217073b4e6912", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "GridspecLayout(children=(Output(layout=Layout(grid_area='widget001')), Output(layout=Layout(grid_area='widget0…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import leafmap.leafmap as leafmap\n", + "\n", + "layers = [\"ROADMAP\", \"HYBRID\"]\n", + "leafmap.linked_maps(rows=1, cols=2, height=\"400px\", layers=layers)" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import xml.etree.ElementTree as ET\n", + "import requests\n", + "\n", + "# WMTS capabilities URL\n", + "wmts_url = \"https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/MapServer/WMTS/1.0.0/WMTSCapabilities.xml\"\n", + "\n", + "# Get the XML content\n", + "response = requests.get(wmts_url)\n", + "root = ET.fromstring(response.content)" + ] + }, + { + "cell_type": "code", + "execution_count": 208, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of layers: 175\n" + ] + } + ], + "source": [ + "import xml.etree.ElementTree as ET\n", + "import requests\n", + "\n", + "# WMTS capabilities URL\n", + "wmts_url = \"https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/MapServer/WMTS/1.0.0/WMTSCapabilities.xml\"\n", + "\n", + "# Fetch the XML content\n", + "response = requests.get(wmts_url)\n", + "root = ET.fromstring(response.content)\n", + "\n", + "# Define namespaces\n", + "namespace = {\n", + " 'wmts': 'https://www.opengis.net/wmts/1.0',\n", + " 'ows': 'https://www.opengis.net/ows/1.1'\n", + "}\n", + "\n", + "# Extract mapping of layer identifiers to their ResourceURL templates\n", + "layer_mapping = {}\n", + "\n", + "# Find all Layer elements\n", + "for layer in root.findall('.//wmts:Layer', namespace):\n", + " identifier = layer.find('ows:Identifier', namespace).text\n", + " title = layer.find('ows:Title', namespace).text\n", + " resource_url_elem = layer.find('wmts:ResourceURL', namespace)\n", + "\n", + " if resource_url_elem is not None:\n", + " resource_template = resource_url_elem.get('template')\n", + " layer_mapping[identifier] = {\n", + " 'title': title,\n", + " 'resource_template': resource_template\n", + " }\n", + "\n", + "# Display the extracted layer mapping\n", + "print(f\"Number of layers: {len(layer_mapping)}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 240, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b822840dfb914ba7b3b96695f6def7f5", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + " 0%| | 0/175 [00:00\n", + " .geemap-dark {\n", + " --jp-widgets-color: white;\n", + " --jp-widgets-label-color: white;\n", + " --jp-ui-font-color1: white;\n", + " --jp-layout-color2: #454545;\n", + " background-color: #383838;\n", + " }\n", + "\n", + " .geemap-dark .jupyter-button {\n", + " --jp-layout-color3: #383838;\n", + " }\n", + "\n", + " .geemap-colab {\n", + " background-color: var(--colab-primary-surface-color, white);\n", + " }\n", + "\n", + " .geemap-colab .jupyter-button {\n", + " --jp-layout-color3: var(--colab-primary-surface-color, white);\n", + " }\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "{'2024-10-10': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/56450/{z}/{y}/{x}',\n", + " '2024-09-19': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/20337/{z}/{y}/{x}',\n", + " '2024-08-15': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/32553/{z}/{y}/{x}',\n", + " '2024-06-27': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/39767/{z}/{y}/{x}',\n", + " '2024-06-06': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/12428/{z}/{y}/{x}',\n", + " '2024-05-09': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/52930/{z}/{y}/{x}',\n", + " '2024-03-28': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/13968/{z}/{y}/{x}',\n", + " '2024-03-07': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/60013/{z}/{y}/{x}',\n", + " '2024-02-08': 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'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/17632/{z}/{y}/{x}',\n", + " '2023-06-29': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/47963/{z}/{y}/{x}',\n", + " '2023-06-13': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/25982/{z}/{y}/{x}',\n", + " '2023-05-03': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/46399/{z}/{y}/{x}',\n", + " '2023-04-05': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/37890/{z}/{y}/{x}',\n", + " '2023-03-15': 'https://wayback.maptiles.arcgis.com/arcgis/rest/services/World_Imagery/WMTS/1.0.0/GoogleMapsCompatible/MapServer/tile/44873/{z}/{y}/{x}',\n", + " '2023-02-23': 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+ "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "6a87c6af055444be8d9f304293e5287f", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "GridspecLayout(children=(Output(layout=Layout(grid_area='widget001')), Output(layout=Layout(grid_area='widget0…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import leafmap.leafmap as leafmap\n", + "\n", + "layers = [\"Esri.WorldTopoMap\", \"OpenTopoMap\"]\n", + "leafmap.linked_maps(rows=1, cols=2, height=\"400px\", layers=layers)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "zeel_py310", + "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": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}