{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "--------\n", "\n", "# Weather Data Access in Search\n", "\n", "--------\n", "\n", "**Short description**\n", "\n", "This notebook introduces the Weather access and refinement.\n", "\n", "--------" ] }, { "cell_type": "markdown", "metadata": { "colab_type": "text", "id": "keC_14irx2wq" }, "source": [ "### 1 - Import spacesense object(s) and other dependencies" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": {}, "colab_type": "code", "id": "l1WpZ6RSx2wr" }, "outputs": [], "source": [ "from spacesense import Client\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "import json\n", "\n", "import os\n", "if \"SS_API_KEY\" not in os.environ:\n", " from getpass import getpass\n", " api_key = getpass('Enter your api key : ')\n", " os.environ[\"SS_API_KEY\"] = api_key" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2 - Define AOI and TOI" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# Define the AOI\n", "aoi = {\n", " \"type\": \"FeatureCollection\",\n", " \"features\": [\n", " {\n", " \"id\": \"0\",\n", " \"type\": \"Feature\",\n", " \"properties\": {},\n", " \"geometry\": {\n", " \"type\": \"Polygon\",\n", " \"coordinates\": [\n", " [\n", " [\n", " 8.622499,\n", " 39.831038\n", " ],\n", " [\n", " 8.622499,\n", " 39.827197\n", " ],\n", " [\n", " 8.630311,\n", " 39.827197\n", " ],\n", " [\n", " 8.630311,\n", " 39.831038\n", " ],\n", " [\n", " 8.622499,\n", " 39.831038\n", " ]\n", " ]\n", " ]\n", " }\n", " }\n", " ]\n", "}\n", "\n", "# Define TOI\n", "start_date = \"2021-02-01\"\n", "end_date = \"2021-04-15\"\n", "\n", "# Get an instance of the SpaceSense Client object\n", "client = Client(id=\"weather_search\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3 - Search Weather" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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datelailowprecuwindvwind
02021-02-011.7250947.1168494.864336-2.266004
12021-02-021.7260891.5815123.563660-2.541020
22021-02-031.7270940.004455-0.7819302.039700
32021-02-041.7280880.000006-1.8367141.226246
42021-02-051.7290920.000006-1.8271591.178977
..................
692021-04-111.9304401.614441-2.8295412.599476
702021-04-121.9337406.2142832.196791-2.096936
712021-04-131.9370540.0000004.891191-3.295530
722021-04-141.9403520.0438610.547026-0.059496
732021-04-151.9407110.046124-0.063789-0.383259
\n", "

74 rows × 5 columns

\n", "
" ], "text/plain": [ " date lailow prec uwind vwind\n", "0 2021-02-01 1.725094 7.116849 4.864336 -2.266004\n", "1 2021-02-02 1.726089 1.581512 3.563660 -2.541020\n", "2 2021-02-03 1.727094 0.004455 -0.781930 2.039700\n", "3 2021-02-04 1.728088 0.000006 -1.836714 1.226246\n", "4 2021-02-05 1.729092 0.000006 -1.827159 1.178977\n", ".. ... ... ... ... ...\n", "69 2021-04-11 1.930440 1.614441 -2.829541 2.599476\n", "70 2021-04-12 1.933740 6.214283 2.196791 -2.096936\n", "71 2021-04-13 1.937054 0.000000 4.891191 -3.295530\n", "72 2021-04-14 1.940352 0.043861 0.547026 -0.059496\n", "73 2021-04-15 1.940711 0.046124 -0.063789 -0.383259\n", "\n", "[74 rows x 5 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Retrieves some weather all S1 images corresponding to the aoi, start date, and end date\n", "weather_variables = [\"LAILOW\", \"PREC\", \"UWIND\", \"VWIND\"]\n", "res_weather = client.weather_search(aoi, start_date, end_date, variables=weather_variables)\n", "df = res_weather.dataframe\n", "df" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 4 - Plot time series of LAI" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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8S2B_32TMK_20210220_0_L2A2021-02-2032TMK100.00sentinel-2b065S2B_MSIL2A_20210220T101939_N0214_R065_T32TMK_2...2021-02-20T10:29:41Z100.00.00.0097.860.000.00.000.000.00.0
7S2A_32TMK_20210225_0_L2A2021-02-2532TMK100.00sentinel-2a065S2A_MSIL2A_20210225T102021_N0214_R065_T32TMK_2...2021-02-25T10:29:43Z100.00.00.0097.800.000.00.000.000.00.0
6S2A_32TMK_20210307_0_L2A2021-03-0732TMK99.00sentinel-2a065S2A_MSIL2A_20210307T102021_N0214_R065_T32TMK_2...2021-03-07T10:29:43Z100.00.00.0068.590.000.01.000.000.00.0
5S2B_32TMK_20210322_0_L2A2021-03-2232TMK97.78sentinel-2b065S2B_MSIL2A_20210322T101649_N0214_R065_T32TMK_2...2021-03-22T10:29:43Z100.00.00.0092.870.980.02.220.000.00.0
4S2B_32TMK_20210329_0_L2A2021-03-2932TMK100.00sentinel-2b022S2B_MSIL2A_20210329T100609_N0214_R022_T32TMK_2...2021-03-29T10:19:46Z100.00.00.0097.860.160.00.000.000.00.0
3S2B_32TMK_20210401_0_L2A2021-04-0132TMK100.00sentinel-2b065S2B_MSIL2A_20210401T101559_N0300_R065_T32TMK_2...2021-04-01T10:29:42Z100.00.00.0097.970.000.00.000.000.00.0
2S2A_32TMK_20210406_0_L2A2021-04-0632TMK100.00sentinel-2a065S2A_MSIL2A_20210406T102021_N0300_R065_T32TMK_2...2021-04-06T10:29:40Z100.00.00.0098.560.000.00.000.000.00.0
1S2B_32TMK_20210408_0_L2A2021-04-0832TMK100.00sentinel-2b022S2B_MSIL2A_20210408T100549_N0300_R022_T32TMK_2...2021-04-08T10:19:45Z100.00.00.0098.130.000.00.000.000.00.0
0S2A_32TMK_20210413_0_L2A2021-04-1332TMK96.34sentinel-2a022S2A_MSIL2A_20210413T101021_N0300_R022_T32TMK_2...2021-04-13T10:19:42Z100.00.00.4989.353.120.03.010.160.00.0
\n", "
" ], "text/plain": [ " id date tile valid_pixel_percentage \\\n", "11 S2A_32TMK_20210205_0_L2A 2021-02-05 32TMK 100.00 \n", "10 S2A_32TMK_20210215_0_L2A 2021-02-15 32TMK 100.00 \n", "9 S2B_32TMK_20210217_0_L2A 2021-02-17 32TMK 100.00 \n", "8 S2B_32TMK_20210220_0_L2A 2021-02-20 32TMK 100.00 \n", "7 S2A_32TMK_20210225_0_L2A 2021-02-25 32TMK 100.00 \n", "6 S2A_32TMK_20210307_0_L2A 2021-03-07 32TMK 99.00 \n", "5 S2B_32TMK_20210322_0_L2A 2021-03-22 32TMK 97.78 \n", "4 S2B_32TMK_20210329_0_L2A 2021-03-29 32TMK 100.00 \n", "3 S2B_32TMK_20210401_0_L2A 2021-04-01 32TMK 100.00 \n", "2 S2A_32TMK_20210406_0_L2A 2021-04-06 32TMK 100.00 \n", "1 S2B_32TMK_20210408_0_L2A 2021-04-08 32TMK 100.00 \n", "0 S2A_32TMK_20210413_0_L2A 2021-04-13 32TMK 96.34 \n", "\n", " platform relative_orbit_number \\\n", "11 sentinel-2a 065 \n", "10 sentinel-2a 065 \n", "9 sentinel-2b 022 \n", "8 sentinel-2b 065 \n", "7 sentinel-2a 065 \n", "6 sentinel-2a 065 \n", "5 sentinel-2b 065 \n", "4 sentinel-2b 022 \n", "3 sentinel-2b 065 \n", "2 sentinel-2a 065 \n", "1 sentinel-2b 022 \n", "0 sentinel-2a 022 \n", "\n", " product_id datetime \\\n", "11 S2A_MSIL2A_20210205T102221_N0214_R065_T32TMK_2... 2021-02-05T10:29:43Z \n", "10 S2A_MSIL2A_20210215T102121_N0214_R065_T32TMK_2... 2021-02-15T10:29:42Z \n", "9 S2B_MSIL2A_20210217T101029_N0214_R022_T32TMK_2... 2021-02-17T10:19:45Z \n", "8 S2B_MSIL2A_20210220T101939_N0214_R065_T32TMK_2... 2021-02-20T10:29:41Z \n", "7 S2A_MSIL2A_20210225T102021_N0214_R065_T32TMK_2... 2021-02-25T10:29:43Z \n", "6 S2A_MSIL2A_20210307T102021_N0214_R065_T32TMK_2... 2021-03-07T10:29:43Z \n", "5 S2B_MSIL2A_20210322T101649_N0214_R065_T32TMK_2... 2021-03-22T10:29:43Z \n", "4 S2B_MSIL2A_20210329T100609_N0214_R022_T32TMK_2... 2021-03-29T10:19:46Z \n", "3 S2B_MSIL2A_20210401T101559_N0300_R065_T32TMK_2... 2021-04-01T10:29:42Z \n", "2 S2A_MSIL2A_20210406T102021_N0300_R065_T32TMK_2... 2021-04-06T10:29:40Z \n", "1 S2B_MSIL2A_20210408T100549_N0300_R022_T32TMK_2... 2021-04-08T10:19:45Z \n", "0 S2A_MSIL2A_20210413T101021_N0300_R022_T32TMK_2... 2021-04-13T10:19:42Z \n", "\n", " swath_coverage_percentage no_data cloud_shadows vegetation \\\n", "11 100.0 0.0 0.00 97.40 \n", "10 100.0 0.0 0.00 97.86 \n", "9 100.0 0.0 0.00 97.97 \n", "8 100.0 0.0 0.00 97.86 \n", "7 100.0 0.0 0.00 97.80 \n", "6 100.0 0.0 0.00 68.59 \n", "5 100.0 0.0 0.00 92.87 \n", "4 100.0 0.0 0.00 97.86 \n", "3 100.0 0.0 0.00 97.97 \n", "2 100.0 0.0 0.00 98.56 \n", "1 100.0 0.0 0.00 98.13 \n", "0 100.0 0.0 0.49 89.35 \n", "\n", " not_vegetated water cloud_medium_probability cloud_high_probability \\\n", "11 0.16 0.0 0.00 0.00 \n", "10 0.00 0.0 0.00 0.00 \n", "9 0.00 0.0 0.00 0.00 \n", "8 0.00 0.0 0.00 0.00 \n", "7 0.00 0.0 0.00 0.00 \n", "6 0.00 0.0 1.00 0.00 \n", "5 0.98 0.0 2.22 0.00 \n", "4 0.16 0.0 0.00 0.00 \n", "3 0.00 0.0 0.00 0.00 \n", "2 0.00 0.0 0.00 0.00 \n", "1 0.00 0.0 0.00 0.00 \n", "0 3.12 0.0 3.01 0.16 \n", "\n", " thin_cirrus snow \n", "11 0.0 0.0 \n", "10 0.0 0.0 \n", "9 0.0 0.0 \n", "8 0.0 0.0 \n", "7 0.0 0.0 \n", "6 0.0 0.0 \n", "5 0.0 0.0 \n", "4 0.0 0.0 \n", "3 0.0 0.0 \n", "2 0.0 0.0 \n", "1 0.0 0.0 \n", "0 0.0 0.0 " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Retrieves all S2 images corresponding to the aoi, start date, and end date\n", "res_S2 = client.s2_search(aoi=aoi, start_date=start_date, end_date=end_date, query_filters = {\"valid_pixel_percentage\" : {\">=\": 95}})\n", "res_S2.dataframe" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 6 - Filter weather dates matching S2 dates\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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datelailowprecuwindvwind
42021-02-051.7290920.000006-1.8271591.178977
142021-02-151.7403110.000006-0.302282-1.600299
162021-02-171.7475220.000006-0.037975-0.273452
192021-02-201.7583550.004262-2.8088610.954008
242021-02-251.7763820.0283800.015086-0.116508
342021-03-071.8124630.682086-2.2306861.315975
492021-03-221.8643130.125496-0.026054-4.197672
562021-03-291.8874620.009414-0.267097-0.117241
592021-04-011.8973750.000000-0.250064-0.198988
642021-04-061.9139040.2991035.917795-2.332012
662021-04-081.9205130.000000-0.086882-0.620076
712021-04-131.9370540.0000004.891191-3.295530
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" ], "text/plain": [ " date lailow prec uwind vwind\n", "4 2021-02-05 1.729092 0.000006 -1.827159 1.178977\n", "14 2021-02-15 1.740311 0.000006 -0.302282 -1.600299\n", "16 2021-02-17 1.747522 0.000006 -0.037975 -0.273452\n", "19 2021-02-20 1.758355 0.004262 -2.808861 0.954008\n", "24 2021-02-25 1.776382 0.028380 0.015086 -0.116508\n", "34 2021-03-07 1.812463 0.682086 -2.230686 1.315975\n", "49 2021-03-22 1.864313 0.125496 -0.026054 -4.197672\n", "56 2021-03-29 1.887462 0.009414 -0.267097 -0.117241\n", "59 2021-04-01 1.897375 0.000000 -0.250064 -0.198988\n", "64 2021-04-06 1.913904 0.299103 5.917795 -2.332012\n", "66 2021-04-08 1.920513 0.000000 -0.086882 -0.620076\n", "71 2021-04-13 1.937054 0.000000 4.891191 -3.295530" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "res_weather.dataframe = res_weather.dataframe[[date in list(res_S2.dataframe[\"date\"]) for date in list(res_weather.dataframe[\"date\"])]]\n", "res_weather.dataframe" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 7 - Filter S2 dates with U-wind<1" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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iddatetilevalid_pixel_percentageplatformrelative_orbit_numberproduct_iddatetimeswath_coverage_percentageno_datacloud_shadowsvegetationnot_vegetatedwatercloud_medium_probabilitycloud_high_probabilitythin_cirrussnow
11S2A_32TMK_20210205_0_L2A2021-02-0532TMK100.00sentinel-2a065S2A_MSIL2A_20210205T102221_N0214_R065_T32TMK_2...2021-02-05T10:29:43Z100.00.00.097.400.160.00.000.00.00.0
10S2A_32TMK_20210215_0_L2A2021-02-1532TMK100.00sentinel-2a065S2A_MSIL2A_20210215T102121_N0214_R065_T32TMK_2...2021-02-15T10:29:42Z100.00.00.097.860.000.00.000.00.00.0
9S2B_32TMK_20210217_0_L2A2021-02-1732TMK100.00sentinel-2b022S2B_MSIL2A_20210217T101029_N0214_R022_T32TMK_2...2021-02-17T10:19:45Z100.00.00.097.970.000.00.000.00.00.0
8S2B_32TMK_20210220_0_L2A2021-02-2032TMK100.00sentinel-2b065S2B_MSIL2A_20210220T101939_N0214_R065_T32TMK_2...2021-02-20T10:29:41Z100.00.00.097.860.000.00.000.00.00.0
7S2A_32TMK_20210225_0_L2A2021-02-2532TMK100.00sentinel-2a065S2A_MSIL2A_20210225T102021_N0214_R065_T32TMK_2...2021-02-25T10:29:43Z100.00.00.097.800.000.00.000.00.00.0
6S2A_32TMK_20210307_0_L2A2021-03-0732TMK99.00sentinel-2a065S2A_MSIL2A_20210307T102021_N0214_R065_T32TMK_2...2021-03-07T10:29:43Z100.00.00.068.590.000.01.000.00.00.0
5S2B_32TMK_20210322_0_L2A2021-03-2232TMK97.78sentinel-2b065S2B_MSIL2A_20210322T101649_N0214_R065_T32TMK_2...2021-03-22T10:29:43Z100.00.00.092.870.980.02.220.00.00.0
4S2B_32TMK_20210329_0_L2A2021-03-2932TMK100.00sentinel-2b022S2B_MSIL2A_20210329T100609_N0214_R022_T32TMK_2...2021-03-29T10:19:46Z100.00.00.097.860.160.00.000.00.00.0
3S2B_32TMK_20210401_0_L2A2021-04-0132TMK100.00sentinel-2b065S2B_MSIL2A_20210401T101559_N0300_R065_T32TMK_2...2021-04-01T10:29:42Z100.00.00.097.970.000.00.000.00.00.0
1S2B_32TMK_20210408_0_L2A2021-04-0832TMK100.00sentinel-2b022S2B_MSIL2A_20210408T100549_N0300_R022_T32TMK_2...2021-04-08T10:19:45Z100.00.00.098.130.000.00.000.00.00.0
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" ], "text/plain": [ " id date tile valid_pixel_percentage \\\n", "11 S2A_32TMK_20210205_0_L2A 2021-02-05 32TMK 100.00 \n", "10 S2A_32TMK_20210215_0_L2A 2021-02-15 32TMK 100.00 \n", "9 S2B_32TMK_20210217_0_L2A 2021-02-17 32TMK 100.00 \n", "8 S2B_32TMK_20210220_0_L2A 2021-02-20 32TMK 100.00 \n", "7 S2A_32TMK_20210225_0_L2A 2021-02-25 32TMK 100.00 \n", "6 S2A_32TMK_20210307_0_L2A 2021-03-07 32TMK 99.00 \n", "5 S2B_32TMK_20210322_0_L2A 2021-03-22 32TMK 97.78 \n", "4 S2B_32TMK_20210329_0_L2A 2021-03-29 32TMK 100.00 \n", "3 S2B_32TMK_20210401_0_L2A 2021-04-01 32TMK 100.00 \n", "1 S2B_32TMK_20210408_0_L2A 2021-04-08 32TMK 100.00 \n", "\n", " platform relative_orbit_number \\\n", "11 sentinel-2a 065 \n", "10 sentinel-2a 065 \n", "9 sentinel-2b 022 \n", "8 sentinel-2b 065 \n", "7 sentinel-2a 065 \n", "6 sentinel-2a 065 \n", "5 sentinel-2b 065 \n", "4 sentinel-2b 022 \n", "3 sentinel-2b 065 \n", "1 sentinel-2b 022 \n", "\n", " product_id datetime \\\n", "11 S2A_MSIL2A_20210205T102221_N0214_R065_T32TMK_2... 2021-02-05T10:29:43Z \n", "10 S2A_MSIL2A_20210215T102121_N0214_R065_T32TMK_2... 2021-02-15T10:29:42Z \n", "9 S2B_MSIL2A_20210217T101029_N0214_R022_T32TMK_2... 2021-02-17T10:19:45Z \n", "8 S2B_MSIL2A_20210220T101939_N0214_R065_T32TMK_2... 2021-02-20T10:29:41Z \n", "7 S2A_MSIL2A_20210225T102021_N0214_R065_T32TMK_2... 2021-02-25T10:29:43Z \n", "6 S2A_MSIL2A_20210307T102021_N0214_R065_T32TMK_2... 2021-03-07T10:29:43Z \n", "5 S2B_MSIL2A_20210322T101649_N0214_R065_T32TMK_2... 2021-03-22T10:29:43Z \n", "4 S2B_MSIL2A_20210329T100609_N0214_R022_T32TMK_2... 2021-03-29T10:19:46Z \n", "3 S2B_MSIL2A_20210401T101559_N0300_R065_T32TMK_2... 2021-04-01T10:29:42Z \n", "1 S2B_MSIL2A_20210408T100549_N0300_R022_T32TMK_2... 2021-04-08T10:19:45Z \n", "\n", " swath_coverage_percentage no_data cloud_shadows vegetation \\\n", "11 100.0 0.0 0.0 97.40 \n", "10 100.0 0.0 0.0 97.86 \n", "9 100.0 0.0 0.0 97.97 \n", "8 100.0 0.0 0.0 97.86 \n", "7 100.0 0.0 0.0 97.80 \n", "6 100.0 0.0 0.0 68.59 \n", "5 100.0 0.0 0.0 92.87 \n", "4 100.0 0.0 0.0 97.86 \n", "3 100.0 0.0 0.0 97.97 \n", "1 100.0 0.0 0.0 98.13 \n", "\n", " not_vegetated water cloud_medium_probability cloud_high_probability \\\n", "11 0.16 0.0 0.00 0.0 \n", "10 0.00 0.0 0.00 0.0 \n", "9 0.00 0.0 0.00 0.0 \n", "8 0.00 0.0 0.00 0.0 \n", "7 0.00 0.0 0.00 0.0 \n", "6 0.00 0.0 1.00 0.0 \n", "5 0.98 0.0 2.22 0.0 \n", "4 0.16 0.0 0.00 0.0 \n", "3 0.00 0.0 0.00 0.0 \n", "1 0.00 0.0 0.00 0.0 \n", "\n", " thin_cirrus snow \n", "11 0.0 0.0 \n", "10 0.0 0.0 \n", "9 0.0 0.0 \n", "8 0.0 0.0 \n", "7 0.0 0.0 \n", "6 0.0 0.0 \n", "5 0.0 0.0 \n", "4 0.0 0.0 \n", "3 0.0 0.0 \n", "1 0.0 0.0 " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "res_S2_df_no_wind = res_S2.dataframe[list(res_weather.dataframe[\"uwind\"]<1)]\n", "res_S2_df_no_wind" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 8 - Merge dataframes" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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datelailowprecproduct_id
02021-02-051.7290920.000006S2A_MSIL2A_20210205T102221_N0214_R065_T32TMK_2...
12021-02-151.7403110.000006S2A_MSIL2A_20210215T102121_N0214_R065_T32TMK_2...
22021-02-171.7475220.000006S2B_MSIL2A_20210217T101029_N0214_R022_T32TMK_2...
32021-02-201.7583550.004262S2B_MSIL2A_20210220T101939_N0214_R065_T32TMK_2...
42021-02-251.7763820.028380S2A_MSIL2A_20210225T102021_N0214_R065_T32TMK_2...
52021-03-071.8124630.682086S2A_MSIL2A_20210307T102021_N0214_R065_T32TMK_2...
62021-03-221.8643130.125496S2B_MSIL2A_20210322T101649_N0214_R065_T32TMK_2...
72021-03-291.8874620.009414S2B_MSIL2A_20210329T100609_N0214_R022_T32TMK_2...
82021-04-011.8973750.000000S2B_MSIL2A_20210401T101559_N0300_R065_T32TMK_2...
92021-04-061.9139040.299103S2A_MSIL2A_20210406T102021_N0300_R065_T32TMK_2...
102021-04-081.9205130.000000S2B_MSIL2A_20210408T100549_N0300_R022_T32TMK_2...
112021-04-131.9370540.000000S2A_MSIL2A_20210413T101021_N0300_R022_T32TMK_2...
\n", "
" ], "text/plain": [ " date lailow prec \\\n", "0 2021-02-05 1.729092 0.000006 \n", "1 2021-02-15 1.740311 0.000006 \n", "2 2021-02-17 1.747522 0.000006 \n", "3 2021-02-20 1.758355 0.004262 \n", "4 2021-02-25 1.776382 0.028380 \n", "5 2021-03-07 1.812463 0.682086 \n", "6 2021-03-22 1.864313 0.125496 \n", "7 2021-03-29 1.887462 0.009414 \n", "8 2021-04-01 1.897375 0.000000 \n", "9 2021-04-06 1.913904 0.299103 \n", "10 2021-04-08 1.920513 0.000000 \n", "11 2021-04-13 1.937054 0.000000 \n", "\n", " product_id \n", "0 S2A_MSIL2A_20210205T102221_N0214_R065_T32TMK_2... \n", "1 S2A_MSIL2A_20210215T102121_N0214_R065_T32TMK_2... \n", "2 S2B_MSIL2A_20210217T101029_N0214_R022_T32TMK_2... \n", "3 S2B_MSIL2A_20210220T101939_N0214_R065_T32TMK_2... \n", "4 S2A_MSIL2A_20210225T102021_N0214_R065_T32TMK_2... \n", "5 S2A_MSIL2A_20210307T102021_N0214_R065_T32TMK_2... \n", "6 S2B_MSIL2A_20210322T101649_N0214_R065_T32TMK_2... \n", "7 S2B_MSIL2A_20210329T100609_N0214_R022_T32TMK_2... \n", "8 S2B_MSIL2A_20210401T101559_N0300_R065_T32TMK_2... \n", "9 S2A_MSIL2A_20210406T102021_N0300_R065_T32TMK_2... \n", "10 S2B_MSIL2A_20210408T100549_N0300_R022_T32TMK_2... \n", "11 S2A_MSIL2A_20210413T101021_N0300_R022_T32TMK_2... " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "global_df = pd.merge(res_weather.dataframe, res_S2.dataframe, on=\"date\", how=\"outer\")\n", "global_df = global_df[[\"date\", \"lailow\", \"prec\", \"product_id\"]]\n", "global_df" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3.7.5 ('venv': venv)", "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": "3.7.5" }, "orig_nbformat": 4, "vscode": { "interpreter": { "hash": "e1ad9e0bf6960974dd8425f76aaa88b32de1b03d6f54bb6bf7fb6a0ca773e449" } } }, "nbformat": 4, "nbformat_minor": 2 }