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{
"cells": [
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <style>\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",
" </style>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import geemap\n",
"import ee\n",
"import plotly.express as px"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <style>\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",
" </style>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"geemap.ee_initialize()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <style>\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",
" </style>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"esa = ee.ImageCollection('ESA/WorldCover/v200').first()\n",
"\n",
"ucs = ee.FeatureCollection(\"projects/ee-curso-gee-rhamon/assets/ucs_estaduais_rj\")\n",
"\n",
" \n",
"esa = esa.clipToCollection(ucs)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <style>\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",
" </style>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Computing ... \n",
"Generating URL ...\n",
"Downloading data from https://earthengine.googleapis.com/v1/projects/346107197273/tables/60f4e2523a74ad9da945ec21ae745a37-75ffe80c0d13be48ca8789157bb6c245:getFeatures\n",
"Please wait ...\n",
"Data downloaded to c:\\Users\\Rhamon\\Desktop\\Solara\\solara-geemap\\notebooks\\esa_stats_ucs_rj.csv\n"
]
}
],
"source": [
"esa_stats = 'esa_stats_ucs_rj.csv'\n",
"\n",
"geemap.zonal_stats_by_group(\n",
" esa,\n",
" ucs,\n",
" esa_stats,\n",
" statistics_type='PERCENTAGE',\n",
" denominator=1e6,\n",
" decimal_places=2,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"<>:1: SyntaxWarning: invalid escape sequence '\\e'\n",
"<>:1: SyntaxWarning: invalid escape sequence '\\e'\n"
]
},
{
"data": {
"text/html": [
"\n",
" <style>\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",
" </style>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\Rhamon\\AppData\\Local\\Temp\\ipykernel_21848\\2857369937.py:1: SyntaxWarning: invalid escape sequence '\\e'\n",
" df = 'CSVs\\esa_stats_ucs_rj.csv'\n"
]
}
],
"source": [
"df = 'CSVs\\esa_stats_ucs_rj.csv'"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <style>\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",
" </style>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"ename": "ValueError",
"evalue": "DataFrame constructor not properly called!",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m~\\AppData\\Local\\Temp\\ipykernel_21848\\385931256.py\u001b[0m in \u001b[0;36m?\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mfig\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpie\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'Class_10'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"nome\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtitle\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'Cobertura Florestal UCs Estaduais RJ'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32mc:\\Users\\Rhamon\\miniconda3\\envs\\geo\\Lib\\site-packages\\plotly\\express\\_chart_types.py\u001b[0m in \u001b[0;36m?\u001b[1;34m(data_frame, names, values, color, facet_row, facet_col, facet_col_wrap, facet_row_spacing, facet_col_spacing, color_discrete_sequence, color_discrete_map, hover_name, hover_data, custom_data, category_orders, labels, title, template, width, height, opacity, hole)\u001b[0m\n\u001b[0;32m 1478\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mcolor_discrete_sequence\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1479\u001b[0m \u001b[0mlayout_patch\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;34m\"piecolorway\"\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mcolor_discrete_sequence\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1480\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1481\u001b[0m \u001b[0mlayout_patch\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1482\u001b[1;33m return make_figure(\n\u001b[0m\u001b[0;32m 1483\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlocals\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1484\u001b[0m \u001b[0mconstructor\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mgo\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPie\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1485\u001b[0m \u001b[0mtrace_patch\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mdict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mshowlegend\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnames\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhole\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mhole\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32mc:\\Users\\Rhamon\\miniconda3\\envs\\geo\\Lib\\site-packages\\plotly\\express\\_core.py\u001b[0m in \u001b[0;36m?\u001b[1;34m(args, constructor, trace_patch, layout_patch)\u001b[0m\n\u001b[0;32m 2086\u001b[0m \u001b[0mtrace_patch\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mtrace_patch\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2087\u001b[0m \u001b[0mlayout_patch\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mlayout_patch\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;33m{\u001b[0m\u001b[1;33m}\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2088\u001b[0m \u001b[0mapply_default_cascade\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2089\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2090\u001b[1;33m \u001b[0margs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mbuild_dataframe\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mconstructor\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2091\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mconstructor\u001b[0m \u001b[1;32min\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mgo\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTreemap\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgo\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSunburst\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgo\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mIcicle\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0margs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m\"path\"\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2092\u001b[0m \u001b[0margs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mprocess_dataframe_hierarchy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 2093\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mconstructor\u001b[0m \u001b[1;32min\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mgo\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mPie\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
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"\u001b[1;32mc:\\Users\\Rhamon\\miniconda3\\envs\\geo\\Lib\\site-packages\\pandas\\core\\frame.py\u001b[0m in \u001b[0;36m?\u001b[1;34m(self, data, index, columns, dtype, copy)\u001b[0m\n\u001b[0;32m 882\u001b[0m \u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 883\u001b[0m \u001b[1;31m# For data is scalar\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 884\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 885\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mindex\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mcolumns\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 886\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"DataFrame constructor not properly called!\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 887\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 888\u001b[0m \u001b[0mindex\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mensure_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 889\u001b[0m \u001b[0mcolumns\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mensure_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mValueError\u001b[0m: DataFrame constructor not properly called!"
]
}
],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "geo",
"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": "3.12.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|