{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4d098df7-6998-4e10-99fd-5e68aa01a997",
   "metadata": {},
   "outputs": [],
   "source": [
    "# data = \"data/data-3d9Ex.csv\"\n",
    "import plotly.express as px\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f49def17-f64f-46bf-a056-1d8a063ce3a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"data/data-3d9Ex.csv\")\n",
    "df = df.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "17975a6c-686e-43c3-a644-18004f74880b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d41f39d0-36fb-45d4-8d34-bd9dfd9545ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "fig = px.scatter_geo(df.head(), lat=\"Lat\", lon=\"Lon\", scope=\"europe\", fitbounds='locations',\n",
    "                     size=\"Lakosság\")\n",
    "fig.show(width=1000, height=800)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2940dc7-1221-4545-bcee-9eecf7b75fdb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.express as px\n",
    "\n",
    "colorscales = px.colors.named_colorscales()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dc5fe5a3-ba73-49ca-8c3d-24c5404b4ad5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "df['text'] = df['Name'] + ': ' + df['Elhunytak száma 100000 főre'].astype('str')\n",
    "tdf = df.head(100)\n",
    "\n",
    "\n",
    "fig = go.Figure(data=go.Scattergeo(\n",
    "        #locationmode = 'USA-states',\n",
    "        lon = tdf['Lon'],\n",
    "        lat = tdf['Lat'],\n",
    "        text = tdf['text'],\n",
    "        mode = 'markers',\n",
    "        marker = dict(\n",
    "            size = 5,\n",
    "            opacity = 0.6,\n",
    "            #color_continuous_scale=px.colors.sequential.Viridis,\n",
    "            #reversescale = True,\n",
    "            #autocolorscale = False,\n",
    "            symbol = 'square',\n",
    "            line = dict(\n",
    "                width=1,\n",
    "                color='rgba(102, 102, 102)'\n",
    "            ),\n",
    "            cmin = 0,\n",
    "            color = np.log(df['Elhunytak száma 100000 főre']),\n",
    "            cmax = np.log(df['Elhunytak száma 100000 főre'].max()),\n",
    "            colorbar_title=\"Population\"\n",
    "        )))\n",
    "\n",
    "fig.update_layout(\n",
    "        title = 'Halálesetek száma',\n",
    "        height=1000,\n",
    "        width=1200,\n",
    "        geo = dict(\n",
    "            fitbounds='locations',\n",
    "            scope='europe',\n",
    "            #projection_type='albers usa',\n",
    "            showland = True,\n",
    "            landcolor = \"rgb(250, 250, 250)\",\n",
    "            subunitcolor = \"rgb(217, 217, 217)\",\n",
    "            countrycolor = \"rgb(217, 217, 217)\",\n",
    "            #countrywidth = 0.5,\n",
    "            #subunitwidth = 0.5\n",
    "        ),\n",
    "        )\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "109c8725-0e01-4ad3-9185-813d5db115b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "df['text'] = df['Name'] + ': ' + df['Elhuyntak száma'].astype('str')\n",
    "tdf = df[df['Elhuyntak száma']>0]#.head(100)\n",
    "\n",
    "\n",
    "fig = go.Figure(data=go.Scattergeo(\n",
    "        #locationmode = 'USA-states',\n",
    "        lon = tdf['Lon'],\n",
    "        lat = tdf['Lat'],\n",
    "        text = tdf['text'],\n",
    "        mode = 'markers',\n",
    "        marker = dict(\n",
    "            size = np.log(tdf['Elhuyntak száma'])*5,\n",
    "            opacity = 0.6,\n",
    "            #color_continuous_scale=px.colors.sequential.Viridis,\n",
    "            #reversescale = True,\n",
    "            #autocolorscale = False,\n",
    "            symbol = 'circle',\n",
    "            line = dict(\n",
    "                width=1,\n",
    "                color='rgba(102, 102, 102)'\n",
    "            ),\n",
    "            cmin = 0,\n",
    "            color = np.log(tdf['Elhuyntak száma']),\n",
    "            cmax = np.log(tdf['Elhuyntak száma'].max()),\n",
    "            colorbar_title=\"Population\"\n",
    "        )))\n",
    "\n",
    "fig.update_layout(\n",
    "        title = 'Halálesetek száma',\n",
    "        height=1000,\n",
    "        width=1200,\n",
    "        geo = dict(\n",
    "            fitbounds='locations',\n",
    "            scope='europe',\n",
    "            #projection_type='albers usa',\n",
    "            showland = True,\n",
    "            landcolor = \"rgb(250, 250, 250)\",\n",
    "            subunitcolor = \"rgb(217, 217, 217)\",\n",
    "            countrycolor = \"rgb(217, 217, 217)\",\n",
    "            #countrywidth = 0.5,\n",
    "            #subunitwidth = 0.5\n",
    "        ),\n",
    "        )\n",
    "fig.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb6b0eda-51f1-4bf9-b161-487db05e4ebc",
   "metadata": {},
   "source": [
    "## Heti adatok"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "770e6ba1-e48a-4fde-aa77-5b898e9853e5",
   "metadata": {},
   "source": [
    "### Letoltes\n",
    "https://atlo.team/koronaterkep/#megyeibovebb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "40f6a53f-c929-4b86-b355-20997ca6adbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"https://docs.google.com/spreadsheets/d/1djH-yUHLPwuEExCjiXS__6-8W2Yp_msFvShpL4bBcuM/export?format=xlsx&gid=1283792994\"\n",
    "heti_df = pd.read_excel(url)         "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e89ed3a-3afe-42ee-b923-cd7e659ae9a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "heti_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7c319fee-1e1b-4b8a-bea0-690b5e3d67d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['text'] = df['Name'] + ': ' + df['Elhuyntak száma'].astype('str')\n",
    "tdf = df[df['Elhuyntak száma']>0]#.head(100)\n",
    "\n",
    "\n",
    "fig = go.Figure(data=go.Scattergeo(\n",
    "        #locationmode = 'USA-states',\n",
    "        lon = tdf['Lon'],\n",
    "        lat = tdf['Lat'],\n",
    "        text = tdf['text'],\n",
    "        mode = 'markers',\n",
    "        marker = dict(\n",
    "            size = np.log(tdf['Elhuyntak száma'])*5,\n",
    "            opacity = 0.6,\n",
    "            #color_continuous_scale=px.colors.sequential.Viridis,\n",
    "            #reversescale = True,\n",
    "            #autocolorscale = False,\n",
    "            symbol = 'circle',\n",
    "            line = dict(\n",
    "                width=1,\n",
    "                color='rgba(102, 102, 102)'\n",
    "            ),\n",
    "            cmin = 0,\n",
    "            color = np.log(tdf['Elhuyntak száma']),\n",
    "            cmax = np.log(tdf['Elhuyntak száma'].max()),\n",
    "            colorbar_title=\"Population\"\n",
    "        )))\n",
    "\n",
    "fig.update_layout(\n",
    "        title = 'Halálesetek száma',\n",
    "        height=1000,\n",
    "        width=1200,\n",
    "        geo = dict(\n",
    "            fitbounds='locations',\n",
    "            scope='europe',\n",
    "            #projection_type='albers usa',\n",
    "            showland = True,\n",
    "            landcolor = \"rgb(250, 250, 250)\",\n",
    "            subunitcolor = \"rgb(217, 217, 217)\",\n",
    "            countrycolor = \"rgb(217, 217, 217)\",\n",
    "            #countrywidth = 0.5,\n",
    "            #subunitwidth = 0.5\n",
    "        ),\n",
    "        )\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1a60442e-74fa-45a3-a50c-6808c52c7ca9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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