Choropleth_map.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://plotly.com/python/choropleth-maps/\n",
    "\n",
    "https://plotly.com/python/mapbox-county-choropleth/\n",
    "\n",
    "https://plotly.github.io/plotly.py-docs/generated/plotly.express.choropleth.html\n",
    "\n",
    "https://plotly.github.io/plotly.py-docs/index.html\n",
    "\n",
    "https://plotly.com/python/builtin-colorscales/\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'counties' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-8b9ac41a9e7e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'FIPS'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'FIPS'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m fig = px.choropleth_mapbox(df, geojson=counties, locations='FIPS',\n\u001b[0m\u001b[1;32m     13\u001b[0m                            \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Deaths'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m                            \u001b[0mcolor_continuous_scale\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"matter\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'counties' is not defined"
     ]
    }
   ],
   "source": [
    "import plotly.express as px\n",
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv(\n",
    "    \"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports/04-22-2020.csv\")\n",
    "\n",
    "# df.sort_values(by=['Province_State'], inplace=True)\n",
    "df = df.dropna(axis=0, subset=['FIPS'])\n",
    "df = df.dropna(axis=0, subset=['Lat'])\n",
    "df['FIPS'] = df['FIPS'].astype(int)\n",
    "\n",
    "fig = px.choropleth_mapbox(df, geojson=counties, locations='FIPS',\n",
    "                           color='Deaths',\n",
    "                           color_continuous_scale=\"matter\",\n",
    "                           mapbox_style=\"carto-positron\",\n",
    "                           zoom=3, center={\"lat\": 37.0902, \"lon\": -95.7129},\n",
    "                           )\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.express as px\n",
    "import pandas as pd\n",
    "us_state_abbrev = {\n",
    "'Alabama': 'AL', 'Alaska': 'AK', 'Arizona': 'AZ', 'Arkansas': 'AR', 'California': 'CA', 'Colorado': 'CO',\n",
    "'Connecticut': 'CT', 'Delaware': 'DE', 'Florida': 'FL', 'Georgia': 'GA', 'Hawaii': 'HI', 'Idaho': 'ID',\n",
    "'Illinois': 'IL', 'Indiana': 'IN', 'Iowa': 'IA', 'Kansas': 'KS', 'Kentucky': 'KY', 'Louisiana': 'LA',\n",
    "'Maine': 'ME', 'Maryland': 'MD', 'Massachusetts': 'MA', 'Michigan': 'MI', 'Minnesota': 'MN', 'Mississippi': 'MS',\n",
    "'Missouri': 'MO', 'Montana': 'MT', 'Nebraska': 'NE', 'Nevada': 'NV', 'New Hampshire': 'NH', 'New Jersey': 'NJ',\n",
    "'New Mexico': 'NM', 'New York': 'NY', 'North Carolina': 'NC', 'North Dakota': 'ND', 'Ohio': 'OH', 'Oklahoma': 'OK',\n",
    "'Oregon': 'OR', 'Pennsylvania': 'PA', 'Rhode Island': 'RI', 'South Carolina': 'SC', 'South Dakota': 'SD',\n",
    "'Tennessee': 'TN', 'Texas': 'TX', 'Utah': 'UT', 'Vermont': 'VT', 'Virginia': 'VA', 'Washington': 'WA',\n",
    "'West Virginia': 'WV', 'Wisconsin': 'WI', 'Wyoming': 'WY'}\n",
    "\n",
    "df = pd.read_csv(\n",
    "    \"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports_us/04-22-2020.csv\")\n",
    "\n",
    "indexNames = df[ df['ISO3'] != 'USA' ].index \n",
    "# Delete these row indexes from dataFrame\n",
    "df.drop(indexNames , inplace=True)\n",
    "\n",
    "df = df.dropna(axis=0, subset=['Lat'])\n",
    "\n",
    "# display(df.head())\n",
    "df['Province_State'] = df['Province_State'].map(us_state_abbrev).fillna(df['Province_State'])\n",
    "\n",
    "fig = px.choropleth_mapbox(df,  \n",
    "                           locations='Province_State',\n",
    "                           color='Deaths',\n",
    "                           color_continuous_scale=\"matter\",\n",
    "                           mapbox_style=\"carto-positron\",\n",
    "                           zoom=3, \n",
    "                           center={\"lat\": 37.0902, \"lon\": -95.7129},\n",
    "                           )\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "# Load data frame and tidy it.\n",
    "import pandas as pd\n",
    "\n",
    "# display(df.head())\n",
    "fig = go.Figure(data=go.Choropleth(\n",
    "    locations=df['Province_State'], # Spatial coordinates\n",
    "    z = df['Deaths'].astype(int), # Data to be color-coded\n",
    "    locationmode = 'USA-states', # set of locations match entries in `locations`\n",
    "    colorscale = 'Reds',\n",
    "#     colorbar_title = \"Millions USD\",\n",
    "))\n",
    "\n",
    "fig.update_layout(\n",
    "    title_text = 'COVID-19 Deaths by State',\n",
    "    geo_scope='usa', # limite map scope to USA\n",
    ")\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "# Load data frame and tidy it.\n",
    "import pandas as pd\n",
    "df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')\n",
    "display(df.head())\n",
    "fig = go.Figure(data=go.Choropleth(\n",
    "    locations=df['code'], # Spatial coordinates\n",
    "    z = df['total exports'].astype(float), # Data to be color-coded\n",
    "    locationmode = 'USA-states', # set of locations match entries in `locations`\n",
    "    colorscale = 'Reds',\n",
    "    colorbar_title = \"Millions USD\",\n",
    "))\n",
    "\n",
    "fig.update_layout(\n",
    "    title_text = '2011 US Agriculture Exports by State',\n",
    "    geo_scope='usa', # limite map scope to USA\n",
    ")\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "type({})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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