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  {
   "cell_type": "markdown",
   "id": "d0e86abf-b283-475d-89a6-d4ba5f8d7c2b",
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   "source": [
    "# Exploring GeoPandas: Natural Earth Low Res Data Set\n",
    "This `JupyterLab` notebook is soley for exploring `GeoPandas` using the builtin data: `naturalearth_lowres`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b189141-3d74-4731-af82-954448d35321",
   "metadata": {},
   "source": [
    "## Setup\n",
    "First let's load the necessary *modules* and *data*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "00e31f7b-a637-427f-8249-7553f8c1f12b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# first let's get the libs\n",
    "import geopandas\n",
    "\n",
    "# get the earth data\n",
    "earth_lr = geopandas.read_file(geopandas.datasets.get_path('naturalearth_lowres'))\n",
    "\n",
    "# see whats in the data\n",
    "earth_lr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1f53e07d-4bea-448b-91e8-167e6fc15d43",
   "metadata": {},
   "outputs": [],
   "source": [
    "# let's see what unique continents are present\n",
    "CONTINENTS_SET = set(earth_lr['continent'].values)\n",
    "\n",
    "# remove some data\n",
    "CONTINENTS_SET.remove('Seven seas (open ocean)')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94e3012b-a5d5-4743-b026-0f83e8ce363b",
   "metadata": {},
   "source": [
    "## Natural Earth Lowres: Population Estimate\n",
    "We will begin exploring this data by looking at the `pop_est` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83aac067-4be4-4d57-b369-db1db32063ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "# first let's look at the entire world's populations\n",
    "earth_lr.plot('pop_est',\n",
    "              legend=True,\n",
    "              legend_kwds={'label': \"Population by Country\",\n",
    "                           'orientation': \"horizontal\"},\n",
    "              figsize=(16, 16));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b3ce1d25-5fdb-4365-bcda-2b0032ef7d49",
   "metadata": {},
   "outputs": [],
   "source": [
    "# next plot all continent Population Estimates separately\n",
    "for continent in CONTINENTS_SET:\n",
    "    # plot\n",
    "    earth_lr[earth_lr['continent'] == continent].plot('pop_est',\n",
    "                                                      figsize=(16, 12),\n",
    "                                                      legend=True,\n",
    "                                                      legend_kwds={'label': \"Population by Country\",\n",
    "                                                                   'orientation': \"horizontal\"});"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "775dcacb-fc3e-42c4-a0e7-bff17bb331ca",
   "metadata": {},
   "source": [
    "## Natural Earth Lowres: GDP Estimate\n",
    "Next we will be looking at the `gdp_md_est` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ca7137f0-41a7-40c6-a2f8-a7da894c4d58",
   "metadata": {},
   "outputs": [],
   "source": [
    "# first let's look at the entire world's gdp\n",
    "earth_lr.plot('gdp_md_est',\n",
    "              figsize=(16, 16),\n",
    "              legend=True,\n",
    "              legend_kwds={'label': \"GDP by Country\",\n",
    "                           'orientation': \"horizontal\"});"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "794100dd-2dd7-4c9f-9f04-2c3a957c002a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot all continent GDP Estimates\n",
    "for continent in CONTINENTS_SET:\n",
    "    # plot\n",
    "    earth_lr[earth_lr['continent'] == continent].plot('gdp_md_est',\n",
    "                                                      figsize=(16, 12),\n",
    "                                                      legend=True,\n",
    "                                                      legend_kwds={'label': \"GDP by Country\",\n",
    "                                                                   'orientation': \"horizontal\"});"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8907ddb4-f6c7-4468-aa4e-ba4517150214",
   "metadata": {},
   "source": [
    "## Natural Earth Lowres: Per Capita GDP\n",
    "Finally we will calculate *per capita GDP* by finding the ration of: \n",
    "$$\n",
    "\\frac{GDP}{Population}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4ffdfb78-f940-4cae-94b6-84de9b398a83",
   "metadata": {},
   "outputs": [],
   "source": [
    "# calc per capita gdp\n",
    "earth_lr['per_capita_gdp'] = earth_lr['gdp_md_est'] / earth_lr['pop_est']\n",
    "\n",
    "# first let's look at the entire world's per capita gdp\n",
    "earth_lr.plot('per_capita_gdp', \n",
    "              legend=True, \n",
    "              figsize=(16, 16),\n",
    "              legend_kwds={'label': \"Per Capita GDP by Country\",\n",
    "                           'orientation': \"horizontal\"});"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3cac121c-a148-4055-8a27-2ae98cbd1b34",
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot all continent Population Estimates\n",
    "for continent in CONTINENTS_SET:\n",
    "    # plot\n",
    "    earth_lr[earth_lr['continent'] == continent].plot('per_capita_gdp', \n",
    "                                                      figsize=(16, 12),\n",
    "                                                      legend=True,\n",
    "                                                      legend_kwds={'label': \"Per Capita GDP by Country\",\n",
    "                                                                   'orientation': \"horizontal\"});"
   ]
  }
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