The_Columbian_exchange.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-------\n",
    "-------\n",
    "\n",
    "Avant de commencer la lecture de ce document, merci d'appuyer sur <font color='red'>  Kernel > Restart & Run All </font>\n",
    "\n",
    "-------\n",
    "-------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Smallpox in America, one byproduct of the Columbian exchange"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style='text-align: justify;'>  \n",
    "    The expression “Colombian exchange” refers to the mutual effects that followed the contact of Spaniards mainly, and Europeans and Africans by extension, with the indigenous populations of America. It corresponds to an exchange of animals, plants, technologies, but also of many diseases.\n",
    "Our choice of study focused on smallpox disease, which was first introduced into South America by the conquistadors and was then one of the major causes of the pre-Columbian populations's decimation.\n",
    "</p>\n",
    "\n",
    "----"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create the dataframe listing smallpox epidemics on the American continent after the arrival of Ch. Columbus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Location (actual name)</th>\n",
       "      <th>Start Year</th>\n",
       "      <th>End Year</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mexico, Central America, South America</td>\n",
       "      <td>1520</td>\n",
       "      <td>1527</td>\n",
       "      <td>19.432630</td>\n",
       "      <td>-99.133178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Chile</td>\n",
       "      <td>1561</td>\n",
       "      <td>1562</td>\n",
       "      <td>-31.761336</td>\n",
       "      <td>-71.318770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Central Chile</td>\n",
       "      <td>1588</td>\n",
       "      <td>1591</td>\n",
       "      <td>-18.360266</td>\n",
       "      <td>-69.958781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>North America northern east coast</td>\n",
       "      <td>1617</td>\n",
       "      <td>1619</td>\n",
       "      <td>43.661028</td>\n",
       "      <td>-70.254860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Chillan, Central Chile</td>\n",
       "      <td>1655</td>\n",
       "      <td>1656</td>\n",
       "      <td>-36.606662</td>\n",
       "      <td>-72.103319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Cherokee Tribe</td>\n",
       "      <td>1674</td>\n",
       "      <td>1675</td>\n",
       "      <td>34.543905</td>\n",
       "      <td>-84.084363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Boston, MA</td>\n",
       "      <td>1692</td>\n",
       "      <td>1693</td>\n",
       "      <td>42.360253</td>\n",
       "      <td>-71.058291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>St. Lawrence Valley, NY</td>\n",
       "      <td>1702</td>\n",
       "      <td>1703</td>\n",
       "      <td>44.177271</td>\n",
       "      <td>-76.167716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Boston, MA</td>\n",
       "      <td>1721</td>\n",
       "      <td>1722</td>\n",
       "      <td>42.360253</td>\n",
       "      <td>-71.058291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>1736</td>\n",
       "      <td>1737</td>\n",
       "      <td>40.969989</td>\n",
       "      <td>-77.727883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>South Carolina</td>\n",
       "      <td>1738</td>\n",
       "      <td>1739</td>\n",
       "      <td>33.687439</td>\n",
       "      <td>-80.436374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>West Coast of North America</td>\n",
       "      <td>1770</td>\n",
       "      <td>1780</td>\n",
       "      <td>44.939157</td>\n",
       "      <td>-123.033121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Hudson Bay</td>\n",
       "      <td>1781</td>\n",
       "      <td>1782</td>\n",
       "      <td>56.794116</td>\n",
       "      <td>-91.857662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Great Lakes</td>\n",
       "      <td>1781</td>\n",
       "      <td>1783</td>\n",
       "      <td>42.309189</td>\n",
       "      <td>-87.850071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Alaska</td>\n",
       "      <td>1830</td>\n",
       "      <td>1840</td>\n",
       "      <td>64.445961</td>\n",
       "      <td>-149.680909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Great Plains</td>\n",
       "      <td>1836</td>\n",
       "      <td>1840</td>\n",
       "      <td>39.416865</td>\n",
       "      <td>-101.292097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>1860</td>\n",
       "      <td>1861</td>\n",
       "      <td>40.969989</td>\n",
       "      <td>-77.727883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>British Columbia</td>\n",
       "      <td>1862</td>\n",
       "      <td>1863</td>\n",
       "      <td>55.001251</td>\n",
       "      <td>-125.002441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Washington state</td>\n",
       "      <td>1862</td>\n",
       "      <td>1863</td>\n",
       "      <td>47.286835</td>\n",
       "      <td>-120.212614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Russian America</td>\n",
       "      <td>1862</td>\n",
       "      <td>1863</td>\n",
       "      <td>57.052497</td>\n",
       "      <td>-135.337612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Philadelphia, PA</td>\n",
       "      <td>1865</td>\n",
       "      <td>1873</td>\n",
       "      <td>39.952724</td>\n",
       "      <td>-75.163526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>New York</td>\n",
       "      <td>1865</td>\n",
       "      <td>1873</td>\n",
       "      <td>40.712728</td>\n",
       "      <td>-74.006015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Boston, MA</td>\n",
       "      <td>1865</td>\n",
       "      <td>1873</td>\n",
       "      <td>42.360253</td>\n",
       "      <td>-71.058291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>New Orleans, LA</td>\n",
       "      <td>1865</td>\n",
       "      <td>1873</td>\n",
       "      <td>29.949932</td>\n",
       "      <td>-90.070116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Araucanía, southern Chile</td>\n",
       "      <td>1869</td>\n",
       "      <td>1870</td>\n",
       "      <td>-38.671012</td>\n",
       "      <td>-72.256458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Los Angeles, CA</td>\n",
       "      <td>1877</td>\n",
       "      <td>1878</td>\n",
       "      <td>34.052230</td>\n",
       "      <td>-118.243680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Tacna, Peru</td>\n",
       "      <td>1880</td>\n",
       "      <td>1881</td>\n",
       "      <td>-18.013852</td>\n",
       "      <td>-70.251161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Boston, Massachusetts</td>\n",
       "      <td>1902</td>\n",
       "      <td>1903</td>\n",
       "      <td>42.360253</td>\n",
       "      <td>-71.058291</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Location (actual name)  Start Year  End Year   Latitude  \\\n",
       "0   Mexico, Central America, South America        1520      1527  19.432630   \n",
       "1                                    Chile        1561      1562 -31.761336   \n",
       "2                            Central Chile        1588      1591 -18.360266   \n",
       "3        North America northern east coast        1617      1619  43.661028   \n",
       "4                   Chillan, Central Chile        1655      1656 -36.606662   \n",
       "5                           Cherokee Tribe        1674      1675  34.543905   \n",
       "6                               Boston, MA        1692      1693  42.360253   \n",
       "7                  St. Lawrence Valley, NY        1702      1703  44.177271   \n",
       "8                               Boston, MA        1721      1722  42.360253   \n",
       "9                             Pennsylvania        1736      1737  40.969989   \n",
       "10                          South Carolina        1738      1739  33.687439   \n",
       "11             West Coast of North America        1770      1780  44.939157   \n",
       "12                              Hudson Bay        1781      1782  56.794116   \n",
       "13                             Great Lakes        1781      1783  42.309189   \n",
       "14                                  Alaska        1830      1840  64.445961   \n",
       "15                            Great Plains        1836      1840  39.416865   \n",
       "16                            Pennsylvania        1860      1861  40.969989   \n",
       "17                        British Columbia        1862      1863  55.001251   \n",
       "18                        Washington state        1862      1863  47.286835   \n",
       "19                         Russian America        1862      1863  57.052497   \n",
       "20                        Philadelphia, PA        1865      1873  39.952724   \n",
       "21                                New York        1865      1873  40.712728   \n",
       "22                              Boston, MA        1865      1873  42.360253   \n",
       "23                         New Orleans, LA        1865      1873  29.949932   \n",
       "24               Araucanía, southern Chile        1869      1870 -38.671012   \n",
       "25                         Los Angeles, CA        1877      1878  34.052230   \n",
       "26                             Tacna, Peru        1880      1881 -18.013852   \n",
       "27                   Boston, Massachusetts        1902      1903  42.360253   \n",
       "\n",
       "     Longitude  \n",
       "0   -99.133178  \n",
       "1   -71.318770  \n",
       "2   -69.958781  \n",
       "3   -70.254860  \n",
       "4   -72.103319  \n",
       "5   -84.084363  \n",
       "6   -71.058291  \n",
       "7   -76.167716  \n",
       "8   -71.058291  \n",
       "9   -77.727883  \n",
       "10  -80.436374  \n",
       "11 -123.033121  \n",
       "12  -91.857662  \n",
       "13  -87.850071  \n",
       "14 -149.680909  \n",
       "15 -101.292097  \n",
       "16  -77.727883  \n",
       "17 -125.002441  \n",
       "18 -120.212614  \n",
       "19 -135.337612  \n",
       "20  -75.163526  \n",
       "21  -74.006015  \n",
       "22  -71.058291  \n",
       "23  -90.070116  \n",
       "24  -72.256458  \n",
       "25 -118.243680  \n",
       "26  -70.251161  \n",
       "27  -71.058291  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "data = {'Location (actual name)' :['Mexico, Central America, South America','Chile','Central Chile','North America northern east coast','Chillan, Central Chile','Cherokee Tribe','Boston, MA','St. Lawrence Valley, NY','Boston, MA','Pennsylvania','South Carolina','West Coast of North America','Hudson Bay','Great Lakes','Alaska','Great Plains','Pennsylvania','British Columbia', 'Washington state','Russian America','Philadelphia, PA','New York', 'Boston, MA' ,'New Orleans, LA','Araucanía, southern Chile','Los Angeles, CA','Tacna, Peru','Boston, Massachusetts'],\n",
    "        'Start Year':[1520,1561,1588,1617,1655,1674,1692,1702,1721,1736,1738,1770,1781,1781,\n",
    "                      1830,1836,1860,1862,1862,1862,1865,1865,1865,1865,1869,1877,1880,1902],\n",
    "        'End Year':[1527,1562,1591,1619,1656,1675,1693,1703,1722,1737,1739,1780,1782,1783,\n",
    "                    1840,1840,1861,1863,1863,1863,1873,1873,1873,1873,1870,1878,1881,1903],\n",
    "        'Latitude' : [19.4326296,-31.7613365,-18.360266,43.661028,-36.606662,34.543905,42.360253,44.177271,42.360253,40.969989,33.687439,44.939157,56.794115531339095,42.309189,64.445961,39.416865,40.9699889,55.001251,47.286835,57.052497,39.9527237,40.712728,42.3602534,29.9499323,-38.6710116,34.05223,-18.0138521,42.3602534],\n",
    "        'Longitude': [-99.1331785,-71.3187697,-69.958781,-70.25486,-72.103319,-84.084363,-71.058291,-76.167716,-71.058291,-77.727883,-80.436374,-123.033121,-91.85766178750002,-87.850071,-149.680909,-101.292097,-77.7278831,-125.002441,-120.212614,-135.337612,-75.1635262,-74.0060152,-71.0582912,-90.0701156,-72.2564576,-118.24368,-70.2511614,-71.0582912],\n",
    "       }\n",
    "\n",
    "df = pd.DataFrame(data, columns = data.keys())\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create the dataframe listing some major European sailors's transatlantic crossings and European settlements that have been linked to the emergence of smallpox epidemics on the American continent "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year of arrival on the American continent</th>\n",
       "      <th>Lead sailor</th>\n",
       "      <th>Place of departure</th>\n",
       "      <th>Place of arrival or settling</th>\n",
       "      <th>Coordinates of departure (latitude, longitude)</th>\n",
       "      <th>Coordinates of arrival (latitude, longitude)</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1493</td>\n",
       "      <td>Christopher Columbus</td>\n",
       "      <td>Palos de la Frontera, Spain</td>\n",
       "      <td>Bahamas; Cuba; Haïti; Dominican Republic</td>\n",
       "      <td>(37.2277697, -6.8932258)</td>\n",
       "      <td>(19.0974031, -70.3028026)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1519</td>\n",
       "      <td>Hernán Cortés</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>(39.3262345, -4.8380649)</td>\n",
       "      <td>(19.4326296, -99.1331785)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1536</td>\n",
       "      <td>Diego de Almagro</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Central Chile</td>\n",
       "      <td>(39.3262345, -4.8380649)</td>\n",
       "      <td>(-27.166283069332913, -70.05561839904344)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1605</td>\n",
       "      <td>Du Gua et Samuel de Champlain</td>\n",
       "      <td>France</td>\n",
       "      <td>Cape Cod, Massachusetts, United States</td>\n",
       "      <td>(49.4938975, 0.1079732)</td>\n",
       "      <td>(41.7988074, -69.9960135)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1609</td>\n",
       "      <td>Henry Hudson</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Hudson Bay, NU, Canada</td>\n",
       "      <td>(54.7023545, -3.2765753)</td>\n",
       "      <td>(58.6590901, -85.9250446)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1784</td>\n",
       "      <td>Grigory Ivanovich Shelikhov</td>\n",
       "      <td>Russia</td>\n",
       "      <td>Kodiak Island, Alaska, United States</td>\n",
       "      <td>(64.6863136, 97.7453061)</td>\n",
       "      <td>(64.4459613, -149.680909)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year of arrival on the American continent                    Lead sailor  \\\n",
       "0                                       1493           Christopher Columbus   \n",
       "1                                       1519                  Hernán Cortés   \n",
       "2                                       1536               Diego de Almagro   \n",
       "3                                       1605  Du Gua et Samuel de Champlain   \n",
       "4                                       1609                   Henry Hudson   \n",
       "5                                       1784    Grigory Ivanovich Shelikhov   \n",
       "\n",
       "            Place of departure              Place of arrival or settling  \\\n",
       "0  Palos de la Frontera, Spain  Bahamas; Cuba; Haïti; Dominican Republic   \n",
       "1                        Spain                                    Mexico   \n",
       "2                        Spain                             Central Chile   \n",
       "3                       France    Cape Cod, Massachusetts, United States   \n",
       "4               United Kingdom                    Hudson Bay, NU, Canada   \n",
       "5                       Russia      Kodiak Island, Alaska, United States   \n",
       "\n",
       "  Coordinates of departure (latitude, longitude)  \\\n",
       "0                       (37.2277697, -6.8932258)   \n",
       "1                       (39.3262345, -4.8380649)   \n",
       "2                       (39.3262345, -4.8380649)   \n",
       "3                        (49.4938975, 0.1079732)   \n",
       "4                       (54.7023545, -3.2765753)   \n",
       "5                       (64.6863136, 97.7453061)   \n",
       "\n",
       "  Coordinates of arrival (latitude, longitude)  \n",
       "0                    (19.0974031, -70.3028026)  \n",
       "1                    (19.4326296, -99.1331785)  \n",
       "2    (-27.166283069332913, -70.05561839904344)  \n",
       "3                    (41.7988074, -69.9960135)  \n",
       "4                    (58.6590901, -85.9250446)  \n",
       "5                    (64.4459613, -149.680909)  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2 = {'Year of arrival on the American continent':[1493, 1519, 1536, 1605, 1609, 1784],\n",
    "         'Lead sailor':['Christopher Columbus', 'Hernán Cortés', 'Diego de Almagro', 'Du Gua et Samuel de Champlain', 'Henry Hudson', 'Grigory Ivanovich Shelikhov'],\n",
    "        'Place of departure':['Palos de la Frontera, Spain', 'Spain', 'Spain', 'France', 'United Kingdom', 'Russia'],\n",
    "        'Place of arrival or settling':['Bahamas; Cuba; Haïti; Dominican Republic', 'Mexico', 'Central Chile', 'Cape Cod, Massachusetts, United States', 'Hudson Bay, NU, Canada', 'Kodiak Island, Alaska, United States'],\n",
    "        'Coordinates of departure (latitude, longitude)':[(37.2277697,-6.8932258), (39.3262345,-4.8380649), (39.3262345,-4.8380649), (49.4938975,0.1079732), (54.7023545,-3.2765753), (64.6863136, 97.7453061)],\n",
    "        'Coordinates of arrival (latitude, longitude)':[(19.0974031,-70.3028026),(19.4326296,-99.1331785), (-27.166283069332913,-70.05561839904344), (41.7988074,-69.9960135), (58.6590901,-85.9250446), (64.4459613,-149.680909)]\n",
    "        }\n",
    "df2 = pd.DataFrame(data2, columns = data2.keys())\n",
    "df2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Convert latitudes and longitudes into graphic coordinates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "from ast import literal_eval\n",
    "def merc(Coords):\n",
    "    Coordinates = literal_eval(Coords)\n",
    "    lat = Coordinates[0]\n",
    "    lon = Coordinates[1]\n",
    "    \n",
    "    r_major = 6378137.000\n",
    "    x = r_major * math.radians(lon)\n",
    "    scale = x/lon\n",
    "    y = 180.0/math.pi * math.log(math.tan(math.pi/4.0 + \n",
    "        lat * (math.pi/180.0)/2.0)) * scale\n",
    "    return (x, y)\n",
    "\n",
    "def make_tuple_str(x, y):\n",
    "    t = (x, y)\n",
    "    return str(t)\n",
    "\n",
    "\n",
    "df['coords'] = df.apply(lambda x: make_tuple_str(x['Latitude'], x['Longitude']), axis = 1)\n",
    "df['coords_latitude'] = df['coords'].apply(lambda x: merc(x)[0])\n",
    "df['coords_longitude'] = df['coords'].apply(lambda x: merc(x)[1])\n",
    "\n",
    "df2['start_coords_lat'] = [df2['Coordinates of departure (latitude, longitude)'][i][0] for i in range(len(data2['Lead sailor']))]\n",
    "df2['end_coords_lat'] = [df2['Coordinates of arrival (latitude, longitude)'][i][0] for i in range(len(data2['Lead sailor']))]\n",
    "\n",
    "df2['start_coords_long'] =[df2['Coordinates of departure (latitude, longitude)'][i][1] for i in range(len(data2['Lead sailor']))]\n",
    "df2['end_coords_long'] =[df2['Coordinates of arrival (latitude, longitude)'][i][1] for i in range(len(data2['Lead sailor']))]\n",
    "\n",
    "\n",
    "df2['start_coords'] = df2.apply(lambda x: make_tuple_str(x['start_coords_lat'], x['start_coords_long']), axis = 1)\n",
    "df2['end_coords'] = df2.apply(lambda x: make_tuple_str(x['end_coords_lat'], x['end_coords_long']), axis = 1)\n",
    "\n",
    "\n",
    "df2['start_coords_lat'] = df2['start_coords'].apply(lambda x: merc(x)[0])\n",
    "df2['end_coords_lat'] = df2['end_coords'].apply(lambda x: merc(x)[0])\n",
    "\n",
    "\n",
    "df2['start_coords_long'] = df2['start_coords'].apply(lambda x: merc(x)[1])\n",
    "df2['end_coords_long'] = df2['end_coords'].apply(lambda x: merc(x)[1])\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Display our main original figure  \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"4374\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  var JS_MIME_TYPE = 'application/javascript';\n",
       "  var HTML_MIME_TYPE = 'text/html';\n",
       "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    var script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    var cell = handle.cell;\n",
       "\n",
       "    var id = cell.output_area._bokeh_element_id;\n",
       "    var server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id != null && id in Bokeh.index) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            var id = msg.content.text.trim();\n",
       "            if (id in Bokeh.index) {\n",
       "              Bokeh.index[id].model.document.clear();\n",
       "              delete Bokeh.index[id];\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    var output_area = handle.output_area;\n",
       "    var output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      var bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      var script_attrs = bk_div.children[0].attributes;\n",
       "      for (var i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      var toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    var el = document.getElementById(\"4374\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\": \"T2yuo9Oe71Cz/I4X9Ac5+gpEa5a8PpJCDlqKYO0CfAuEszu1JrXLl8YugMqYe3sM\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\": \"98GDGJ0kOMCUMUePhksaQ/GYgB3+NH9h996V88sh3aOiUNX3N+fLXAtry6xctSZ6\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\": \"89bArO+nlbP3sgakeHjCo1JYxYR5wufVgA3IbUvDY+K7w4zyxJqssu7wVnfeKCq8\"};\n",
       "\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      if (url in hashes) {\n",
       "        element.crossOrigin = \"anonymous\";\n",
       "        element.integrity = \"sha384-\" + hashes[url];\n",
       "      }\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  \n",
       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.2.3.min.js\"];\n",
       "  var css_urls = [];\n",
       "  \n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "    \n",
       "    \n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if (root.Bokeh !== undefined || force === true) {\n",
       "      \n",
       "    for (var i = 0; i < inline_js.length; i++) {\n",
       "      inline_js[i].call(root, root.Bokeh);\n",
       "    }\n",
       "    if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"4374\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(\"4374\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (var i = 0; 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       "  var render_items = [{\"docid\":\"4f972ffe-9569-4e82-8e4c-84b083dfdb48\",\"root_ids\":[\"4373\"],\"roots\":{\"4373\":\"45747965-5a1d-4472-89e6-2a708d1b1a8d\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "4373"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "from bokeh.plotting import figure, show, output_notebook\n",
    "from bokeh.tile_providers import CARTODBPOSITRON_RETINA, get_provider, Vendors \n",
    "from bokeh.models import HoverTool, Label, ColumnDataSource\n",
    "from datetime import date\n",
    "from bokeh.models import CustomJS, DateSlider, Slider, Arrow, VeeHead, Title, Paragraph\n",
    "from bokeh.layouts import column\n",
    "\n",
    "\n",
    "hover1 = HoverTool(tooltips = [(\"Location (actual name)\", \"@desc\"),\n",
    "                             (\"Smallpox epidemics\",\"@start_year - @end_year \" )], names = ['cir'])\n",
    "\n",
    "hover2 = HoverTool(tooltips = [(\"Year of arrival on the American continent\", \"@crossing_year\"),\n",
    "                             (\"Lead sailor\",\"@sail \" )], names = ['seg'])\n",
    "\n",
    "hover3 = HoverTool(tooltips = [('','@desc3')], names = ['dia'])\n",
    "\n",
    "p = figure(plot_width=900, plot_height=600,\n",
    "           x_range=(min(df['coords_latitude'])-1.5e+05, max(df['coords_latitude']+1.5e+06)), \n",
    "           y_range=(min(df['coords_longitude'])-1e+06,max(df['coords_longitude'])+1e+06),\n",
    "           title=\"The Columbian exchange\", \n",
    "           x_axis_type=\"mercator\", \n",
    "           y_axis_type=\"mercator\", tools = \"pan, wheel_zoom, box_zoom, reset\")\n",
    "\n",
    "p.title.text_font_size = '20pt'\n",
    "p.title.align = 'center'\n",
    "p.add_layout(Title(text=\"from Columbus’ first arrival to the eradication of the virus\", text_font_style=\"normal\",align=\"center\"), 'above')\n",
    "p.add_layout(Title(text=\"Correlation between European expeditions to the Americas and the spread of smallpox\", text_font_style=\"normal\", align=\"center\"), 'above')\n",
    "\n",
    "\n",
    "tile_provider = get_provider(Vendors.CARTODBPOSITRON_RETINA)\n",
    "p.add_tile(tile_provider)\n",
    "p.add_tools(hover1, hover2, hover3)\n",
    "\n",
    "\n",
    "source_epidemics = ColumnDataSource(data=dict(\n",
    "    x = df['coords_latitude'],\n",
    "    y = df['coords_longitude'],\n",
    "    dim = [0 for i in range(len(df['coords_longitude']))],\n",
    "    start_year = df['Start Year'],\n",
    "    end_year = df['End Year'],\n",
    "    desc = df['Location (actual name)']\n",
    ",))\n",
    "\n",
    "\n",
    "source_travel = ColumnDataSource(data=dict(\n",
    "    x_start = df2['start_coords_lat'],\n",
    "    y_start = df2['start_coords_long'],\n",
    "    x_end = df2['end_coords_lat'],\n",
    "    y_end = df2['end_coords_long'],\n",
    "    vis = [0 for i in range(len(df2['end_coords_lat']))],\n",
    "    crossing_year = df2['Year of arrival on the American continent'],\n",
    "    sail = df2['Lead sailor']\n",
    ",))\n",
    "\n",
    "\n",
    "source_last_case = ColumnDataSource(data=dict(\n",
    "    x = [merc('(-10.3333333,-53.2)')[0]], \n",
    "    y = [merc('(-10.3333333,-53.2)')[1]],\n",
    "    last_case_year = [1971],\n",
    "    desc3 = [\"April 19, 1971\"],\n",
    "    dim3 = [0.]\n",
    ",))\n",
    "\n",
    "\n",
    "callback = CustomJS(args=dict(source1=source_epidemics, source2=source_travel, source3=source_last_case), code=\"\"\"\n",
    "    var value = cb_obj.value;\n",
    "    \n",
    "    var data1 = source1.data;  \n",
    "    var start_year = data1['start_year']; \n",
    "    var end_year = data1['end_year'];\n",
    "    var dims = data1['dim'];\n",
    "    for (var i = 0; i < dims.length; i++) {\n",
    "        if ( start_year[i] <= value ) {\n",
    "            if (end_year[i]>= value) {dims[i]=30 }\n",
    "            else {dims[i]=13 }\n",
    "            }\n",
    "        else {dims[i]=0 }\n",
    "    }\n",
    "        \n",
    "    var data2 = source2.data;\n",
    "    var visi = data2['vis'];\n",
    "    var cr_year = data2['crossing_year']\n",
    "    for (var i = 0; i < visi.length; i++) {\n",
    "        if (cr_year[i]<= value) { visi[i] = 1}\n",
    "        else {visi[i]=0 }\n",
    "    }\n",
    "    \n",
    "    var data3 = source3.data;\n",
    "    var dims3 = data3['dim3'];\n",
    "    var last_case_year = data3['last_case_year'];\n",
    "    for (var i = 0; i < dims3.length; i++) {\n",
    "        if (last_case_year[i] <= value ) {dims3[i] = 20}\n",
    "        else {dims3[i]=0 }\n",
    "    }\n",
    "    \n",
    "    source3.change.emit(); \n",
    "    source2.change.emit(); \n",
    "    source1.change.emit();\n",
    "\"\"\")\n",
    "\n",
    "p.circle('x', 'y', legend_label=\"Major smallpox epidemics in America\", \n",
    "         color= \"red\", fill_color=\"red\", alpha=0.6, hover_color='orange',\n",
    "         size ='dim',\n",
    "         name = 'cir',\n",
    "         source = source_epidemics)\n",
    "\n",
    "legend_crossings = \"Some major European sailors's transatlantic crossings\"\n",
    "p.segment(x0=\"x_start\", y0=\"y_start\", x1=\"x_end\", y1=\"y_end\", legend_label= legend_crossings,\n",
    "          line_color=\"grey\", line_width=.5, line_dash='dashed', hover_color='orange',\n",
    "          line_alpha = 'vis', \n",
    "          name = 'seg',\n",
    "          source = source_travel)\n",
    "\n",
    "p.diamond('x', 'y', legend_label=\"Last known case of smallpox on the continent\",\n",
    "         color= \"green\", hover_color='grey',\n",
    "         size = 'dim3',\n",
    "         name = 'dia',\n",
    "         source = source_last_case \n",
    "         )\n",
    "\n",
    "p.legend.location = \"bottom_left\"\n",
    "slider = Slider(start=1492, end=1975, value=1492, step=1, title=\"Date\")\n",
    "\n",
    "slider.js_on_change('value', callback)\n",
    "\n",
    "text = \"Caption: \\nBased on data from historical records of both smallpox epidemics and transatlantic crossings, this interactive map shows the correlation between European settlement on America’s “virgin soil” and the spread of a disease that Native Americans had yet never suffered from.\"\n",
    "caption = Paragraph(text=text)\n",
    "\n",
    "layout = column(p,slider,caption)\n",
    "output_notebook()\n",
    "\n",
    "show(layout)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Columbian exchange, an example of spatial approach to diseases (6000 signs text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style='text-align:justify;'> In 1492, Christopher Columbus did not \"discover\" America strictly speaking: this land had long been inhabited by natives, and the Vikings (among others) had already « bridged » the gap between the American continent and Eurasia. However, Columbus’s expedition did paved the way from what would become the strong connection and the interdependency between the so-called Old and New Worlds. From this day on, transfers of all imaginable things, living beings, human practices, and ideas have increasingly intensify and produced irreversible changes on both continents. These exchanges, which particularly affected the American fauna and flora, have been deeply investigated by the environmental historian Alfred Crosby who gave them the name of Colombian exchange in a 1972’s publication entitled The Columbian exchange: Biological and Cultural Consequences of 1492. Indeed, America was full of living beings new to Europeans who were therefore all at once frightened, greatly amazed and highly intrigued by their encounters. The sailors brought back some of their discoveries to the Old World to be studied or exhibited. Likewise, as settlers needed Old World cattle, crops, and other animals to thrive and feel in control of the land, they started to import those to the New World. Very soon, flux intensified and trade was permanently established. America’s isolation broke. New supplies became - more or less - accessible to all continents through the Columbian exchange, although trades were often made at natives’ expense. </p>\n",
    "<p style='text-align:justify;'>However, this is only the tip of the iceberg. As demonstrated by environmental historians and spatial epidemiologists, America and Europe did not only exchange animals and crops but also germs and diseases, and the difference between populations was not only cultural: it was also a contrast between immunities. As there had been almost no contact between those two parts of the  world during thousands of years, each had developed its own diseases, had biologically adapted to resist those specific diseases, had learned to control the spread and had created social responses to the symptoms of those specific diseases they had learned to know. As a result, the impact of disease exchanges was huge. They were even more dramatic among natives whose unique and singular  homogeneous biology made excessively vulnerable to European germs (« no population of comparable size has remained so uniform after expanding, in whatever time has been involved, over such a large area. » T. D. Stewart, 1960). Thus, Europeans brought syphilis back from America (although this thesis is controversial) when they themselves spread smallpox, measles and typhoid in America. </p>\n",
    "\n",
    "----\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import matplotlib.dates as mdates\n",
    "from datetime import datetime\n",
    "\n",
    "events = [\" Earliest evidence of smallpox : \\n mummified remains of Egyptian Pharaoh Ramses V \\n show telltale pockmarks on his skin\",\n",
    "          \"Smallpox is introduced into \\nthe Caribbean island of Hispaniola \",\n",
    "          \"Edward Jenner successfully tested in humans \\na cowpox vaccine against smallpox\", \n",
    "          \"The World Health Organization launched \\na worldwide eradication campaign \\nbased on vaccination \",\n",
    "          \"Last known case of smallpox on the American continent\",\n",
    "          \"Last known case of smallpox worldwide (Somalia)\"]\n",
    "\n",
    "dates = [-1157, 1509, 1796, 1967, 1971,1977]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 7), constrained_layout=True)\n",
    "\n",
    "for event, i , date in zip(events[::-1], range(len(dates)), dates[::-1]) :\n",
    "    ax.annotate(\"{} \".format(date)+\"\\n\"+event, xy=(0, i), \n",
    "                fontsize=10,\n",
    "                horizontalalignment=\"left\" if i%2==0 else \"right\")\n",
    "\n",
    "ax.set_title(\"3000 years of smallpox from its first detection to its eradication\", c=\"#3776ab\", weight=1000)\n",
    "ax.plot(np.zeros_like(dates), range(len(dates)), \"-o\",\n",
    "        color=\"k\", markerfacecolor=\"w\") \n",
    "\n",
    "ax.axis(\"off\")\n",
    "ax.margins(y=0.2)\n",
    "text = \"Caption : Smallpox’s history cannot be reduced to Europeans’ contamination of the American continent. First detected in Egypt, it was spread back \\nand forth in Eurasia and Africa well before the Columbian exchange. To this date, smallpox is the only human disease successfully eradicated by man.\"\n",
    "fig.text(0,0,text, fontsize = 12,  multialignment= \"left\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style='text-align:justify;'>Of all the diseases involuntarily brought by Europeans to America, smallpox may have been the deadliest (Crosby, 1972). Both Variola major and Variola minor arrived in America. Passed from human to human, smallpox was very contagious as it could transmit through the air by oral and nasal droplets or through contact with erupted pustules. After 12 days of incubation, infected patients would suffer from fever, fatigue, vomiting and intense pain preceding a more severe and dangerous eruptive stage. At this point of the disease, victims of smallpox were easily identified as their skin was quickly covered with pustules or fluid-filled blisters, scarring them. Throughout the whole month-long process, sick people were contagious. Finally, those who did not die of smallpox would become at least partially immune to it. </p>\n",
    "<p style='text-align:justify;'>The timeline shows that smallpox was introduced to America a few years only after Christopher Columbus’s first landing on the Caribbean island of Hispaniola in 1492. Indeed, some inhabitants of this island were infected as soon as 1509. The interactive map sheds light on the correlation between Europeans presence on American soil and the fast spreading of smallpox all over the continent. As mentioned, smallpox was a virulent disease and infected people were contagious even before the first symptoms appeared, while they were still able to travel. Contrary to stereotypical narratives, natives’ tribes were in a dense network of exchange and communication with one another long before the arrival of the Europeans. Therefore, smallpox traveled quickly throughout the whole continent.</p>\n",
    "<p style='text-align:justify;'> However, that being said, one should keep in mind that the link between disease spreading and intercontinental migration dates back well before the Columbian exchange. Indeed, the timeline shows that the first known case of smallpox was detected in Egypt in 1157 BC. Centuries before  the Columbian Exchange, European trade with another continent (in this case, Africa) led to the spreading of smallpox in Europe. Trade has long been a vector of diseases. </p>\n",
    "\n",
    "-----"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![title](https://raw.githubusercontent.com/ArianeVerzura/maping_epidemics-the_Columbian_exchange/main/case_fatality_rate.png)\n",
    "Caption: This map aims at showing the evolution, from the 18th century to its eradication, of the case fatality rate of smallpox throughout the world. It can be seen that smallpox became less deadly as exchanges between continents developed, meaning that the first encounter of the virus is deadlier than later encounters. The development of a vaccine can also be a clue to understand the lowering fatality rate. \n",
    "\n",
    "--------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style='text-align:justify;'>The study of smallpox in post-columbian America is of great interest because it is conducive to Alfred Crosby’s notion of \"virgin soil epidemic » i.e. epidemics affecting populations that “had no previous contact with the diseases that strike them and are therefore immunologically almost defenceless” (Crosby, 1972). As natives had not yet been in contact with smallpox, they were extremely vulnerable to it whereas Spaniards showed far more resistance thanks to the evolution of European immune systems and acquired immunity. Natives’ immuno-naïvity therefore explains the numerous outbreaks following Europeans’ settlings that we can see on the interactive map.</p>\n",
    "<p style='text-align:justify;'>Moreover, the study of fatality case rates (CFR) allows to better understand the evolution of smallpox and the different immunity of populations affected by the disease. The CFR is the proportion of deaths compared to the number of diseased. It should logically decrease when populations’ immunity is increasing. The second map shows this decrease. The intensification of trade throughout the world led to progressive biological homogeneity, everyone developing immunity against the diseases they share. This is why the fatality case rate of smallpox decreases over time. Added to the natural development of immunity, the development of a vaccine against smallpox in 1796 (according to the timeline) explains the decrease of fatality case rates we can see on the map. This vaccine was the subject of a worldwide campaign against smallpox organized by WHO in 1967. Thanks to this campaign, smallpox was the first and only disease eradicated by humans. The last case known on American continent and in the world, were respectively discovered in 1971 and 1977.</p>\n",
    " \n",
    "-----------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style='text-align:justify;'>Smallpox helped by other diseases decimated the local population. 80% to 95% of Amerindians were decimated by 1650 (Newson, 2001). This demographic catastrophe had political consequences. Diseases such as smallpox were a very efficient weapon against natives. Smallpox epidemics decimated by turns the Aztec and the Incas population and army. This facilitated European expeditions and colonization. Those easy conquests reinforced Europeans’ conviction of a divine mission of civilization through colonization. Therefore, diseases from the Columbian Exchange had an important role in the colonization of the American continent and its irreversible demographic and ecological consequences.</p>\n",
    "\n",
    "---------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## BIBLIOGRAPHY\n",
    "\n",
    "### Books and magazines :\n",
    "\n",
    "Bengoa, J. (2020). Historia del pueblo mapuche. Siglos XIX y XX. _Historia del pueblo mapuche. Siglos XIX y XX_. Editorial lom. 224\n",
    "\n",
    "Carlos, A. M., & Lewis, F. D. (2012). Smallpox and Native American mortality : The 1780s epidemic in the Hudson Bay region. _Explorations in Economic History_. 49(3), 277‑290.\n",
    "\n",
    "Crosby, A. (1976). Virgin Soil Epidemics as a Factor in the Aboriginal Depopulation in America. _The William and Mary Quarterly_. 33(2) p. 289‑299.\n",
    "Elderd, B. D., Dwyer, G., & Dukic, V. (2013). Population-level differences in disease transmission : A Bayesian analysis of multiple smallpox epidemics. _Epidemics_. 5(3), 146‑156.\n",
    "\n",
    "Fenn, E. A. (2002). _Pox Americana : The Great Smallpox Epidemic of 1775-82_ (1st éd.). Hill and Wang.\n",
    "\n",
    "Fenner, F., Henderson D.A., Arita I., Jezek Z., Ladnyi I.D. (1989). _Smallpox and Its Eradication_ (History of International Public Health, No. 6) (v. 6). World Health Organization.\n",
    "\n",
    "Frederiksen, H., & Motameni, S. T. (1957). The 1954–1955 Epidemic of Smallpox in Tabriz. _The American Journal of Tropical Medicine and Hygiene_. 6(5), 853‑857.\n",
    "\n",
    "Hughes, A.L., Irausquin, S., Friedman, R. (2010). The evolutionary biology of poxviruses. _Infection, Genetics and Evolution_. Volume 10, Issue 1, 50-59.\n",
    "\n",
    "Koch, A., Brierley, C., Maslin, M. M., & Lewis, S. L. (2019). Earth system impacts of the European arrival and Great Dying in the Americas after 1492. _Quaternary Science Reviews_. 207, 13‑36\n",
    "\n",
    "Mack, T. M., Thomas, D. B., & Khan, M. M. (1970). Variola Major in West Pakistan. _Journal of Infectious Diseases_. 122(6), 479‑488.\n",
    "Newson, L. (2001). Pathogens, Places and Peoples. Dans Technology, Disease and Colonial Conquests, _Sixteenth to Eighteenth Centuries_. Vol. 2. Illustrated edition. 167‑210.\n",
    "Razzell, P. (1977). _The Conquest of Smallpox_. Caliban Books\n",
    "\n",
    "Rojas, F. C., Araya, A. D., & Ramírez, D. C. (2017). Tras los pasos de la muerte. Mortandad en Tacna durante la Guerra del Pacífico, 1879-1880. _Historia (Santiago)_. 50(2), 399‑441.\n",
    "\n",
    "Stewart, T. D. (1960). A Physical Anthropologist’s View of the Peopling of the New World. _Southwestern Journal of Anthropology_. 16(3), p. 262.\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    " \n",
    "### Sitography :\n",
    "\n",
    "Krahn, A.-M., Lorenz, C., & Moore, E. (2000). _The Smallpox Epidemic of 1862 (Victoria BC)--Overview and Timeline_. http://web.uvic.ca/vv/student/smallpox/overview/index.html \n",
    "\n",
    "Lange, G. (2004, April 2). _Smallpox Epidemic of 1862 among Northwest Coast and Puget Sound Indians_. HistoryLink.org. Retrieved : 04/12/2020. From https://www.historylink.org/File/5171#:~:text=There%20is%20evidence%20that%20the,resident%20perished%20from%20the%20disease.&text=These%20two%20reports%20were%20not,Sound%20papers%20that%20have%20survived. \n",
    "\n",
    "Swanky, S. (2012, June 10). _June 10th, 1862 and the Seizure of British Columbia_. shawnswanky.com. Retrieved : 02/12/2020. From http://www.shawnswanky.com/articles/canadas-war/june-10th-1862-and-the-seizure-of-british-columbia-from-first-nations/ \n",
    "\n",
    "Wikipedia contributors. (2020, December 7). _History of smallpox_. Wikipedia. Retrieved: 07/12/2020. From https://en.wikipedia.org/wiki/History_of_smallpox?fbclid=IwAR3EJ7hq_fI_dna569JeRtiwkh2T4Uu-H2EV0UpsWAQQiXYyz3ZuqZggkto \n",
    "\n"
   ]
  }
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