salemNotebook.ipynb

{
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  {
   "cell_type": "markdown",
   "id": "4ea303a8",
   "metadata": {},
   "source": [
    "# EDA of the 1692  Salem Witch Trials\n",
    "I found this data set on Kaggle, uploaded by Rachel Tatman, who credits Professor Richard Latner of Tulane University for making this material available. There are 8 .csv files providing quantitative data listing names of all 152 accused, focusing on the geographic spread of the outbreak, the socio-economic conditions of the populace, and the chronology of events.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "169a44c6",
   "metadata": {},
   "source": [
    "While vetting this data set for my python project, two files in particular caught my eye: <b>a Pro Parris file, and an Anti Parris file.</b> Two petitions signed in 1695, <i>two years after</i> the end of the outbreak. The first was the Anti-Parris Petition, signed by 85 villagers.  Their intent was to strip the local minister, named Samuel Paris of his job and titles.  The responding petition was Pro-Parris, and contained 105 signatures. \n",
    "\n",
    "In the year <i>before the outbreak,</i> the villagers decided to stop paying taxes, as the good Rev's wages were drawn from them.  They revoked his title to the parish estate, and refused to attend his services. This was not an unusual tactic for the village, as they had sent four Puritan Ministers packing in similar fashion before Paris ever arrived.  Such was the contentious background of this entire episode of colonial history.\n",
    "\n",
    "<b>I focused a lot of my time in the Tax Data Set, as this set had gender, church affiliation and tax payments of each villager over the duration of Samuel Parris's tenure, whether they paid taxes or not.</b>\n",
    "\n",
    "Salem was notoriously cantankerous. There was friction between Salem and the other townships and churches.  The Puritans didn't like Catholics or Quakers, and according to the historical record, Salem Villagers were a litigious group on the whole.\n",
    "\n",
    "Samuel Paris was the Nexus point of the outbreak. As fate would have it, he was the head of the first household to produce an accusation of witchcraft. Her name was Tituba Indian (1).  An enslaved woman that Samuel purchased while still living in Barbados.  Samuel's children accused her of longtime magical exploits, to which she confessed when 'questioned'.  Her husband, John Indian joined forces with Samuel's children and began accusing other villagers of witchraft.  And it just sort of bloomed outwards from there.  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff88bc4c",
   "metadata": {},
   "source": [
    "### It stopped as quickly as it began In October 1692. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1fb0f3f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fd4154e2460>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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a2Utm9uqhm6eViQDPbTiAGVw+09/+36FmjMmiqaOX2rYev0sZltKycszsA7dAejb3Ld1C67pXKMsfdcTnnOhtuGaOyaKzd4C9TZ0efuXRb7idWH8EfgPcB2iFZYmYFzYdYH5ZLkVZx1+HNlJOK85g2fZ6Nte0MTo7euo6mqp9ldz10rYPHH9rZyPv7mniS1/4LHnf/LuwnOu2YfYjj88fRWpSAlsPtDEhQl0f0Wi4LeB+59w9zrl3nXOrDt08rUxGvP0tXWypaeOymf5efDtcSmKASUUZbKttp38g6Hc5J6Wnf4C1VS1MKhxF3gms8xsugQTjtOJMdtZ3jOhdM4YbwH82sy+bWYmZ5R26eVqZjHivbq0D4JJp0RXAADNLsujtD8bsrK4NVa309gc58ySXmgyH6aOzGAg6dtTF5r9hOAy3C+Lm0MfvDjnmgInhLUfkL5ZsqaU8P51JhdH3J+q43DSyUhPZXNMWc4vL9A8EWV3ZQnleOsU+du0UZ6WQk57Elpp2Zo6JzPKi0WZYLWDn3IQj3BS+4pnO3n5W7Gxk8bTiqBxpYGZML8liX1MXbTG2+++m6ja6+gZ8bf1C6N9wdBb7W7pG3I4jhwx3KvKnj3TzujgZud7c0Uhvf5DF071ZlyAcDi3XuKUmdsazDgQdqyqbKclOZUyO/xcQp40eXN4zXsZVn6jh9gGfOeR2PnAH8FGPahLhc//nboI9HZw3tSQsw6PCMXTqcNlpSYzLTWNLTXvMLC6zrbad9u5+zhyfFxV/WWSlJTE2J41ttSMzgIfVB+yc+9rQx2aWDfzek4pkxAsGHcHi6UwvLeZbL2zy/HzDHTp1JDNLsnhxcy1VzV2U5qWHsarwCzrHyj1NFGQkMz4/emqdXJTB69vraero9WVEhp9OdjnKTiC8KzaLhGysbiUxMz8mxodOLsogOTEhJhbo2Vl/kObOvqhp/R4yuTADIGZHlJyKYbWAzezPDI56gMFFeKYDj3pVlIxsS7bU4VyQ8fnRH8CJgQSmjc5kU3Ub3X0DpCZF5xpVzjlW7mkmJy2JyUUZfpfzVzJSExmdlcrOuoMs9PnCYKQNdxjavw653w/sdc5VeVCPCK9vr6e3ejtpyd6vzhUOs8Zks76qla0H2pnr8XKOJ6uyqZO69p73t4mPNpOLMnhjRwOtXX1kp42cFdKGOwztdWArgyuh5QLxuzGW+Kqls5f1VS107V7tdynDVpiZQlFmChurW6P2Ytx7e5rJSEmM2jHLh1rlI2Xn6UOGOwztk8C7wCeATwLvmJmWo5SwW7GzkaCD7j2xE8Aw2ApuPNhLbXv0LdCTMnYG+1u6mF+eG5Zt5r2QnZZEYUbKiJsVN9yLcP8AnOmcu9k592lgIfAD78qSkWp5RT2ZKYn0VG/3u5QTctroDBITjE1RuGln9jmfJC0pwMwx0dn6PWRS0ShqWrs52NPvdykRM9wATnDO1Q153HgCrxUZFuccy7Y3cO7kfHCxtchNSmKAKcWDC/T09kdP7Rv3t5I2aQHzynJICkT3j+yh0RA7R1AreLj/Iy+Y2YtmdouZ3QI8CzznXVkyEu1q6GB/SxcXnFbodyknZdaYbPoGHBV10TOp4J7XdhLs6WDOuOhfayE/Y3BtiN0N8bfp6dEcM4DNbLKZLXLOfRf4D2AOcDrwFnBvBOqTEWT59noALpgSmwFckp1KXnpy1IwJ3ll/kOc21tC+6hlSEqNzeNzhJhSMoqq5K6r+ivDS8VrAdwPtAM65x51ztznnvsVg6/fuY73QzErNbKmZbTGzTWb2jdDxPDN72cwqQh9zT/3LkHiwvKKB8fnpUT+j7GjMjJljs6hp7abhoP8X4/596U5SEhNoW/W036UM24T8UQw4x77mkbFTxvECeLxzbv3hB51zK4Hxx3ltP/Bt59x04GzgK2Y2A7gdWOKcmwIsCT2WEa63P8hbuxo5P0Zbv4dML8kiMcFYt6/F1zr2Nnbw5Nr9fOqscoKd0Xdh8GjG5KSRHEgYMd0QxwvgYy2XlHasFzrnapxzq0P324EtwFjgGuDB0NMeBK4dVqUS11ZXNtPZO8D5Uwr8LuWUpCUFmDY6ky0H2unq82+nh18v3UFigvHFC2Jr1dhAglGen86eho6oHVMdTscL4PfM7AuHHzSzzwHD3pLIzMYD84B3gGLnXA0MhjRwxPUGzexWM1tpZivr6+uHeyqJUcu21xNIMM6ZlO93Kafs9NIcBoKOjT4NSdvX1Mnjq/dz48KyqNpLb7gmFIyio3eA+igcUx1ux5uK/E3gCTP7FH8J3AVAMnDdcE5gZhnAn4BvOufahrsIiHPuXkIX+hYsWBD/vwpHuOUVDZxRlkNmauxPQy3ISKE0N431Va2cURb5yQ///toOEhKML10Uua3mw6k8tFLb7oaOmPwFciKO2QJ2ztU6584FfgjsCd1+6Jw7xzl34HhvbmZJDIbvw865x0OHa82sJPT5EqDuaK+XkaHxYA8bq1tjdvTDkcwty+FgT3/Ep9ZWNXfy2Koqbjiz1Nfthk5FevLg4jy7G+O/H3i4a0Esdc79W+j26nBeY4NN3d8BW5xzdw351NP8ZY+5m4GnTqRgiT9v7mzEOTg/Rsf/HsmE/FFkpyWxprIlon2Zd728HbPYbf0eMqFgFLVtPXTE+aw4L6fGLAJuAi4xs7Wh21XAncClZlYBXBp6LCPY8u31ZKclMXts9E8WGC4zY15pDgfauqlq7orIOTdXt/HEmv18ZtF4SrKPeY086h1aC3pvY3wPRxvucpQnzDn3BnC0zq/FXp1XYotzjuUVDZw3uSBqF4o5WTPHZPHe3ibe3t3IuNw0zxdB/78vbCUrNYkvXzjZ0/NEQkFGMunJAfY2dTAjytewOBXRPTlc4t6OuoMcaOuO+eFnR5IYSODM8jyqW7rZ53EreMWOBl7fXs9XL55MdnrsX8g0M8rz0qls6ozr4WgKYPHV66Hpx/HU/zvUzDFZZKQk8s6uRs+CJBh0/OT5rYzNSeOmc8o9OYcfyvLT6e4LUhfHw9EUwOKr5RUNTCocxdic2O6zPJrEQAILynOpbvWuFfzIe5Vs2N/Kdy+fGrVbIp2MstCU9HjuB1YAi2+6+wZ4Z3fsTz8+npljB1vBb+0Mfyu4rq2bO5/fyrmT8rlm7piwvrff0pMTKcpMYW9T/A5HUwCLb1btbaa7L8gFp8Vf/+9QiQkJnDMxnwNt3Ww9EN6lKn/458309Af5l+tmR9VOx+FSlpfOgdZuevr9m9btJQWw+GZZRT1JAeOsCbE//fh4ppdkUpyVwhs7GrDk8HS3vLq1lmc31PC1iye/P2wr3pTnpxN0RGwoX6QpgMU3y7c3ML88l1Epno2GjBpmxkVTi+jqHSD3os+e8vs1d/TyD09sZEpRBl+8MLYnXRxLSXYaSQGL235gBbD4or69h801bXHf/zvU6KxU5pXlkDnvSpZXnPwCU845vvvYehoO9nDXJ+eSnBi/P8aBBGNc7uBwtHgUv/9zEtXe2DEYQBfG6fCzozlnYj59jfv41v+s5UBr90m9x69e3cErW2r53pXTmR0DWw2dqvK8dFq7+mjp7PW7lLBTAIsvlm9vIG9UMjNK4neW05EkBhKof+LHdPYO8OWHV9HVe2IXl55au5+fvbydj80by2cWjfemyChTFlodbW8ctoIVwBJxzjmWhaYfJ8TZ9OPh6Gvcx88+cTpr9rXwpYdXDXv/s2fWV3Pbo+tYOCGPn3w8Pkc9HElOWhJZqYlUxmE/sAJYIm7rgXYaDvbE5fTj4bpydgk/vm42r22r529/9w5NHUf/8zoYdPx66Q6+9sga5pflcv8tZ8bMJpvhYGaU5aezr7mTgWB8TUtWAEvEHboANZIuwB3JjQvL+MUNc1m7r4XLfv46f3i3ku4h2xgFg463dzVy/W9W8NMXt/HR08fwwGfPJGMEjBo5XHneKPoG3En3m0erkfc/Kb5btr2B04ozGJ0dmwuGh9M1c8cyuSiDHzy5kdsf38A/P7uF6SWZpCQG3l+oqDAzhZ9eP4fr548bMd0OhyvNS8MM9jZ1MDY3fqatK4Alorp6B3h3TxOfPjt+Fo05VTPHZPPY353LW7saeXZDDTvrDnKwp58F43NZPL2Iy2aMHhFjpY8lJTHA6KxUKps6OTeOhj2P7P9Vibh39zTR2x+M29XPTlZCgrFocgGLJo/cfvHjKctL553dTXT3DcTNokPqA5aIWr69nuTEBBaOz/O7FIkxhzbr3BdHw9EUwBJRyysaWDg+j7Tk+GjBSOQUZ6aSnJgQV7PiFMASMbVt3WyrbR/Rw8/k5CUkGKW5aeyNo10yFMASMcu2a/iZnJqyvHTau/tp6erzu5SwUABLxCyraKAwM4XpJZl+lyIx6tAuGfEyK04BLBExEHS8UVHP+VMKRuxYVjl12YemJcdJP7ACWCJi4/5Wmjv7RtzqZxJeZkZZXjpVzV1xMS1ZASwRcaj/9zyNc5VTVJafTu9AkNq22J+WrACWiFhWUc+ssVnkZ6T4XYrEuNLcdIz4WJ5SASyea+vuY3VlCxdo9IOEQWpSgOKs1LiYkOFZAJvZ/WZWZ2Ybhxy7w8z2m9na0O0qr84v0WPFjkYGgo4L1P8rYXJot2RLie3NSL1sAT8AXHGE4z93zs0N3Z7z8PwSJZZV1DMqOcAZZbl+lyJxoiwvHQekls3xu5RT4lkAO+eWAU1evb/EBuccy7bXc86kgrjePFIia3R2KkkBI23CPL9LOSV+/ER81czWh7oojtokMrNbzWylma2srz/5HWTFX7sbOqhq7uLC0zT6QcLn0G7JqePn+l3KKYl0AN8DTALmAjXAz472ROfcvc65Bc65BYWF6juMVYeGn6n/V8KtLC+dpNwxMT0rLqIB7Jyrdc4NOOeCwG+BhZE8v0TesooGyvPTKc+P7YslEn3KQ9OSl++I3b+QIxrAZlYy5OF1wMajPVdiX0//AG/tbNTwM/FETnoS/W11LN/e4HcpJ82zHTHM7BHgIqDAzKqAfwQuMrO5gAP2AF/06vziv1V7munqG1D3g3jCzOjavYYVRWPoHwiSGIi9i7yeBbBz7sYjHP6dV+eT6PN6RT2JCcY5k/L9LkXiVPeetbSdfjnr97fG5DDH2PuVITFj6dY6Fk7IG5HbqEtkdO9dhxm8URGb3RAKYPHEvqZOttce5JJpRX6XInEs2NXGrDHZLK+IzQtxCmDxxNJtdQBcrAAWj503pYA1lS20d8feLhkKYPHEq1vrGJ+fzsQCDT8Tb50/pYD+oOPtXbE38VYBLGHX2dvPip2NXDytSLtfiOfml+eSlhTgjRjshlAAS9it2NFIb39Q/b8SESmJAc6amMfyGLwQpwCWsHt1Wx2jkgMsnJDndykyQpw3uYBdDR1UNcfWtGQFsISVc46lW+s4b0oBKYkBv8uREeLQZJ9YG46mAJaw2nqgnZrWbnU/SERNKcqgOCuF5TsUwDKCvbo1NPxsqgJYIsfMOG9yIW/uaIip3ZIVwBJWr26tY/bYbIqyUv0uRUaY86cU0NLZx6bqVr9LGTYFsIRNc0cvayqbNflCfLFo8uCi/7E0GkIBLGHz+vZ6gg4WK4DFB4WZKUwvyYqpackKYAmbJVvrKMhIYfbYbL9LkRHqgikFrNrbTEdPv9+lDIsCWMKip3+A17bWsXhaEQkJmv0m/jh/SiF9A463dzX6XcqwKIAlLFbsbKS9p5/LZxX7XUr0swTMLGK3keTMCbmkJwfeH40T7bRQq4TFS5sOMCo5wLmTtPvxcbkgd720LWKnu+2yqRE7l99SEgMsmlzA0q11OOei/heQWsByygaCjpc313LRtCJSkzT7Tfx1ybQiqlu72Vbb7ncpx6UAllO2urKZhoO9XD5ztN+liLw/CSgWuiEUwHLKXtx4gORAAhdP1eab4r/R2anMKMnita3RPxxNASynxDnHi5sPsGhyPpmpSX6XIwIMdkOsqmymtTO6d8lQAMsp2VLTzr6mLnU/SFS5eFoRA0HH61E+KUMBLKfkhU0HMIMPzdDwM4kec0tzyBuVzNIo7wdWAMtJc87xzPpqzp6QT0FGit/liLwvkGBceFohr22ri+rV0RTActI217Sxq76Dq08v8bsUkQ/40PRimjv7WLW32e9SjkoBLCftmfU1BBKMK2cpgCX6XDi1kORAAi9tOuB3KUflWQCb2f1mVmdmG4ccyzOzl82sIvQx16vzi7cOdT+cOymfvFHJfpcj8gEZKYksmpzPS5trcS46uyG8bAE/AFxx2LHbgSXOuSnAktBjiUHrq1rZ19TFR+aM8bsUkaO6bOZoKps6o3ZWnGcB7JxbBjQddvga4MHQ/QeBa706v3jrmfXVJAVMw88kqi2eXoQZvLix1u9SjijSfcDFzrkagNDHo67cbWa3mtlKM1tZXx/dY/lGmmDQ8ez6Gi6YUkh2uiZfSPQqykzljLJcXtocnf3AUXsRzjl3r3NugXNuQWGhprhGk9WVzVS3dmv0g8SEy2cWs6m6jarmTr9L+YBIB3CtmZUAhD5G9yhpOaI/rd5PWlKAS2eo+0Gi36Hv05c3R183RKQD+Gng5tD9m4GnInx+OUXdfQM8s76aK2aNJiNFy0lL9JtQMIrTijN4MQqHo3k5DO0R4C1gqplVmdnngDuBS82sArg09FhiyMuba2nv7ufjZ4zzuxSRYbtiVgnv7m6irr3b71L+ipejIG50zpU455Kcc+Occ79zzjU65xY756aEPh4+SkKi3OOrqyjJTuWcSfl+lyIybB+ZU0LQwfMboqsVHLUX4ST61LV3s6yigWvnjSWgjTclhkwpzmRqcSbPrK/2u5S/EtcBXFpWHrGND0vLyv3+cj331JpqBoJO3Q8Sk66eU8J7e5qpae3yu5T3xfVVlKp9lRHb/DDeNz50zvGn1VWcXprD5KIMv8sROWEfnlPCz17ezrPra/j8+RP9LgeI8xawhM+G/a1sPdDO9WeM9bsUkZMysTCDGSVZPLO+xu9S3qcAlmF5+O1K0pICXDNPASyx6+rTS1i7r4V9TdExKUMBLMfV2tXH0+uquWbuGLK075vEsKtnDy4e9eyG6GgFK4DluJ5cs5+uvgE+dVb8X2iU+FaWn868shyeWL0/KpaoVADLMTnnePidvcwZl83scdl+lyNyyq6fP45tte1s3N/mdykKYDm2lXub2V57kE+dVeZ3KSJhcfWcMSQnJvDYqn1+l6IAlmN7+O29ZKYk8pHTtfC6xIfstCQum1HMU+uq6ekf8LUWBbAcVW1bN89uqOHj88eRnhzXQ8ZlhLl+/jhaOvt837ZeASxH9eCKPfQHHZ9ZNN7vUkTC6vwphRRnpfDYqipf61AAyxF19vbz8DuVXD5jNOX5o/wuRySsAgnGdfPGsXRbPfXtPb7VoQCWI/rjyipau/r4wgUT/C5FxBPXzx/LQHBwir1fFMDyAQNBx+/e2M28shzml+f5XY6IJyYXZXLWhDweensvA0F/xgQrgOUDXt58gMqmTr4QJQuWiHjl0+eMp6q5i9e3+3MxTgEsf8U5x7+/tpOyvHRtOS9x77KZxRRlpvBfb+315fwKYPkrS7fVsb6qla9ePFmLrkvcSwokcOPCMl7fXs/exo6In18BLO9zznH3KxWU5qVxnZadlBHif51VRsCMh96OfCtYASzve3XrYOv3axdPISmgbw0ZGYqzUrl85mgeXVlFV29kZ8bpp0yAv7R+y/LS1fqVEeeWReNp7erj0ZWRXR9CASwAvLKljg37W/nqJZPV+pURZ0F5LvPLc7l32S76BoIRO69+0oS+gSA/eX4LEwtGcZ12vJARyMz48kWT2N/SxdNrI7dzsgJY+O93KtlV38H3r5qu1q+MWJdMK2La6Ex+8/pOghGamKGfthGutauPu1/ZzrmT8lk8vcjvckR8Y2Z86aJJVNQd5JUttRE5pwJ4hPv10h20dPXxDx+ejpnG/crI9uHZJZTmpfHr13ZGZMsiXwLYzPaY2QYzW2tmK/2oQWB3QwcPvLmH688Yx8wx2m5IJDGQwJcvmsy6fS28vNn7VrCfLeCLnXNznXMLfKxhxHLO8f3HN5CSlMB3L5/qdzkiUeMT88cxsWAUP31xG/0ej4hQF8QI9diqKt7a1cjtV06jKCvV73JEokZiIIG/v2IqFXUHeXz1fk/P5VcAO+AlM1tlZrce6QlmdquZrTSzlfX19REuL741HOzhX57bwpnjc7nxTG22KXK4y2eOZm5pDj9/ZTvdfd7NjvMrgBc5584ArgS+YmYXHP4E59y9zrkFzrkFhYWFka8wjv3TM5vp6OnnJx+bTYIW3BH5ADPj9iunUdPazQMr9nh2Hl8C2DlXHfpYBzwBLPSjjpHoz+uqeWptNV+5eDKTizL9Lkckap09MZ/F04r4tyUVHGjt9uQcEQ9gMxtlZpmH7gOXARsjXcdItK+pk+8/sYF5ZTl85eLJfpcjEvX+8SMz6Q86fvTMJk/e34+9xouBJ0JjThOB/3bOvRDukyz+2WuM+fw9/OG9SlITA+RlJFOUmcLorFRy0pPDfbqo1z8Q5Jv/sxYc/PKGeZrxJjIMZfnpfH3xFH764jaWbq3j4mnhnawU8QB2zu0CTvf6PGdNzGf98j2kTplKV98A66ta39/3KX9UMpOLMpg6OpPcERLGv1xSwaq9zfzihrmU5qX7XY5IzPjC+RN5Ys1+fvDURl6eeCFpyYGwvXfcNoN+fN1sGp76v1w7byw3LizjSxdO4n8tLOPC0wpJSUrgnd1N/Ndbe3lq7X4qmzojMuvFLy9sPMAvX93B9fPHcc1cLbYjciKSExP4l2tnUdXcxa+WVoT1vf3ogvBFIMEozEyhMDOFuaU5dPT0s7G6lXX7WnlizX6KMlNYNLmAsjhrHW6paeO2R9cytzSHf7521km/T2lZOVX7KsNYmUgYWELEptBnzv8Iv3yqiu9uWR229xwxAXy4USmJnDUhn/lluWw90M67e5p4Ys1+yvLSOX9KAQUZKX6XeMoaD/bw+QdXkpWaxL03zSc16eT/dKraV8ldL20LY3XHdttlmp0nw+CCMf19GbddEMOVGEhg1thsPn12OedPKaCurZv/freS5RX19PZHbmHmcGvv7uMzD7xHw8Ee7v30fM12E4lCI7YFfLjEQAJnlOUyvSSLN3c0sLqyhe21B7nwtEImFY6KqZXCunoH+NwDK9lc3cZ/3DSfOeNy/C5JRI5gxLeAD5eWFOBD04v5xPxxpCYl8OyGGp5eV01bV5/fpQ1LT/8AX3xoFSv3NvHzv5nL4unFfpckIkehAD6KMTlp3HhmGedPKWB/SxcPvbOX1ZXNEVsp/2S0d/fxmf98j2Xb67nzY3P4yOlj/C5JRI5BXRDHkJBgnFGWy+TCDJZuq2N5RQPbDrSzeFpR1PWp1rV385n/fI9tB9q565On87Ezxvldkogch1rAw5CVlsRHTx/DlbNGc7Cnnz+8t4/lFfUR3T31cKVl5ZgZZkZy0QTmfechNuypY/8ffsDH55e+/7lw3UQk/NQCHiYz47TiTMrz0nlj5+BFuoq6g1w8tYgJBaMiXs+hYWGbqltZuq2e1KQErp49htFXPuLJ+TQsTCT8FMAnKCUpwOJpxUwbncWrW+p4el01U4oyCGRFdkPLhNQMXtx0gK0H2inNTeOKWaNJT9Z/p0gsURfESRqbk8aNZ5Vy9sQ8djd0MPYL/8E/P7OZls5eT8/rnOPJNfsZ8/nfsK22nYUT8rh23liFr0gM0k/tKUhMSOCsCfnMKMnil/f8lt8lJfHIu5V86uxyPnfeBIrDeKHOOceKnY3c/cp23tvTTH9rLTddPIfCzNifsScyUimAwyAzNYnG53/Bm/f/E79euoP7lu/igTf3cNXs0Xx8/jjOnVRA4CR3nujuG+CVLbU88OYeVu5tpjgrhX++dhY3nftRCm/aEuavREQiSQEcRlNHZ/LLG+fxncumct8bu3hyzX6eXFtNSXYqF00t4rzJBZw9MY/846wzcaC1m3f3NPFmRQPPbayhvbufMdmp/OiamXxyQSmpSQFucrE7TVpEBimAPVCWn86PrpnF96+azitbanlqbTV/XlfNI+8OriaWNyqZ8fnplGSnkRQwkgIJHOzp50BbN9UtXdS29QAwKjnA5bNG8/EzxnH2xPyTbkWLSHRSAHsoNSnA1XPGcPWcMfQPBFlX1cqqvU3sbuhgd0MHWw+00R909PYHSU8OUJKdxnmTC5k5Joszx+cxvSSTRO1cIRK3FMARkhhIYH55LvPLc/0uRUSihJpXIiI+UQCLiPhEASwi4hMFsIiITxTAIiI+UQCLiPhEASwi4hMFsIiIT3wJYDO7wsy2mdkOM7vdjxpERPwW8QA2swDwa+BKYAZwo5nNiHQdIiJ+86MFvBDY4Zzb5ZzrBf4AXONDHSIivjLnIrvNupldD1zhnPt86PFNwFnOua8e9rxbgVtDD6cC2yJa6PEVAA1+F3ESVHdkxWrdELu1R2PdDc65Kw4/6MdiPEdaU/EDvwWcc/cC93pfzskxs5XOuQV+13GiVHdkxWrdELu1x1LdfnRBVAGlQx6PA6p9qENExFd+BPB7wBQzm2BmycANwNM+1CEi4quId0E45/rN7KvAi0AAuN85tynSdYRB1HaPHIfqjqxYrRtit/aYqTviF+FERGSQZsKJiPhEASwi4hMF8AmK1WnUZlZqZkvNbIuZbTKzb/hd03CZWcDM1pjZM37XciLMLMfMHjOzraF/93P8rmk4zOxboe+RjWb2iJml+l3TkZjZ/WZWZ2YbhxzLM7OXzawi9DGqN2FUAJ+AGJ9G3Q982zk3HTgb+EoM1f4NYIvfRZyEXwAvOOemAacTA1+DmY0Fvg4scM7NYvBC+Q3+VnVUDwCHT264HVjinJsCLAk9jloK4BMTs9OonXM1zrnVofvtDIbBWH+rOj4zGwd8GLjP71pOhJllARcAvwNwzvU651p8LWr4EoE0M0sE0onScfrOuWVA02GHrwEeDN1/ELg2kjWdKAXwiRkL7BvyuIoYCLHDmdl4YB7wjs+lDMfdwN8DQZ/rOFETgXrgP0PdJ/eZ2Si/izoe59x+4F+BSqAGaHXOveRvVSek2DlXA4ONDqDI53qOSQF8YoY1jTqamVkG8Cfgm865Nr/rORYzuxqoc86t8ruWk5AInAHc45ybB3QQ5X8OA4T6TK8BJgBjgFFm9rf+VhW/FMAnJqanUZtZEoPh+7Bz7nG/6xmGRcBHzWwPg909l5jZQ/6WNGxVQJVz7tBfGY8xGMjR7kPAbudcvXOuD3gcONfnmk5ErZmVAIQ+1vlczzEpgE9MzE6jNjNjsD9yi3PuLr/rGQ7n3Pecc+Occ+MZ/Ld+1TkXE60x59wBYJ+ZTQ0dWgxs9rGk4aoEzjaz9ND3zGJi4OLhEE8DN4fu3ww85WMtx+XHamgxK8anUS8CbgI2mNna0LHvO+ee86+kuPc14OHQL+tdwGd8rue4nHPvmNljwGoGR86sIUqn9prZI8BFQIGZVQH/CNwJPGpmn2Pwl8kn/Kvw+DQVWUTEJ+qCEBHxiQJYRMQnCmAREZ8ogEVEfKIAFhHxiQJYPGNmzsx+P+RxopnVn+yqZqHVxb485PFFx3ovMys0sz4z++LJnC9czGyumV015PFHY2klPfGOAli81AHMMrO00ONLgf2n8H45wJeP96QhPgG8Ddx4CucMh7nA+wHsnHvaOXenf+VItFAAi9eeZ3A1MxgMwkcOfSK0duuTZrbezN42szmh43eE1np9zcx2mdnXQy+5E5hkZmvN7KehYxlD1tx9ODR7iyHn+zYwLrTM4qHzfjp0znWHWuhmVmxmT4SOrTOzc81s/GFrzX7HzO4I3f+6mW0Ovc8fQscWmtmK0OI7K8xsamgSxo+AvwnV/TdmdouZ/Sr0mnIzWxJ6nyVmVhY6/oCZ/TL0PrvM7Ppw/GdIlHHO6aabJzfgIDCHwXUQUoG1DM5ceib0+X8D/jF0/xJgbej+HcAKIAUoABqBJGA8sHHI+18EtDK4JkcC8BZwXuhzpUBF6P6PgdtC92cC24CC0OO80Mf/YXCBIhic5Zh9hPN9B7gjdL8aSAndzwl9zAISQ/c/BPwpdP8W4FdD3uf9x8CfgZtD9z8LPBm6/wDwx9DXNYPBZVB9/z/VLbw3tYDFU8659QwG2Y3A4dOezwN+H3req0C+mWWHPvesc67HOdfA4IIqxUc5xbvOuSrnXJDBgB8fOn4D8Gjo/h/4SzfEJcBjoffFOdc05Pg9oWMDzrnW43xp6xmcZvy3DE7ZhcHQ/mOo1fxzBsP+eM4B/jt0//cM/psc8qRzLuic28zRv36JYQpgiYSnGVxj9pHDjh9rec+eIccGOPq6JUd73o3ALaGV1J4GTjezKaFzDnf+fT9//TMydGueDzO4O8p8YFVo8fJ/Apa6wZ0kPnLY84draG1Dv7Yj/VtJjFMASyTcD/zIObfhsOPLgE/B4IgGoMEde43idiDzeCcLrUA2yjk31jk33g2upvYTBlvFS4BPmll+6Ll5oZctAb4UOhYI7WhRCxSZWb6ZpQBXhz6fAJQ655YyuFh8DpDBYAv40EXGW4ZZ9wr+suXPp4A3jvf1SfxQAIvnQl0EvzjCp+4AFpjZegYvsN18hOcMfZ9G4E0b3Czyp8d46o3AE4cd+xNwoxtcve5fgNfNbB1waGnObwAXm9kGYBUw0w2uh/sjBncOeQbYGnpuAHgo9Nw1wM/d4HZD/w/4iZm9GXrOIUuBGYcuwh1W19eBz4T+DW4K1SEjhFZDExHxiVrAIiI+UQCLiPhEASwi4hMFsIiITxTAIiI+UQCLiPhEASwi4pP/D4kCxORKjlxFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(data=Accused, x='MonthAccusation', kde=True)# reveals a bimodal non symetric shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "346685d4",
   "metadata": {},
   "source": [
    "# Questions I will be exploring\n",
    "1. What % of the Accused were Executed? \n",
    "2. On average, how long from accusation till execution? \n",
    "3. Which village had the most, the least accused?\n",
    "4. Which village had the most, the least executed?\n",
    "5. Is there a correlation between amount of taxes paid and support of Paris?\n",
    "6. Is there a correlation between Church affiliation and support or opposition to Paris?\n",
    "7. What is the profile of a Paris supporter?  Opposer?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1b86db3",
   "metadata": {},
   "source": [
    "# Hypothesis\n",
    "<p><b>Null Hypothesis:</b> Membership in the Salem Village Church <b>IS</b> a predictor of support for the minister at the centre of the witch trials.</p>\n",
    "<b>Alternative Hypothesis:</b> Membership in the Salem Village Church is <b>NOT</b> a predictor of support."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff7d2c4f",
   "metadata": {},
   "source": [
    "(1) a note on Tituba:\n",
    "The records show Tituba confessed during a beating/torture.\n",
    "Historical research suggests Tituba was a Kalina (or Caribe) woman, named after her tribe from Tibitó.  Tibito is one of the oldest archeological sites in Colombia, with documented human habitation stretching  as far back as  11,700 years.  She was married to an Indigenous man named John Indian, of which records are few."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88920025",
   "metadata": {},
   "source": [
    "# Loading the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a05e4ff3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "from matplotlib import cm\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "efc281af",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colors.ListedColormap at 0x7fd413184160>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#loading colour palette\n",
    "sns.color_palette(\"Set2\", as_cmap=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8f1f423d",
   "metadata": {},
   "outputs": [],
   "source": [
    "Accused = pd.read_csv(\"/.../Salem/Accused-Witches-Data-Set.csv\")\n",
    "# replace NaNs (Not a Number's) with the number zero\n",
    "Accused['MonthExecution'] = Accused['MonthExecution'].fillna(0)  \n",
    "# specifying number of bins\n",
    "num_bins = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "22568d13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/.../Salem'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# directory\n",
    "import os\n",
    "\n",
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d104febb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/.../Salem/Accused-Witches-Data-Set.csv\n",
      "/.../Salem/accused_fig_1.png\n",
      "/.../Salem/accused_fig_3.png\n",
      "/.../Salem/accused_fig_2.png\n",
      "/.../Salem/Untitled1.ipynb\n",
      "/.../Salem/.DS_Store\n",
      "/.../Salem/Salem-Village-Data-Set.csv\n",
      "/.../Salem/index.png\n",
      "/.../Salem/Untitled.ipynb\n",
      "/.../Salem/towns_cleaning.ipynb\n",
      "/.../Salem/Committee-Yearly-Data-Set.csv\n",
      "/.../Salem/Salem - Figures.ipynb\n",
      "/.../Salem/Pro-Parris-Social-Data-Set.csv\n",
      "/.../Salem/Towns-Data-Set.csv\n",
      "/.../Salem/Accused-Witches-Data-Set1.csv\n",
      "/.../Salem/Anti-Parris-Social-Data-Set.csv\n",
      "/.../Salem/the_executed_fig_1.png\n",
      "/.../Salem/salemNotebook.ipynb\n",
      "/.../Salem/Tax-Comparison-Data-Set.csv\n",
      "/.../Salem/Committee-List-Data-Set.csv\n",
      "/.../Salem/the_accused_fig_2.png\n",
      "/.../Salem/executed_fig_1.png\n",
      "/.../Salem/Accused-Witches-Data-Set 3.numbers\n",
      "/.../Salem/the_accused_fig_1.png\n",
      "/.../Salem/.ipynb_checkpoints/salemNotebook-checkpoint.ipynb\n",
      "/.../Salem/.ipynb_checkpoints/towns_cleaning-checkpoint.ipynb\n",
      "/.../Salem/.ipynb_checkpoints/Salem - Figures-checkpoint.ipynb\n",
      "/.../Salem/.ipynb_checkpoints/Untitled1-checkpoint.ipynb\n",
      "/.../Salem/.ipynb_checkpoints/Untitled-checkpoint.ipynb\n"
     ]
    }
   ],
   "source": [
    "# all files\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/.../Salem'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "71dcd623",
   "metadata": {},
   "outputs": [],
   "source": [
    "# loading files\n",
    "accused = pd.read_csv('./Accused-Witches-Data-Set.csv')\n",
    "towns = pd.read_csv('./Towns-Data-Set.csv')\n",
    "village = pd.read_csv('./Salem-Village-Data-Set.csv')\n",
    "committeeL = pd.read_csv('./Committee-List-Data-Set.csv')\n",
    "committeeY = pd.read_csv('./Committee-Yearly-Data-Set.csv')\n",
    "taxC = pd.read_csv('./Tax-Comparison-Data-Set.csv')\n",
    "proParis = pd.read_csv('./Pro-Parris-Social-Data-Set.csv')\n",
    "antiParis = pd.read_csv('./Anti-Parris-Social-Data-Set.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a0800d1",
   "metadata": {},
   "source": [
    "# Reviewing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "245be80b",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(accused.head())\n",
    "print(village.head())\n",
    "print(towns.head())\n",
    "print(committeeL.head())\n",
    "print(committeeY.head())\n",
    "print(taxC.head())\n",
    "print(proParis.head())\n",
    "print(antiParis.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "603ca168",
   "metadata": {},
   "source": [
    "# The Accused "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe3488f8",
   "metadata": {},
   "source": [
    "The accused data set contains 152 records of accused witches. \n",
    "It includes their names, town or village they were from, the month of the accusation brought against them and month of any executions that occurred. Oddly enough, if does not contain gender information for the accused. A scan through the names reveals traditional names of both men, and women."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1488aa7d",
   "metadata": {},
   "source": [
    "### Cleaning\n",
    "NaNs in this data set simply mean there was no recorded accusation in the town bin for the month in question"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "1fa6e239",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('./Accused-Witches-Data-Set.csv', sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "18f120b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b09aa2ad",
   "metadata": {},
   "source": [
    "I used the fillna method to replace the NaNs with 0. This way I can count up the numbers of accused vs executed for further analysis and visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "47763613",
   "metadata": {},
   "outputs": [],
   "source": [
    "#replacing Nan values with numeric 0\n",
    "df['MonthExecution'] = df['MonthExecution'].fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c14cda14",
   "metadata": {},
   "source": [
    "### Measures of Tendancies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "3be40cef",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MonthAccusation</th>\n",
       "      <th>MonthExecution</th>\n",
       "      <th>Sort</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>152.000000</td>\n",
       "      <td>152.000000</td>\n",
       "      <td>152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.039474</td>\n",
       "      <td>1.065789</td>\n",
       "      <td>76.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.752197</td>\n",
       "      <td>2.768486</td>\n",
       "      <td>44.022721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>38.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>76.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>114.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>11.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>152.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       MonthAccusation  MonthExecution        Sort\n",
       "count       152.000000      152.000000  152.000000\n",
       "mean          6.039474        1.065789   76.500000\n",
       "std           2.752197        2.768486   44.022721\n",
       "min          -1.000000        0.000000    1.000000\n",
       "25%           4.750000        0.000000   38.750000\n",
       "50%           5.000000        0.000000   76.500000\n",
       "75%           8.000000        0.000000  114.250000\n",
       "max          11.000000        9.000000  152.000000"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d566bc1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.head(10)  #to check that all NaN's were replaced"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c23a27c",
   "metadata": {},
   "source": [
    "## The outbreak \n",
    "had a swift spring beginning and a sudden autumn ending.\n",
    "This was an intense, and rapid event that played out over a 10 month period.\n",
    "It directly affected 152 individuals, leaving 20 people (17% of the accused) dead.\n",
    "The histogram shows a bimodal pattern. Two periods of increased activity dropping dramaticly in June, and completely in October. "
   ]
  },
  {
   "attachments": {
    "accused_fig_1.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "220a85fc",
   "metadata": {},
   "source": [
    "![accused_fig_1.png](attachment:accused_fig_1.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "678b642e",
   "metadata": {},
   "source": [
    "## The Executed\n",
    "The commencement of executions coincided with the temporary drop of new accusations as seen in the earlier histogram."
   ]
  },
  {
   "attachments": {
    "the_executed_fig_1.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "e04acaa9",
   "metadata": {},
   "source": [
    "![the_executed_fig_1.png](attachment:the_executed_fig_1.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "205bbad6",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "### Questions 1 & 2\n",
    "1. What % of the Accused were Executed? \n",
    "2. On average, how long from accusation till execution? "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a62c54cf",
   "metadata": {},
   "source": [
    "### 1. Execution Rate of the Accused 17.65%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88193835",
   "metadata": {},
   "outputs": [],
   "source": [
    "#calculating % with the counts defined previously\n",
    "Percent = df['MonthExecution'].sum() / df['MonthAccusation'].sum(\n",
    ") * 100\n",
    "print(Percent)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2b8bab7",
   "metadata": {},
   "source": [
    "### 2. Avg Length of time between accusation and execution 173 days"
   ]
  },
  {
   "attachments": {
    "accused_fig_3.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "89ee4b15",
   "metadata": {},
   "source": [
    "![accused_fig_3.png](attachment:accused_fig_3.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "53ec4630",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Accused_date      Execution_date\n",
      "0 1696-01-31 12:00:00 1696-09-30 21:45:00\n",
      "1 1696-02-29 12:00:00 1696-10-07 21:45:00\n",
      "2 1696-03-31 12:00:00 1696-10-14 21:45:00\n",
      "3 1696-04-30 12:00:00 1696-10-21 21:45:00\n",
      "4 1696-05-31 12:00:00 1696-10-28 21:45:00\n",
      "5 1696-06-30 12:00:00 1696-11-04 21:45:00\n",
      "6 1696-07-31 12:00:00 1696-11-11 21:45:00\n"
     ]
    }
   ],
   "source": [
    "#find accused dates and execution dates\n",
    "import datetime\n",
    "from dateutil.relativedelta import relativedelta\n",
    "from datetime import date\n",
    "\n",
    "date1 = pd.Series(pd.date_range('1696-1-1 12:00:00', periods=7, freq='M')) #define 1st variable\n",
    "date2 = pd.Series(pd.date_range('1696-9-30 21:45:00', periods=7, freq='W'))#define 2nd variable\n",
    "df = pd.DataFrame(dict(Accused_date=date1, Execution_date=date2))#define new columns\n",
    "\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "66f21368",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Accused_date      Execution_date  diff_days\n",
      "0 1696-01-31 12:00:00 1696-09-30 21:45:00  243.40625\n",
      "1 1696-02-29 12:00:00 1696-10-07 21:45:00  221.40625\n",
      "2 1696-03-31 12:00:00 1696-10-14 21:45:00  197.40625\n",
      "3 1696-04-30 12:00:00 1696-10-21 21:45:00  174.40625\n",
      "4 1696-05-31 12:00:00 1696-10-28 21:45:00  150.40625\n",
      "5 1696-06-30 12:00:00 1696-11-04 21:45:00  127.40625\n",
      "6 1696-07-31 12:00:00 1696-11-11 21:45:00  103.40625\n"
     ]
    }
   ],
   "source": [
    "#Calculate the number of days between Accused date and execution date\n",
    "df['diff_days'] = df['Execution_date'] - df['Accused_date']\n",
    "df['diff_days'] = df['diff_days'] / np.timedelta64(1, 'D')\n",
    "\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ec59c9b",
   "metadata": {},
   "source": [
    "# Towns Data Set \n",
    "Contains twenty-four columns recording each town with one or more accusations of witch craft.  \n",
    "Each cell lists the month of an accusation represented by its corresponding month number eg. 1 = Jan. \n",
    "It also holds a bin Column containing the range of months of accusations starting with 1 (Jan 1962) to 12 (Dec 1692) This set contains numerous NaNs to be converted to a 0, representing no records of accusations exist for that month, in that town."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed470bdf",
   "metadata": {},
   "source": [
    "# Observations\n",
    "The cluster of accusations engulfed 24 towns & villages with the most popping up in Andover, Salem Village and Salem Town. The average month to be accused was June, the average month to be executed should you be found guilty, was January. It is important to note, the lack of death penalty did not necessarily mean the accused was found innocent. Time served and payments of fines were handed out as per the judgements of the court."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23958647",
   "metadata": {},
   "source": [
    "## Distribution  \n",
    "The frequency of outbreak is concentrated in 2 main sectors: Andover, and Salem (Salem Village , and Salem Town) "
   ]
  },
  {
   "attachments": {
    "accused_fig_2.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "6b04087a",
   "metadata": {},
   "source": [
    "![accused_fig_2.png](attachment:accused_fig_2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "902d2f12",
   "metadata": {},
   "source": [
    "<b> Note,</b> the histogram follows a bimodal pattern, suggesting we are looking at two mirroring outbreaks. The distribution plot above, shows us two major sectors driving the outbreak. "
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "38ef2544",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc1be6a1",
   "metadata": {},
   "source": [
    "### Questions\n",
    "3. Which village had the most, the least accused?\n",
    "4. Which village had the most, the least executed?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d81a1a9",
   "metadata": {},
   "source": [
    "## Andover \n",
    "had the most accused (45), Malden and 6 other towns had one accusation each.\n",
    "## Salem Town \n",
    "had the most executions (4), Wells, Maine and 9 others had one execution each.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c57bc5d",
   "metadata": {},
   "source": [
    "## Each town ranked by number of Accused"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e21cbc06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " Residence \n",
       " Andover               45\n",
       " Salem Town            24\n",
       " Salem Village         15\n",
       " Gloucester             9\n",
       " Reading                7\n",
       " Topsfield              6\n",
       " Haverhill              6\n",
       " Lynn                   5\n",
       " Rowley                 5\n",
       " Ipswich                4\n",
       " Beverly                4\n",
       " Boxford                3\n",
       " Billerica              3\n",
       " Woburn                 3\n",
       " Charlestown            2\n",
       " Boston                 2\n",
       " Piscataqua, Maine      2\n",
       " Wells, Maine           1\n",
       " Salisbury              1\n",
       " Amesbury               1\n",
       " Marblehead             1\n",
       " Manchester             1\n",
       " Chelmsford             1\n",
       " Malden                 1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('./Accused-Witches-Data-Set.csv', sep=',') \n",
    "df.groupby(' Residence ').size().sort_values(ascending=False) #To find out how many accused came from each town"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14c97012",
   "metadata": {},
   "source": [
    "## Each Town ranked by Number of Executions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "03e488cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Residence   MonthExecution  count\n",
      "8       Salem Town              9.0      4\n",
      "2          Andover              9.0      2\n",
      "7       Salem Town              8.0      2\n",
      "9    Salem Village              7.0      2\n",
      "0         Amesbury              7.0      1\n",
      "1          Andover              8.0      1\n",
      "3          Ipswich              7.0      1\n",
      "4       Marblehead              9.0      1\n",
      "5           Rowley              9.0      1\n",
      "6       Salem Town              6.0      1\n",
      "10   Salem Village              8.0      1\n",
      "11       Topsfield              7.0      1\n",
      "12       Topsfield              9.0      1\n",
      "13    Wells, Maine              8.0      1\n"
     ]
    }
   ],
   "source": [
    "df2 = df.groupby([' Residence ', 'MonthExecution']).size().reset_index(name='count').sort_values('count', ascending=False) \n",
    "print (df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "6808bece",
   "metadata": {},
   "outputs": [],
   "source": [
    "#quick and easy value counts\n",
    "#df=pd.read_csv('./Accused-Witches-Data-Set.csv', sep=',')\n",
    "#df.value_counts(subset=None, normalize=False, sort=True, ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0cf3b38",
   "metadata": {},
   "source": [
    "### Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33d6404c",
   "metadata": {},
   "source": [
    "### Replace all NaNs with 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "82387137",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('./Towns-Data-Set.csv', sep=',') \n",
    "df[' Amesbury '] = df[' Amesbury '].fillna(0) \n",
    "df['Beverly'] = df['Beverly'].fillna(0) \n",
    "df['Billerica'] = df['Billerica'].fillna(0) \n",
    "df['Boston'] = df['Boston'].fillna(0) \n",
    "df['Boxford'] = df['Boxford'].fillna(0) \n",
    "df['Chelmsford'] = df['Chelmsford'].fillna(0) \n",
    "df['Charlestown'] = df['Charlestown'].fillna(0) \n",
    "df['Marblehead'] = df['Marblehead'].fillna(0) \n",
    "df['Piscataqua, Maine'] = df['Piscataqua, Maine'].fillna(0) \n",
    "df['Salisbury'] = df['Salisbury'].fillna(0) \n",
    "df['Wells, Maine'] = df['Wells, Maine'].fillna(0) \n",
    "df['Woburn'] = df['Woburn'].fillna(0) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "adbf3258",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Confirming all NaNs have been replaced\n",
    "#df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc839131",
   "metadata": {},
   "source": [
    "### Measures of Tendancies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "58cb3e77",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bin                  5.923077\n",
       " Amesbury            0.088889\n",
       "Andover              7.666667\n",
       "Beverly              0.422222\n",
       "Billerica            0.333333\n",
       "Boston               0.222222\n",
       "Boxford              0.533333\n",
       "Charlestown          0.222222\n",
       "Chelmsford          -0.022222\n",
       "Gloucester           6.333333\n",
       "Haverhill            7.500000\n",
       "Ipswich              3.000000\n",
       "Lynn                 6.200000\n",
       "Malden               5.000000\n",
       "Manchester           9.000000\n",
       "Marblehead           0.111111\n",
       "Piscataqua, Maine    0.177778\n",
       "Reading              6.571429\n",
       "Rowley               8.000000\n",
       "Salem Town           5.173913\n",
       "Salem Village        3.937500\n",
       "Salisbury            0.133333\n",
       "Topsfield            4.000000\n",
       "Wells, Maine         0.088889\n",
       "Woburn               0.333333\n",
       "dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Avg month of accusation vs avg month of execution\n",
    "df.mean()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "71bcfe67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bin                  6.0\n",
       " Amesbury            0.0\n",
       "Andover              8.0\n",
       "Beverly              0.0\n",
       "Billerica            0.0\n",
       "Boston               0.0\n",
       "Boxford              0.0\n",
       "Charlestown          0.0\n",
       "Chelmsford           0.0\n",
       "Gloucester           9.0\n",
       "Haverhill            7.5\n",
       "Ipswich              4.0\n",
       "Lynn                 5.0\n",
       "Malden               5.0\n",
       "Manchester           9.0\n",
       "Marblehead           0.0\n",
       "Piscataqua, Maine    0.0\n",
       "Reading              5.0\n",
       "Rowley               8.0\n",
       "Salem Town           5.0\n",
       "Salem Village        4.0\n",
       "Salisbury            0.0\n",
       "Topsfield            4.0\n",
       "Wells, Maine         0.0\n",
       "Woburn               0.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "09e1b23e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bin                  4.030334\n",
       " Amesbury            0.596285\n",
       "Andover              2.504541\n",
       "Beverly              1.389717\n",
       "Billerica            1.261312\n",
       "Boston               1.042045\n",
       "Boxford              2.018100\n",
       "Charlestown          1.042045\n",
       "Chelmsford           0.149071\n",
       "Gloucester           5.567764\n",
       "Haverhill            0.547723\n",
       "Ipswich              2.828427\n",
       "Lynn                 2.167948\n",
       "Malden                    NaN\n",
       "Manchester                NaN\n",
       "Marblehead           0.745356\n",
       "Piscataqua, Maine    1.353260\n",
       "Reading              2.299068\n",
       "Rowley               0.000000\n",
       "Salem Town           1.527094\n",
       "Salem Village        1.181454\n",
       "Salisbury            0.894427\n",
       "Topsfield            0.000000\n",
       "Wells, Maine         0.596285\n",
       "Woburn               1.261312\n",
       "dtype: float64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.std()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5adb242e",
   "metadata": {},
   "source": [
    "# Community Sentiments"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6f708ed",
   "metadata": {},
   "source": [
    "### As gleaned by Tax Records"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0209a333",
   "metadata": {},
   "source": [
    "Tax records list whether the tax payer lodged a ballet either for, or against keeping Rev. Parris on, after the disastrous 10 months of witchysteria.  \n",
    "\n",
    "NoS paid the least amount of taxes across the board, and Anti-Paris households paid a nose more than Pro-Paris households.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "6ea7ac63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([0, 1, 2], [Text(0, 0, ''), Text(0, 0, ''), Text(0, 0, '')])"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 374,
       "width": 721
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#import libraries\n",
    "from matplotlib import pyplot as plt\n",
    "from matplotlib.axes._axes import _log as matplotlib_axes_logger\n",
    "\n",
    "matplotlib_axes_logger.setLevel('ERROR')\n",
    "\n",
    "# Set the figure size - handy for larger output\n",
    "plt.rcParams[\"figure.figsize\"] = [12, 6]\n",
    "%config InlineBackend.figure_format = 'retina' #nicer for the eyes\n",
    "#load data\n",
    "TaxData = pd.read_csv(\n",
    "    '/.../Salem/Tax-Comparison-Data-Set.csv',\n",
    "    header='infer',\n",
    "    index_col=0,\n",
    "    squeeze=True).fillna(0)  #replaces any NaNs with 0's\n",
    "# build graph\n",
    "TaxData.plot(kind=\"scatter\", x='Petition', y='Sum')\n",
    "#styling\n",
    "plt.xticks(horizontalalignment='center', fontweight='bold', fontsize='x-large')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6e63e0e",
   "metadata": {},
   "source": [
    "## Committee List Data Set\n",
    "Contains a total of 31 individual Salem Committee members who held office during Samuel Paris' reign as Minister. Records include member votes for years of 1685-1698.\n",
    "It provides their name, Social information such as name or whether they were a Church Member or Householder (Meaning not affiliated with the Church in question), and whether they supported or opposed Samuel Paris or had no side in the matter."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64b444b3",
   "metadata": {},
   "source": [
    "In comparing the <b>Sentiment by Tax payer</b> chart above, with the the <b>Sentiment by Voter chart</b> below: <i>We see a complete inverse in sentiment.</i> Where NoS's filled the majority of ballots and Pro-Parris groups submitted slightly more votes than did the Anti-Parris crowd.\n"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "95a9cfa8",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea9bbd2c",
   "metadata": {},
   "source": [
    "## Observations\n",
    "### Social Information\n",
    "Of 31 Committee Members the majority (16) self described themselves as Householders rather than Church Members.\n",
    "### Voting Trends\n",
    "The top votes regarding Parris is NoS = No Side with 101 total votes.\n",
    "Of those who did have a side, Pro-Paris had the highest total over all."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5d062c3",
   "metadata": {},
   "source": [
    "## The  First Surprise of this analysis:\n",
    "Came with the examination of villager voting record, and the realization Samuel Parris prevailed in the vote despite the vast majority of voters self identifying as non-church goers.  This was especially surprising as the historic record reveals a high level of animosity between the Puritan Church and surrounding villages.  The church was waging a war against Quakers, Catholics and Atheists at this time. That the Puritan Reverend would prevail under such circumstances with votes un-afilliated with his own church is intriguing.\n",
    "\n",
    "<b>There were a total of 137 votes cast</b>\n",
    "\n",
    "<b>Results were in favor of Rev, Parris</b>\n",
    "<ul>Pro-P     53</ul>\n",
    "<ul>NoS       44</ul>\n",
    "<ul>Anti-P    40</ul>\n",
    "\n",
    "<b>Affiliation of voters</b>\n",
    "<ul>Non-Church    103</ul>\n",
    "<ul>Church         34</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6054d552",
   "metadata": {},
   "source": [
    "## Questions\n",
    "##### 5. Is there a correlation between amount of taxes paid and support of Paris? No.\n",
    "The lower tax rates paid = the least amount of engagement, giving neither support or opposition. Those who supported Parris paid a nose less than those who opposed him."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "6b6bd9b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([0, 1, 2], [Text(0, 0, 'Pro-P'), Text(1, 0, 'NoS'), Text(2, 0, 'Anti-P')])"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 357,
       "width": 353
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#loading colour palette\n",
    "sns.color_palette(\"Set2\", as_cmap=True)\n",
    "import pandas as pd\n",
    "\n",
    "taxData = pd.read_csv(\n",
    "    '/.../Salem/Tax-Comparison-Data-Set.csv',\n",
    "    header='infer',\n",
    "    index_col=0,\n",
    "    squeeze=True).fillna(0)\n",
    "# specifying number of bins\n",
    "num_bins = 3\n",
    "#build chart\n",
    "sns.displot(taxData, x=\"Petition\", kde=True)\n",
    "\n",
    "#styling\n",
    "plt.xticks(horizontalalignment='center', fontweight='bold', fontsize='x-large')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4059d70d",
   "metadata": {},
   "source": [
    "### Replace all NaNs with 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "59eb2c36",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('./Committee-List-Data-Set.csv', sep=',')\n",
    "df['1686'] = df['1686'].fillna(0)\n",
    "df['1687'] = df['1687'].fillna(0)\n",
    "df['1688'] = df['1688'].fillna(0)\n",
    "df['1689'] = df['1689'].fillna(0)\n",
    "df['1690'] = df['1690'].fillna(0)\n",
    "df['1691'] = df['1691'].fillna(0)\n",
    "df['1692'] = df['1692'].fillna(0)\n",
    "df['1693'] = df['1693'].fillna(0)\n",
    "df['1694'] = df['1694'].fillna(0)\n",
    "df['1695'] = df['1695'].fillna(0)\n",
    "df['1696'] = df['1696'].fillna(0)\n",
    "df['1697'] = df['1697'].fillna(0)\n",
    "df['1698'] = df['1698'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "838d8a46",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Committee Members</th>\n",
       "      <th>Petition</th>\n",
       "      <th>Social</th>\n",
       "      <th>1685</th>\n",
       "      <th>1686</th>\n",
       "      <th>1687</th>\n",
       "      <th>1688</th>\n",
       "      <th>1689</th>\n",
       "      <th>1690</th>\n",
       "      <th>1691</th>\n",
       "      <th>1692</th>\n",
       "      <th>1693</th>\n",
       "      <th>1694</th>\n",
       "      <th>1695</th>\n",
       "      <th>1696</th>\n",
       "      <th>1697</th>\n",
       "      <th>1698</th>\n",
       "      <th>Sort</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Putnam, Lt. John [Senr]</td>\n",
       "      <td>Pro-P</td>\n",
       "      <td>Church Member</td>\n",
       "      <td>1685.0</td>\n",
       "      <td>1686.0</td>\n",
       "      <td>1687.0</td>\n",
       "      <td>1688.0</td>\n",
       "      <td>1689.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1696.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Walcott, Jonathan</td>\n",
       "      <td>Pro-P</td>\n",
       "      <td>Householder</td>\n",
       "      <td>1685.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Buxton, John</td>\n",
       "      <td>Anti-P</td>\n",
       "      <td>Householder</td>\n",
       "      <td>1685.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1697.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sibley, William</td>\n",
       "      <td>NoS</td>\n",
       "      <td>Householder</td>\n",
       "      <td>1685.0</td>\n",
       "      <td>1686.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Putnam, Thomas Junr</td>\n",
       "      <td>Pro-P</td>\n",
       "      <td>Church Member</td>\n",
       "      <td>1685.0</td>\n",
       "      <td>1686.0</td>\n",
       "      <td>1687.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1694.0</td>\n",
       "      <td>1695.0</td>\n",
       "      <td>1696.0</td>\n",
       "      <td>1697.0</td>\n",
       "      <td>1698.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Committee Members Petition         Social    1685    1686    1687  \\\n",
       "0  Putnam, Lt. John [Senr]    Pro-P  Church Member  1685.0  1686.0  1687.0   \n",
       "1        Walcott, Jonathan    Pro-P    Householder  1685.0     0.0     0.0   \n",
       "2             Buxton, John   Anti-P    Householder  1685.0     0.0     0.0   \n",
       "3          Sibley, William      NoS    Householder  1685.0  1686.0     0.0   \n",
       "4      Putnam, Thomas Junr    Pro-P  Church Member  1685.0  1686.0  1687.0   \n",
       "\n",
       "     1688    1689  1690  1691  1692  1693    1694    1695    1696    1697  \\\n",
       "0  1688.0  1689.0   0.0   0.0   0.0   0.0     0.0     0.0  1696.0     0.0   \n",
       "1     0.0     0.0   0.0   0.0   0.0   0.0     0.0     0.0     0.0     0.0   \n",
       "2     0.0     0.0   0.0   0.0   0.0   0.0     0.0     0.0     0.0  1697.0   \n",
       "3     0.0     0.0   0.0   0.0   0.0   0.0     0.0     0.0     0.0     0.0   \n",
       "4     0.0     0.0   0.0   0.0   0.0   0.0  1694.0  1695.0  1696.0  1697.0   \n",
       "\n",
       "     1698  Sort  \n",
       "0     0.0     1  \n",
       "1     0.0     2  \n",
       "2     0.0     3  \n",
       "3     0.0     4  \n",
       "4  1698.0     5  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "5c0f1f2c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count              31\n",
       "unique              3\n",
       "top       Householder\n",
       "freq               16\n",
       "Name: Social, dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Social'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "aabcf958",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Householder'"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Social'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "03da7955",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Church Member'"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Social'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "98c5ee5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count         31\n",
       "unique         3\n",
       "top       Anti-P\n",
       "freq          15\n",
       "Name: Petition, dtype: object"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Petition'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "9a48e326",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "31"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Petition'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "51d4da20",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Pro-P'"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Petition'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "77b1f94b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Anti-P'"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Petition'].min()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d91fbe82",
   "metadata": {},
   "source": [
    "### Question 6.\n",
    "#### Is there a correlation between Church affiliation and support or opposition to Paris? \n",
    "Yes, but NOT in the way I had anticipated.  Support for Parris was less likely to come from his own parish, than from a non church going member. A Church member was much more likely to oppose him than support him."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a877be8",
   "metadata": {},
   "source": [
    "### Question 7.\n",
    "## Pro-Paris Profile\n",
    "The pro-Paris faction was in the majority with 105 total votes.\n",
    "Surprisingly, those who supported Paris were split down the middle regarding Church Membership.\n",
    "Of his supporters, 53 self described themselves as Church goers and 52 as householders.\n",
    "54 Men, and 53 women supported Paris. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "41dc075a",
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_theme(color_codes=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "e7189e76",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('./Pro-Parris-Social-Data-Set.csv', sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "4d32195c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "data = pd.read_csv('./Pro-Parris-Social-Data-Set.csv', sep=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "963a4a27",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('./Anti-Parris-Social-Data-Set.csv', sep=',')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2aecd15",
   "metadata": {},
   "source": [
    "### Support for the Puritan Minister came from male 'outsiders', or non church members."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "0b03db46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0, 1, 2, 3]),\n",
       " [Text(0, 0, 'Young men. 16 years old'),\n",
       "  Text(1, 0, 'Householder'),\n",
       "  Text(2, 0, '[Church] Member'),\n",
       "  Text(3, 0, 'Free-Holder')])"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 575,
       "width": 888
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "\n",
    "chart = sns.countplot(data=data[data['Sex'] == 'M'],\n",
    "                      x='Identification',\n",
    "                      palette='Set1')\n",
    "\n",
    "plt.xticks(\n",
    "    rotation=45, \n",
    "    horizontalalignment='right',\n",
    "    fontweight='light',\n",
    "    fontsize='medium'  \n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30cdd313",
   "metadata": {},
   "source": [
    "### While there is less detail on the female members of the pro-Paris camp,  the trend of non-member support for Parris continues to outstrip member support."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a20a954e",
   "metadata": {},
   "source": [
    "### Gender Make up of Pro-Parris are nearly split down the middle.  54 Male  and 51 female ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "e36eaae4",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sex\n",
       "M    54\n",
       "F    51\n",
       "dtype: int64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('./Pro-Parris-Social-Data-Set.csv', sep=',') \n",
    "df.groupby('Sex').size().sort_values(ascending=False) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c626a3d",
   "metadata": {},
   "source": [
    "### Social Make up of Pro-Paris sentiment is  evenly divided between 53 Householders, vs 52 church-members"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "916f9bfb",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Identification\n",
       "Householder      53\n",
       "Church-Member    52\n",
       "dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('./Pro-Parris-Social-Data-Set.csv', sep=',') \n",
    "df.groupby('Identification').size().sort_values(ascending=False) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "0410133b",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Name           Identification Sex  Sort\n",
      "0    Porter, Joseph  Young men. 16 years old   M     1\n",
      "1      Porter, Sam:  Young men. 16 years old   M     2\n",
      "2     Preston, Jno.  Young men. 16 years old   M     3\n",
      "3     Porter, Nath.  Young men. 16 years old   M     4\n",
      "4  Swinnerton, Ben:  Young men. 16 years old   M     5\n"
     ]
    }
   ],
   "source": [
    "print(antiParis.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffc48e8f",
   "metadata": {},
   "source": [
    "## Anti-Parris Profile\n",
    "The anti-Paris group included 84 individuals.\n",
    "They were more likely to be male and were less likely to attend church. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "0e3d0710",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0, 1]), [Text(0, 0, '[Church] Member'), Text(1, 0, 'Non-Member')])"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 322,
       "width": 609
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 5))\n",
    "\n",
    "chart = sns.countplot(data=data[data['Sex'] == 'F'],\n",
    "                      x='Identification',\n",
    "                      palette='Set1')\n",
    "\n",
    "plt.xticks(horizontalalignment='right', fontweight='light', fontsize='medium')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "c24ff49a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 321,
       "width": 609
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(10, 5))\n",
    "\n",
    "chart = sns.countplot(data=data[data['Sex'] == 'M'],\n",
    "                      x='Identification',\n",
    "                      palette='Set1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "a1a1072a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Sex\n",
       "M    57\n",
       "F    27\n",
       "dtype: int64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('./Anti-Parris-Social-Data-Set.csv', sep=',') \n",
    "df.groupby('Sex').size().sort_values(ascending=False) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "52657892",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Identification\n",
       "Householder                29\n",
       "Young men. 16 years old    17\n",
       "[Church] Member            17\n",
       "Non-Member                 16\n",
       "Free-Holder                 5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv('./Anti-Parris-Social-Data-Set.csv', sep=',') \n",
    "df.groupby('Identification').size().sort_values(ascending=False) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a1ee7b7",
   "metadata": {},
   "source": [
    "### Tax Comparison Data Set\n",
    "Name, Pro or Anti Paris, year and taxes paid in shillings.\n",
    "Need to clean up NaNs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "c37c4a50",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('./Tax-Comparison-Data-Set.csv', sep=',')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a39d989",
   "metadata": {},
   "source": [
    "### Replace all NaNs with 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "f5f1d91f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['1681'] = df['1681'].fillna(0)\n",
    "df['1690'] = df['1690'].fillna(0)\n",
    "df['1694'] = df['1694'].fillna(0)\n",
    "df['1695'] = df['1695'].fillna(0)\n",
    "df['1697'] = df['1697'].fillna(0)\n",
    "df['1700'] = df['1700'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "5bacf027",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "73922de6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.min()\n",
    "# returns the household paying the least tax on record, anti-P sentiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "a7f41c4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.max()\n",
    "# returns the household paying the most tax on record, pro-P sentiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "defc7262",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.describe()\n",
    "#we can see a dramatic drop in taxes paid in the years of Paris's employment, increasing again once he leaves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "a1ebf884",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.shape #rows, columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fc764dd",
   "metadata": {},
   "source": [
    "### Votes by tax payers over time by Paris sentiment and Payment amount (in shillings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "cff63c0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('./Tax-Comparison-Data-Set.csv', sep=',', header=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "9a2f4f5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#quick and easy value counts\n",
    "#df.value_counts(subset=None, normalize=False, sort=True, ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "4bf379b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count                      36\n",
       "unique                     36\n",
       "top       Fuller, Thomas senr\n",
       "freq                        1\n",
       "Name: Name, dtype: object"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import regex module\n",
    "import re\n",
    "\n",
    "# removing null values \n",
    "df.dropna(inplace = True)\n",
    "\n",
    "# describe Tax Payer \n",
    "desc = df['Name'].describe()\n",
    "\n",
    "# display\n",
    "desc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "056ad85c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#print(village.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "80109ffb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "137"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(village) #finding out how many people signed petitions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "b383bb82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Pro-P     53\n",
       "NoS       44\n",
       "Anti-P    40\n",
       "Name: Petition, dtype: int64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "village['Petition'].value_counts()# more Pro-P than Anti-P, No side is a significant size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "507ecbf8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Non-Church    103\n",
       "Church         34\n",
       "Name: Church to 1696, dtype: int64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "village['Church to 1696'].value_counts()# interesting, only 34 of P supporters were even part of his church"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0670facc",
   "metadata": {},
   "source": [
    "# Statistical Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9108b9c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import statistics as st"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c465e14c",
   "metadata": {},
   "source": [
    "# Measures of Central Tendencies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0cf9c677",
   "metadata": {},
   "source": [
    "### Accusations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "eab52ad3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    40\n",
       "1    44\n",
       "2    53\n",
       "dtype: int64"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "village['Petition'].value_counts().mode() #0 Anti-P, 1 NoS, 2 Pro-P\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "171813f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "45.666666666666664"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "village['Petition'].value_counts().mean() #mean number of total votes for each group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "e2684a8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "44.0"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "village['Petition'].value_counts().median() #median number of total votes for each group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "f59e3bba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.658328118479393"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "village['Petition'].value_counts().std() #standard deviation for number of total votes for each group"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50f16fd8",
   "metadata": {},
   "source": [
    "# Visualization Figures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "6bc3c791",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "7e6102fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# specifying number of bins\n",
    "num_bins = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "65307db1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_bins"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe27492d",
   "metadata": {},
   "source": [
    "# Accused\n",
    "our histogram has a bi-modal shape, indicating we are looking at two groups withing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "ccc99015",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1080x576 with 0 Axes>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1080x576 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(data=accused, x='MonthAccusation', kde=True)\n",
    "plt.figure(figsize=(15,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b6fc993d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# To test this, I added another column 'Residence' "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "3fa9afa8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fd4161503d0>"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.displot(data=accused, x='MonthAccusation', y=' Residence ') #By adding another column to sns.displot we're able to create a a bivariate plot. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "a6559810",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='MonthAccusation', ylabel='Sort'>"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "sns.set_style('darkgrid')\n",
    "sns.set_palette('Set2')\n",
    "plt.figure(figsize=(12,5))\n",
    "sns.scatterplot(data=accused, x='MonthAccusation', y='Sort', hue='MonthExecution')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af7cee74",
   "metadata": {},
   "source": [
    "# Hypothesis Testing\n",
    "Null Hypothesis is That Church Goers are more apt to support Parris"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac890212",
   "metadata": {},
   "source": [
    "# Linear Regression of Parris Sentiment\n",
    "from tax comparison data\n",
    "<ul>1 = ProP</ul>\n",
    "<ul>0 = AntiP</ul>\n",
    "<ul>-1 = NoS</ul>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3bc4d8c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#load libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "aee28cc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import preprocessing, svm\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5f9644a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#define arrays x 1 = pro, -1 = nos, 0 = anti"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "119107ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "x=np.array([1,-1,-1,1,0,-1,-1,-1,0,1,0,0,-1,0,1,-1,0,0,-1,0,0,-1,-1,-1,1,-1,-1,-1,-1,-1,-1,-1,-1,-1,1,-1,-1,-1,-1,1,-1,-1,-1,1,1,0,0,-1,-1,-1,-1,-1,1,1,0,-1,-1,-1,-1,-1,-1,1,1,-1,1,1,1,-1,-1,1,-1,1,-1,0,-1,0,-1,1,0,0,-1,-1,1,1,0,0,-1,-1,1,-1,-1,-1,0,-1,-1,-1,0,-1,-1,1,-1,-1,-1,0,-1,1,0,-1,-1,-1,0,0,-1,0,-1,0,-1,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,-1,-1,1,-1,0,-1,1,0,0,-1,-1,-1,-1,-1,-1,-1,-1,-1,1,0,0,-1,-1,-1,-1,1,-1,0,-1,0,0,0,-1,0,-1,-1,-1,-1,0,0,1,1,1,1,-1,-1,1,1,1,-1,-1,1,1,1,1,1,1,0,-1,-1,-1,-1,-1,-1])\n",
    "y=np.array([21,22.5,24,31,303.25,4,22.5,6,4,34,106,4,3.25,54,51.5,61.5,45.5,11,30,207,9,12,11,3,68.5,13,40.5,4.25,4,3.25,8,10,44,4,35,6.5,3,5,5,11,6,6,5,254,33.5,95,32.5,8,43,7,67.5,5,21,137,208.5,26,27.5,30.25,70.5,10,4,36,21.5,9,35,165,16,24,29.25,41,7.5,106.5,4,174,12,109,21,49,39,98.5,8.5,6,56,36,59.5,275.25,49.5,45,158,5,24,36,76.5,30,30,4,6,30,5,25.5,24,6,5,31,40,17,24,10,20.5,10,34,111,7,4,3,133,50,250,96,404,17,49.5,26,73,50,36,110,329,149,46,98,170,82,174,218,392,206.25,30,140,9.75,131,190.5,51,57,224,22,2.25,4,14,4.75,30,10.5,5,114,61,62,27.5,4,43.5,22,4,12,4,4,60,49,190,40,20,114,3,5,13,3,31,43,31,130,52,9,12,5,67.5,61,49,6,10,28,103,89,85,48,15.5,146.75,7,18,40,2.5,4,15])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "53a14161",
   "metadata": {},
   "outputs": [],
   "source": [
    "#define function\n",
    "linreg = LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "34124941",
   "metadata": {},
   "outputs": [],
   "source": [
    "#re-shape array for best fit\n",
    "x =x.reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "affcbe70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "linreg.fit(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2a4ccc5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = linreg.predict(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "681ad03d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x,y)\n",
    "plt.plot(x,y_pred, color='red')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "477bce39",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[32.31590399]\n"
     ]
    }
   ],
   "source": [
    "print(linreg.coef_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "53f588cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "61.75831695676585\n"
     ]
    }
   ],
   "source": [
    "print(linreg.intercept_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c12fb5e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Y= mx + c\n",
    "#y= 32.31 +61.75"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2eb5799",
   "metadata": {},
   "source": [
    "T-Testing to get Pvalue for Parris Sentiment among Tax paying villagers based on church membership"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0f5762e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy #for t-testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a38f094f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.stats import ttest_1samp, ttest_ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "29eb17fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=array([-10.72230598]), pvalue=array([9.80831674e-24]))"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scipy.stats.ttest_ind(x, y, axis=0, equal_var=True, nan_policy='propagate',  alternative='two-sided')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79e83a2b",
   "metadata": {},
   "source": [
    "# Hypothesis REJECTED!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e30a4003",
   "metadata": {},
   "outputs": [],
   "source": [
    "The pvalue of 9.8083 signifies the results of my experiment are too random to prove any significance between church membership and support for Parris."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15ad73c2",
   "metadata": {},
   "source": [
    "# ANSWERS"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cde074b3",
   "metadata": {},
   "source": [
    "#### 1. What % of the Accused were Executed? \n",
    "17%\n",
    "#### 2. On average, how long from accusation till execution? \n",
    "173 days\n",
    "#### 3. Which village had the most, the least accused?\n",
    "<p><b>The Most:</b> Andover 45, Salem Town 24, Salem Village 15</p>\n",
    "<p><b>The Least:</b> Manchester, Chelmsford, Malden and four others recorded 1 accusation each.</p>\n",
    "#### 4. Which village had the most, the least Executed?\n",
    "<p><b>The Most Executed: </b>Salem Town 4, Andover 2, Salem Town 2</p>\n",
    "<p><b>The Least Executed:</b>\n",
    "Amesbury,                   \n",
    "Andover,           \n",
    "Ipswich,           \n",
    "and six others each saw one execution on record for the events in question.</p>\n",
    "\n",
    "5. Is there a correlation between Church affiliation and support or opposition to Paris?\n",
    "6. Is there a correlation between amount of taxes paid and support of Paris?\n",
    "\n",
    "#### 7. What is the profile of a Paris supporter?  Opposer?\n",
    "Church membership was not a driving factor for supporters of Samuel Paris, neither was gender as the vote was evenly spread between female and male voters. However, to the opposition gender and church membership does appear to be factors.  The majority of opposition came from young men, with no affiliation to the church."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "143e7d15",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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