Final project(climate change).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#importing libraries\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def mean(file,place): #function\n",
    "    df=pd.read_csv(file)\n",
    "    year2013=df.loc[df['Year']==2013]\n",
    "    year2014=df.loc[df['Year']==2014]\n",
    "    year2015=df.loc[df['Year']==2015]\n",
    "    year2016=df.loc[df['Year']==2016]\n",
    "    year2017=df.loc[df['Year']==2017]\n",
    "    year2018=df.loc[df['Year']==2018]\n",
    "#group data for a given year by month and calculate the mean temperature for the month\n",
    "    groupby_month2013 = year2013[\"Sea_Surface_Temperature\"].groupby(year2013[\"Month\"]).mean()\n",
    "    groupby_month2014 = year2014[\"Sea_Surface_Temperature\"].groupby(year2014[\"Month\"]).mean()\n",
    "    groupby_month2015 = year2015[\"Sea_Surface_Temperature\"].groupby(year2015[\"Month\"]).mean()\n",
    "    groupby_month2016 = year2016[\"Sea_Surface_Temperature\"].groupby(year2016[\"Month\"]).mean()\n",
    "    groupby_month2017 = year2017[\"Sea_Surface_Temperature\"].groupby(year2017[\"Month\"]).mean()\n",
    "    groupby_month2018 = year2018[\"Sea_Surface_Temperature\"].groupby(year2018[\"Month\"]).mean()\n",
    "    groupby_month=pd.concat([groupby_month2013,groupby_month2014,groupby_month2015,\n",
    "                             groupby_month2016,groupby_month2017,groupby_month2018])\n",
    "    groupby_month.to_csv(place+\"Bleaching_Monthmean.csv\",header=[\"Mean\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#using the function for Hawaii and Florida.\n",
    "mean(\"Florida_Keys_Bleaching.csv\",\"Florida\")\n",
    "mean(\"Hawaii_Bleaching.csv\",\"Hawaii \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#Assigning the file to a variable.\n",
    "monthMF=pd.read_csv(\"FloridaBleaching_Monthmean.csv\")\n",
    "monthMH=pd.read_csv(\"Hawaii Bleaching_Monthmean.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#Assigning the variable to the year 2014 and changing it into a csv file.\n",
    "year14H=monthMH.loc[10:21]\n",
    "year14H.to_csv(\"Year14HBleaching_Monthmean.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "year17H=monthMH.loc[46:57]\n",
    "year17H.to_csv(\"Year17HBleaching_Monthmean.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "year14h=pd.read_csv(\"Year14HBleaching_Monthmean.csv\")\n",
    "year17h=pd.read_csv(\"Year17HBleaching_Monthmean.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#Naming the ticks.\n",
    "months=[\"Jan\",\"Feb\",\"Mar\",\"April\",\"May\",\"June\",\"July\",\"Aug\",\"Sept\",\"Oct\",\"Nov\",\"Dec\"]\n",
    "months_num=[1,2,3,4,5,6,7,8,9,10,11,12]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
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kzczWYM00JU0jdQqfAbwlIjaPiL8Hts7z2oCpLYvQzMxq1UxT0rsj4uX2M/O8GcAMSev0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\nODGYmVmJE4OZmZX8HzeFg4GgoSZ5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a221940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#bar graph for hawaii 2014.\n",
    "plt.bar(year14h[\"Month\"],year14h[\"Mean\"],color='orange')\n",
    "plt.xlabel(\"Month\")\n",
    "plt.ylabel(\"Temperature($^\\circ$C)\")\n",
    "plt.title(\"Hawaii Sea Surface Temperature 2014\")\n",
    "plt.xticks(months_num,months)\n",
    "plt.ylim(22,29)\n",
    "plt.axhline(y=25.1,color='black')\n",
    "plt.axhline(y=28.2,color='black')\n",
    "plt.savefig(\"Hawaii Sea Surface Temperature(2014).png\",bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AIzNrF994NOtVKzWGMZLGN8+UNF7StvDPJGFmZkNAK4nhW8DybuYvz8vMzGwIaSUxbBER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\nzEr+Dw5IJzgPe+apAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11e830fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#bar graph for Hawaii 2017.\n",
    "plt.bar(year17h[\"Month\"],year17h[\"Mean\"],color='orange')\n",
    "plt.xlabel(\"Month\")\n",
    "plt.ylabel(\"Temperature($^\\circ$C) \")\n",
    "plt.title(\"Hawaii Sea Surface Temperature 2017\")\n",
    "plt.xticks(months_num,months)\n",
    "plt.ylim(22,29)\n",
    "plt.axhline(y=25.1,color='black')\n",
    "plt.axhline(y=28.2,color='black')\n",
    "plt.savefig(\"Hawaii Sea Surface Temperature(2017).png\",bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#Assigning the variable to the year 2014 and changing it into a csv file.\n",
    "year14F=monthMF.loc[10:21]\n",
    "year14F.to_csv(\"Year14FBleaching_Monthmean.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#Assigning the variable to the year 2017 and changing it into a csv file.\n",
    "year17F=monthMF.loc[46:57]\n",
    "year17F.to_csv(\"Year17FBleaching_Monthmean.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#Assigning the file a variable.\n",
    "year14f=pd.read_csv(\"Year14FBleaching_Monthmean.csv\")\n",
    "year17f=pd.read_csv(\"Year17FBleaching_Monthmean.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mZlbiwGBmZiXL5gtuZsuA/n7xDPzymXWGawxmZlbiwGBmZiUODGZmVuLAYGZmJQ4MZmZW\n4sBgZmYlDgxmZlbiwGBmZiUODGZmVuLAYGZmJZUDg6QRklZuR2HMzGzg9dpXkiQBBwIHA28BBKwg\naSHwB+CHwLUR7sXFzGwoaKXGcAuwLXAW8PqIWC8iXgdslMd1A5N7SyTXNO6SdI+kWZLOzONfK2mi\npD/n/2v0eW3MrG2k/v2zwauV3lX3jIh/1I/M4+4E7pS0UgvpvALsHhHzJQ0HbpO0C/A24LcRcaak\nE4ETgc+2vgpmZtafWqkxjJW0U/1ISTtJ2hj+FSSaimR+HhwODAPmAgcAl+Xxl5GarczMbIC0Ehi+\nDjzfw/jn87SWSRomaTrwDDA5Iu4D1omIp/IsTwPrNFj2KElTJE2ZPXt2lWzNzKyCVgLDOhFxb/3I\nPG5clcwiYlFEbAVsAOwiabe66QH0eBM7Ii6KiO6I6O7q6qqSrZmZVdBKYBjdZNrIvmQaEfOA60k3\nrv8maV2A/P+ZvqRpZmb9o5XAMEXSh+tHSjoSmNpqRpK6JI3On0cCewHTgeuAw/JshwG/aDVNMzPr\nf608lXQccI2kQ1gcCLqBlYC3V8hrXeAySSuQAtIVETFR0jTgp5I+BDwCvKdCmmZm1s96DQwR8Tfg\nLfl+wOZ59PURcXOVjCJiBrB1D+P/DuxRJS0zM2ufVmoMAETEJGBSG8tiZmaDgDvRMzOzkl4Dg6Qd\nazeNzcxs6GsaGCR9CegCLuxMcczMbKD1VmP4PfBm4MEOlMXMzAaBpjefI+IG4IYOlcXMzAYB33w2\nM7OSln6op7cf4WllHrPBoh2/BeCj34aSVmoMkyV9WtIm9RMkbSLps7TwQz1mZrZsaCUw7AXMAc6X\n9JSkByQ9KOlJ4FukrrL3amchzcysc1rpEuMfwPeA7+V+jtbKk+ZExD/bWTgzM+u8lm8+SxJwMHB0\nRDwDbCBp+7aVzMyWO/39u9L+bem+qfJU0reBHYGD8vALwPn9XiIzMxtQLXeiB+wQEdtIuhsgIuZK\nWqlN5TIzswFSpcbwqqRh5J/elNQF+B6DmdkQUyUwnAdcA6wt6XTgNuCMtpTKzMwGTEtNSfnG862k\nX3DbAxBwYETMamPZzMxsALQUGCIiJP0qIt4E3N/mMpmZ2QCq0pQ0TdJ2bSuJmZkNCpWeSgIOkfQI\n8CKpOSkiYou2lMzMzAZElcDw1raVwszMBo2WA0NEPNLOgpiZ2eDQcmCQdGpP4yPii/1XHDMzG2hV\nmpJeLHweAewP+HFVM7MhpkpT0tnFYUlnATf2e4nMzGxALc1Pe64CbNBfBTEzs8Ghyj2Ge8n9JAHD\ngC7gS+0olJmZDZwq9xj2L3xeCPwtIha2urCkMcAPgHVIAeaiiPhG/k2H84HhOd1jIuKuCuUyM7N+\nVKUp6ZiIeCT/PRERCyV9pcLyC4HjI2Iz4M3AxyRtBnwVODUitgJOzcNmZjZAqgSGnn7Xed9WF46I\npyJiWv78AumJpvVJvxn9mjzb6sCTFcpkZmb9rNemJEkfBY4BNpI0ozBpNeD2vmQqaRywNXAn8CDw\n+/yU0wrAWxoscxRwFMDYsWP7kq2ZmbVAEdF8Bml1YA3gy8CJhUkvRMSzlTOURgG3AKdHxNWSfgN8\nJyKukvQe4KiI2LNZGt3d3TFlypSqWZsB7fkd4J6+RstqPo1OCZ3Ip1PbbHklaWpEdPc2X681hoh4\nDngOOEjSGsAbSC+4IYmIuLVCoYYDVwFXRsTVefQOLG6m+hlwcavpmZlZ/6vyuOqRwLGkdxemk24g\n/wHYvcXlBVwCzIqIcwqT/gLsCkzOaf251TKZmVn/q/K46rHAdsAdEbGbpPFU+2nPnYBDgXslTc/j\nTiLdNzhf0srAgjxsZmYDpEpgWBARCyQhaeWIuF/Spq0uHBG3kX7DoSfbVyiHmZm1UZXA8Lik0cC1\nwERJcwF3xW1mNsS0FBjy/YFPRsQ84DRJk0jvHNzQzsKZmVnntRQYIiIk/Qp4Ux6+pa2lMjOzAVPl\nzedpkrZrW0nMzGxQqHKPYQfg/ZIeJv1oj0iViS3aUTAzMxsYVQLDW9tWCjP81qvZYFGlKelRYBfg\nsIh4hNR19jptKZWZmQ2YKoHh28COwEF5+AXS7yiYmdkQUukeQ0RsI+lugIiYK2mlNpXLzMwGSJUa\nw6uShpF/3lNSF/DPtpTKzMwGTJXAcB5wDbCOpNOB26jWV5KZmS0DWm5KiogrJU0F9sijDoyIWe0p\nlpmZDZQq3W6PAPYjPZn0T2AlSQ9FxIJ2Fc7MzDqvys3nH5CeRDovDx8MXA68u78LZWZmA6dKYNg8\nIjYrDE+S9Kf+LpCZmQ2sqn0lvbk2IGkHwD+8bGY2xFSpMWwL3C7p0Tw8FnhA0r24zyQzsyGjSmDY\np22lMDOzQaPK46r+tTYzs+VAlcdVu4GTgQ3zcu5228xsCKrSlHQl8GngXtwVhpnZkFUlMMyJiOva\nVhIzMxsUqgSG0yRdAvwGeKU2MiKu7vdSmZnZgKkSGA4HNs3L1JqSAnBgMDMbQqoEhu6I2LRtJTEz\n6xD/jGxzVd58vl3SZr3PZkOR1L9/ZjZ4VakxvBmYLukh0j0GP65qZjYEdezNZ0ljSD20rkO6N3FR\nRHwjT/sE8DFgEXB9RHxmafIyM7O+qxIYHgUOATaKiC9KGgu8Dmj1jeiFwPERMU3SasBUSRNJgeIA\nYMuIeEXS2hXKZGZm/azKPYZvAzsCB+XhF4DzW104Ip6KiGn58wvALGB94KPAmRHxSp72TIUymZlZ\nP6sSGHaIiI8BCwAiYi6wUl8ylTQO2Bq4E9gE2EXSnZJukbRdg2WOkjRF0pTZs2f3JVszM2tBlcDw\nqqRhpPsDSOqiD11jSBoFXAUcFxHPk5qzXku6uf1p4KfSks+tRMRFEdEdEd1dXV1VszUzsxZVCQzn\nAdcAa0s6HbgNOKNKZpKGk4LClYU3ph8Hro7kLlKwWatKumZm1n96vfksacWIWBgRV0qaCuxBelT1\nwIiY1WpGuRZwCTArIs4pTLoW2I30U6GbkJqn5lRZCTMz6z+tPJV0F7ANQETcD9zfx7x2Ag4F7pU0\nPY87CbgUuFTSfcA/gMMihtI7hGZmy5ZWAkO/vKcaEbc1Sev9/ZGHmZktvVYCQ5ek/9doYl2zkJmZ\nLeNaCQzDgFH0U83BzMwGt1YCw1MR8cW2l8TMzAaFVh5XdU3BzGw50kpg2KPtpTAzs0Gj16akiHi2\nEwUZavxDIGa2rKrSu6qZmVWwrF4gVukSw8zMlgOuMSzj+vuKxM1VZuYag5mZlTgwmJlZybLZlPTA\nAzBhQp8WnXxL/xYFYMKuS46b1P/ZwIQO5NNDHp3KZ5ndZkMtnx7y6FQ+y+w2G+B8+ptrDGZmVqJl\nsYfr7u7umDJlSp+W7dTjY8tqPo0Oh07ks6xus6GWj4+BZS+fVkmaGhHdvc3nGoOZmZU4MJiZWYkD\ng5mZlTgwmJlZiQODmZmVODCYmVmJA4OZmZU4MJiZWYkDg5mZlTgwmJlZiQODmZmVODCYmVmJA4OZ\nmZV0LDBIGiNpkqQ/SZop6di66cdLCklrdapMZma2pE7+UM9C4PiImCZpNWCqpIkR8SdJY4C9gUc7\nWB4zM+tBx2oMEfFUREzLn18AZgHr58nnAp8Blr0fhzAzG2IG5B6DpHHA1sCdkg4AnoiIewaiLGZm\nVtbx33yWNAq4CjiO1Lx0EqkZqbfljgKOAhg7dmw7i2hmtlzraI1B0nBSULgyIq4GNgZeD9wj6WFg\nA2CapNfVLxsRF0VEd0R0d3V1dbLYZmbLlY7VGCQJuASYFRHnAETEvcDahXkeBrojYk6nymVmZmWd\nrDHsBBwK7C5pev7br4P5m5lZCzpWY4iI2wD1Ms+4zpTGzMwa8ZvPZmZW4sBgZmYlDgxmZlbiwGBm\nZiUODGZmVuLAYGZmJQ4MZmZW4sBgZmYlDgxmZlbiwGBmZiUODGZmVuLAYGZmJQ4MZmZW4sBgZmYl\nDgxmZlbiwGBmZiUODGZmVuLAYGZmJQ4MZmZW4sBgZmYlDgxmZlbiwGBmZiUODGZmVuLAYGZmJQ4M\nZmZW4sBgZmYlDgxmZlbiwGBmZiUdCwySxkiaJOlPkmZKOjaP/5qk+yXNkHSNpNGdKpOZmS2pkzWG\nhcDxEbEZ8GbgY5I2AyYCm0fEFsCDwOc6WCYzM6vTscAQEU9FxLT8+QVgFrB+RNwUEQvzbHcAG3Sq\nTGZmtqQVByJTSeOArYE76yYdAfykwTJHAUflwfmSHmhX+bK1gDmtzCgNnXyWMo+hls+g2jedymcZ\n2TedymdQ7Zt+yGfDlvKIiKXKpSpJo4BbgNMj4urC+JOBbuAd0elC9UDSlIjodj7Lbz5DaV2cz+DN\no5P5tKqjNQZJw4GrgCvrgsLhwP7AHoMhKJiZLc86FhgkCbgEmBUR5xTG7wN8Btg1Il7qVHnMzKxn\nnawx7AQcCtwraXoedxJwHrAyMDHFDu6IiKM7WK5GLnI+y30+Q2ldnM/gzaOT+bSk4/cYzMxscPOb\nz2ZmVuLAYGZmJct9YJA0v83pL5I0vfA3rsm8EyT9so/5hKQrCsMrSprd1/R6SP/AnMf4Pix7cX7L\nHUkPS1qrybxtXY9Cum3d71XzkzRZ0lI9rrg0+6jF9E/O3dnMyMfyDn1IY4Kkt1SYfwNJv5D0Z0n/\nK+kbklZqMv9xklapkH5IOrswfIKk01pdvkI+tfPATEn3SDpe0qA9/w7agg0hL0fEVoW/h9uUz4vA\n5pJG5uG9gCeqJCCp2cMIBwHX5/9V0hwWEUdGxJ9aXGSp12M51qd91ApJO5IeKd8md1+zJ/BYH5Ka\nALQUGPKTjFcD10bEG4BNgFHA6U0WOw5oOTAArwDvaHax0k9q54E3ko7pfYHPtznPPnNgIL10J+m3\nkqZJulfSAXn8OEmzJH03R/qbCiespclvWO488I/56usjhcmvkXS9pAckXVDxquJXwH/mzwcBPyrk\nub2kP0i6W9LtkjbN4w+XdJ2km4HfNijvKHL/VsB787gJkm7tqayS5ks6W9I9wI59uBruy3rcKmmr\nwny3SdqyWSb1NTRJ38rv1NRqNl8oHBPj8/hVJV0q6a5chgNaXalm+RXGHSHp64XhD0s6t4W0G+2j\nRuu3n1LnlVMlnddCjWxdYE5EvAIQEXMi4klJ20q6Jadzo6R1c/qT89X9dEn35f02Djga+FQev0sv\nee4OLIiI7+U8FwGfAo7I++GsnPYMSZ+Q9ElgPWCSpEm9bbNsIemJoE/VT8jf/5tz+r+VNFbS6pIe\nKRzrq0p6TOkdrZZExDOkXhw+rqTh+UDSZ/Pxd4+kM1vNY2k5MCQLgLdHxDbAbsDZ0r9ePH8DcH6O\n9POAd1ZMe6QWNyNdk8d9CHguIrYDtgM+LOn1edr2wCeAzYCNgXdUyOvHwPskjQC2oNzlyP3ALhGx\nNXAqcEZh2jbAuyJi1wbpHgDcGBGPALMlbdtLWVcF7oyILSPitgrlX5r1uAQ4HEDSJsCIiLinD3kX\nzcnHxHeAE/K4k4GbI2J70rHyNUmrLmU+RT8F3lY40XwQuLSF5RrtoyXk7XohsG9EbAt0tZD+TcAY\nSQ9K+rakXXMZv0k6drbN5Sxeza8SEVsBxwCX5tryBcC5+er5d73k+UZganFERDwPPAocCYwDtso1\nmCsj4jzgSWC3iNithXWqOR84RNLqdeO/CVxWSx84LyKeA6YDte/K/qTt/mqF/IiIvwLDgLVpcD6Q\ntC9pv+4QEVsCX62Sx9JwYEgEnCFpBvAbYH1gnTztoYiovXcxlXQwVlFsSnp7Hrc38AGl9znuBNYk\nBSCAuyLir/nq6EfAzq1mFBEzcvkOIl11F60O/EzSfcC5pC9dzcSIeLZJ0geRTljk/7WmikZlXUR6\nw71P+rgePwP2zyerI4Dv9zX/gtrb+cX9vjdwYt53k4ERwNh+yAuAiJgP3Exal/HA8Ii4t4VFG+2j\nnowH/hoRD+XhHzWZt1iubUlXurNJfZp9BNic9A7SdOAUyp1g/igveyupJtyfXepPAC6sdcDZy/Hb\nVA42PwA+WTdpR+CH+fPlLD6+f0KulQHvo0H/bhU0Oh/sCXyv9uLv0qxjVQPSid4gdAjpqmnbiHhV\n0sOkLzxs6mXmAAAEv0lEQVSkNsiaRcBSNyWRAtEnIuLG0khpAlD/YknVF02uA84ifXHWLIz/EjAp\nIt6eq/STC9NebFhQ6bWkKv2bJAXpKidIbdmNyrogB4ulUWk9IuIlSRNJV1jvIZ3EerOQ8sXRiLrp\ntX2/iMXfFQHvjIi+dOLYW341F5Ne/rwf+F5viTbZR79oMb+W5H06GZgs6V5Ss9XMiNix0SK9DPfm\nT8C7iiMkvYYUiB+umFZvvg5Mo4XtTTo2z8jbfVtSIK9E0kak4+oZGp8P3lo13f7iGkOyOvBMDgq7\n0WIPhEvhRuCjteYCSZsUmiO2z9XIFUhXJVWbYi4FvtDDVebqLL6Je3iF9N4FXB4RG0bEuIgYAzwE\n7NIPZW2mL+txMelN+j9GxNwW8ngE2EzSyvlqdo8WlrkR+EStqVHS1i0sUym/iLgTGAMcTAtX8zTe\nRys0yO8BYCMtfkLuvfUJ1pO0qaQ3FEZtReo6v0vpxjSShksq1kRr9zp2JjWVPAe8AKzWwjpBuue1\niqQP5HSGAWeTaoM3Ah9RfmAin6SpmP6/5Kvxn5KadWpuJ9UIIF08/i7POx/4I/AN4JdVL4IkdZGa\n1L6V+4ZrdD6YCHxQ+Smrwjq23XIdGPJB9Qqp/bA7XwV9gHSl1k4Xk66GpuUmkQtZfEX6R+BbpC/d\nQ8A1PabQQEQ8ntta630V+LKku6lWUzyohzJclccvVVmb6ct6RMRU4Hl6ueqr7feIeIx0Mrgv/7+7\nhaJ9CRgOzJA0Mw831cf8fgr8vsUA12gfva+n/CLiZVK7/w2SppJOps/1ksco4DKlX2CcQbqvdCop\nKH1F6UGD6ZSfOFqQ99MFLD7h/n/g7Wrh5nM+ab4deLekP5N+yGsBqTZ1Melew4yc98F5sYvyerV6\n87nobFL31zWfIJ2YZ5C68zm2MO0nwPtpvRmpdq9xJqm5+ibgC3laj+eDiLiBVDuZkpuZTugh3bZY\nrrvEUHpq5bv5RqJVkJu9ToiI/Qe6LDWS1iM1dYyPiH82ma+j+70v+Sk9JXRuRPT4pFg/lGlURMzP\nNZ/zgT9HRK9PP1VIfzLp+JjSX2la5yy3NQZJR5Oq6acMdFls6eXmhjuBk3sJCh3d71XzkzRa0oOk\nhxbaEhSyD+er0Jmk5rkL25iXLWOW6xqDmZktabmtMZiZWc8cGMzMrMSBwczMShwYzHqgfu7lNd9U\nPqYw3OeedM3azYHBrGf93cvraNK7A2aDngODWWPNenl9raRrlXrDvEPSFnn8aUq9r06W9FelHj8B\nzgQ2zi85fS2PGyXp50q9nF5Ze5vabKA5MJg11qyX1y8Ad+eeN08idcJWMx54K6n32c/nrg5OBP43\nd6b46Tzf1qTfD9gM2AjYqZ0rY9YqBwazBnrp5XVnUo+bRMTNwJq5gzeA6yPilYiYQ+okbR16dlfu\n+uOfpO4kxvXvGpj1jXtXNWuuUS+vzdT3yNvoe9bqfGYd5RqDWXONenn9HanHzVq/UXNyv/6N9KnX\nT7OB4CsUsyYi4nFSV971TgMuzT1vvgQc1ks6f5f0+9x75q9Jv2dhNii5ryQzMytxU5KZmZU4MJiZ\nWYkDg5mZlTgwmJlZiQODmZmVODCYmVmJA4OZmZX8H+PCAuSUyY+GAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11e075da0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#bar graph for Florida Keys 2014.\n",
    "plt.bar(year14f[\"Month\"],year14f[\"Mean\"],color='blue')\n",
    "plt.xlabel(\"Month\")\n",
    "plt.ylabel(\"Temperature($^\\circ$C) \")\n",
    "plt.title(\"Florida Keys Sea Surface Temperature 2014\")\n",
    "plt.xticks(months_num,months)\n",
    "plt.ylim(22,34)\n",
    "plt.axhline(y=31.4,color='red')\n",
    "plt.axhline(y=25,color='red')\n",
    "plt.savefig(\"Florida Keys Sea Surface Temperature(2014).png\",bbox_inches='tight')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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SBwYzMytZPLvEMLNXVOzloLKIwU3PFj+uMZiZWYkDg5mZlTgwmJlZiQODmZmV+OazWZsM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\nWYkDg5mZlTgwmJlZiQODmZmV/H9Jkg0RgN/oJgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a8d3908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#bar graph for Florida Keys 2017.\n",
    "plt.bar(year17f[\"Month\"],year17f[\"Mean\"],color='blue')\n",
    "plt.xlabel(\"Month\")\n",
    "plt.ylabel(\"Temperature($^\\circ$C) \")\n",
    "plt.title(\"Florida Keys Sea Surface Temperature 2017\")\n",
    "plt.xticks(months_num,months)\n",
    "plt.ylim(22,34)\n",
    "plt.axhline(y=31.4,color='red')\n",
    "plt.axhline(y=25,color='red')\n",
    "plt.savefig(\"Florida Keys Sea Surface Temperature(2017).png\",bbox_inches='tight')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}