{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Earthquake Patterns in Areas of Fracking</b>\n",
    "\n",
    "by Reva Kakaria\n",
    "\n",
    "According to the USGS, fracking as a method to extract oil and natural gas has been in use in the United States for the past five decades. However, only more recently have newer methods of fracking pushed it into the high rate of use we see today.\n",
    "\n",
    "The following map by the USGS illustrates where in the United States fracking occurred from 2011 to 2014: \n",
    "\n",
    " <img src=https://prd-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/thumbnails/image/horizontal_well_percentage.jpg> \n",
    " \n",
    "In this notebook, I aim to look at seismic data from some of the areas highlighted in the above figure and see whether there has been any increase in earthquakes over the last decades which might correlate to fracking. Of course, there are a number of other factors that could contribute to the presence or absence of seismic activity; however, given that these areas generally are not earthquake-prone, I feel that looking at seismic trends over time is a useful approach.\n",
    "\n",
    "The three areas I will be considering in detail are those of high fracking rates in North Dakota, Oklahoma, and Texas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Step one is to import libraries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "from obspy import UTCDateTime\n",
    "from obspy.clients.fdsn import Client\n",
    "client = Client(\"IRIS\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>North Dakota</b>\n",
    "\n",
    "I will begin with North Dakota, looking at seismic activity with a magnitude of 1.0 or above and a time period from 1950 to 2020. Below, I set my search parameters according to this timeframe, using a latitude and longitude near the center of the red area in the USGS map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "startt = UTCDateTime(\"1950-01-01\")\n",
    "endt = UTCDateTime(\"2019-12-31\")\n",
    "minmag = 1.0\n",
    "maxrad = 1.5\n",
    "lon = -102.484722\n",
    "lat = 47.981667"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat = client.get_events(starttime=startt, endtime=endt, latitude=lat, longitude=lon, maxradius=maxrad, minmagnitude=minmag, catalog=\"ISC\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "28 Event(s) in Catalog:\n",
      "2014-05-06T16:01:14.860000Z | +47.606, -104.427 | 2.6 ML\n",
      "2012-09-28T10:53:42.960000Z | +48.048, -103.350 | 3.5 ML\n",
      "...\n",
      "1982-03-09T13:10:47.030000Z | +48.534, -104.073 | 3.3 MBLG\n",
      "1975-09-05T20:47:40.690000Z | +48.366, -104.377 | 3.9 ML\n",
      "To see all events call 'print(CatalogObject.__str__(print_all=True))'\n"
     ]
    }
   ],
   "source": [
    "print(cat)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, I will create separate lists for the times and magnitudes of the five events. These lists will then be used to graph seismicity over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "times = []\n",
    "magnitudes = []\n",
    "for quake in cat:\n",
    "    times.append(mdates.date2num(quake.origins[0].time.datetime))\n",
    "    magnitudes.append(quake.magnitudes[0].mag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "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": [
    "fig1 = plt.subplots(1,1)\n",
    "plt.xlim([mdates.date2num(startt.datetime),mdates.date2num(endt.datetime)])\n",
    "plt.plot_date(times,magnitudes, color = \"red\", marker='.', markersize = 10) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems that North Dakota had an anomalous burst of seismic activity in the early 2010s, around the same time, according to the USGS map, that fracking was occurring at a high rate.\n",
    "\n",
    "We can also look at the seismicity rate for each year:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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gZPKIWe/bNPqgm/9ZwGdWrOMUBi9B93T9swP49Vnv25SOg2OBf+iOhd3A73Xtj2NwXvmz3WNvnvV+TbkfFoDPd//mHwceu2I9u7vbebPerxH74OndsXzL0LH8fAaf3rkWuK3b34d38/9Y11ffZvDG8F4GH4x4EnBzt56dwB/Mcr+8UlSSGnHYnnKRpNYY6JLUCANdkhphoEtSIwx0SWqEgS5JjTDQJakRBrokNeL/AXelKPmZq1LbAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2, axes = plt.subplots(1,1)\n",
    "axes.hist(times, bins=70, color=\"red\")\n",
    "plt.xlim([mdates.date2num(startt.datetime),mdates.date2num(endt.datetime)])\n",
    "axes.xaxis.set_major_formatter(mdates.DateFormatter('%Y'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, we see a similar trend: a leap in seismicity rates in the early 2010s."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Oklahoma</b>\n",
    "\n",
    "Next, let us look at the region of Oklahoma in which extensive fracking has occurred, using the same process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "lon1 = -99.671389\n",
    "lat1 = 35.613889"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat1 = client.get_events(starttime=startt, endtime=endt, latitude=lat1, longitude=lon1, maxradius=maxrad, minmagnitude=minmag, catalog=\"ISC\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "459 Event(s) in Catalog:\n",
      "2015-08-31T16:05:36.330000Z | +36.515,  -98.469 | 2.5 mb_Lg\n",
      "2015-08-30T21:24:41.670000Z | +36.504,  -98.728 | 2.5 mb_Lg\n",
      "...\n",
      "1974-02-15T13:33:49.940000Z | +36.383, -100.525 | 4.5 mb\n",
      "1966-07-20T09:04:59.500000Z | +35.650, -101.140 | 3.9 mb\n",
      "To see all events call 'print(CatalogObject.__str__(print_all=True))'\n"
     ]
    }
   ],
   "source": [
    "print(cat1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "times1 = []\n",
    "magnitudes1 = []\n",
    "for quake in cat1:\n",
    "    times1.append(mdates.date2num(quake.origins[0].time.datetime))\n",
    "    magnitudes1.append(quake.magnitudes[0].mag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "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": [
    "fig3 = plt.subplots(1,1)\n",
    "plt.xlim([mdates.date2num(startt.datetime),mdates.date2num(endt.datetime)])\n",
    "plt.plot_date(times1,magnitudes1, color = \"blue\", marker='.', markersize = 10) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Clearly, Oklahoma has much more seismic activity than North Dakota. Also notable, however, is how much the amount of earthquakes has increased over time. This can better be seen in the graph showing seismicity rates:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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": [
    "fig4, axes = plt.subplots(1,1)\n",
    "axes.hist(times1, bins=70, color=\"blue\")\n",
    "plt.xlim([mdates.date2num(startt.datetime),mdates.date2num(endt.datetime)])\n",
    "axes.xaxis.set_major_formatter(mdates.DateFormatter('%Y'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Much like North Dakota, there has been a significant rise in seismicity rates in Oklahoma since the advent and increase of fracking."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Texas</b>\n",
    "\n",
    "Finally, I will run the same analysis on an area of fracking in Texas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "lon2 = -98.616111\n",
    "lat2 = 27.879167"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat2 = client.get_events(starttime=startt, endtime=endt, latitude=lat2, longitude=lon2, maxradius=maxrad, minmagnitude=minmag, catalog=\"ISC\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "32 Event(s) in Catalog:\n",
      "2015-01-31T03:30:02.570000Z | +29.031,  -97.969 | 2.8 mb_Lg\n",
      "2015-01-31T02:17:02.280000Z | +28.846,  -98.080 | 3.1 mb_Lg\n",
      "...\n",
      "1984-03-03T01:03:30.040000Z | +29.096,  -98.270 | 3.9 MbLg\n",
      "1983-07-23T15:24:35.360000Z | +28.444,  -98.023 | 3.4 MbLg\n",
      "To see all events call 'print(CatalogObject.__str__(print_all=True))'\n"
     ]
    }
   ],
   "source": [
    "print(cat2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "times2 = []\n",
    "magnitudes2 = []\n",
    "for quake in cat2:\n",
    "    times2.append(mdates.date2num(quake.origins[0].time.datetime))\n",
    "    magnitudes2.append(quake.magnitudes[0].mag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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": [
    "fig5 = plt.subplots(1,1)\n",
    "plt.xlim([mdates.date2num(startt.datetime),mdates.date2num(endt.datetime)])\n",
    "plt.plot_date(times2,magnitudes2, color = \"green\", marker='.', markersize = 10) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There appears to be a slight concentration of earthquakes in the early 2010s."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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": [
    "fig6, axes = plt.subplots(1,1)\n",
    "axes.hist(times2, bins=70, color=\"green\")\n",
    "plt.xlim([mdates.date2num(startt.datetime),mdates.date2num(endt.datetime)])\n",
    "axes.xaxis.set_major_formatter(mdates.DateFormatter('%Y'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once again, rates of sesmic activity have been higher in the late 2000s and early 2010s."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Conclusions</b>\n",
    "\n",
    "From this simple study of number and rate of earthquakes, it seems that seismic activity has increased in areas in which fracking has occurred. As a control, I attempted to perform the same analysis on central Iowa, where no fracking has occurred. However, my catalog request returned no earthquakes. I increased the maximum radius, and the results can be seen below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "lat3 = 42.034722\n",
    "lon3 = -93.62"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat3 = client.get_events(starttime=startt, endtime=endt, latitude=lat3, longitude=lon3, maxradius=2, minmagnitude=minmag, catalog=\"ISC\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2 Event(s) in Catalog:\n",
      "2004-07-16T12:17:28.360000Z | +40.654,  -95.522 | 3.3 MN\n",
      "1995-02-11T05:54:10.860000Z | +40.460,  -94.891 | 3.1 mbLg\n"
     ]
    }
   ],
   "source": [
    "print(cat3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "times3 = []\n",
    "magnitudes3 = []\n",
    "for quake in cat3:\n",
    "    times3.append(mdates.date2num(quake.origins[0].time.datetime))\n",
    "    magnitudes3.append(quake.magnitudes[0].mag)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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taUDSAUl/Jumk5pySmZlNl5wrjVFgZUScD3QBqyVdWNfnBeA64DsTbP/ziOhK05pS+5eBOyPil4GXgesbrt7MzGbUcUMjCsNpcW6aoq7P8xGxC3g956CSBKwEHkpN9wKX5xZtZmatkTWmIalD0iBwGNgSEQMNHGOepJqkrZLGg+FU4EhEvJaWDwKnT3LsdWn72tDQUAOHNTOzZssKjYgYi4guYCmwQtJ5DRzjrPRA808CfyjplxopMCI2RkQ1IqqVSqWRTc3MrMkaunsqIo4A/cDqBrY5lH4+C3wPWA78FFgoaU7qthQ41EgtZmY283LunqpIWpjm5wOrgP05O5e0SNLJaf404NeAfRERFOEzfqfVWuCRxss3M7OZlHOlsQTol7QLeJxiTGOzpA2S1gBIukDSQeDjwF2S9qZtfwWoSdpJERJfioh9ad3NwA2SDlCMcXyzeadlZmbTQcUf/e2hWq1GrVZrdRlmZm1F0vY0tnzC/I1wMzPL5tAwM7NsDg0zM8vm0DAzs2wODTMzy+bQMDOzbA4NMzPL5tAwM7NsDg0zM8vm0DAzs2wODTMzy+bQMDOzbA4NMzPL5tAwM7NsDg0zM8vm0DAzs2w5j3udJ2mbpJ2S9kpaP0GfiyQ9Iek1SVeU2rsk/TBtt0vSVaV190h6TtJgmrqad1pmZjYd5mT0GQVWRsSwpLnAY5J6I2Jrqc8LwHXAjXXbHgWujYinJb0b2C6pLyKOpPU3RcRDJ3gOZmY2Q44bGlE8D3Y4Lc5NU9T1eR5A0ut17U+V5v9B0mGgAhzBzMzaTtaYhqQOSYPAYWBLRAw0eiBJK4CTgGdKzbenj63ulHTyJNutk1STVBsaGmr0sGZm1kRZoRERYxHRBSwFVkg6r5GDSFoC/Anw6YgYvxq5BTgXuABYDNw8ybE3RkQ1IqqVSqWRw5qZWZM1dPdUGovoB1bnbiPpFOAvgVvL4yAR8WIURoG7gRWN1GJmZjMv5+6piqSFaX4+sArYn7NzSScBDwPfrh/wTlcfSBJwObCnsdLNzGym5VxpLAH6Je0CHqcY09gsaYOkNQCSLpB0EPg4cJekvWnbK4GLgOsmuLX2Pkm7gd3AacAfNPG8zMxsGqi4Oao9VKvVqNVqrS7DzKytSNoeEdVm7MvfCDczs2wODTMzy+bQMDOzbA4NMzPL5tAwM7NsDg0zM8vm0DAzs2wODTMzy+bQMDOzbA4NMzPL5tAwM7NsDg0zM8vm0DAzs2wODTMzy+bQMDOzbDlP7psnaZuknZL2Slo/QZ+LJD0h6TVJV9StWyvp6TStLbV/SNJuSQckfS09wc/MzGaxORl9RoGVETEsaS7wmKTe8vO+gReA64AbyxtKWgx8EagCAWyXtCkiXgb+CPhtYAD4K4rnjvee4PmYWYPGxsbo7e1lx44dLF++nJ6eHjo6Olpdls1Sxw2NKB7tN5wW56Yp6vo8DyDp9brNL6V4POxLaf0WYLWk7wGnjAePpG9TPCfcoWE2g8bGxrj00ksZGBhgZGSEzs5Ouru76evrc3DYhLLGNCR1SBoEDlOEwEDm/k8HflxaPpjaTk/z9e1mNoN6e3sZGBhgeHiYiGB4eJiBgQF6e/33m00sKzQiYiwiuoClwApJ501vWW+QtE5STVJtaGhopg5r9rawY8cORkZG3tQ2MjLC4OBgiyqy2a6hu6ci4gjQTzH+kOMQcEZpeWlqO5Tm69snOubGiKhGRLVSqTRSrpkdx/Lly+ns7HxTW2dnJ11dXS2qyGa7nLunKpIWpvn5wCpgf+b++4BLJC2StAi4BOiLiBeBVyRdmO6auhZ4ZEpnYGZT1tPTQ3d3NwsWLEASCxYsoLu7m56enlaXZrNUzt1TS4B7JXVQhMwDEbFZ0gagFhGbJF0APAwsAn5D0vqI+NWIeEnSbcDjaV8bxgfFgc8B9wDzKQbA/SGq2Qzr6Oigr6+P3t5eBgcH6erq8t1Tdkwqbo5qD9VqNWq1WqvLMDNrK5K2R0S1GfvyN8LNzCybQ8PMzLI5NMzMLJtDw8zMsjk0zMwsW1vdPSXp/wJPtrqOE3Aa8JNWFzFF7Vw7uP5Wc/2t9c8j4heasaOc72nMJk8267axVpBUa9f627l2cP2t5vpbS1LTvqvgj6fMzCybQ8PMzLK1W2hsbHUBJ6id62/n2sH1t5rrb62m1d9WA+FmZtZa7XalYWZmLdTS0JD0LUmHJe0ptZ0v6YeSdkv6C0mnpPZlkn4uaTBN3yht86HU/4Ckr6V/bn1W1Z/WfSCt25vWz2uX+iV9qvTaD0p6XVJXG9U/V9K9qf1Hkm4pbbNa0pOp/i/MRO1TqP8kSXen9p2SPlLaZsZff0lnSOqXtC+9n38vtS+WtEXS0+nnotSuVNsBSbskfbC0r7Wp/9OS1k537VOs/9z032VU0o11+5rx988U6v9Uet13S/qBpPOnXH9EtGwCLgI+COwptT0OfDjNfwa4Lc0vK/er28824EJAFP/Ees8srH8OsAs4Py2fCnS0S/11270feKbNXv9PAven+XcCz6f3VAfwDPAe4CRgJ/C+WVj/54G70/y7gO3AO1r1+lM8MuGDaf4XgKeA9wF3AF9I7V8AvpzmP5ZqU6p1ILUvBp5NPxel+UWzsP53ARcAtwM3lvbTkvfPFOr/l+OvK9BTev0brn/afzEyTn5Z3S/Nz3hjrOUMYN9E/epevP2l5U8Ad83C+j8G/Gm71l+3zX8Fbm+n+lNdf0ER3qemX7LFwL+geDDY+Pa3ALfMwvq/DvxWqd+jwIpWv/6l4z5C8YC2J4ElpffGk2n+LuATpf5PpvVvqre+32ypv9Tvv/Dm0Gjp+6fR+lP7IuDQVOufjWMae4HfTPMf582Piz1b0g5J35f0r1Pb6cDBUp+Dqa1VJqv/vUBI6pP0hKT/nNrbpf6yq4Dvpvl2qf8hYAR4EXgB+G9RPBDsdODHpe1na/07gTWS5kg6G/hQWtfy11/SMmA5MAD8YhRP5gT438AvpvnJXueWv/6Z9U+mHeu/njceetdw/bMxND4DfE7SdorLrn9K7S8CZ0bEcuAG4DsqjRfMIpPVPwf4V8Cn0s9/K+nftKbEY5qsfgAkdQNHI2LPRBvPApPVvwIYA94NnA38J0nvaU2JxzRZ/d+i+IWuAX8I/IDifFpK0gLgfwD/ISJeKa+L4k/XWX175tutfkkfpQiNm6d6zFn3z4hExH6KZ4kj6b3Ar6f2UWA0zW+X9AzFX++HgKWlXSxNbS0xWf0Uv/B/FxE/Sev+iuLz7D+lPeofdzVvXGVA+7z+nwT+Z0S8ChyW9PdAleKvrPLV1KysPyJeA/7jeD9JP6D4iO1lWvT6S5pL8T+s+yLiz1Pz/5G0JCJelLQEOJzaDzHx63wI+Ehd+/ems+5xDdY/mcnOa9o1Wr+kDwB/TDHm9dPU3HD9s+5KQ9K70s93AL8PfCMtV1Q8p5z0F+I5wLPpUuwVSRemu0aupfh8ryUmqx/oA94v6Z2S5gAfpvi8ul3qH2+7Erh/vK2N6n8BWJnWdVIMxu6nGHg+R9LZkk6iCMVNM133uGO8/9+Z6kbSKuC1iGjZ+ycd65vAjyLiq6VVm4DxO6DWlmrZBFyrwoXAz1LtfcAlkhalO30uSW2zrf7JtOT902j9ks4E/pxiXOypE6p/pgds6gZkvkvxsdOrFH+JXw/8HsVfUE8BX+KNQcF/R/F57yDwBPAbpf1UgT0UdwH89/FtZlP9qf816Rz2AHe0Yf0fAbZOsJ9ZXz+wAHgwvf77gJtK+/lY6v8McOssff8voxjk/BHwN8BZrXz9KT5iDYo7AgfT9DGKmwweBZ5OdS5O/UUxmP8MsBuolvb1GeBAmj49Q699o/X/s/Tf6BXgSJo/pVXvnynU/8cUV6XjfWtTff/7G+FmZpZt1n08ZWZms5dDw8zMsjk0zMwsm0PDzMyyOTTMzCybQ8PMzLI5NMzMLJtDw8zMsv0/bzAJyv7JyrkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig7 = plt.subplots(1,1)\n",
    "plt.xlim([mdates.date2num(startt.datetime),mdates.date2num(endt.datetime)])\n",
    "plt.plot_date(times3,magnitudes3, color = \"black\", marker='.', markersize = 10) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "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": [
    "fig8, axes = plt.subplots(1,1)\n",
    "axes.hist(times3, bins=70, color=\"black\")\n",
    "plt.xlim([mdates.date2num(startt.datetime),mdates.date2num(endt.datetime)])\n",
    "axes.xaxis.set_major_formatter(mdates.DateFormatter('%Y'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given that earthquakes are so rare in Iowa, it is effectively impossible to say whether or not earthquake rates are remaining constant there. It is of note that earthquakes are also relatively uncommon in North Dakota, but that state still saw an increase in seismicity.  \n",
    "\n",
    "More exhaustive studies would better determine whether fracking has indeed contributed to this rise in seismic activity in certain states. The answer to this question would help us make more informed decisions about how we extract natural resources, and how we can prevent said extraction from adversely affecting the environment and society."
   ]
  }
 ],
 "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": 4
}