Time Series analysis for CHNEP Step0

gistfile1.txt

{
 "metadata": {
  "name": "step0"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "Read data into a Pandas Data Frame and then plot the time series in the frame below."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "import pandas as pd\n#df = pd.read_csv(\"DataDownload_745449_row.txt\", sep=\"\\t\",infer_datetime_format=True)\ndf = pd.read_csv(\"DataDownload_745449_row.txt\", \n                 usecols=[\"SampleDate\",\"Rainfall_IN\"],\n                 sep=\"\\t\",\n                 infer_datetime_format=True)",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 81
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "df.plot(x='SampleDate', y='Rainfall_IN', figsize=(18,7))",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 82,
       "text": "<matplotlib.axes.AxesSubplot at 0x10c68b00>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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YN9HXKk+17kJfn7Sb8BUBCQDwGEFCt+3cKfLzn7ddCgA2Nd3e0r7r0R3ayvoE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\n3nuT26eOu2xk1bMZAffcXD+OReUbSz2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UMYeEaaDUZkDgiitE/vZvpz+fFVxlyIa/CEgY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       "text": "<matplotlib.figure.Figure at 0x10c439e8>"
      }
     ],
     "prompt_number": 82
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "Bin each row by Month and then:\n\n1. print some summary stats for each month \n\n2. boxplot each month. \n\nThe plots need some prettying up but this is a proof of concept."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "import numpy\nimport matplotlib.pyplot as plt\n\n# define lambda function to get Month from DateTime\ngetmo = lambda x: x.month\n\n# Create a new column in the data frame with the numeric month for each row \n#  (this is irrespective of year)\ndf[\"SampleDate_dt\"] = pd.to_datetime(df[\"SampleDate\"])\ndf[\"SampleDate_mo\"] = df[\"SampleDate_dt\"].apply(getmo)\n\n#grouped = df[\"SampleDate_dt\"].groupby(lambda x: x.month)  #Someday/Maybe\ngrouped = df.groupby(\"SampleDate_mo\")\n\nfig = plt.figure(figsize=(18,7))\n\ncnt = 1\nfor SampleDate_mo, group in grouped:\n    ax1 = fig.add_subplot(1,12,cnt)\n    ax1.set_ylim(bottom=0, top=.5)\n    print SampleDate_mo\n    print \"Min\\tMean\\t\\tMax\\tStdDev\"\n    print min(group[\"Rainfall_IN\"]),'\\t', \\\n          mean(group[\"Rainfall_IN\"]), \\\n          max(group[\"Rainfall_IN\"]),'\\t', \\\n          numpy.std(group[\"Rainfall_IN\"], axis=0)\n    ax1.boxplot(group[\"Rainfall_IN\"].values)\n    cnt += 1\nplt.show()",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "1\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.0513452914798 1.69 \t0.206182430569\n2\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.0865470852018 5.68 \t0.437422337787\n3"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.0650806451613 1.95 \t0.224515593135\n4\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.0646443514644 1.49 \t0.211202422979\n5"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.0425225225225 1.27 \t0.159543088978\n6\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.302543103448 3.25 \t0.566586115015\n7"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.316910569106 3.58 \t0.578224265268\n8\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.237449392713 2.69 \t0.456366094951\n9"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.189152542373 4.04 \t0.539525177734\n10\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.0592244897959 1.81 \t0.195439354893\n11"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.0318396226415 1.25 \t0.141727591273\n12\nMin\tMean\t\tMax\tStdDev\n0.0 \t0.0569565217391 1.34 \t0.195433404261\n"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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8bKakB005RuPV1tQD5uJpGk/TftI0nqaxWpmblsSDEAEAoFClLGgDjNPLRQP7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\njPX/AeBzRri85ZoxAAAAAElFTkSuQmCC\n",
       "text": "<matplotlib.figure.Figure at 0xd8a9c50>"
      }
     ],
     "prompt_number": 83
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "Cells below are scratchpad\n=========================="
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "import pandas as pd\n\ndf = pd.read_csv(\"DataDownload_745449_row.txt\", \n                 usecols=[\"SampleDate\",\"Rainfall_IN\"],\n                 sep=\"\\t\",\n                 infer_datetime_format=True)",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 41
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "df[\"SampleDate_dt\"] = pd.to_datetime(df[\"SampleDate\"])\ngetmo = lambda x: x.month\ndf[\"SampleDate_mo\"] = df[\"SampleDate_dt\"].apply(getmo)\ncols = df.columns.tolist()\ncols = [cols[-1],cols[1]]\ndf = df[cols]\n#df = df.drop('SampleDate',1)\n#df = df.drop('SampleDate_dt',1)\n#df = df[[\"SampleDate_mo\"],[\"Rainfall_IN\"]]",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 44
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "\n\n    \n    \n",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 79
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": "",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>SampleDate</th>\n      <th>WBodyID</th>\n      <th>WaterBodyName</th>\n      <th>DataSource</th>\n      <th>Column1</th>\n      <th>Column2</th>\n      <th>ReachCode</th>\n      <th>POR_Min</th>\n      <th>POR_Max</th>\n      <th>Rainfall_IN</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0 </th>\n      <td> 12/10/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>1 </th>\n      <td> 12/11/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.03</td>\n    </tr>\n    <tr>\n      <th>2 </th>\n      <td> 12/12/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.17</td>\n    </tr>\n    <tr>\n      <th>3 </th>\n      <td> 12/13/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>4 </th>\n      <td> 12/14/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>5 </th>\n      <td> 12/15/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>6 </th>\n      <td> 12/16/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>7 </th>\n      <td> 12/17/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.30</td>\n    </tr>\n    <tr>\n      <th>8 </th>\n      <td> 12/18/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>9 </th>\n      <td> 12/19/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.01</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td> 12/20/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td> 12/21/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td> 12/22/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td> 12/23/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td> 12/24/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td> 12/25/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td> 12/26/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td> 12/27/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td> 12/28/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.41</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td> 12/29/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td> 12/30/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td> 12/31/2000 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>   1/1/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>   1/2/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td>   1/3/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>   1/4/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>   1/5/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>   1/6/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>   1/7/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>   1/8/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.26</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>   1/9/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>31</th>\n      <td>  1/10/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>32</th>\n      <td>  1/11/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td>  1/12/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.07</td>\n    </tr>\n    <tr>\n      <th>34</th>\n      <td>  1/13/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>35</th>\n      <td>  1/14/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>36</th>\n      <td>  1/15/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>37</th>\n      <td>  1/16/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>38</th>\n      <td>  1/17/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>39</th>\n      <td>  1/18/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>40</th>\n      <td>  1/19/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>41</th>\n      <td>  1/20/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.06</td>\n    </tr>\n    <tr>\n      <th>42</th>\n      <td>  1/21/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>43</th>\n      <td>  1/22/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>44</th>\n      <td>  1/23/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>45</th>\n      <td>  1/24/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>  1/25/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td>  1/26/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>  1/27/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>49</th>\n      <td>  1/28/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>50</th>\n      <td>  1/29/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>51</th>\n      <td>  1/30/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>52</th>\n      <td>  1/31/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.01</td>\n    </tr>\n    <tr>\n      <th>53</th>\n      <td>   2/1/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.25</td>\n    </tr>\n    <tr>\n      <th>54</th>\n      <td>   2/2/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>55</th>\n      <td>   2/3/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.26</td>\n    </tr>\n    <tr>\n      <th>56</th>\n      <td>   2/4/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>57</th>\n      <td>   2/5/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.01</td>\n    </tr>\n    <tr>\n      <th>58</th>\n      <td>   2/6/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th>59</th>\n      <td>   2/7/2001 0:00</td>\n      <td> 41</td>\n      <td> Hillsborough River</td>\n      <td> USGS_NWIS</td>\n      <td> 2304500</td>\n      <td>   HILLSBOROUGH RIVER NEAR TAMPA FL</td>\n      <td> 3.100210e+12</td>\n      <td> 12/10/2000 0:00</td>\n      <td> 11/3/2008 0:00</td>\n      <td> 0.00</td>\n    </tr>\n    <tr>\n      <th></th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n  </tbody>\n</table>\n<p>2803 rows \u00d7 10 columns</p>\n</div>",
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 29,
       "text": "         SampleDate  WBodyID       WaterBodyName DataSource  Column1  \\\n0   12/10/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n1   12/11/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n2   12/12/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n3   12/13/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n4   12/14/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n5   12/15/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n6   12/16/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n7   12/17/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n8   12/18/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n9   12/19/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n10  12/20/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n11  12/21/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n12  12/22/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n13  12/23/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n14  12/24/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n15  12/25/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n16  12/26/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n17  12/27/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n18  12/28/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n19  12/29/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n20  12/30/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n21  12/31/2000 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n22    1/1/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n23    1/2/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n24    1/3/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n25    1/4/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n26    1/5/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n27    1/6/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n28    1/7/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n29    1/8/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n30    1/9/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n31   1/10/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n32   1/11/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n33   1/12/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n34   1/13/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n35   1/14/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n36   1/15/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n37   1/16/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n38   1/17/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n39   1/18/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n40   1/19/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n41   1/20/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n42   1/21/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n43   1/22/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n44   1/23/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n45   1/24/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n46   1/25/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n47   1/26/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n48   1/27/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n49   1/28/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n50   1/29/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n51   1/30/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n52   1/31/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n53    2/1/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n54    2/2/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n55    2/3/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n56    2/4/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n57    2/5/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n58    2/6/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n59    2/7/2001 0:00       41  Hillsborough River  USGS_NWIS  2304500   \n                ...      ...                 ...        ...      ...   \n\n                               Column2     ReachCode          POR_Min  \\\n0     HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n1     HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n2     HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n3     HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n4     HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n5     HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n6     HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n7     HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n8     HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n9     HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n10    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n11    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n12    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n13    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n14    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n15    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n16    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n17    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n18    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n19    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n20    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n21    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n22    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n23    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n24    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n25    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n26    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n27    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n28    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n29    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n30    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n31    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n32    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n33    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n34    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n35    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n36    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n37    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n38    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n39    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n40    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n41    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n42    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n43    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n44    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n45    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n46    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n47    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n48    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n49    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n50    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n51    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n52    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n53    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n54    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n55    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n56    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n57    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n58    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n59    HILLSBOROUGH RIVER NEAR TAMPA FL  3.100210e+12  12/10/2000 0:00   \n                                   ...           ...              ...   \n\n           POR_Max  Rainfall_IN  \n0   11/3/2008 0:00         0.00  \n1   11/3/2008 0:00         0.03  \n2   11/3/2008 0:00         0.17  \n3   11/3/2008 0:00         0.00  \n4   11/3/2008 0:00         0.00  \n5   11/3/2008 0:00         0.00  \n6   11/3/2008 0:00         0.00  \n7   11/3/2008 0:00         0.30  \n8   11/3/2008 0:00         0.00  \n9   11/3/2008 0:00         0.01  \n10  11/3/2008 0:00         0.00  \n11  11/3/2008 0:00         0.00  \n12  11/3/2008 0:00         0.00  \n13  11/3/2008 0:00         0.00  \n14  11/3/2008 0:00         0.00  \n15  11/3/2008 0:00         0.00  \n16  11/3/2008 0:00         0.00  \n17  11/3/2008 0:00         0.00  \n18  11/3/2008 0:00         0.41  \n19  11/3/2008 0:00         0.00  \n20  11/3/2008 0:00         0.00  \n21  11/3/2008 0:00         0.00  \n22  11/3/2008 0:00         0.00  \n23  11/3/2008 0:00         0.00  \n24  11/3/2008 0:00         0.00  \n25  11/3/2008 0:00         0.00  \n26  11/3/2008 0:00         0.00  \n27  11/3/2008 0:00         0.00  \n28  11/3/2008 0:00         0.00  \n29  11/3/2008 0:00         0.26  \n30  11/3/2008 0:00         0.00  \n31  11/3/2008 0:00         0.00  \n32  11/3/2008 0:00         0.00  \n33  11/3/2008 0:00         0.07  \n34  11/3/2008 0:00         0.00  \n35  11/3/2008 0:00         0.00  \n36  11/3/2008 0:00         0.00  \n37  11/3/2008 0:00         0.00  \n38  11/3/2008 0:00         0.00  \n39  11/3/2008 0:00         0.00  \n40  11/3/2008 0:00         0.00  \n41  11/3/2008 0:00         0.06  \n42  11/3/2008 0:00         0.00  \n43  11/3/2008 0:00         0.00  \n44  11/3/2008 0:00         0.00  \n45  11/3/2008 0:00         0.00  \n46  11/3/2008 0:00         0.00  \n47  11/3/2008 0:00         0.00  \n48  11/3/2008 0:00         0.00  \n49  11/3/2008 0:00         0.00  \n50  11/3/2008 0:00         0.00  \n51  11/3/2008 0:00         0.00  \n52  11/3/2008 0:00         0.01  \n53  11/3/2008 0:00         0.25  \n54  11/3/2008 0:00         0.00  \n55  11/3/2008 0:00         0.26  \n56  11/3/2008 0:00         0.00  \n57  11/3/2008 0:00         0.01  \n58  11/3/2008 0:00         0.00  \n59  11/3/2008 0:00         0.00  \n               ...          ...  \n\n[2803 rows x 10 columns]"
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 50
    }
   ],
   "metadata": {}
  }
 ]
}