10_local_south.ipynb

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  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML\n",
      "import folium\n",
      "import random as RD\n",
      "import pandas as pd\n",
      "%pylab inline\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def inline_map(map):\n",
      "    \"\"\"\n",
      "    Embeds the HTML source of the map directly into the IPython notebook.\n",
      "    \n",
      "    This method will not work if the map depends on any files (json data). Also this uses\n",
      "    the HTML5 srcdoc attribute, which may not be supported in all browsers.\n",
      "    \"\"\"\n",
      "    map._build_map()\n",
      "    return HTML('<iframe srcdoc=\"{srcdoc}\" style=\"width: 100%; height: 510px; border: none\"></iframe>'.format(srcdoc=map.HTML.replace('\"', '&quot;')))\n",
      "\n",
      "def embed_map(map, path=\"map.html\"):\n",
      "    \"\"\"\n",
      "    Embeds a linked iframe to the map into the IPython notebook.\n",
      "    \n",
      "    Note: this method will not capture the source of the map into the notebook.\n",
      "    This method should work for all maps (as long as they use relative urls).\n",
      "    \"\"\"\n",
      "    map.create_map(path=path)\n",
      "    return HTML('<iframe src=\"files/{path}\" style=\"width: 100%; height: 510px; border: none\"></iframe>'.format(path=path))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Base layer for south"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import folium\n",
      "map_osm = folium.Map(location=[33.7550, -87.3900], zoom_start=5)\n",
      "map_osm.geo_json(geo_path = 'data/south.json')\n",
      "embed_map(map_osm)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=\"files/map.html\" style=\"width: 100%; height: 510px; border: none\"></iframe>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "<IPython.core.display.HTML at 0x109c649d0>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Binding Attribute Data to the Map"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import json\n",
      "\n",
      "f = open(r'data/south.json')\n",
      "q = json.load(f)\n",
      "f.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "q.keys()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "[u'type', u'features']"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "features = q['features']\n",
      "len(features)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "1412"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "indices = []\n",
      "values = []\n",
      "for feature in features:\n",
      "    indices.append(str(feature['properties']['FIPS']))\n",
      "    values.append(feature['properties']['HR80'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.DataFrame({'HR80': values,\n",
      "                   'FIPS': indices} )"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "y = np.array(df.HR80.tolist())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import pysal as ps\n",
      "w = ps.queen_from_shapefile('data/south.shp')\n",
      "w.transform = 'r'"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "y = np.array(df['HR80'].tolist())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Local Moran\n",
      "$li_i = \\frac{n-1}{\\sum_j z_j^2}z_i \\sum_j w_{i,j} z_j$"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "li_hr80 = ps.Moran_Local(y,w)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "li_hr80.p_sim.shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "(1412,)"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sig01 = 1.* (li_hr80.p_sim<=0.01)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sig01.sum()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "166.0"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sig05 = 1.* (li_hr80.p_sim<=0.05)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sig05.sum()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "376.0"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df['sig01']  = sig01\n",
      "df['sig05'] = sig05"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "map_osm = folium.Map(location=[33.7550, -87.3900], zoom_start=5,)\n",
      "map_osm.geo_json(geo_path='data/south.json',\n",
      "                 key_on='feature.properties.FIPS',\n",
      "                 data_out='data.json', data=df,\n",
      "                 columns=['FIPS','HR80'],\n",
      "                 fill_color='YlGn', fill_opacity=0.7,\n",
      "                 line_opacity=0.2,\n",
      "                 legend_name='Homicide Rate HR80')\n",
      "embed_map(map_osm)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=\"files/map.html\" style=\"width: 100%; height: 510px; border: none\"></iframe>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 22,
       "text": [
        "<IPython.core.display.HTML at 0x10c770190>"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "map_osm = folium.Map(location=[33.7550, -87.3900], zoom_start=5,)\n",
      "map_osm.geo_json(geo_path='data/south.json',\n",
      "                 key_on='feature.properties.FIPS',\n",
      "                 data_out='data.json', data=df,\n",
      "                 columns=['FIPS','sig01'],\n",
      "                 fill_color='YlGn', fill_opacity=0.7,\n",
      "                 line_opacity=0.2,\n",
      "                 threshold_scale=[0,1],\n",
      "                 legend_name='Homicide Rate HR80 - Significant LISA (0.01)')\n",
      "embed_map(map_osm)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=\"files/map.html\" style=\"width: 100%; height: 510px; border: none\"></iframe>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 23,
       "text": [
        "<IPython.core.display.HTML at 0x10c6780d0>"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "raw",
     "metadata": {},
     "source": [
      "Note that folium only is bound to threshold scales - no discrete or ordinal scale yet, so we have to fake it with two class threshold scales."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "map_osm = folium.Map(location=[33.7550, -87.3900], zoom_start=5,)\n",
      "map_osm.geo_json(geo_path='data/south.json',\n",
      "                 key_on='feature.properties.FIPS',\n",
      "                 data_out='data.json', data=df,\n",
      "                 columns=['FIPS','sig01'],\n",
      "                 fill_color='YlGn', fill_opacity=0.7,\n",
      "                 line_opacity=0.2,\n",
      "                 legend_name='Homicide Rate HR80 - Significant LISA (0.01)')\n",
      "embed_map(map_osm)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=\"files/map.html\" style=\"width: 100%; height: 510px; border: none\"></iframe>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 24,
       "text": [
        "<IPython.core.display.HTML at 0x10c5d0a90>"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "map_osm = folium.Map(location=[33.7550, -87.3900], zoom_start=5,)\n",
      "map_osm.geo_json(geo_path='data/south.json',\n",
      "                 key_on='feature.properties.FIPS',\n",
      "                 data_out='data.json', data=df,\n",
      "                 columns=['FIPS','sig05'],\n",
      "                 fill_color='YlGn', fill_opacity=0.7,\n",
      "                 line_opacity=0.2,\n",
      "                 legend_name='Homicide Rate HR80 - Significant LISA (0.05)')\n",
      "embed_map(map_osm)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=\"files/map.html\" style=\"width: 100%; height: 510px; border: none\"></iframe>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 25,
       "text": [
        "<IPython.core.display.HTML at 0x10c687e90>"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "li_hr80.q"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 26,
       "text": [
        "array([3, 3, 3, ..., 3, 3, 3])"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cold_spots = 1. * (li_hr80.q==3) * (li_hr80.p_sim < 0.01)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cold_spots.sum()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 28,
       "text": [
        "69.0"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Cold spots in pandas'y way\n",
      "lisa_df = pd.DataFrame({'q': li_hr80.q, 'p_sim': li_hr80.p_sim})\n",
      "cold = lisa_df[(lisa_df['q']==3) & (lisa_df['p_sim']<0.01)]\n",
      "print cold.info()\n",
      "print '\\n~~~~~~~~~~\\n'\n",
      "# Hot spots in pandas'y way\n",
      "hot = lisa_df[(lisa_df['q']==1) & (lisa_df['p_sim']<0.01)]\n",
      "print hot.info()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "<class 'pandas.core.frame.DataFrame'>\n",
        "Int64Index: 69 entries, 5 to 1286\n",
        "Data columns (total 2 columns):\n",
        "p_sim    69 non-null float64\n",
        "q        69 non-null int64\n",
        "dtypes: float64(1), int64(1)None\n",
        "\n",
        "~~~~~~~~~~\n",
        "\n",
        "<class 'pandas.core.frame.DataFrame'>\n",
        "Int64Index: 51 entries, 199 to 1401\n",
        "Data columns (total 2 columns):\n",
        "p_sim    51 non-null float64\n",
        "q        51 non-null int64\n",
        "dtypes: float64(1), int64(1)None\n"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "hot_spots = 1. * (li_hr80.q==1) * (li_hr80.p_sim < 0.01)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 30
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "hot_spots.sum()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 31,
       "text": [
        "51.0"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df['hot_01'] = hot_spots\n",
      "df['cold_01'] = cold_spots"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 32
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.hot_01"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 33,
       "text": [
        "0     0\n",
        "1     0\n",
        "2     0\n",
        "3     0\n",
        "4     0\n",
        "5     0\n",
        "6     0\n",
        "7     0\n",
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        "9     0\n",
        "10    0\n",
        "11    0\n",
        "12    0\n",
        "13    0\n",
        "14    0\n",
        "...\n",
        "1397    1\n",
        "1398    0\n",
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        "1407    0\n",
        "1408    0\n",
        "1409    0\n",
        "1410    0\n",
        "1411    0\n",
        "Name: hot_01, Length: 1412, dtype: float64"
       ]
      }
     ],
     "prompt_number": 33
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.cold_01"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 34,
       "text": [
        "0     0\n",
        "1     0\n",
        "2     0\n",
        "3     0\n",
        "4     0\n",
        "5     1\n",
        "6     1\n",
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        "9     0\n",
        "10    1\n",
        "11    1\n",
        "12    0\n",
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        "...\n",
        "1397    0\n",
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        "1400    0\n",
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        "1404    0\n",
        "1405    0\n",
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        "1407    0\n",
        "1408    0\n",
        "1409    0\n",
        "1410    0\n",
        "1411    0\n",
        "Name: cold_01, Length: 1412, dtype: float64"
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "map_osm = folium.Map(location=[33.7550, -87.3900], zoom_start=5,)\n",
      "map_osm.geo_json(geo_path='data/south.json',\n",
      "                 key_on='feature.properties.FIPS',\n",
      "                 data_out='data.json', data=df,\n",
      "                 columns=['FIPS','hot_01'],\n",
      "                 fill_color='RdPu', fill_opacity=0.7,\n",
      "                 line_opacity=0.2,\n",
      "                 threshold_scale=[0,1],\n",
      "                 legend_name='Homicide Rate HR80 - Hot Spots (0.01)')\n",
      "embed_map(map_osm)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=\"files/map.html\" style=\"width: 100%; height: 510px; border: none\"></iframe>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 35,
       "text": [
        "<IPython.core.display.HTML at 0x10c6a44d0>"
       ]
      }
     ],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "map_osm = folium.Map(location=[33.7550, -87.3900], zoom_start=5,)\n",
      "map_osm.geo_json(geo_path='data/south.json',\n",
      "                 key_on='feature.properties.FIPS',\n",
      "                 data_out='data.json', data=df,\n",
      "                 columns=['FIPS','cold_01'],\n",
      "                 fill_color='YlGnBu', fill_opacity=0.7,\n",
      "                 line_opacity=0.2,\n",
      "                 threshold_scale=[0,1],\n",
      "                 legend_name='Homicide Rate HR80 - Cold Spots (0.01)')\n",
      "embed_map(map_osm)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=\"files/map.html\" style=\"width: 100%; height: 510px; border: none\"></iframe>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 36,
       "text": [
        "<IPython.core.display.HTML at 0x10cb08110>"
       ]
      }
     ],
     "prompt_number": 36
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dbf = ps.open('data/south.dbf')\n",
      "dbf.header"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 37,
       "text": [
        "['NAME',\n",
        " 'STATE_NAME',\n",
        " 'STATE_FIPS',\n",
        " 'CNTY_FIPS',\n",
        " 'FIPS',\n",
        " 'STFIPS',\n",
        " 'COFIPS',\n",
        " 'FIPSNO',\n",
        " 'SOUTH',\n",
        " 'HR60',\n",
        " 'HR70',\n",
        " 'HR80',\n",
        " 'HR90',\n",
        " 'HC60',\n",
        " 'HC70',\n",
        " 'HC80',\n",
        " 'HC90',\n",
        " 'PO60',\n",
        " 'PO70',\n",
        " 'PO80',\n",
        " 'PO90',\n",
        " 'RD60',\n",
        " 'RD70',\n",
        " 'RD80',\n",
        " 'RD90',\n",
        " 'PS60',\n",
        " 'PS70',\n",
        " 'PS80',\n",
        " 'PS90',\n",
        " 'UE60',\n",
        " 'UE70',\n",
        " 'UE80',\n",
        " 'UE90',\n",
        " 'DV60',\n",
        " 'DV70',\n",
        " 'DV80',\n",
        " 'DV90',\n",
        " 'MA60',\n",
        " 'MA70',\n",
        " 'MA80',\n",
        " 'MA90',\n",
        " 'POL60',\n",
        " 'POL70',\n",
        " 'POL80',\n",
        " 'POL90',\n",
        " 'DNL60',\n",
        " 'DNL70',\n",
        " 'DNL80',\n",
        " 'DNL90',\n",
        " 'MFIL59',\n",
        " 'MFIL69',\n",
        " 'MFIL79',\n",
        " 'MFIL89',\n",
        " 'FP59',\n",
        " 'FP69',\n",
        " 'FP79',\n",
        " 'FP89',\n",
        " 'BLK60',\n",
        " 'BLK70',\n",
        " 'BLK80',\n",
        " 'BLK90',\n",
        " 'GI59',\n",
        " 'GI69',\n",
        " 'GI79',\n",
        " 'GI89',\n",
        " 'FH60',\n",
        " 'FH70',\n",
        " 'FH80',\n",
        " 'FH90']"
       ]
      }
     ],
     "prompt_number": 37
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      " df['STATE_NAME'] = dbf.by_col('STATE_NAME')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 38
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df['County'] = dbf.by_col('NAME')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 39
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "hot_01 = df['hot_01']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 40
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "hot  = df[hot_01>0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 41
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "hot"
     ],
     "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>FIPS</th>\n",
        "      <th>HR80</th>\n",
        "      <th>sig01</th>\n",
        "      <th>sig05</th>\n",
        "      <th>hot_01</th>\n",
        "      <th>cold_01</th>\n",
        "      <th>STATE_NAME</th>\n",
        "      <th>County</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>199 </th>\n",
        "      <td> 21025</td>\n",
        "      <td> 19.603231</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>    Breathitt</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>231 </th>\n",
        "      <td> 21193</td>\n",
        "      <td> 37.516413</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>        Perry</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>240 </th>\n",
        "      <td> 21051</td>\n",
        "      <td> 29.301453</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>         Clay</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>247 </th>\n",
        "      <td> 21131</td>\n",
        "      <td> 38.077319</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>       Leslie</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>285 </th>\n",
        "      <td> 21095</td>\n",
        "      <td> 20.689600</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>       Harlan</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>305 </th>\n",
        "      <td> 21013</td>\n",
        "      <td> 19.419361</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>         Bell</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>712 </th>\n",
        "      <td> 28027</td>\n",
        "      <td> 15.349333</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Coahoma</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>804 </th>\n",
        "      <td> 48387</td>\n",
        "      <td> 10.351324</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>    Red River</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>831 </th>\n",
        "      <td> 13045</td>\n",
        "      <td> 14.197991</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Carroll</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>850 </th>\n",
        "      <td> 28015</td>\n",
        "      <td> 10.229133</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Carroll</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>862 </th>\n",
        "      <td> 13245</td>\n",
        "      <td> 19.637099</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>     Richmond</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>868 </th>\n",
        "      <td> 13077</td>\n",
        "      <td> 11.884147</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>       Coweta</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>876 </th>\n",
        "      <td> 13141</td>\n",
        "      <td> 14.085499</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Hancock</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>905 </th>\n",
        "      <td> 13163</td>\n",
        "      <td> 21.735587</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>    Jefferson</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>908 </th>\n",
        "      <td> 28007</td>\n",
        "      <td> 20.135917</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>       Attala</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>914 </th>\n",
        "      <td> 13285</td>\n",
        "      <td> 14.665787</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>        Troup</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>924 </th>\n",
        "      <td> 01123</td>\n",
        "      <td> 13.789775</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>   Tallapoosa</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>927 </th>\n",
        "      <td> 48063</td>\n",
        "      <td> 10.781671</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>         Camp</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>930 </th>\n",
        "      <td> 28163</td>\n",
        "      <td> 23.157459</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>        Yazoo</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>932 </th>\n",
        "      <td> 22017</td>\n",
        "      <td> 23.115310</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>   Louisiana</td>\n",
        "      <td>        Caddo</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>939 </th>\n",
        "      <td> 01065</td>\n",
        "      <td> 10.681022</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>         Hale</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>951 </th>\n",
        "      <td> 01119</td>\n",
        "      <td> 15.771627</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>       Sumter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>963 </th>\n",
        "      <td> 28099</td>\n",
        "      <td> 11.209663</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Neshoba</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>966 </th>\n",
        "      <td> 48459</td>\n",
        "      <td> 12.822755</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>       Upshur</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>968 </th>\n",
        "      <td> 28089</td>\n",
        "      <td> 20.025793</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Madison</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>978 </th>\n",
        "      <td> 48203</td>\n",
        "      <td> 15.944386</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>     Harrison</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>995 </th>\n",
        "      <td> 28149</td>\n",
        "      <td> 14.204454</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>       Warren</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1024</th>\n",
        "      <td> 13283</td>\n",
        "      <td> 10.952303</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>     Treutlen</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1033</th>\n",
        "      <td> 48365</td>\n",
        "      <td> 12.867529</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>       Panola</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1037</th>\n",
        "      <td> 22031</td>\n",
        "      <td> 18.139179</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>   Louisiana</td>\n",
        "      <td>      De Soto</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1058</th>\n",
        "      <td> 13259</td>\n",
        "      <td> 33.921303</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Stewart</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1059</th>\n",
        "      <td> 13307</td>\n",
        "      <td> 14.238929</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Webster</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1060</th>\n",
        "      <td> 13261</td>\n",
        "      <td> 10.217984</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>       Sumter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1062</th>\n",
        "      <td> 01005</td>\n",
        "      <td> 24.236549</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>      Barbour</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1064</th>\n",
        "      <td> 22069</td>\n",
        "      <td> 19.232538</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>   Louisiana</td>\n",
        "      <td> Natchitoches</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1093</th>\n",
        "      <td> 13239</td>\n",
        "      <td> 28.284542</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Quitman</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1101</th>\n",
        "      <td> 13243</td>\n",
        "      <td> 17.362920</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>     Randolph</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1119</th>\n",
        "      <td> 01067</td>\n",
        "      <td> 13.070187</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>        Henry</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1120</th>\n",
        "      <td> 13061</td>\n",
        "      <td> 18.763486</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>         Clay</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1134</th>\n",
        "      <td> 13095</td>\n",
        "      <td> 17.540724</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>    Dougherty</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1141</th>\n",
        "      <td> 13037</td>\n",
        "      <td> 17.491691</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Calhoun</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1162</th>\n",
        "      <td> 13007</td>\n",
        "      <td> 17.507003</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>        Baker</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1184</th>\n",
        "      <td> 01003</td>\n",
        "      <td> 11.456795</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>      Baldwin</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1254</th>\n",
        "      <td> 48339</td>\n",
        "      <td> 12.193192</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>   Montgomery</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1379</th>\n",
        "      <td> 12093</td>\n",
        "      <td> 24.674299</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>   Okeechobee</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1391</th>\n",
        "      <td> 12099</td>\n",
        "      <td> 11.267840</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>   Palm Beach</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1392</th>\n",
        "      <td> 12051</td>\n",
        "      <td> 21.506533</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>       Hendry</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1395</th>\n",
        "      <td> 12071</td>\n",
        "      <td> 12.341709</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>          Lee</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1397</th>\n",
        "      <td> 12021</td>\n",
        "      <td> 22.875931</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>      Collier</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1399</th>\n",
        "      <td> 12011</td>\n",
        "      <td> 15.615793</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>      Broward</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1401</th>\n",
        "      <td> 12087</td>\n",
        "      <td> 12.133105</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>       Monroe</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 42,
       "text": [
        "       FIPS       HR80  sig01  sig05  hot_01  cold_01   STATE_NAME  \\\n",
        "199   21025  19.603231      1      1       1        0     Kentucky   \n",
        "231   21193  37.516413      1      1       1        0     Kentucky   \n",
        "240   21051  29.301453      1      1       1        0     Kentucky   \n",
        "247   21131  38.077319      1      1       1        0     Kentucky   \n",
        "285   21095  20.689600      1      1       1        0     Kentucky   \n",
        "305   21013  19.419361      1      1       1        0     Kentucky   \n",
        "712   28027  15.349333      1      1       1        0  Mississippi   \n",
        "804   48387  10.351324      1      1       1        0        Texas   \n",
        "831   13045  14.197991      1      1       1        0      Georgia   \n",
        "850   28015  10.229133      1      1       1        0  Mississippi   \n",
        "862   13245  19.637099      1      1       1        0      Georgia   \n",
        "868   13077  11.884147      1      1       1        0      Georgia   \n",
        "876   13141  14.085499      1      1       1        0      Georgia   \n",
        "905   13163  21.735587      1      1       1        0      Georgia   \n",
        "908   28007  20.135917      1      1       1        0  Mississippi   \n",
        "914   13285  14.665787      1      1       1        0      Georgia   \n",
        "924   01123  13.789775      1      1       1        0      Alabama   \n",
        "927   48063  10.781671      1      1       1        0        Texas   \n",
        "930   28163  23.157459      1      1       1        0  Mississippi   \n",
        "932   22017  23.115310      1      1       1        0    Louisiana   \n",
        "939   01065  10.681022      1      1       1        0      Alabama   \n",
        "951   01119  15.771627      1      1       1        0      Alabama   \n",
        "963   28099  11.209663      1      1       1        0  Mississippi   \n",
        "966   48459  12.822755      1      1       1        0        Texas   \n",
        "968   28089  20.025793      1      1       1        0  Mississippi   \n",
        "978   48203  15.944386      1      1       1        0        Texas   \n",
        "995   28149  14.204454      1      1       1        0  Mississippi   \n",
        "1024  13283  10.952303      1      1       1        0      Georgia   \n",
        "1033  48365  12.867529      1      1       1        0        Texas   \n",
        "1037  22031  18.139179      1      1       1        0    Louisiana   \n",
        "1058  13259  33.921303      1      1       1        0      Georgia   \n",
        "1059  13307  14.238929      1      1       1        0      Georgia   \n",
        "1060  13261  10.217984      1      1       1        0      Georgia   \n",
        "1062  01005  24.236549      1      1       1        0      Alabama   \n",
        "1064  22069  19.232538      1      1       1        0    Louisiana   \n",
        "1093  13239  28.284542      1      1       1        0      Georgia   \n",
        "1101  13243  17.362920      1      1       1        0      Georgia   \n",
        "1119  01067  13.070187      1      1       1        0      Alabama   \n",
        "1120  13061  18.763486      1      1       1        0      Georgia   \n",
        "1134  13095  17.540724      1      1       1        0      Georgia   \n",
        "1141  13037  17.491691      1      1       1        0      Georgia   \n",
        "1162  13007  17.507003      1      1       1        0      Georgia   \n",
        "1184  01003  11.456795      1      1       1        0      Alabama   \n",
        "1254  48339  12.193192      1      1       1        0        Texas   \n",
        "1379  12093  24.674299      1      1       1        0      Florida   \n",
        "1391  12099  11.267840      1      1       1        0      Florida   \n",
        "1392  12051  21.506533      1      1       1        0      Florida   \n",
        "1395  12071  12.341709      1      1       1        0      Florida   \n",
        "1397  12021  22.875931      1      1       1        0      Florida   \n",
        "1399  12011  15.615793      1      1       1        0      Florida   \n",
        "1401  12087  12.133105      1      1       1        0      Florida   \n",
        "\n",
        "            County  \n",
        "199      Breathitt  \n",
        "231          Perry  \n",
        "240           Clay  \n",
        "247         Leslie  \n",
        "285         Harlan  \n",
        "305           Bell  \n",
        "712        Coahoma  \n",
        "804      Red River  \n",
        "831        Carroll  \n",
        "850        Carroll  \n",
        "862       Richmond  \n",
        "868         Coweta  \n",
        "876        Hancock  \n",
        "905      Jefferson  \n",
        "908         Attala  \n",
        "914          Troup  \n",
        "924     Tallapoosa  \n",
        "927           Camp  \n",
        "930          Yazoo  \n",
        "932          Caddo  \n",
        "939           Hale  \n",
        "951         Sumter  \n",
        "963        Neshoba  \n",
        "966         Upshur  \n",
        "968        Madison  \n",
        "978       Harrison  \n",
        "995         Warren  \n",
        "1024      Treutlen  \n",
        "1033        Panola  \n",
        "1037       De Soto  \n",
        "1058       Stewart  \n",
        "1059       Webster  \n",
        "1060        Sumter  \n",
        "1062       Barbour  \n",
        "1064  Natchitoches  \n",
        "1093       Quitman  \n",
        "1101      Randolph  \n",
        "1119         Henry  \n",
        "1120          Clay  \n",
        "1134     Dougherty  \n",
        "1141       Calhoun  \n",
        "1162         Baker  \n",
        "1184       Baldwin  \n",
        "1254    Montgomery  \n",
        "1379    Okeechobee  \n",
        "1391    Palm Beach  \n",
        "1392        Hendry  \n",
        "1395           Lee  \n",
        "1397       Collier  \n",
        "1399       Broward  \n",
        "1401        Monroe  "
       ]
      }
     ],
     "prompt_number": 42
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[['STATE_NAME', 'County']]"
     ],
     "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>STATE_NAME</th>\n",
        "      <th>County</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0   </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>        Hancock</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1   </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>         Brooke</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2   </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>           Ohio</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3   </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>       Marshall</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4   </th>\n",
        "      <td>      Delaware</td>\n",
        "      <td>     New Castle</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5   </th>\n",
        "      <td>      Maryland</td>\n",
        "      <td>     Washington</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6   </th>\n",
        "      <td>      Maryland</td>\n",
        "      <td>       Allegany</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7   </th>\n",
        "      <td>      Maryland</td>\n",
        "      <td>          Cecil</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8   </th>\n",
        "      <td>      Maryland</td>\n",
        "      <td>        Garrett</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9   </th>\n",
        "      <td>      Maryland</td>\n",
        "      <td>        Harford</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>     Monongalia</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>        Preston</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12  </th>\n",
        "      <td>      Maryland</td>\n",
        "      <td>        Carroll</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13  </th>\n",
        "      <td>      Maryland</td>\n",
        "      <td>      Baltimore</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>         Wetzel</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15  </th>\n",
        "      <td>      Maryland</td>\n",
        "      <td>      Frederick</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>         Morgan</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>        Mineral</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>         Marion</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>       Berkeley</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>          Tyler</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>      Hampshire</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>      Jefferson</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>      Pleasants</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>       Harrison</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25  </th>\n",
        "      <td>      Virginia</td>\n",
        "      <td>      Frederick</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>26  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>      Doddridge</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>27  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>         Taylor</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>28  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>           Wood</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>29  </th>\n",
        "      <td> West Virginia</td>\n",
        "      <td>        Ritchie</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1382</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>       Sarasota</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1383</th>\n",
        "      <td>         Texas</td>\n",
        "      <td>       Jim Hogg</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1384</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>        De Soto</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1385</th>\n",
        "      <td>         Texas</td>\n",
        "      <td>         Zapata</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1386</th>\n",
        "      <td>         Texas</td>\n",
        "      <td>         Brooks</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1387</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>         Martin</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1388</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>         Glades</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1389</th>\n",
        "      <td>         Texas</td>\n",
        "      <td>         Kenedy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1390</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>      Charlotte</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1391</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>     Palm Beach</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1392</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>         Hendry</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1393</th>\n",
        "      <td>         Texas</td>\n",
        "      <td>          Starr</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1394</th>\n",
        "      <td>         Texas</td>\n",
        "      <td>        Hidalgo</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1395</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>            Lee</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1396</th>\n",
        "      <td>         Texas</td>\n",
        "      <td>        Willacy</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1397</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>        Collier</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1398</th>\n",
        "      <td>         Texas</td>\n",
        "      <td>        Cameron</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1399</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>        Broward</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1400</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>           Dade</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1401</th>\n",
        "      <td>       Florida</td>\n",
        "      <td>         Monroe</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1402</th>\n",
        "      <td>      Virginia</td>\n",
        "      <td>        Bedford</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1403</th>\n",
        "      <td>      Virginia</td>\n",
        "      <td>        Norfolk</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1404</th>\n",
        "      <td>      Virginia</td>\n",
        "      <td>    Greensville</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1405</th>\n",
        "      <td>      Virginia</td>\n",
        "      <td>        Fairfax</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1406</th>\n",
        "      <td>      Virginia</td>\n",
        "      <td>    Southampton</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1407</th>\n",
        "      <td>      Virginia</td>\n",
        "      <td>        Halifax</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1408</th>\n",
        "      <td>      Virginia</td>\n",
        "      <td>     Rockbridge</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1409</th>\n",
        "      <td>      Virginia</td>\n",
        "      <td>        Roanoke</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1410</th>\n",
        "      <td>      Virginia</td>\n",
        "      <td>           York</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1411</th>\n",
        "      <td>      Virginia</td>\n",
        "      <td> Prince William</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>1412 rows \u00d7 2 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 43,
       "text": [
        "         STATE_NAME          County\n",
        "0     West Virginia         Hancock\n",
        "1     West Virginia          Brooke\n",
        "2     West Virginia            Ohio\n",
        "3     West Virginia        Marshall\n",
        "4          Delaware      New Castle\n",
        "5          Maryland      Washington\n",
        "6          Maryland        Allegany\n",
        "7          Maryland           Cecil\n",
        "8          Maryland         Garrett\n",
        "9          Maryland         Harford\n",
        "10    West Virginia      Monongalia\n",
        "11    West Virginia         Preston\n",
        "12         Maryland         Carroll\n",
        "13         Maryland       Baltimore\n",
        "14    West Virginia          Wetzel\n",
        "15         Maryland       Frederick\n",
        "16    West Virginia          Morgan\n",
        "17    West Virginia         Mineral\n",
        "18    West Virginia          Marion\n",
        "19    West Virginia        Berkeley\n",
        "20    West Virginia           Tyler\n",
        "21    West Virginia       Hampshire\n",
        "22    West Virginia       Jefferson\n",
        "23    West Virginia       Pleasants\n",
        "24    West Virginia        Harrison\n",
        "25         Virginia       Frederick\n",
        "26    West Virginia       Doddridge\n",
        "27    West Virginia          Taylor\n",
        "28    West Virginia            Wood\n",
        "29    West Virginia         Ritchie\n",
        "...             ...             ...\n",
        "1382        Florida        Sarasota\n",
        "1383          Texas        Jim Hogg\n",
        "1384        Florida         De Soto\n",
        "1385          Texas          Zapata\n",
        "1386          Texas          Brooks\n",
        "1387        Florida          Martin\n",
        "1388        Florida          Glades\n",
        "1389          Texas          Kenedy\n",
        "1390        Florida       Charlotte\n",
        "1391        Florida      Palm Beach\n",
        "1392        Florida          Hendry\n",
        "1393          Texas           Starr\n",
        "1394          Texas         Hidalgo\n",
        "1395        Florida             Lee\n",
        "1396          Texas         Willacy\n",
        "1397        Florida         Collier\n",
        "1398          Texas         Cameron\n",
        "1399        Florida         Broward\n",
        "1400        Florida            Dade\n",
        "1401        Florida          Monroe\n",
        "1402       Virginia         Bedford\n",
        "1403       Virginia         Norfolk\n",
        "1404       Virginia     Greensville\n",
        "1405       Virginia         Fairfax\n",
        "1406       Virginia     Southampton\n",
        "1407       Virginia         Halifax\n",
        "1408       Virginia      Rockbridge\n",
        "1409       Virginia         Roanoke\n",
        "1410       Virginia            York\n",
        "1411       Virginia  Prince William\n",
        "\n",
        "[1412 rows x 2 columns]"
       ]
      }
     ],
     "prompt_number": 43
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.head()"
     ],
     "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>FIPS</th>\n",
        "      <th>HR80</th>\n",
        "      <th>sig01</th>\n",
        "      <th>sig05</th>\n",
        "      <th>hot_01</th>\n",
        "      <th>cold_01</th>\n",
        "      <th>STATE_NAME</th>\n",
        "      <th>County</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 54029</td>\n",
        "      <td> 6.597720</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> West Virginia</td>\n",
        "      <td>    Hancock</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 54009</td>\n",
        "      <td> 3.213677</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> West Virginia</td>\n",
        "      <td>     Brooke</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 54069</td>\n",
        "      <td> 7.601796</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> West Virginia</td>\n",
        "      <td>       Ohio</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 54051</td>\n",
        "      <td> 4.005640</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> West Virginia</td>\n",
        "      <td>   Marshall</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 10003</td>\n",
        "      <td> 7.116872</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td>      Delaware</td>\n",
        "      <td> New Castle</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 44,
       "text": [
        "    FIPS      HR80  sig01  sig05  hot_01  cold_01     STATE_NAME      County\n",
        "0  54029  6.597720      0      0       0        0  West Virginia     Hancock\n",
        "1  54009  3.213677      0      0       0        0  West Virginia      Brooke\n",
        "2  54069  7.601796      0      1       0        0  West Virginia        Ohio\n",
        "3  54051  4.005640      0      0       0        0  West Virginia    Marshall\n",
        "4  10003  7.116872      0      0       0        0       Delaware  New Castle"
       ]
      }
     ],
     "prompt_number": 44
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.tail()"
     ],
     "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>FIPS</th>\n",
        "      <th>HR80</th>\n",
        "      <th>sig01</th>\n",
        "      <th>sig05</th>\n",
        "      <th>hot_01</th>\n",
        "      <th>cold_01</th>\n",
        "      <th>STATE_NAME</th>\n",
        "      <th>County</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1407</th>\n",
        "      <td> 51083</td>\n",
        "      <td> 15.034136</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> Virginia</td>\n",
        "      <td>        Halifax</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1408</th>\n",
        "      <td> 51163</td>\n",
        "      <td>  3.967782</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> Virginia</td>\n",
        "      <td>     Rockbridge</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1409</th>\n",
        "      <td> 51161</td>\n",
        "      <td>  4.127839</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> Virginia</td>\n",
        "      <td>        Roanoke</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1410</th>\n",
        "      <td> 51199</td>\n",
        "      <td>  5.280349</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> Virginia</td>\n",
        "      <td>           York</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1411</th>\n",
        "      <td> 51153</td>\n",
        "      <td>  3.000030</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> Virginia</td>\n",
        "      <td> Prince William</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 45,
       "text": [
        "       FIPS       HR80  sig01  sig05  hot_01  cold_01 STATE_NAME  \\\n",
        "1407  51083  15.034136      0      0       0        0   Virginia   \n",
        "1408  51163   3.967782      0      0       0        0   Virginia   \n",
        "1409  51161   4.127839      0      0       0        0   Virginia   \n",
        "1410  51199   5.280349      0      0       0        0   Virginia   \n",
        "1411  51153   3.000030      0      0       0        0   Virginia   \n",
        "\n",
        "              County  \n",
        "1407         Halifax  \n",
        "1408      Rockbridge  \n",
        "1409         Roanoke  \n",
        "1410            York  \n",
        "1411  Prince William  "
       ]
      }
     ],
     "prompt_number": 45
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[[0,2,4]]"
     ],
     "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>FIPS</th>\n",
        "      <th>sig01</th>\n",
        "      <th>hot_01</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0   </th>\n",
        "      <td> 54029</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1   </th>\n",
        "      <td> 54009</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2   </th>\n",
        "      <td> 54069</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3   </th>\n",
        "      <td> 54051</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4   </th>\n",
        "      <td> 10003</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5   </th>\n",
        "      <td> 24043</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6   </th>\n",
        "      <td> 24001</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7   </th>\n",
        "      <td> 24015</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8   </th>\n",
        "      <td> 24023</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9   </th>\n",
        "      <td> 24025</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10  </th>\n",
        "      <td> 54061</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11  </th>\n",
        "      <td> 54077</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12  </th>\n",
        "      <td> 24013</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13  </th>\n",
        "      <td> 24005</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14  </th>\n",
        "      <td> 54103</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15  </th>\n",
        "      <td> 24021</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16  </th>\n",
        "      <td> 54065</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17  </th>\n",
        "      <td> 54057</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18  </th>\n",
        "      <td> 54049</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19  </th>\n",
        "      <td> 54003</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20  </th>\n",
        "      <td> 54095</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21  </th>\n",
        "      <td> 54027</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22  </th>\n",
        "      <td> 54037</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23  </th>\n",
        "      <td> 54073</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24  </th>\n",
        "      <td> 54033</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25  </th>\n",
        "      <td> 51069</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>26  </th>\n",
        "      <td> 54017</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>27  </th>\n",
        "      <td> 54091</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>28  </th>\n",
        "      <td> 54107</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>29  </th>\n",
        "      <td> 54085</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1382</th>\n",
        "      <td> 12115</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1383</th>\n",
        "      <td> 48247</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1384</th>\n",
        "      <td> 12027</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1385</th>\n",
        "      <td> 48505</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1386</th>\n",
        "      <td> 48047</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1387</th>\n",
        "      <td> 12085</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1388</th>\n",
        "      <td> 12043</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1389</th>\n",
        "      <td> 48261</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1390</th>\n",
        "      <td> 12015</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1391</th>\n",
        "      <td> 12099</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1392</th>\n",
        "      <td> 12051</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1393</th>\n",
        "      <td> 48427</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1394</th>\n",
        "      <td> 48215</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1395</th>\n",
        "      <td> 12071</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1396</th>\n",
        "      <td> 48489</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1397</th>\n",
        "      <td> 12021</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1398</th>\n",
        "      <td> 48061</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1399</th>\n",
        "      <td> 12011</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1400</th>\n",
        "      <td> 12025</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1401</th>\n",
        "      <td> 12087</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1402</th>\n",
        "      <td> 51019</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1403</th>\n",
        "      <td> 51710</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1404</th>\n",
        "      <td> 51081</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1405</th>\n",
        "      <td> 51059</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1406</th>\n",
        "      <td> 51175</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1407</th>\n",
        "      <td> 51083</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1408</th>\n",
        "      <td> 51163</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1409</th>\n",
        "      <td> 51161</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1410</th>\n",
        "      <td> 51199</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1411</th>\n",
        "      <td> 51153</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>1412 rows \u00d7 3 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 46,
       "text": [
        "       FIPS  sig01  hot_01\n",
        "0     54029      0       0\n",
        "1     54009      0       0\n",
        "2     54069      0       0\n",
        "3     54051      0       0\n",
        "4     10003      0       0\n",
        "5     24043      1       0\n",
        "6     24001      1       0\n",
        "7     24015      0       0\n",
        "8     24023      1       0\n",
        "9     24025      0       0\n",
        "10    54061      1       0\n",
        "11    54077      1       0\n",
        "12    24013      0       0\n",
        "13    24005      0       0\n",
        "14    54103      1       0\n",
        "15    24021      1       0\n",
        "16    54065      1       0\n",
        "17    54057      0       0\n",
        "18    54049      0       0\n",
        "19    54003      1       0\n",
        "20    54095      1       0\n",
        "21    54027      0       0\n",
        "22    54037      1       0\n",
        "23    54073      1       0\n",
        "24    54033      1       0\n",
        "25    51069      1       0\n",
        "26    54017      1       0\n",
        "27    54091      1       0\n",
        "28    54107      1       0\n",
        "29    54085      1       0\n",
        "...     ...    ...     ...\n",
        "1382  12115      0       0\n",
        "1383  48247      0       0\n",
        "1384  12027      0       0\n",
        "1385  48505      0       0\n",
        "1386  48047      0       0\n",
        "1387  12085      1       0\n",
        "1388  12043      0       0\n",
        "1389  48261      0       0\n",
        "1390  12015      0       0\n",
        "1391  12099      1       1\n",
        "1392  12051      1       1\n",
        "1393  48427      0       0\n",
        "1394  48215      0       0\n",
        "1395  12071      1       1\n",
        "1396  48489      0       0\n",
        "1397  12021      1       1\n",
        "1398  48061      0       0\n",
        "1399  12011      1       1\n",
        "1400  12025      0       0\n",
        "1401  12087      1       1\n",
        "1402  51019      0       0\n",
        "1403  51710      0       0\n",
        "1404  51081      0       0\n",
        "1405  51059      0       0\n",
        "1406  51175      0       0\n",
        "1407  51083      0       0\n",
        "1408  51163      0       0\n",
        "1409  51161      0       0\n",
        "1410  51199      0       0\n",
        "1411  51153      0       0\n",
        "\n",
        "[1412 rows x 3 columns]"
       ]
      }
     ],
     "prompt_number": 46
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[df.hot_01 > 0 ].all()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 47,
       "text": [
        "FIPS           True\n",
        "HR80           True\n",
        "sig01          True\n",
        "sig05          True\n",
        "hot_01         True\n",
        "cold_01       False\n",
        "STATE_NAME     True\n",
        "County         True\n",
        "dtype: bool"
       ]
      }
     ],
     "prompt_number": 47
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[0:10]"
     ],
     "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>FIPS</th>\n",
        "      <th>HR80</th>\n",
        "      <th>sig01</th>\n",
        "      <th>sig05</th>\n",
        "      <th>hot_01</th>\n",
        "      <th>cold_01</th>\n",
        "      <th>STATE_NAME</th>\n",
        "      <th>County</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 54029</td>\n",
        "      <td> 6.597720</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> West Virginia</td>\n",
        "      <td>    Hancock</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 54009</td>\n",
        "      <td> 3.213677</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> West Virginia</td>\n",
        "      <td>     Brooke</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 54069</td>\n",
        "      <td> 7.601796</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> West Virginia</td>\n",
        "      <td>       Ohio</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 54051</td>\n",
        "      <td> 4.005640</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> West Virginia</td>\n",
        "      <td>   Marshall</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 10003</td>\n",
        "      <td> 7.116872</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td>      Delaware</td>\n",
        "      <td> New Castle</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td> 24043</td>\n",
        "      <td> 2.063326</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>      Maryland</td>\n",
        "      <td> Washington</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td> 24001</td>\n",
        "      <td> 3.724487</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>      Maryland</td>\n",
        "      <td>   Allegany</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td> 24015</td>\n",
        "      <td> 6.067626</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td>      Maryland</td>\n",
        "      <td>      Cecil</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td> 24023</td>\n",
        "      <td> 5.031826</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>      Maryland</td>\n",
        "      <td>    Garrett</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td> 24025</td>\n",
        "      <td> 3.426300</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td>      Maryland</td>\n",
        "      <td>    Harford</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 48,
       "text": [
        "    FIPS      HR80  sig01  sig05  hot_01  cold_01     STATE_NAME      County\n",
        "0  54029  6.597720      0      0       0        0  West Virginia     Hancock\n",
        "1  54009  3.213677      0      0       0        0  West Virginia      Brooke\n",
        "2  54069  7.601796      0      1       0        0  West Virginia        Ohio\n",
        "3  54051  4.005640      0      0       0        0  West Virginia    Marshall\n",
        "4  10003  7.116872      0      0       0        0       Delaware  New Castle\n",
        "5  24043  2.063326      1      1       0        1       Maryland  Washington\n",
        "6  24001  3.724487      1      1       0        1       Maryland    Allegany\n",
        "7  24015  6.067626      0      1       0        0       Maryland       Cecil\n",
        "8  24023  5.031826      1      1       0        1       Maryland     Garrett\n",
        "9  24025  3.426300      0      0       0        0       Maryland     Harford"
       ]
      }
     ],
     "prompt_number": 48
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "hot = df[df['hot_01']>0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 49
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "hot"
     ],
     "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>FIPS</th>\n",
        "      <th>HR80</th>\n",
        "      <th>sig01</th>\n",
        "      <th>sig05</th>\n",
        "      <th>hot_01</th>\n",
        "      <th>cold_01</th>\n",
        "      <th>STATE_NAME</th>\n",
        "      <th>County</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>199 </th>\n",
        "      <td> 21025</td>\n",
        "      <td> 19.603231</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>    Breathitt</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>231 </th>\n",
        "      <td> 21193</td>\n",
        "      <td> 37.516413</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>        Perry</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>240 </th>\n",
        "      <td> 21051</td>\n",
        "      <td> 29.301453</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>         Clay</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>247 </th>\n",
        "      <td> 21131</td>\n",
        "      <td> 38.077319</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>       Leslie</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>285 </th>\n",
        "      <td> 21095</td>\n",
        "      <td> 20.689600</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>       Harlan</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>305 </th>\n",
        "      <td> 21013</td>\n",
        "      <td> 19.419361</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>         Bell</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>712 </th>\n",
        "      <td> 28027</td>\n",
        "      <td> 15.349333</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Coahoma</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>804 </th>\n",
        "      <td> 48387</td>\n",
        "      <td> 10.351324</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>    Red River</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>831 </th>\n",
        "      <td> 13045</td>\n",
        "      <td> 14.197991</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Carroll</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>850 </th>\n",
        "      <td> 28015</td>\n",
        "      <td> 10.229133</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Carroll</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>862 </th>\n",
        "      <td> 13245</td>\n",
        "      <td> 19.637099</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>     Richmond</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>868 </th>\n",
        "      <td> 13077</td>\n",
        "      <td> 11.884147</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>       Coweta</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>876 </th>\n",
        "      <td> 13141</td>\n",
        "      <td> 14.085499</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Hancock</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>905 </th>\n",
        "      <td> 13163</td>\n",
        "      <td> 21.735587</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>    Jefferson</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>908 </th>\n",
        "      <td> 28007</td>\n",
        "      <td> 20.135917</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>       Attala</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>914 </th>\n",
        "      <td> 13285</td>\n",
        "      <td> 14.665787</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>        Troup</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>924 </th>\n",
        "      <td> 01123</td>\n",
        "      <td> 13.789775</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>   Tallapoosa</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>927 </th>\n",
        "      <td> 48063</td>\n",
        "      <td> 10.781671</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>         Camp</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>930 </th>\n",
        "      <td> 28163</td>\n",
        "      <td> 23.157459</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>        Yazoo</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>932 </th>\n",
        "      <td> 22017</td>\n",
        "      <td> 23.115310</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>   Louisiana</td>\n",
        "      <td>        Caddo</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>939 </th>\n",
        "      <td> 01065</td>\n",
        "      <td> 10.681022</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>         Hale</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>951 </th>\n",
        "      <td> 01119</td>\n",
        "      <td> 15.771627</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>       Sumter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>963 </th>\n",
        "      <td> 28099</td>\n",
        "      <td> 11.209663</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Neshoba</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>966 </th>\n",
        "      <td> 48459</td>\n",
        "      <td> 12.822755</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>       Upshur</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>968 </th>\n",
        "      <td> 28089</td>\n",
        "      <td> 20.025793</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Madison</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>978 </th>\n",
        "      <td> 48203</td>\n",
        "      <td> 15.944386</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>     Harrison</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>995 </th>\n",
        "      <td> 28149</td>\n",
        "      <td> 14.204454</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>       Warren</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1024</th>\n",
        "      <td> 13283</td>\n",
        "      <td> 10.952303</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>     Treutlen</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1033</th>\n",
        "      <td> 48365</td>\n",
        "      <td> 12.867529</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>       Panola</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1037</th>\n",
        "      <td> 22031</td>\n",
        "      <td> 18.139179</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>   Louisiana</td>\n",
        "      <td>      De Soto</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1058</th>\n",
        "      <td> 13259</td>\n",
        "      <td> 33.921303</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Stewart</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1059</th>\n",
        "      <td> 13307</td>\n",
        "      <td> 14.238929</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Webster</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1060</th>\n",
        "      <td> 13261</td>\n",
        "      <td> 10.217984</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>       Sumter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1062</th>\n",
        "      <td> 01005</td>\n",
        "      <td> 24.236549</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>      Barbour</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1064</th>\n",
        "      <td> 22069</td>\n",
        "      <td> 19.232538</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>   Louisiana</td>\n",
        "      <td> Natchitoches</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1093</th>\n",
        "      <td> 13239</td>\n",
        "      <td> 28.284542</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Quitman</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1101</th>\n",
        "      <td> 13243</td>\n",
        "      <td> 17.362920</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>     Randolph</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1119</th>\n",
        "      <td> 01067</td>\n",
        "      <td> 13.070187</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>        Henry</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1120</th>\n",
        "      <td> 13061</td>\n",
        "      <td> 18.763486</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>         Clay</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1134</th>\n",
        "      <td> 13095</td>\n",
        "      <td> 17.540724</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>    Dougherty</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1141</th>\n",
        "      <td> 13037</td>\n",
        "      <td> 17.491691</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Calhoun</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1162</th>\n",
        "      <td> 13007</td>\n",
        "      <td> 17.507003</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>        Baker</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1184</th>\n",
        "      <td> 01003</td>\n",
        "      <td> 11.456795</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>      Baldwin</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1254</th>\n",
        "      <td> 48339</td>\n",
        "      <td> 12.193192</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>   Montgomery</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1379</th>\n",
        "      <td> 12093</td>\n",
        "      <td> 24.674299</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>   Okeechobee</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1391</th>\n",
        "      <td> 12099</td>\n",
        "      <td> 11.267840</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>   Palm Beach</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1392</th>\n",
        "      <td> 12051</td>\n",
        "      <td> 21.506533</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>       Hendry</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1395</th>\n",
        "      <td> 12071</td>\n",
        "      <td> 12.341709</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>          Lee</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1397</th>\n",
        "      <td> 12021</td>\n",
        "      <td> 22.875931</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>      Collier</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1399</th>\n",
        "      <td> 12011</td>\n",
        "      <td> 15.615793</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>      Broward</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1401</th>\n",
        "      <td> 12087</td>\n",
        "      <td> 12.133105</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>       Monroe</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 50,
       "text": [
        "       FIPS       HR80  sig01  sig05  hot_01  cold_01   STATE_NAME  \\\n",
        "199   21025  19.603231      1      1       1        0     Kentucky   \n",
        "231   21193  37.516413      1      1       1        0     Kentucky   \n",
        "240   21051  29.301453      1      1       1        0     Kentucky   \n",
        "247   21131  38.077319      1      1       1        0     Kentucky   \n",
        "285   21095  20.689600      1      1       1        0     Kentucky   \n",
        "305   21013  19.419361      1      1       1        0     Kentucky   \n",
        "712   28027  15.349333      1      1       1        0  Mississippi   \n",
        "804   48387  10.351324      1      1       1        0        Texas   \n",
        "831   13045  14.197991      1      1       1        0      Georgia   \n",
        "850   28015  10.229133      1      1       1        0  Mississippi   \n",
        "862   13245  19.637099      1      1       1        0      Georgia   \n",
        "868   13077  11.884147      1      1       1        0      Georgia   \n",
        "876   13141  14.085499      1      1       1        0      Georgia   \n",
        "905   13163  21.735587      1      1       1        0      Georgia   \n",
        "908   28007  20.135917      1      1       1        0  Mississippi   \n",
        "914   13285  14.665787      1      1       1        0      Georgia   \n",
        "924   01123  13.789775      1      1       1        0      Alabama   \n",
        "927   48063  10.781671      1      1       1        0        Texas   \n",
        "930   28163  23.157459      1      1       1        0  Mississippi   \n",
        "932   22017  23.115310      1      1       1        0    Louisiana   \n",
        "939   01065  10.681022      1      1       1        0      Alabama   \n",
        "951   01119  15.771627      1      1       1        0      Alabama   \n",
        "963   28099  11.209663      1      1       1        0  Mississippi   \n",
        "966   48459  12.822755      1      1       1        0        Texas   \n",
        "968   28089  20.025793      1      1       1        0  Mississippi   \n",
        "978   48203  15.944386      1      1       1        0        Texas   \n",
        "995   28149  14.204454      1      1       1        0  Mississippi   \n",
        "1024  13283  10.952303      1      1       1        0      Georgia   \n",
        "1033  48365  12.867529      1      1       1        0        Texas   \n",
        "1037  22031  18.139179      1      1       1        0    Louisiana   \n",
        "1058  13259  33.921303      1      1       1        0      Georgia   \n",
        "1059  13307  14.238929      1      1       1        0      Georgia   \n",
        "1060  13261  10.217984      1      1       1        0      Georgia   \n",
        "1062  01005  24.236549      1      1       1        0      Alabama   \n",
        "1064  22069  19.232538      1      1       1        0    Louisiana   \n",
        "1093  13239  28.284542      1      1       1        0      Georgia   \n",
        "1101  13243  17.362920      1      1       1        0      Georgia   \n",
        "1119  01067  13.070187      1      1       1        0      Alabama   \n",
        "1120  13061  18.763486      1      1       1        0      Georgia   \n",
        "1134  13095  17.540724      1      1       1        0      Georgia   \n",
        "1141  13037  17.491691      1      1       1        0      Georgia   \n",
        "1162  13007  17.507003      1      1       1        0      Georgia   \n",
        "1184  01003  11.456795      1      1       1        0      Alabama   \n",
        "1254  48339  12.193192      1      1       1        0        Texas   \n",
        "1379  12093  24.674299      1      1       1        0      Florida   \n",
        "1391  12099  11.267840      1      1       1        0      Florida   \n",
        "1392  12051  21.506533      1      1       1        0      Florida   \n",
        "1395  12071  12.341709      1      1       1        0      Florida   \n",
        "1397  12021  22.875931      1      1       1        0      Florida   \n",
        "1399  12011  15.615793      1      1       1        0      Florida   \n",
        "1401  12087  12.133105      1      1       1        0      Florida   \n",
        "\n",
        "            County  \n",
        "199      Breathitt  \n",
        "231          Perry  \n",
        "240           Clay  \n",
        "247         Leslie  \n",
        "285         Harlan  \n",
        "305           Bell  \n",
        "712        Coahoma  \n",
        "804      Red River  \n",
        "831        Carroll  \n",
        "850        Carroll  \n",
        "862       Richmond  \n",
        "868         Coweta  \n",
        "876        Hancock  \n",
        "905      Jefferson  \n",
        "908         Attala  \n",
        "914          Troup  \n",
        "924     Tallapoosa  \n",
        "927           Camp  \n",
        "930          Yazoo  \n",
        "932          Caddo  \n",
        "939           Hale  \n",
        "951         Sumter  \n",
        "963        Neshoba  \n",
        "966         Upshur  \n",
        "968        Madison  \n",
        "978       Harrison  \n",
        "995         Warren  \n",
        "1024      Treutlen  \n",
        "1033        Panola  \n",
        "1037       De Soto  \n",
        "1058       Stewart  \n",
        "1059       Webster  \n",
        "1060        Sumter  \n",
        "1062       Barbour  \n",
        "1064  Natchitoches  \n",
        "1093       Quitman  \n",
        "1101      Randolph  \n",
        "1119         Henry  \n",
        "1120          Clay  \n",
        "1134     Dougherty  \n",
        "1141       Calhoun  \n",
        "1162         Baker  \n",
        "1184       Baldwin  \n",
        "1254    Montgomery  \n",
        "1379    Okeechobee  \n",
        "1391    Palm Beach  \n",
        "1392        Hendry  \n",
        "1395           Lee  \n",
        "1397       Collier  \n",
        "1399       Broward  \n",
        "1401        Monroe  "
       ]
      }
     ],
     "prompt_number": 50
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[df['hot_01']>0]"
     ],
     "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>FIPS</th>\n",
        "      <th>HR80</th>\n",
        "      <th>sig01</th>\n",
        "      <th>sig05</th>\n",
        "      <th>hot_01</th>\n",
        "      <th>cold_01</th>\n",
        "      <th>STATE_NAME</th>\n",
        "      <th>County</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>199 </th>\n",
        "      <td> 21025</td>\n",
        "      <td> 19.603231</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>    Breathitt</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>231 </th>\n",
        "      <td> 21193</td>\n",
        "      <td> 37.516413</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>        Perry</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>240 </th>\n",
        "      <td> 21051</td>\n",
        "      <td> 29.301453</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>         Clay</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>247 </th>\n",
        "      <td> 21131</td>\n",
        "      <td> 38.077319</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>       Leslie</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>285 </th>\n",
        "      <td> 21095</td>\n",
        "      <td> 20.689600</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>       Harlan</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>305 </th>\n",
        "      <td> 21013</td>\n",
        "      <td> 19.419361</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>    Kentucky</td>\n",
        "      <td>         Bell</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>712 </th>\n",
        "      <td> 28027</td>\n",
        "      <td> 15.349333</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Coahoma</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>804 </th>\n",
        "      <td> 48387</td>\n",
        "      <td> 10.351324</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>    Red River</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>831 </th>\n",
        "      <td> 13045</td>\n",
        "      <td> 14.197991</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Carroll</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>850 </th>\n",
        "      <td> 28015</td>\n",
        "      <td> 10.229133</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Carroll</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>862 </th>\n",
        "      <td> 13245</td>\n",
        "      <td> 19.637099</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>     Richmond</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>868 </th>\n",
        "      <td> 13077</td>\n",
        "      <td> 11.884147</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>       Coweta</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>876 </th>\n",
        "      <td> 13141</td>\n",
        "      <td> 14.085499</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Hancock</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>905 </th>\n",
        "      <td> 13163</td>\n",
        "      <td> 21.735587</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>    Jefferson</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>908 </th>\n",
        "      <td> 28007</td>\n",
        "      <td> 20.135917</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>       Attala</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>914 </th>\n",
        "      <td> 13285</td>\n",
        "      <td> 14.665787</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>        Troup</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>924 </th>\n",
        "      <td> 01123</td>\n",
        "      <td> 13.789775</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>   Tallapoosa</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>927 </th>\n",
        "      <td> 48063</td>\n",
        "      <td> 10.781671</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>         Camp</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>930 </th>\n",
        "      <td> 28163</td>\n",
        "      <td> 23.157459</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>        Yazoo</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>932 </th>\n",
        "      <td> 22017</td>\n",
        "      <td> 23.115310</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>   Louisiana</td>\n",
        "      <td>        Caddo</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>939 </th>\n",
        "      <td> 01065</td>\n",
        "      <td> 10.681022</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>         Hale</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>951 </th>\n",
        "      <td> 01119</td>\n",
        "      <td> 15.771627</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>       Sumter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>963 </th>\n",
        "      <td> 28099</td>\n",
        "      <td> 11.209663</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Neshoba</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>966 </th>\n",
        "      <td> 48459</td>\n",
        "      <td> 12.822755</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>       Upshur</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>968 </th>\n",
        "      <td> 28089</td>\n",
        "      <td> 20.025793</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>      Madison</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>978 </th>\n",
        "      <td> 48203</td>\n",
        "      <td> 15.944386</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>     Harrison</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>995 </th>\n",
        "      <td> 28149</td>\n",
        "      <td> 14.204454</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> Mississippi</td>\n",
        "      <td>       Warren</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1024</th>\n",
        "      <td> 13283</td>\n",
        "      <td> 10.952303</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>     Treutlen</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1033</th>\n",
        "      <td> 48365</td>\n",
        "      <td> 12.867529</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>       Panola</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1037</th>\n",
        "      <td> 22031</td>\n",
        "      <td> 18.139179</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>   Louisiana</td>\n",
        "      <td>      De Soto</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1058</th>\n",
        "      <td> 13259</td>\n",
        "      <td> 33.921303</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Stewart</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1059</th>\n",
        "      <td> 13307</td>\n",
        "      <td> 14.238929</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Webster</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1060</th>\n",
        "      <td> 13261</td>\n",
        "      <td> 10.217984</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>       Sumter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1062</th>\n",
        "      <td> 01005</td>\n",
        "      <td> 24.236549</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>      Barbour</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1064</th>\n",
        "      <td> 22069</td>\n",
        "      <td> 19.232538</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>   Louisiana</td>\n",
        "      <td> Natchitoches</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1093</th>\n",
        "      <td> 13239</td>\n",
        "      <td> 28.284542</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Quitman</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1101</th>\n",
        "      <td> 13243</td>\n",
        "      <td> 17.362920</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>     Randolph</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1119</th>\n",
        "      <td> 01067</td>\n",
        "      <td> 13.070187</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>        Henry</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1120</th>\n",
        "      <td> 13061</td>\n",
        "      <td> 18.763486</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>         Clay</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1134</th>\n",
        "      <td> 13095</td>\n",
        "      <td> 17.540724</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>    Dougherty</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1141</th>\n",
        "      <td> 13037</td>\n",
        "      <td> 17.491691</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>      Calhoun</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1162</th>\n",
        "      <td> 13007</td>\n",
        "      <td> 17.507003</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Georgia</td>\n",
        "      <td>        Baker</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1184</th>\n",
        "      <td> 01003</td>\n",
        "      <td> 11.456795</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Alabama</td>\n",
        "      <td>      Baldwin</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1254</th>\n",
        "      <td> 48339</td>\n",
        "      <td> 12.193192</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>       Texas</td>\n",
        "      <td>   Montgomery</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1379</th>\n",
        "      <td> 12093</td>\n",
        "      <td> 24.674299</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>   Okeechobee</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1391</th>\n",
        "      <td> 12099</td>\n",
        "      <td> 11.267840</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>   Palm Beach</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1392</th>\n",
        "      <td> 12051</td>\n",
        "      <td> 21.506533</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>       Hendry</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1395</th>\n",
        "      <td> 12071</td>\n",
        "      <td> 12.341709</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>          Lee</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1397</th>\n",
        "      <td> 12021</td>\n",
        "      <td> 22.875931</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>      Collier</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1399</th>\n",
        "      <td> 12011</td>\n",
        "      <td> 15.615793</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>      Broward</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1401</th>\n",
        "      <td> 12087</td>\n",
        "      <td> 12.133105</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>     Florida</td>\n",
        "      <td>       Monroe</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 51,
       "text": [
        "       FIPS       HR80  sig01  sig05  hot_01  cold_01   STATE_NAME  \\\n",
        "199   21025  19.603231      1      1       1        0     Kentucky   \n",
        "231   21193  37.516413      1      1       1        0     Kentucky   \n",
        "240   21051  29.301453      1      1       1        0     Kentucky   \n",
        "247   21131  38.077319      1      1       1        0     Kentucky   \n",
        "285   21095  20.689600      1      1       1        0     Kentucky   \n",
        "305   21013  19.419361      1      1       1        0     Kentucky   \n",
        "712   28027  15.349333      1      1       1        0  Mississippi   \n",
        "804   48387  10.351324      1      1       1        0        Texas   \n",
        "831   13045  14.197991      1      1       1        0      Georgia   \n",
        "850   28015  10.229133      1      1       1        0  Mississippi   \n",
        "862   13245  19.637099      1      1       1        0      Georgia   \n",
        "868   13077  11.884147      1      1       1        0      Georgia   \n",
        "876   13141  14.085499      1      1       1        0      Georgia   \n",
        "905   13163  21.735587      1      1       1        0      Georgia   \n",
        "908   28007  20.135917      1      1       1        0  Mississippi   \n",
        "914   13285  14.665787      1      1       1        0      Georgia   \n",
        "924   01123  13.789775      1      1       1        0      Alabama   \n",
        "927   48063  10.781671      1      1       1        0        Texas   \n",
        "930   28163  23.157459      1      1       1        0  Mississippi   \n",
        "932   22017  23.115310      1      1       1        0    Louisiana   \n",
        "939   01065  10.681022      1      1       1        0      Alabama   \n",
        "951   01119  15.771627      1      1       1        0      Alabama   \n",
        "963   28099  11.209663      1      1       1        0  Mississippi   \n",
        "966   48459  12.822755      1      1       1        0        Texas   \n",
        "968   28089  20.025793      1      1       1        0  Mississippi   \n",
        "978   48203  15.944386      1      1       1        0        Texas   \n",
        "995   28149  14.204454      1      1       1        0  Mississippi   \n",
        "1024  13283  10.952303      1      1       1        0      Georgia   \n",
        "1033  48365  12.867529      1      1       1        0        Texas   \n",
        "1037  22031  18.139179      1      1       1        0    Louisiana   \n",
        "1058  13259  33.921303      1      1       1        0      Georgia   \n",
        "1059  13307  14.238929      1      1       1        0      Georgia   \n",
        "1060  13261  10.217984      1      1       1        0      Georgia   \n",
        "1062  01005  24.236549      1      1       1        0      Alabama   \n",
        "1064  22069  19.232538      1      1       1        0    Louisiana   \n",
        "1093  13239  28.284542      1      1       1        0      Georgia   \n",
        "1101  13243  17.362920      1      1       1        0      Georgia   \n",
        "1119  01067  13.070187      1      1       1        0      Alabama   \n",
        "1120  13061  18.763486      1      1       1        0      Georgia   \n",
        "1134  13095  17.540724      1      1       1        0      Georgia   \n",
        "1141  13037  17.491691      1      1       1        0      Georgia   \n",
        "1162  13007  17.507003      1      1       1        0      Georgia   \n",
        "1184  01003  11.456795      1      1       1        0      Alabama   \n",
        "1254  48339  12.193192      1      1       1        0        Texas   \n",
        "1379  12093  24.674299      1      1       1        0      Florida   \n",
        "1391  12099  11.267840      1      1       1        0      Florida   \n",
        "1392  12051  21.506533      1      1       1        0      Florida   \n",
        "1395  12071  12.341709      1      1       1        0      Florida   \n",
        "1397  12021  22.875931      1      1       1        0      Florida   \n",
        "1399  12011  15.615793      1      1       1        0      Florida   \n",
        "1401  12087  12.133105      1      1       1        0      Florida   \n",
        "\n",
        "            County  \n",
        "199      Breathitt  \n",
        "231          Perry  \n",
        "240           Clay  \n",
        "247         Leslie  \n",
        "285         Harlan  \n",
        "305           Bell  \n",
        "712        Coahoma  \n",
        "804      Red River  \n",
        "831        Carroll  \n",
        "850        Carroll  \n",
        "862       Richmond  \n",
        "868         Coweta  \n",
        "876        Hancock  \n",
        "905      Jefferson  \n",
        "908         Attala  \n",
        "914          Troup  \n",
        "924     Tallapoosa  \n",
        "927           Camp  \n",
        "930          Yazoo  \n",
        "932          Caddo  \n",
        "939           Hale  \n",
        "951         Sumter  \n",
        "963        Neshoba  \n",
        "966         Upshur  \n",
        "968        Madison  \n",
        "978       Harrison  \n",
        "995         Warren  \n",
        "1024      Treutlen  \n",
        "1033        Panola  \n",
        "1037       De Soto  \n",
        "1058       Stewart  \n",
        "1059       Webster  \n",
        "1060        Sumter  \n",
        "1062       Barbour  \n",
        "1064  Natchitoches  \n",
        "1093       Quitman  \n",
        "1101      Randolph  \n",
        "1119         Henry  \n",
        "1120          Clay  \n",
        "1134     Dougherty  \n",
        "1141       Calhoun  \n",
        "1162         Baker  \n",
        "1184       Baldwin  \n",
        "1254    Montgomery  \n",
        "1379    Okeechobee  \n",
        "1391    Palm Beach  \n",
        "1392        Hendry  \n",
        "1395           Lee  \n",
        "1397       Collier  \n",
        "1399       Broward  \n",
        "1401        Monroe  "
       ]
      }
     ],
     "prompt_number": 51
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df[df['cold_01']>0]"
     ],
     "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>FIPS</th>\n",
        "      <th>HR80</th>\n",
        "      <th>sig01</th>\n",
        "      <th>sig05</th>\n",
        "      <th>hot_01</th>\n",
        "      <th>cold_01</th>\n",
        "      <th>STATE_NAME</th>\n",
        "      <th>County</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>5   </th>\n",
        "      <td> 24043</td>\n",
        "      <td>  2.063326</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Maryland</td>\n",
        "      <td>  Washington</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6   </th>\n",
        "      <td> 24001</td>\n",
        "      <td>  3.724487</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Maryland</td>\n",
        "      <td>    Allegany</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8   </th>\n",
        "      <td> 24023</td>\n",
        "      <td>  5.031826</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Maryland</td>\n",
        "      <td>     Garrett</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10  </th>\n",
        "      <td> 54061</td>\n",
        "      <td>  4.443023</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>  Monongalia</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11  </th>\n",
        "      <td> 54077</td>\n",
        "      <td>  1.094331</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>     Preston</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14  </th>\n",
        "      <td> 54103</td>\n",
        "      <td>  4.571638</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>      Wetzel</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15  </th>\n",
        "      <td> 24021</td>\n",
        "      <td>  3.194183</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Maryland</td>\n",
        "      <td>   Frederick</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16  </th>\n",
        "      <td> 54065</td>\n",
        "      <td>  6.224131</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>      Morgan</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22  </th>\n",
        "      <td> 54037</td>\n",
        "      <td>  4.400150</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>   Jefferson</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23  </th>\n",
        "      <td> 54073</td>\n",
        "      <td>  0.000000</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>   Pleasants</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24  </th>\n",
        "      <td> 54033</td>\n",
        "      <td>  6.005233</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>    Harrison</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>26  </th>\n",
        "      <td> 54017</td>\n",
        "      <td>  4.484506</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>   Doddridge</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>27  </th>\n",
        "      <td> 54091</td>\n",
        "      <td>  2.009969</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>      Taylor</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>28  </th>\n",
        "      <td> 54107</td>\n",
        "      <td>  2.135657</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>        Wood</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>29  </th>\n",
        "      <td> 54085</td>\n",
        "      <td>  2.913244</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>     Ritchie</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>36  </th>\n",
        "      <td> 51107</td>\n",
        "      <td>  4.063129</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Virginia</td>\n",
        "      <td>     Loudoun</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>37  </th>\n",
        "      <td> 54001</td>\n",
        "      <td>  0.000000</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>     Barbour</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>44  </th>\n",
        "      <td> 54105</td>\n",
        "      <td>  6.772315</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>        Wirt</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>46  </th>\n",
        "      <td> 21015</td>\n",
        "      <td>  1.454270</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Kentucky</td>\n",
        "      <td>       Boone</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>51  </th>\n",
        "      <td> 54097</td>\n",
        "      <td>  4.268579</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>      Upshur</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>52  </th>\n",
        "      <td> 54021</td>\n",
        "      <td>  3.999680</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>      Gilmer</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>55  </th>\n",
        "      <td> 21117</td>\n",
        "      <td>  6.080151</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Kentucky</td>\n",
        "      <td>      Kenton</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>68  </th>\n",
        "      <td> 21191</td>\n",
        "      <td>  3.033336</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Kentucky</td>\n",
        "      <td>   Pendleton</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75  </th>\n",
        "      <td> 21081</td>\n",
        "      <td>  0.000000</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Kentucky</td>\n",
        "      <td>       Grant</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>78  </th>\n",
        "      <td> 21161</td>\n",
        "      <td>  1.876349</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Kentucky</td>\n",
        "      <td>       Mason</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>82  </th>\n",
        "      <td> 54075</td>\n",
        "      <td> 10.081661</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>  West Virginia</td>\n",
        "      <td>  Pocahontas</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>83  </th>\n",
        "      <td> 21187</td>\n",
        "      <td>  3.735246</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Kentucky</td>\n",
        "      <td>        Owen</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>105 </th>\n",
        "      <td> 21209</td>\n",
        "      <td>  1.528141</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Kentucky</td>\n",
        "      <td>       Scott</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>118 </th>\n",
        "      <td> 21073</td>\n",
        "      <td>  4.781257</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Kentucky</td>\n",
        "      <td>    Franklin</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>120 </th>\n",
        "      <td> 21211</td>\n",
        "      <td>  4.286694</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Kentucky</td>\n",
        "      <td>      Shelby</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",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>337 </th>\n",
        "      <td> 47163</td>\n",
        "      <td>  4.862192</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>      Tennessee</td>\n",
        "      <td>    Sullivan</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>339 </th>\n",
        "      <td> 40103</td>\n",
        "      <td>  2.880267</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Oklahoma</td>\n",
        "      <td>       Noble</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>346 </th>\n",
        "      <td> 40047</td>\n",
        "      <td>  7.959249</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Oklahoma</td>\n",
        "      <td>    Garfield</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>347 </th>\n",
        "      <td> 47073</td>\n",
        "      <td>  6.856986</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>      Tennessee</td>\n",
        "      <td>     Hawkins</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>351 </th>\n",
        "      <td> 37171</td>\n",
        "      <td>  4.485638</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td> North Carolina</td>\n",
        "      <td>       Surry</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>387 </th>\n",
        "      <td> 05007</td>\n",
        "      <td>  4.267213</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Arkansas</td>\n",
        "      <td>      Benton</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>398 </th>\n",
        "      <td> 47057</td>\n",
        "      <td>  7.959724</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>      Tennessee</td>\n",
        "      <td>    Grainger</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>463 </th>\n",
        "      <td> 48341</td>\n",
        "      <td>  6.033183</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>       Moore</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>522 </th>\n",
        "      <td> 47003</td>\n",
        "      <td>  8.358409</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>      Tennessee</td>\n",
        "      <td>     Bedford</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>594 </th>\n",
        "      <td> 05149</td>\n",
        "      <td>  5.873370</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Arkansas</td>\n",
        "      <td>        Yell</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>611 </th>\n",
        "      <td> 48129</td>\n",
        "      <td>  8.179959</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>      Donley</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>620 </th>\n",
        "      <td> 05127</td>\n",
        "      <td>  6.883497</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>       Arkansas</td>\n",
        "      <td>       Scott</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>684 </th>\n",
        "      <td> 48191</td>\n",
        "      <td>  5.958765</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>        Hall</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>746 </th>\n",
        "      <td> 48101</td>\n",
        "      <td>  0.000000</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>      Cottle</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>822 </th>\n",
        "      <td> 48125</td>\n",
        "      <td>  9.418857</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>     Dickens</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>825 </th>\n",
        "      <td> 48009</td>\n",
        "      <td>  0.000000</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>      Archer</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>875 </th>\n",
        "      <td> 48237</td>\n",
        "      <td>  4.499640</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>        Jack</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>889 </th>\n",
        "      <td> 48503</td>\n",
        "      <td>  3.493511</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>       Young</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>953 </th>\n",
        "      <td> 48417</td>\n",
        "      <td>  8.514261</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td> Shackelford</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1050</th>\n",
        "      <td> 48093</td>\n",
        "      <td>  5.283876</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>    Comanche</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1091</th>\n",
        "      <td> 48141</td>\n",
        "      <td>  8.821301</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>     El Paso</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1131</th>\n",
        "      <td> 48451</td>\n",
        "      <td>  7.863119</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>   Tom Green</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1196</th>\n",
        "      <td> 48243</td>\n",
        "      <td>  0.000000</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>  Jeff Davis</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1239</th>\n",
        "      <td> 48267</td>\n",
        "      <td>  8.204118</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>      Kimble</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1242</th>\n",
        "      <td> 48435</td>\n",
        "      <td>  0.000000</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>      Sutton</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1246</th>\n",
        "      <td> 48043</td>\n",
        "      <td>  4.401602</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>    Brewster</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1252</th>\n",
        "      <td> 48377</td>\n",
        "      <td>  6.425084</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>    Presidio</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1284</th>\n",
        "      <td> 48137</td>\n",
        "      <td>  0.000000</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>     Edwards</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1285</th>\n",
        "      <td> 48465</td>\n",
        "      <td>  3.712986</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>   Val Verde</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1286</th>\n",
        "      <td> 48265</td>\n",
        "      <td>  5.791059</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 1</td>\n",
        "      <td>          Texas</td>\n",
        "      <td>        Kerr</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>69 rows \u00d7 8 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 52,
       "text": [
        "       FIPS       HR80  sig01  sig05  hot_01  cold_01      STATE_NAME  \\\n",
        "5     24043   2.063326      1      1       0        1        Maryland   \n",
        "6     24001   3.724487      1      1       0        1        Maryland   \n",
        "8     24023   5.031826      1      1       0        1        Maryland   \n",
        "10    54061   4.443023      1      1       0        1   West Virginia   \n",
        "11    54077   1.094331      1      1       0        1   West Virginia   \n",
        "14    54103   4.571638      1      1       0        1   West Virginia   \n",
        "15    24021   3.194183      1      1       0        1        Maryland   \n",
        "16    54065   6.224131      1      1       0        1   West Virginia   \n",
        "22    54037   4.400150      1      1       0        1   West Virginia   \n",
        "23    54073   0.000000      1      1       0        1   West Virginia   \n",
        "24    54033   6.005233      1      1       0        1   West Virginia   \n",
        "26    54017   4.484506      1      1       0        1   West Virginia   \n",
        "27    54091   2.009969      1      1       0        1   West Virginia   \n",
        "28    54107   2.135657      1      1       0        1   West Virginia   \n",
        "29    54085   2.913244      1      1       0        1   West Virginia   \n",
        "36    51107   4.063129      1      1       0        1        Virginia   \n",
        "37    54001   0.000000      1      1       0        1   West Virginia   \n",
        "44    54105   6.772315      1      1       0        1   West Virginia   \n",
        "46    21015   1.454270      1      1       0        1        Kentucky   \n",
        "51    54097   4.268579      1      1       0        1   West Virginia   \n",
        "52    54021   3.999680      1      1       0        1   West Virginia   \n",
        "55    21117   6.080151      1      1       0        1        Kentucky   \n",
        "68    21191   3.033336      1      1       0        1        Kentucky   \n",
        "75    21081   0.000000      1      1       0        1        Kentucky   \n",
        "78    21161   1.876349      1      1       0        1        Kentucky   \n",
        "82    54075  10.081661      1      1       0        1   West Virginia   \n",
        "83    21187   3.735246      1      1       0        1        Kentucky   \n",
        "105   21209   1.528141      1      1       0        1        Kentucky   \n",
        "118   21073   4.781257      1      1       0        1        Kentucky   \n",
        "120   21211   4.286694      1      1       0        1        Kentucky   \n",
        "...     ...        ...    ...    ...     ...      ...             ...   \n",
        "337   47163   4.862192      1      1       0        1       Tennessee   \n",
        "339   40103   2.880267      1      1       0        1        Oklahoma   \n",
        "346   40047   7.959249      1      1       0        1        Oklahoma   \n",
        "347   47073   6.856986      1      1       0        1       Tennessee   \n",
        "351   37171   4.485638      1      1       0        1  North Carolina   \n",
        "387   05007   4.267213      1      1       0        1        Arkansas   \n",
        "398   47057   7.959724      1      1       0        1       Tennessee   \n",
        "463   48341   6.033183      1      1       0        1           Texas   \n",
        "522   47003   8.358409      1      1       0        1       Tennessee   \n",
        "594   05149   5.873370      1      1       0        1        Arkansas   \n",
        "611   48129   8.179959      1      1       0        1           Texas   \n",
        "620   05127   6.883497      1      1       0        1        Arkansas   \n",
        "684   48191   5.958765      1      1       0        1           Texas   \n",
        "746   48101   0.000000      1      1       0        1           Texas   \n",
        "822   48125   9.418857      1      1       0        1           Texas   \n",
        "825   48009   0.000000      1      1       0        1           Texas   \n",
        "875   48237   4.499640      1      1       0        1           Texas   \n",
        "889   48503   3.493511      1      1       0        1           Texas   \n",
        "953   48417   8.514261      1      1       0        1           Texas   \n",
        "1050  48093   5.283876      1      1       0        1           Texas   \n",
        "1091  48141   8.821301      1      1       0        1           Texas   \n",
        "1131  48451   7.863119      1      1       0        1           Texas   \n",
        "1196  48243   0.000000      1      1       0        1           Texas   \n",
        "1239  48267   8.204118      1      1       0        1           Texas   \n",
        "1242  48435   0.000000      1      1       0        1           Texas   \n",
        "1246  48043   4.401602      1      1       0        1           Texas   \n",
        "1252  48377   6.425084      1      1       0        1           Texas   \n",
        "1284  48137   0.000000      1      1       0        1           Texas   \n",
        "1285  48465   3.712986      1      1       0        1           Texas   \n",
        "1286  48265   5.791059      1      1       0        1           Texas   \n",
        "\n",
        "           County  \n",
        "5      Washington  \n",
        "6        Allegany  \n",
        "8         Garrett  \n",
        "10     Monongalia  \n",
        "11        Preston  \n",
        "14         Wetzel  \n",
        "15      Frederick  \n",
        "16         Morgan  \n",
        "22      Jefferson  \n",
        "23      Pleasants  \n",
        "24       Harrison  \n",
        "26      Doddridge  \n",
        "27         Taylor  \n",
        "28           Wood  \n",
        "29        Ritchie  \n",
        "36        Loudoun  \n",
        "37        Barbour  \n",
        "44           Wirt  \n",
        "46          Boone  \n",
        "51         Upshur  \n",
        "52         Gilmer  \n",
        "55         Kenton  \n",
        "68      Pendleton  \n",
        "75          Grant  \n",
        "78          Mason  \n",
        "82     Pocahontas  \n",
        "83           Owen  \n",
        "105         Scott  \n",
        "118      Franklin  \n",
        "120        Shelby  \n",
        "...           ...  \n",
        "337      Sullivan  \n",
        "339         Noble  \n",
        "346      Garfield  \n",
        "347       Hawkins  \n",
        "351         Surry  \n",
        "387        Benton  \n",
        "398      Grainger  \n",
        "463         Moore  \n",
        "522       Bedford  \n",
        "594          Yell  \n",
        "611        Donley  \n",
        "620         Scott  \n",
        "684          Hall  \n",
        "746        Cottle  \n",
        "822       Dickens  \n",
        "825        Archer  \n",
        "875          Jack  \n",
        "889         Young  \n",
        "953   Shackelford  \n",
        "1050     Comanche  \n",
        "1091      El Paso  \n",
        "1131    Tom Green  \n",
        "1196   Jeff Davis  \n",
        "1239       Kimble  \n",
        "1242       Sutton  \n",
        "1246     Brewster  \n",
        "1252     Presidio  \n",
        "1284      Edwards  \n",
        "1285    Val Verde  \n",
        "1286         Kerr  \n",
        "\n",
        "[69 rows x 8 columns]"
       ]
      }
     ],
     "prompt_number": 52
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print df[df['cold_01']>0].to_string() "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "       FIPS       HR80  sig01  sig05  hot_01  cold_01      STATE_NAME       County\n",
        "5     24043   2.063326      1      1       0        1        Maryland   Washington\n",
        "6     24001   3.724487      1      1       0        1        Maryland     Allegany\n",
        "8     24023   5.031826      1      1       0        1        Maryland      Garrett\n",
        "10    54061   4.443023      1      1       0        1   West Virginia   Monongalia\n",
        "11    54077   1.094331      1      1       0        1   West Virginia      Preston\n",
        "14    54103   4.571638      1      1       0        1   West Virginia       Wetzel\n",
        "15    24021   3.194183      1      1       0        1        Maryland    Frederick\n",
        "16    54065   6.224131      1      1       0        1   West Virginia       Morgan\n",
        "22    54037   4.400150      1      1       0        1   West Virginia    Jefferson\n",
        "23    54073   0.000000      1      1       0        1   West Virginia    Pleasants\n",
        "24    54033   6.005233      1      1       0        1   West Virginia     Harrison\n",
        "26    54017   4.484506      1      1       0        1   West Virginia    Doddridge\n",
        "27    54091   2.009969      1      1       0        1   West Virginia       Taylor\n",
        "28    54107   2.135657      1      1       0        1   West Virginia         Wood\n",
        "29    54085   2.913244      1      1       0        1   West Virginia      Ritchie\n",
        "36    51107   4.063129      1      1       0        1        Virginia      Loudoun\n",
        "37    54001   0.000000      1      1       0        1   West Virginia      Barbour\n",
        "44    54105   6.772315      1      1       0        1   West Virginia         Wirt\n",
        "46    21015   1.454270      1      1       0        1        Kentucky        Boone\n",
        "51    54097   4.268579      1      1       0        1   West Virginia       Upshur\n",
        "52    54021   3.999680      1      1       0        1   West Virginia       Gilmer\n",
        "55    21117   6.080151      1      1       0        1        Kentucky       Kenton\n",
        "68    21191   3.033336      1      1       0        1        Kentucky    Pendleton\n",
        "75    21081   0.000000      1      1       0        1        Kentucky        Grant\n",
        "78    21161   1.876349      1      1       0        1        Kentucky        Mason\n",
        "82    54075  10.081661      1      1       0        1   West Virginia   Pocahontas\n",
        "83    21187   3.735246      1      1       0        1        Kentucky         Owen\n",
        "105   21209   1.528141      1      1       0        1        Kentucky        Scott\n",
        "118   21073   4.781257      1      1       0        1        Kentucky     Franklin\n",
        "120   21211   4.286694      1      1       0        1        Kentucky       Shelby\n",
        "135   21173   4.988526      1      1       0        1        Kentucky   Montgomery\n",
        "136   21239   1.874977      1      1       0        1        Kentucky     Woodford\n",
        "164   21101   3.264054      1      1       0        1        Kentucky    Henderson\n",
        "169   21059   5.429576      1      1       0        1        Kentucky      Daviess\n",
        "192   21183   6.126043      1      1       0        1        Kentucky         Ohio\n",
        "238   51121   6.822428      1      1       0        1        Virginia   Montgomery\n",
        "294   40003   9.420187      1      1       0        1        Oklahoma      Alfalfa\n",
        "310   51035   4.889378      1      1       0        1        Virginia      Carroll\n",
        "321   40153   9.446439      1      1       0        1        Oklahoma     Woodward\n",
        "337   47163   4.862192      1      1       0        1       Tennessee     Sullivan\n",
        "339   40103   2.880267      1      1       0        1        Oklahoma        Noble\n",
        "346   40047   7.959249      1      1       0        1        Oklahoma     Garfield\n",
        "347   47073   6.856986      1      1       0        1       Tennessee      Hawkins\n",
        "351   37171   4.485638      1      1       0        1  North Carolina        Surry\n",
        "387   05007   4.267213      1      1       0        1        Arkansas       Benton\n",
        "398   47057   7.959724      1      1       0        1       Tennessee     Grainger\n",
        "463   48341   6.033183      1      1       0        1           Texas        Moore\n",
        "522   47003   8.358409      1      1       0        1       Tennessee      Bedford\n",
        "594   05149   5.873370      1      1       0        1        Arkansas         Yell\n",
        "611   48129   8.179959      1      1       0        1           Texas       Donley\n",
        "620   05127   6.883497      1      1       0        1        Arkansas        Scott\n",
        "684   48191   5.958765      1      1       0        1           Texas         Hall\n",
        "746   48101   0.000000      1      1       0        1           Texas       Cottle\n",
        "822   48125   9.418857      1      1       0        1           Texas      Dickens\n",
        "825   48009   0.000000      1      1       0        1           Texas       Archer\n",
        "875   48237   4.499640      1      1       0        1           Texas         Jack\n",
        "889   48503   3.493511      1      1       0        1           Texas        Young\n",
        "953   48417   8.514261      1      1       0        1           Texas  Shackelford\n",
        "1050  48093   5.283876      1      1       0        1           Texas     Comanche\n",
        "1091  48141   8.821301      1      1       0        1           Texas      El Paso\n",
        "1131  48451   7.863119      1      1       0        1           Texas    Tom Green\n",
        "1196  48243   0.000000      1      1       0        1           Texas   Jeff Davis\n",
        "1239  48267   8.204118      1      1       0        1           Texas       Kimble\n",
        "1242  48435   0.000000      1      1       0        1           Texas       Sutton\n",
        "1246  48043   4.401602      1      1       0        1           Texas     Brewster\n",
        "1252  48377   6.425084      1      1       0        1           Texas     Presidio\n",
        "1284  48137   0.000000      1      1       0        1           Texas      Edwards\n",
        "1285  48465   3.712986      1      1       0        1           Texas    Val Verde\n",
        "1286  48265   5.791059      1      1       0        1           Texas         Kerr\n"
       ]
      }
     ],
     "prompt_number": 53
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "hot_01"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 54,
       "text": [
        "0     0\n",
        "1     0\n",
        "2     0\n",
        "3     0\n",
        "4     0\n",
        "5     0\n",
        "6     0\n",
        "7     0\n",
        "8     0\n",
        "9     0\n",
        "10    0\n",
        "11    0\n",
        "12    0\n",
        "13    0\n",
        "14    0\n",
        "...\n",
        "1397    1\n",
        "1398    0\n",
        "1399    1\n",
        "1400    0\n",
        "1401    1\n",
        "1402    0\n",
        "1403    0\n",
        "1404    0\n",
        "1405    0\n",
        "1406    0\n",
        "1407    0\n",
        "1408    0\n",
        "1409    0\n",
        "1410    0\n",
        "1411    0\n",
        "Name: hot_01, Length: 1412, dtype: float64"
       ]
      }
     ],
     "prompt_number": 54
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "y"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 55,
       "text": [
        "array([ 6.59772049,  3.21367741,  7.6017962 , ...,  4.12783918,\n",
        "        5.2803488 ,  3.00003   ])"
       ]
      }
     ],
     "prompt_number": 55
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "w = ps.queen_from_shapefile('data/south.shp')\n",
      "w.transform = 'r'\n",
      "wy = ps.lag_spatial(w,y)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 56
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scatter(y,wy, alpha=0.5, lw=0)\n",
      "vlines(y.mean(),wy.min(),wy.max())\n",
      "hlines(wy.mean(),y.min(),y.max())\n",
      "xlabel('y')\n",
      "ylabel('wy')\n",
      "lm = ps.spreg.OLS(wy[:, None], y[:, None])\n",
      "plot(y, lm.predy, color='red')\n",
      "title('Moran Scatter Plot')\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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1h4Occc891LQ7Ongcm41CsK5O1R5s3Kj8/ps3c+qbd/fNjg7Vnz88XA1tuekm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\nY/9+vp+SQqJ/5RWmTErRlwSGw8JI0ocO8dHTo1pbS0xA5v8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       "text": [
        "<matplotlib.figure.Figure at 0x10c6787d0>"
       ]
      }
     ],
     "prompt_number": 57
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "c = 2*hot_01 + df.cold_01\n",
      "scatter(y,wy, c=c, s=(sig01+1)*50)\n",
      "vlines(y.mean(),wy.min(),wy.max())\n",
      "hlines(wy.mean(),y.min(),y.max())\n",
      "xlabel('y')\n",
      "ylabel('wy')\n",
      "title('Moran Scatter Plot')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 58,
       "text": [
        "<matplotlib.text.Text at 0x109c64910>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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XF0ehQoXo3r07FSpUuN5iKa4R/9QQ5MeaxYobCLvdjsFgJu/vkBlwB9hek9OnV7N161aa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E5vPSI991bEaKgExNdzJOKu4Q9EUAAxeSwZsWpZ4SAAYDZ3IibmWyIjI+/5RO3o6Mj8+d/xyScf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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10c5f4b50>"
       ]
      }
     ],
     "prompt_number": 58
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sig01.sum()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 59,
       "text": [
        "166.0"
       ]
      }
     ],
     "prompt_number": 59
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df['wHR80'] = wy"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 60
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print df[df['cold_01']>0].to_string() "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "       FIPS       HR80  sig01  sig05  hot_01  cold_01      STATE_NAME       County     wHR80\n",
        "5     24043   2.063326      1      1       0        1        Maryland   Washington  4.669960\n",
        "6     24001   3.724487      1      1       0        1        Maryland     Allegany  3.153441\n",
        "8     24023   5.031826      1      1       0        1        Maryland      Garrett  3.527749\n",
        "10    54061   4.443023      1      1       0        1   West Virginia   Monongalia  2.932325\n",
        "11    54077   1.094331      1      1       0        1   West Virginia      Preston  3.642804\n",
        "14    54103   4.571638      1      1       0        1   West Virginia       Wetzel  3.831961\n",
        "15    24021   3.194183      1      1       0        1        Maryland    Frederick  4.037935\n",
        "16    54065   6.224131      1      1       0        1   West Virginia       Morgan  3.416385\n",
        "22    54037   4.400150      1      1       0        1   West Virginia    Jefferson  4.153122\n",
        "23    54073   0.000000      1      1       0        1   West Virginia    Pleasants  1.682967\n",
        "24    54033   6.005233      1      1       0        1   West Virginia     Harrison  2.769722\n",
        "26    54017   4.484506      1      1       0        1   West Virginia    Doddridge  2.914966\n",
        "27    54091   2.009969      1      1       0        1   West Virginia       Taylor  3.119190\n",
        "28    54107   2.135657      1      1       0        1   West Virginia         Wood  3.390607\n",
        "29    54085   2.913244      1      1       0        1   West Virginia      Ritchie  3.061795\n",
        "36    51107   4.063129      1      1       0        1        Virginia      Loudoun  4.390625\n",
        "37    54001   0.000000      1      1       0        1   West Virginia      Barbour  4.416850\n",
        "44    54105   6.772315      1      1       0        1   West Virginia         Wirt  3.429076\n",
        "46    21015   1.454270      1      1       0        1        Kentucky        Boone  2.026717\n",
        "51    54097   4.268579      1      1       0        1   West Virginia       Upshur  3.601592\n",
        "52    54021   3.999680      1      1       0        1   West Virginia       Gilmer  3.727101\n",
        "55    21117   6.080151      1      1       0        1        Kentucky       Kenton  1.922059\n",
        "68    21191   3.033336      1      1       0        1        Kentucky    Pendleton  4.054054\n",
        "75    21081   0.000000      1      1       0        1        Kentucky        Grant  3.831520\n",
        "78    21161   1.876349      1      1       0        1        Kentucky        Mason  3.277904\n",
        "82    54075  10.081661      1      1       0        1   West Virginia   Pocahontas  4.290141\n",
        "83    21187   3.735246      1      1       0        1        Kentucky         Owen  4.484162\n",
        "105   21209   1.528141      1      1       0        1        Kentucky        Scott  4.641435\n",
        "118   21073   4.781257      1      1       0        1        Kentucky     Franklin  2.340248\n",
        "120   21211   4.286694      1      1       0        1        Kentucky       Shelby  4.284222\n",
        "135   21173   4.988526      1      1       0        1        Kentucky   Montgomery  4.467380\n",
        "136   21239   1.874977      1      1       0        1        Kentucky     Woodford  4.907030\n",
        "164   21101   3.264054      1      1       0        1        Kentucky    Henderson  3.416317\n",
        "169   21059   5.429576      1      1       0        1        Kentucky      Daviess  2.347524\n",
        "192   21183   6.126043      1      1       0        1        Kentucky         Ohio  3.074290\n",
        "238   51121   6.822428      1      1       0        1        Virginia   Montgomery  3.835457\n",
        "294   40003   9.420187      1      1       0        1        Oklahoma      Alfalfa  1.989812\n",
        "310   51035   4.889378      1      1       0        1        Virginia      Carroll  4.608768\n",
        "321   40153   9.446439      1      1       0        1        Oklahoma     Woodward  1.191327\n",
        "337   47163   4.862192      1      1       0        1       Tennessee     Sullivan  5.389851\n",
        "339   40103   2.880267      1      1       0        1        Oklahoma        Noble  4.858220\n",
        "346   40047   7.959249      1      1       0        1        Oklahoma     Garfield  4.817456\n",
        "347   47073   6.856986      1      1       0        1       Tennessee      Hawkins  4.841746\n",
        "351   37171   4.485638      1      1       0        1  North Carolina        Surry  5.059591\n",
        "387   05007   4.267213      1      1       0        1        Arkansas       Benton  3.998879\n",
        "398   47057   7.959724      1      1       0        1       Tennessee     Grainger  4.754336\n",
        "463   48341   6.033183      1      1       0        1           Texas        Moore  5.183679\n",
        "522   47003   8.358409      1      1       0        1       Tennessee      Bedford  4.300313\n",
        "594   05149   5.873370      1      1       0        1        Arkansas         Yell  5.270285\n",
        "611   48129   8.179959      1      1       0        1           Texas       Donley  4.519983\n",
        "620   05127   6.883497      1      1       0        1        Arkansas        Scott  4.185357\n",
        "684   48191   5.958765      1      1       0        1           Texas         Hall  3.357944\n",
        "746   48101   0.000000      1      1       0        1           Texas       Cottle  3.629756\n",
        "822   48125   9.418857      1      1       0        1           Texas      Dickens  4.771036\n",
        "825   48009   0.000000      1      1       0        1           Texas       Archer  3.635333\n",
        "875   48237   4.499640      1      1       0        1           Texas         Jack  4.549122\n",
        "889   48503   3.493511      1      1       0        1           Texas        Young  4.178185\n",
        "953   48417   8.514261      1      1       0        1           Texas  Shackelford  4.808184\n",
        "1050  48093   5.283876      1      1       0        1           Texas     Comanche  3.728266\n",
        "1091  48141   8.821301      1      1       0        1           Texas      El Paso  0.000000\n",
        "1131  48451   7.863119      1      1       0        1           Texas    Tom Green  4.059151\n",
        "1196  48243   0.000000      1      1       0        1           Texas   Jeff Davis  4.674117\n",
        "1239  48267   8.204118      1      1       0        1           Texas       Kimble  2.120236\n",
        "1242  48435   0.000000      1      1       0        1           Texas       Sutton  3.830180\n",
        "1246  48043   4.401602      1      1       0        1           Texas     Brewster  2.746418\n",
        "1252  48377   6.425084      1      1       0        1           Texas     Presidio  1.467201\n",
        "1284  48137   0.000000      1      1       0        1           Texas      Edwards  4.227311\n",
        "1285  48465   3.712986      1      1       0        1           Texas    Val Verde  1.446759\n",
        "1286  48265   5.791059      1      1       0        1           Texas         Kerr  2.151593\n"
       ]
      }
     ],
     "prompt_number": 61
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print df[df['hot_01']>0].to_string() "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "       FIPS       HR80  sig01  sig05  hot_01  cold_01   STATE_NAME        County      wHR80\n",
        "199   21025  19.603231      1      1       1        0     Kentucky     Breathitt  20.213720\n",
        "231   21193  37.516413      1      1       1        0     Kentucky         Perry  18.053386\n",
        "240   21051  29.301453      1      1       1        0     Kentucky          Clay  19.064651\n",
        "247   21131  38.077319      1      1       1        0     Kentucky        Leslie  26.731707\n",
        "285   21095  20.689600      1      1       1        0     Kentucky        Harlan  20.361694\n",
        "305   21013  19.419361      1      1       1        0     Kentucky          Bell  19.268191\n",
        "712   28027  15.349333      1      1       1        0  Mississippi       Coahoma  18.435638\n",
        "804   48387  10.351324      1      1       1        0        Texas     Red River  19.645064\n",
        "831   13045  14.197991      1      1       1        0      Georgia       Carroll  16.907577\n",
        "850   28015  10.229133      1      1       1        0  Mississippi       Carroll  20.176860\n",
        "862   13245  19.637099      1      1       1        0      Georgia      Richmond  16.970401\n",
        "868   13077  11.884147      1      1       1        0      Georgia        Coweta  17.892569\n",
        "876   13141  14.085499      1      1       1        0      Georgia       Hancock  16.891151\n",
        "905   13163  21.735587      1      1       1        0      Georgia     Jefferson  19.314330\n",
        "908   28007  20.135917      1      1       1        0  Mississippi        Attala  16.953643\n",
        "914   13285  14.665787      1      1       1        0      Georgia         Troup  18.389184\n",
        "924   01123  13.789775      1      1       1        0      Alabama    Tallapoosa  16.972680\n",
        "927   48063  10.781671      1      1       1        0        Texas          Camp  18.053473\n",
        "930   28163  23.157459      1      1       1        0  Mississippi         Yazoo  18.021208\n",
        "932   22017  23.115310      1      1       1        0    Louisiana         Caddo  19.128359\n",
        "939   01065  10.681022      1      1       1        0      Alabama          Hale  18.465013\n",
        "951   01119  15.771627      1      1       1        0      Alabama        Sumter  16.980758\n",
        "963   28099  11.209663      1      1       1        0  Mississippi       Neshoba  18.659732\n",
        "966   48459  12.822755      1      1       1        0        Texas        Upshur  19.088636\n",
        "968   28089  20.025793      1      1       1        0  Mississippi       Madison  19.401358\n",
        "978   48203  15.944386      1      1       1        0        Texas      Harrison  19.890318\n",
        "995   28149  14.204454      1      1       1        0  Mississippi        Warren  17.991778\n",
        "1024  13283  10.952303      1      1       1        0      Georgia      Treutlen  17.745963\n",
        "1033  48365  12.867529      1      1       1        0        Texas        Panola  19.027194\n",
        "1037  22031  18.139179      1      1       1        0    Louisiana       De Soto  19.654971\n",
        "1058  13259  33.921303      1      1       1        0      Georgia       Stewart  18.068855\n",
        "1059  13307  14.238929      1      1       1        0      Georgia       Webster  19.959551\n",
        "1060  13261  10.217984      1      1       1        0      Georgia        Sumter  17.826729\n",
        "1062  01005  24.236549      1      1       1        0      Alabama       Barbour  18.211972\n",
        "1064  22069  19.232538      1      1       1        0    Louisiana  Natchitoches  16.522239\n",
        "1093  13239  28.284542      1      1       1        0      Georgia       Quitman  21.470889\n",
        "1101  13243  17.362920      1      1       1        0      Georgia      Randolph  22.019482\n",
        "1119  01067  13.070187      1      1       1        0      Alabama         Henry  18.363221\n",
        "1120  13061  18.763486      1      1       1        0      Georgia          Clay  20.308494\n",
        "1134  13095  17.540724      1      1       1        0      Georgia     Dougherty  17.875898\n",
        "1141  13037  17.491691      1      1       1        0      Georgia       Calhoun  19.320700\n",
        "1162  13007  17.507003      1      1       1        0      Georgia         Baker  17.276367\n",
        "1184  01003  11.456795      1      1       1        0      Alabama       Baldwin  17.564441\n",
        "1254  48339  12.193192      1      1       1        0        Texas    Montgomery  17.506628\n",
        "1379  12093  24.674299      1      1       1        0      Florida    Okeechobee  15.611664\n",
        "1391  12099  11.267840      1      1       1        0      Florida    Palm Beach  20.597051\n",
        "1392  12051  21.506533      1      1       1        0      Florida        Hendry  16.138073\n",
        "1395  12071  12.341709      1      1       1        0      Florida           Lee  19.725170\n",
        "1397  12021  22.875931      1      1       1        0      Florida       Collier  18.494922\n",
        "1399  12011  15.615793      1      1       1        0      Florida       Broward  21.631943\n",
        "1401  12087  12.133105      1      1       1        0      Florida        Monroe  26.876699\n"
       ]
      }
     ],
     "prompt_number": 62
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 62
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}