plot-hop1-hop2-interleaving-depths-cdf.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*This notebook plots the distribution of probes that witness 2-levels and 3-levels of interleaving depth level changes*\n",
    "- - - "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "import pandas as pd\n",
    "import matplotlib.dates as dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "DB_LOCATION = 'lastmile.db'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "RA_PROBE = 'ra_probe'\n",
    "RA_PROBE_API = 'ra_probe_api'\n",
    "RA_ASN = 'ra_asn'\n",
    "RA_ONE_OFF_EXTENSIONS = 'ra_one_off_extensions'\n",
    "RA_LATENCIES_AGG = 'ra_latencies_agg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "SK_ONE_OFF_EXTENSIONS = 'sk_one_off_extensions'\n",
    "SK_LATENCIES_AGG = 'sk_latencies_agg'\n",
    "SK_ASN = 'sk_asn'\n",
    "METADATA_SNAPSHOT = 'metadata_snapshot'\n",
    "METADATA_SNAPSHOT_EXTENSIONS = 'metadata_snapshot_extensions'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "con = sqlite3.connect(DB_LOCATION)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "query_ra = '''SELECT      agg.probeid\n",
    "                        , agg.timestamp\n",
    "                        , s.asn\n",
    "                        , s.asn_holder_name\n",
    "                        , s.asn_access_type\n",
    "                        , agg.h1_median as h1\n",
    "                        , agg.h2_median as h2                        \n",
    "\n",
    "               FROM   %s                             as  agg\n",
    "                    , %s                             as  api               \n",
    "                    , %s                             as  s                  \n",
    "                    , %s                             as  hardware\n",
    "                    , %s                             as  ext\n",
    "\n",
    "               WHERE     agg.probeid                  =  api.probeid\n",
    "               AND       agg.probeid                  =  hardware.probeid\n",
    "               AND       agg.probeid                  =  ext.probeid\n",
    "               AND       api.asn_v4                   =  s.asn\n",
    "               \n",
    "\n",
    "               AND       hardware.hardware_version    =  'v3'\n",
    "               AND       ext.if_residential           =  1\n",
    "               \n",
    "            '''%(  RA_LATENCIES_AGG\n",
    "                 , RA_PROBE_API\n",
    "                 , RA_ASN\n",
    "                 , RA_PROBE\n",
    "                 , RA_ONE_OFF_EXTENSIONS\n",
    "                )\n",
    "\n",
    "df_ra = pd.read_sql(query_ra, con)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "probeid            134724\n",
       "timestamp          134724\n",
       "asn                134724\n",
       "asn_holder_name    134724\n",
       "asn_access_type    134724\n",
       "h1                 133920\n",
       "h2                 130563\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>probeid</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>asn</th>\n",
       "      <th>asn_holder_name</th>\n",
       "      <th>asn_access_type</th>\n",
       "      <th>h1</th>\n",
       "      <th>h2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10006</td>\n",
       "      <td>1406548034</td>\n",
       "      <td>3265</td>\n",
       "      <td>XS4ALL-NL XS4ALL Internet BV,NL</td>\n",
       "      <td>DSL</td>\n",
       "      <td>0.429</td>\n",
       "      <td>20.490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10006</td>\n",
       "      <td>1406562432</td>\n",
       "      <td>3265</td>\n",
       "      <td>XS4ALL-NL XS4ALL Internet BV,NL</td>\n",
       "      <td>DSL</td>\n",
       "      <td>0.431</td>\n",
       "      <td>17.700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10006</td>\n",
       "      <td>1406576835</td>\n",
       "      <td>3265</td>\n",
       "      <td>XS4ALL-NL XS4ALL Internet BV,NL</td>\n",
       "      <td>DSL</td>\n",
       "      <td>0.438</td>\n",
       "      <td>17.776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10006</td>\n",
       "      <td>1406591230</td>\n",
       "      <td>3265</td>\n",
       "      <td>XS4ALL-NL XS4ALL Internet BV,NL</td>\n",
       "      <td>DSL</td>\n",
       "      <td>0.478</td>\n",
       "      <td>17.577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10006</td>\n",
       "      <td>1406605631</td>\n",
       "      <td>3265</td>\n",
       "      <td>XS4ALL-NL XS4ALL Internet BV,NL</td>\n",
       "      <td>DSL</td>\n",
       "      <td>0.422</td>\n",
       "      <td>17.526</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   probeid   timestamp   asn                  asn_holder_name asn_access_type  \\\n",
       "0    10006  1406548034  3265  XS4ALL-NL XS4ALL Internet BV,NL             DSL   \n",
       "1    10006  1406562432  3265  XS4ALL-NL XS4ALL Internet BV,NL             DSL   \n",
       "2    10006  1406576835  3265  XS4ALL-NL XS4ALL Internet BV,NL             DSL   \n",
       "3    10006  1406591230  3265  XS4ALL-NL XS4ALL Internet BV,NL             DSL   \n",
       "4    10006  1406605631  3265  XS4ALL-NL XS4ALL Internet BV,NL             DSL   \n",
       "\n",
       "      h1      h2  \n",
       "0  0.429  20.490  \n",
       "1  0.431  17.700  \n",
       "2  0.438  17.776  \n",
       "3  0.478  17.577  \n",
       "4  0.422  17.526  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "query_sk = ''' SELECT     agg.probeid\n",
    "                        , agg.timestamp\n",
    "                        , s.asn \n",
    "                        , s.asn_access_type\n",
    "                        , s.asn_holder_name\n",
    "                        , meta.product                        \n",
    "                        , agg.h1_avg as h1\n",
    "                        , agg.h2_avg as h2\n",
    "                                                                                     \n",
    "               FROM       %s                            as   agg\n",
    "                        , %s                            as   api               \n",
    "                        , %s                            as   ext\n",
    "                        , %s                            as   s\n",
    "                        , %s                            as   meta\n",
    "                        \n",
    "                        \n",
    "\n",
    "               WHERE      agg.probeid                    =    ext.probeid\n",
    "               AND        agg.probeid                    =    api.probeid\n",
    "               AND        agg.probeid                    =    meta.id               \n",
    "               AND        api.asn                        =    s.asn               \n",
    "               \n",
    "               AND        ext.if_residential             =    1\n",
    "               AND        agg.h1_avg                     <>   0\n",
    "               AND        agg.h2_avg                     <>   0\n",
    "               \n",
    "           '''%(   SK_LATENCIES_AGG\n",
    "                 , METADATA_SNAPSHOT_EXTENSIONS                \n",
    "                 , SK_ONE_OFF_EXTENSIONS\n",
    "                 , SK_ASN        \n",
    "                 , METADATA_SNAPSHOT                \n",
    "               )\n",
    "\n",
    "df_sk = pd.read_sql(query_sk, con)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_ra = df_ra.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_sk = df_sk.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "probeid            415903\n",
       "timestamp          415903\n",
       "asn                415903\n",
       "asn_access_type    415903\n",
       "asn_holder_name    415903\n",
       "product            415903\n",
       "h1                 415903\n",
       "h2                 415903\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "probeid            130006\n",
       "timestamp          130006\n",
       "asn                130006\n",
       "asn_holder_name    130006\n",
       "asn_access_type    130006\n",
       "h1                 130006\n",
       "h2                 130006\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_ra = df_ra[df_ra.asn_access_type == 'DSL']\n",
    "df_sk = df_sk[df_sk.asn_access_type == 'DSL']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def create_pretty_node_names(asn, holder):\n",
    "    \n",
    "    d = {\n",
    "          'NTL'        : 'VIRGINMEDIA'\n",
    "        , 'AS3215'     : 'ORANGE'        \n",
    "        , 'VODANET'    : 'VODAFONE'\n",
    "        , 'PROXAD'     : 'FREE'\n",
    "        , 'ROADRUNNER' : 'TWC'\n",
    "        , 'TDDE'       : 'TELEFONICA-DE'\n",
    "        , 'TT'         : 'TALKTALK'\n",
    "    }\n",
    "    \n",
    "    firstname = holder.split('-')[0].split(' ')[0]\n",
    "    try: firstname = d[firstname]\n",
    "    except Exception as e: pass\n",
    "    \n",
    "    if 'AS' in str(asn): nodename = '%s (%s)'%(firstname, asn)\n",
    "    else: nodename = '%s (AS%s)'%(firstname, asn)\n",
    "    return nodename\n",
    "\n",
    "def myfunc(x):\n",
    "    asn = x['asn']; holder = x['asn_holder_name']; \n",
    "    nodename = create_pretty_node_names(asn, holder)\n",
    "    x['nodename'] = nodename\n",
    "    return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_ra_groupby = df_ra.groupby(['asn', 'asn_holder_name'])\n",
    "df_sk_groupby = df_sk.groupby(['asn', 'asn_holder_name'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from scipy.cluster.vq import kmeans\n",
    "from scipy.signal import argrelextrema\n",
    "\n",
    "def calculate_kde(df):\n",
    "\n",
    "    x = df.sort('h2')['h2'].values\n",
    "    from scipy.stats import kde    \n",
    "    try: density = kde.gaussian_kde(x)\n",
    "    except Exception as e: print(e, type(e), key, end=''); return None\n",
    "    else: \n",
    "        xgrid = np.linspace(x.min(), x.max(), len(x))   \n",
    "        ygrid = density(xgrid)\n",
    "        return xgrid, ygrid\n",
    "        \n",
    "def calculate_kde_peaks(df):\n",
    "    \n",
    "    xgrid, ygrid = calculate_kde(df)\n",
    "    maximas_indexes = argrelextrema(ygrid, np.greater)[0]\n",
    "    max_y = ygrid[maximas_indexes]        \n",
    "    max_x = xgrid[maximas_indexes]\n",
    "    zipped_x_y = zip(max_x, max_y)\n",
    "    peaks = []\n",
    "    prev = None; interval = False\n",
    "    for x, y in zipped_x_y:\n",
    "        if prev is None: interval = True\n",
    "        if prev is not None: \n",
    "            if abs(x - prev) < 5: continue\n",
    "            else: interval = True\n",
    "        if interval:\n",
    "            prev = x\n",
    "            if y >= 0.01: peaks.append((x,y))\n",
    "    return (peaks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def start_plot():    \n",
    "    plt.style.use('ggplot')\n",
    "    fig = plt.figure(figsize=(9,5))\n",
    "    plt.rcParams['font.size'] = 22\n",
    "    ax = fig.add_subplot(111)\n",
    "    return ax\n",
    "\n",
    "def stop_plot_cdf(ax, chosen, count):\n",
    "    \n",
    "    ax.grid(True)\n",
    "    ax.set_xlim([0.25, 64])    \n",
    "    ax.set_xscale('log', basex=2)\n",
    "    ax.set_xlabel('Latency (ms)', fontsize=22)\n",
    "    ax.set_ylabel('CDF', fontsize=22)\n",
    "    plt.legend(loc='best', fontsize=22)\n",
    "    plt.title('%s (RIPE Atlas)'%(chosen), fontsize=22, y=1.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def add_to_d(df_groupby):\n",
    "    d = {}\n",
    "    for i, (key, group) in enumerate(df_groupby):\n",
    "        asn, holder_name = key; draw=False\n",
    "        nodename = create_pretty_node_names(asn, holder_name)\n",
    "        df_groupby_probeid = group.groupby('probeid')\n",
    "\n",
    "        for j, (probeid, group) in enumerate(df_groupby_probeid):\n",
    "            if group['timestamp'].count() <= 1: continue\n",
    "            try: peaks = calculate_kde_peaks(group)\n",
    "            except Exception as e: print(e)\n",
    "            if len(peaks) <= 1: continue\n",
    "            print('.', end='')\n",
    "            try: d[len(peaks)].append(probeid)\n",
    "            except Exception as e: d[len(peaks)] = [probeid]\n",
    "    return d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "..................................................................................................................................."
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/ipykernel/__main__.py:6: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n"
     ]
    }
   ],
   "source": [
    "d_ra = add_to_d(df_ra_groupby)\n",
    "d_sk = add_to_d(df_sk_groupby)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_ra_groupby = df_ra.groupby('probeid')\n",
    "df_agg = df_ra_groupby.agg([len])\n",
    "df_ra_merge = pd.merge(df_ra, df_agg, left_on=\"probeid\", right_index=True)\n",
    "df_ra_merge_cut = df_ra_merge.iloc[:,[0,2,3]]\n",
    "df_ra_probes = df_ra_merge_cut.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_sk_groupby = df_sk.groupby('probeid')\n",
    "df_agg = df_sk_groupby.agg([len])\n",
    "df_sk_merge = pd.merge(df_sk, df_agg, left_on=\"probeid\", right_index=True)\n",
    "df_sk_merge_cut = df_sk_merge.iloc[:,[0,2,4]]\n",
    "df_sk_probes = df_sk_merge_cut.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "probeid            451\n",
       "asn                451\n",
       "asn_holder_name    451\n",
       "dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra_probes.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "probeid            986\n",
       "asn                986\n",
       "asn_holder_name    986\n",
       "dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk_probes.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/ipykernel/__main__.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/ipykernel/__main__.py:10: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n"
     ]
    }
   ],
   "source": [
    "def get_depth_level(d, probeid):\n",
    "    for k, v in d.items():\n",
    "        if probeid in v: return k\n",
    "    return 1\n",
    "\n",
    "def get_ra_depth_level(probeid): return get_depth_level(d_ra, probeid)\n",
    "def get_sk_depth_level(probeid): return get_depth_level(d_sk, probeid)   \n",
    "    \n",
    "df_ra_probes['level'] = df_ra_probes['probeid'].apply(get_ra_depth_level)\n",
    "df_sk_probes['level'] = df_sk_probes['probeid'].apply(get_sk_depth_level)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>probeid</th>\n",
       "      <th>asn</th>\n",
       "      <th>asn_holder_name</th>\n",
       "      <th>level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10006</td>\n",
       "      <td>3265</td>\n",
       "      <td>XS4ALL-NL XS4ALL Internet BV,NL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570</th>\n",
       "      <td>10012</td>\n",
       "      <td>3265</td>\n",
       "      <td>XS4ALL-NL XS4ALL Internet BV,NL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>778</th>\n",
       "      <td>10013</td>\n",
       "      <td>3265</td>\n",
       "      <td>XS4ALL-NL XS4ALL Internet BV,NL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986</th>\n",
       "      <td>10015</td>\n",
       "      <td>3265</td>\n",
       "      <td>XS4ALL-NL XS4ALL Internet BV,NL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1194</th>\n",
       "      <td>10022</td>\n",
       "      <td>3265</td>\n",
       "      <td>XS4ALL-NL XS4ALL Internet BV,NL</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      probeid   asn                  asn_holder_name  level\n",
       "0       10006  3265  XS4ALL-NL XS4ALL Internet BV,NL      1\n",
       "570     10012  3265  XS4ALL-NL XS4ALL Internet BV,NL      1\n",
       "778     10013  3265  XS4ALL-NL XS4ALL Internet BV,NL      1\n",
       "986     10015  3265  XS4ALL-NL XS4ALL Internet BV,NL      1\n",
       "1194    10022  3265  XS4ALL-NL XS4ALL Internet BV,NL      1"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra_probes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>probeid</th>\n",
       "      <th>asn</th>\n",
       "      <th>asn_holder_name</th>\n",
       "      <th>level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14905</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>14971</td>\n",
       "      <td>12576</td>\n",
       "      <td>ORANGE-PCS Orange Personal Communications Serv...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>564</th>\n",
       "      <td>15015</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>15058</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1304</th>\n",
       "      <td>15129</td>\n",
       "      <td>6871</td>\n",
       "      <td>PLUSNET PlusNet PLC,GB</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      probeid    asn                                    asn_holder_name  level\n",
       "0       14905   2856             BT-UK-AS BT Public Internet Service,GB      1\n",
       "418     14971  12576  ORANGE-PCS Orange Personal Communications Serv...      1\n",
       "564     15015   2856             BT-UK-AS BT Public Internet Service,GB      1\n",
       "978     15058   2856             BT-UK-AS BT Public Internet Service,GB      1\n",
       "1304    15129   6871                             PLUSNET PlusNet PLC,GB      1"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk_probes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import Cdf\n",
    "\n",
    "markers = ['d', 'x', '+', 'o', 'p', 'v', '8', '*', 'D', '<', 's']\n",
    "\n",
    "def draw_cdf(df):\n",
    "    \n",
    "    sample = df['level'].values\n",
    "    c = Cdf.MakeCdfFromList(sample)\n",
    "    \n",
    "    print(c.xs, c.ps)\n",
    "    plt.plot (  c.xs\n",
    "              , c.ps\n",
    "              , marker='s'\n",
    "              , linewidth=0.3\n",
    "              , color='Red'\n",
    "              , markersize=15\n",
    "              , fillstyle='none'\n",
    "             )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>probeid</th>\n",
       "      <th>asn</th>\n",
       "      <th>asn_holder_name</th>\n",
       "      <th>level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>54245</th>\n",
       "      <td>141012</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90763</th>\n",
       "      <td>142056</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96334</th>\n",
       "      <td>142920</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105848</th>\n",
       "      <td>143082</td>\n",
       "      <td>13285</td>\n",
       "      <td>OPALTELECOM-AS TalkTalk Communications Limited,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123386</th>\n",
       "      <td>143268</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231957</th>\n",
       "      <td>146314</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236809</th>\n",
       "      <td>146358</td>\n",
       "      <td>13285</td>\n",
       "      <td>OPALTELECOM-AS TalkTalk Communications Limited,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280620</th>\n",
       "      <td>147230</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>282214</th>\n",
       "      <td>147250</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>292598</th>\n",
       "      <td>147542</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>324427</th>\n",
       "      <td>148550</td>\n",
       "      <td>9105</td>\n",
       "      <td>TISCALI-UK Tiscali UK,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>385452</th>\n",
       "      <td>202328</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>397728</th>\n",
       "      <td>249892</td>\n",
       "      <td>12576</td>\n",
       "      <td>ORANGE-PCS Orange Personal Communications Serv...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415516</th>\n",
       "      <td>469838</td>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        probeid    asn                                    asn_holder_name  \\\n",
       "54245    141012   2856             BT-UK-AS BT Public Internet Service,GB   \n",
       "90763    142056   2856             BT-UK-AS BT Public Internet Service,GB   \n",
       "96334    142920   2856             BT-UK-AS BT Public Internet Service,GB   \n",
       "105848   143082  13285  OPALTELECOM-AS TalkTalk Communications Limited,GB   \n",
       "123386   143268   2856             BT-UK-AS BT Public Internet Service,GB   \n",
       "231957   146314   2856             BT-UK-AS BT Public Internet Service,GB   \n",
       "236809   146358  13285  OPALTELECOM-AS TalkTalk Communications Limited,GB   \n",
       "280620   147230   2856             BT-UK-AS BT Public Internet Service,GB   \n",
       "282214   147250   2856             BT-UK-AS BT Public Internet Service,GB   \n",
       "292598   147542   2856             BT-UK-AS BT Public Internet Service,GB   \n",
       "324427   148550   9105                           TISCALI-UK Tiscali UK,GB   \n",
       "385452   202328   2856             BT-UK-AS BT Public Internet Service,GB   \n",
       "397728   249892  12576  ORANGE-PCS Orange Personal Communications Serv...   \n",
       "415516   469838   2856             BT-UK-AS BT Public Internet Service,GB   \n",
       "\n",
       "        level  \n",
       "54245       3  \n",
       "90763       3  \n",
       "96334       3  \n",
       "105848      3  \n",
       "123386      3  \n",
       "231957      3  \n",
       "236809      3  \n",
       "280620      3  \n",
       "282214      3  \n",
       "292598      3  \n",
       "324427      3  \n",
       "385452      3  \n",
       "397728      3  \n",
       "415516      3  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk_probes[df_sk_probes.level == 3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "probeid            986\n",
       "asn                986\n",
       "asn_holder_name    986\n",
       "level              986\n",
       "dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk_probes.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "probeid            451\n",
       "asn                451\n",
       "asn_holder_name    451\n",
       "level              451\n",
       "dtype: int64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra_probes.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def get_levels_by_asn(df):\n",
    "    df_groupby = df.groupby(['asn', 'level'])\n",
    "    df_groupby_agg = df_groupby.agg([len])\n",
    "    df_merge = pd.merge(  df\n",
    "                        , df_groupby_agg\n",
    "                        , left_on=['asn', 'level']\n",
    "                        , right_index=True\n",
    "                       )\n",
    "    del df_merge['probeid']\n",
    "    df_levels = df_merge.drop_duplicates()\n",
    "    df_levels = df_levels.sort('asn')\n",
    "    return df_levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/ipykernel/__main__.py:11: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n"
     ]
    }
   ],
   "source": [
    "df_ra_levels = get_levels_by_asn(df_ra_probes)\n",
    "df_sk_levels = get_levels_by_asn(df_sk_probes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>asn</th>\n",
       "      <th>asn_holder_name</th>\n",
       "      <th>level</th>\n",
       "      <th>(probeid, len)</th>\n",
       "      <th>(asn_holder_name, len)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6346</th>\n",
       "      <td>701</td>\n",
       "      <td>UUNET - MCI Communications Services, Inc. d/b/...</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1811</th>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3955</th>\n",
       "      <td>3209</td>\n",
       "      <td>VODANET Vodafone GmbH,DE</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24705</th>\n",
       "      <td>3215</td>\n",
       "      <td>AS3215 Orange S.A.,FR</td>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3265</td>\n",
       "      <td>XS4ALL-NL XS4ALL Internet BV,NL</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        asn                                    asn_holder_name  level  \\\n",
       "6346    701  UUNET - MCI Communications Services, Inc. d/b/...      1   \n",
       "1811   2856             BT-UK-AS BT Public Internet Service,GB      1   \n",
       "3955   3209                           VODANET Vodafone GmbH,DE      1   \n",
       "24705  3215                              AS3215 Orange S.A.,FR      1   \n",
       "0      3265                    XS4ALL-NL XS4ALL Internet BV,NL      1   \n",
       "\n",
       "       (probeid, len)  (asn_holder_name, len)  \n",
       "6346               23                      23  \n",
       "1811               23                      23  \n",
       "3955               10                      10  \n",
       "24705              60                      60  \n",
       "0                  29                      29  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra_levels.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>asn</th>\n",
       "      <th>asn_holder_name</th>\n",
       "      <th>level</th>\n",
       "      <th>(probeid, len)</th>\n",
       "      <th>(asn_holder_name, len)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>1</td>\n",
       "      <td>264</td>\n",
       "      <td>264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6056</th>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>2</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54245</th>\n",
       "      <td>2856</td>\n",
       "      <td>BT-UK-AS BT Public Internet Service,GB</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173243</th>\n",
       "      <td>5607</td>\n",
       "      <td>BSKYB-BROADBAND-AS British Sky Broadcasting Li...</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15622</th>\n",
       "      <td>5607</td>\n",
       "      <td>BSKYB-BROADBAND-AS British Sky Broadcasting Li...</td>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         asn                                    asn_holder_name  level  \\\n",
       "0       2856             BT-UK-AS BT Public Internet Service,GB      1   \n",
       "6056    2856             BT-UK-AS BT Public Internet Service,GB      2   \n",
       "54245   2856             BT-UK-AS BT Public Internet Service,GB      3   \n",
       "173243  5607  BSKYB-BROADBAND-AS British Sky Broadcasting Li...      2   \n",
       "15622   5607  BSKYB-BROADBAND-AS British Sky Broadcasting Li...      1   \n",
       "\n",
       "        (probeid, len)  (asn_holder_name, len)  \n",
       "0                  264                     264  \n",
       "6056                40                      40  \n",
       "54245               10                      10  \n",
       "173243               1                       1  \n",
       "15622               35                      35  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk_levels.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_ra_levels = df_ra_levels.apply(myfunc, axis=1)\n",
    "df_sk_levels = df_sk_levels.apply(myfunc, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "del df_ra_levels['asn']; del df_ra_levels['asn_holder_name'];\n",
    "del df_sk_levels['asn']; del df_sk_levels['asn_holder_name'];"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>level</th>\n",
       "      <th>(probeid, len)</th>\n",
       "      <th>(asn_holder_name, len)</th>\n",
       "      <th>nodename</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6346</th>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>UUNET (AS701)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1811</th>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>BT (AS2856)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3955</th>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>VODAFONE (AS3209)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24705</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>60</td>\n",
       "      <td>ORANGE (AS3215)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>XS4ALL (AS3265)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       level  (probeid, len)  (asn_holder_name, len)           nodename\n",
       "6346       1              23                      23      UUNET (AS701)\n",
       "1811       1              23                      23        BT (AS2856)\n",
       "3955       1              10                      10  VODAFONE (AS3209)\n",
       "24705      1              60                      60    ORANGE (AS3215)\n",
       "0          1              29                      29    XS4ALL (AS3265)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra_levels.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>level</th>\n",
       "      <th>(probeid, len)</th>\n",
       "      <th>(asn_holder_name, len)</th>\n",
       "      <th>nodename</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>264</td>\n",
       "      <td>264</td>\n",
       "      <td>BT (AS2856)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6056</th>\n",
       "      <td>2</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>BT (AS2856)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54245</th>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>BT (AS2856)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173243</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>BSKYB (AS5607)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15622</th>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>BSKYB (AS5607)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        level  (probeid, len)  (asn_holder_name, len)        nodename\n",
       "0           1             264                     264     BT (AS2856)\n",
       "6056        2              40                      40     BT (AS2856)\n",
       "54245       3              10                      10     BT (AS2856)\n",
       "173243      2               1                       1  BSKYB (AS5607)\n",
       "15622       1              35                      35  BSKYB (AS5607)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk_levels.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_ra_levels.rename(columns={df_ra_levels.columns[1]: 'probes'}, inplace=True)\n",
    "df_sk_levels.rename(columns={df_sk_levels.columns[1]: 'probes'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_ra = df_ra_levels.iloc[:,[0,1,3]]\n",
    "df_sk = df_sk_levels.iloc[:,[0,1,3]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>level</th>\n",
       "      <th>probes</th>\n",
       "      <th>nodename</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6346</th>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>UUNET (AS701)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1811</th>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>BT (AS2856)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3955</th>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>VODAFONE (AS3209)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24705</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>ORANGE (AS3215)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>XS4ALL (AS3265)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17953</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>XS4ALL (AS3265)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1400</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>DTAG (AS3320)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92869</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>DTAG (AS3320)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13375</th>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>BELGACOM (AS5432)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20046</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>BELGACOM (AS5432)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       level  probes           nodename\n",
       "6346       1      23      UUNET (AS701)\n",
       "1811       1      23        BT (AS2856)\n",
       "3955       1      10  VODAFONE (AS3209)\n",
       "24705      1      60    ORANGE (AS3215)\n",
       "0          1      29    XS4ALL (AS3265)\n",
       "17953      2       1    XS4ALL (AS3265)\n",
       "1400       1      60      DTAG (AS3320)\n",
       "92869      2       1      DTAG (AS3320)\n",
       "13375      1      23  BELGACOM (AS5432)\n",
       "20046      2       1  BELGACOM (AS5432)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra.head(n=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>level</th>\n",
       "      <th>probes</th>\n",
       "      <th>nodename</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>264</td>\n",
       "      <td>BT (AS2856)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6056</th>\n",
       "      <td>2</td>\n",
       "      <td>40</td>\n",
       "      <td>BT (AS2856)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54245</th>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>BT (AS2856)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173243</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>BSKYB (AS5607)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15622</th>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>BSKYB (AS5607)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1304</th>\n",
       "      <td>1</td>\n",
       "      <td>261</td>\n",
       "      <td>PLUSNET (AS6871)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128310</th>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>PLUSNET (AS6871)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4800</th>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>TISCALI (AS9105)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20588</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>TISCALI (AS9105)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>324427</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>TISCALI (AS9105)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        level  probes          nodename\n",
       "0           1     264       BT (AS2856)\n",
       "6056        2      40       BT (AS2856)\n",
       "54245       3      10       BT (AS2856)\n",
       "173243      2       1    BSKYB (AS5607)\n",
       "15622       1      35    BSKYB (AS5607)\n",
       "1304        1     261  PLUSNET (AS6871)\n",
       "128310      2      10  PLUSNET (AS6871)\n",
       "4800        2      12  TISCALI (AS9105)\n",
       "20588       1      60  TISCALI (AS9105)\n",
       "324427      3       1  TISCALI (AS9105)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk.head(n=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def split_by_levels(df):\n",
    "    df['l1'] = 0; df['l2'] = 0; df['l3'] = 0\n",
    "    for index, row in df.iterrows():\n",
    "        try: l = row['level']; count = row['probes']\n",
    "        except Exception as e: print(e, type(e))\n",
    "        else: df.ix[index, 'l%d'%l] = count\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_ra = split_by_levels(df_ra)\n",
    "df_sk = split_by_levels(df_sk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "level       20\n",
       "probes      20\n",
       "nodename    20\n",
       "l1          20\n",
       "l2          20\n",
       "l3          20\n",
       "dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "level       22\n",
       "probes      22\n",
       "nodename    22\n",
       "l1          22\n",
       "l2          22\n",
       "l3          22\n",
       "dtype: int64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "del df_ra['level']; del df_ra['probes']\n",
    "del df_sk['level']; del df_sk['probes']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nodename</th>\n",
       "      <th>l1</th>\n",
       "      <th>l2</th>\n",
       "      <th>l3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6346</th>\n",
       "      <td>UUNET (AS701)</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1811</th>\n",
       "      <td>BT (AS2856)</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3955</th>\n",
       "      <td>VODAFONE (AS3209)</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24705</th>\n",
       "      <td>ORANGE (AS3215)</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>XS4ALL (AS3265)</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17953</th>\n",
       "      <td>XS4ALL (AS3265)</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1400</th>\n",
       "      <td>DTAG (AS3320)</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92869</th>\n",
       "      <td>DTAG (AS3320)</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13375</th>\n",
       "      <td>BELGACOM (AS5432)</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20046</th>\n",
       "      <td>BELGACOM (AS5432)</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                nodename  l1  l2  l3\n",
       "6346       UUNET (AS701)  23   0   0\n",
       "1811         BT (AS2856)  23   0   0\n",
       "3955   VODAFONE (AS3209)  10   0   0\n",
       "24705    ORANGE (AS3215)  60   0   0\n",
       "0        XS4ALL (AS3265)  29   0   0\n",
       "17953    XS4ALL (AS3265)   0   1   0\n",
       "1400       DTAG (AS3320)  60   0   0\n",
       "92869      DTAG (AS3320)   0   1   0\n",
       "13375  BELGACOM (AS5432)  23   0   0\n",
       "20046  BELGACOM (AS5432)   0   1   0"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra.head(n=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nodename</th>\n",
       "      <th>l1</th>\n",
       "      <th>l2</th>\n",
       "      <th>l3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BT (AS2856)</td>\n",
       "      <td>264</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6056</th>\n",
       "      <td>BT (AS2856)</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54245</th>\n",
       "      <td>BT (AS2856)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173243</th>\n",
       "      <td>BSKYB (AS5607)</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15622</th>\n",
       "      <td>BSKYB (AS5607)</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1304</th>\n",
       "      <td>PLUSNET (AS6871)</td>\n",
       "      <td>261</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128310</th>\n",
       "      <td>PLUSNET (AS6871)</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4800</th>\n",
       "      <td>TISCALI (AS9105)</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20588</th>\n",
       "      <td>TISCALI (AS9105)</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>324427</th>\n",
       "      <td>TISCALI (AS9105)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                nodename   l1  l2  l3\n",
       "0            BT (AS2856)  264   0   0\n",
       "6056         BT (AS2856)    0  40   0\n",
       "54245        BT (AS2856)    0   0  10\n",
       "173243    BSKYB (AS5607)    0   1   0\n",
       "15622     BSKYB (AS5607)   35   0   0\n",
       "1304    PLUSNET (AS6871)  261   0   0\n",
       "128310  PLUSNET (AS6871)    0  10   0\n",
       "4800    TISCALI (AS9105)    0  12   0\n",
       "20588   TISCALI (AS9105)   60   0   0\n",
       "324427  TISCALI (AS9105)    0   0   1"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk.head(n=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def merge_levels(df):\n",
    "    df_gby = df.groupby('nodename')\n",
    "    df_gby_agg = df_gby.agg([sum])\n",
    "    df_gby_merged = pd.merge(  df\n",
    "                             , df_gby_agg\n",
    "                             , left_on='nodename'\n",
    "                             , right_index=True\n",
    "                            )\n",
    "\n",
    "    del df_gby_merged['l1']; \n",
    "    del df_gby_merged['l2']; \n",
    "    del df_gby_merged['l3'];\n",
    "\n",
    "    df = df_gby_merged.drop_duplicates()\n",
    "\n",
    "    df.rename(  columns={  df.columns[1]: 'l1'\n",
    "                         , df.columns[2]: 'l2'\n",
    "                         , df.columns[3]: 'l3'                   \n",
    "                        }\n",
    "                 , inplace=True\n",
    "             )\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/pandas/core/frame.py:2697: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  **kwargs)\n"
     ]
    }
   ],
   "source": [
    "df_ra = merge_levels(df_ra)\n",
    "df_sk = merge_levels(df_sk)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nodename</th>\n",
       "      <th>l1</th>\n",
       "      <th>l2</th>\n",
       "      <th>l3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6346</th>\n",
       "      <td>UUNET (AS701)</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1811</th>\n",
       "      <td>BT (AS2856)</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3955</th>\n",
       "      <td>VODAFONE (AS3209)</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24705</th>\n",
       "      <td>ORANGE (AS3215)</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>XS4ALL (AS3265)</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1400</th>\n",
       "      <td>DTAG (AS3320)</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13375</th>\n",
       "      <td>BELGACOM (AS5432)</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50853</th>\n",
       "      <td>TELEFONICA-DE (AS6805)</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15250</th>\n",
       "      <td>FREE (AS12322)</td>\n",
       "      <td>125</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46481</th>\n",
       "      <td>ZEN (AS13037)</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32133</th>\n",
       "      <td>LDCOMNET (AS15557)</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3542</th>\n",
       "      <td>OVH (AS35540)</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     nodename   l1  l2  l3\n",
       "6346            UUNET (AS701)   23   0   0\n",
       "1811              BT (AS2856)   23   0   0\n",
       "3955        VODAFONE (AS3209)   10   0   0\n",
       "24705         ORANGE (AS3215)   60   0   0\n",
       "0             XS4ALL (AS3265)   29   1   0\n",
       "1400            DTAG (AS3320)   60   1   0\n",
       "13375       BELGACOM (AS5432)   23   1   0\n",
       "50853  TELEFONICA-DE (AS6805)   11   2   0\n",
       "15250          FREE (AS12322)  125  12   0\n",
       "46481           ZEN (AS13037)   10   2   0\n",
       "32133      LDCOMNET (AS15557)   28   1   0\n",
       "3542            OVH (AS35540)   28   1   0"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra.head(n=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nodename</th>\n",
       "      <th>l1</th>\n",
       "      <th>l2</th>\n",
       "      <th>l3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BT (AS2856)</td>\n",
       "      <td>264</td>\n",
       "      <td>40</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173243</th>\n",
       "      <td>BSKYB (AS5607)</td>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1304</th>\n",
       "      <td>PLUSNET (AS6871)</td>\n",
       "      <td>261</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4800</th>\n",
       "      <td>TISCALI (AS9105)</td>\n",
       "      <td>60</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2522</th>\n",
       "      <td>ECLIPSE (AS12513)</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40875</th>\n",
       "      <td>ORANGE (AS12576)</td>\n",
       "      <td>73</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156741</th>\n",
       "      <td>ZEN (AS13037)</td>\n",
       "      <td>33</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20200</th>\n",
       "      <td>OPALTELECOM (AS13285)</td>\n",
       "      <td>109</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14242</th>\n",
       "      <td>AS20712 (AS20712)</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44826</th>\n",
       "      <td>TALKTALK (AS43234)</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     nodename   l1  l2  l3\n",
       "0                 BT (AS2856)  264  40  10\n",
       "173243         BSKYB (AS5607)   35   1   0\n",
       "1304         PLUSNET (AS6871)  261  10   0\n",
       "4800         TISCALI (AS9105)   60  12   1\n",
       "2522        ECLIPSE (AS12513)    6   0   0\n",
       "40875        ORANGE (AS12576)   73   8   1\n",
       "156741          ZEN (AS13037)   33   2   0\n",
       "20200   OPALTELECOM (AS13285)  109  21   2\n",
       "14242       AS20712 (AS20712)    3   0   0\n",
       "44826      TALKTALK (AS43234)   32   2   0"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk.head(n=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/ipykernel/__main__.py:1: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "  if __name__ == '__main__':\n",
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/ipykernel/__main__.py:2: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "df_ra = df_ra.sort('l2')\n",
    "df_sk = df_sk.sort('l2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_ra = df_ra.reset_index()\n",
    "df_sk = df_sk.reset_index()\n",
    "del df_ra['index']; del df_sk['index']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nodename</th>\n",
       "      <th>l1</th>\n",
       "      <th>l2</th>\n",
       "      <th>l3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>UUNET (AS701)</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BT (AS2856)</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>VODAFONE (AS3209)</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ORANGE (AS3215)</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>XS4ALL (AS3265)</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>DTAG (AS3320)</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BELGACOM (AS5432)</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>LDCOMNET (AS15557)</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>OVH (AS35540)</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>TELEFONICA-DE (AS6805)</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ZEN (AS13037)</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>FREE (AS12322)</td>\n",
       "      <td>125</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  nodename   l1  l2  l3\n",
       "0            UUNET (AS701)   23   0   0\n",
       "1              BT (AS2856)   23   0   0\n",
       "2        VODAFONE (AS3209)   10   0   0\n",
       "3          ORANGE (AS3215)   60   0   0\n",
       "4          XS4ALL (AS3265)   29   1   0\n",
       "5            DTAG (AS3320)   60   1   0\n",
       "6        BELGACOM (AS5432)   23   1   0\n",
       "7       LDCOMNET (AS15557)   28   1   0\n",
       "8            OVH (AS35540)   28   1   0\n",
       "9   TELEFONICA-DE (AS6805)   11   2   0\n",
       "10           ZEN (AS13037)   10   2   0\n",
       "11          FREE (AS12322)  125  12   0"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ra.head(n=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nodename</th>\n",
       "      <th>l1</th>\n",
       "      <th>l2</th>\n",
       "      <th>l3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ECLIPSE (AS12513)</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AS20712 (AS20712)</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BSKYB (AS5607)</td>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ZEN (AS13037)</td>\n",
       "      <td>33</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TALKTALK (AS43234)</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ORANGE (AS12576)</td>\n",
       "      <td>73</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>PLUSNET (AS6871)</td>\n",
       "      <td>261</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>TISCALI (AS9105)</td>\n",
       "      <td>60</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>OPALTELECOM (AS13285)</td>\n",
       "      <td>109</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>BT (AS2856)</td>\n",
       "      <td>264</td>\n",
       "      <td>40</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                nodename   l1  l2  l3\n",
       "0      ECLIPSE (AS12513)    6   0   0\n",
       "1      AS20712 (AS20712)    3   0   0\n",
       "2         BSKYB (AS5607)   35   1   0\n",
       "3          ZEN (AS13037)   33   2   0\n",
       "4     TALKTALK (AS43234)   32   2   0\n",
       "5       ORANGE (AS12576)   73   8   1\n",
       "6       PLUSNET (AS6871)  261  10   0\n",
       "7       TISCALI (AS9105)   60  12   1\n",
       "8  OPALTELECOM (AS13285)  109  21   2\n",
       "9            BT (AS2856)  264  40  10"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sk.head(n=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.concat([df_ra, df_sk])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/ipykernel/__main__.py:2: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "df_l2 = df[df.l2 > 0]\n",
    "df_l2 = df_l2.sort('l2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/ipykernel/__main__.py:2: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "df_l3 = df[df.l3 > 0]\n",
    "df_l3 = df_l3.sort('l3')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nodename</th>\n",
       "      <th>l1</th>\n",
       "      <th>l2</th>\n",
       "      <th>l3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>XS4ALL (AS3265)</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>DTAG (AS3320)</td>\n",
       "      <td>60</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BELGACOM (AS5432)</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>LDCOMNET (AS15557)</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>OVH (AS35540)</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BSKYB (AS5607)</td>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>TELEFONICA-DE (AS6805)</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ZEN (AS13037)</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ZEN (AS13037)</td>\n",
       "      <td>33</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TALKTALK (AS43234)</td>\n",
       "      <td>32</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ORANGE (AS12576)</td>\n",
       "      <td>73</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>PLUSNET (AS6871)</td>\n",
       "      <td>261</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>FREE (AS12322)</td>\n",
       "      <td>125</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>TISCALI (AS9105)</td>\n",
       "      <td>60</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>OPALTELECOM (AS13285)</td>\n",
       "      <td>109</td>\n",
       "      <td>21</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>BT (AS2856)</td>\n",
       "      <td>264</td>\n",
       "      <td>40</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  nodename   l1  l2  l3\n",
       "4          XS4ALL (AS3265)   29   1   0\n",
       "5            DTAG (AS3320)   60   1   0\n",
       "6        BELGACOM (AS5432)   23   1   0\n",
       "7       LDCOMNET (AS15557)   28   1   0\n",
       "8            OVH (AS35540)   28   1   0\n",
       "2           BSKYB (AS5607)   35   1   0\n",
       "9   TELEFONICA-DE (AS6805)   11   2   0\n",
       "10           ZEN (AS13037)   10   2   0\n",
       "3            ZEN (AS13037)   33   2   0\n",
       "4       TALKTALK (AS43234)   32   2   0\n",
       "5         ORANGE (AS12576)   73   8   1\n",
       "6         PLUSNET (AS6871)  261  10   0\n",
       "11          FREE (AS12322)  125  12   0\n",
       "7         TISCALI (AS9105)   60  12   1\n",
       "8    OPALTELECOM (AS13285)  109  21   2\n",
       "9              BT (AS2856)  264  40  10"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_l2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/pandas/core/frame.py:2697: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  **kwargs)\n",
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/ipykernel/__main__.py:2: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "df_l2 = merge_levels(df_l2)\n",
    "df_l2 = df_l2.sort('l2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vbajpai/.virtualenvs/lastmile-data-collection-analysis-python3/lib/python3.4/site-packages/ipykernel/__main__.py:2: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "df_l3 = merge_levels(df_l3)\n",
    "df_l3 = df_l3.sort('l3')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_l2 = df_l2.reset_index(); df_l3 = df_l3.reset_index()\n",
    "del df_l2['index']; del df_l3['index']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_l2['nodename'] = df_l2['nodename'].apply(lambda x: x.split()[0])\n",
    "df_l3['nodename'] = df_l3['nodename'].apply(lambda x: x.split()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f011bbbdcc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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mhbasnThxosTsgoSEBF555RXlZ2dnZ2xsbEhMTASgVatWREVF0aRJE6KiomjdujWpqaUb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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f011be00f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "plt.figure()\n",
    "plt.rcParams['font.size'] = 12\n",
    "\n",
    "xticks = [i for i in range(0, 60, 10)]\n",
    "\n",
    "ax = df_l2.plot(  kind='barh'\n",
    "                , x='nodename'\n",
    "                , y=['l2']\n",
    "                , xticks=xticks\n",
    "                , stacked=False\n",
    "                , legend=None\n",
    "                , figsize=(4,3.5)\n",
    "                , grid=False\n",
    "               );\n",
    "\n",
    "for idx, label in enumerate(df_l2.index):\n",
    "    pos      = df_l2.ix[idx][0]\n",
    "    l2_value = df_l2.ix[idx][2]\n",
    "    try: \n",
    "        plt.annotate(str(l2_value), xy=(l2_value + 1, idx), va='center', fontsize=12, color='blue')            \n",
    "    except Exception as e: print(e, type(e), value)\n",
    "\n",
    "ax.yaxis.set_ticks_position('none')\n",
    "ax.xaxis.set_ticks_position('none')\n",
    "\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['left'].set_visible(False)\n",
    "ax.spines['bottom'].set_visible(False)\n",
    "\n",
    "ax.set_axis_bgcolor('#E2E2E2')    \n",
    "plt.xlim(0,max(xticks))\n",
    "plt.xlabel('# (Probes)', fontsize=12)\n",
    "plt.ylabel('')\n",
    "plt.legend([\"depth levels = 2\"], loc='lower right', fontsize=12)\n",
    "plt.title('Residential Probes', fontsize=12, y=1.02)\n",
    "plt.savefig('interleaving-depth-level2.pdf', format='pdf', bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f011d426550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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pVBIbG6uWjUbQXHFxcaWusCcIz0PT1001UaOCpZubG+vXr2fXrl3069ePEydO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\nNCCCpSAIggb+H3U3EoK1/sjrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f011d426630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "plt.figure()\n",
    "plt.rcParams['font.size'] = 12\n",
    "\n",
    "xticks = [i for i in range(0, 15, 2)]\n",
    "\n",
    "ax = df_l3.plot(  kind='barh'\n",
    "                , x='nodename'\n",
    "                , y=['l3']\n",
    "                , xticks=xticks\n",
    "                , stacked=False\n",
    "                , legend=None\n",
    "                , figsize=(4,1)\n",
    "                , grid=False\n",
    "               );\n",
    "\n",
    "for idx, label in enumerate(df_l3.index):\n",
    "    pos      = df_l3.ix[idx][0]\n",
    "    l3_value = df_l3.ix[idx][3]\n",
    "    try: \n",
    "        plt.annotate(str(l3_value), xy=(l3_value + 1, idx), va='center', fontsize=12, color='blue')            \n",
    "    except Exception as e: print(e, type(e), value)\n",
    "\n",
    "ax.yaxis.set_ticks_position('none')\n",
    "ax.xaxis.set_ticks_position('none')\n",
    "\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['left'].set_visible(False)\n",
    "ax.spines['bottom'].set_visible(False)\n",
    "\n",
    "ax.set_axis_bgcolor('#E2E2E2')    \n",
    "plt.xlim(0,max(xticks))\n",
    "plt.xlabel('# (Probes)', fontsize=12)\n",
    "plt.ylabel('')\n",
    "plt.legend([\"depth levels = 3\"], loc='lower right', fontsize=12)\n",
    "plt.title('Residential Probes', fontsize=12, y=1.02)\n",
    "plt.savefig('interleaving-depth-level3.pdf', format='pdf', bbox_inches='tight')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}