1_0_0_Ranking_Investors_Exit_Score.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ranking investors based on historical data:\n",
    "\n",
    "In this notebook the historically available data on what has happened to the companies (closed, went IPO, acquired or still operating) is used to generate a ranking for 44552  investors.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/scipy/sparse/sparsetools.py:20: DeprecationWarning:\n",
      "\n",
      "`scipy.sparse.sparsetools` is deprecated!\n",
      "scipy.sparse.sparsetools is a private module for scipy.sparse, and should not be used.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "plotly  2.4.0\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window.Plotly) {{require(['plotly'],function(plotly) {window.Plotly=plotly;});}}</script>"
      ],
      "text/vnd.plotly.v1+html": [
       "<script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window.Plotly) {{require(['plotly'],function(plotly) {window.Plotly=plotly;});}}</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from utils import *\n",
    "from sklearn import preprocessing\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df1 = pd.read_csv('./data/companies_funding.csv')\n",
    "df2 = pd.read_csv('./data/companies_status.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((423918, 12), (690594, 6))"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.shape, df2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_main = join_df(df1, df2, \"ds_uuid\", \"ds_uuid\", col_on = ['ds_uuid','status'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((423918, 12), (690594, 6), (423918, 13))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.shape, df2.shape, df_main.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:111: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_numeric_dtype is deprecated. import from the public API: pandas.api.types.is_numeric_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:111: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_numeric_dtype is deprecated. import from the public API: pandas.api.types.is_numeric_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:111: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_numeric_dtype is deprecated. import from the public API: pandas.api.types.is_numeric_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:111: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_numeric_dtype is deprecated. import from the public API: pandas.api.types.is_numeric_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:111: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_numeric_dtype is deprecated. import from the public API: pandas.api.types.is_numeric_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:111: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_numeric_dtype is deprecated. import from the public API: pandas.api.types.is_numeric_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:111: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_numeric_dtype is deprecated. import from the public API: pandas.api.types.is_numeric_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:111: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_numeric_dtype is deprecated. import from the public API: pandas.api.types.is_numeric_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:111: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_numeric_dtype is deprecated. import from the public API: pandas.api.types.is_numeric_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:111: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_numeric_dtype is deprecated. import from the public API: pandas.api.types.is_numeric_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:111: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_numeric_dtype is deprecated. import from the public API: pandas.api.types.is_numeric_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:114: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_datetime64_dtype is deprecated. import from the public API: pandas.api.types.is_datetime64_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:114: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_datetime64_dtype is deprecated. import from the public API: pandas.api.types.is_datetime64_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:114: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_datetime64_dtype is deprecated. import from the public API: pandas.api.types.is_datetime64_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:114: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_datetime64_dtype is deprecated. import from the public API: pandas.api.types.is_datetime64_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:114: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_datetime64_dtype is deprecated. import from the public API: pandas.api.types.is_datetime64_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:114: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_datetime64_dtype is deprecated. import from the public API: pandas.api.types.is_datetime64_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:114: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_datetime64_dtype is deprecated. import from the public API: pandas.api.types.is_datetime64_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:114: DeprecationWarning:\n",
      "\n",
      "pandas.core.common.is_datetime64_dtype is deprecated. import from the public API: pandas.api.types.is_datetime64_dtype instead\n",
      "\n",
      "/opt/anaconda/envs/Python3/lib/python3.6/site-packages/pandas_summary/__init__.py:91: DeprecationWarning:\n",
      "\n",
      "\n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "\n"
     ]
    },
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>ds_uuid</th>\n",
       "      <th>investor</th>\n",
       "      <th>date</th>\n",
       "      <th>amount_raised</th>\n",
       "      <th>round_type</th>\n",
       "      <th>update_status</th>\n",
       "      <th>source</th>\n",
       "      <th>round_id</th>\n",
       "      <th>currency</th>\n",
       "      <th>clean_url</th>\n",
       "      <th>update_date</th>\n",
       "      <th>status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>423918</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>278905</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>333596</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>211958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.44921e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.17115</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>122375</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.57354e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.61722</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>105979</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>211958</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.725e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>317938</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.3e+07</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>423917</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0005e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>counts</th>\n",
       "      <td>423918</td>\n",
       "      <td>423918</td>\n",
       "      <td>333504</td>\n",
       "      <td>333505</td>\n",
       "      <td>278905</td>\n",
       "      <td>333505</td>\n",
       "      <td>423606</td>\n",
       "      <td>333596</td>\n",
       "      <td>333596</td>\n",
       "      <td>284873</td>\n",
       "      <td>423918</td>\n",
       "      <td>423918</td>\n",
       "      <td>423798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>uniques</th>\n",
       "      <td>423918</td>\n",
       "      <td>184146</td>\n",
       "      <td>44552</td>\n",
       "      <td>6428</td>\n",
       "      <td>15784</td>\n",
       "      <td>34</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>54</td>\n",
       "      <td>184146</td>\n",
       "      <td>201</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>missing</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>90414</td>\n",
       "      <td>90413</td>\n",
       "      <td>145013</td>\n",
       "      <td>90413</td>\n",
       "      <td>312</td>\n",
       "      <td>90322</td>\n",
       "      <td>90322</td>\n",
       "      <td>139045</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>missing_perc</th>\n",
       "      <td>0%</td>\n",
       "      <td>0%</td>\n",
       "      <td>21.33%</td>\n",
       "      <td>21.33%</td>\n",
       "      <td>34.21%</td>\n",
       "      <td>21.33%</td>\n",
       "      <td>0.07%</td>\n",
       "      <td>21.31%</td>\n",
       "      <td>21.31%</td>\n",
       "      <td>32.80%</td>\n",
       "      <td>0%</td>\n",
       "      <td>0%</td>\n",
       "      <td>0.03%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>types</th>\n",
       "      <td>numeric</td>\n",
       "      <td>categorical</td>\n",
       "      <td>categorical</td>\n",
       "      <td>categorical</td>\n",
       "      <td>numeric</td>\n",
       "      <td>categorical</td>\n",
       "      <td>bool</td>\n",
       "      <td>bool</td>\n",
       "      <td>numeric</td>\n",
       "      <td>categorical</td>\n",
       "      <td>categorical</td>\n",
       "      <td>categorical</td>\n",
       "      <td>categorical</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Unnamed: 0      ds_uuid     investor         date amount_raised  \\\n",
       "count            423918          NaN          NaN          NaN        278905   \n",
       "mean             211958          NaN          NaN          NaN   3.44921e+07   \n",
       "std              122375          NaN          NaN          NaN   1.57354e+09   \n",
       "min                   0          NaN          NaN          NaN             0   \n",
       "25%              105979          NaN          NaN          NaN         1e+06   \n",
       "50%              211958          NaN          NaN          NaN     3.725e+06   \n",
       "75%              317938          NaN          NaN          NaN       1.3e+07   \n",
       "max              423917          NaN          NaN          NaN    5.0005e+11   \n",
       "counts           423918       423918       333504       333505        278905   \n",
       "uniques          423918       184146        44552         6428         15784   \n",
       "missing               0            0        90414        90413        145013   \n",
       "missing_perc         0%           0%       21.33%       21.33%        34.21%   \n",
       "types           numeric  categorical  categorical  categorical       numeric   \n",
       "\n",
       "               round_type update_status  source round_id     currency  \\\n",
       "count                 NaN           NaN     NaN   333596          NaN   \n",
       "mean                  NaN           NaN     NaN  2.17115          NaN   \n",
       "std                   NaN           NaN     NaN  1.61722          NaN   \n",
       "min                   NaN           NaN     NaN        1          NaN   \n",
       "25%                   NaN           NaN     NaN        1          NaN   \n",
       "50%                   NaN           NaN     NaN        2          NaN   \n",
       "75%                   NaN           NaN     NaN        3          NaN   \n",
       "max                   NaN           NaN     NaN       10          NaN   \n",
       "counts             333505        423606  333596   333596       284873   \n",
       "uniques                34             2       2       10           54   \n",
       "missing             90413           312   90322    90322       139045   \n",
       "missing_perc       21.33%         0.07%  21.31%   21.31%       32.80%   \n",
       "types         categorical          bool    bool  numeric  categorical   \n",
       "\n",
       "                clean_url  update_date       status  \n",
       "count                 NaN          NaN          NaN  \n",
       "mean                  NaN          NaN          NaN  \n",
       "std                   NaN          NaN          NaN  \n",
       "min                   NaN          NaN          NaN  \n",
       "25%                   NaN          NaN          NaN  \n",
       "50%                   NaN          NaN          NaN  \n",
       "75%                   NaN          NaN          NaN  \n",
       "max                   NaN          NaN          NaN  \n",
       "counts             423918       423918       423798  \n",
       "uniques            184146          201            4  \n",
       "missing                 0            0          120  \n",
       "missing_perc           0%           0%        0.03%  \n",
       "types         categorical  categorical  categorical  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(DataFrameSummary(df_main).summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "operating    317539\n",
       "acquired      60253\n",
       "closed        24546\n",
       "ipo           21460\n",
       "Name: status, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_main.status.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The companies that are closed is consider to be a loss for their investors so we are going to mark them with a -4 score. On the other hand, the companies that managed to become IPO or acquired are reflecting the successes of the investor decision to invest in them. With this logic I mind I have labeled each company with a score that is a reflection of their operating status and afterword by summing these scores as the function of investor, each investor resaved a quality number.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def successes_value(x): \n",
    "    if x == 'operating':\n",
    "        return(0)\n",
    "    elif x == 'acquired':\n",
    "        return (1)\n",
    "    elif x == 'closed':\n",
    "        return (-2)\n",
    "    elif x == 'ipo':\n",
    "        return (2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def period(x): return (20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_main['exit_scores'] = df_main['status'].apply(successes_value)\n",
    "df_main['period'] = df_main['status'].apply(period)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>ds_uuid</th>\n",
       "      <th>investor</th>\n",
       "      <th>date</th>\n",
       "      <th>amount_raised</th>\n",
       "      <th>round_type</th>\n",
       "      <th>update_status</th>\n",
       "      <th>source</th>\n",
       "      <th>round_id</th>\n",
       "      <th>currency</th>\n",
       "      <th>clean_url</th>\n",
       "      <th>update_date</th>\n",
       "      <th>status</th>\n",
       "      <th>exit_scores</th>\n",
       "      <th>period</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>c9005990-b1f3-4e27-a1fd-945bb8d16cfd</td>\n",
       "      <td>Menlo Ventures</td>\n",
       "      <td>2006-06-29</td>\n",
       "      <td>40000000.0</td>\n",
       "      <td>venture C</td>\n",
       "      <td>success</td>\n",
       "      <td>crunchbase</td>\n",
       "      <td>3.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>epac.com</td>\n",
       "      <td>2018-01-21</td>\n",
       "      <td>operating</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>bc44e52d-c991-469d-b769-8571623437fa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no data</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>creditrepairexpert.org</td>\n",
       "      <td>2017-06-16</td>\n",
       "      <td>operating</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>90214116-40c1-472b-b0b4-3fc53fd8dc38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no data</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>xpertfinancial.com</td>\n",
       "      <td>2017-08-05</td>\n",
       "      <td>closed</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>438ed619-7fdb-45ba-9788-5fce90536b46</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no data</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>searchoptmedia.com</td>\n",
       "      <td>2017-07-06</td>\n",
       "      <td>operating</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>6ff5e99a-c45d-494b-b4cb-257b55d1bc73</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no data</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vision64.com</td>\n",
       "      <td>2017-06-16</td>\n",
       "      <td>operating</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20</td>\n",
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      "text/plain": [
       "   Unnamed: 0                               ds_uuid        investor  \\\n",
       "0           0  c9005990-b1f3-4e27-a1fd-945bb8d16cfd  Menlo Ventures   \n",
       "1           1  bc44e52d-c991-469d-b769-8571623437fa             NaN   \n",
       "2           2  90214116-40c1-472b-b0b4-3fc53fd8dc38             NaN   \n",
       "3           3  438ed619-7fdb-45ba-9788-5fce90536b46             NaN   \n",
       "4           4  6ff5e99a-c45d-494b-b4cb-257b55d1bc73             NaN   \n",
       "\n",
       "         date  amount_raised round_type update_status      source  round_id  \\\n",
       "0  2006-06-29     40000000.0  venture C       success  crunchbase       3.0   \n",
       "1         NaN            NaN        NaN       no data         NaN       NaN   \n",
       "2         NaN            NaN        NaN       no data         NaN       NaN   \n",
       "3         NaN            NaN        NaN       no data         NaN       NaN   \n",
       "4         NaN            NaN        NaN       no data         NaN       NaN   \n",
       "\n",
       "  currency               clean_url update_date     status  exit_scores  period  \n",
       "0      USD                epac.com  2018-01-21  operating          0.0      20  \n",
       "1      NaN  creditrepairexpert.org  2017-06-16  operating          0.0      20  \n",
       "2      NaN      xpertfinancial.com  2017-08-05     closed         -2.0      20  \n",
       "3      NaN      searchoptmedia.com  2017-07-06  operating          0.0      20  \n",
       "4      NaN            vision64.com  2017-06-16  operating          0.0      20  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_main.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# df_g1 = df_main.groupby([ 'investor'],as_index = False)[['exit_scores']].sum()\n",
    "\n",
    "# num_investments = df_main.groupby([ 'investor'],as_index = False)[['clean_url']].count()\n",
    "# num_investments.head()\n",
    "\n",
    "# result = pd.merge(df_g1, num_investments, on=['investor', 'investor'])\n",
    "# result.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_g1 = df_main.groupby([ 'investor' ],as_index = True)[['exit_scores']].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lets look at the scores:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
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          "Skypoint Capital",
          "TPG Biotech",
          "ff Venture Capital",
          "Technology Partners",
          "EcoR1 Capital",
          "Rho Capital Partners",
          "Ontario Teachers' Pension Plan",
          "Claremont Creek Ventures",
          "Juniper Networks",
          "Pontifax",
          "Tech Coast Angels",
          "Kearny Venture Partners",
          "CF",
          "Northzone",
          "Draper Richards",
          "Norwest Mezzanine Partners",
          "Sevin Rosen Funds",
          "Draper Associates",
          "Sanderling Ventures",
          "Wellcome Trust",
          "Parkwalk Advisors Ltd",
          "Mediphase Venture Partners",
          "Comerica Bank",
          "Care Capital",
          "Canaccord Genuity Group",
          "Pappas Ventures",
          "Converge Venture Partners",
          "Evergreen Venture Partners",
          "Silver Lake Partners",
          "Artiman Ventures",
          "Invesco",
          "Forward Ventures",
          "Birchmere Ventures",
          "The Aurora Funds",
          "Mountain Group Capital",
          "Atomico",
          "Stanford University",
          "Real Ventures",
          "Fidelity Management and Research Company",
          "Lundbeckfonden Ventures",
          "Naval Ravikant",
          "Deerfield Capital Management",
          "Morado Venture Partners",
          "Viola Ventures",
          "OpenView",
          "Morningside Group",
          "FTVentures",
          "Agility Capital",
          "360 Capital Partners",
          "Novo Ventures",
          "Ziegler Meditech Equity Partners",
          "Aeris Capital",
          "Solstice Capital",
          "Thomas, McNerney & Partners",
          "Palomar Ventures",
          "Gemini Israel Ventures",
          "Pinnacle Ventures",
          "New Venture Partners",
          "Hatteras Venture Partners",
          "RiverVest",
          "Singtel Innov8",
          "BioMedPartners",
          "Kapor Capital",
          "Passport Capital",
          "Techstars Ventures",
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          "QVT Financial",
          "Asset Management Ventures (AMV)",
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          "PTV Healthcare Capital",
          "WPP Ventures",
          "RBC Venture Partners",
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          "Entrepreneurs Fund",
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          "Beacon Securities",
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          "CMEA Ventures",
          "China Development Industrial Bank (CDIB)",
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          "Newbury Ventures",
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          "Ardian",
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          "MVM Life Science Partners",
          "Pilot House Ventures",
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          "Barclays PLC",
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          "Key Venture Partners",
          "Funding Global Innovation",
          "Ascend Technology Ventures",
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          "MMV Financial",
          "Plug and Play",
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          "TIAA",
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          "Dharmesh Shah",
          "Boston Scientific",
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          "Omega Funds",
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          "Revolution",
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          "YJ Capital",
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          "Four Rivers Group",
          "AFSquare",
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          "Lighter Capital",
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          "Sony",
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          "Northern Light Venture Capital",
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          "FA Technology Ventures",
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          "Walden Venture Capital",
          "Joshua Schachter",
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          "Altimeter Capital",
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          "Fortissimo Capital",
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          "Mercury Fund",
          "Leapfrog Ventures",
          "Beringea",
          "Chris Sacca",
          "Phenomen Ventures",
          "Hikari Tsushin Group",
          "RPM Ventures",
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          "Plymouth Growth Partners",
          "Regal Funds Management",
          "Chase Capital Partners",
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          "Capricorn Investment Group",
          "Scott Banister",
          "Oracle Investment Management Inc.",
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          "Gold Hill Capital",
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          "Innoven Partners",
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          "Okapi Venture Capital",
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          "AVI Capital",
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          "MK Capital",
          "Partner Fund Management",
          "Digital Garage",
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          "Alexandria Venture",
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          "Cambrian Ventures",
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          "Telegraph Hill Partners",
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          "Gabriel Venture Partners",
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          "Horizon Ventures",
          "DoCoMo Capital",
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          "GlaxoSmithKline",
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          "Bloomberg Beta",
          "News Corp.",
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          "Roger Ehrenberg",
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          "Fluke Venture Partners",
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          "Benjamin Ling",
          "Coatue Management",
          "PROfounders Capital",
          "Chengwei Capital",
          "Atlantic Bridge",
          "Frontline Strategy",
          "Aspire Capital Partners LLC",
          "StageOne Ventures",
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          "Hadi Partovi",
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          "Amazon",
          "MidCap Financial",
          "Pelion Venture Partners",
          "Dafna Capital Management",
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          "Heliad Equity Partners GmbH & Co. KGaA",
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          "Bank of America",
          "Contour Venture Partners",
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          "Tullis Health Investors",
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          "Tako Ventures",
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          "William Blair",
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          "Tekla Capital Management",
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          "Lighthouse Capital Partners",
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          "Yaletown Partners",
          "Formula Ventures",
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          "NanoDimension",
          "EuclidSR Partners",
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          "Formative Ventures",
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          "Clark Landry",
          "Wing Venture Capital",
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          "Cipio Partners",
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          "Third Security",
          "Shlomo Kramer",
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          "Nippon Venture Capital",
          "Wells Fargo Capital Finance",
          "Cormark Securities Inc.",
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          "Arcturus Capital",
          "Arcus Ventures",
          "ArrowPath Venture Partners",
          "TD Capital",
          "East West Bank",
          "BlackRock",
          "Hambrecht & Quist Capital Management",
          "SCP Partners",
          "Whitney & Co.",
          "Ali Partovi",
          "Firelake Capital Management",
          "Vitruvian Partners",
          "Robert Bosch Venture Capital",
          "A Plus Finance",
          "Lansdowne Partners",
          "Wheatley Partners",
          "Weston Presidio Capital",
          "Wexford Capital",
          "Duff, Ackerman and Goodrich",
          "Reuters",
          "VeriSign",
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   "source": [
    "df_des = df_g1.sort_values('exit_scores', ascending=False)\n",
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    "                 xTitle='',\n",
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    "                 title='Best investors'), \n",
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  {
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       "<div id=\"00938c80-0891-499b-8882-f4c5561f385a\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"00938c80-0891-499b-8882-f4c5561f385a\", [{\"type\": \"bar\", \"x\": [167.0, 178.0, 182.0, 190.0, 193.0, 201.0, 214.0, 214.0, 216.0, 218.0, 221.0, 271.0, 273.0, 274.0, 313.0, 355.0, 380.0, 430.0, 497.0], \"y\": [\"Battery Ventures\", \"Silicon Valley Bank\", \"Index Ventures\", \"Foundation Capital\", \"Lightspeed Venture Partners\", \"OrbiMed\", \"Matrix Partners\", \"Draper Fisher Jurvetson (DFJ)\", \"Goldman Sachs\", \"Norwest Venture Partners - NVP\", \"Bessemer Venture Partners\", \"Benchmark\", \"Greylock Partners\", \"Venrock\", \"Kleiner Perkins Caufield & Byers\", \"Intel Capital\", \"Accel Partners\", \"New Enterprise Associates\", \"Sequoia Capital\"], \"orientation\": \"h\"}], {}, {\"showLink\": true, \"linkText\": \"Export to plot.ly\"})});</script>"
      ],
      "text/vnd.plotly.v1+html": [
       "<div id=\"00938c80-0891-499b-8882-f4c5561f385a\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"00938c80-0891-499b-8882-f4c5561f385a\", [{\"type\": \"bar\", \"x\": [167.0, 178.0, 182.0, 190.0, 193.0, 201.0, 214.0, 214.0, 216.0, 218.0, 221.0, 271.0, 273.0, 274.0, 313.0, 355.0, 380.0, 430.0, 497.0], \"y\": [\"Battery Ventures\", \"Silicon Valley Bank\", \"Index Ventures\", \"Foundation Capital\", \"Lightspeed Venture Partners\", \"OrbiMed\", \"Matrix Partners\", \"Draper Fisher Jurvetson (DFJ)\", \"Goldman Sachs\", \"Norwest Venture Partners - NVP\", \"Bessemer Venture Partners\", \"Benchmark\", \"Greylock Partners\", \"Venrock\", \"Kleiner Perkins Caufield & Byers\", \"Intel Capital\", \"Accel Partners\", \"New Enterprise Associates\", \"Sequoia Capital\"], \"orientation\": \"h\"}], {}, {\"showLink\": true, \"linkText\": \"Export to plot.ly\"})});</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plottest = df_des.reset_index()\n",
    "\n",
    "data = [go.Bar(\n",
    "            x=plottest.exit_scores[1:20].sort_values(),\n",
    "            y=plottest.investor[1:20].tolist()[::-1],\n",
    "            orientation = 'h'\n",
    ")]\n",
    "\n",
    "iplot(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "exit_scores    182.0\n",
       "Name: Index Ventures, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_des.loc['Index Ventures']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Top performing investors:\n",
    "\n",
    "\n",
    "By exploring the data it becomes obvious that not all the 44552 are actively investing. For instance, there are many investment firms who has only invested couple of times throughout their history. Thus, to reduce the noise and also identify who are the main competitors to Index Ventures, we can start looking at the top 201 investor firms.\n",
    "\n",
    "In this section, a second score is calculated by normalizing the “exit score” with the number of investments that each investment firm have made over the years. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "most = df_des[1:].copy()\n",
    "most = most.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(exit_scores    0.0\n",
       " dtype: float64, exit_scores    1.134587\n",
       " dtype: float64)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most.median(), most.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>exit_scores</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>44551.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.134587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.486841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-69.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>497.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        exit_scores\n",
       "count  44551.000000\n",
       "mean       1.134587\n",
       "std        8.486841\n",
       "min      -69.000000\n",
       "25%        0.000000\n",
       "50%        0.000000\n",
       "75%        0.000000\n",
       "max      497.000000"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "most.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(201, 1)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "limited_df = most[most.exit_scores>=44]\n",
    "limited_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "investor\n",
       " A. James and Alice B. Clark Foundation    1\n",
       " ACME Investments                          1\n",
       " AERIUM Analytics                          1\n",
       " AI Life Sciences Investments              1\n",
       " Abhijeet  Birewar                         2\n",
       "Name: clean_url, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_investments = df_main.groupby( ['investor'],as_index = True)['clean_url'].nunique()\n",
    "num_investments.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "result = pd.concat([limited_df ,num_investments], axis=1, join='inner')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((201, 2), (201, 1), (44552,))"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.shape, limited_df.shape, num_investments.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>exit_scores</th>\n",
       "      <th>clean_url</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>investor</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Sequoia Capital</th>\n",
       "      <td>497.0</td>\n",
       "      <td>731</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Enterprise Associates</th>\n",
       "      <td>430.0</td>\n",
       "      <td>695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Accel Partners</th>\n",
       "      <td>380.0</td>\n",
       "      <td>583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Intel Capital</th>\n",
       "      <td>355.0</td>\n",
       "      <td>718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kleiner Perkins Caufield &amp; Byers</th>\n",
       "      <td>313.0</td>\n",
       "      <td>441</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  exit_scores  clean_url\n",
       "investor                                                \n",
       "Sequoia Capital                         497.0        731\n",
       "New Enterprise Associates               430.0        695\n",
       "Accel Partners                          380.0        583\n",
       "Intel Capital                           355.0        718\n",
       "Kleiner Perkins Caufield & Byers        313.0        441"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "exit_scores    497.0\n",
       "clean_url      731.0\n",
       "Name: Sequoia Capital, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.loc['Sequoia Capital'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def norm (x,y):\n",
    "    return (x/y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "result['norm_clean_url'] = np.vectorize(norm)(result['exit_scores'],result['clean_url'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>investor</th>\n",
       "      <th>exit_scores</th>\n",
       "      <th>clean_url</th>\n",
       "      <th>norm_clean_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sequoia Capital</td>\n",
       "      <td>497.0</td>\n",
       "      <td>731</td>\n",
       "      <td>0.679891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>New Enterprise Associates</td>\n",
       "      <td>430.0</td>\n",
       "      <td>695</td>\n",
       "      <td>0.618705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Accel Partners</td>\n",
       "      <td>380.0</td>\n",
       "      <td>583</td>\n",
       "      <td>0.651801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Intel Capital</td>\n",
       "      <td>355.0</td>\n",
       "      <td>718</td>\n",
       "      <td>0.494429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kleiner Perkins Caufield &amp; Byers</td>\n",
       "      <td>313.0</td>\n",
       "      <td>441</td>\n",
       "      <td>0.709751</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           investor  exit_scores  clean_url  norm_clean_url\n",
       "0                   Sequoia Capital        497.0        731        0.679891\n",
       "1         New Enterprise Associates        430.0        695        0.618705\n",
       "2                    Accel Partners        380.0        583        0.651801\n",
       "3                     Intel Capital        355.0        718        0.494429\n",
       "4  Kleiner Perkins Caufield & Byers        313.0        441        0.709751"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result= result.reset_index()\n",
    "result.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "data": [
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         "x": [
          "Skyline Ventures",
          "Aisling Capital",
          "Boulder Ventures",
          "Clarus Ventures",
          "Brookside Capital",
          "HealthCap",
          "Domain Associates",
          "Alta Partners",
          "Employee Stock Option Fund (ESO Fund)",
          "Auriga Partners",
          "Third Rock Ventures",
          "Lilly Ventures",
          "Chrys Capital",
          "Rock Springs Capital",
          "Frazier Healthcare Partners",
          "MPM Capital",
          "Abingworth",
          "RA Capital Management",
          "Perceptive Advisors",
          "Vivo Capital",
          "OrbiMed",
          "5AM Ventures",
          "Novak Biddle Venture Partners",
          "Sutter Hill Ventures",
          "Crosspoint Venture Partners",
          "Deerfield",
          "HealthCare Ventures",
          "T. Rowe Price",
          "Sofinnova Ventures",
          "Fidelity Ventures",
          "Cormorant Asset Management",
          "ARCH Venture Partners",
          "Flagship Pioneering",
          "CRG L.P.",
          "HWVP, Hummer Winblad Venture Partners",
          "St. Paul Venture Capital",
          "Labrador Ventures",
          "Venrock",
          "Steamboat Ventures",
          "Mohr Davidow Ventures",
          "Novo A/S",
          "Crescendo Ventures",
          "El Dorado Ventures",
          "Sapphire Ventures",
          "Benchmark",
          "Delphi Ventures",
          "Split Rock Partners",
          "Kodiak Venture Partners",
          "Meritech Capital Partners",
          "Novartis Venture Fund",
          "Focus Ventures",
          "Oxford Finance Corporation",
          "Rembrandt Venture Partners",
          "Investor Growth Capital Limited",
          "Lehman Brothers",
          "Versant Ventures",
          "New Leaf Venture Partners",
          "Gimv",
          "Three Arch Partners",
          "Viola Credit",
          "Longworth Venture Partners",
          "Integral Capital Partners",
          "Austin Ventures",
          "Worldview Technology Partners",
          "Sigma Partners",
          "Apax Partners",
          "North Bridge Venture Partners & Growth Equity",
          "Silverton Partners",
          "DAG Ventures",
          "Bay Partners",
          "Avalon Ventures",
          "Life Sciences Partners",
          "Matrix Partners",
          "InterWest Partners",
          "Alloy Ventures",
          "Intersouth Partners",
          "Icon Ventures",
          "Norwest Venture Partners - NVP",
          "Trinity Ventures",
          "Scale Venture Partners",
          "JPMorgan Partners (JPMP)",
          "Flybridge Capital Partners",
          "IVP (Institutional Venture Partners)",
          "TCV",
          "Columbia Capital",
          "SR One",
          "Hercules Capital, Inc.",
          "Union Square Ventures",
          "HarbourVest Partners",
          "Advanced Technology Ventures",
          "3i Group",
          "Foundation Capital",
          "Relay Ventures",
          "Greylock Partners",
          "Greenspring Associates",
          "Hearst Ventures",
          "Polaris Partners",
          "Summit Partners",
          "Adams Street Partners",
          "SV Health Investors",
          "JMI Equity",
          "Madrona Venture Group",
          "Walden International",
          "Osage University Partners",
          "Giza Venture Capital",
          "Atlas Venture",
          "Tenaya Capital",
          "Fidelity Investments",
          "Scottish Equity Partners (SEP)",
          "August Capital",
          "NGP Capital",
          "Northgate Capital",
          "Johnson & Johnson Development Corporation",
          "Kleiner Perkins Caufield & Byers",
          "Canaan Partners",
          "Morgenthaler Ventures",
          "GGV Capital",
          "Motorola Solutions Venture Capital",
          "Lightspeed Venture Partners",
          "Storm Ventures",
          "Sequoia Capital",
          "Menlo Ventures",
          "Norwest Equity Partners (NEP)",
          "Pitango Venture Capital",
          "Sofinnova Partners",
          "Globespan Capital Partners",
          "U.S. Venture Partners (USVP)",
          "Accel Partners",
          "Oak Investment Partners",
          "Wellington Partners",
          "F-Prime Capital Partners",
          "Cisco",
          "Tiger Global Management",
          "Highland Capital Partners",
          "Edison Partners",
          "Omnes Capital",
          "New Enterprise Associates",
          "Mayfield Fund",
          "Sierra Ventures",
          "Battery Ventures",
          "Pequot Capital",
          "Warburg Pincus",
          "GE Capital",
          "TA Associates",
          "General Atlantic",
          "Morgan Stanley",
          "Bain Capital Ventures",
          "Bessemer Venture Partners",
          "Draper Fisher Jurvetson (DFJ)",
          "Insight Venture Partners",
          "Idinvest Partners",
          "Vulcan Capital",
          "HV Holtzbrinck Ventures",
          "Mitsui Global Investment",
          "Vertex Ventures",
          "VantagePoint Capital Partners",
          "Redpoint",
          "Index Ventures",
          "SoftBank Capital",
          "Temasek Holdings",
          "General Catalyst",
          "Ignition Partners",
          "Goldman Sachs",
          "In-Q-Tel",
          "Intel Capital",
          "Shasta Ventures",
          "CRV",
          "Uncork Capital",
          "Allen & Company",
          "Felicis Ventures",
          "KKR & Co. (Kohlberg Kravis Roberts & Co.)",
          "Silicon Valley Bank",
          "First Round Capital",
          "DCM Ventures",
          "Spark Capital",
          "Balderton Capital",
          "SAIF Partners",
          "Samsung Ventures",
          "IDG Capital Partners",
          "True Ventures",
          "Partech Ventures",
          "Upfront Ventures",
          "Khosla Ventures",
          "Crosslink Capital",
          "Foundry Group",
          "Comcast Ventures",
          "RRE Ventures",
          "Qualcomm Ventures",
          "Salesforce Ventures",
          "BDC Venture Capital",
          "Brand Capital",
          "Founders Fund",
          "Andreessen Horowitz",
          "Greycroft",
          "FLOODGATE",
          "NYSERDA",
          "Founder Collective",
          "GV",
          "Great Oaks Venture Capital",
          "SV Angel"
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0.6666666666666666, 0.6585365853658537, 0.6518010291595198, 0.6463414634146342, 0.6436781609195402, 0.6395348837209303, 0.6386554621848739, 0.6356589147286822, 0.6335078534031413, 0.6293103448275862, 0.6190476190476191, 0.6187050359712231, 0.6153846153846154, 0.6129032258064516, 0.6028880866425993, 0.6027397260273972, 0.6013986013986014, 0.6, 0.5949367088607594, 0.59375, 0.5869565217391305, 0.5828220858895705, 0.5785340314136126, 0.5768194070080862, 0.5743589743589743, 0.5700934579439252, 0.569620253164557, 0.5683453237410072, 0.5617977528089888, 0.5578231292517006, 0.5447154471544715, 0.532258064516129, 0.5244956772334294, 0.52046783625731, 0.5188679245283019, 0.5137931034482759, 0.5081967213114754, 0.5058548009367682, 0.5039370078740157, 0.49442896935933145, 0.4878048780487805, 0.4788732394366197, 0.46808510638297873, 0.45918367346938777, 0.45454545454545453, 0.4536082474226804, 0.4506329113924051, 0.44816053511705684, 0.4375, 0.40789473684210525, 0.40310077519379844, 0.4017857142857143, 0.4017857142857143, 0.3686868686868687, 0.36585365853658536, 0.3522727272727273, 0.35, 0.3472222222222222, 0.3372093023255814, 0.3356643356643357, 0.33540372670807456, 0.3317757009345794, 0.3316582914572864, 0.32407407407407407, 0.3021978021978022, 0.2944915254237288, 0.2895927601809955, 0.28732394366197184, 0.2863636363636364, 0.2822085889570552, 0.28125, 0.2623762376237624, 0.24079320113314448, 0.18072289156626506, 0.17061611374407584], \"name\": \"norm_clean_url\", \"text\": \"\", \"marker\": {\"color\": \"rgba(255, 153, 51, 0.6)\", \"line\": {\"color\": \"rgba(255, 153, 51, 1.0)\", \"width\": 1}}, \"orientation\": \"v\"}], {\"legend\": {\"bgcolor\": \"#F5F6F9\", \"font\": {\"color\": \"#4D5663\"}}, \"paper_bgcolor\": \"#F5F6F9\", \"plot_bgcolor\": \"#F5F6F9\", \"yaxis1\": {\"tickfont\": {\"color\": \"#4D5663\"}, \"gridcolor\": \"#E1E5ED\", \"titlefont\": {\"color\": \"#4D5663\"}, \"zerolinecolor\": \"#E1E5ED\", \"showgrid\": true, \"title\": \"quality score\"}, \"xaxis1\": {\"tickfont\": {\"color\": \"#4D5663\"}, \"gridcolor\": \"#E1E5ED\", \"titlefont\": {\"color\": \"#4D5663\"}, \"zerolinecolor\": \"#E1E5ED\", \"showgrid\": true, \"title\": \"\"}, \"titlefont\": {\"color\": \"#4D5663\"}, \"title\": \"Best investors\"}, {\"showLink\": true, \"linkText\": \"Export to plot.ly\"})});</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = result.groupby([ 'investor'],as_index = True)[['norm_clean_url']].sum()\n",
    "df_des = plot.sort_values('norm_clean_url', ascending=False)\n",
    "\n",
    "iplot(df_des[:200].iplot(asFigure=True,\n",
    "                 kind='bar',\n",
    "                 xTitle='',\n",
    "                 yTitle='quality score',\n",
    "                 title='Best investors'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>norm_clean_url</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>investor</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Skyline Ventures</th>\n",
       "      <td>1.961538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aisling Capital</th>\n",
       "      <td>1.902439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Boulder Ventures</th>\n",
       "      <td>1.853659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clarus Ventures</th>\n",
       "      <td>1.818182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brookside Capital</th>\n",
       "      <td>1.806452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HealthCap</th>\n",
       "      <td>1.781250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Domain Associates</th>\n",
       "      <td>1.705882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alta Partners</th>\n",
       "      <td>1.691358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Employee Stock Option Fund (ESO Fund)</th>\n",
       "      <td>1.657143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Auriga Partners</th>\n",
       "      <td>1.648148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Third Rock Ventures</th>\n",
       "      <td>1.609756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lilly Ventures</th>\n",
       "      <td>1.607143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chrys Capital</th>\n",
       "      <td>1.605263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rock Springs Capital</th>\n",
       "      <td>1.588235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frazier Healthcare Partners</th>\n",
       "      <td>1.578125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPM Capital</th>\n",
       "      <td>1.538462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abingworth</th>\n",
       "      <td>1.520000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RA Capital Management</th>\n",
       "      <td>1.468750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Perceptive Advisors</th>\n",
       "      <td>1.441176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vivo Capital</th>\n",
       "      <td>1.395349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OrbiMed</th>\n",
       "      <td>1.340000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5AM Ventures</th>\n",
       "      <td>1.320755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Novak Biddle Venture Partners</th>\n",
       "      <td>1.304348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sutter Hill Ventures</th>\n",
       "      <td>1.289474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crosspoint Venture Partners</th>\n",
       "      <td>1.282609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Deerfield</th>\n",
       "      <td>1.277778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HealthCare Ventures</th>\n",
       "      <td>1.275000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T. Rowe Price</th>\n",
       "      <td>1.257143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sofinnova Ventures</th>\n",
       "      <td>1.244898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fidelity Ventures</th>\n",
       "      <td>1.239130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Silicon Valley Bank</th>\n",
       "      <td>0.450633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>First Round Capital</th>\n",
       "      <td>0.448161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DCM Ventures</th>\n",
       "      <td>0.437500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Spark Capital</th>\n",
       "      <td>0.407895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Balderton Capital</th>\n",
       "      <td>0.403101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAIF Partners</th>\n",
       "      <td>0.401786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samsung Ventures</th>\n",
       "      <td>0.401786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IDG Capital Partners</th>\n",
       "      <td>0.368687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>True Ventures</th>\n",
       "      <td>0.365854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Partech Ventures</th>\n",
       "      <td>0.352273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Upfront Ventures</th>\n",
       "      <td>0.350000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Khosla Ventures</th>\n",
       "      <td>0.347222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crosslink Capital</th>\n",
       "      <td>0.337209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Foundry Group</th>\n",
       "      <td>0.335664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Comcast Ventures</th>\n",
       "      <td>0.335404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RRE Ventures</th>\n",
       "      <td>0.331776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Qualcomm Ventures</th>\n",
       "      <td>0.331658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Salesforce Ventures</th>\n",
       "      <td>0.324074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BDC Venture Capital</th>\n",
       "      <td>0.302198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brand Capital</th>\n",
       "      <td>0.294492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Founders Fund</th>\n",
       "      <td>0.289593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andreessen Horowitz</th>\n",
       "      <td>0.287324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Greycroft</th>\n",
       "      <td>0.286364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLOODGATE</th>\n",
       "      <td>0.282209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NYSERDA</th>\n",
       "      <td>0.281250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Founder Collective</th>\n",
       "      <td>0.262376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GV</th>\n",
       "      <td>0.240793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Great Oaks Venture Capital</th>\n",
       "      <td>0.180723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SV Angel</th>\n",
       "      <td>0.170616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500 Startups</th>\n",
       "      <td>0.036842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>201 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       norm_clean_url\n",
       "investor                                             \n",
       "Skyline Ventures                             1.961538\n",
       "Aisling Capital                              1.902439\n",
       "Boulder Ventures                             1.853659\n",
       "Clarus Ventures                              1.818182\n",
       "Brookside Capital                            1.806452\n",
       "HealthCap                                    1.781250\n",
       "Domain Associates                            1.705882\n",
       "Alta Partners                                1.691358\n",
       "Employee Stock Option Fund (ESO Fund)        1.657143\n",
       "Auriga Partners                              1.648148\n",
       "Third Rock Ventures                          1.609756\n",
       "Lilly Ventures                               1.607143\n",
       "Chrys Capital                                1.605263\n",
       "Rock Springs Capital                         1.588235\n",
       "Frazier Healthcare Partners                  1.578125\n",
       "MPM Capital                                  1.538462\n",
       "Abingworth                                   1.520000\n",
       "RA Capital Management                        1.468750\n",
       "Perceptive Advisors                          1.441176\n",
       "Vivo Capital                                 1.395349\n",
       "OrbiMed                                      1.340000\n",
       "5AM Ventures                                 1.320755\n",
       "Novak Biddle Venture Partners                1.304348\n",
       "Sutter Hill Ventures                         1.289474\n",
       "Crosspoint Venture Partners                  1.282609\n",
       "Deerfield                                    1.277778\n",
       "HealthCare Ventures                          1.275000\n",
       "T. Rowe Price                                1.257143\n",
       "Sofinnova Ventures                           1.244898\n",
       "Fidelity Ventures                            1.239130\n",
       "...                                               ...\n",
       "Silicon Valley Bank                          0.450633\n",
       "First Round Capital                          0.448161\n",
       "DCM Ventures                                 0.437500\n",
       "Spark Capital                                0.407895\n",
       "Balderton Capital                            0.403101\n",
       "SAIF Partners                                0.401786\n",
       "Samsung Ventures                             0.401786\n",
       "IDG Capital Partners                         0.368687\n",
       "True Ventures                                0.365854\n",
       "Partech Ventures                             0.352273\n",
       "Upfront Ventures                             0.350000\n",
       "Khosla Ventures                              0.347222\n",
       "Crosslink Capital                            0.337209\n",
       "Foundry Group                                0.335664\n",
       "Comcast Ventures                             0.335404\n",
       "RRE Ventures                                 0.331776\n",
       "Qualcomm Ventures                            0.331658\n",
       "Salesforce Ventures                          0.324074\n",
       "BDC Venture Capital                          0.302198\n",
       "Brand Capital                                0.294492\n",
       "Founders Fund                                0.289593\n",
       "Andreessen Horowitz                          0.287324\n",
       "Greycroft                                    0.286364\n",
       "FLOODGATE                                    0.282209\n",
       "NYSERDA                                      0.281250\n",
       "Founder Collective                           0.262376\n",
       "GV                                           0.240793\n",
       "Great Oaks Venture Capital                   0.180723\n",
       "SV Angel                                     0.170616\n",
       "500 Startups                                 0.036842\n",
       "\n",
       "[201 rows x 1 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_des"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>norm_clean_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>201.000000</td>\n",
       "    </tr>\n",
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       "      <th>mean</th>\n",
       "      <td>0.842250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.393281</td>\n",
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       "      <th>min</th>\n",
       "      <td>0.036842</td>\n",
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       "      <th>25%</th>\n",
       "      <td>0.570093</td>\n",
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       "      <th>50%</th>\n",
       "      <td>0.784615</td>\n",
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       "      <th>75%</th>\n",
       "      <td>1.084746</td>\n",
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       "      <th>max</th>\n",
       "      <td>1.961538</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       norm_clean_url\n",
       "count      201.000000\n",
       "mean         0.842250\n",
       "std          0.393281\n",
       "min          0.036842\n",
       "25%          0.570093\n",
       "50%          0.784615\n",
       "75%          1.084746\n",
       "max          1.961538"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_des.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "norm_clean_url    0.679891\n",
       "Name: Sequoia Capital, dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_des.loc['Sequoia Capital']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>investor</th>\n",
       "      <th>exit_scores</th>\n",
       "      <th>clean_url</th>\n",
       "      <th>norm_clean_url</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Sequoia Capital</td>\n",
       "      <td>497.0</td>\n",
       "      <td>731</td>\n",
       "      <td>0.679891</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "          investor  exit_scores  clean_url  norm_clean_url\n",
       "0  Sequoia Capital        497.0        731        0.679891"
      ]
     },
     "execution_count": 34,
     "metadata": {},
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   "source": [
    "result[result.investor == 'Sequoia Capital']"
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  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "norm_clean_url    0.524496\n",
       "Name: Index Ventures, dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_des.loc['Index Ventures']"
   ]
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   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Index Ventures</td>\n",
       "      <td>182.0</td>\n",
       "      <td>347</td>\n",
       "      <td>0.524496</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "          investor  exit_scores  clean_url  norm_clean_url\n",
       "16  Index Ventures        182.0        347        0.524496"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
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   "execution_count": null,
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   "outputs": [],
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