{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import what we need for this analysis of historical trading multiples for selected SAAS companies\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from quantopian.pipeline import Pipeline, CustomFactor\n",
    "from quantopian.pipeline.data import Fundamentals\n",
    "from quantopian.research import run_pipeline\n",
    "\n",
    "# Create our customer ticker list\n",
    "symbols = Fundamentals.symbol.latest.element_of(\"\"\"\n",
    "    TEAM SEND PAYC WDAY NOW HUBS ZEN RNG APPF QLYS CRM PCTY PFPT RP LOGM INST YEXT MIME ADBE MB QTWO\n",
    "    OKTA NEWR FIVN COUP BOX\n",
    "\"\"\".split())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>ev_ttm_rev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2018-01-02 00:00:00+00:00</th>\n",
       "      <th>Equity(114 [ADBE])</th>\n",
       "      <td>11.966616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(26401 [CRM])</th>\n",
       "      <td>7.294119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(38560 [LOGM])</th>\n",
       "      <td>7.179605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(40030 [RP])</th>\n",
       "      <td>6.262215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(42825 [PFPT])</th>\n",
       "      <td>8.188433</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                ev_ttm_rev\n",
       "2018-01-02 00:00:00+00:00 Equity(114 [ADBE])     11.966616\n",
       "                          Equity(26401 [CRM])     7.294119\n",
       "                          Equity(38560 [LOGM])    7.179605\n",
       "                          Equity(40030 [RP])      6.262215\n",
       "                          Equity(42825 [PFPT])    8.188433"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "class TrailingTwelveMonths(CustomFactor):\n",
    "    window_length=400\n",
    "    window_safe = True\n",
    "    mask=symbols\n",
    "    outputs=\"\"\"\n",
    "        factor\n",
    "        asof_date\n",
    "        \"\"\".split()\n",
    "    def compute(self, today, assets, out, values, dates):\n",
    "        out.factor[:] = [\n",
    "            (v[d + np.timedelta64(52, 'W') > d[-1]])[\n",
    "                np.unique(\n",
    "                    d[d + np.timedelta64(52, 'W') > d[-1]],\n",
    "                    return_index=True\n",
    "                )[1]\n",
    "            ].sum()\n",
    "            for v, d in zip(values.T, dates.T)\n",
    "        ]\n",
    "        out.asof_date[:] = dates[-1]\n",
    "def make_pipeline():\n",
    "    (\n",
    "        total_revenue_ttm,\n",
    "        total_revenue_ttm_asof_date\n",
    "    ) = TrailingTwelveMonths(\n",
    "        inputs=[\n",
    "            Fundamentals.total_revenue,\n",
    "            Fundamentals.total_revenue_asof_date,\n",
    "        ]\n",
    "    )\n",
    "    enterprise_value = Fundamentals.enterprise_value.latest\n",
    "    market_cap = Fundamentals.market_cap.latest\n",
    "    enterprise_value_ttm_rev = Fundamentals.enterprise_value.latest / total_revenue_ttm\n",
    "    \n",
    "    return Pipeline(\n",
    "        columns={\n",
    "            #'ent_value': enterprise_value,\n",
    "            #'mkt_value': MarketCap(),\n",
    "            'ev_ttm_rev': enterprise_value_ttm_rev\n",
    "            #'total_revenue_ttm': total_revenue_ttm,\n",
    "            #'total_revenue_ttm_asof_date': total_revenue_ttm_asof_date\n",
    "        },\n",
    "        screen=symbols\n",
    "    )\n",
    "df = run_pipeline(make_pipeline(), '2018-1-01', '2019-1-24')\n",
    "#df['total_revenue_ttm_asof_date'] = df['total_revenue_ttm_asof_date'].astype('datetime64[ns]')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"21\" halign=\"left\">ev_ttm_rev</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Equity(114 [ADBE])</th>\n",
       "      <th>Equity(26401 [CRM])</th>\n",
       "      <th>Equity(38560 [LOGM])</th>\n",
       "      <th>Equity(40030 [RP])</th>\n",
       "      <th>Equity(42825 [PFPT])</th>\n",
       "      <th>Equity(43127 [NOW])</th>\n",
       "      <th>Equity(43454 [QLYS])</th>\n",
       "      <th>Equity(43510 [WDAY])</th>\n",
       "      <th>Equity(45521 [RNG])</th>\n",
       "      <th>Equity(46569 [PCTY])</th>\n",
       "      <th>...</th>\n",
       "      <th>Equity(48486 [BOX])</th>\n",
       "      <th>Equity(49156 [MB])</th>\n",
       "      <th>Equity(49193 [APPF])</th>\n",
       "      <th>Equity(49594 [INST])</th>\n",
       "      <th>Equity(49606 [MIME])</th>\n",
       "      <th>Equity(49655 [TEAM])</th>\n",
       "      <th>Equity(50350 [COUP])</th>\n",
       "      <th>Equity(50758 [OKTA])</th>\n",
       "      <th>Equity(50781 [YEXT])</th>\n",
       "      <th>Equity(51455 [SEND])</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-02 00:00:00+00:00</th>\n",
       "      <td>11.966616</td>\n",
       "      <td>7.294119</td>\n",
       "      <td>7.179605</td>\n",
       "      <td>6.262215</td>\n",
       "      <td>8.188433</td>\n",
       "      <td>12.414835</td>\n",
       "      <td>8.848112</td>\n",
       "      <td>9.837853</td>\n",
       "      <td>7.672582</td>\n",
       "      <td>7.517804</td>\n",
       "      <td>...</td>\n",
       "      <td>5.814029</td>\n",
       "      <td>7.081477</td>\n",
       "      <td>10.197639</td>\n",
       "      <td>6.384513</td>\n",
       "      <td>7.004518</td>\n",
       "      <td>14.566147</td>\n",
       "      <td>8.765207</td>\n",
       "      <td>10.329181</td>\n",
       "      <td>6.233919</td>\n",
       "      <td>18.622845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:00:00+00:00</th>\n",
       "      <td>12.141677</td>\n",
       "      <td>7.452802</td>\n",
       "      <td>7.255172</td>\n",
       "      <td>6.399834</td>\n",
       "      <td>8.500690</td>\n",
       "      <td>12.545408</td>\n",
       "      <td>9.149557</td>\n",
       "      <td>10.012579</td>\n",
       "      <td>7.572878</td>\n",
       "      <td>7.612387</td>\n",
       "      <td>...</td>\n",
       "      <td>5.919104</td>\n",
       "      <td>7.176996</td>\n",
       "      <td>10.121590</td>\n",
       "      <td>6.436178</td>\n",
       "      <td>6.890895</td>\n",
       "      <td>15.089600</td>\n",
       "      <td>9.025883</td>\n",
       "      <td>10.704129</td>\n",
       "      <td>6.129888</td>\n",
       "      <td>19.273771</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  ev_ttm_rev                      \\\n",
       "                          Equity(114 [ADBE]) Equity(26401 [CRM])   \n",
       "2018-01-02 00:00:00+00:00          11.966616            7.294119   \n",
       "2018-01-03 00:00:00+00:00          12.141677            7.452802   \n",
       "\n",
       "                                                                   \\\n",
       "                          Equity(38560 [LOGM]) Equity(40030 [RP])   \n",
       "2018-01-02 00:00:00+00:00             7.179605           6.262215   \n",
       "2018-01-03 00:00:00+00:00             7.255172           6.399834   \n",
       "\n",
       "                                                                    \\\n",
       "                          Equity(42825 [PFPT]) Equity(43127 [NOW])   \n",
       "2018-01-02 00:00:00+00:00             8.188433           12.414835   \n",
       "2018-01-03 00:00:00+00:00             8.500690           12.545408   \n",
       "\n",
       "                                                                     \\\n",
       "                          Equity(43454 [QLYS]) Equity(43510 [WDAY])   \n",
       "2018-01-02 00:00:00+00:00             8.848112             9.837853   \n",
       "2018-01-03 00:00:00+00:00             9.149557            10.012579   \n",
       "\n",
       "                                                                    \\\n",
       "                          Equity(45521 [RNG]) Equity(46569 [PCTY])   \n",
       "2018-01-02 00:00:00+00:00            7.672582             7.517804   \n",
       "2018-01-03 00:00:00+00:00            7.572878             7.612387   \n",
       "\n",
       "                                  ...                               \\\n",
       "                                  ...          Equity(48486 [BOX])   \n",
       "2018-01-02 00:00:00+00:00         ...                     5.814029   \n",
       "2018-01-03 00:00:00+00:00         ...                     5.919104   \n",
       "\n",
       "                                                                   \\\n",
       "                          Equity(49156 [MB]) Equity(49193 [APPF])   \n",
       "2018-01-02 00:00:00+00:00           7.081477            10.197639   \n",
       "2018-01-03 00:00:00+00:00           7.176996            10.121590   \n",
       "\n",
       "                                                                     \\\n",
       "                          Equity(49594 [INST]) Equity(49606 [MIME])   \n",
       "2018-01-02 00:00:00+00:00             6.384513             7.004518   \n",
       "2018-01-03 00:00:00+00:00             6.436178             6.890895   \n",
       "\n",
       "                                                                     \\\n",
       "                          Equity(49655 [TEAM]) Equity(50350 [COUP])   \n",
       "2018-01-02 00:00:00+00:00            14.566147             8.765207   \n",
       "2018-01-03 00:00:00+00:00            15.089600             9.025883   \n",
       "\n",
       "                                                                     \\\n",
       "                          Equity(50758 [OKTA]) Equity(50781 [YEXT])   \n",
       "2018-01-02 00:00:00+00:00            10.329181             6.233919   \n",
       "2018-01-03 00:00:00+00:00            10.704129             6.129888   \n",
       "\n",
       "                                                \n",
       "                          Equity(51455 [SEND])  \n",
       "2018-01-02 00:00:00+00:00            18.622845  \n",
       "2018-01-03 00:00:00+00:00            19.273771  \n",
       "\n",
       "[2 rows x 26 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# unstack the dataframe to create tickers as columns\n",
    "new_df = df.unstack()\n",
    "new_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Equity(114 [ADBE])</th>\n",
       "      <th>Equity(26401 [CRM])</th>\n",
       "      <th>Equity(38560 [LOGM])</th>\n",
       "      <th>Equity(40030 [RP])</th>\n",
       "      <th>Equity(42825 [PFPT])</th>\n",
       "      <th>Equity(43127 [NOW])</th>\n",
       "      <th>Equity(43454 [QLYS])</th>\n",
       "      <th>Equity(43510 [WDAY])</th>\n",
       "      <th>Equity(45521 [RNG])</th>\n",
       "      <th>Equity(46569 [PCTY])</th>\n",
       "      <th>...</th>\n",
       "      <th>Equity(48486 [BOX])</th>\n",
       "      <th>Equity(49156 [MB])</th>\n",
       "      <th>Equity(49193 [APPF])</th>\n",
       "      <th>Equity(49594 [INST])</th>\n",
       "      <th>Equity(49606 [MIME])</th>\n",
       "      <th>Equity(49655 [TEAM])</th>\n",
       "      <th>Equity(50350 [COUP])</th>\n",
       "      <th>Equity(50758 [OKTA])</th>\n",
       "      <th>Equity(50781 [YEXT])</th>\n",
       "      <th>Equity(51455 [SEND])</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-02 00:00:00+00:00</th>\n",
       "      <td>11.966616</td>\n",
       "      <td>7.294119</td>\n",
       "      <td>7.179605</td>\n",
       "      <td>6.262215</td>\n",
       "      <td>8.188433</td>\n",
       "      <td>12.414835</td>\n",
       "      <td>8.848112</td>\n",
       "      <td>9.837853</td>\n",
       "      <td>7.672582</td>\n",
       "      <td>7.517804</td>\n",
       "      <td>...</td>\n",
       "      <td>5.814029</td>\n",
       "      <td>7.081477</td>\n",
       "      <td>10.197639</td>\n",
       "      <td>6.384513</td>\n",
       "      <td>7.004518</td>\n",
       "      <td>14.566147</td>\n",
       "      <td>8.765207</td>\n",
       "      <td>10.329181</td>\n",
       "      <td>6.233919</td>\n",
       "      <td>18.622845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:00:00+00:00</th>\n",
       "      <td>12.141677</td>\n",
       "      <td>7.452802</td>\n",
       "      <td>7.255172</td>\n",
       "      <td>6.399834</td>\n",
       "      <td>8.500690</td>\n",
       "      <td>12.545408</td>\n",
       "      <td>9.149557</td>\n",
       "      <td>10.012579</td>\n",
       "      <td>7.572878</td>\n",
       "      <td>7.612387</td>\n",
       "      <td>...</td>\n",
       "      <td>5.919104</td>\n",
       "      <td>7.176996</td>\n",
       "      <td>10.121590</td>\n",
       "      <td>6.436178</td>\n",
       "      <td>6.890895</td>\n",
       "      <td>15.089600</td>\n",
       "      <td>9.025883</td>\n",
       "      <td>10.704129</td>\n",
       "      <td>6.129888</td>\n",
       "      <td>19.273771</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Equity(114 [ADBE])  Equity(26401 [CRM])  \\\n",
       "2018-01-02 00:00:00+00:00           11.966616             7.294119   \n",
       "2018-01-03 00:00:00+00:00           12.141677             7.452802   \n",
       "\n",
       "                           Equity(38560 [LOGM])  Equity(40030 [RP])  \\\n",
       "2018-01-02 00:00:00+00:00              7.179605            6.262215   \n",
       "2018-01-03 00:00:00+00:00              7.255172            6.399834   \n",
       "\n",
       "                           Equity(42825 [PFPT])  Equity(43127 [NOW])  \\\n",
       "2018-01-02 00:00:00+00:00              8.188433            12.414835   \n",
       "2018-01-03 00:00:00+00:00              8.500690            12.545408   \n",
       "\n",
       "                           Equity(43454 [QLYS])  Equity(43510 [WDAY])  \\\n",
       "2018-01-02 00:00:00+00:00              8.848112              9.837853   \n",
       "2018-01-03 00:00:00+00:00              9.149557             10.012579   \n",
       "\n",
       "                           Equity(45521 [RNG])  Equity(46569 [PCTY])  \\\n",
       "2018-01-02 00:00:00+00:00             7.672582              7.517804   \n",
       "2018-01-03 00:00:00+00:00             7.572878              7.612387   \n",
       "\n",
       "                                   ...           Equity(48486 [BOX])  \\\n",
       "2018-01-02 00:00:00+00:00          ...                      5.814029   \n",
       "2018-01-03 00:00:00+00:00          ...                      5.919104   \n",
       "\n",
       "                           Equity(49156 [MB])  Equity(49193 [APPF])  \\\n",
       "2018-01-02 00:00:00+00:00            7.081477             10.197639   \n",
       "2018-01-03 00:00:00+00:00            7.176996             10.121590   \n",
       "\n",
       "                           Equity(49594 [INST])  Equity(49606 [MIME])  \\\n",
       "2018-01-02 00:00:00+00:00              6.384513              7.004518   \n",
       "2018-01-03 00:00:00+00:00              6.436178              6.890895   \n",
       "\n",
       "                           Equity(49655 [TEAM])  Equity(50350 [COUP])  \\\n",
       "2018-01-02 00:00:00+00:00             14.566147              8.765207   \n",
       "2018-01-03 00:00:00+00:00             15.089600              9.025883   \n",
       "\n",
       "                           Equity(50758 [OKTA])  Equity(50781 [YEXT])  \\\n",
       "2018-01-02 00:00:00+00:00             10.329181              6.233919   \n",
       "2018-01-03 00:00:00+00:00             10.704129              6.129888   \n",
       "\n",
       "                           Equity(51455 [SEND])  \n",
       "2018-01-02 00:00:00+00:00             18.622845  \n",
       "2018-01-03 00:00:00+00:00             19.273771  \n",
       "\n",
       "[2 rows x 26 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# eliminate multi-index columns\n",
    "new_df.columns = new_df.columns.droplevel()\n",
    "new_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 267 entries, 2018-01-02 to 2019-01-24\n",
      "Data columns (total 26 columns):\n",
      "Equity(114 [ADBE])      267 non-null float64\n",
      "Equity(26401 [CRM])     267 non-null float64\n",
      "Equity(38560 [LOGM])    267 non-null float64\n",
      "Equity(40030 [RP])      267 non-null float64\n",
      "Equity(42825 [PFPT])    267 non-null float64\n",
      "Equity(43127 [NOW])     267 non-null float64\n",
      "Equity(43454 [QLYS])    267 non-null float64\n",
      "Equity(43510 [WDAY])    267 non-null float64\n",
      "Equity(45521 [RNG])     267 non-null float64\n",
      "Equity(46569 [PCTY])    267 non-null float64\n",
      "Equity(46578 [QTWO])    267 non-null float64\n",
      "Equity(46695 [FIVN])    267 non-null float64\n",
      "Equity(46744 [PAYC])    267 non-null float64\n",
      "Equity(46918 [ZEN])     267 non-null float64\n",
      "Equity(47872 [HUBS])    267 non-null float64\n",
      "Equity(48253 [NEWR])    267 non-null float64\n",
      "Equity(48486 [BOX])     267 non-null float64\n",
      "Equity(49156 [MB])      267 non-null float64\n",
      "Equity(49193 [APPF])    267 non-null float64\n",
      "Equity(49594 [INST])    267 non-null float64\n",
      "Equity(49606 [MIME])    267 non-null float64\n",
      "Equity(49655 [TEAM])    267 non-null float64\n",
      "Equity(50350 [COUP])    267 non-null float64\n",
      "Equity(50758 [OKTA])    267 non-null float64\n",
      "Equity(50781 [YEXT])    267 non-null float64\n",
      "Equity(51455 [SEND])    267 non-null float64\n",
      "dtypes: float64(26)\n",
      "memory usage: 56.3 KB\n"
     ]
    }
   ],
   "source": [
    "# check to see if there are any NAN values\n",
    "new_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ADBE</th>\n",
       "      <th>CRM</th>\n",
       "      <th>LOGM</th>\n",
       "      <th>RP</th>\n",
       "      <th>PFPT</th>\n",
       "      <th>NOW</th>\n",
       "      <th>QLYS</th>\n",
       "      <th>WDAY</th>\n",
       "      <th>RNG</th>\n",
       "      <th>PCTY</th>\n",
       "      <th>...</th>\n",
       "      <th>BOX</th>\n",
       "      <th>MB</th>\n",
       "      <th>APPF</th>\n",
       "      <th>INST</th>\n",
       "      <th>MIME</th>\n",
       "      <th>TEAM</th>\n",
       "      <th>COUP</th>\n",
       "      <th>OKTA</th>\n",
       "      <th>YEXT</th>\n",
       "      <th>SEND</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-01-02 00:00:00+00:00</th>\n",
       "      <td>11.966616</td>\n",
       "      <td>7.294119</td>\n",
       "      <td>7.179605</td>\n",
       "      <td>6.262215</td>\n",
       "      <td>8.188433</td>\n",
       "      <td>12.414835</td>\n",
       "      <td>8.848112</td>\n",
       "      <td>9.837853</td>\n",
       "      <td>7.672582</td>\n",
       "      <td>7.517804</td>\n",
       "      <td>...</td>\n",
       "      <td>5.814029</td>\n",
       "      <td>7.081477</td>\n",
       "      <td>10.197639</td>\n",
       "      <td>6.384513</td>\n",
       "      <td>7.004518</td>\n",
       "      <td>14.566147</td>\n",
       "      <td>8.765207</td>\n",
       "      <td>10.329181</td>\n",
       "      <td>6.233919</td>\n",
       "      <td>18.622845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-03 00:00:00+00:00</th>\n",
       "      <td>12.141677</td>\n",
       "      <td>7.452802</td>\n",
       "      <td>7.255172</td>\n",
       "      <td>6.399834</td>\n",
       "      <td>8.500690</td>\n",
       "      <td>12.545408</td>\n",
       "      <td>9.149557</td>\n",
       "      <td>10.012579</td>\n",
       "      <td>7.572878</td>\n",
       "      <td>7.612387</td>\n",
       "      <td>...</td>\n",
       "      <td>5.919104</td>\n",
       "      <td>7.176996</td>\n",
       "      <td>10.121590</td>\n",
       "      <td>6.436178</td>\n",
       "      <td>6.890895</td>\n",
       "      <td>15.089600</td>\n",
       "      <td>9.025883</td>\n",
       "      <td>10.704129</td>\n",
       "      <td>6.129888</td>\n",
       "      <td>19.273771</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                ADBE       CRM      LOGM        RP      PFPT  \\\n",
       "2018-01-02 00:00:00+00:00  11.966616  7.294119  7.179605  6.262215  8.188433   \n",
       "2018-01-03 00:00:00+00:00  12.141677  7.452802  7.255172  6.399834  8.500690   \n",
       "\n",
       "                                 NOW      QLYS       WDAY       RNG      PCTY  \\\n",
       "2018-01-02 00:00:00+00:00  12.414835  8.848112   9.837853  7.672582  7.517804   \n",
       "2018-01-03 00:00:00+00:00  12.545408  9.149557  10.012579  7.572878  7.612387   \n",
       "\n",
       "                             ...           BOX        MB       APPF      INST  \\\n",
       "2018-01-02 00:00:00+00:00    ...      5.814029  7.081477  10.197639  6.384513   \n",
       "2018-01-03 00:00:00+00:00    ...      5.919104  7.176996  10.121590  6.436178   \n",
       "\n",
       "                               MIME       TEAM      COUP       OKTA      YEXT  \\\n",
       "2018-01-02 00:00:00+00:00  7.004518  14.566147  8.765207  10.329181  6.233919   \n",
       "2018-01-03 00:00:00+00:00  6.890895  15.089600  9.025883  10.704129  6.129888   \n",
       "\n",
       "                                SEND  \n",
       "2018-01-02 00:00:00+00:00  18.622845  \n",
       "2018-01-03 00:00:00+00:00  19.273771  \n",
       "\n",
       "[2 rows x 26 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# change the names of the columns to look nicer for bar chart later\n",
    "import re\n",
    "col_tickers = []\n",
    "for values in new_df.columns.values.tolist():\n",
    "    col_tickers.append(re.search(r\"\\[(\\w+)\\]\", str(values)).group(1))\n",
    "new_df.columns = col_tickers\n",
    "new_df.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculate the mean of all multiples to create the chart\n",
    "mean_df = new_df.mean(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.8"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# calc the average for the period\n",
    "z_mean = mean_df.mean()\n",
    "round(z_mean,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Y7XbWr1/P+eefT1FREcXFxd4gZvHixVgsFgoKCsjIyCA8PJzo6GiKior4+OOPKSoqAtyd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\nRLLGUERERERERLL2f8UDW7Adk1DIAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f89e3dd73d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# make the line chart of multiple\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "fig, ax = plt.subplots()\n",
    "x = mean_df.index.values\n",
    "y = mean_df.values\n",
    "ax.plot(x,y)\n",
    "\n",
    "plt.legend(['Average EV/LTM Sales Multiple'],loc='best')\n",
    "plt.axhline(z_mean, color='r', linestyle='dashed', linewidth=2)\n",
    "plt.ylabel(\"Enterprise Value to Sales Multiple\")\n",
    "plt.xlabel(\"Date\")\n",
    "plt.text(.65, 0.48, 'Average = 10.8x',\n",
    "        horizontalalignment='right',\n",
    "        verticalalignment='center',\n",
    "        fontsize=16, color='black',\n",
    "        transform=ax.transAxes)\n",
    "plt.grid(b=True, which=u'major', axis=u'both')\n",
    "plt.title(\"Selected BVP Public Cloud/SaaS Companies\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2018-01-02 00:00:00+00:00</th>\n",
       "      <th>2019-01-24 00:00:00+00:00</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>OKTA</th>\n",
       "      <td>10.329181</td>\n",
       "      <td>22.965134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TEAM</th>\n",
       "      <td>14.566147</td>\n",
       "      <td>20.792172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COUP</th>\n",
       "      <td>8.765207</td>\n",
       "      <td>17.763635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEND</th>\n",
       "      <td>18.622845</td>\n",
       "      <td>15.672389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAYC</th>\n",
       "      <td>11.425151</td>\n",
       "      <td>15.057702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WDAY</th>\n",
       "      <td>9.837853</td>\n",
       "      <td>14.155241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADBE</th>\n",
       "      <td>11.966616</td>\n",
       "      <td>14.064069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NOW</th>\n",
       "      <td>12.414835</td>\n",
       "      <td>13.094260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZEN</th>\n",
       "      <td>8.108488</td>\n",
       "      <td>12.564684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEWR</th>\n",
       "      <td>9.645174</td>\n",
       "      <td>12.148729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HUBS</th>\n",
       "      <td>8.987554</td>\n",
       "      <td>12.024270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>APPF</th>\n",
       "      <td>10.197639</td>\n",
       "      <td>11.680769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RNG</th>\n",
       "      <td>7.672582</td>\n",
       "      <td>11.088207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIVN</th>\n",
       "      <td>7.232944</td>\n",
       "      <td>11.064666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QLYS</th>\n",
       "      <td>8.848112</td>\n",
       "      <td>10.624367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QTWO</th>\n",
       "      <td>7.844578</td>\n",
       "      <td>10.183477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CRM</th>\n",
       "      <td>7.294119</td>\n",
       "      <td>9.251813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFPT</th>\n",
       "      <td>8.188433</td>\n",
       "      <td>7.441663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MB</th>\n",
       "      <td>7.081477</td>\n",
       "      <td>7.298173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIME</th>\n",
       "      <td>7.004518</td>\n",
       "      <td>6.814543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RP</th>\n",
       "      <td>6.262215</td>\n",
       "      <td>6.374633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INST</th>\n",
       "      <td>6.384513</td>\n",
       "      <td>6.158726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YEXT</th>\n",
       "      <td>6.233919</td>\n",
       "      <td>6.142649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PCTY</th>\n",
       "      <td>7.517804</td>\n",
       "      <td>5.729630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOX</th>\n",
       "      <td>5.814029</td>\n",
       "      <td>4.583193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LOGM</th>\n",
       "      <td>7.179605</td>\n",
       "      <td>3.917689</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      2018-01-02 00:00:00+00:00  2019-01-24 00:00:00+00:00\n",
       "OKTA                  10.329181                  22.965134\n",
       "TEAM                  14.566147                  20.792172\n",
       "COUP                   8.765207                  17.763635\n",
       "SEND                  18.622845                  15.672389\n",
       "PAYC                  11.425151                  15.057702\n",
       "WDAY                   9.837853                  14.155241\n",
       "ADBE                  11.966616                  14.064069\n",
       "NOW                   12.414835                  13.094260\n",
       "ZEN                    8.108488                  12.564684\n",
       "NEWR                   9.645174                  12.148729\n",
       "HUBS                   8.987554                  12.024270\n",
       "APPF                  10.197639                  11.680769\n",
       "RNG                    7.672582                  11.088207\n",
       "FIVN                   7.232944                  11.064666\n",
       "QLYS                   8.848112                  10.624367\n",
       "QTWO                   7.844578                  10.183477\n",
       "CRM                    7.294119                   9.251813\n",
       "PFPT                   8.188433                   7.441663\n",
       "MB                     7.081477                   7.298173\n",
       "MIME                   7.004518                   6.814543\n",
       "RP                     6.262215                   6.374633\n",
       "INST                   6.384513                   6.158726\n",
       "YEXT                   6.233919                   6.142649\n",
       "PCTY                   7.517804                   5.729630\n",
       "BOX                    5.814029                   4.583193\n",
       "LOGM                   7.179605                   3.917689"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# look at how multiples have changed from beg date to end date\n",
    "# slice new_df with Saas company mulitples on first date, last date\n",
    "results_df = new_df.iloc[[0,-1],:]\n",
    "# sort results by Jan 23\n",
    "result_sorted = results_df.T.sort_values(by='2019-01-24',ascending= False)\n",
    "result_sorted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['OKTA', 'TEAM', 'COUP', 'SEND', 'PAYC']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#sort tickers for bar chart\n",
    "sorted_tickers = []\n",
    "for values in result_sorted.index.values.tolist():\n",
    "    sorted_tickers.append(values)\n",
    "sorted_tickers[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get data for bar chart\n",
    "bar_df = result_sorted.loc[:,'2019-01-24']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BSdq9e7dq166dobV4eXlp48aN2rBhg3x8fNLcduvWrbp586ZR52uvvaYPPvhAx48fV3x8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\nIiIik/X/ANMtBA+e4C2RAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f89e3c62410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f89e3a5ef90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create the bar chart\n",
    "N = len(sorted_tickers)\n",
    "mult = bar_df.values  #.tolist()\n",
    "ind = np.arange(N)\n",
    "fig, ax = plt.subplots()\n",
    "mults = ax.bar(ind,mult,color='b',align=\"center\")  \n",
    "ax.set_ylabel('EV/TTM Sales Multiples')\n",
    "ax.set_title(\"EV/TTM Sales Multiples for High Gross Margin SaaS Companies\")\n",
    "\n",
    "width = 0.45\n",
    "ax.set_xticks(ind + width / 2)\n",
    "ax.set_xticklabels(sorted_tickers)\n",
    "\n",
    "#ax = result_sorted.plot(kind='bar',x=result_sorted.index,title=\"EV-TTM Sales Multiples\", use_index=True)\n",
    "def autolabel(rects):\n",
    "    \"\"\"\n",
    "    Attach a text label above each bar displaying its height\n",
    "    \"\"\"\n",
    "    for rect in rects:\n",
    "        height = rect.get_height()\n",
    "        ax.text(rect.get_x() + rect.get_width()/2., 1.02*height,\n",
    "                '%d' % int(height), ha='center', va='bottom')\n",
    "autolabel(mults)\n",
    "ax.legend(['Multiples'],loc='best')\n",
    "ax.grid(False)\n",
    "plt.xticks(ind, (sorted_tickers),rotation='vertical')\n",
    "plt.axhline(z_mean, color='r', linestyle='dashed', linewidth=2)\n",
    "#plt.axis('tight') #scaled square\n",
    "plt.autoscale(enable=True, axis='both', tight=None)\n",
    "ax.text(0.95, 0.48, 'Average = 10.8x',\n",
    "        horizontalalignment='right',\n",
    "        verticalalignment='center',\n",
    "        fontsize=20, color='black',\n",
    "        transform=ax.transAxes)\n",
    "#plt.margins(0.1,0)\n",
    "\n",
    "fig = plt.figure(figsize=(8,6))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create New Pipeline for spread chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>High Value</th>\n",
       "      <th>Low Value</th>\n",
       "      <th>ev_ttm_rev</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2018-02-01 00:00:00+00:00</th>\n",
       "      <th>Equity(114 [ADBE])</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>12.909582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(40030 [RP])</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>6.976519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(43127 [NOW])</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>14.215578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(46695 [FIVN])</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>7.565621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Equity(46744 [PAYC])</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>13.254838</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               High Value Low Value  \\\n",
       "2018-02-01 00:00:00+00:00 Equity(114 [ADBE])         True     False   \n",
       "                          Equity(40030 [RP])        False      True   \n",
       "                          Equity(43127 [NOW])        True     False   \n",
       "                          Equity(46695 [FIVN])      False      True   \n",
       "                          Equity(46744 [PAYC])       True     False   \n",
       "\n",
       "                                                ev_ttm_rev  \n",
       "2018-02-01 00:00:00+00:00 Equity(114 [ADBE])     12.909582  \n",
       "                          Equity(40030 [RP])      6.976519  \n",
       "                          Equity(43127 [NOW])    14.215578  \n",
       "                          Equity(46695 [FIVN])    7.565621  \n",
       "                          Equity(46744 [PAYC])   13.254838  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def make_pipeline():\n",
    "    (\n",
    "        total_revenue_ttm,\n",
    "        total_revenue_ttm_asof_date\n",
    "    ) = TrailingTwelveMonths(\n",
    "        inputs=[\n",
    "            Fundamentals.total_revenue,\n",
    "            Fundamentals.total_revenue_asof_date,\n",
    "        ]\n",
    "    )\n",
    "    enterprise_value = Fundamentals.enterprise_value.latest\n",
    "    market_cap = Fundamentals.market_cap.latest\n",
    "    enterprise_value_ttm_rev = Fundamentals.enterprise_value.latest / total_revenue_ttm\n",
    "    combined_rank = enterprise_value_ttm_rev.rank(mask=symbols)\n",
    "    #set filters\n",
    "    sec_high = combined_rank.percentile_between(80,100)\n",
    "    sec_low = combined_rank.percentile_between(0,20)\n",
    "    \n",
    "    sec_to_trade = (sec_high | sec_low)\n",
    "    \n",
    "    return Pipeline(\n",
    "        columns={\n",
    "            'ev_ttm_rev': enterprise_value_ttm_rev,\n",
    "            'High Value': sec_high,\n",
    "            'Low Value': sec_low\n",
    "        },\n",
    "        screen=sec_to_trade\n",
    "    )\n",
    "df = run_pipeline(make_pipeline(), '2018-2-01', '2019-1-24')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create High Value dataframe\n",
    "df_high = df[df['High Value']== True].drop(['High Value','Low Value'],axis=1).unstack()\n",
    "#eliminate multi-index columns\n",
    "df_high.columns = df_high.columns.droplevel()\n",
    "df_high_m = df_high.mean(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "# perform a few checks\n",
    "print(df_high_m.iloc[-1] == df_high.iloc[-1,:].mean())\n",
    "print(df_high_m.iloc[0] == df_high.iloc[0,:].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17.73437883542656"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check the average for the most recent date\n",
    "df_high.iloc[-1,:].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14.307796177982217"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check the average for the start date\n",
    "df_high.iloc[0,:].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create Low Value dataframe\n",
    "df_low = df[df['Low Value']== True].drop(['High Value','Low Value'],axis=1).unstack()\n",
    "#eliminate multi-index columns\n",
    "df_low.columns = df_low.columns.droplevel()\n",
    "df_low_m = df_low.mean(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "# perform a few checks and look at mean values\n",
    "print(df_low_m.iloc[-1] == df_low.iloc[-1,:].mean())\n",
    "print(df_low_m.iloc[0] == df_low.iloc[0,:].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.484420016000128"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# avg for the most recent date\n",
    "df_low.iloc[-1,:].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.904087230648571"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# avg for start date\n",
    "df_low.iloc[0,:].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Concatenate dataframes to create spread \n",
    "spread_df = pd.concat([df_high_m,df_low_m],axis=1)\n",
    "spread_df.columns = ['Top', 'Bottom']\n",
    "spread_comb_df = spread_df['Top'] - spread_df['Bottom']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.7"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# what is the average spread of time period\n",
    "spr_mean = spread_comb_df.mean()\n",
    "round(spr_mean,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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r8d133+Gnn36CXq+HTqeDl5cX1Go19Ho9pk6dKh4jPz9f/N3LZDKx/FAqlVaaLRF88skn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SAAAg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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f89e6ea6710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#create line chart\n",
    "spread_comb_df.plot(colormap='plasma',figsize=(14,10))\n",
    "plt.ylabel(\"Spread between High Avg and Low Avg Multiple\")\n",
    "plt.xlabel(\"Date\")\n",
    "plt.axhline(spr_mean, color='r', linestyle='dashed', linewidth=2)\n",
    "plt.grid(b=True, which=u'major', axis=u'both')\n",
    "plt.text(.15, 0.6, 'Average = 9.7x',\n",
    "        horizontalalignment='center',\n",
    "        verticalalignment='center',\n",
    "        fontsize=16, color='black',\n",
    "        transform=ax.transAxes)\n",
    "plt.title(\"Valuation Spread between High Value and Low Value BVP Cloud/SaaS Companies\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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