{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Pre-Funding', 'Seed', 'A', 'Mature', 'C', 'Public', 'D',\n",
       "       'Pre-Seed', 'B', 'Debt Financing', 'F', 'Crowdfunding', 'E'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.stage.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 3., 1., 4., 2., 5.])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.stage.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>name</th>\n",
       "      <th>description</th>\n",
       "      <th>year</th>\n",
       "      <th>target</th>\n",
       "      <th>size</th>\n",
       "      <th>stage</th>\n",
       "      <th>raised</th>\n",
       "      <th>tags</th>\n",
       "      <th>country</th>\n",
       "      <th>source</th>\n",
       "      <th>text_vector_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.10 of a Second</td>\n",
       "      <td>Smart Indicators for Connected Vehicles</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>B2B</td>\n",
       "      <td>1-10</td>\n",
       "      <td>Pre-Funding</td>\n",
       "      <td>Undisclosed</td>\n",
       "      <td>[connected-vehicles, adas, autonomous-vehicles...</td>\n",
       "      <td>Israel</td>\n",
       "      <td>https://finder.startupnationcentral.org/</td>\n",
       "      <td>[-0.031224824488162994, -0.06342269480228424, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>12trix</td>\n",
       "      <td>Math Lessons for Young Kids</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>B2B, B2C</td>\n",
       "      <td>1-10</td>\n",
       "      <td>Pre-Funding</td>\n",
       "      <td>Undisclosed</td>\n",
       "      <td>[sdg, schools, pre-k, serious-games, games, mo...</td>\n",
       "      <td>Israel</td>\n",
       "      <td>https://finder.startupnationcentral.org/</td>\n",
       "      <td>[-0.038649097084999084, 0.028091922402381897, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1E Therapeutics</td>\n",
       "      <td>Novel RNA-targeting Drugs</td>\n",
       "      <td>2021.0</td>\n",
       "      <td>B2B</td>\n",
       "      <td>51-200</td>\n",
       "      <td>Seed</td>\n",
       "      <td>$120M</td>\n",
       "      <td>[pharmaceuticals, chronic-disease, immunology,...</td>\n",
       "      <td>Israel</td>\n",
       "      <td>https://finder.startupnationcentral.org/</td>\n",
       "      <td>[0.04561534896492958, -0.017776092514395714, 0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1MRobotics</td>\n",
       "      <td>Retail Automation Solutions with Nano Fulfillment</td>\n",
       "      <td>2021.0</td>\n",
       "      <td>B2B</td>\n",
       "      <td>11-50</td>\n",
       "      <td>A</td>\n",
       "      <td>$25M</td>\n",
       "      <td>[omni-channel, ecommerce, climate-tech, artifi...</td>\n",
       "      <td>Israel</td>\n",
       "      <td>https://finder.startupnationcentral.org/</td>\n",
       "      <td>[0.0024080690927803516, -0.03042100928723812, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1touch.io</td>\n",
       "      <td>Personal Data Flow Tracking and Data Cataloging</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>B2B</td>\n",
       "      <td>51-200</td>\n",
       "      <td>A</td>\n",
       "      <td>$16.1M</td>\n",
       "      <td>[enterprise-solutions, data-protection, cyber-...</td>\n",
       "      <td>Israel</td>\n",
       "      <td>https://finder.startupnationcentral.org/</td>\n",
       "      <td>[-0.01007091999053955, 0.10431888699531555, -0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4981</th>\n",
       "      <td>YOW HR</td>\n",
       "      <td>Human Resources Engagement and Optimization Pl...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>B2B, B2B2C</td>\n",
       "      <td>1-10</td>\n",
       "      <td>Pre-Funding</td>\n",
       "      <td>Undisclosed</td>\n",
       "      <td>[content-creators, e-learning, software-applic...</td>\n",
       "      <td>Israel</td>\n",
       "      <td>https://finder.startupnationcentral.org/</td>\n",
       "      <td>[0.026961881667375565, 0.002459645736962557, -...</td>\n",
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       "    <tr>\n",
       "      <th>4982</th>\n",
       "      <td>Yummi Home Food</td>\n",
       "      <td>Marketplace for Homemade Food</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>B2C</td>\n",
       "      <td>11-50</td>\n",
       "      <td>Pre-Funding</td>\n",
       "      <td>Undisclosed</td>\n",
       "      <td>[ecommerce, p2p, delivery, online-shopping, ma...</td>\n",
       "      <td>Israel</td>\n",
       "      <td>https://finder.startupnationcentral.org/</td>\n",
       "      <td>[0.0036857957020401955, 0.03582162782549858, -...</td>\n",
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       "    <tr>\n",
       "      <th>4983</th>\n",
       "      <td>Yung-Etgar</td>\n",
       "      <td>Custom Mechanized Harvesting Systems</td>\n",
       "      <td>1982.0</td>\n",
       "      <td>B2B</td>\n",
       "      <td>51-200</td>\n",
       "      <td>Mature</td>\n",
       "      <td>Undisclosed</td>\n",
       "      <td>[crops, agtech, harvesting, machinery, sdg, cl...</td>\n",
       "      <td>Israel</td>\n",
       "      <td>https://finder.startupnationcentral.org/</td>\n",
       "      <td>[0.027293115854263306, 0.010461761616170406, 0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4984</th>\n",
       "      <td>YuviTal</td>\n",
       "      <td>Digital Health and Fitness Solutions for Organ...</td>\n",
       "      <td>2017.0</td>\n",
       "      <td>B2B, B2C, B2G</td>\n",
       "      <td>11-50</td>\n",
       "      <td>Pre-Funding</td>\n",
       "      <td>Undisclosed</td>\n",
       "      <td>[fitness, digital-wallet, discount, mobile-app...</td>\n",
       "      <td>Israel</td>\n",
       "      <td>https://finder.startupnationcentral.org/</td>\n",
       "      <td>[0.02851911261677742, 0.05474231392145157, -0....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4985</th>\n",
       "      <td>Z-square</td>\n",
       "      <td>Microendoscope for Minimally Invasive Imaging ...</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>B2B</td>\n",
       "      <td>11-50</td>\n",
       "      <td>Seed</td>\n",
       "      <td>$10M</td>\n",
       "      <td>[endoscopy, medical-devices, minimally-invasiv...</td>\n",
       "      <td>Israel</td>\n",
       "      <td>https://finder.startupnationcentral.org/</td>\n",
       "      <td>[0.012587728910148144, -0.07959864288568497, -...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4986 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  name                                        description  \\\n",
       "0     0.10 of a Second           Smart Indicators for Connected Vehicles    \n",
       "1               12trix                        Math Lessons for Young Kids   \n",
       "2      1E Therapeutics                          Novel RNA-targeting Drugs   \n",
       "3           1MRobotics  Retail Automation Solutions with Nano Fulfillment   \n",
       "4            1touch.io    Personal Data Flow Tracking and Data Cataloging   \n",
       "...                ...                                                ...   \n",
       "4981            YOW HR  Human Resources Engagement and Optimization Pl...   \n",
       "4982   Yummi Home Food                      Marketplace for Homemade Food   \n",
       "4983        Yung-Etgar               Custom Mechanized Harvesting Systems   \n",
       "4984           YuviTal  Digital Health and Fitness Solutions for Organ...   \n",
       "4985          Z-square  Microendoscope for Minimally Invasive Imaging ...   \n",
       "\n",
       "        year         target    size        stage       raised  \\\n",
       "0     2019.0            B2B    1-10  Pre-Funding  Undisclosed   \n",
       "1     2012.0       B2B, B2C    1-10  Pre-Funding  Undisclosed   \n",
       "2     2021.0            B2B  51-200         Seed        $120M   \n",
       "3     2021.0            B2B   11-50            A         $25M   \n",
       "4     2017.0            B2B  51-200            A       $16.1M   \n",
       "...      ...            ...     ...          ...          ...   \n",
       "4981  2020.0     B2B, B2B2C    1-10  Pre-Funding  Undisclosed   \n",
       "4982  2012.0            B2C   11-50  Pre-Funding  Undisclosed   \n",
       "4983  1982.0            B2B  51-200       Mature  Undisclosed   \n",
       "4984  2017.0  B2B, B2C, B2G   11-50  Pre-Funding  Undisclosed   \n",
       "4985  2013.0            B2B   11-50         Seed         $10M   \n",
       "\n",
       "                                                   tags country  \\\n",
       "0     [connected-vehicles, adas, autonomous-vehicles...  Israel   \n",
       "1     [sdg, schools, pre-k, serious-games, games, mo...  Israel   \n",
       "2     [pharmaceuticals, chronic-disease, immunology,...  Israel   \n",
       "3     [omni-channel, ecommerce, climate-tech, artifi...  Israel   \n",
       "4     [enterprise-solutions, data-protection, cyber-...  Israel   \n",
       "...                                                 ...     ...   \n",
       "4981  [content-creators, e-learning, software-applic...  Israel   \n",
       "4982  [ecommerce, p2p, delivery, online-shopping, ma...  Israel   \n",
       "4983  [crops, agtech, harvesting, machinery, sdg, cl...  Israel   \n",
       "4984  [fitness, digital-wallet, discount, mobile-app...  Israel   \n",
       "4985  [endoscopy, medical-devices, minimally-invasiv...  Israel   \n",
       "\n",
       "                                        source  \\\n",
       "0     https://finder.startupnationcentral.org/   \n",
       "1     https://finder.startupnationcentral.org/   \n",
       "2     https://finder.startupnationcentral.org/   \n",
       "3     https://finder.startupnationcentral.org/   \n",
       "4     https://finder.startupnationcentral.org/   \n",
       "...                                        ...   \n",
       "4981  https://finder.startupnationcentral.org/   \n",
       "4982  https://finder.startupnationcentral.org/   \n",
       "4983  https://finder.startupnationcentral.org/   \n",
       "4984  https://finder.startupnationcentral.org/   \n",
       "4985  https://finder.startupnationcentral.org/   \n",
       "\n",
       "                                           text_vector_  \n",
       "0     [-0.031224824488162994, -0.06342269480228424, ...  \n",
       "1     [-0.038649097084999084, 0.028091922402381897, ...  \n",
       "2     [0.04561534896492958, -0.017776092514395714, 0...  \n",
       "3     [0.0024080690927803516, -0.03042100928723812, ...  \n",
       "4     [-0.01007091999053955, 0.10431888699531555, -0...  \n",
       "...                                                 ...  \n",
       "4981  [0.026961881667375565, 0.002459645736962557, -...  \n",
       "4982  [0.0036857957020401955, 0.03582162782549858, -...  \n",
       "4983  [0.027293115854263306, 0.010461761616170406, 0...  \n",
       "4984  [0.02851911261677742, 0.05474231392145157, -0....  \n",
       "4985  [0.012587728910148144, -0.07959864288568497, -...  \n",
       "\n",
       "[4986 rows x 11 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df1 = pd.read_parquet('df_encoded.parquet')\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>title</th>\n",
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       "      <th>0</th>\n",
       "      <td>Digipal</td>\n",
       "      <td>Digipal is a digital consultancy based in Tbil...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Software &amp; Data</td>\n",
       "      <td>https://www.digipal.agency/</td>\n",
       "      <td>georgia</td>\n",
       "      <td>tbilisi</td>\n",
       "      <td>Tbilisi, Georgia</td>\n",
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       "      <td>[0.017287444323301315, 0.06208805367350578, -0...</td>\n",
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       "      <th>1</th>\n",
       "      <td>BeatBind</td>\n",
       "      <td>BeatBind is the industry's long overdue platfo...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Social &amp; Leisure</td>\n",
       "      <td>https://beatbind.io/</td>\n",
       "      <td>georgia</td>\n",
       "      <td>tbilisi</td>\n",
       "      <td>Tbilisi, Georgia</td>\n",
       "      <td>Europe</td>\n",
       "      <td>[-0.00438214186578989, -0.051213208585977554, ...</td>\n",
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       "      <th>2</th>\n",
       "      <td>Smart Academy</td>\n",
       "      <td>Smart Academy is a modern educational institut...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Edtech</td>\n",
       "      <td>https://smartacademy.ge/</td>\n",
       "      <td>georgia</td>\n",
       "      <td>tbilisi</td>\n",
       "      <td>Tbilisi, Georgia</td>\n",
       "      <td>Europe</td>\n",
       "      <td>[0.0005468669114634395, -0.05331585183739662, ...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MaxinAI</td>\n",
       "      <td>MaxinAI isglobal AI development company that w...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Software &amp; Data</td>\n",
       "      <td>https://www.maxinai.com/#all-industries</td>\n",
       "      <td>georgia</td>\n",
       "      <td>tbilisi</td>\n",
       "      <td>Tbilisi, Georgia</td>\n",
       "      <td>Europe</td>\n",
       "      <td>[0.021948501467704773, 0.024166792631149292, -...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TLANCER</td>\n",
       "      <td>Tlancer aims to create an unlimited educationa...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Edtech</td>\n",
       "      <td>https://www.tlancer.ge/</td>\n",
       "      <td>georgia</td>\n",
       "      <td>tbilisi</td>\n",
       "      <td>Tbilisi, Georgia</td>\n",
       "      <td>Europe</td>\n",
       "      <td>[0.02025573141872883, -0.022812215611338615, -...</td>\n",
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       "      <th>...</th>\n",
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       "      <th>94521</th>\n",
       "      <td>OneTwo</td>\n",
       "      <td>klkdčksč kdč skdčlsk čdksčd ksčk dčskdčk čdk</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Software &amp; Data</td>\n",
       "      <td>www.nethr</td>\n",
       "      <td>croatia</td>\n",
       "      <td>zagreb</td>\n",
       "      <td>Zagreb, Croatia</td>\n",
       "      <td>Europe</td>\n",
       "      <td>[0.07235302031040192, -0.05674564838409424, -0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94522</th>\n",
       "      <td>Trialfire</td>\n",
       "      <td>Engaged trialers turn into customers, engaged ...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Software &amp; Data</td>\n",
       "      <td>http://www.trialfire.com</td>\n",
       "      <td>canada</td>\n",
       "      <td>toronto</td>\n",
       "      <td>Toronto, Canada</td>\n",
       "      <td>North America</td>\n",
       "      <td>[0.030764097347855568, 0.054082825779914856, -...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94523</th>\n",
       "      <td>ILLUMAGEAR</td>\n",
       "      <td>ILLUMAGEAR’s mission is to illuminate people a...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Software &amp; Data</td>\n",
       "      <td>http://www.illumagear.com</td>\n",
       "      <td>united-states</td>\n",
       "      <td>seattle</td>\n",
       "      <td>Seattle, United States</td>\n",
       "      <td>North America</td>\n",
       "      <td>[0.015447210520505905, -0.0984775498509407, 0....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94524</th>\n",
       "      <td>Knowillage</td>\n",
       "      <td>Knowillage lets you add personalization to you...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Edtech</td>\n",
       "      <td>http://www.knowillage.com</td>\n",
       "      <td>canada</td>\n",
       "      <td>vancouver</td>\n",
       "      <td>Vancouver, Canada</td>\n",
       "      <td>North America</td>\n",
       "      <td>[0.007970919832587242, -0.04347420111298561, -...</td>\n",
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       "    <tr>\n",
       "      <th>94525</th>\n",
       "      <td>Iris Holidays</td>\n",
       "      <td>Iris Holidays is a full service Kerala tours o...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Software &amp; Data</td>\n",
       "      <td>http://www.irisholidays.com</td>\n",
       "      <td>india</td>\n",
       "      <td>kochi</td>\n",
       "      <td>Kochi, India</td>\n",
       "      <td>Asia Pacific</td>\n",
       "      <td>[0.0032976483926177025, -0.010843133553862572,...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>94526 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                title                                        description  \\\n",
       "0            Digipal   Digipal is a digital consultancy based in Tbil...   \n",
       "1            BeatBind  BeatBind is the industry's long overdue platfo...   \n",
       "2       Smart Academy  Smart Academy is a modern educational institut...   \n",
       "3             MaxinAI  MaxinAI isglobal AI development company that w...   \n",
       "4             TLANCER  Tlancer aims to create an unlimited educationa...   \n",
       "...               ...                                                ...   \n",
       "94521          OneTwo       klkdčksč kdč skdčlsk čdksčd ksčk dčskdčk čdk   \n",
       "94522       Trialfire  Engaged trialers turn into customers, engaged ...   \n",
       "94523      ILLUMAGEAR  ILLUMAGEAR’s mission is to illuminate people a...   \n",
       "94524      Knowillage  Knowillage lets you add personalization to you...   \n",
       "94525  Iris Holidays   Iris Holidays is a full service Kerala tours o...   \n",
       "\n",
       "       stage     industry_name                                      url  \\\n",
       "0        0.0   Software & Data              https://www.digipal.agency/   \n",
       "1        0.0  Social & Leisure                     https://beatbind.io/   \n",
       "2        0.0            Edtech                 https://smartacademy.ge/   \n",
       "3        0.0   Software & Data  https://www.maxinai.com/#all-industries   \n",
       "4        0.0            Edtech                  https://www.tlancer.ge/   \n",
       "...      ...               ...                                      ...   \n",
       "94521    0.0   Software & Data                                www.nethr   \n",
       "94522    0.0   Software & Data                 http://www.trialfire.com   \n",
       "94523    0.0   Software & Data                http://www.illumagear.com   \n",
       "94524    0.0            Edtech                http://www.knowillage.com   \n",
       "94525    0.0   Software & Data              http://www.irisholidays.com   \n",
       "\n",
       "        country_slug  city_slug                location    region_name  \\\n",
       "0            georgia    tbilisi        Tbilisi, Georgia         Europe   \n",
       "1            georgia    tbilisi        Tbilisi, Georgia         Europe   \n",
       "2            georgia    tbilisi        Tbilisi, Georgia         Europe   \n",
       "3            georgia    tbilisi        Tbilisi, Georgia         Europe   \n",
       "4            georgia    tbilisi        Tbilisi, Georgia         Europe   \n",
       "...              ...        ...                     ...            ...   \n",
       "94521        croatia     zagreb         Zagreb, Croatia         Europe   \n",
       "94522         canada    toronto         Toronto, Canada  North America   \n",
       "94523  united-states    seattle  Seattle, United States  North America   \n",
       "94524         canada  vancouver       Vancouver, Canada  North America   \n",
       "94525          india      kochi            Kochi, India   Asia Pacific   \n",
       "\n",
       "                                            text_vector_  \n",
       "0      [0.017287444323301315, 0.06208805367350578, -0...  \n",
       "1      [-0.00438214186578989, -0.051213208585977554, ...  \n",
       "2      [0.0005468669114634395, -0.05331585183739662, ...  \n",
       "3      [0.021948501467704773, 0.024166792631149292, -...  \n",
       "4      [0.02025573141872883, -0.022812215611338615, -...  \n",
       "...                                                  ...  \n",
       "94521  [0.07235302031040192, -0.05674564838409424, -0...  \n",
       "94522  [0.030764097347855568, 0.054082825779914856, -...  \n",
       "94523  [0.015447210520505905, -0.0984775498509407, 0....  \n",
       "94524  [0.007970919832587242, -0.04347420111298561, -...  \n",
       "94525  [0.0032976483926177025, -0.010843133553862572,...  \n",
       "\n",
       "[94526 rows x 10 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stage_dict = {\n",
    "    0 : \"pre-seed\",\n",
    "    1 : \"seed\",\n",
    "    2 : \"A\",\n",
    "    3 : \"B\",\n",
    "    4 : \"C\",\n",
    "    5 : \"Exit\",\n",
    "}\n",
    "\n",
    "df2 = pd.read_parquet('df_encoded2.parquet')\n",
    "df2.columns = [['name', 'description', 'stage', 'industry_name', 'url', 'country_slug', 'text_vector_']]\n",
    "df2['stage'] = df2['stage'].apply(lambda x : stage_dict[x])\n",
    "df2['raised'] = 'Undisclosed'\n",
    "df2['size'] = '11-500+'\n",
    "df2['source'] = 'https://www.startupblink.com'\n",
    "df2.columns = [['name', 'description', 'stage', 'tags', 'url', 'country_slug', 'text_vector_', 'raised', 'size', 'source']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.system('pip install openpyxl')\n",
    "os.system('pip install sentence-transformers')\n",
    "import pandas as pd\n",
    "import gradio as gr\n",
    "from sentence_transformers import SentenceTransformer\n",
    "\n",
    "model = SentenceTransformer('all-mpnet-base-v2') #all-MiniLM-L6-v2 #all-mpnet-base-v2\n",
    "\n",
    "df = pd.read_parquet('df_encoded.parquet')\n",
    "df['tags'] = df['tags'].apply(lambda x : str(x))\n",
    "def parse_raised(x):\n",
    "    if x == 'Undisclosed':\n",
    "        return 0\n",
    "    else: \n",
    "        quantifier = x[-1]\n",
    "        x = float(x[1:-1])\n",
    "        if quantifier == 'K':\n",
    "            return x/1000\n",
    "        elif quantifier == 'M':\n",
    "            return x\n",
    "df['raised'] = df['raised'].apply(lambda x : parse_raised(x))\n",
    "df = df.reset_index(drop=True)\n",
    "\n",
    "from sklearn.neighbors import NearestNeighbors\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sentence_transformers import SentenceTransformer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\ardit\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\gradio\\deprecation.py:43: UserWarning: You have unused kwarg parameters in Radio, please remove them: {'multiselect': False}\n",
      "  warnings.warn(\n",
      "c:\\Users\\ardit\\AppData\\Local\\Programs\\Python\\Python39\\lib\\site-packages\\gradio\\deprecation.py:43: UserWarning: You have unused kwarg parameters in Slider, please remove them: {'step_size': 1}\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on local URL:  http://127.0.0.1:7896\n",
      "\n",
      "To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><iframe src=\"http://127.0.0.1:7896/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a\n"
     ]
    }
   ],
   "source": [
    "def filter_df(df, column_name, filter_type, filter_value):\n",
    "    if filter_type == '==':\n",
    "        df_filtered = df[df[column_name]==filter_value]\n",
    "    elif filter_type == '>=':\n",
    "        df_filtered = df[df[column_name]>=filter_value]\n",
    "    elif filter_type == '<=':\n",
    "        df_filtered = df[df[column_name]<=filter_value]\n",
    "    elif filter_type == 'contains':\n",
    "        df_filtered = df[df['target'].str.contains(filter_value)]\n",
    "    return df_filtered\n",
    "\n",
    "def search(df, query):\n",
    "    product = model.encode(query).tolist()\n",
    "    # product = df.iloc[0]['text_vector_'] #use one of the products as sample\n",
    "\n",
    "    #prepare model\n",
    "    nbrs = NearestNeighbors(n_neighbors=20, algorithm='ball_tree').fit(df['text_vector_'].values.tolist())\n",
    "\n",
    "    distances, indices = nbrs.kneighbors([product]) #input the vector of the reference object\n",
    "\n",
    "    #print out the description of every recommended product\n",
    "    return df.iloc[list(indices)[0]][['name', 'description', 'raised', 'year', 'target', 'size', 'stage', 'tags']]\n",
    "\n",
    "#the first module becomes text1, the second module file1\n",
    "def greet(size, target, raised, query): \n",
    "    df_size = filter_df(df, 'size', '==', size)\n",
    "    df_target = filter_df(df_size, 'target', 'contains', target)\n",
    "    def raised_zero(x):\n",
    "        if x == 0:\n",
    "            return 'Undisclosed'\n",
    "        else:\n",
    "            return x\n",
    "    print('a')\n",
    "    df_raised = df_target[(df_target['raised'] >= raised) | (df_target['raised'] == 0)]\n",
    "    df_knn = search(df_raised, query)\n",
    "    #we live the sorting for last\n",
    "    df_knn = df_knn.sort_values('raised', ascending=False)\n",
    "    df_knn['raised'] = df_knn['raised'].apply(lambda x : raised_zero(x))\n",
    "\n",
    "    return df_knn\n",
    "\n",
    "with gr.Blocks(theme=gr.themes.Soft(primary_hue='amber', secondary_hue='gray', neutral_hue='amber')) as demo:\n",
    "    gr.Markdown(\n",
    "    \"\"\"\n",
    "    # Gradio with History\n",
    "    \"\"\"\n",
    "    )\n",
    "    size = gr.Radio(['1-10', '11-50', '51-200', '201-500', '500+'], multiselect=False, value='11-50', label='size')\n",
    "    target = gr.Radio(['B2B', 'B2C', 'B2G', 'B2B2C'], value='B2B', multiselect=False, label='target')\n",
    "    raised = gr.Slider(0, 20, value=5, step_size=1, label=\"Minimum raising (in Millions)\")\n",
    "    query = gr.Textbox(label='Describe the Startup you are searching for', value='age reversing')\n",
    "    btn = gr.Button(value=\"Search for a Startup\")\n",
    "    output1 = gr.DataFrame(label='value')\n",
    "    # btn.click(greet, inputs='text', outputs=['dataframe'])\n",
    "    btn.click(greet, [size, target, raised, query], [output1])\n",
    "demo.launch(share=False)"
   ]
  }
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