03_Startup Investments query/Startup Investments query.ipynb

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   "metadata": {},
   "source": [
    "# Исследование рынка инвестиций по датасету Startup Investments"
   ]
  },
  {
   "cell_type": "markdown",
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   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Содержание<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Обзор-данных\" data-toc-modified-id=\"Обзор-данных-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Обзор данных</a></span><ul class=\"toc-item\"><li><span><a href=\"#Выведем-первые-строки-каждой-таблицы-и-изучим-значение-столбцов\" data-toc-modified-id=\"Выведем-первые-строки-каждой-таблицы-и-изучим-значение-столбцов-1.1\"><span class=\"toc-item-num\">1.1&nbsp;&nbsp;</span>Выведем первые строки каждой таблицы и изучим значение столбцов</a></span><ul class=\"toc-item\"><li><span><a href=\"#Таблица-acquisition\" data-toc-modified-id=\"Таблица-acquisition-1.1.1\"><span class=\"toc-item-num\">1.1.1&nbsp;&nbsp;</span>Таблица acquisition</a></span></li><li><span><a href=\"#Таблица-company\" data-toc-modified-id=\"Таблица-company-1.1.2\"><span class=\"toc-item-num\">1.1.2&nbsp;&nbsp;</span>Таблица company</a></span></li><li><span><a href=\"#Таблица-education\" data-toc-modified-id=\"Таблица-education-1.1.3\"><span class=\"toc-item-num\">1.1.3&nbsp;&nbsp;</span>Таблица education</a></span></li><li><span><a href=\"#Таблица-fund\" data-toc-modified-id=\"Таблица-fund-1.1.4\"><span class=\"toc-item-num\">1.1.4&nbsp;&nbsp;</span>Таблица fund</a></span></li><li><span><a href=\"#Таблица-funding_round\" data-toc-modified-id=\"Таблица-funding_round-1.1.5\"><span class=\"toc-item-num\">1.1.5&nbsp;&nbsp;</span>Таблица funding_round</a></span></li><li><span><a href=\"#Таблица-investment\" data-toc-modified-id=\"Таблица-investment-1.1.6\"><span class=\"toc-item-num\">1.1.6&nbsp;&nbsp;</span>Таблица investment</a></span></li><li><span><a href=\"#Таблица-people\" data-toc-modified-id=\"Таблица-people-1.1.7\"><span class=\"toc-item-num\">1.1.7&nbsp;&nbsp;</span>Таблица people</a></span></li></ul></li></ul></li><li><span><a href=\"#Исследовательский-анализ-данных\" data-toc-modified-id=\"Исследовательский-анализ-данных-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Исследовательский анализ данных</a></span><ul class=\"toc-item\"><li><span><a href=\"#Запрос-№1\" data-toc-modified-id=\"Запрос-№1-2.1\"><span class=\"toc-item-num\">2.1&nbsp;&nbsp;</span>Запрос №1</a></span></li><li><span><a href=\"#Запрос-№2\" data-toc-modified-id=\"Запрос-№2-2.2\"><span class=\"toc-item-num\">2.2&nbsp;&nbsp;</span>Запрос №2</a></span></li><li><span><a href=\"#Запрос-№3\" data-toc-modified-id=\"Запрос-№3-2.3\"><span class=\"toc-item-num\">2.3&nbsp;&nbsp;</span>Запрос №3</a></span></li><li><span><a href=\"#Запрос-№4\" data-toc-modified-id=\"Запрос-№4-2.4\"><span class=\"toc-item-num\">2.4&nbsp;&nbsp;</span>Запрос №4</a></span></li><li><span><a href=\"#Запрос-№5\" data-toc-modified-id=\"Запрос-№5-2.5\"><span class=\"toc-item-num\">2.5&nbsp;&nbsp;</span>Запрос №5</a></span></li><li><span><a href=\"#Запрос-№6\" data-toc-modified-id=\"Запрос-№6-2.6\"><span class=\"toc-item-num\">2.6&nbsp;&nbsp;</span>Запрос №6</a></span></li><li><span><a href=\"#Запрос-№7\" data-toc-modified-id=\"Запрос-№7-2.7\"><span class=\"toc-item-num\">2.7&nbsp;&nbsp;</span>Запрос №7</a></span></li><li><span><a href=\"#Запрос-№8\" data-toc-modified-id=\"Запрос-№8-2.8\"><span class=\"toc-item-num\">2.8&nbsp;&nbsp;</span>Запрос №8</a></span></li><li><span><a href=\"#Запрос-№9\" data-toc-modified-id=\"Запрос-№9-2.9\"><span class=\"toc-item-num\">2.9&nbsp;&nbsp;</span>Запрос №9</a></span></li><li><span><a href=\"#Запрос-№10\" data-toc-modified-id=\"Запрос-№10-2.10\"><span class=\"toc-item-num\">2.10&nbsp;&nbsp;</span>Запрос №10</a></span></li><li><span><a href=\"#Запрос-№11\" data-toc-modified-id=\"Запрос-№11-2.11\"><span class=\"toc-item-num\">2.11&nbsp;&nbsp;</span>Запрос №11</a></span></li><li><span><a href=\"#Запрос-№12\" data-toc-modified-id=\"Запрос-№12-2.12\"><span class=\"toc-item-num\">2.12&nbsp;&nbsp;</span>Запрос №12</a></span></li><li><span><a href=\"#Запрос-№13\" data-toc-modified-id=\"Запрос-№13-2.13\"><span class=\"toc-item-num\">2.13&nbsp;&nbsp;</span>Запрос №13</a></span></li><li><span><a href=\"#Запрос-№14\" data-toc-modified-id=\"Запрос-№14-2.14\"><span class=\"toc-item-num\">2.14&nbsp;&nbsp;</span>Запрос №14</a></span></li><li><span><a href=\"#Запрос-№15\" data-toc-modified-id=\"Запрос-№15-2.15\"><span class=\"toc-item-num\">2.15&nbsp;&nbsp;</span>Запрос №15</a></span></li></ul></li><li><span><a href=\"#Общий-вывод\" data-toc-modified-id=\"Общий-вывод-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Общий вывод</a></span></li></ul></div>"
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  {
   "cell_type": "markdown",
   "id": "4a4a5940",
   "metadata": {},
   "source": [
    "**Описание проекта**"
   ]
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  {
   "cell_type": "markdown",
   "id": "b2663780",
   "metadata": {},
   "source": [
    "В рамках данного проекта мы пропишем рабочие SQL запросы к базе данных основанной на датасете Startup Investments. Данная база данных хранит информацию о венчурных фондах и инвестициях в компании-стартапы. Датасет Startup Investments взят на популярной платформе для соревнований по исследованию данных Kaggle. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8414ea6b",
   "metadata": {},
   "source": [
    "**ER-диаграмма**"
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  {
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"
    }
   },
   "cell_type": "markdown",
   "id": "25d5e2de",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b31fc7ba",
   "metadata": {},
   "source": [
    "- `acquisition` - таблица содержит информацию о покупках одних компаний другими.\n",
    "- `company` - таблица содержит информацию о компаниях-стартапах.\n",
    "- `education` - таблица хранит информацию об уровне образования сотрудников компаний.\n",
    "- `fund` - таблица хранит информацию о венчурных фондах. \n",
    "- `funding_round` - таблица содержит информацию о раундах инвестиций. \n",
    "- `investment` - таблица содержит информацию об инвестициях венчурных фондов в компании-стартапы.\n",
    "- `people` - таблица содержит информацию о сотрудниках компаний-стартапов."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f15a4a03",
   "metadata": {},
   "source": [
    "**Цель исследования**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2543f739",
   "metadata": {},
   "source": [
    "- Написать рабочие, оптимальные запросы к БД\n",
    "- Проанализировать полученные результаты\n",
    "- Сформулировать выводы"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "603385dd",
   "metadata": {},
   "source": [
    "**Основные шаги**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6013c20a",
   "metadata": {},
   "source": [
    "1. Обзор данных\n",
    "2. Исследовательский анализ данных\n",
    "3. Общий вывод"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bc5d710",
   "metadata": {},
   "source": [
    "## Обзор данных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0976cf22",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load\n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the read-only \"../input/\" directory\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "db240ea4",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: csv-to-sqlite in c:\\users\\nikita\\anaconda3\\envs\\da_practicum_env1\\lib\\site-packages (2.1.3)\n",
      "Requirement already satisfied: click in c:\\users\\nikita\\anaconda3\\envs\\da_practicum_env1\\lib\\site-packages (from csv-to-sqlite) (8.1.3)\n",
      "Requirement already satisfied: colorama in c:\\users\\nikita\\anaconda3\\envs\\da_practicum_env1\\lib\\site-packages (from click->csv-to-sqlite) (0.4.6)\n"
     ]
    }
   ],
   "source": [
    "# install translation from cvs to sqlite\n",
    "!pip install csv-to-sqlite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0d02f517",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import libraries\n",
    "import csv_to_sqlite\n",
    "import sqlite3\n",
    "import csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e27ee0fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# устанавливка опции display.max_colwidth равной None, что означает, \n",
    "# что ширина столбцов при выводе данных в DataFrame не будет ограничена максимальной длиной.\n",
    "\n",
    "pd.set_option('display.max_colwidth', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9b893707",
   "metadata": {},
   "outputs": [],
   "source": [
    "# downlaud dataframes\n",
    "funding_round = pd.read_csv(\"D:\\\\myuser\\\\Startup Investments\\\\funding_rounds.csv\", low_memory=False)\n",
    "acquisition = pd.read_csv(\"D:\\\\myuser\\\\Startup Investments\\\\acquisitions.csv\", low_memory=False)\n",
    "company = pd.read_csv(\"D:\\\\myuser\\\\Startup Investments\\\\objects.csv\", low_memory=False)\n",
    "people = pd.read_csv(\"D:\\\\myuser\\\\Startup Investments\\\\people.csv\", low_memory=False)\n",
    "education = pd.read_csv(\"D:\\\\myuser\\\\Startup Investments\\\\degrees.csv\", low_memory=False)\n",
    "investment = pd.read_csv(\"D:\\\\myuser\\\\Startup Investments\\\\investments.csv\", low_memory=False)\n",
    "fund = pd.read_csv(\"D:\\\\myuser\\\\Startup Investments\\\\funds.csv\", low_memory=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "85330c96",
   "metadata": {},
   "outputs": [],
   "source": [
    "# bringing dataframe formats to csv \n",
    "funding_round.to_csv('funding_round.csv', index=False)\n",
    "acquisition.to_csv('acquisition.csv', index=False)\n",
    "company.to_csv('company.csv', index=False)\n",
    "people.to_csv('people.csv', index=False)\n",
    "education.to_csv('education.csv', index=False)\n",
    "investment.to_csv('investment.csv', index=False)\n",
    "fund.to_csv('fund.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3a5c1593",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Written 943926 rows into 7 tables in 23.039 seconds\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "943926"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# translating dataframe formarts from csv to sqlite\n",
    "options=csv_to_sqlite.CsvOptions(typing_style='full',encoding='utf-8')\n",
    "input_name = ['funding_round.csv', 'acquisition.csv', \n",
    "              'company.csv', 'people.csv', 'education.csv',\n",
    "              'investment.csv', 'fund.csv']\n",
    "database_name = 'output.sqlite'\n",
    "if os.path.exists(database_name):\n",
    "    os.remove(database_name)\n",
    "csv_to_sqlite.write_csv(input_name, database_name, options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "25d8760b",
   "metadata": {},
   "outputs": [],
   "source": [
    "con=sqlite3.connect('output.sqlite')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fd1197a",
   "metadata": {},
   "source": [
    "### Выведем первые строки каждой таблицы и изучим значение столбцов"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f98bb2cd",
   "metadata": {},
   "source": [
    "#### Таблица acquisition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "eda3a05f",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "*\n",
    "FROM acquisition\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a3651666",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>id</th>\n",
       "      <th>acquisition_id</th>\n",
       "      <th>acquiring_object_id</th>\n",
       "      <th>acquired_object_id</th>\n",
       "      <th>term_code</th>\n",
       "      <th>price_amount</th>\n",
       "      <th>price_currency_code</th>\n",
       "      <th>acquired_at</th>\n",
       "      <th>source_url</th>\n",
       "      <th>source_description</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>c:11</td>\n",
       "      <td>c:10</td>\n",
       "      <td></td>\n",
       "      <td>20000000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>2007-05-30</td>\n",
       "      <td>http://venturebeat.com/2007/05/30/fox-interactive-confirms-purchase-of-photobucket-and-flektor/</td>\n",
       "      <td>Fox Interactive confirms purchase of Photobucket and Flektor</td>\n",
       "      <td>2007-05-31 22:19:54</td>\n",
       "      <td>2008-05-21 19:23:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>c:59</td>\n",
       "      <td>c:72</td>\n",
       "      <td>cash</td>\n",
       "      <td>60000000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>2007-07-01</td>\n",
       "      <td>http://www.techcrunch.com/2007/07/02/deal-is-confirmed-google-acquired-grandcentral/</td>\n",
       "      <td>Deal is Confirmed: Google Acquired GrandCentral</td>\n",
       "      <td>2007-07-03 08:14:50</td>\n",
       "      <td>2011-05-06 21:51:05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "      <td>c:24</td>\n",
       "      <td>c:132</td>\n",
       "      <td>cash</td>\n",
       "      <td>280000000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>2007-05-01</td>\n",
       "      <td>http://www.techcrunch.com/2007/05/30/cbs-acquires-lastfm-for-280m/</td>\n",
       "      <td>CBS Acquires Europeâs Last.fm for $280 million</td>\n",
       "      <td>2007-07-12 04:19:24</td>\n",
       "      <td>2008-05-19 04:48:50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>c:59</td>\n",
       "      <td>c:155</td>\n",
       "      <td>cash</td>\n",
       "      <td>100000000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>2007-06-01</td>\n",
       "      <td>http://techcrunch.com/2007/05/23/100-million-payday-for-feedburner-this-deal-is-confirmed/</td>\n",
       "      <td>$100 Million Payday For Feedburner  This Deal Is Confirmed</td>\n",
       "      <td>2007-07-13 09:52:59</td>\n",
       "      <td>2012-06-05 03:22:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>c:212</td>\n",
       "      <td>c:215</td>\n",
       "      <td>cash</td>\n",
       "      <td>25000000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>2007-07-01</td>\n",
       "      <td>http://blog.seattlepi.nwsource.com/venture/archives/118242.asp</td>\n",
       "      <td>seatlepi.com</td>\n",
       "      <td>2007-07-20 05:29:07</td>\n",
       "      <td>2008-02-25 00:23:47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  acquisition_id acquiring_object_id acquired_object_id term_code  \\\n",
       "0   1               1                c:11               c:10             \n",
       "1   2               7                c:59               c:72      cash   \n",
       "2   3               8                c:24              c:132      cash   \n",
       "3   4               9                c:59              c:155      cash   \n",
       "4   5              10               c:212              c:215      cash   \n",
       "\n",
       "   price_amount price_currency_code acquired_at  \\\n",
       "0    20000000.0                 USD  2007-05-30   \n",
       "1    60000000.0                 USD  2007-07-01   \n",
       "2   280000000.0                 USD  2007-05-01   \n",
       "3   100000000.0                 USD  2007-06-01   \n",
       "4    25000000.0                 USD  2007-07-01   \n",
       "\n",
       "                                                                                        source_url  \\\n",
       "0  http://venturebeat.com/2007/05/30/fox-interactive-confirms-purchase-of-photobucket-and-flektor/   \n",
       "1             http://www.techcrunch.com/2007/07/02/deal-is-confirmed-google-acquired-grandcentral/   \n",
       "2                               http://www.techcrunch.com/2007/05/30/cbs-acquires-lastfm-for-280m/   \n",
       "3       http://techcrunch.com/2007/05/23/100-million-payday-for-feedburner-this-deal-is-confirmed/   \n",
       "4                                   http://blog.seattlepi.nwsource.com/venture/archives/118242.asp   \n",
       "\n",
       "                                             source_description  \\\n",
       "0  Fox Interactive confirms purchase of Photobucket and Flektor   \n",
       "1               Deal is Confirmed: Google Acquired GrandCentral   \n",
       "2              CBS Acquires Europeâs Last.fm for $280 million   \n",
       "3   $100 Million Payday For Feedburner  This Deal Is Confirmed   \n",
       "4                                                  seatlepi.com   \n",
       "\n",
       "            created_at           updated_at  \n",
       "0  2007-05-31 22:19:54  2008-05-21 19:23:44  \n",
       "1  2007-07-03 08:14:50  2011-05-06 21:51:05  \n",
       "2  2007-07-12 04:19:24  2008-05-19 04:48:50  \n",
       "3  2007-07-13 09:52:59  2012-06-05 03:22:17  \n",
       "4  2007-07-20 05:29:07  2008-02-25 00:23:47  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1ce5269a",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "COUNT(*)\n",
    "FROM acquisition\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "604dce5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>COUNT(*)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>9562</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COUNT(*)\n",
       "0      9562"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1529d16f",
   "metadata": {},
   "source": [
    "В таблице 12-ть столбцов и 9562 строк:\n",
    "\n",
    "Дальнейшие запросы будут производится со следующими столбцами:\n",
    "- **id** — первичный ключ, идентификатор или уникальный номер покупки\n",
    "- **acquiring_company_id** — внешний ключ, ссылается на таблицу company — идентификатор компании-покупателя, то есть той, что покупает другую компанию;\n",
    "- **acquired_company_id** — внешний ключ, ссылается на таблицу company — идентификатор компании, которую покупают;\n",
    "- **term_code** — способ оплаты сделки\n",
    "   - cash — наличными;\n",
    "   - stock — акциями компании;\n",
    "   - cash_and_stock — смешанный тип оплаты: наличные и акции.\n",
    "- **price_amount** — сумма покупки в долларах\n",
    "- **acquired_at** —  дата совершения сделки\n",
    "- **created_at** —  дата и время создания записи в таблице\n",
    "- **updated_at** —  дата и время обновления записи в таблице"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe00ae31",
   "metadata": {},
   "source": [
    "#### Таблица company"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "13a7eee0",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "*\n",
    "FROM company\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "652f455d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>id</th>\n",
       "      <th>entity_type</th>\n",
       "      <th>entity_id</th>\n",
       "      <th>parent_id</th>\n",
       "      <th>name</th>\n",
       "      <th>normalized_name</th>\n",
       "      <th>permalink</th>\n",
       "      <th>category_code</th>\n",
       "      <th>status</th>\n",
       "      <th>founded_at</th>\n",
       "      <th>...</th>\n",
       "      <th>last_funding_at</th>\n",
       "      <th>funding_rounds</th>\n",
       "      <th>funding_total_usd</th>\n",
       "      <th>first_milestone_at</th>\n",
       "      <th>last_milestone_at</th>\n",
       "      <th>milestones</th>\n",
       "      <th>relationships</th>\n",
       "      <th>created_by</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c:1</td>\n",
       "      <td>Company</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td>Wetpaint</td>\n",
       "      <td>wetpaint</td>\n",
       "      <td>/company/wetpaint</td>\n",
       "      <td>web</td>\n",
       "      <td>operating</td>\n",
       "      <td>2005-10-17</td>\n",
       "      <td>...</td>\n",
       "      <td>2008-05-19</td>\n",
       "      <td>3</td>\n",
       "      <td>39750000.0</td>\n",
       "      <td>2010-09-05</td>\n",
       "      <td>2013-09-18</td>\n",
       "      <td>5</td>\n",
       "      <td>17</td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-05-25 06:51:27</td>\n",
       "      <td>2013-04-13 03:29:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c:10</td>\n",
       "      <td>Company</td>\n",
       "      <td>10</td>\n",
       "      <td></td>\n",
       "      <td>Flektor</td>\n",
       "      <td>flektor</td>\n",
       "      <td>/company/flektor</td>\n",
       "      <td>games_video</td>\n",
       "      <td>acquired</td>\n",
       "      <td></td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-05-31 21:11:51</td>\n",
       "      <td>2008-05-23 23:23:14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c:100</td>\n",
       "      <td>Company</td>\n",
       "      <td>100</td>\n",
       "      <td></td>\n",
       "      <td>There</td>\n",
       "      <td>there</td>\n",
       "      <td>/company/there</td>\n",
       "      <td>games_video</td>\n",
       "      <td>acquired</td>\n",
       "      <td></td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2003-02-01</td>\n",
       "      <td>2011-09-23</td>\n",
       "      <td>4</td>\n",
       "      <td>12</td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-08-06 23:52:45</td>\n",
       "      <td>2013-11-04 02:09:48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c:10000</td>\n",
       "      <td>Company</td>\n",
       "      <td>10000</td>\n",
       "      <td></td>\n",
       "      <td>MYWEBBO</td>\n",
       "      <td>mywebbo</td>\n",
       "      <td>/company/mywebbo</td>\n",
       "      <td>network_hosting</td>\n",
       "      <td>operating</td>\n",
       "      <td>2008-07-26</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>2008-08-24 16:51:57</td>\n",
       "      <td>2008-09-06 14:19:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c:10001</td>\n",
       "      <td>Company</td>\n",
       "      <td>10001</td>\n",
       "      <td></td>\n",
       "      <td>THE Movie Streamer</td>\n",
       "      <td>the movie streamer</td>\n",
       "      <td>/company/the-movie-streamer</td>\n",
       "      <td>games_video</td>\n",
       "      <td>operating</td>\n",
       "      <td>2008-07-26</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>2008-08-24 17:10:34</td>\n",
       "      <td>2008-09-06 14:19:18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id entity_type  entity_id parent_id                name  \\\n",
       "0      c:1     Company          1                      Wetpaint   \n",
       "1     c:10     Company         10                       Flektor   \n",
       "2    c:100     Company        100                         There   \n",
       "3  c:10000     Company      10000                       MYWEBBO   \n",
       "4  c:10001     Company      10001            THE Movie Streamer   \n",
       "\n",
       "      normalized_name                    permalink    category_code  \\\n",
       "0            wetpaint            /company/wetpaint              web   \n",
       "1             flektor             /company/flektor      games_video   \n",
       "2               there               /company/there      games_video   \n",
       "3             mywebbo             /company/mywebbo  network_hosting   \n",
       "4  the movie streamer  /company/the-movie-streamer      games_video   \n",
       "\n",
       "      status  founded_at  ... last_funding_at funding_rounds  \\\n",
       "0  operating  2005-10-17  ...      2008-05-19              3   \n",
       "1   acquired              ...                              0   \n",
       "2   acquired              ...                              0   \n",
       "3  operating  2008-07-26  ...                              0   \n",
       "4  operating  2008-07-26  ...                              0   \n",
       "\n",
       "  funding_total_usd first_milestone_at last_milestone_at  milestones  \\\n",
       "0        39750000.0         2010-09-05        2013-09-18           5   \n",
       "1               0.0                                                0   \n",
       "2               0.0         2003-02-01        2011-09-23           4   \n",
       "3               0.0                                                0   \n",
       "4               0.0                                                0   \n",
       "\n",
       "   relationships        created_by           created_at           updated_at  \n",
       "0             17  initial-importer  2007-05-25 06:51:27  2013-04-13 03:29:00  \n",
       "1              6  initial-importer  2007-05-31 21:11:51  2008-05-23 23:23:14  \n",
       "2             12  initial-importer  2007-08-06 23:52:45  2013-11-04 02:09:48  \n",
       "3              0                    2008-08-24 16:51:57  2008-09-06 14:19:18  \n",
       "4              0                    2008-08-24 17:10:34  2008-09-06 14:19:18  \n",
       "\n",
       "[5 rows x 40 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "36e74763",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "COUNT(*)\n",
    "FROM company\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f42e7b50",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>COUNT(*)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>462651</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COUNT(*)\n",
       "0    462651"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67fb41ef",
   "metadata": {},
   "source": [
    "В таблице 20-ть столбцов и 462651 строк:\n",
    "\n",
    "Дальнейшие запросы будут производится со следующими столбцами:\n",
    "- **id** — первичный ключ, идентификатор, или уникальный номер компании\n",
    "- **name** — название компании\n",
    "- **category_code** — категория деятельности компании, например\n",
    "   - news — специализируется на работе с новостями;\n",
    "   - social — специализируется на социальной работе.\n",
    "- **status** — статус компании\n",
    "   - acquired — приобретена;\n",
    "   - operating — действует;\n",
    "   - ipo — вышла на IPO;\n",
    "   - closed — перестала существовать\n",
    "- **founded_at** — дата основания компании  \n",
    "- **closed_at** — дата закрытия компании, которую указывают в том случае, если компании больше не существует\n",
    "- **domain** — домен сайта компании\n",
    "- **network_username** —  профиль фонда в корпоративной сети биржи\n",
    "- **country_code** —   код страны, например, USA для США, GBR для Великобритании\n",
    "- **investment_rounds** —   число раундов, в которых компания участвовала как инвестор\n",
    "- **funding_rounds** —   число раундов, в которых компания привлекала инвестиции\n",
    "- **funding_total** —   сумма привлечённых инвестиций в долларах\n",
    "- **milestones** —    количество важных этапов в истории компании\n",
    "- **created_at** —    дата и время создания записи в таблице\n",
    "- **updated_at** —    дата и время обновления записи в таблице\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f982d3e",
   "metadata": {},
   "source": [
    "#### Таблица education"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "888cf37c",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "*\n",
    "FROM education\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e0564f2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>id</th>\n",
       "      <th>object_id</th>\n",
       "      <th>degree_type</th>\n",
       "      <th>subject</th>\n",
       "      <th>institution</th>\n",
       "      <th>graduated_at</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>p:6117</td>\n",
       "      <td>MBA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>2008-02-19 03:17:36</td>\n",
       "      <td>2008-02-19 03:17:36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>p:6136</td>\n",
       "      <td>BA</td>\n",
       "      <td>English, French</td>\n",
       "      <td>Washington University, St. Louis</td>\n",
       "      <td>1990-01-01</td>\n",
       "      <td>2008-02-19 17:58:31</td>\n",
       "      <td>2008-02-25 00:23:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>p:6136</td>\n",
       "      <td>MS</td>\n",
       "      <td>Mass Communication</td>\n",
       "      <td>Boston University</td>\n",
       "      <td>1992-01-01</td>\n",
       "      <td>2008-02-19 17:58:31</td>\n",
       "      <td>2008-02-25 00:23:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>p:6005</td>\n",
       "      <td>MS</td>\n",
       "      <td>Internet Technology</td>\n",
       "      <td>University of Greenwich</td>\n",
       "      <td>2006-01-01</td>\n",
       "      <td>2008-02-19 23:40:40</td>\n",
       "      <td>2008-02-25 00:23:55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>p:5832</td>\n",
       "      <td>BCS</td>\n",
       "      <td>Computer Science, Psychology</td>\n",
       "      <td>Rice University</td>\n",
       "      <td></td>\n",
       "      <td>2008-02-20 05:28:09</td>\n",
       "      <td>2008-02-20 05:28:09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id object_id degree_type                       subject  \\\n",
       "0   1    p:6117         MBA                                 \n",
       "1   2    p:6136          BA               English, French   \n",
       "2   3    p:6136          MS            Mass Communication   \n",
       "3   4    p:6005          MS           Internet Technology   \n",
       "4   5    p:5832         BCS  Computer Science, Psychology   \n",
       "\n",
       "                        institution graduated_at           created_at  \\\n",
       "0                                                 2008-02-19 03:17:36   \n",
       "1  Washington University, St. Louis   1990-01-01  2008-02-19 17:58:31   \n",
       "2                 Boston University   1992-01-01  2008-02-19 17:58:31   \n",
       "3           University of Greenwich   2006-01-01  2008-02-19 23:40:40   \n",
       "4                   Rice University               2008-02-20 05:28:09   \n",
       "\n",
       "            updated_at  \n",
       "0  2008-02-19 03:17:36  \n",
       "1  2008-02-25 00:23:55  \n",
       "2  2008-02-25 00:23:55  \n",
       "3  2008-02-25 00:23:55  \n",
       "4  2008-02-20 05:28:09  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "73849b0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "COUNT(*)\n",
    "FROM education\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "450cf1fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>COUNT(*)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>109610</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COUNT(*)\n",
       "0    109610"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34a0fa35",
   "metadata": {},
   "source": [
    "В таблице 7 столбцов и 109610 строк:\n",
    "\n",
    "Дальнейшие запросы будут производится со следующими столбцами:\n",
    "- **id** — первичный ключ,уникальный номер записи с информацией об образовании\n",
    "- **person_id** — внешний ключ ссылается на таблицу people — идентификатор человека, информация о котором представлена в записи;\n",
    "- **degree_type** — учебная степень, например:\n",
    "    - BA — Bachelor of Arts — бакалавр гуманитарных наук;\n",
    "    - MS — Master of Science — магистр естественных наук.\n",
    "- **instituition** — учебное заведение, название университета\n",
    "- **graduated_at** — дата завершения обучения, выпуска\n",
    "- **created_at** — дата и время создания записи в таблице\n",
    "- **updated_at** — дата и время обновления записи в таблице"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de910660",
   "metadata": {},
   "source": [
    "#### Таблица fund"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "66a06d6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "*\n",
    "FROM fund\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9c2e27a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>id</th>\n",
       "      <th>fund_id</th>\n",
       "      <th>object_id</th>\n",
       "      <th>name</th>\n",
       "      <th>funded_at</th>\n",
       "      <th>raised_amount</th>\n",
       "      <th>raised_currency_code</th>\n",
       "      <th>source_url</th>\n",
       "      <th>source_description</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>f:371</td>\n",
       "      <td>Second Fund</td>\n",
       "      <td>2008-12-16</td>\n",
       "      <td>300000000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>http://www.pehub.com/26194/dfj-dragon-raising-second-fund/</td>\n",
       "      <td>peHub</td>\n",
       "      <td>2008-12-17 03:07:16</td>\n",
       "      <td>2008-12-17 03:07:16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>f:17</td>\n",
       "      <td>Sequoia Israel Fourth Fund</td>\n",
       "      <td>2008-12-17</td>\n",
       "      <td>200750000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>http://www.pehub.com/26725/sequoia-israel-raises-fourth-fund/</td>\n",
       "      <td>Sequoia Israel Raises Fourth Fund</td>\n",
       "      <td>2008-12-18 22:04:42</td>\n",
       "      <td>2008-12-18 22:04:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>f:951</td>\n",
       "      <td>Tenth fund</td>\n",
       "      <td>2008-08-11</td>\n",
       "      <td>650000000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>http://venturebeat.com/2008/08/11/interwest-closes-650m-fund/</td>\n",
       "      <td>Venture Beat</td>\n",
       "      <td>2008-12-31 09:47:51</td>\n",
       "      <td>2008-12-31 09:47:51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>f:192</td>\n",
       "      <td>New funds acquire</td>\n",
       "      <td></td>\n",
       "      <td>625000000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>http://venturebeat.com/2008/07/28/us-venture-partners-raises-625m-fund-for-new-investments/</td>\n",
       "      <td>U.S. Venture Partners raises $625M fund for new investments</td>\n",
       "      <td>2009-01-01 18:13:44</td>\n",
       "      <td>2009-01-01 18:16:27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>f:519</td>\n",
       "      <td>Third fund</td>\n",
       "      <td>2008-05-20</td>\n",
       "      <td>200000000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>http://venturebeat.com/2008/05/20/disneys-steamboat-ventures-looking-to-raise-200m-fund/</td>\n",
       "      <td>Venture Beat</td>\n",
       "      <td>2009-01-03 09:51:58</td>\n",
       "      <td>2013-09-03 16:34:54</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  fund_id object_id                        name   funded_at  \\\n",
       "0   1        1     f:371                 Second Fund  2008-12-16   \n",
       "1   4        4      f:17  Sequoia Israel Fourth Fund  2008-12-17   \n",
       "2   5        5     f:951                  Tenth fund  2008-08-11   \n",
       "3   6        6     f:192           New funds acquire               \n",
       "4   7        7     f:519                  Third fund  2008-05-20   \n",
       "\n",
       "   raised_amount raised_currency_code  \\\n",
       "0    300000000.0                  USD   \n",
       "1    200750000.0                  USD   \n",
       "2    650000000.0                  USD   \n",
       "3    625000000.0                  USD   \n",
       "4    200000000.0                  USD   \n",
       "\n",
       "                                                                                    source_url  \\\n",
       "0                                   http://www.pehub.com/26194/dfj-dragon-raising-second-fund/   \n",
       "1                                http://www.pehub.com/26725/sequoia-israel-raises-fourth-fund/   \n",
       "2                                http://venturebeat.com/2008/08/11/interwest-closes-650m-fund/   \n",
       "3  http://venturebeat.com/2008/07/28/us-venture-partners-raises-625m-fund-for-new-investments/   \n",
       "4     http://venturebeat.com/2008/05/20/disneys-steamboat-ventures-looking-to-raise-200m-fund/   \n",
       "\n",
       "                                            source_description  \\\n",
       "0                                                        peHub   \n",
       "1                            Sequoia Israel Raises Fourth Fund   \n",
       "2                                                 Venture Beat   \n",
       "3  U.S. Venture Partners raises $625M fund for new investments   \n",
       "4                                                 Venture Beat   \n",
       "\n",
       "            created_at           updated_at  \n",
       "0  2008-12-17 03:07:16  2008-12-17 03:07:16  \n",
       "1  2008-12-18 22:04:42  2008-12-18 22:04:42  \n",
       "2  2008-12-31 09:47:51  2008-12-31 09:47:51  \n",
       "3  2009-01-01 18:13:44  2009-01-01 18:16:27  \n",
       "4  2009-01-03 09:51:58  2013-09-03 16:34:54  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "23e6375a",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "COUNT(*)\n",
    "FROM fund\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "68e77131",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>COUNT(*)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1564</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COUNT(*)\n",
       "0      1564"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae8053c4",
   "metadata": {},
   "source": [
    "В таблице 7 столбцов и 109610 строк:\n",
    "\n",
    "Дальнейшие запросы будут производится со следующими столбцами:\n",
    "- **id** — первичный ключ, никальный номер венчурного фонда\n",
    "- **name** — название венчурного фонда\n",
    "- **founded_at** — дата основания фонда\n",
    "- **domain** — домен сайта фонда\n",
    "- **network_username** — профиль фонда в корпоративной сети биржи\n",
    "- **country_code** — код страны фонда\n",
    "- **investment_rounds** — число инвестиционных раундов, в которых фонд принимал участие\n",
    "- **invested_companies** — число компаний, в которые инвестировал фонд\n",
    "- **milestones** — количество важных этапов в истории фонда\n",
    "- **created_at** — дата и время создания записи в таблице\n",
    "- **updated_at** — дата и время обновления записи в таблице"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67e25808",
   "metadata": {},
   "source": [
    "#### Таблица funding_round"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "845f55a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "*\n",
    "FROM funding_round\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "2d9b8373",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>id</th>\n",
       "      <th>funding_round_id</th>\n",
       "      <th>object_id</th>\n",
       "      <th>funded_at</th>\n",
       "      <th>funding_round_type</th>\n",
       "      <th>funding_round_code</th>\n",
       "      <th>raised_amount_usd</th>\n",
       "      <th>raised_amount</th>\n",
       "      <th>raised_currency_code</th>\n",
       "      <th>pre_money_valuation_usd</th>\n",
       "      <th>...</th>\n",
       "      <th>post_money_valuation</th>\n",
       "      <th>post_money_currency_code</th>\n",
       "      <th>participants</th>\n",
       "      <th>is_first_round</th>\n",
       "      <th>is_last_round</th>\n",
       "      <th>source_url</th>\n",
       "      <th>source_description</th>\n",
       "      <th>created_by</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>c:4</td>\n",
       "      <td>2006-12-01</td>\n",
       "      <td>series-b</td>\n",
       "      <td>b</td>\n",
       "      <td>8500000.0</td>\n",
       "      <td>8500000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td></td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>http://www.marketingvox.com/archives/2006/12/29/digg-gets-85mm-in-funding/</td>\n",
       "      <td></td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-07-04 04:52:57</td>\n",
       "      <td>2008-02-27 23:14:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>c:5</td>\n",
       "      <td>2004-09-01</td>\n",
       "      <td>angel</td>\n",
       "      <td>angel</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-05-27 06:08:18</td>\n",
       "      <td>2013-06-28 20:07:23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>c:5</td>\n",
       "      <td>2005-05-01</td>\n",
       "      <td>series-a</td>\n",
       "      <td>a</td>\n",
       "      <td>12700000.0</td>\n",
       "      <td>12700000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>115000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>http://www.techcrunch.com/2007/11/02/jim-breyer-extra-500-million-round-for-facebook-a-total-fiction/</td>\n",
       "      <td>Jim Breyer: Extra $500 Million Round For Facebook A \"Total Fiction\"</td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-05-27 06:09:10</td>\n",
       "      <td>2013-06-28 20:07:23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>c:5</td>\n",
       "      <td>2006-04-01</td>\n",
       "      <td>series-b</td>\n",
       "      <td>b</td>\n",
       "      <td>27500000.0</td>\n",
       "      <td>27500000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>525000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>http://www.facebook.com/press/info.php?factsheet</td>\n",
       "      <td>Facebook Funding</td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-05-27 06:09:36</td>\n",
       "      <td>2013-06-28 20:07:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>c:7299</td>\n",
       "      <td>2006-05-01</td>\n",
       "      <td>series-b</td>\n",
       "      <td>b</td>\n",
       "      <td>10500000.0</td>\n",
       "      <td>10500000.0</td>\n",
       "      <td>USD</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td></td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>http://www.techcrunch.com/2006/05/14/photobucket-closes-105-from-trinity-ventures/</td>\n",
       "      <td>PhotoBucket Closes $10.5M From Trinity Ventures</td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-05-29 11:05:59</td>\n",
       "      <td>2008-04-16 17:09:12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  funding_round_id object_id   funded_at funding_round_type  \\\n",
       "0   1                 1       c:4  2006-12-01           series-b   \n",
       "1   2                 2       c:5  2004-09-01              angel   \n",
       "2   3                 3       c:5  2005-05-01           series-a   \n",
       "3   4                 4       c:5  2006-04-01           series-b   \n",
       "4   5                 5    c:7299  2006-05-01           series-b   \n",
       "\n",
       "  funding_round_code  raised_amount_usd  raised_amount raised_currency_code  \\\n",
       "0                  b          8500000.0      8500000.0                  USD   \n",
       "1              angel           500000.0       500000.0                  USD   \n",
       "2                  a         12700000.0     12700000.0                  USD   \n",
       "3                  b         27500000.0     27500000.0                  USD   \n",
       "4                  b         10500000.0     10500000.0                  USD   \n",
       "\n",
       "   pre_money_valuation_usd  ...  post_money_valuation  \\\n",
       "0                      0.0  ...                   0.0   \n",
       "1                      0.0  ...                   0.0   \n",
       "2              115000000.0  ...                   0.0   \n",
       "3              525000000.0  ...                   0.0   \n",
       "4                      0.0  ...                   0.0   \n",
       "\n",
       "  post_money_currency_code  participants  is_first_round is_last_round  \\\n",
       "0                                      2               0             0   \n",
       "1                      USD             2               0             1   \n",
       "2                      USD             3               0             0   \n",
       "3                      USD             4               0             0   \n",
       "4                                      2               0             0   \n",
       "\n",
       "                                                                                              source_url  \\\n",
       "0                             http://www.marketingvox.com/archives/2006/12/29/digg-gets-85mm-in-funding/   \n",
       "1                                                                                                          \n",
       "2  http://www.techcrunch.com/2007/11/02/jim-breyer-extra-500-million-round-for-facebook-a-total-fiction/   \n",
       "3                                                       http://www.facebook.com/press/info.php?factsheet   \n",
       "4                     http://www.techcrunch.com/2006/05/14/photobucket-closes-105-from-trinity-ventures/   \n",
       "\n",
       "                                                    source_description  \\\n",
       "0                                                                        \n",
       "1                                                                        \n",
       "2  Jim Breyer: Extra $500 Million Round For Facebook A \"Total Fiction\"   \n",
       "3                                                     Facebook Funding   \n",
       "4                      PhotoBucket Closes $10.5M From Trinity Ventures   \n",
       "\n",
       "         created_by           created_at           updated_at  \n",
       "0  initial-importer  2007-07-04 04:52:57  2008-02-27 23:14:29  \n",
       "1  initial-importer  2007-05-27 06:08:18  2013-06-28 20:07:23  \n",
       "2  initial-importer  2007-05-27 06:09:10  2013-06-28 20:07:23  \n",
       "3  initial-importer  2007-05-27 06:09:36  2013-06-28 20:07:24  \n",
       "4  initial-importer  2007-05-29 11:05:59  2008-04-16 17:09:12  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4efa58f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "COUNT(*)\n",
    "FROM funding_round\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "fd87af8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        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>COUNT(*)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>52928</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COUNT(*)\n",
       "0     52928"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec2cef31",
   "metadata": {},
   "source": [
    "В таблице 20-ть столбцов и 52928 строк:\n",
    "\n",
    "Дальнейшие запросы будут производится со следующими столбцами:\n",
    "- **id** — первичный ключ, уникальный номер инвестиционного раунда\n",
    "- **company_id** — внешний ключ,ссылается на таблицу company — уникальный номер компании, участвовавшей в инвестиционном раунде\n",
    "- **funded_at** — дата проведения раунда\n",
    "- **funding_round_type** — тип инвестиционного раунда, например:\n",
    "    - venture — венчурный раунд;\n",
    "    - angel — ангельский раунд;\n",
    "    - series_a — раунд А.\n",
    "- **raised_amount** — сумма инвестиций, которую привлекла компания в этом раунде в долларах\n",
    "- **pre_money_valuation** — предварительная, проведённая до инвестиций оценка стоимости компании в долларах\n",
    "- **participants** — количество участников инвестиционного раунда\n",
    "- **is_first_round** — является ли этот раунд первым для компании\n",
    "- **is_last_round** — является ли этот раунд последним для компании\n",
    "- **created_at** — дата и время создания записи в таблице\n",
    "- **updated_at** — дата и время обновления записи в таблице "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0eef66e",
   "metadata": {},
   "source": [
    "#### Таблица investment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "0a2f8629",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "*\n",
    "FROM investment\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "dd2f1180",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>id</th>\n",
       "      <th>funding_round_id</th>\n",
       "      <th>funded_object_id</th>\n",
       "      <th>investor_object_id</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>c:4</td>\n",
       "      <td>f:1</td>\n",
       "      <td>2007-07-04 04:52:57</td>\n",
       "      <td>2008-02-27 23:14:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>c:4</td>\n",
       "      <td>f:2</td>\n",
       "      <td>2007-07-04 04:52:57</td>\n",
       "      <td>2008-02-27 23:14:29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>c:5</td>\n",
       "      <td>f:4</td>\n",
       "      <td>2007-05-27 06:09:10</td>\n",
       "      <td>2013-06-28 20:07:23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>c:5</td>\n",
       "      <td>f:1</td>\n",
       "      <td>2007-05-27 06:09:36</td>\n",
       "      <td>2013-06-28 20:07:24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>c:5</td>\n",
       "      <td>f:5</td>\n",
       "      <td>2007-05-27 06:09:36</td>\n",
       "      <td>2013-06-28 20:07:24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id  funding_round_id funded_object_id investor_object_id  \\\n",
       "0   1                 1              c:4                f:1   \n",
       "1   2                 1              c:4                f:2   \n",
       "2   3                 3              c:5                f:4   \n",
       "3   4                 4              c:5                f:1   \n",
       "4   5                 4              c:5                f:5   \n",
       "\n",
       "            created_at           updated_at  \n",
       "0  2007-07-04 04:52:57  2008-02-27 23:14:29  \n",
       "1  2007-07-04 04:52:57  2008-02-27 23:14:29  \n",
       "2  2007-05-27 06:09:10  2013-06-28 20:07:23  \n",
       "3  2007-05-27 06:09:36  2013-06-28 20:07:24  \n",
       "4  2007-05-27 06:09:36  2013-06-28 20:07:24  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ac14b8e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "COUNT(*)\n",
    "FROM investment\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "cf042e5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead 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>COUNT(*)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>80902</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COUNT(*)\n",
       "0     80902"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c53d99f5",
   "metadata": {},
   "source": [
    "В таблице 6-ть столбцов и 80902 строк:\n",
    "\n",
    "Дальнейшие запросы будут производится со следующими столбцами:\n",
    "- **id** — первичный ключ, уникальный номер инвестиции\n",
    "- **funding_round_id** — внешний ключ,ссылается на таблицу funding_round — уникальный номер раунда инвестиции\n",
    "- **company_id** — внешний ключ, ссылается на таблицу company — уникальный номер компании-стартапа, в которую инвестируют\n",
    "- **fund_id** — внешний ключ, ссылается на таблицу fund — уникальный номер фонда, инвестирующего в компанию-стартап\n",
    "- **created_at** — дата и время создания записи в таблице\n",
    "- **updated_at** — дата и время обновления записи в таблице"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb4870d5",
   "metadata": {},
   "source": [
    "#### Таблица people"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "09fb7581",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "*\n",
    "FROM  people\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "afe8ea98",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>id</th>\n",
       "      <th>object_id</th>\n",
       "      <th>first_name</th>\n",
       "      <th>last_name</th>\n",
       "      <th>birthplace</th>\n",
       "      <th>affiliation_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>p:2</td>\n",
       "      <td>Ben</td>\n",
       "      <td>Elowitz</td>\n",
       "      <td></td>\n",
       "      <td>Blue Nile</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>p:3</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>Flaherty</td>\n",
       "      <td></td>\n",
       "      <td>Wetpaint</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>p:4</td>\n",
       "      <td>Raju</td>\n",
       "      <td>Vegesna</td>\n",
       "      <td></td>\n",
       "      <td>Zoho</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>p:5</td>\n",
       "      <td>Ian</td>\n",
       "      <td>Wenig</td>\n",
       "      <td></td>\n",
       "      <td>Zoho</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>p:6</td>\n",
       "      <td>Kevin</td>\n",
       "      <td>Rose</td>\n",
       "      <td>Redding, CA</td>\n",
       "      <td>i/o Ventures</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id object_id first_name last_name   birthplace affiliation_name\n",
       "0   1       p:2        Ben   Elowitz                     Blue Nile\n",
       "1   2       p:3      Kevin  Flaherty                      Wetpaint\n",
       "2   3       p:4       Raju   Vegesna                          Zoho\n",
       "3   4       p:5        Ian     Wenig                          Zoho\n",
       "4   5       p:6      Kevin      Rose  Redding, CA     i/o Ventures"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a28a6e70",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "COUNT(*)\n",
    "FROM people\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "502bc4d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>COUNT(*)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>226709</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COUNT(*)\n",
       "0    226709"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aaa4a40b",
   "metadata": {},
   "source": [
    "В таблице 7-мь столбцов и 226709 строк:\n",
    "\n",
    "Дальнейшие запросы будут производится со следующими столбцами:\n",
    "- **id** — первичный ключ,  уникальный номер сотрудника\n",
    "- **first_name** — имя сотрудника\n",
    "- **last_name** — фамилия сотрудника\n",
    "- **company_id** — внешний ключ, ссылается на таблицу company — уникальный номер компании-стартапа\n",
    "- **network_username** — профиль фонда в корпоративной сети биржи\n",
    "- **created_at** — дата и время создания записи в таблице\n",
    "- **updated_at** — дата и время обновления записи в таблице"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa070b1f",
   "metadata": {},
   "source": [
    "**Вывод** \n",
    "\n",
    "В представленных таблицах - информация о покупках одних компаний другими, информация о компаниях-стартапах, информация об уровне образования сотрудников компаний, информация о венчурных фондах, информация о раундах инвестиций, информация об инвестициях венчурных фондов в компании-стартапы, информация о сотрудниках компаний-стартапов. Предварительно данных достаточно для анализа."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "464055dc",
   "metadata": {},
   "source": [
    "## Исследовательский анализ данных"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d997b45",
   "metadata": {},
   "source": [
    "В рамках дальнейшего анализа изучим и проверим полученные данные. Найдём особенности. Соберём наблюдения в один общий вывод."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7ddad7d",
   "metadata": {},
   "source": [
    "###  Запрос №1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c269600",
   "metadata": {},
   "source": [
    "Отобразим все записи из таблицы company по компаниям, которые закрылись"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "97b89e1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "*\n",
    "FROM company\n",
    "WHERE status = 'closed'\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "77354774",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\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>id</th>\n",
       "      <th>entity_type</th>\n",
       "      <th>entity_id</th>\n",
       "      <th>parent_id</th>\n",
       "      <th>name</th>\n",
       "      <th>normalized_name</th>\n",
       "      <th>permalink</th>\n",
       "      <th>category_code</th>\n",
       "      <th>status</th>\n",
       "      <th>founded_at</th>\n",
       "      <th>...</th>\n",
       "      <th>last_funding_at</th>\n",
       "      <th>funding_rounds</th>\n",
       "      <th>funding_total_usd</th>\n",
       "      <th>first_milestone_at</th>\n",
       "      <th>last_milestone_at</th>\n",
       "      <th>milestones</th>\n",
       "      <th>relationships</th>\n",
       "      <th>created_by</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c:10012</td>\n",
       "      <td>Company</td>\n",
       "      <td>10012</td>\n",
       "      <td></td>\n",
       "      <td>moviestring.com</td>\n",
       "      <td>moviestring</td>\n",
       "      <td>/company/moviestring-com</td>\n",
       "      <td>games_video</td>\n",
       "      <td>closed</td>\n",
       "      <td>2008-08-22</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td>2008-08-24 23:07:26</td>\n",
       "      <td>2010-10-01 00:12:22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c:1006</td>\n",
       "      <td>Company</td>\n",
       "      <td>1006</td>\n",
       "      <td></td>\n",
       "      <td>Youlicit</td>\n",
       "      <td>youlicit</td>\n",
       "      <td>/company/youlicit</td>\n",
       "      <td>web</td>\n",
       "      <td>closed</td>\n",
       "      <td>2006-09-01</td>\n",
       "      <td>...</td>\n",
       "      <td>2008-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-10-02 09:45:00</td>\n",
       "      <td>2013-10-19 10:39:54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c:10062</td>\n",
       "      <td>Company</td>\n",
       "      <td>10062</td>\n",
       "      <td></td>\n",
       "      <td>Workstir</td>\n",
       "      <td>workstir</td>\n",
       "      <td>/company/workstir</td>\n",
       "      <td>web</td>\n",
       "      <td>closed</td>\n",
       "      <td></td>\n",
       "      <td>...</td>\n",
       "      <td>2009-06-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2008-11-12</td>\n",
       "      <td>2009-04-01</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td></td>\n",
       "      <td>2008-08-25 18:26:25</td>\n",
       "      <td>2013-10-16 09:57:06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c:10092</td>\n",
       "      <td>Company</td>\n",
       "      <td>10092</td>\n",
       "      <td></td>\n",
       "      <td>FairSoftware</td>\n",
       "      <td>fairsoftware</td>\n",
       "      <td>/company/fairsoftware</td>\n",
       "      <td>web</td>\n",
       "      <td>closed</td>\n",
       "      <td>2007-01-01</td>\n",
       "      <td>...</td>\n",
       "      <td>2007-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>2009-01-16</td>\n",
       "      <td>2009-01-16</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td>2008-08-25 23:41:44</td>\n",
       "      <td>2013-10-15 04:33:46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c:101</td>\n",
       "      <td>Company</td>\n",
       "      <td>101</td>\n",
       "      <td></td>\n",
       "      <td>SellABand</td>\n",
       "      <td>sellaband</td>\n",
       "      <td>/company/sellaband</td>\n",
       "      <td>games_video</td>\n",
       "      <td>closed</td>\n",
       "      <td>2006-08-01</td>\n",
       "      <td>...</td>\n",
       "      <td>2008-04-08</td>\n",
       "      <td>1</td>\n",
       "      <td>5000000.0</td>\n",
       "      <td>2008-03-10</td>\n",
       "      <td>2012-05-10</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-07-04 05:29:56</td>\n",
       "      <td>2010-04-29 21:39:39</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id entity_type  entity_id parent_id             name normalized_name  \\\n",
       "0  c:10012     Company      10012            moviestring.com     moviestring   \n",
       "1   c:1006     Company       1006                   Youlicit        youlicit   \n",
       "2  c:10062     Company      10062                   Workstir        workstir   \n",
       "3  c:10092     Company      10092               FairSoftware    fairsoftware   \n",
       "4    c:101     Company        101                  SellABand       sellaband   \n",
       "\n",
       "                  permalink category_code  status  founded_at  ...  \\\n",
       "0  /company/moviestring-com   games_video  closed  2008-08-22  ...   \n",
       "1         /company/youlicit           web  closed  2006-09-01  ...   \n",
       "2         /company/workstir           web  closed              ...   \n",
       "3     /company/fairsoftware           web  closed  2007-01-01  ...   \n",
       "4        /company/sellaband   games_video  closed  2006-08-01  ...   \n",
       "\n",
       "  last_funding_at funding_rounds funding_total_usd first_milestone_at  \\\n",
       "0                              0               0.0                      \n",
       "1      2008-01-01              1               0.0                      \n",
       "2      2009-06-01              1               0.0         2008-11-12   \n",
       "3      2007-01-01              1          100000.0         2009-01-16   \n",
       "4      2008-04-08              1         5000000.0         2008-03-10   \n",
       "\n",
       "  last_milestone_at  milestones  relationships        created_by  \\\n",
       "0                             0              1                     \n",
       "1                             0              5  initial-importer   \n",
       "2        2009-04-01           2              4                     \n",
       "3        2009-01-16           1              1                     \n",
       "4        2012-05-10           5              3  initial-importer   \n",
       "\n",
       "            created_at           updated_at  \n",
       "0  2008-08-24 23:07:26  2010-10-01 00:12:22  \n",
       "1  2007-10-02 09:45:00  2013-10-19 10:39:54  \n",
       "2  2008-08-25 18:26:25  2013-10-16 09:57:06  \n",
       "3  2008-08-25 23:41:44  2013-10-15 04:33:46  \n",
       "4  2007-07-04 05:29:56  2010-04-29 21:39:39  \n",
       "\n",
       "[5 rows x 40 columns]"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "403ac5f7",
   "metadata": {},
   "source": [
    "###  Запрос №2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "815bfeab",
   "metadata": {},
   "source": [
    "Отобразим количество привлечённых средств для новостных компаний США. Используем данные из таблицы company. Отсортируем таблицу по убыванию значений в поле funding_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "718ebad8",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "c.funding_total_usd\n",
    "FROM company AS c\n",
    "WHERE\n",
    "c.category_code = 'news'\n",
    "AND c.country_code = 'USA'\n",
    "ORDER BY c.funding_total_usd DESC\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "29876400",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\n",
       "        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>funding_total_usd</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>622552813.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>250000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>160500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>128000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>126500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>215 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     funding_total_usd\n",
       "0          622552813.0\n",
       "1          250000000.0\n",
       "2          160500000.0\n",
       "3          128000000.0\n",
       "4          126500000.0\n",
       "..                 ...\n",
       "210                0.0\n",
       "211                0.0\n",
       "212                0.0\n",
       "213                0.0\n",
       "214                0.0\n",
       "\n",
       "[215 rows x 1 columns]"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0859d519",
   "metadata": {},
   "source": [
    "###  Запрос №3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3dc0a103",
   "metadata": {},
   "source": [
    "Найдём общую сумму сделок по покупке одних компаний другими в долларах. Отберём сделки, которые осуществлялись только за наличные с 2011 по 2013 год включительно."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "fae335e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "SUM(a.price_amount)\n",
    "FROM \n",
    "acquisition AS a\n",
    "WHERE term_code = 'cash'\n",
    "AND (a.acquired_at > '2011-01-01' AND a.acquired_at <= '2013-12-31')\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "b43feeba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>SUM(a.price_amount)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.390772e+11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SUM(a.price_amount)\n",
       "0         1.390772e+11"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef16cced",
   "metadata": {},
   "source": [
    "Общая сумма сделок за наличные по покупке одних компаний другими в долларах с 2011 по 2013 год включительно составила 139077200000 USD"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf0dcbb6",
   "metadata": {},
   "source": [
    "###  Запрос №4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55840156",
   "metadata": {},
   "source": [
    "Отобразим имя, фамилию и названия аккаунтов людей в поле network_username, у которых названия аккаунтов начинаются на 'Silver'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "9442b175",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "p.first_name,\n",
    "p.last_name,\n",
    "p.affiliation_name\n",
    "FROM \n",
    "people AS p\n",
    "WHERE p.affiliation_name LIKE 'Silver%'\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "a1c06343",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>first_name</th>\n",
       "      <th>last_name</th>\n",
       "      <th>affiliation_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mike</td>\n",
       "      <td>Eynon</td>\n",
       "      <td>Silver Tail Systems</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>John</td>\n",
       "      <td>O'Farrell</td>\n",
       "      <td>Silver Spring Networks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Raj</td>\n",
       "      <td>Gajwani</td>\n",
       "      <td>SilverDock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Madhav</td>\n",
       "      <td>SBSS</td>\n",
       "      <td>Silverlink Communications</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Craig</td>\n",
       "      <td>Stouffer</td>\n",
       "      <td>Silver Peak Systems</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  first_name  last_name           affiliation_name\n",
       "0       Mike      Eynon        Silver Tail Systems\n",
       "1       John  O'Farrell     Silver Spring Networks\n",
       "2        Raj    Gajwani                 SilverDock\n",
       "3     Madhav       SBSS  Silverlink Communications\n",
       "4      Craig   Stouffer        Silver Peak Systems"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5fd19af",
   "metadata": {},
   "source": [
    "###  Запрос №5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "719f4c7f",
   "metadata": {},
   "source": [
    "Выведим на экран всю информацию о людях, у которых названия аккаунтов в поле network_username содержат подстроку 'money', а фамилия начинается на 'K'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "c05867c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "*\n",
    "FROM \n",
    "people\n",
    "WHERE \n",
    "affiliation_name LIKE '%money%'\n",
    "AND last_name LIKE 'K%'\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "ad361955",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>id</th>\n",
       "      <th>object_id</th>\n",
       "      <th>first_name</th>\n",
       "      <th>last_name</th>\n",
       "      <th>birthplace</th>\n",
       "      <th>affiliation_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>134417</td>\n",
       "      <td>p:165626</td>\n",
       "      <td>Vijay</td>\n",
       "      <td>Khubchandani</td>\n",
       "      <td>India</td>\n",
       "      <td>MoneyLeo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id object_id first_name     last_name birthplace affiliation_name\n",
       "0  134417  p:165626      Vijay  Khubchandani      India         MoneyLeo"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0b97c7f",
   "metadata": {},
   "source": [
    "###  Запрос №6"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a28770c7",
   "metadata": {},
   "source": [
    "Для каждой страны отобразим общую сумму привлечённых инвестиций, которые получили компании, зарегистрированные в этой стране. Страну, в которой зарегистрирована компания, определим по коду страны. Отсортируем данные по убыванию суммы."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "16b9abce",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "country_code, \n",
    "SUM(funding_total_usd)\n",
    "FROM\n",
    "company \n",
    "GROUP BY country_code\n",
    "ORDER BY SUM(funding_total_usd) DESC\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "5c91be57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>country_code</th>\n",
       "      <th>SUM(funding_total_usd)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>USA</td>\n",
       "      <td>3.105884e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GBR</td>\n",
       "      <td>1.770562e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td></td>\n",
       "      <td>1.085592e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CHN</td>\n",
       "      <td>1.068974e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CAN</td>\n",
       "      <td>9.866362e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>ARA</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>AND</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>AIA</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>AGO</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>AFG</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>178 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    country_code  SUM(funding_total_usd)\n",
       "0            USA            3.105884e+11\n",
       "1            GBR            1.770562e+10\n",
       "2                           1.085592e+10\n",
       "3            CHN            1.068974e+10\n",
       "4            CAN            9.866362e+09\n",
       "..           ...                     ...\n",
       "173          ARA            0.000000e+00\n",
       "174          AND            0.000000e+00\n",
       "175          AIA            0.000000e+00\n",
       "176          AGO            0.000000e+00\n",
       "177          AFG            0.000000e+00\n",
       "\n",
       "[178 rows x 2 columns]"
      ]
     },
     "execution_count": 154,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07aff522",
   "metadata": {},
   "source": [
    "Больше всего привлечённых инвестиций в компании, которые зарегистрированны в USA, сумма инвестиций составила 310588400000.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3564c56d",
   "metadata": {},
   "source": [
    "###  Запрос №7"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fd7ed8b",
   "metadata": {},
   "source": [
    "Составим таблицу, в которую войдёт дата проведения раунда, а также минимальное и максимальное значения суммы инвестиций, привлечённых в эту дату.\n",
    "Оставим в итоговой таблице только те записи, в которых минимальное значение суммы инвестиций не равно нулю и не равно максимальному значению."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "04b32993",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "fr.funded_at,\n",
    "MIN(fr.raised_amount),\n",
    "MAX(fr.raised_amount)\n",
    "FROM\n",
    "funding_round AS fr\n",
    "GROUP BY(fr.funded_at)\n",
    "HAVING\n",
    "MIN(fr.raised_amount) != 0\n",
    "AND MIN(fr.raised_amount) != MAX(fr.raised_amount)\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "007bed5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>funded_at</th>\n",
       "      <th>MIN(fr.raised_amount)</th>\n",
       "      <th>MAX(fr.raised_amount)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1960-11-01</td>\n",
       "      <td>75000.0</td>\n",
       "      <td>861030.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1995-01-01</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>10000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1999-03-01</td>\n",
       "      <td>750000.0</td>\n",
       "      <td>25000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1999-04-01</td>\n",
       "      <td>1360000.0</td>\n",
       "      <td>16000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1999-05-01</td>\n",
       "      <td>1500000.0</td>\n",
       "      <td>5000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1281</th>\n",
       "      <td>2013-11-10</td>\n",
       "      <td>240000.0</td>\n",
       "      <td>13000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td>2013-11-13</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>79000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td>2013-11-17</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>7500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1284</th>\n",
       "      <td>2013-11-28</td>\n",
       "      <td>111500.0</td>\n",
       "      <td>90000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1285</th>\n",
       "      <td>2013-12-08</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>364000000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1286 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       funded_at  MIN(fr.raised_amount)  MAX(fr.raised_amount)\n",
       "0     1960-11-01                75000.0               861030.0\n",
       "1     1995-01-01              2000000.0             10000000.0\n",
       "2     1999-03-01               750000.0             25000000.0\n",
       "3     1999-04-01              1360000.0             16000000.0\n",
       "4     1999-05-01              1500000.0              5000000.0\n",
       "...          ...                    ...                    ...\n",
       "1281  2013-11-10               240000.0             13000000.0\n",
       "1282  2013-11-13                50000.0             79000000.0\n",
       "1283  2013-11-17               250000.0              7500000.0\n",
       "1284  2013-11-28               111500.0             90000000.0\n",
       "1285  2013-12-08               250000.0            364000000.0\n",
       "\n",
       "[1286 rows x 3 columns]"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9a927d0",
   "metadata": {},
   "source": [
    "###  Запрос №8"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "026554b1",
   "metadata": {},
   "source": [
    "Создадим поле с категориями:\n",
    "   - Для фондов, которые инвестируют в 100 и более компаний, назначим категорию high_activity.\n",
    "   - Для фондов, которые инвестируют в 20 и более компаний до 100, назначим категорию middle_activity.\n",
    "   - Если количество инвестируемых компаний фонда не достигает 20, назначим категорию low_activity.\n",
    "   \n",
    "Отобразим все поля таблицы fund и новое поле с категориями."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "65bb224f",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT *,\n",
    "                                       (CASE\n",
    "                                       WHEN invested_companies>=100 THEN 'high_activity'\n",
    "                                       WHEN invested_companies BETWEEN 20 AND 100 THEN 'middle_activity'\n",
    "                                       WHEN invested_companies<20 THEN 'low_activity' \n",
    "                                       END) AS activity\n",
    "                                       FROM company\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "b295a8f8",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>id</th>\n",
       "      <th>entity_type</th>\n",
       "      <th>entity_id</th>\n",
       "      <th>parent_id</th>\n",
       "      <th>name</th>\n",
       "      <th>normalized_name</th>\n",
       "      <th>permalink</th>\n",
       "      <th>category_code</th>\n",
       "      <th>status</th>\n",
       "      <th>founded_at</th>\n",
       "      <th>...</th>\n",
       "      <th>funding_rounds</th>\n",
       "      <th>funding_total_usd</th>\n",
       "      <th>first_milestone_at</th>\n",
       "      <th>last_milestone_at</th>\n",
       "      <th>milestones</th>\n",
       "      <th>relationships</th>\n",
       "      <th>created_by</th>\n",
       "      <th>created_at</th>\n",
       "      <th>updated_at</th>\n",
       "      <th>activity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c:1</td>\n",
       "      <td>Company</td>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td>Wetpaint</td>\n",
       "      <td>wetpaint</td>\n",
       "      <td>/company/wetpaint</td>\n",
       "      <td>web</td>\n",
       "      <td>operating</td>\n",
       "      <td>2005-10-17</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>39750000.0</td>\n",
       "      <td>2010-09-05</td>\n",
       "      <td>2013-09-18</td>\n",
       "      <td>5</td>\n",
       "      <td>17</td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-05-25 06:51:27</td>\n",
       "      <td>2013-04-13 03:29:00</td>\n",
       "      <td>low_activity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>c:10</td>\n",
       "      <td>Company</td>\n",
       "      <td>10</td>\n",
       "      <td></td>\n",
       "      <td>Flektor</td>\n",
       "      <td>flektor</td>\n",
       "      <td>/company/flektor</td>\n",
       "      <td>games_video</td>\n",
       "      <td>acquired</td>\n",
       "      <td></td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-05-31 21:11:51</td>\n",
       "      <td>2008-05-23 23:23:14</td>\n",
       "      <td>low_activity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c:100</td>\n",
       "      <td>Company</td>\n",
       "      <td>100</td>\n",
       "      <td></td>\n",
       "      <td>There</td>\n",
       "      <td>there</td>\n",
       "      <td>/company/there</td>\n",
       "      <td>games_video</td>\n",
       "      <td>acquired</td>\n",
       "      <td></td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2003-02-01</td>\n",
       "      <td>2011-09-23</td>\n",
       "      <td>4</td>\n",
       "      <td>12</td>\n",
       "      <td>initial-importer</td>\n",
       "      <td>2007-08-06 23:52:45</td>\n",
       "      <td>2013-11-04 02:09:48</td>\n",
       "      <td>low_activity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>c:10000</td>\n",
       "      <td>Company</td>\n",
       "      <td>10000</td>\n",
       "      <td></td>\n",
       "      <td>MYWEBBO</td>\n",
       "      <td>mywebbo</td>\n",
       "      <td>/company/mywebbo</td>\n",
       "      <td>network_hosting</td>\n",
       "      <td>operating</td>\n",
       "      <td>2008-07-26</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>2008-08-24 16:51:57</td>\n",
       "      <td>2008-09-06 14:19:18</td>\n",
       "      <td>low_activity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c:10001</td>\n",
       "      <td>Company</td>\n",
       "      <td>10001</td>\n",
       "      <td></td>\n",
       "      <td>THE Movie Streamer</td>\n",
       "      <td>the movie streamer</td>\n",
       "      <td>/company/the-movie-streamer</td>\n",
       "      <td>games_video</td>\n",
       "      <td>operating</td>\n",
       "      <td>2008-07-26</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td>2008-08-24 17:10:34</td>\n",
       "      <td>2008-09-06 14:19:18</td>\n",
       "      <td>low_activity</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        id entity_type  entity_id parent_id                name  \\\n",
       "0      c:1     Company          1                      Wetpaint   \n",
       "1     c:10     Company         10                       Flektor   \n",
       "2    c:100     Company        100                         There   \n",
       "3  c:10000     Company      10000                       MYWEBBO   \n",
       "4  c:10001     Company      10001            THE Movie Streamer   \n",
       "\n",
       "      normalized_name                    permalink    category_code  \\\n",
       "0            wetpaint            /company/wetpaint              web   \n",
       "1             flektor             /company/flektor      games_video   \n",
       "2               there               /company/there      games_video   \n",
       "3             mywebbo             /company/mywebbo  network_hosting   \n",
       "4  the movie streamer  /company/the-movie-streamer      games_video   \n",
       "\n",
       "      status  founded_at  ... funding_rounds funding_total_usd  \\\n",
       "0  operating  2005-10-17  ...              3        39750000.0   \n",
       "1   acquired              ...              0               0.0   \n",
       "2   acquired              ...              0               0.0   \n",
       "3  operating  2008-07-26  ...              0               0.0   \n",
       "4  operating  2008-07-26  ...              0               0.0   \n",
       "\n",
       "  first_milestone_at last_milestone_at milestones  relationships  \\\n",
       "0         2010-09-05        2013-09-18          5             17   \n",
       "1                                               0              6   \n",
       "2         2003-02-01        2011-09-23          4             12   \n",
       "3                                               0              0   \n",
       "4                                               0              0   \n",
       "\n",
       "         created_by           created_at           updated_at      activity  \n",
       "0  initial-importer  2007-05-25 06:51:27  2013-04-13 03:29:00  low_activity  \n",
       "1  initial-importer  2007-05-31 21:11:51  2008-05-23 23:23:14  low_activity  \n",
       "2  initial-importer  2007-08-06 23:52:45  2013-11-04 02:09:48  low_activity  \n",
       "3                    2008-08-24 16:51:57  2008-09-06 14:19:18  low_activity  \n",
       "4                    2008-08-24 17:10:34  2008-09-06 14:19:18  low_activity  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d781a444",
   "metadata": {},
   "source": [
    "###  Запрос №9"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e26ebd5",
   "metadata": {},
   "source": [
    "Для каждой из категорий, назначенных в предыдущем задании, посчитаем округлённое до ближайшего целого числа среднее количество инвестиционных раундов, в которых фонд принимал участие. Выведим на экран категории и среднее число инвестиционных раундов. Отсортируем таблицу по возрастанию среднего."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "3c9c9ec2",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT \n",
    "       CASE\n",
    "           WHEN invested_companies>=100 THEN 'high_activity'\n",
    "           WHEN invested_companies>=20 THEN 'middle_activity'\n",
    "           ELSE 'low_activity'\n",
    "       END AS activity,\n",
    "       ROUND(AVG(investment_rounds)) AS count_round\n",
    "FROM company\n",
    "GROUP BY activity\n",
    "ORDER BY count_round;\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "ee290ec7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>activity</th>\n",
       "      <th>count_round</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>low_activity</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>middle_activity</td>\n",
       "      <td>50.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>high_activity</td>\n",
       "      <td>252.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          activity  count_round\n",
       "0     low_activity          0.0\n",
       "1  middle_activity         50.0\n",
       "2    high_activity        252.0"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2336e03d",
   "metadata": {},
   "source": [
    "###  Запрос №10"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c45ec7e",
   "metadata": {},
   "source": [
    "Проанализируем, в каких странах находятся фонды, которые чаще всего инвестируют в стартапы. \n",
    "Для каждой страны посчитаем минимальное, максимальное и среднее число компаний, в которые инвестировали фонды этой страны, основанные с 2005 по 2008 год включительно. Исключим страны с фондами, у которых минимальное число компаний, получивших инвестиции, равно нулю. \n",
    "Выгрузим самых активных стран-инвесторов: отсортируем таблицу по среднему количеству компаний от большего к меньшему. Затем добавим сортировку по коду страны в лексикографическом порядке."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "724e200a",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "country_code,\n",
    "MIN(invested_companies),\n",
    "MAX(invested_companies),\n",
    "AVG(invested_companies) AS AVG \n",
    "FROM\n",
    "company\n",
    "WHERE \n",
    "founded_at >= '2005-01-01' AND founded_at <= '2008-12-31'\n",
    "GROUP BY country_code\n",
    "HAVING MIN(invested_companies) >0\n",
    "ORDER BY AVG  DESC,country_code;\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "68bad6c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>country_code</th>\n",
       "      <th>MIN(invested_companies)</th>\n",
       "      <th>MAX(invested_companies)</th>\n",
       "      <th>AVG</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>GIB</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BHR</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country_code  MIN(invested_companies)  MAX(invested_companies)  AVG\n",
       "0          GIB                        7                        7  7.0\n",
       "1          BHR                        1                        1  1.0"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3803de0f",
   "metadata": {},
   "source": [
    "В Гибралтаре и Бахрейне находятся фонды, которые чаще всего инвестируют в стартапы."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f60d8d49",
   "metadata": {},
   "source": [
    "###  Запрос №11"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6a42d41",
   "metadata": {},
   "source": [
    "Составим список с уникальными названиями закрытых компаний, для которых первый раунд финансирования оказался последним."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "1cd68284",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "WITH \n",
    "HH AS (SELECT\n",
    "      c.name AS company_name,\n",
    "      c.id AS id_\n",
    "      FROM company AS c\n",
    "      WHERE status = 'closed'),\n",
    " \n",
    "GG AS (SELECT\n",
    "      fr.object_id AS id_ \n",
    "      FROM funding_round AS fr\n",
    "      WHERE is_first_round = 1\n",
    "      AND is_last_round = 1)\n",
    " \n",
    "SELECT \n",
    "DISTINCT(HH.company_name)\n",
    "FROM HH\n",
    "INNER JOIN GG ON HH.id_ = GG.id_\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "a327a4e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>company_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Youlicit</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Workstir</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FairSoftware</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SellABand</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HammerKit</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   company_name\n",
       "0      Youlicit\n",
       "1      Workstir\n",
       "2  FairSoftware\n",
       "3     SellABand\n",
       "4     HammerKit"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97239e37",
   "metadata": {},
   "source": [
    "В представленных закрытых компаниях первый раунд финансирования оказался последним.\n",
    "- Youlicit\n",
    "- Workstir\n",
    "- FairSoftware\n",
    "- SellABand\n",
    "- HammerKit"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0863a34f",
   "metadata": {},
   "source": [
    "###  Запрос №12"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "133a8f0a",
   "metadata": {},
   "source": [
    "Выгрузим таблицу, в которой будут такие поля:\n",
    "\n",
    "- название компании-покупателя;\n",
    "- сумма сделки;\n",
    "- название компании, которую купили;\n",
    "- сумма инвестиций, вложенных в купленную компанию;\n",
    "- доля, которая отображает, во сколько раз сумма покупки превысила сумму вложенных в компанию инвестиций, округлённая до ближайшего целого числа.\n",
    "\n",
    "Не будем учитывать те сделки, в которых сумма покупки равна нулю. Если сумма инвестиций в компанию равна нулю, исключим такую компанию из таблицы. \n",
    "\n",
    "Отсортируем таблицу по сумме сделки от большей к меньшей, а затем по названию купленной компании в лексикографическом порядке. Ограничем таблицу первыми десятью записями."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "f2d3fe05",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "c.name AS company_buyer,\n",
    "a.price_amount AS price,\n",
    "v.name AS company_seller,\n",
    "v.funding_total_usd AS invest_sum,\n",
    "ROUND(a.price_amount/v.funding_total_usd)\n",
    "FROM acquisition AS a\n",
    "JOIN company AS c ON a.acquiring_object_id = c.id\n",
    "JOIN company AS v ON a.acquired_object_id = v.id\n",
    "WHERE a.price_amount > 0\n",
    "AND  v.funding_total_usd > 0\n",
    "\n",
    "ORDER BY price DESC, company_seller\n",
    "\n",
    "LIMIT 10;\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "aa1c778d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>company_buyer</th>\n",
       "      <th>price</th>\n",
       "      <th>company_seller</th>\n",
       "      <th>invest_sum</th>\n",
       "      <th>ROUND(a.price_amount/v.funding_total_usd)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Microsoft</td>\n",
       "      <td>8.500000e+09</td>\n",
       "      <td>Skype</td>\n",
       "      <td>76805032.0</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Scout Labs</td>\n",
       "      <td>4.900000e+09</td>\n",
       "      <td>Varian Semiconductor Equipment Associates</td>\n",
       "      <td>4800000.0</td>\n",
       "      <td>1021.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Broadcom</td>\n",
       "      <td>3.700000e+09</td>\n",
       "      <td>Aeluros</td>\n",
       "      <td>7970000.0</td>\n",
       "      <td>464.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Broadcom</td>\n",
       "      <td>3.700000e+09</td>\n",
       "      <td>NetLogic Microsystems</td>\n",
       "      <td>188527015.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Level 3 Communications</td>\n",
       "      <td>3.000000e+09</td>\n",
       "      <td>Global Crossing</td>\n",
       "      <td>41000000.0</td>\n",
       "      <td>73.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            company_buyer         price  \\\n",
       "0               Microsoft  8.500000e+09   \n",
       "1              Scout Labs  4.900000e+09   \n",
       "2                Broadcom  3.700000e+09   \n",
       "3                Broadcom  3.700000e+09   \n",
       "4  Level 3 Communications  3.000000e+09   \n",
       "\n",
       "                              company_seller   invest_sum  \\\n",
       "0                                      Skype   76805032.0   \n",
       "1  Varian Semiconductor Equipment Associates    4800000.0   \n",
       "2                                    Aeluros    7970000.0   \n",
       "3                      NetLogic Microsystems  188527015.0   \n",
       "4                            Global Crossing   41000000.0   \n",
       "\n",
       "   ROUND(a.price_amount/v.funding_total_usd)  \n",
       "0                                      111.0  \n",
       "1                                     1021.0  \n",
       "2                                      464.0  \n",
       "3                                       20.0  \n",
       "4                                       73.0  "
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cefe877",
   "metadata": {},
   "source": [
    "###  Запрос №13"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e28dbe96",
   "metadata": {},
   "source": [
    "Выгрузим таблицу, в которую войдут названия компаний из категории social, получившие финансирование с 2010 по 2013 год включительно. Проверим, чтобы сумма инвестиций не равна нулю. Выведим также номер месяца, в котором проходил раунд финансирования."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "1a570594",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "SELECT\n",
    "    c.name,\n",
    "    CAST(strftime('%m', fr.funded_at) AS int) AS month\n",
    "FROM\n",
    "    company AS c\n",
    "LEFT OUTER JOIN\n",
    "    funding_round AS fr ON c.id = fr.object_id\n",
    "WHERE\n",
    "    category_code = 'social'\n",
    "    AND fr.raised_amount > 0\n",
    "    AND fr.funded_at BETWEEN '2010-01-01' AND '2013-12-31';\n",
    "    '''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "1ed90750",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>name</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gopogo</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CrushBlvd</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Collective Bias</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RuffWire</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Get.com</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>741</th>\n",
       "      <td>LockerDome</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>742</th>\n",
       "      <td>LockerDome</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>743</th>\n",
       "      <td>LockerDome</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>744</th>\n",
       "      <td>Horrance</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>745</th>\n",
       "      <td>ChatterBlock</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>746 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                name  month\n",
       "0             gopogo      4\n",
       "1          CrushBlvd      1\n",
       "2    Collective Bias      4\n",
       "3           RuffWire      6\n",
       "4            Get.com      9\n",
       "..               ...    ...\n",
       "741       LockerDome      4\n",
       "742       LockerDome      6\n",
       "743       LockerDome      3\n",
       "744         Horrance      7\n",
       "745     ChatterBlock      9\n",
       "\n",
       "[746 rows x 2 columns]"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71bb62b9",
   "metadata": {},
   "source": [
    "###  Запрос №14"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cce3821",
   "metadata": {},
   "source": [
    "Отберём данные по месяцам с 2010 по 2013 год, когда проходили инвестиционные раунды. Сгруппируем данные по номеру месяца и получим таблицу, в которой будут поля:\n",
    "\n",
    "- номер месяца, в котором проходили раунды;\n",
    "- количество уникальных названий фондов из США, которые инвестировали в этом месяце;\n",
    "- количество компаний, купленных за этот месяц;\n",
    "- общая сумма сделок по покупкам в этом месяце."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "4199e164",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "WITH \n",
    "DD AS (\n",
    "    SELECT\n",
    "        STRFTIME('%m', fr.funded_at) AS month,\n",
    "        COUNT(DISTINCT f.id) AS fund_count\n",
    "    FROM \n",
    "        funding_round AS fr\n",
    "    LEFT JOIN investment AS i ON fr.id = i.funding_round_id\n",
    "    LEFT JOIN fund AS f ON i.funded_object_id = f.id\n",
    "    LEFT JOIN company AS c ON i.investor_object_id = c.id\n",
    "    WHERE \n",
    "        STRFTIME('%Y', fr.funded_at) BETWEEN '2010' AND '2013'\n",
    "        AND c.country_code = 'USA'\n",
    "    GROUP BY month\n",
    "),\n",
    "HH AS (\n",
    "    SELECT\n",
    "        STRFTIME('%m', a.acquired_at) AS month,\n",
    "        COUNT(a.acquired_object_id) AS buy_company_count,\n",
    "        SUM(a.price_amount) AS total_sum\n",
    "    FROM \n",
    "        acquisition AS a\n",
    "    WHERE \n",
    "        STRFTIME('%Y', a.acquired_at) BETWEEN '2010' AND '2013'\n",
    "    GROUP BY month\n",
    ")\n",
    "\n",
    "SELECT\n",
    "    DD.month,\n",
    "    DD.fund_count,\n",
    "    HH.buy_company_count,\n",
    "    HH.total_sum\n",
    "FROM \n",
    "    DD\n",
    "LEFT JOIN \n",
    "    HH ON DD.month = HH.month;\n",
    "\n",
    "    '''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "31142881",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>month</th>\n",
       "      <th>fund_count</th>\n",
       "      <th>buy_company_count</th>\n",
       "      <th>total_sum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>01</td>\n",
       "      <td>0</td>\n",
       "      <td>605</td>\n",
       "      <td>2.712098e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>02</td>\n",
       "      <td>0</td>\n",
       "      <td>422</td>\n",
       "      <td>4.152996e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>03</td>\n",
       "      <td>0</td>\n",
       "      <td>467</td>\n",
       "      <td>5.969051e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>04</td>\n",
       "      <td>0</td>\n",
       "      <td>419</td>\n",
       "      <td>3.060131e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>05</td>\n",
       "      <td>0</td>\n",
       "      <td>543</td>\n",
       "      <td>8.688131e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>06</td>\n",
       "      <td>0</td>\n",
       "      <td>542</td>\n",
       "      <td>5.446979e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>07</td>\n",
       "      <td>0</td>\n",
       "      <td>497</td>\n",
       "      <td>5.008458e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>08</td>\n",
       "      <td>0</td>\n",
       "      <td>462</td>\n",
       "      <td>7.800402e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>09</td>\n",
       "      <td>0</td>\n",
       "      <td>504</td>\n",
       "      <td>7.065387e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>480</td>\n",
       "      <td>5.024669e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>422</td>\n",
       "      <td>4.851931e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>437</td>\n",
       "      <td>4.033359e+10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   month  fund_count  buy_company_count     total_sum\n",
       "0     01           0                605  2.712098e+10\n",
       "1     02           0                422  4.152996e+10\n",
       "2     03           0                467  5.969051e+10\n",
       "3     04           0                419  3.060131e+10\n",
       "4     05           0                543  8.688131e+10\n",
       "5     06           0                542  5.446979e+10\n",
       "6     07           0                497  5.008458e+10\n",
       "7     08           0                462  7.800402e+10\n",
       "8     09           0                504  7.065387e+10\n",
       "9     10           0                480  5.024669e+10\n",
       "10    11           0                422  4.851931e+10\n",
       "11    12           0                437  4.033359e+10"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dda77f15",
   "metadata": {},
   "source": [
    "###  Запрос №15"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2664d43b",
   "metadata": {},
   "source": [
    "Составим сводную таблицу и выведим среднюю сумму инвестиций для стран, в которых есть стартапы, зарегистрированные в 2011, 2012 и 2013 годах. Данные за каждый год должны быть в отдельном поле. Отсортируем таблицу по среднему значению инвестиций за 2011 год от большего к меньшему."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "44fe1fa3",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = '''\n",
    "WITH \n",
    "inv_2011 AS (\n",
    "    SELECT \n",
    "        c.country_code,\n",
    "        AVG(c.funding_total_usd) AS avg_invest_2011\n",
    "    FROM \n",
    "        company AS c\n",
    "    WHERE \n",
    "        strftime('%Y', c.founded_at) = '2011'\n",
    "    GROUP BY \n",
    "        c.country_code\n",
    "),\n",
    "inv_2012 AS (\n",
    "    SELECT \n",
    "        c.country_code,\n",
    "        AVG(c.funding_total_usd) AS avg_invest_2012\n",
    "    FROM \n",
    "        company AS c\n",
    "    WHERE \n",
    "        strftime('%Y', c.founded_at) = '2012'\n",
    "    GROUP BY \n",
    "        c.country_code\n",
    "),\n",
    "inv_2013 AS (\n",
    "    SELECT \n",
    "        c.country_code,\n",
    "        AVG(c.funding_total_usd) AS avg_invest_2013\n",
    "    FROM \n",
    "        company AS c\n",
    "    WHERE \n",
    "        strftime('%Y', c.founded_at) = '2013'\n",
    "    GROUP BY \n",
    "        c.country_code\n",
    ")\n",
    "SELECT \n",
    "    inv_2011.country_code,\n",
    "    inv_2011.avg_invest_2011,\n",
    "    inv_2012.avg_invest_2012,\n",
    "    inv_2013.avg_invest_2013\n",
    "FROM \n",
    "    inv_2011\n",
    "INNER JOIN \n",
    "    inv_2012 ON inv_2011.country_code = inv_2012.country_code\n",
    "INNER JOIN \n",
    "    inv_2013 ON inv_2011.country_code = inv_2013.country_code\n",
    "ORDER BY \n",
    "    inv_2011.avg_invest_2011 DESC;\n",
    "\n",
    "\n",
    "    '''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "9a738331",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        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>country_code</th>\n",
       "      <th>avg_invest_2011</th>\n",
       "      <th>avg_invest_2012</th>\n",
       "      <th>avg_invest_2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PER</td>\n",
       "      <td>4.000000e+06</td>\n",
       "      <td>4.100000e+04</td>\n",
       "      <td>1.666667e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>USA</td>\n",
       "      <td>2.195878e+06</td>\n",
       "      <td>1.181421e+06</td>\n",
       "      <td>1.071700e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HKG</td>\n",
       "      <td>2.062903e+06</td>\n",
       "      <td>2.195735e+05</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PHL</td>\n",
       "      <td>1.750000e+06</td>\n",
       "      <td>3.970588e+03</td>\n",
       "      <td>2.500000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ARE</td>\n",
       "      <td>1.636190e+06</td>\n",
       "      <td>1.972222e+05</td>\n",
       "      <td>3.533333e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>SAU</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>SVN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.396160e+05</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>UGA</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.040000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>VEN</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1.400000e+05</td>\n",
       "      <td>1.250000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>VNM</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>9.090909e+06</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>80 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   country_code  avg_invest_2011  avg_invest_2012  avg_invest_2013\n",
       "0           PER     4.000000e+06     4.100000e+04     1.666667e+04\n",
       "1           USA     2.195878e+06     1.181421e+06     1.071700e+06\n",
       "2           HKG     2.062903e+06     2.195735e+05     0.000000e+00\n",
       "3           PHL     1.750000e+06     3.970588e+03     2.500000e+03\n",
       "4           ARE     1.636190e+06     1.972222e+05     3.533333e+04\n",
       "..          ...              ...              ...              ...\n",
       "75          SAU     0.000000e+00     0.000000e+00     0.000000e+00\n",
       "76          SVN     0.000000e+00     2.396160e+05     0.000000e+00\n",
       "77          UGA     0.000000e+00     0.000000e+00     6.040000e+04\n",
       "78          VEN     0.000000e+00     1.400000e+05     1.250000e+04\n",
       "79          VNM     0.000000e+00     9.090909e+06     0.000000e+00\n",
       "\n",
       "[80 rows x 4 columns]"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_sql_query(query, con = con)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "035863c5",
   "metadata": {},
   "source": [
    "В 2011 г. лидерами-странами по среднему значению инвестиций в стартапы стали:\n",
    "\n",
    "1. PER 4 000 000\n",
    "2. USA 2195878\n",
    "3. HKG 2062903"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10738772",
   "metadata": {},
   "source": [
    "## Общий вывод"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d14709d",
   "metadata": {},
   "source": [
    "Мы произвели анализ предоставленной базы данных. В представленных таблицах - информация о покупках одних компаний другими,о компаниях-стартапах,информация о венчурных фондах и т.д. Предварительно данных достаточно для анализа.\n",
    "\n",
    "Найденные особенности по исследованным данным:\n",
    "\n",
    "- Общая сумма сделок за наличные по покупке одних компаний другими в долларах с 2011 по 2013 год включительно составила 139077200000 USD\n",
    "- Больше всего привлечённых инвестиций в компании, которые зарегистрированны в USA, сумма инвестиций составила 310588400000\n",
    "- В Гибралтаре и Бахрейне находятся фонды, которые чаще всего инвестируют в стартапы.\n",
    "- В представленных закрытых компаниях первый раунд финансирования оказался последним.\n",
    "  - Youlicit\n",
    "  - Workstir\n",
    "  - FairSoftware\n",
    "  - SellABand\n",
    "  - HammerKit\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "- В 2011 г. лидерами-странами по среднему значению инвестиций в стартапы стали:\n",
    "  1. PER 4 000 000\n",
    "  2. USA 2195878\n",
    "  3. HKG 2062903"
   ]
  }
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