diff --git a/.gitignore b/.gitignore
index ae7cc92..43024ce 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,7 +1,5 @@
-.~lock*
 .mypy_cache
 .venv
 __pycache__
 .env
-*.docx
 data*.csv
\ No newline at end of file
diff --git a/README.md b/README.md
deleted file mode 100644
index a468b45..0000000
--- a/README.md
+++ /dev/null
@@ -1,21 +0,0 @@
-# СПБ ГУП «ИАЦ»
-
-## Тестовое задание для Python-разработчика (дата аналитика)
-
-Задание: [Task.md](https://git.dm1sh.ru/dm1sh/iac_test/src/branch/main/Task.md)
-
-- Скрипт для парсинга и работа с данными: [rosseti_parser](https://git.dm1sh.ru/dm1sh/iac_test/src/branch/main/rosseti_parser)
-
-    Модуль можно запустить командой `python -m rosseti_parser`, или импортировать из него необходимые методы и использовать где-то ещё
-
-- Анализ данных: [analysis.ipynb](https://git.dm1sh.ru/dm1sh/iac_test/raw/branch/main/analysis.ipynb) 
-    
-    Необходимо скачать (платформа пока не поддерживает отображение ноутбука). Для запуска, установить библиотеки из `requirements.dev.txt`
-
-- Визуализация: [Yandex DataLens](https://datalens.yandex/kq0ymfuy5w7e9)
-    
-    Простенький дашборд с картой точек, хитмапом и несколькими графиками
-
-- Создание базы данных, API и docker: [parser_api](https://git.dm1sh.ru/dm1sh/iac_test/src/branch/main/parser_api)
-
-    FastAPI приложение, запускающее в дополнительном потоке периодическое обновление данных в базе.
diff --git a/Task.md b/Task.md
deleted file mode 100644
index da1655b..0000000
--- a/Task.md
+++ /dev/null
@@ -1,82 +0,0 @@
-**СПБ ГУП «ИАЦ»**
-
-**Тестовое задание для Python-разработчика (дата аналитика)**
-
-О компании:
-
-Государственное унитарное предприятие, работающее в области
-информатизации и информационного обеспечения органов государственной
-власти Санкт-Петербурга и других организаций, а также предоставления
-услуг в сфере создания и использования современных информационных и
-телекоммуникационных систем, средств и технологий 
-
-Более подробно о нас: <https://iac.spb.ru/>
-
-Мы на Хабре: <https://career.habr.com/companies/iac-spb>
-
-**Текст задания:**
-
-**- Парсинг**
-
-Считывание таблицы с сайта <https://rosseti-lenenergo.ru/planned_work/>
-
-![](media/image1.png){width="6.818295056867892in"
-height="2.37117125984252in"}
-
-Фильтр по времени - период текущей недели (текущий день и неделя вперед)
-
--   Успешное чтение необходимых полей на сайте и их сохранение в
-    pandas.DataFrame
-
--   Переключение между страницами и совершение полной выгрузки
-    ![](media/image2.png){width="2.468441601049869in"
-    height="0.49993766404199474in"}
-
--   Настройка автоматического запуска скрипта по расписанию
-
-**- Работа с данными**
-
--   Парсинг столбца Улица (разбиение строки на отдельные адреса)
-
--   Геокод адресов через
-    <https://petersburg.ru/mainPortal/api_services/view/2223> и
-    сохранение building_id найденных зданий
-
--   Запись результата в csv файл
-
-**- Анализ данных и Визуализация**
-
--   Выполнить в свободной форме на основе данных, полученных ранее
-
-В дополнение к скрипту можно сделать дашборд на [Yandex DataLens
-/Grafana](https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwiCrdStlbKBAxViSPEDHcw0B4kQFnoECB0QAQ&url=https%3A%2F%2Fdatalens.yandex.ru%2F&usg=AOvVaw3gsVaz_KTvGMRtFZrsXAGk&opi=89978449)
-
-**\*Создание базы данных**
-
--   Вместо сохранения результата в csv, развернуть базу данных и
-    сохранять результаты в неё (PostgreSQL, Clickhouse, MongoDB)
-
--   (Можно сделать скелет с подключением и записью в бд на локалхосте)
-
-**\*API**
-
--   Написать API к базе данных или csv-файлу на FastAPI
-
-**\*\*Docker**
-
--   Оборачивание всей сделанной работы в docker-compose
-
--   При первоначальной настройке и запуске компоуза парсер начнет
-    работать и собирать данные в БД / csv. Доступ к данным
-    осуществляется по API.
-
-Результаты проделанной работы залить на Github и прислать на
-[tg:Faneagain](https://t.me/faneagain)
-
-//При проблемах с парсингом для выполнения остальных задач можно
-попросить готовый набор данных
-
-Задания помеченные «**\***, **\*\***» будут оцениваться как
-дополнительные.
-
-Удачи!
diff --git a/analysis.ipynb b/analysis.ipynb
deleted file mode 100644
index 5e762dc..0000000
--- a/analysis.ipynb
+++ /dev/null
@@ -1,1521 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Parsing"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "from rosseti_parser import RossetiParser"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Parse Rosseti site or load data from csv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Read from \"./data.csv\"\n"
-     ]
-    }
-   ],
-   "source": [
-    "import os\n",
-    "\n",
-    "file_path = './data.csv'\n",
-    "\n",
-    "if os.path.isfile(file_path):\n",
-    "    parser = RossetiParser(file_path=file_path)\n",
-    "else:\n",
-    "    parser = RossetiParser()\n",
-    "    parser.save_df(file_path)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "From 2023-09-21 for 7 days with 296 records\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(parser)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = parser.df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Parse street dataframe column and split row by it"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "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>index</th>\n",
-       "      <th>Регион РФ (область, край, город фед. значения, округ)</th>\n",
-       "      <th>Административный район</th>\n",
-       "      <th>Населённый пункт</th>\n",
-       "      <th>Улица</th>\n",
-       "      <th>Плановая дата начала отключения электроснабжения</th>\n",
-       "      <th>Плановое время начала отключения электроснабжения</th>\n",
-       "      <th>Плановая дата восстановления отключения электроснабжения</th>\n",
-       "      <th>Плановое время восстановления отключения электроснабжения</th>\n",
-       "      <th>Филиал</th>\n",
-       "      <th>РЭС</th>\n",
-       "      <th>Комментарий</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0</td>\n",
-       "      <td>Ленинградская область</td>\n",
-       "      <td>Тосненский район</td>\n",
-       "      <td>п. Рябово</td>\n",
-       "      <td>Мысленская,Заречная</td>\n",
-       "      <td>28-09-2023</td>\n",
-       "      <td>17:00</td>\n",
-       "      <td>28-09-2023</td>\n",
-       "      <td>18:00</td>\n",
-       "      <td>Гатчинские ЭС</td>\n",
-       "      <td>Тосненский РЭС</td>\n",
-       "      <td>В связи с производством оперативных переключен...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>1</td>\n",
-       "      <td>Санкт-Петербург</td>\n",
-       "      <td>Фрунзенский район</td>\n",
-       "      <td>г. Санкт-Петербург</td>\n",
-       "      <td>ул. Димитрова  д. 12</td>\n",
-       "      <td>28-09-2023</td>\n",
-       "      <td>11:00</td>\n",
-       "      <td>28-09-2023</td>\n",
-       "      <td>17:00</td>\n",
-       "      <td>Кабельная сеть</td>\n",
-       "      <td>Невский РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1</td>\n",
-       "      <td>Санкт-Петербург</td>\n",
-       "      <td>Фрунзенский район</td>\n",
-       "      <td>г. Санкт-Петербург</td>\n",
-       "      <td>ул. Димитрова  к.1</td>\n",
-       "      <td>28-09-2023</td>\n",
-       "      <td>11:00</td>\n",
-       "      <td>28-09-2023</td>\n",
-       "      <td>17:00</td>\n",
-       "      <td>Кабельная сеть</td>\n",
-       "      <td>Невский РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>1</td>\n",
-       "      <td>Санкт-Петербург</td>\n",
-       "      <td>Фрунзенский район</td>\n",
-       "      <td>г. Санкт-Петербург</td>\n",
-       "      <td>ул. Димитрова  лит.А</td>\n",
-       "      <td>28-09-2023</td>\n",
-       "      <td>11:00</td>\n",
-       "      <td>28-09-2023</td>\n",
-       "      <td>17:00</td>\n",
-       "      <td>Кабельная сеть</td>\n",
-       "      <td>Невский РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>1</td>\n",
-       "      <td>Санкт-Петербург</td>\n",
-       "      <td>Фрунзенский район</td>\n",
-       "      <td>г. Санкт-Петербург</td>\n",
-       "      <td>д. 16  к.1</td>\n",
-       "      <td>28-09-2023</td>\n",
-       "      <td>11:00</td>\n",
-       "      <td>28-09-2023</td>\n",
-       "      <td>17:00</td>\n",
-       "      <td>Кабельная сеть</td>\n",
-       "      <td>Невский РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1989</th>\n",
-       "      <td>295</td>\n",
-       "      <td>Ленинградская область</td>\n",
-       "      <td>Гатчинский район</td>\n",
-       "      <td>Антропшино, г. Коммунар, д. Покровское, Пудомя...</td>\n",
-       "      <td>Гамболовский проезд Парковая д.3</td>\n",
-       "      <td>21-09-2023</td>\n",
-       "      <td>00:00</td>\n",
-       "      <td>21-09-2023</td>\n",
-       "      <td>07:00</td>\n",
-       "      <td>Южные электрические сети</td>\n",
-       "      <td>Пушкинский РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1990</th>\n",
-       "      <td>295</td>\n",
-       "      <td>Ленинградская область</td>\n",
-       "      <td>Гатчинский район</td>\n",
-       "      <td>Антропшино, г. Коммунар, д. Покровское, Пудомя...</td>\n",
-       "      <td>Гамболовский проезд Садоводство Славяночка-2</td>\n",
-       "      <td>21-09-2023</td>\n",
-       "      <td>00:00</td>\n",
-       "      <td>21-09-2023</td>\n",
-       "      <td>07:00</td>\n",
-       "      <td>Южные электрические сети</td>\n",
-       "      <td>Пушкинский РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1991</th>\n",
-       "      <td>295</td>\n",
-       "      <td>Ленинградская область</td>\n",
-       "      <td>Гатчинский район</td>\n",
-       "      <td>Антропшино, г. Коммунар, д. Покровское, Пудомя...</td>\n",
-       "      <td>Гамболовский проезд Славяночка-3</td>\n",
-       "      <td>21-09-2023</td>\n",
-       "      <td>00:00</td>\n",
-       "      <td>21-09-2023</td>\n",
-       "      <td>07:00</td>\n",
-       "      <td>Южные электрические сети</td>\n",
-       "      <td>Пушкинский РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1992</th>\n",
-       "      <td>295</td>\n",
-       "      <td>Ленинградская область</td>\n",
-       "      <td>Гатчинский район</td>\n",
-       "      <td>Антропшино, г. Коммунар, д. Покровское, Пудомя...</td>\n",
-       "      <td>Гамболовский проезд КП Павловские Дачи</td>\n",
-       "      <td>21-09-2023</td>\n",
-       "      <td>00:00</td>\n",
-       "      <td>21-09-2023</td>\n",
-       "      <td>07:00</td>\n",
-       "      <td>Южные электрические сети</td>\n",
-       "      <td>Пушкинский РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1993</th>\n",
-       "      <td>295</td>\n",
-       "      <td>Ленинградская область</td>\n",
-       "      <td>Гатчинский район</td>\n",
-       "      <td>Антропшино, г. Коммунар, д. Покровское, Пудомя...</td>\n",
-       "      <td>Гамболовский проезд</td>\n",
-       "      <td>21-09-2023</td>\n",
-       "      <td>00:00</td>\n",
-       "      <td>21-09-2023</td>\n",
-       "      <td>07:00</td>\n",
-       "      <td>Южные электрические сети</td>\n",
-       "      <td>Пушкинский РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1994 rows × 12 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "      index  ...                                        Комментарий\n",
-       "0         0  ...  В связи с производством оперативных переключен...\n",
-       "1         1  ...                                                NaN\n",
-       "2         1  ...                                                NaN\n",
-       "3         1  ...                                                NaN\n",
-       "4         1  ...                                                NaN\n",
-       "...     ...  ...                                                ...\n",
-       "1989    295  ...                                                NaN\n",
-       "1990    295  ...                                                NaN\n",
-       "1991    295  ...                                                NaN\n",
-       "1992    295  ...                                                NaN\n",
-       "1993    295  ...                                                NaN\n",
-       "\n",
-       "[1994 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from rosseti_parser import split_addresses\n",
-    "\n",
-    "df = split_addresses(df)\n",
-    "\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Fetch `Building_ID` and coordinates from Geocoder API"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from rosseti_parser import async_fetch_building_ids\n",
-    "\n",
-    "file_path = 'data_with_building_id.csv'\n",
-    "\n",
-    "if os.path.isfile(file_path):\n",
-    "    df = pd.read_csv(file_path)\n",
-    "else:\n",
-    "    df = await async_fetch_building_ids(df)\n",
-    "    df.to_csv('./data_with_building_id.csv', index=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 1994 entries, 0 to 1993\n",
-      "Data columns (total 15 columns):\n",
-      " #   Column                                                     Non-Null Count  Dtype  \n",
-      "---  ------                                                     --------------  -----  \n",
-      " 0   index                                                      1994 non-null   int64  \n",
-      " 1   Регион РФ (область, край, город фед. значения, округ)      1992 non-null   object \n",
-      " 2   Административный район                                     1994 non-null   object \n",
-      " 3   Населённый пункт                                           1994 non-null   object \n",
-      " 4   Улица                                                      1865 non-null   object \n",
-      " 5   Плановая дата начала отключения электроснабжения           1994 non-null   object \n",
-      " 6   Плановое время начала отключения электроснабжения          1994 non-null   object \n",
-      " 7   Плановая дата восстановления отключения электроснабжения   1994 non-null   object \n",
-      " 8   Плановое время восстановления отключения электроснабжения  1994 non-null   object \n",
-      " 9   Филиал                                                     1993 non-null   object \n",
-      " 10  РЭС                                                        1993 non-null   object \n",
-      " 11  Комментарий                                                793 non-null    object \n",
-      " 12  ID здания                                                  624 non-null    float64\n",
-      " 13  Широта                                                     624 non-null    float64\n",
-      " 14  Долгота                                                    624 non-null    float64\n",
-      "dtypes: float64(3), int64(1), object(11)\n",
-      "memory usage: 233.8+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "df.info()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Run dataframe preprocessing"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from rosseti_parser import preprocess_df, COL_NS, ICOL_NS, preprocess_read_df\n",
-    "\n",
-    "file_path = 'data_preprocessed.csv'\n",
-    "\n",
-    "if os.path.isfile(file_path):\n",
-    "    df = pd.read_csv(file_path)\n",
-    "    df = preprocess_read_df(df)\n",
-    "else:\n",
-    "    df = preprocess_df(df)\n",
-    "    df.to_csv('./data_preprocessed.csv', index=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 1994 entries, 0 to 1993\n",
-      "Data columns (total 13 columns):\n",
-      " #   Column       Non-Null Count  Dtype         \n",
-      "---  ------       --------------  -----         \n",
-      " 0   index        1994 non-null   int64         \n",
-      " 1   region       1992 non-null   object        \n",
-      " 2   area         1994 non-null   object        \n",
-      " 3   town         1994 non-null   object        \n",
-      " 4   street       1865 non-null   object        \n",
-      " 5   branch       1993 non-null   object        \n",
-      " 6   res          1993 non-null   object        \n",
-      " 7   comment      793 non-null    object        \n",
-      " 8   building_id  624 non-null    float64       \n",
-      " 9   lat          624 non-null    float64       \n",
-      " 10  lng          624 non-null    float64       \n",
-      " 11  start        1994 non-null   datetime64[ns]\n",
-      " 12  finish       1994 non-null   datetime64[ns]\n",
-      "dtypes: datetime64[ns](2), float64(3), int64(1), object(7)\n",
-      "memory usage: 202.6+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "df.info()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Group dataframe rows by Rosseti table indexes "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from rosseti_parser import group_by_index\n",
-    "\n",
-    "igr_df = group_by_index(df)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "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>region</th>\n",
-       "      <th>area</th>\n",
-       "      <th>town</th>\n",
-       "      <th>street</th>\n",
-       "      <th>branch</th>\n",
-       "      <th>res</th>\n",
-       "      <th>comment</th>\n",
-       "      <th>building_id</th>\n",
-       "      <th>lat</th>\n",
-       "      <th>lng</th>\n",
-       "      <th>start</th>\n",
-       "      <th>finish</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>index</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Ленинградская область</td>\n",
-       "      <td>Тосненский район</td>\n",
-       "      <td>п. Рябово</td>\n",
-       "      <td>[Мысленская,Заречная]</td>\n",
-       "      <td>Гатчинские ЭС</td>\n",
-       "      <td>Тосненский РЭС</td>\n",
-       "      <td>В связи с производством оперативных переключен...</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2023-09-28 17:00:00</td>\n",
-       "      <td>2023-09-28 18:00:00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Санкт-Петербург</td>\n",
-       "      <td>Фрунзенский район</td>\n",
-       "      <td>г. Санкт-Петербург</td>\n",
-       "      <td>[ул. Димитрова  д. 12, ул. Димитрова  к.1, ул....</td>\n",
-       "      <td>Кабельная сеть</td>\n",
-       "      <td>Невский РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>[46292.0, nan, nan, nan, nan, nan, nan, nan]</td>\n",
-       "      <td>[59.847309449, nan, nan, nan, nan, nan, nan, nan]</td>\n",
-       "      <td>[30.380589538, nan, nan, nan, nan, nan, nan, nan]</td>\n",
-       "      <td>2023-09-28 11:00:00</td>\n",
-       "      <td>2023-09-28 17:00:00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Ленинградская область</td>\n",
-       "      <td>Бокситогорский район</td>\n",
-       "      <td>д.Носово</td>\n",
-       "      <td>None</td>\n",
-       "      <td>Тихвинские ЭС</td>\n",
-       "      <td>Бокситогорский РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2023-09-28 11:00:00</td>\n",
-       "      <td>2023-09-28 17:00:00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Санкт-Петербург</td>\n",
-       "      <td>Приморский район (СПб)</td>\n",
-       "      <td>Санкт-Петербург</td>\n",
-       "      <td>[пр. Комендантский д. 7 к. 1 лит. А , пр. Коме...</td>\n",
-       "      <td>Кабельная сеть</td>\n",
-       "      <td>Западный РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>[112146.0, 126063.0, nan]</td>\n",
-       "      <td>[60.005013183, 60.004879653, nan]</td>\n",
-       "      <td>[30.266799897, 30.264780597, nan]</td>\n",
-       "      <td>2023-09-28 10:00:00</td>\n",
-       "      <td>2023-09-28 17:00:00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Санкт-Петербург</td>\n",
-       "      <td>Выборгский район (СПб)</td>\n",
-       "      <td>Санкт-Петербург</td>\n",
-       "      <td>[ул. Композиторов д.10 д.6]</td>\n",
-       "      <td>Кабельная сеть</td>\n",
-       "      <td>Северный РЭС</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>[56457.0]</td>\n",
-       "      <td>[60.049447721]</td>\n",
-       "      <td>[30.314760352]</td>\n",
-       "      <td>2023-09-28 10:00:00</td>\n",
-       "      <td>2023-09-28 17:00:00</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                      region  ...              finish\n",
-       "index                         ...                    \n",
-       "0      Ленинградская область  ... 2023-09-28 18:00:00\n",
-       "1            Санкт-Петербург  ... 2023-09-28 17:00:00\n",
-       "2      Ленинградская область  ... 2023-09-28 17:00:00\n",
-       "3            Санкт-Петербург  ... 2023-09-28 17:00:00\n",
-       "4            Санкт-Петербург  ... 2023-09-28 17:00:00\n",
-       "\n",
-       "[5 rows x 12 columns]"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "igr_df.head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "Index: 296 entries, 0 to 295\n",
-      "Data columns (total 12 columns):\n",
-      " #   Column       Non-Null Count  Dtype         \n",
-      "---  ------       --------------  -----         \n",
-      " 0   region       294 non-null    object        \n",
-      " 1   area         296 non-null    object        \n",
-      " 2   town         296 non-null    object        \n",
-      " 3   street       167 non-null    object        \n",
-      " 4   branch       295 non-null    object        \n",
-      " 5   res          295 non-null    object        \n",
-      " 6   comment      99 non-null     object        \n",
-      " 7   building_id  72 non-null     object        \n",
-      " 8   lat          72 non-null     object        \n",
-      " 9   lng          72 non-null     object        \n",
-      " 10  start        296 non-null    datetime64[ns]\n",
-      " 11  finish       296 non-null    datetime64[ns]\n",
-      "dtypes: datetime64[ns](2), object(10)\n",
-      "memory usage: 30.1+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "igr_df.info()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Analysis"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Building fetching visualisation "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def print_percent(n):\n",
-    "    print(np.round(n * 100))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Percent of rows with street specified"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "56.0\n"
-     ]
-    }
-   ],
-   "source": [
-    "igr_not_nan_street_df = igr_df[~pd.isnull(igr_df['street'])].copy()\n",
-    "\n",
-    "not_nan_street = len(igr_not_nan_street_df)/len(igr_df)\n",
-    "\n",
-    "print_percent(not_nan_street)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Percent of rows with at least one building found"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "43.0\n"
-     ]
-    }
-   ],
-   "source": [
-    "@np.vectorize\n",
-    "def has_fetched_building_id(cell):\n",
-    "    return len(np.array(cell)[~pd.isnull(np.array(cell))]) > 0\n",
-    "\n",
-    "\n",
-    "not_nan_building_rows = len(igr_not_nan_street_df[\n",
-    "    has_fetched_building_id(igr_not_nan_street_df['building_id'])\n",
-    "]) / len(igr_not_nan_street_df)\n",
-    "\n",
-    "print_percent(not_nan_building_rows)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Percent of street entities with found buildings"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "30.0\n",
-      "69.0\n"
-     ]
-    }
-   ],
-   "source": [
-    "def count_found_building_percent(row: pd.Series):\n",
-    "    streets = np.array(row['street'])\n",
-    "    buildings = np.array(row['building_id'])\n",
-    "\n",
-    "    buildings = buildings[~pd.isnull(buildings)]\n",
-    "\n",
-    "    return len(buildings) / len(streets)\n",
-    "\n",
-    "\n",
-    "found_buildings_per_row = igr_not_nan_street_df[['street', 'building_id']].apply(\n",
-    "    count_found_building_percent, axis=1)\n",
-    "\n",
-    "found_buildings = found_buildings_per_row.mean()\n",
-    "found_buildings_not_nan_street = found_buildings_per_row[found_buildings_per_row != 0].mean()\n",
-    "\n",
-    "print_percent(found_buildings)\n",
-    "\n",
-    "print_percent(found_buildings_not_nan_street)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: >"
-      ]
-     },
-     "execution_count": 17,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "def full_pair(n):\n",
-    "    return np.array([n, 1 - n])\n",
-    "\n",
-    "\n",
-    "percents_df = pd.DataFrame({\n",
-    "    'Найдено зданий всего': full_pair(found_buildings) * not_nan_street,\n",
-    "    'Найдено хотя бы одно здание': full_pair(found_buildings_not_nan_street) * not_nan_street,\n",
-    "    'Непустое поле \"Улица\"': full_pair(not_nan_street),\n",
-    "}, index=['Да', 'Нет']).T\n",
-    "\n",
-    "percents_df.plot(kind='barh', stacked=True)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "area\n",
-       "Приморский район (СПб)     9.681592\n",
-       "Курортный район            6.953731\n",
-       "Красногвардейский район    6.571429\n",
-       "Фрунзенский район          6.554798\n",
-       "Пушкинский район           5.998735\n",
-       "Name: found_building_percent, dtype: float64"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "region\n",
-       "Санкт-Петербург          49.110285\n",
-       "Ленинградская область     0.893617\n",
-       "Name: found_building_percent, dtype: float64"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "town\n",
-       "г. Санкт-Петербург               35.142893\n",
-       "г.Зеленогорск                     3.000000\n",
-       "г. Пушкин                         3.000000\n",
-       "г. Пушкин, п. Александровская     1.998735\n",
-       "п.Лисий Нос                       1.253731\n",
-       "Name: found_building_percent, dtype: float64"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "res\n",
-       "Западный РЭС      8.666667\n",
-       "Курортный РЭС     6.953731\n",
-       "Пушкинский РЭС    6.892352\n",
-       "Южный РЭС         5.333333\n",
-       "Невский РЭС       4.804798\n",
-       "Name: found_building_percent, dtype: float64"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "igr_not_nan_street_df['found_building_percent'] = found_buildings_per_row\n",
-    "\n",
-    "fb_area = igr_not_nan_street_df.groupby('area')['found_building_percent'].sum().sort_values(ascending=False)\n",
-    "fb_region = igr_not_nan_street_df.groupby('region')['found_building_percent'].sum().sort_values(ascending=False)\n",
-    "fb_town = igr_not_nan_street_df.groupby('town')['found_building_percent'].sum().sort_values(ascending=False)\n",
-    "fb_res = igr_not_nan_street_df.groupby('res')['found_building_percent'].sum().sort_values(ascending=False)\n",
-    "\n",
-    "fb_town.loc['г. Санкт-Петербург'] += fb_town['Санкт-Петербург']\n",
-    "fb_town.drop('Санкт-Петербург', inplace=True)\n",
-    "\n",
-    "fb_area = fb_area[~(fb_area == 0)]\n",
-    "fb_town = fb_town[~(fb_town == 0)]\n",
-    "fb_res = fb_res[~(fb_res == 0)]\n",
-    "\n",
-    "for series in (fb_area, fb_region, fb_town, fb_res):\n",
-    "    display(series.head())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def plot_found_building_percent(df, name):\n",
-    "    fb_area_df = pd.DataFrame(df).rename(columns={\n",
-    "        'found_building_percent': 'Найдено зданий в ' + name\n",
-    "    })\n",
-    "\n",
-    "    ax = fb_area_df.T.plot(kind='barh', stacked=True)\n",
-    "\n",
-    "    ax.spines['top'].set_visible(False)\n",
-    "    ax.spines['right'].set_visible(False)\n",
-    "    ax.spines['bottom'].set_visible(False)\n",
-    "    ax.spines['left'].set_visible(False)\n",
-    "\n",
-    "    ax.set_xticks([])\n",
-    "\n",
-    "    return ax"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x7fce2a9e4890>"
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fb_area_ax = plot_found_building_percent(fb_area, 'районах')\n",
-    "fb_area_ax.legend(ncol=3, loc=(-0.46, -0.25), framealpha=1, title='Район')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x7fce2aac9b50>"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fb_region_ax = plot_found_building_percent(fb_region, 'регионах РФ')\n",
-    "fb_region_ax.legend(loc=(0.05, 0), title='Регион')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x7fce2a8a59d0>"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fb_town_ax = plot_found_building_percent(fb_town, 'населённых пунктах')\n",
-    "fb_town_ax.legend(ncol=2, loc=(-0.8, -0.25), framealpha=1, title='Населённый пункт')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x7fce2ad67250>"
-      ]
-     },
-     "execution_count": 23,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fb_res_ax = plot_found_building_percent(fb_res, 'РЭС')\n",
-    "fb_res_ax.legend(ncol=3, loc=(-0.245, -0.1), framealpha=1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Outage statistics"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 624 entries, 0 to 623\n",
-      "Data columns (total 13 columns):\n",
-      " #   Column       Non-Null Count  Dtype         \n",
-      "---  ------       --------------  -----         \n",
-      " 0   index        624 non-null    int64         \n",
-      " 1   region       624 non-null    object        \n",
-      " 2   area         624 non-null    object        \n",
-      " 3   town         624 non-null    object        \n",
-      " 4   street       624 non-null    object        \n",
-      " 5   branch       624 non-null    object        \n",
-      " 6   res          624 non-null    object        \n",
-      " 7   comment      320 non-null    object        \n",
-      " 8   building_id  624 non-null    float64       \n",
-      " 9   lat          624 non-null    float64       \n",
-      " 10  lng          624 non-null    float64       \n",
-      " 11  start        624 non-null    datetime64[ns]\n",
-      " 12  finish       624 non-null    datetime64[ns]\n",
-      "dtypes: datetime64[ns](2), float64(3), int64(1), object(7)\n",
-      "memory usage: 63.5+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "has_geo_df = df[pd.notnull(df['building_id'])].reset_index(drop=True)\n",
-    "\n",
-    "has_geo_df.info()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Distribution of outage by observation day"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "dates_df = pd.DataFrame(index=pd.to_datetime(np.unique(np.concatenate([has_geo_df[a].dt.date.unique() for a in ('start', 'finish')]))))\n",
-    "\n",
-    "start_day_count = has_geo_df.groupby(has_geo_df['start'].dt.day).size()\n",
-    "finish_day_count = has_geo_df.groupby(has_geo_df['finish'].dt.day).size()\n",
-    "\n",
-    "dates_df = dates_df.join(pd.Series(start_day_count, name='Количество начавшихся'), on=dates_df.index.day)\n",
-    "\n",
-    "dates_df = dates_df.join(pd.Series(finish_day_count, name='Количество закончившихся'), on=dates_df.index.day)\n",
-    "\n",
-    "ax = plt.subplot()\n",
-    "\n",
-    "dates_df.plot(kind='bar', ax=ax)\n",
-    "\n",
-    "ax.set_xticklabels(dates_df.index.strftime(\"%m-%d\\n%a\"))\n",
-    "ax.get_xaxis().set_tick_params(labelrotation=0)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Distribution of outage time by hour"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "start_n = has_geo_df.groupby(has_geo_df['start'].dt.hour).size().rename('Начавшиеся')\n",
-    "finish_n = has_geo_df.groupby(has_geo_df['finish'].dt.hour).size().rename('Закончившиеся')\n",
-    "\n",
-    "hrs_df = pd.concat([start_n, finish_n], axis=1, sort=True)\n",
-    "\n",
-    "hrs_df.fillna(0, inplace=True)\n",
-    "\n",
-    "hrs_df.plot()\n",
-    "\n",
-    "xlim = plt.xlim()\n",
-    "\n",
-    "plt.ylabel('Количество')\n",
-    "plt.gca().get_xaxis().set_major_formatter('{x:.0f}:00')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Number of outages in time"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'Количество')"
-      ]
-     },
-     "execution_count": 27,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "start_series = has_geo_df.resample('1H', on='start').size()\n",
-    "finish_series = has_geo_df.resample('1H', on='finish').size()\n",
-    "\n",
-    "start_series.plot(label='Начавшиеся')\n",
-    "finish_series.plot(label='Закончившиеся')\n",
-    "\n",
-    "plt.legend()\n",
-    "plt.xlabel('')\n",
-    "plt.ylabel('Количество')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Frequency representation"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x7fce2aa37c50>"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "for series in (start_series, finish_series):\n",
-    "    plt.plot(abs(np.fft.rfft(series)))\n",
-    "\n",
-    "plt.legend(('Начало', 'Конец'))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Number of simultanious outages"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'Количество одновременно отключённых')"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "@np.vectorize\n",
-    "def count_inclusions(now):\n",
-    "    return has_geo_df[(has_geo_df['start'] <= now) & (now <= has_geo_df['finish'])].size\n",
-    "\n",
-    "\n",
-    "hours = pd.date_range(has_geo_df['start'].min(), has_geo_df['finish'].max(), freq='1H')\n",
-    "\n",
-    "outages = count_inclusions(hours)\n",
-    "\n",
-    "pd.DataFrame(outages, index=hours).plot()\n",
-    "\n",
-    "plt.legend().set_visible(False)\n",
-    "plt.ylabel('Количество одновременно отключённых')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x7fce2aeccc10>]"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.plot(abs(np.fft.rfft(outages)))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Outages, that will last for more than a day"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "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>index</th>\n",
-       "      <th>region</th>\n",
-       "      <th>area</th>\n",
-       "      <th>town</th>\n",
-       "      <th>street</th>\n",
-       "      <th>branch</th>\n",
-       "      <th>res</th>\n",
-       "      <th>comment</th>\n",
-       "      <th>building_id</th>\n",
-       "      <th>lat</th>\n",
-       "      <th>lng</th>\n",
-       "      <th>start</th>\n",
-       "      <th>finish</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "Empty DataFrame\n",
-       "Columns: [index, region, area, town, street, branch, res, comment, building_id, lat, lng, start, finish]\n",
-       "Index: []"
-      ]
-     },
-     "execution_count": 31,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "has_geo_df[has_geo_df['finish'] - has_geo_df['start'] > pd.Timedelta(\"1d\")]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Outages lengths distribution"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0, 0.5, 'Частота')"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "durations = (has_geo_df['finish'] - has_geo_df['start']) / pd.Timedelta('1H')\n",
-    "\n",
-    "durations.plot(kind='hist', density=True)\n",
-    "plt.xlabel(\"Часы\")\n",
-    "plt.ylabel(\"Частота\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Number of buildings where outages occur more than once"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<Axes: >"
-      ]
-     },
-     "execution_count": 33,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "repeating_buildings = has_geo_df[has_geo_df.duplicated('building_id', keep=False)].drop_duplicates(['index', 'building_id']).groupby('building_id')\n",
-    "\n",
-    "dups = repeating_buildings.size().value_counts()\n",
-    "\n",
-    "dups.rename({1: 'Повторно\\nв одном запросе'}, inplace=True)\n",
-    "\n",
-    "dups.plot(kind='bar', rot=0)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": ".venv",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.5"
-  },
-  "orig_nbformat": 4
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/requirements.dev.txt b/requirements.dev.txt
deleted file mode 100644
index b4d1aa0..0000000
--- a/requirements.dev.txt
+++ /dev/null
@@ -1,79 +0,0 @@
-aiohttp==3.8.5
-aiosignal==1.3.1
-annotated-types==0.5.0
-anyio==3.7.1
-asttokens==2.4.0
-async-timeout==4.0.3
-attrs==23.1.0
-autopep8==2.0.4
-backcall==0.2.0
-beautifulsoup4==4.12.2
-certifi==2023.7.22
-charset-normalizer==3.2.0
-comm==0.1.4
-contourpy==1.1.1
-cycler==0.11.0
-debugpy==1.8.0
-decorator==5.1.1
-executing==1.2.0
-fastapi==0.103.1
-fonttools==4.42.1
-frozenlist==1.4.0
-greenlet==2.0.2
-idna==3.4
-ipykernel==6.25.2
-ipython==8.15.0
-jedi==0.19.0
-jupyter_client==8.3.1
-jupyter_core==5.3.1
-kiwisolver==1.4.5
-lxml==4.9.3
-matplotlib==3.8.0
-matplotlib-inline==0.1.6
-multidict==6.0.4
-mypy==1.5.1
-mypy-extensions==1.0.0
-nest-asyncio==1.5.8
-numpy==1.26.0
-packaging==23.1
-pandas==2.1.0
-pandas-stubs==2.0.3.230814
-parso==0.8.3
-pexpect==4.8.0
-pickleshare==0.7.5
-Pillow==10.0.1
-platformdirs==3.10.0
-prompt-toolkit==3.0.39
-psutil==5.9.5
-ptyprocess==0.7.0
-pure-eval==0.2.2
-pycodestyle==2.11.0
-pydantic==2.3.0
-pydantic_core==2.6.3
-Pygments==2.16.1
-pyparsing==3.1.1
-python-dateutil==2.8.2
-pytz==2023.3.post1
-pyzmq==25.1.1
-requests==2.31.0
-schedule==1.2.0
-scipy==1.11.2
-seaborn==0.12.2
-six==1.16.0
-sniffio==1.3.0
-soupsieve==2.5
-SQLAlchemy==2.0.21
-stack-data==0.6.2
-starlette==0.27.0
-tornado==6.3.3
-traitlets==5.10.0
-types-beautifulsoup4==4.12.0.6
-types-html5lib==1.1.11.15
-types-pytz==2023.3.1.0
-types-requests==2.31.0.2
-types-urllib3==1.26.25.14
-typing_extensions==4.8.0
-tzdata==2023.3
-urllib3==2.0.4
-wcwidth==0.2.6
-yarl==1.9.2
diff --git a/requirements.txt b/requirements.txt
index c80ff7b..e66b2bb 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,39 +1,11 @@
 aiohttp==3.8.5
-aiosignal==1.3.1
-annotated-types==0.5.0
-anyio==3.7.1
-async-timeout==4.0.3
-attrs==23.1.0
 beautifulsoup4==4.12.2
-bs4==0.0.1
-certifi==2023.7.22
-charset-normalizer==3.2.0
-click==8.1.7
-fastapi==0.103.1
-frozenlist==1.4.0
-greenlet==2.0.2
-h11==0.14.0
-idna==3.4
-lxml==4.9.3
-multidict==6.0.4
-numpy==1.26.0
 pandas==2.1.1
-psycopg==3.1.10
-psycopg-binary==3.1.10
-psycopg-pool==3.1.7
-pydantic==2.3.0
-pydantic_core==2.6.3
-python-dateutil==2.8.2
-pytz==2023.3.post1
-requests==2.31.0
+Requests==2.31.0
+schedule==1.2.0
+pandas==2.1.1
 schedule==1.2.0
-six==1.16.0
-sniffio==1.3.0
-soupsieve==2.5
 SQLAlchemy==2.0.21
-starlette==0.27.0
-typing_extensions==4.8.0
-tzdata==2023.3
-urllib3==2.0.5
-uvicorn==0.23.2
-yarl==1.9.2
+lxml==4.9.3
+psycopg==3.1.12
+psycopg-binary==3.1.12
\ No newline at end of file
diff --git a/runner/__main__.py b/runner/__main__.py
new file mode 100644
index 0000000..4dc4f37
--- /dev/null
+++ b/runner/__main__.py
@@ -0,0 +1,15 @@
+import schedule
+
+from . import models
+from .config import REFETCH_PERIOD_H
+from .database import engine
+from .job import job
+from .scheduler import run_continuously
+
+models.Base.metadata.create_all(bind=engine)
+
+schedule.every(REFETCH_PERIOD_H).hours.do(job)
+stop_run_continuously = run_continuously()
+
+# First run
+job()
diff --git a/runner/controller.py b/runner/controller.py
index 30211e9..1976959 100644
--- a/runner/controller.py
+++ b/runner/controller.py
@@ -1,11 +1,4 @@
-import datetime
-from functools import reduce
-from typing import List, Optional
-
-from fastapi import HTTPException
-from parser import get_building_id
 from sqlalchemy.orm import Session
-from sqlalchemy.sql.expression import BinaryExpression
 
 from . import models, schemas
 
@@ -30,80 +23,3 @@ def create_record(db: Session, record: schemas.Record):
     db.refresh(db_record)
 
     return db_record
-
-
-def contains_lower(name, val):
-    if isinstance(val, str):
-        return getattr(models.Record, name).icontains(val)
-    else:
-        return getattr(models.Record, name) == val
-
-
-def and_if_can(a: BinaryExpression, b: Optional[BinaryExpression]) -> BinaryExpression:
-    if b is not None:
-        return a & b
-    else:
-        return a
-
-
-def search_each(db: Session, filters: schemas.RecordRequest) -> List[schemas.Record]:
-    query = None
-
-    if filters.start:
-        query = models.Record.start <= filters.start
-    if filters.finish:
-        query = and_if_can(models.Record.finish >= filters.finish, query)
-
-    filters = list(
-        filter(lambda x: x[1] is not None and x[0] not in ("start, finish"), filters)
-    )
-
-    query = reduce(
-        lambda acc, ftr: and_if_can(contains_lower(*ftr), acc), filters, query
-    )
-
-    if query is None:
-        res = db.query(models.Record).all()
-    else:
-        res = db.query(models.Record).filter(query).all()
-
-    return res
-
-
-def search_all(db: Session, prompt: str) -> List[schemas.Record]:
-    prompt = prompt.strip()
-
-    query = reduce(
-        lambda acc, name: acc | contains_lower(name, prompt),
-        ("region", "area", "town", "street", "branch", "res"),
-        contains_lower("comment", prompt),
-    )
-
-    building_id, *_ = get_building_id(prompt)
-
-    if building_id is not None:
-        query |= models.Record.building_id == building_id
-
-    res = db.query(models.Record).filter(query).all()
-
-    return res
-
-
-def check_outage(db: Session, building_id: int) -> schemas.CheckResponse:
-    building_query = db.query(models.Record).filter(
-        (models.Record.building_id == building_id)
-    )
-
-    if building_query.count() == 0:
-        raise HTTPException(404, "No such building")
-
-    now = datetime.datetime.now()
-
-    res = building_query.filter(
-        (models.Record.start <= now) & (now <= models.Record.finish)
-    ).first()
-
-    if res is None:
-        return {"is_outage": False}
-
-    return {"is_outage": True, "when_finish": res.finish}
diff --git a/runner/main.py b/runner/main.py
deleted file mode 100644
index cad95e6..0000000
--- a/runner/main.py
+++ /dev/null
@@ -1,35 +0,0 @@
-import datetime
-
-import schedule
-from fastapi import FastAPI
-
-from . import models, router, schemas
-from .config import REFETCH_PERIOD_H
-from .database import engine
-from .job import job
-from .scheduler import run_continuously, run_threaded
-
-models.Base.metadata.create_all(bind=engine)
-
-start_stamp = datetime.datetime.now()
-
-
-async def lifespan(app: FastAPI):
-    schedule.every(REFETCH_PERIOD_H).hours.do(job)
-    stop_run_continuously = run_continuously()
-
-    run_threaded(job)
-
-    yield
-
-    stop_run_continuously()
-
-
-app = FastAPI(lifespan=lifespan)
-
-app.include_router(router.router)
-
-
-@app.get("/", response_model=schemas.Healthcheck)
-def Healthcheck():
-    return {"up_since": start_stamp}
diff --git a/runner/router.py b/runner/router.py
deleted file mode 100644
index 8326372..0000000
--- a/runner/router.py
+++ /dev/null
@@ -1,74 +0,0 @@
-from typing import Annotated, List
-
-from fastapi import APIRouter, Depends
-from sqlalchemy.orm import Session
-
-from . import controller, schemas
-from .database import get_db
-
-router = APIRouter(prefix="/api")
-
-
-@router.get("/list", response_model=List[schemas.Record], summary="Search by filters")
-def list_rows(
-    filters: Annotated[schemas.RecordRequest, Depends()], db: Session = Depends(get_db)
-):
-    """
-    Searches rows with specified filters.
-
-    Case insensitive contains:
-    - **region**
-    - **area**
-    - **town**
-    - **street**
-    - **start**
-    - **finish**
-    - **branch**
-    - **res**
-    - **comment**
-    Exact match:
-    - **index**
-    - **building_id**
-    - **lat**
-    - **lng**
-    Later or earlier than respectively:
-    - **start**
-    - **finish**
-    """
-    return controller.search_each(db, filters)
-
-
-@router.get("/search", response_model=List[schemas.Record], summary="Search by query")
-def search_rows(query: str, db: Session = Depends(get_db)):
-    """
-    Selects rows with cells containing case insensitive prompt as its part.
-    In addition, geocoding is being applied to prompt and if building_id found, corresponding row is being returned.
-
-    Rows to be searched:
-    - **region**
-    - **area**
-    - **town**
-    - **street**
-    - **branch**
-    - **res**
-    - **comment**
-    """
-    return controller.search_all(db, query)
-
-
-@router.get(
-    "/check", response_model=schemas.CheckResponse, summary="Check when outage ends"
-)
-def check(building_id: int, db: Session = Depends(get_db)):
-    """
-    Checks if there is an active outage for building_id and if there is, also returns when will it end
-    """
-    return controller.check_outage(db, building_id)
-
-
-@router.put("/create", response_model=schemas.Record)
-def create_record(record: schemas.RecordCreate, db: Session = Depends(get_db)):
-    """
-    Not for public usage
-    """
-    return controller.create_record(db, record)
diff --git a/runner/scheduler.py b/runner/scheduler.py
index 48501fd..a4ff9ba 100644
--- a/runner/scheduler.py
+++ b/runner/scheduler.py
@@ -18,8 +18,3 @@ def run_continuously(interval=1):
     continuous_thread.start()
 
     return cease_continuous_run.set
-
-
-def run_threaded(job):
-    job_thread = threading.Thread(target=job)
-    job_thread.start()
diff --git a/runner/schemas.py b/runner/schemas.py
deleted file mode 100644
index 480978a..0000000
--- a/runner/schemas.py
+++ /dev/null
@@ -1,43 +0,0 @@
-import datetime
-from typing import Optional
-
-from pydantic import BaseModel
-
-
-class BaseRecord(BaseModel):
-    index: Optional[int] = None
-    region: Optional[str] = None
-    area: Optional[str] = None
-    town: Optional[str] = None
-    street: Optional[str] = None
-    branch: Optional[str] = None
-    res: Optional[str] = None
-    comment: Optional[str] = None
-    building_id: Optional[int] = None
-    lat: Optional[float] = None
-    lng: Optional[float] = None
-
-
-class Record(BaseRecord):
-    id: int
-    start: datetime.datetime
-    finish: datetime.datetime
-
-
-class RecordRequest(BaseRecord):
-    start: Optional[datetime.datetime] = None
-    finish: Optional[datetime.datetime] = None
-
-
-class RecordCreate(BaseRecord):
-    start: datetime.datetime
-    finish: datetime.datetime
-
-
-class CheckResponse(BaseModel):
-    is_outage: bool
-    when_finish: Optional[datetime.datetime] = None
-
-
-class Healthcheck(BaseModel):
-    up_since: datetime.datetime