{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Car Price Prediction Challenge\n",
    "https://www.kaggle.com/datasets/deepcontractor/car-price-prediction-challenge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['ID', 'Price', 'Levy', 'Manufacturer', 'Model', 'Prod. year',\n",
      "       'Category', 'Leather interior', 'Fuel type', 'Engine volume', 'Mileage',\n",
      "       'Cylinders', 'Gear box type', 'Drive wheels', 'Doors', 'Wheel', 'Color',\n",
      "       'Airbags'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "df = pd.read_csv(\".//static//csv//car_price_prediction.csv\")\n",
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Автомобильный рынок представляет собой динамичную среду, где цены, спрос и предложение автомобилей постоянно меняются в зависимости от множества факторов, таких как возраст автомобиля, пробег, техническое состояние, марка, модель и другие характеристики. Основная проблема заключается в том, как эффективно анализировать и использовать эти данные для принятия бизнес-решений, таких как оценка стоимости подержанных автомобилей, прогнозирование спроса на определенные модели и типы автомобилей, а также определение факторов, наиболее влияющих на ценность автомобиля."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<bound method DataFrame.info of              ID  Price  Levy   Manufacturer    Model  Prod. year   Category  \\\n",
      "0      45654403  13328  1399          LEXUS   RX 450        2010       Jeep   \n",
      "1      44731507  16621  1018      CHEVROLET  Equinox        2011       Jeep   \n",
      "2      45774419   8467     -          HONDA      FIT        2006  Hatchback   \n",
      "3      45769185   3607   862           FORD   Escape        2011       Jeep   \n",
      "4      45809263  11726   446          HONDA      FIT        2014  Hatchback   \n",
      "...         ...    ...   ...            ...      ...         ...        ...   \n",
      "19232  45798355   8467     -  MERCEDES-BENZ  CLK 200        1999      Coupe   \n",
      "19233  45778856  15681   831        HYUNDAI   Sonata        2011      Sedan   \n",
      "19234  45804997  26108   836        HYUNDAI   Tucson        2010       Jeep   \n",
      "19235  45793526   5331  1288      CHEVROLET  Captiva        2007       Jeep   \n",
      "19236  45813273    470   753        HYUNDAI   Sonata        2012      Sedan   \n",
      "\n",
      "      Leather interior Fuel type Engine volume    Mileage  Cylinders  \\\n",
      "0                  Yes    Hybrid           3.5  186005 km        6.0   \n",
      "1                   No    Petrol             3  192000 km        6.0   \n",
      "2                   No    Petrol           1.3  200000 km        4.0   \n",
      "3                  Yes    Hybrid           2.5  168966 km        4.0   \n",
      "4                  Yes    Petrol           1.3   91901 km        4.0   \n",
      "...                ...       ...           ...        ...        ...   \n",
      "19232              Yes       CNG     2.0 Turbo  300000 km        4.0   \n",
      "19233              Yes    Petrol           2.4  161600 km        4.0   \n",
      "19234              Yes    Diesel             2  116365 km        4.0   \n",
      "19235              Yes    Diesel             2   51258 km        4.0   \n",
      "19236              Yes    Hybrid           2.4  186923 km        4.0   \n",
      "\n",
      "      Gear box type Drive wheels   Doors             Wheel   Color  Airbags  \n",
      "0         Automatic          4x4  04-May        Left wheel  Silver       12  \n",
      "1         Tiptronic          4x4  04-May        Left wheel   Black        8  \n",
      "2          Variator        Front  04-May  Right-hand drive   Black        2  \n",
      "3         Automatic          4x4  04-May        Left wheel   White        0  \n",
      "4         Automatic        Front  04-May        Left wheel  Silver        4  \n",
      "...             ...          ...     ...               ...     ...      ...  \n",
      "19232        Manual         Rear  02-Mar        Left wheel  Silver        5  \n",
      "19233     Tiptronic        Front  04-May        Left wheel     Red        8  \n",
      "19234     Automatic        Front  04-May        Left wheel    Grey        4  \n",
      "19235     Automatic        Front  04-May        Left wheel   Black        4  \n",
      "19236     Automatic        Front  04-May        Left wheel   White       12  \n",
      "\n",
      "[19237 rows x 18 columns]> \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(df.info, \"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Объектами наблюдения** являются автомобили, каждый из которых описывается определенным набором характеристик (атрибутов). Атрибуты включают как *количественные* данные (например, цена, объем двигателя), так и *качественные* (например, цвет, тип топлива, марка).\n",
    "\n",
    "**Анализ сведений о каждом наборе данных**: В данном случае каждый набор данных — это информация об отдельных автомобилях. Здесь присутствуют атрибуты такие как: идентификатор (ID), цена, марка, модель, год выпуска, объем двигателя, тип коробки передач, тип топлива, пробег, цилиндры, тип коробки передач, ведущие колеса, двери, колеса, цвет, подушки безопасности.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "mean_price_per_year = df.groupby('Prod. year')['Price'].mean()\n",
    "plt.figure(figsize=(8, 6))\n",
    "mean_price_per_year.plot(kind='line', marker='o', color='blue')\n",
    "plt.title('Зависимость средней цены от года выпуска автомобиля')\n",
    "plt.xlabel('Год выпуска')\n",
    "plt.ylabel('Средняя цена ($)')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Связь между средней ценой автомобиля и годом:** \n",
    "Этот график полезен для анализа динамики цен на автомобили в зависимости от года выпуска и выявления тенденций на рынке.\n",
    "\n",
    "Из графика следует что автомобили растут в цене по мере увеличения года, за исключением некоторых автомобилей, которые повышают свою цену до невероятных значений."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Пример бизнес-целей:**\n",
    "\n",
    "1. Ценообразование автомобилей\n",
    "\n",
    "Цель: Создать модель, которая точно предсказывает рыночную стоимость автомобиля на основе ограниченного набора характеристик: года выпуска, пробега и объема двигателя.\n",
    "\n",
    "Эффекты для бизнеса: Увеличение доходов за счет точного определения рыночной стоимости, минимизация убытков от недооценки или переоценки автомобилей.\n",
    "\n",
    "Вход:\n",
    "\n",
    "* Год выпуска\n",
    "* Пробег\n",
    "* Объем двигателя\n",
    "\n",
    "Целевой признак: Цена автомобиля.\n",
    "\n",
    "2. Анализ спроса и предложения\n",
    "\n",
    "Цель: Провести анализ спроса на автомобили по моделям, годам выпуска и регионам для лучшего планирования ассортимента и распределения ресурсов.\n",
    "\n",
    "Эффекты для бизнеса: Оптимизация ассортимента и планирования закупок, снижение издержек на хранение нераспроданных автомобилей.\n",
    "\n",
    "Вход:\n",
    "\n",
    "* Модель автомобиля\n",
    "* Год выпуска\n",
    "* Регион продажи\n",
    "\n",
    "Целевой признак: Количество проданных автомобилей (спрос) или количество доступных автомобилей (предложение).\n",
    "\n",
    "3. Оценка состояния подержанных автомобилей\n",
    "\n",
    "Цель: Разработать модель для оценки состояния автомобиля на основе пробега и года выпуска, которая поможет при установлении рыночной стоимости подержанных автомобилей.\n",
    "\n",
    "Эффекты для бизнеса: Ускорение процессов оценки подержанных автомобилей, повышение доверия клиентов к оценке автомобилей.\n",
    "\n",
    "Вход:\n",
    "\n",
    "* Пробег\n",
    "* Возраст автомобиля (год выпуска)\n",
    "\n",
    "Целевой признак: Оценка технического состояния автомобиля."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Опредиление проблем данных с помощью кода:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Максимальные значения:\n",
      " ID                          45816654\n",
      "Price                       26307500\n",
      "Levy                           11714\n",
      "Manufacturer                    სხვა\n",
      "Model                             xD\n",
      "Prod. year                      2020\n",
      "Category                   Universal\n",
      "Leather interior                 Yes\n",
      "Fuel type             Plug-in Hybrid\n",
      "Engine volume                   20.0\n",
      "Mileage                 2147483647.0\n",
      "Cylinders                       16.0\n",
      "Gear box type               Variator\n",
      "Drive wheels                    Rear\n",
      "Doors                             >5\n",
      "Wheel               Right-hand drive\n",
      "Color                         Yellow\n",
      "Airbags                           16\n",
      "dtype: object \n",
      "\n",
      "Признаки с нулевыми значениями:\n",
      " Index(['Levy', 'Engine volume', 'Mileage', 'Airbags'], dtype='object') \n",
      "\n",
      "Признаки с низкой дисперсией:\n",
      " Series([], dtype: float64) \n",
      "\n",
      "Год производства:\n",
      " 0        2010\n",
      "1        2011\n",
      "2        2006\n",
      "3        2011\n",
      "4        2014\n",
      "         ... \n",
      "19232    1999\n",
      "19233    2011\n",
      "19234    2010\n",
      "19235    2007\n",
      "19236    2012\n",
      "Name: Prod. year, Length: 19237, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "numeric_columns = ['Price', 'Levy', 'Engine volume', 'Mileage', 'Cylinders', 'Airbags']\n",
    "\n",
    "df[numeric_columns] = df[numeric_columns].replace(\"-\", np.nan)\n",
    "\n",
    "df[numeric_columns] = df[numeric_columns].apply(pd.to_numeric, errors='coerce')\n",
    "\n",
    "max_value = df.max(axis=0)\n",
    "\n",
    "columns_with_zero = df.columns[(df == 0).any()]\n",
    "\n",
    "numeric_data = df.select_dtypes(include='number')\n",
    "\n",
    "shum = numeric_data.var()\n",
    "\n",
    "low_dispers = 0.1\n",
    "low_var_columns = shum[shum < low_dispers]\n",
    "\n",
    "year = df['Prod. year']\n",
    "\n",
    "print(\"Максимальные значения:\\n\", max_value, \"\\n\")\n",
    "print(\"Признаки с нулевыми значениями:\\n\", columns_with_zero, \"\\n\")\n",
    "print(\"Признаки с низкой дисперсией:\\n\", low_var_columns, \"\\n\")\n",
    "print(\"Год производства:\\n\", year)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Признаки, содержащие нулевые значения: 'Engine volume' и 'Airbags'. Наличие нулевых значений может создать смещение при анализе, если учитывать такие автомобили.\n",
    "2. Признаки 'Price', 'Engine volume', и 'Cylinders' могут иметь аномально высокие значения, что указывает на наличие выбросов.\n",
    "3. Признаки с низкой дисперсией, такие как Leather interior, Fuel type, Drive wheels, могут иметь слишком малую вариативность, что снижает их значимость для анализа.\n",
    "4. Признак Prod. year варьируется от 1900 до 2020, что делает его полезным для анализа возрастных характеристик автомобилей. Однако автомобили более старого возраста могут быть редкими в выборке, что может повлиять на выводы относительно корреляции между годом выпуска и ценой."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Примеры решения обнаруженных проблем для каждого набора данных:**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Нулевые значения: удаление строк с нулями если нулевые значения редки и их удаление не повлияет на анализ.\n",
    "2. Аномально высокие значения: можно ограничить выбросы, заменив их на определенные пороговые значения. Это позволит избежать влияния аномально высоких значений на анализ.\n",
    "3. Низкая дисперсия признаков: если признаки имеют низкую вариативность, можно преобразовать их в бинарные переменные. Это сделает признаки более значимыми для моделей.\n",
    "4. Устаревшие данные: можно отфильтровать автомобили по годам выпуска, чтобы учесть только актуальные модели."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Оценить качество каждого набора данных:** "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Информативность: Набор данных предоставляет достаточную информацию для анализа характиристик машины.\n",
    "2. Степень покрытия: Включает данные только о автомобилях одного региона, что ограничивает возможности обобщения результатов на другие регионы.\n",
    "3. Соответствие реальным данным: Данные в целом соответствуют реальным значениям, но встречаются редкие выбросы.\n",
    "4. Согласованность меток: Метки, такие как тип топлива и категория автомобиля, имеют четкие и согласованные значения, что способствует правильному анализу данных."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Устранить проблему пропущенных данных. Для каждого набора данных:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Пропущенные значения до обработки:\n",
      "ID                     0\n",
      "Price                  0\n",
      "Levy                5819\n",
      "Manufacturer           0\n",
      "Model                  0\n",
      "Prod. year             0\n",
      "Category               0\n",
      "Leather interior       0\n",
      "Fuel type              0\n",
      "Engine volume          0\n",
      "Mileage                0\n",
      "Cylinders              0\n",
      "Gear box type          0\n",
      "Drive wheels           0\n",
      "Doors                  0\n",
      "Wheel                  0\n",
      "Color                  0\n",
      "Airbags                0\n",
      "dtype: int64\n",
      "Пропущенные значения после обработки:\n",
      "ID                  0\n",
      "Price               0\n",
      "Levy                0\n",
      "Manufacturer        0\n",
      "Model               0\n",
      "Prod. year          0\n",
      "Category            0\n",
      "Leather interior    0\n",
      "Fuel type           0\n",
      "Engine volume       0\n",
      "Mileage             0\n",
      "Cylinders           0\n",
      "Gear box type       0\n",
      "Drive wheels        0\n",
      "Doors               0\n",
      "Wheel               0\n",
      "Color               0\n",
      "Airbags             0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "numeric_columns = ['Price', 'Levy', 'Engine volume', 'Cylinders', 'Airbags']\n",
    "df[numeric_columns] = df[numeric_columns].replace(\"-\", np.nan)\n",
    "print(\"Пропущенные значения до обработки:\")\n",
    "print(df.isnull().sum())\n",
    "\n",
    "df['Levy'] = df['Levy'].fillna(0)  # Подстановка 0\n",
    "df['Mileage'] = df['Mileage'].str.replace(' km', '').str.replace(',', '').astype(float)  # Среднее значение\n",
    "df.dropna(subset=['Fuel type'], inplace=True)  # Удаление строк\n",
    "\n",
    "print(\"Пропущенные значения после обработки:\")\n",
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Выполнить разбиение каждого набора данных на обучающую, контрольную и тестовую выборки:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Исходный размер строк: 19237\n",
      "Размер обучающей выборки: 11541\n",
      "Размер контрольной выборки: 3848\n",
      "Размер тестовой выборки: 3848\n"
     ]
    }
   ],
   "source": [
    "df_numeric = df.select_dtypes(include='number')\n",
    "\n",
    "X = df.drop('Price', axis=1)  \n",
    "y = df['Price']  \n",
    "\n",
    "X_train_val, X_test, y_train_val, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "X_train, X_val, y_train, y_val = train_test_split(X_train_val, y_train_val, test_size=0.25, random_state=42)\n",
    "\n",
    "# Проверка размеров выборок\n",
    "print(f\"Исходный размер строк: {df_numeric.shape[0]}\")\n",
    "print(f\"Размер обучающей выборки: {X_train.shape[0]}\")\n",
    "print(f\"Размер контрольной выборки: {X_val.shape[0]}\")\n",
    "print(f\"Размер тестовой выборки: {X_test.shape[0]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Статистические показатели для обучающей выборки:\n",
      "Среднее значение: 9.02\n",
      "Стандартное отклонение: 1.60\n",
      "Минимальное значение: 0.00\n",
      "Максимальное значение: 17.09\n",
      "Количество наблюдений: 13465\n",
      "\n",
      "Статистические показатели для валидационной выборки:\n",
      "Среднее значение: 9.03\n",
      "Стандартное отклонение: 1.59\n",
      "Минимальное значение: 1.10\n",
      "Максимальное значение: 13.35\n",
      "Количество наблюдений: 2886\n",
      "\n",
      "Статистические показатели для тестовой выборки:\n",
      "Среднее значение: 9.06\n",
      "Стандартное отклонение: 1.56\n",
      "Минимальное значение: 0.00\n",
      "Максимальное значение: 12.06\n",
      "Количество наблюдений: 2886\n",
      "\n"
     ]
    }
   ],
   "source": [
    "\n",
    "df['price_log'] = np.log(df['Price'])\n",
    "\n",
    "X = df.drop(['Price', 'price_log'], axis=1) \n",
    "y = df['price_log']  \n",
    "\n",
    "X = X.select_dtypes(include='number')\n",
    "\n",
    "X_train, X_temp, y_train, y_temp = train_test_split(X, y, test_size=0.3, random_state=42)\n",
    "\n",
    "X_val, X_test, y_val, y_test = train_test_split(X_temp, y_temp, test_size=0.5, random_state=42)\n",
    "\n",
    "def plot_distribution(data, title):\n",
    "    \"\"\"Построение гистограммы распределения целевого признака\"\"\"\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    sns.histplot(data, kde=True, bins=30, color='skyblue')\n",
    "    plt.title(title)\n",
    "    plt.xlabel('Logarithm of Price')\n",
    "    plt.ylabel('Count')\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "plot_distribution(y_train, 'Распределение логарифма цены в обучающей выборке')\n",
    "plot_distribution(y_val, 'Распределение логарифма цены в валидационной выборке')\n",
    "plot_distribution(y_test, 'Распределение логарифма цены в тестовой выборке')\n",
    "\n",
    "def get_statistics(df, name):\n",
    "    print(f\"Статистические показатели для {name} выборки:\")\n",
    "    print(f\"Среднее значение: {df.mean():.2f}\")\n",
    "    print(f\"Стандартное отклонение: {df.std():.2f}\")\n",
    "    print(f\"Минимальное значение: {df.min():.2f}\")\n",
    "    print(f\"Максимальное значение: {df.max():.2f}\")\n",
    "    print(f\"Количество наблюдений: {df.count()}\\n\")\n",
    "\n",
    "get_statistics(y_train, \"обучающей\")\n",
    "get_statistics(y_val, \"валидационной\")\n",
    "get_statistics(y_test, \"тестовой\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Обучающая, валидационная и тестовая выборки достаточно сбалансированы по основным статистическим показателям (среднее, стандартное отклонение, количество наблюдений), что говорит о хорошем качестве разбиения данных. Различия минимальны, и распределение данных выглядит однородным. Нет необходимости использовать методы аугментации данных, так как выборки сбалансированы и объем данных достаточно велик."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Выполнить приращение данных методами выборки с избытком (oversampling) и выборки с недостатком (undersampling):**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Распределение классов после SMOTE (oversampling):\n",
      "price_category\n",
      "0    2782\n",
      "1    2782\n",
      "2    2782\n",
      "3    2782\n",
      "4    2782\n",
      "Name: count, dtype: int64\n",
      "Распределение классов после RandomUnderSampler (undersampling):\n",
      "price_category\n",
      "0    2613\n",
      "1    2613\n",
      "2    2613\n",
      "3    2613\n",
      "4    2613\n",
      "Name: count, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "from imblearn.over_sampling import SMOTE\n",
    "from imblearn.under_sampling import RandomUnderSampler\n",
    "from collections import Counter\n",
    "\n",
    "df['price_log'] = np.log(df['Price'])\n",
    "\n",
    "df['price_category'] = pd.qcut(df['price_log'], q=5, labels=[0, 1, 2, 3, 4])\n",
    "\n",
    "X = df.drop(['Price', 'price_log', 'price_category'], axis=1)\n",
    "y = df['price_category']\n",
    "X = pd.get_dummies(X, drop_first=True)\n",
    "for col in X.columns:\n",
    "    X[col] = X[col].fillna(X[col].mode()[0])\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)\n",
    "\n",
    "smote = SMOTE(random_state=42)\n",
    "X_train_smote, y_train_smote = smote.fit_resample(X_train, y_train)\n",
    "\n",
    "print(\"Распределение классов после SMOTE (oversampling):\")\n",
    "print(pd.Series(y_train_smote).value_counts())\n",
    "\n",
    "undersampler = RandomUnderSampler(random_state=42)\n",
    "X_train_under, y_train_under = undersampler.fit_resample(X_train, y_train)\n",
    "\n",
    "print(\"Распределение классов после RandomUnderSampler (undersampling):\")\n",
    "print(pd.Series(y_train_under).value_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Forbes 2022 Billionaires data\n",
    "https://www.kaggle.com/datasets/imakash3011/customer-personality-analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Rank ', 'Name', 'Networth', 'Age', 'Country', 'Source', 'Industry'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "df2 = pd.read_csv(\".//static//csv//forbes_billionaires.csv\")\n",
    "print(df2.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Мировой рынок миллионеров представляет собой сложную и динамичную среду, где состояние, возраст, страна происхождения и источники богатства сильно варьируются в зависимости от множества факторов. Основная проблема заключается в том, как правильно интерпретировать эти данные, выявлять ключевые корреляции между параметрами, и на основе этого строить прогнозы по развитию рынка капиталов."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<bound method DataFrame.info of       Rank                        Name  Networth  Age        Country  \\\n",
      "0         1                 Elon Musk      219.0   50  United States   \n",
      "1         2                Jeff Bezos      171.0   58  United States   \n",
      "2         3  Bernard Arnault & family      158.0   73         France   \n",
      "3         4                Bill Gates      129.0   66  United States   \n",
      "4         5            Warren Buffett      118.0   91  United States   \n",
      "...     ...                        ...       ...  ...            ...   \n",
      "2595   2578    Jorge Gallardo Ballart        1.0   80          Spain   \n",
      "2596   2578              Nari Genomal        1.0   82    Philippines   \n",
      "2597   2578            Ramesh Genomal        1.0   71    Philippines   \n",
      "2598   2578            Sunder Genomal        1.0   68    Philippines   \n",
      "2599   2578     Horst-Otto Gerberding        1.0   69        Germany   \n",
      "\n",
      "                      Source                Industry  \n",
      "0              Tesla, SpaceX             Automotive   \n",
      "1                     Amazon             Technology   \n",
      "2                       LVMH       Fashion & Retail   \n",
      "3                  Microsoft             Technology   \n",
      "4         Berkshire Hathaway  Finance & Investments   \n",
      "...                      ...                     ...  \n",
      "2595         pharmaceuticals             Healthcare   \n",
      "2596                 apparel       Fashion & Retail   \n",
      "2597                 apparel       Fashion & Retail   \n",
      "2598                garments       Fashion & Retail   \n",
      "2599  flavors and fragrances        Food & Beverage   \n",
      "\n",
      "[2600 rows x 7 columns]> \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(df2.info, \"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Объектами наблюдения** являются миллионеры. Каждый миллионер представлен одной строкой в таблице, которая описывает его основные характеристики.\n",
    "\n",
    "**Анализ сведений о каждом наборе данных**: В данном случае каждый набор данных — это информация об отдельном миллиардере. Здесь присутствуют атрибуты такие как: Ранг, Имя, Состояние, Возраст, Страна, Источник дохода, Отрасль.\n",
    "\n",
    "**Связи между объектами:** Можно выявить связи между возрастом и состоянием или источник дохода и состояние.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "plt.subplot(2, 2, 1)\n",
    "sns.scatterplot(data=df2, x='Age', y='Networth')\n",
    "plt.title('Связь между возрастом и состоянием')\n",
    "plt.xlabel('Возраст')\n",
    "plt.ylabel('Состояние (млрд)')\n",
    "\n",
    "\n",
    "plt.subplot(2, 2, 2)\n",
    "top_sources = df2['Source'].value_counts().index[:10]\n",
    "sns.boxplot(data=df2[df2['Source'].isin(top_sources)], x='Source', y='Networth')\n",
    "plt.title('Связь между источником дохода и состоянием')\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Источник дохода')\n",
    "plt.ylabel('Состояние (млрд)')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Из 1 графика видно что меньше всего миллиардеров от 0 до 30 и от 95 до 100 лет. Из 2 графка видно больше всего миллиардеров в diversified и real estate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Оценка состояния миллиардера\n",
    "\n",
    "Цель: Разработать модель, которая точно предсказывает состояние миллиардера на основе ограниченного набора характеристик: возраста, страны проживания и отрасли, в которой он работает.\n",
    "\n",
    "Эффекты для бизнеса: Более точная оценка состояния миллиардеров позволит компаниям лучше адаптировать свои маркетинговые стратегии, улучшить целевую рекламу и предложить персонализированные финансовые услуги для богатых клиентов.\n",
    "\n",
    "Вход:\n",
    "\n",
    "* Возраст миллиардера\n",
    "* Страна проживания\n",
    "* Отрасль\n",
    "\n",
    "Целевой признак: Состояние миллиардера (Networth).\n",
    "\n",
    "2. Анализ влияния источников дохода на состояние\n",
    "\n",
    "Цель: Провести анализ, чтобы выявить наиболее прибыльные источники дохода среди миллиардеров и как они влияют на накопленное состояние.\n",
    "\n",
    "Эффекты для бизнеса: Компании могут использовать эту информацию для определения наиболее перспективных отраслей для инвестиций и бизнес-стратегий, а также для оптимизации инвестиционных портфелей.\n",
    "\n",
    "Вход:\n",
    "\n",
    "* Источник дохода\n",
    "* Возраст миллиардера\n",
    "* Страна проживания\n",
    "\n",
    "Целевой признак: Состояние миллиардера (Networth).\n",
    "\n",
    "3. Прогнозирование роста капитала\n",
    "\n",
    "Цель: Разработать модель для прогнозирования роста капитала на основе возраста, страны проживания и источника дохода, которая поможет в оценке потенциального роста состояния миллиардера в будущем.\n",
    "\n",
    "Эффекты для бизнеса: Компании смогут лучше планировать свои инвестиции и расширять деловые связи с растущими миллиардерами, оптимизируя свои ресурсы для привлечения наиболее перспективных клиентов.\n",
    "\n",
    "Вход:\n",
    "\n",
    "* Возраст миллиардера\n",
    "* Страна проживания\n",
    "* Источник дохода\n",
    "\n",
    "Целевой признак: Прогнозируемый рост состояния миллиардера (Networth).\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Опредиление проблем данных с помощью кода:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Максимальные значения:\n",
      " Rank                            2578\n",
      "Name             Zygmunt Solorz-Zak \n",
      "Networth                       219.0\n",
      "Age                              100\n",
      "Country                     Zimbabwe\n",
      "Source      wireless networking gear\n",
      "Industry              diversified   \n",
      "dtype: object \n",
      "\n",
      "Признаки с нулевыми значениями:\n",
      " Index([], dtype='object') \n",
      "\n",
      "Признаки с низкой дисперсией:\n",
      " Series([], dtype: float64) \n",
      "\n"
     ]
    }
   ],
   "source": [
    "max_value = df2.max(axis=0)\n",
    "\n",
    "columns_with_zero = df2.columns[(df2 == 0).any()]\n",
    "\n",
    "numeric_data = df2.select_dtypes(include='number')\n",
    "\n",
    "shum = numeric_data.var()\n",
    "\n",
    "low_dispers = 0.1\n",
    "low_var_columns = shum[shum < low_dispers]\n",
    "\n",
    "\n",
    "print(\"Максимальные значения:\\n\", max_value, \"\\n\")\n",
    "print(\"Признаки с нулевыми значениями:\\n\", columns_with_zero, \"\\n\")\n",
    "print(\"Признаки с низкой дисперсией:\\n\", low_var_columns, \"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8))\n",
    "numeric_data = df2.select_dtypes(include='number')\n",
    "correlation_matrix = numeric_data.corr()\n",
    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', vmin=-1, vmax=1)\n",
    "plt.title('Корреляционная матрица для проверки просачивания данных')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "В данных которые содержаться в таблице нету ни нулевых значений, ни низкой дисперсии, ни выбросов связанных с аномально высокими значениями. По графику видно целом, данные не указывают на очевидное просачивание, поскольку корреляции не слишком высокие и ожидаемы. Данные хорошо сформированны поэтому здесь нет проблем чтобы их решать."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Оценить качество каждого набора данных:** "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Информативность: Набор данных предоставляет достаточную информацию для анализа характиристик миллиардеров.\n",
    "2. Степень покрытия: Включает данные всего мира поэтому с.п. лучше не придумаешь.\n",
    "3. Соответствие реальным данным: Данные в целом соответствуют реальным значениям, но это все будет зависеть от года.\n",
    "4. Согласованность меток: В данных о миллиардерах признаки Source (Источник дохода), Industry (Отрасль) и Country (Страна) могут иметь несогласованность меток, если одна и та же категория указана разными способами."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Выполнить разбиение каждого набора данных на обучающую, контрольную и тестовую выборки:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Исходный размер строк: 2600\n",
      "Размер обучающей выборки: 1560\n",
      "Размер контрольной выборки: 520\n",
      "Размер тестовой выборки: 520\n"
     ]
    }
   ],
   "source": [
    "df_numeric = df2.select_dtypes(include='number')\n",
    "\n",
    "X = df2.drop('Networth', axis=1)  \n",
    "y = df2['Networth']  \n",
    "\n",
    "X_train_val, X_test, y_train_val, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
    "\n",
    "X_train, X_val, y_train, y_val = train_test_split(X_train_val, y_train_val, test_size=0.25, random_state=42)\n",
    "\n",
    "# Проверка размеров выборок\n",
    "print(f\"Исходный размер строк: {df_numeric.shape[0]}\")\n",
    "print(f\"Размер обучающей выборки: {X_train.shape[0]}\")\n",
    "print(f\"Размер контрольной выборки: {X_val.shape[0]}\")\n",
    "print(f\"Размер тестовой выборки: {X_test.shape[0]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Статистические показатели для обучающей выборки:\n",
      "Среднее значение: 1.08\n",
      "Стандартное отклонение: 0.85\n",
      "Минимальное значение: 0.00\n",
      "Максимальное значение: 5.39\n",
      "Количество наблюдений: 1820\n",
      "\n",
      "Статистические показатели для валидационной выборки:\n",
      "Среднее значение: 1.04\n",
      "Стандартное отклонение: 0.77\n",
      "Минимальное значение: 0.00\n",
      "Максимальное значение: 3.72\n",
      "Количество наблюдений: 390\n",
      "\n",
      "Статистические показатели для тестовой выборки:\n",
      "Среднее значение: 1.03\n",
      "Стандартное отклонение: 0.75\n",
      "Минимальное значение: 0.00\n",
      "Максимальное значение: 4.17\n",
      "Количество наблюдений: 390\n",
      "\n"
     ]
    }
   ],
   "source": [
    "df2['networth_log'] = np.log(df2['Networth'])\n",
    "\n",
    "X = df2.drop(['Networth', 'networth_log'], axis=1) \n",
    "y = df2['networth_log']  \n",
    "\n",
    "X = X.select_dtypes(include='number')\n",
    "\n",
    "X_train, X_temp, y_train, y_temp = train_test_split(X, y, test_size=0.3, random_state=42)\n",
    "\n",
    "X_val, X_test, y_val, y_test = train_test_split(X_temp, y_temp, test_size=0.5, random_state=42)\n",
    "\n",
    "def plot_distribution(data, title):\n",
    "    \"\"\"Построение гистограммы распределения целевого признака\"\"\"\n",
    "    plt.figure(figsize=(10, 6))\n",
    "    sns.histplot(data, kde=True, bins=30, color='skyblue')\n",
    "    plt.title(title)\n",
    "    plt.xlabel('Logarithm of Price')\n",
    "    plt.ylabel('Count')\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "plot_distribution(y_train, 'Распределение логарифма капитала в обучающей выборке')\n",
    "plot_distribution(y_val, 'Распределение логарифма капитала в валидационной выборке')\n",
    "plot_distribution(y_test, 'Распределение логарифма капитала в тестовой выборке')\n",
    "\n",
    "def get_statistics(df2, name):\n",
    "    print(f\"Статистические показатели для {name} выборки:\")\n",
    "    print(f\"Среднее значение: {df2.mean():.2f}\")\n",
    "    print(f\"Стандартное отклонение: {df2.std():.2f}\")\n",
    "    print(f\"Минимальное значение: {df2.min():.2f}\")\n",
    "    print(f\"Максимальное значение: {df2.max():.2f}\")\n",
    "    print(f\"Количество наблюдений: {df2.count()}\\n\")\n",
    "\n",
    "get_statistics(y_train, \"обучающей\")\n",
    "get_statistics(y_val, \"валидационной\")\n",
    "get_statistics(y_test, \"тестовой\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Различия между обучающей, валидационной и тестовой выборками минимальны, и это свидетельствует о хорошем разбиении данных. Методы аугментации данных здесь не требуются, так как количество данных достаточно велико, и выборки сбалансированы по ключевым показателям."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Выполнить приращение данных методами выборки с избытком (oversampling) и выборки с недостатком (undersampling):**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Размеры после oversampling: (1945, 6) (1945,)\n",
      "Размеры после undersampling: (1730, 6) (1730,)\n"
     ]
    }
   ],
   "source": [
    "from imblearn.over_sampling import RandomOverSampler\n",
    "oversampler = RandomOverSampler(random_state=12)\n",
    "X_train_over, y_train_over = oversampler.fit_resample(X_train, y_train)\n",
    "\n",
    "undersampler = RandomUnderSampler(random_state=12)\n",
    "X_train_under, y_train_under = undersampler.fit_resample(X_train, y_train)\n",
    "\n",
    "print(\"Размеры после oversampling:\", X_train_over.shape, y_train_over.shape)\n",
    "print(\"Размеры после undersampling:\", X_train_under.shape, y_train_under.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pima Indians Diabetes Database\n",
    "https://www.kaggle.com/datasets/uciml/pima-indians-diabetes-database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin',\n",
      "       'BMI', 'DiabetesPedigreeFunction', 'Age', 'Outcome'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "df3 = pd.read_csv(\".//static//csv//diabetes.csv\")\n",
    "print(df3.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Набор данных Pima Indians Diabetes Database представляет собой сложную среду, где факторы риска диабета, такие как количество беременностей, уровень глюкозы, давление и индекс массы тела, варьируются в зависимости от множества параметров. Основная проблема заключается в том, как правильно интерпретировать эти данные, выявлять ключевые взаимосвязи между признаками и на основе этого строить точные прогнозы вероятности возникновения диабета."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<bound method DataFrame.info of       Rank                        Name  Networth  Age        Country  \\\n",
      "0         1                 Elon Musk      219.0   50  United States   \n",
      "1         2                Jeff Bezos      171.0   58  United States   \n",
      "2         3  Bernard Arnault & family      158.0   73         France   \n",
      "3         4                Bill Gates      129.0   66  United States   \n",
      "4         5            Warren Buffett      118.0   91  United States   \n",
      "...     ...                        ...       ...  ...            ...   \n",
      "2595   2578    Jorge Gallardo Ballart        1.0   80          Spain   \n",
      "2596   2578              Nari Genomal        1.0   82    Philippines   \n",
      "2597   2578            Ramesh Genomal        1.0   71    Philippines   \n",
      "2598   2578            Sunder Genomal        1.0   68    Philippines   \n",
      "2599   2578     Horst-Otto Gerberding        1.0   69        Germany   \n",
      "\n",
      "                      Source                Industry  networth_log  \\\n",
      "0              Tesla, SpaceX             Automotive       5.389072   \n",
      "1                     Amazon             Technology       5.141664   \n",
      "2                       LVMH       Fashion & Retail       5.062595   \n",
      "3                  Microsoft             Technology       4.859812   \n",
      "4         Berkshire Hathaway  Finance & Investments       4.770685   \n",
      "...                      ...                     ...           ...   \n",
      "2595         pharmaceuticals             Healthcare       0.000000   \n",
      "2596                 apparel       Fashion & Retail       0.000000   \n",
      "2597                 apparel       Fashion & Retail       0.000000   \n",
      "2598                garments       Fashion & Retail       0.000000   \n",
      "2599  flavors and fragrances        Food & Beverage       0.000000   \n",
      "\n",
      "     networth_category  \n",
      "0                    4  \n",
      "1                    4  \n",
      "2                    4  \n",
      "3                    4  \n",
      "4                    4  \n",
      "...                ...  \n",
      "2595                 0  \n",
      "2596                 0  \n",
      "2597                 0  \n",
      "2598                 0  \n",
      "2599                 0  \n",
      "\n",
      "[2600 rows x 9 columns]> \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(df2.info, \"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Объектами наблюдения** являются пациенты, которые представляют собой индейцев Пима. Каждый пациент представлен одной строкой в таблице, которая описывает его основные характеристики.\n",
    "\n",
    "**Анализ сведений о каждом наборе данных**: В данном случае каждый набор данных — это информация об отдельном пациенте. Здесь присутствуют атрибуты такие как: Количество беременностей, Уровень глюкозы, Давление, Толщина кожи, Инсулин, Индекс массы тела, Генетическая предрасположенность к диабету, Возраст, Результат.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlation_matrix = df3[['Glucose', 'Insulin', 'BMI', 'Outcome']].corr()\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\")\n",
    "plt.title('Корреляция между атрибутами и наличием диабета')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Glucose и Outcome (0.47):\n",
    "\n",
    "Уровень глюкозы показывает довольно сильную положительную корреляцию с наличием диабета (корреляция 0.47). Это значит, что чем выше уровень глюкозы в крови, тем больше вероятность развития диабета.\n",
    "\n",
    "2. BMI и Outcome (0.29):\n",
    "\n",
    "Индекс массы тела (BMI) также имеет положительную, но более слабую корреляцию с диабетом (0.29). Это указывает на то, что более высокий BMI также связан с повышенным риском диабета, хотя эта связь слабее, чем с уровнем глюкозы.\n",
    "\n",
    "3. Insulin и Outcome (0.13):\n",
    "\n",
    "Уровень инсулина имеет самую слабую положительную корреляцию с наличием диабета (0.13). Это может указывать на то, что, хотя инсулин важен для метаболических процессов, в данном наборе данных его влияние на вероятность развития диабета не является значительным.\n",
    "\n",
    "4. Взаимосвязь между атрибутами:\n",
    "\n",
    "* Glucose и Insulin (0.33): Существует умеренная положительная корреляция между уровнем глюкозы и инсулина, что ожидаемо, так как инсулин контролирует уровень глюкозы в организме.\n",
    "* Glucose и BMI (0.22): Также наблюдается слабая положительная корреляция между уровнем глюкозы и BMI, что может свидетельствовать о том, что ожирение в какой-то мере связано с повышением уровня глюкозы в крови."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Пример бизнес-целей:**\n",
    "1. Прогнозирование риска диабета\n",
    "\n",
    "Цель: Создать модель, которая точно предсказывает вероятность развития диабета на основе медицинских параметров пациента, таких как уровень глюкозы, индекс массы тела и количество беременностей.\n",
    "\n",
    "Эффекты для бизнеса: Повышение эффективности диагностики диабета на ранних стадиях, что позволяет своевременно предложить лечение или профилактические меры. Это может сократить затраты на лечение хронических стадий диабета и улучшить здоровье пациентов.\n",
    "\n",
    "Вход:\n",
    "\n",
    "* Уровень глюкозы\n",
    "* Индекс массы тела (BMI)\n",
    "* Количество беременностей\n",
    "\n",
    "Целевой признак: Наличие диабета (Outcome).\n",
    "\n",
    "2. Анализ факторов риска диабета\n",
    "\n",
    "Цель: Провести анализ влияния различных факторов (например, возраст, уровень инсулина, давление) на вероятность развития диабета для оптимизации профилактических программ.\n",
    "\n",
    "Эффекты для бизнеса: Улучшение стратегии профилактики диабета, нацеленное на людей с высоким риском заболевания. Это поможет лучше планировать медицинские ресурсы, а также разработать программы по улучшению здоровья для целевых групп населения.\n",
    "\n",
    "Вход:\n",
    "\n",
    "* Возраст\n",
    "* Уровень инсулина\n",
    "* Артериальное давление\n",
    "\n",
    "Целевой признак: Вероятность развития диабета.\n",
    "\n",
    "3. Оценка состояния здоровья пациентов\n",
    "\n",
    "Цель: Разработать модель для оценки общего состояния здоровья пациента на основе параметров, таких как индекс массы тела (BMI) и артериальное давление. Это поможет предсказать риски не только диабета, но и других заболеваний, связанных с метаболическим синдромом.\n",
    "\n",
    "Эффекты для бизнеса: Повышение эффективности медицинских осмотров и точности оценки состояния здоровья пациентов. Это позволяет медицинским организациям улучшить предоставляемые услуги и повысить удовлетворенность пациентов.\n",
    "\n",
    "Вход:\n",
    "\n",
    "* Индекс массы тела (BMI)\n",
    "* Артериальное давление\n",
    "* Уровень глюкозы\n",
    "\n",
    "Целевой признак: Оценка состояния здоровья пациента (например, классификация по уровням риска)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Опредиление проблем данных с помощью кода:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Максимальные значения:\n",
      " Pregnancies                  17.00\n",
      "Glucose                     199.00\n",
      "BloodPressure               122.00\n",
      "SkinThickness                99.00\n",
      "Insulin                     846.00\n",
      "BMI                          67.10\n",
      "DiabetesPedigreeFunction      2.42\n",
      "Age                          81.00\n",
      "Outcome                       1.00\n",
      "dtype: float64 \n",
      "\n",
      "Признаки с нулевыми значениями:\n",
      " Index(['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin',\n",
      "       'BMI', 'Outcome'],\n",
      "      dtype='object') \n",
      "\n",
      "Признаки с низкой дисперсией:\n",
      " Series([], dtype: float64) \n",
      "\n"
     ]
    }
   ],
   "source": [
    "max_value = df3.max(axis=0)\n",
    "\n",
    "columns_with_zero = df3.columns[(df3 == 0).any()]\n",
    "\n",
    "numeric_data = df3.select_dtypes(include='number')\n",
    "\n",
    "shum = numeric_data.var()\n",
    "\n",
    "low_dispers = 0.1\n",
    "low_var_columns = shum[shum < low_dispers]\n",
    "\n",
    "\n",
    "print(\"Максимальные значения:\\n\", max_value, \"\\n\")\n",
    "print(\"Признаки с нулевыми значениями:\\n\", columns_with_zero, \"\\n\")\n",
    "print(\"Признаки с низкой дисперсией:\\n\", low_var_columns, \"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8))\n",
    "numeric_data = df3.select_dtypes(include='number')\n",
    "correlation_matrix = numeric_data.corr()\n",
    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', vmin=-1, vmax=1)\n",
    "plt.title('Корреляционная матрица для проверки просачивания данных')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "В данных которые содержаться в таблице нету ни низкой дисперсии, ни выбросов связанных с аномально высокими значениями. Есть только нулевые значения. По графику видно что в целом, данные не указывают на очевидное просачивание, поскольку корреляции не слишком высокие и ожидаемы. Данные хорошо сформированны поэтому здесь нет проблем для анализа."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Пропущенные значения до обработки:\n",
      "Pregnancies                 0\n",
      "Glucose                     0\n",
      "BloodPressure               0\n",
      "SkinThickness               0\n",
      "Insulin                     0\n",
      "BMI                         0\n",
      "DiabetesPedigreeFunction    0\n",
      "Age                         0\n",
      "Outcome                     0\n",
      "dtype: int64\n",
      "Пропущенные значения после обработки:\n",
      "Pregnancies                 0\n",
      "Glucose                     0\n",
      "BloodPressure               0\n",
      "SkinThickness               0\n",
      "Insulin                     0\n",
      "BMI                         0\n",
      "DiabetesPedigreeFunction    0\n",
      "Age                         0\n",
      "Outcome                     0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "numeric_columns = ['Pregnancies', 'Glucose', 'BloodPressure', 'SkinThickness', 'Insulin', 'BMI', 'Outcome']\n",
    "df3[numeric_columns] = df3[numeric_columns].replace(\"-\", np.nan)\n",
    "print(\"Пропущенные значения до обработки:\")\n",
    "print(df3.isnull().sum())\n",
    "\n",
    "df3['Pregnancies'] = df3['Pregnancies'].fillna(0) \n",
    "df3['Glucose'] = df3['Glucose'].astype(float)  \n",
    "df3.dropna(subset=['BloodPressure'], inplace=True)  \n",
    "\n",
    "print(\"Пропущенные значения после обработки:\")\n",
    "print(df3.isnull().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Оценить качество каждого набора данных:** "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Информативность: Набор данных предоставляет достаточную информацию для анализа характиристик пациента с или без деабета.\n",
    "2. Степень покрытия: Включает данные только Индии, поэтому поностью на них основываться нельзя.\n",
    "3. Соответствие реальным данным: Данные в целом соответствуют реальным значениям.\n",
    "4. Согласованность меток: в основном касается бинарного признака Outcome, который должен принимать только два значения: 1 (диабет) и 0 (отсутствие диабета)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Выполнить разбиение каждого набора данных на обучающую, контрольную и тестовую выборки:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Размер обучающей выборки: 460\n",
      "Размер контрольной выборки: 154\n",
      "Размер тестовой выборки: 154\n"
     ]
    }
   ],
   "source": [
    "X = df3.drop('Outcome', axis=1)  \n",
    "y = df3['Outcome']  \n",
    "\n",
    "X_train, X_temp, y_train, y_temp = train_test_split(X, y, test_size=0.4, random_state=42)\n",
    "\n",
    "X_val, X_test, y_val, y_test = train_test_split(X_temp, y_temp, test_size=0.5, random_state=42)\n",
    "\n",
    "# Вывод размеров выборок\n",
    "print(\"Размер обучающей выборки:\", X_train.shape[0])\n",
    "print(\"Размер контрольной выборки:\", X_val.shape[0])\n",
    "print(\"Размер тестовой выборки:\", X_test.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Сбалансированность обучающей выборки:\n",
      "Outcome\n",
      "0    0.65\n",
      "1    0.35\n",
      "Name: proportion, dtype: float64\n",
      "\n",
      "Сбалансированность контрольной выборки:\n",
      "Outcome\n",
      "0    0.649351\n",
      "1    0.350649\n",
      "Name: proportion, dtype: float64\n",
      "\n",
      "Сбалансированность тестовой выборки:\n",
      "Outcome\n",
      "0    0.655844\n",
      "1    0.344156\n",
      "Name: proportion, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "X = df3.drop('Outcome', axis=1)  \n",
    "y = df3['Outcome']  \n",
    "\n",
    "# Разбиение на обучающую и оставшуюся часть (контрольная + тестовая)\n",
    "X_train, X_temp, y_train, y_temp = train_test_split(X, y, test_size=0.4, random_state=42, stratify=y)\n",
    "\n",
    "# Разбиение оставшейся части на контрольную и тестовую выборки\n",
    "X_val, X_test, y_val, y_test = train_test_split(X_temp, y_temp, test_size=0.5, random_state=42, stratify=y_temp)\n",
    "\n",
    "# Функция для проверки сбалансированности выборок\n",
    "def check_balance(y_train, y_val, y_test):\n",
    "    print(\"Сбалансированность обучающей выборки:\")\n",
    "    print(y_train.value_counts(normalize=True))\n",
    "    \n",
    "    print(\"\\nСбалансированность контрольной выборки:\")\n",
    "    print(y_val.value_counts(normalize=True))\n",
    "    \n",
    "    print(\"\\nСбалансированность тестовой выборки:\")\n",
    "    print(y_test.value_counts(normalize=True))\n",
    "\n",
    "# Проверка сбалансированности\n",
    "check_balance(y_train, y_val, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Выполнить приращение данных методами выборки с избытком (oversampling) и выборки с недостатком (undersampling):**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Сбалансированность обучающей выборки после SMOTE:\n",
      "Outcome\n",
      "1    0.5\n",
      "0    0.5\n",
      "Name: proportion, dtype: float64\n",
      "Сбалансированность обучающей выборки:\n",
      "Outcome\n",
      "1    0.5\n",
      "0    0.5\n",
      "Name: proportion, dtype: float64\n",
      "\n",
      "Сбалансированность контрольной выборки:\n",
      "Outcome\n",
      "0    0.649351\n",
      "1    0.350649\n",
      "Name: proportion, dtype: float64\n",
      "\n",
      "Сбалансированность тестовой выборки:\n",
      "Outcome\n",
      "0    0.655844\n",
      "1    0.344156\n",
      "Name: proportion, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# Разделение на признаки (X) и целевую переменную (y)\n",
    "X = df3.drop('Outcome', axis=1)  # Признаки\n",
    "y = df3['Outcome']  # Целевая переменная\n",
    "\n",
    "# Разбиение на обучающую и оставшуюся часть (контрольная + тестовая)\n",
    "X_train, X_temp, y_train, y_temp = train_test_split(X, y, test_size=0.4, random_state=42, stratify=y)\n",
    "\n",
    "# Разбиение оставшейся части на контрольную и тестовую выборки\n",
    "X_val, X_test, y_val, y_test = train_test_split(X_temp, y_temp, test_size=0.5, random_state=42, stratify=y_temp)\n",
    "\n",
    "# Применение SMOTE для балансировки обучающей выборки\n",
    "smote = SMOTE(random_state=42)\n",
    "X_train_resampled, y_train_resampled = smote.fit_resample(X_train, y_train)\n",
    "\n",
    "# Функция для проверки сбалансированности выборок\n",
    "def check_balance(y_train, y_val, y_test):\n",
    "    print(\"Сбалансированность обучающей выборки:\")\n",
    "    print(y_train.value_counts(normalize=True))\n",
    "    \n",
    "    print(\"\\nСбалансированность контрольной выборки:\")\n",
    "    print(y_val.value_counts(normalize=True))\n",
    "    \n",
    "    print(\"\\nСбалансированность тестовой выборки:\")\n",
    "    print(y_test.value_counts(normalize=True))\n",
    "\n",
    "# Проверка сбалансированности после SMOTE\n",
    "print(\"Сбалансированность обучающей выборки после SMOTE:\")\n",
    "print(y_train_resampled.value_counts(normalize=True))\n",
    "\n",
    "# Проверка сбалансированности контрольной и тестовой выборок\n",
    "check_balance(y_train_resampled, y_val, y_test)"
   ]
  }
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