AIM-PIbd-31-Alekseev-I-S/Lab_1/Lab1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Начало лабораторной\n",
    "\n",
    "Выгрузка данных из csv-файла в датафрейм"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['id', 'name', 'est_diameter_min', 'est_diameter_max',\n",
      "       'relative_velocity', 'miss_distance', 'orbiting_body', 'sentry_object',\n",
      "       'absolute_magnitude', 'hazardous'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv(\".//static//csv//neo.csv\")\n",
    "print(df.columns)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Группированная столбчатая диаграмма: опасные и неопасные объекты\n",
    "\n",
    "Это столбчатая диаграмма, показывающая распределение объектов, классифицированных как \"опасные\" (hazardous=True) и \"неопасные\" (hazardous=False).\n",
    "Исходя из нее, мы можем увидеть долю потенциально опасных объектов среди всех ближайших к Земле объектов\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Загрузка данных\n",
    "df = pd.read_csv(\".//static//csv//neo.csv\")\n",
    "\n",
    "# Отбор первых 15000 записей\n",
    "df_subset = df.head(15000)\n",
    "\n",
    "# Создаем группированную столбчатую диаграмму для опасных и неопасных объектов\n",
    "sns.countplot(x='hazardous', data=df_subset)\n",
    "\n",
    "# Настройка подписей и заголовков\n",
    "plt.title('Распределение опасных и неопасных объектов (первые 15000)')\n",
    "plt.xlabel('Опасный объект')\n",
    "plt.ylabel('Количество объектов')\n",
    "\n",
    "# Отображение диаграммы\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Коробчатая диаграмма: Сравнение скорости и дистанции (relative_velocity, miss_distance)\n",
    "\n",
    "Это диаграмма, показывающая медиану, квартилы и выбросы для относительной скорости и минимального расстояния до Земли. Использование relative_velocity и miss_distance в одной диаграмме покажет, как сильно варьируются данные, и выделит потенциальные \"быстрые\" объекты, которые проходят близко к Земле."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Импорт библиотек\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Загрузка данных\n",
    "df = pd.read_csv(\".//static//csv//neo.csv\")\n",
    "\n",
    "# Отбор первых 15000 записей\n",
    "df_subset = df[['relative_velocity', 'miss_distance']].head(15000)\n",
    "\n",
    "# Создание боксплота для сравнения relative_velocity и miss_distance\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.boxplot(data=df_subset)\n",
    "plt.title(\"Boxplot: Сравнение относительной скорости и минимального расстояния до Земли (первые 15000 записей)\")\n",
    "plt.ylabel(\"Значение\")\n",
    "plt.xticks([0, 1], ['Relative Velocity', 'Miss Distance'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Точечная диаграмма: Взаимосвязь между абсолютной магнитудой и минимальным диаметром (absolute_magnitude vs. est_diameter_min)\n",
    "\n",
    "Это диаграмма, показывающая взаимосвязь между абсолютной магнитудой объектов (которая часто связана с их яркостью) и их минимальными размерами.\n",
    "С помощью нее можно сделать вывод, что большинство объектов — это небольшие тела с относительно высокой абсолютной магнитудой (менее яркие), но встречаются и исключения — более крупные объекты с малой абсолютной магнитудой (яркие)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt  \n",
    "\n",
    "# Загрузка данных\n",
    "df = pd.read_csv(\".//static//csv//neo.csv\")\n",
    "\n",
    "# Создаем точечную диаграмму для взаимосвязи абсолютной магнитуды и минимального диаметра\n",
    "plt.figure(figsize=(10, 6))\n",
    "sns.scatterplot(x='absolute_magnitude', y='est_diameter_min', data=df)\n",
    "\n",
    "# Настройка подписей и заголовков\n",
    "plt.title('Взаимосвязь между абсолютной магнитудой и минимальным диаметром')\n",
    "plt.xlabel('Абсолютная магнитуда')\n",
    "plt.ylabel('Минимальный диаметр (км)')\n",
    "\n",
    "# Отображение диаграммы\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "aimenv",
   "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": "3.12.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}