2labaPractica/week2_analysis.ipynb

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   "source": [
    "# Анализ данных - Неделя 2\n",
    "**Автор:** Александр Писцов  \n",
    "Этот блокнот содержит базовый анализ с pandas и matplotlib."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4b73c60f-cd31-402a-b3a8-97e9fa0eacb7",
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'pandas'",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mModuleNotFoundError\u001b[39m                       Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[3]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mpandas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mpd\u001b[39;00m\n\u001b[32m      3\u001b[39m \u001b[38;5;66;03m# Создаем таблицу\u001b[39;00m\n\u001b[32m      4\u001b[39m data = {\n\u001b[32m      5\u001b[39m     \u001b[33m\"\u001b[39m\u001b[33mИмя\u001b[39m\u001b[33m\"\u001b[39m: [\u001b[33m\"\u001b[39m\u001b[33mАнна\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mБорис\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mВиктор\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mГалина\u001b[39m\u001b[33m\"\u001b[39m],\n\u001b[32m      6\u001b[39m     \u001b[33m\"\u001b[39m\u001b[33mВозраст\u001b[39m\u001b[33m\"\u001b[39m: [\u001b[32m21\u001b[39m, \u001b[32m22\u001b[39m, \u001b[32m23\u001b[39m, \u001b[32m24\u001b[39m],\n\u001b[32m      7\u001b[39m     \u001b[33m\"\u001b[39m\u001b[33mБаллы\u001b[39m\u001b[33m\"\u001b[39m: [\u001b[32m89\u001b[39m, \u001b[32m76\u001b[39m, \u001b[32m95\u001b[39m, \u001b[32m82\u001b[39m]\n\u001b[32m      8\u001b[39m }\n",
      "\u001b[31mModuleNotFoundError\u001b[39m: No module named 'pandas'"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Создаем таблицу\n",
    "data = {\n",
    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
    "    \"Возраст\": [21, 22, 23, 24],\n",
    "    \"Баллы\": [89, 76, 95, 82]\n",
    "}\n",
    "df = pd.DataFrame(data)\n",
    "\n",
    "# Добавляем столбец\n",
    "df[\"Бонусные баллы\"] = df[\"Баллы\"] * 1.1\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c2e25c6c-bbda-4bb7-8b27-56579b481174",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Произведение матриц:\n",
      " [[ 7 10]\n",
      " [15 22]]\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "# Создаем матрицу 2x2\n",
    "matrix = np.array([[1, 2], [3, 4]])\n",
    "print(\"Произведение матриц:\\n\", np.dot(matrix, matrix))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d8412aa4-fb69-4da4-9d5e-ce6e1924c7ae",
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'matplotlib'",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mModuleNotFoundError\u001b[39m                       Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[2]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mmatplotlib\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mpyplot\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mplt\u001b[39;00m\n\u001b[32m      3\u001b[39m plt.figure(figsize=(\u001b[32m8\u001b[39m, \u001b[32m4\u001b[39m))\n\u001b[32m      4\u001b[39m plt.bar(df[\u001b[33m\"\u001b[39m\u001b[33mИмя\u001b[39m\u001b[33m\"\u001b[39m], df[\u001b[33m\"\u001b[39m\u001b[33mБаллы\u001b[39m\u001b[33m\"\u001b[39m], color=\u001b[33m'\u001b[39m\u001b[33mskyblue\u001b[39m\u001b[33m'\u001b[39m)\n",
      "\u001b[31mModuleNotFoundError\u001b[39m: No module named 'matplotlib'"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.figure(figsize=(8, 4))\n",
    "plt.bar(df[\"Имя\"], df[\"Баллы\"], color='skyblue')\n",
    "plt.title(\"Баллы студентов\")\n",
    "plt.xlabel(\"Имя\")\n",
    "plt.ylabel(\"Баллы\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2b5c128b-f9a8-408e-b128-6360630b4f9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "sns.scatterplot(data=df, x=\"Возраст\", y=\"Баллы\", hue=\"Имя\", s=100)\n",
    "plt.title(\"Зависимость баллов от возраста\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "652d456d-8a78-40a2-84ea-b76caf74224f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm\n",
    "import time\n",
    "\n",
    "print(\"Обработка данных:\")\n",
    "for i in tqdm(range(100), desc=\"Прогресс\"):\n",
    "    time.sleep(0.02)  # Имитация работы"
   ]
  }
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