Pract_Jupiter/Jupyter_pract.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "06b5a5fb-cc6e-45f2-bb8c-c61ca7763bc0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Первый взгляд на данные:\n",
      "      Имя  Возраст  Баллы\n",
      "0    Анна       21     89\n",
      "1   Борис       22     76\n",
      "2  Виктор       23     95\n",
      "3  Галина       24     82\n",
      "=======================\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4 entries, 0 to 3\n",
      "Data columns (total 3 columns):\n",
      " #   Column   Non-Null Count  Dtype \n",
      "---  ------   --------------  ----- \n",
      " 0   Имя      4 non-null      object\n",
      " 1   Возраст  4 non-null      int64 \n",
      " 2   Баллы    4 non-null      int64 \n",
      "dtypes: int64(2), object(1)\n",
      "memory usage: 228.0+ bytes\n",
      "None\n",
      "=======================\n",
      "         Возраст      Баллы\n",
      "count   4.000000   4.000000\n",
      "mean   22.500000  85.500000\n",
      "std     1.290994   8.266398\n",
      "min    21.000000  76.000000\n",
      "25%    21.750000  80.500000\n",
      "50%    22.500000  85.500000\n",
      "75%    23.250000  90.500000\n",
      "max    24.000000  95.000000\n",
      "=======================\n",
      "Имя        0\n",
      "Возраст    0\n",
      "Баллы      0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Создадим DataFrame\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",
    "print(\"Первый взгляд на данные:\")\n",
    "print(df.head())\n",
    "print(\"=======================\")\n",
    "print(df.info())\n",
    "print(\"=======================\")\n",
    "print(df.describe())\n",
    "print(\"=======================\")\n",
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c60c2cc7-05db-43b1-af88-42da63a514ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Первый взгляд на данные:\n",
      "      Имя  Возраст  Баллы\n",
      "0    Анна       21     89\n",
      "1   Борис       22     76\n",
      "2  Виктор       23     95\n",
      "3  Галина       24     82\n",
      "=======================\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4 entries, 0 to 3\n",
      "Data columns (total 3 columns):\n",
      " #   Column   Non-Null Count  Dtype \n",
      "---  ------   --------------  ----- \n",
      " 0   Имя      4 non-null      object\n",
      " 1   Возраст  4 non-null      int64 \n",
      " 2   Баллы    4 non-null      int64 \n",
      "dtypes: int64(2), object(1)\n",
      "memory usage: 228.0+ bytes\n",
      "None\n",
      "=======================\n",
      "         Возраст      Баллы\n",
      "count   4.000000   4.000000\n",
      "mean   22.500000  85.500000\n",
      "std     1.290994   8.266398\n",
      "min    21.000000  76.000000\n",
      "25%    21.750000  80.500000\n",
      "50%    22.500000  85.500000\n",
      "75%    23.250000  90.500000\n",
      "max    24.000000  95.000000\n",
      "=======================\n",
      "Имя        0\n",
      "Возраст    0\n",
      "Баллы      0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Создадим DataFrame\n",
    "data = {\n",
    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
    "    \"Возраст\": [21, 22, 23, 24],\n",
    "    \"Баллы\": [89, 76, 95, 82]\n",
    "}\n",
    "\n",
    "print(\"Первый взгляд на данные:\")\n",
    "print(df.head())\n",
    "print(\"=======================\")\n",
    "print(df.info())\n",
    "print(\"=======================\")\n",
    "print(df.describe())\n",
    "print(\"=======================\")\n",
    "print(df.isnull().sum())\n",
    "df = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4e09e604-c338-4a7e-9f2e-17daca392b2d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Первый взгляд на данные:\n",
      "      Имя  Возраст  Баллы  Баллы + 10\n",
      "0    Анна       21     89        97.9\n",
      "1   Борис       22     76        83.6\n",
      "2  Виктор       23     95       104.5\n",
      "3  Галина       24     82        90.2\n",
      "=======================\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4 entries, 0 to 3\n",
      "Data columns (total 4 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   Имя         4 non-null      object \n",
      " 1   Возраст     4 non-null      int64  \n",
      " 2   Баллы       4 non-null      int64  \n",
      " 3   Баллы + 10  4 non-null      float64\n",
      "dtypes: float64(1), int64(2), object(1)\n",
      "memory usage: 260.0+ bytes\n",
      "None\n",
      "=======================\n",
      "         Возраст      Баллы  Баллы + 10\n",
      "count   4.000000   4.000000    4.000000\n",
      "mean   22.500000  85.500000   94.050000\n",
      "std     1.290994   8.266398    9.093038\n",
      "min    21.000000  76.000000   83.600000\n",
      "25%    21.750000  80.500000   88.550000\n",
      "50%    22.500000  85.500000   94.050000\n",
      "75%    23.250000  90.500000   99.550000\n",
      "max    24.000000  95.000000  104.500000\n",
      "=======================\n",
      "Имя           0\n",
      "Возраст       0\n",
      "Баллы         0\n",
      "Баллы + 10    0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Создадим DataFrame\n",
    "data = {\n",
    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
    "    \"Возраст\": [21, 22, 23, 24],\n",
    "    \"Баллы\": [89, 76, 95, 82]\n",
    "}\n",
    "\n",
    "df = pd.DataFrame(data)\n",
    "df[\"Баллы + 10\"] = df[\"Баллы\"] * 1.1\n",
    "\n",
    "print(\"Первый взгляд на данные:\")\n",
    "print(df.head())\n",
    "print(\"=======================\")\n",
    "print(df.info())\n",
    "print(\"=======================\")\n",
    "print(df.describe())\n",
    "print(\"=======================\")\n",
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "54b9a1b3-ac47-47ee-ba7f-38c4cbf778ed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Первый взгляд на данные:\n",
      "      Имя  Возраст  Баллы  Баллы + 10\n",
      "0    Анна       21     89        97.9\n",
      "1   Борис       22     76        83.6\n",
      "2  Виктор       23     95       104.5\n",
      "3  Галина       24     82        90.2\n",
      "=======================\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4 entries, 0 to 3\n",
      "Data columns (total 4 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   Имя         4 non-null      object \n",
      " 1   Возраст     4 non-null      int64  \n",
      " 2   Баллы       4 non-null      int64  \n",
      " 3   Баллы + 10  4 non-null      float64\n",
      "dtypes: float64(1), int64(2), object(1)\n",
      "memory usage: 260.0+ bytes\n",
      "None\n",
      "=======================\n",
      "         Возраст      Баллы  Баллы + 10\n",
      "count   4.000000   4.000000    4.000000\n",
      "mean   22.500000  85.500000   94.050000\n",
      "std     1.290994   8.266398    9.093038\n",
      "min    21.000000  76.000000   83.600000\n",
      "25%    21.750000  80.500000   88.550000\n",
      "50%    22.500000  85.500000   94.050000\n",
      "75%    23.250000  90.500000   99.550000\n",
      "max    24.000000  95.000000  104.500000\n",
      "=======================\n",
      "Имя           0\n",
      "Возраст       0\n",
      "Баллы         0\n",
      "Баллы + 10    0\n",
      "dtype: int64\n",
      "=======================\n",
      "Минимальные Баллы    76\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Создадим DataFrame\n",
    "data = {\n",
    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
    "    \"Возраст\": [21, 22, 23, 24],\n",
    "    \"Баллы\": [89, 76, 95, 82]\n",
    "}\n",
    "\n",
    "df = pd.DataFrame(data)\n",
    "df[\"Баллы + 10\"] = df[\"Баллы\"] * 1.1\n",
    "\n",
    "print(\"Первый взгляд на данные:\")\n",
    "print(df.head())\n",
    "print(\"=======================\")\n",
    "print(df.info())\n",
    "print(\"=======================\")\n",
    "print(df.describe())\n",
    "print(\"=======================\")\n",
    "print(df.isnull().sum())\n",
    "print(\"=======================\")\n",
    "grouped = df.groupby([\"Баллы\",\"Баллы + 10\"])\n",
    "print(\"Минимальные\", df.agg({\"Баллы\":\"min\"}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c8d503ba-a3c8-41b7-85fa-a5513c9d9c18",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Сумма элементов массива: 15\n",
      "Среднее значение: 3.0\n",
      "Медиана: 3.0\n",
      "Стандартное отклонение: 1.4142135623730951\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "arr = np.array([1, 2, 3, 4, 5])\n",
    "print(\"Сумма элементов массива:\", np.sum(arr))\n",
    "print(\"Среднее значение:\", np.mean(arr))\n",
    "print(\"Медиана:\", np.median(arr))\n",
    "print(\"Стандартное отклонение:\", np.std(arr))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "61f46ba7-8a0f-476a-b93a-4de803f6cb1b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Сумма элементов массива: 15\n",
      "Среднее значение: 3.0\n",
      "Медиана: 3.0\n",
      "Стандартное отклонение: 1.4142135623730951\n",
      "[[1 2]\n",
      " [3 4]]\n",
      "[1. 2. 3. 4. 5.]\n",
      "0.4694445923080879\n",
      "55.0\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "arr = np.array([1, 2, 3, 4, 5])\n",
    "print(\"Сумма элементов массива:\", np.sum(arr))\n",
    "print(\"Среднее значение:\", np.mean(arr))\n",
    "print(\"Медиана:\", np.median(arr))\n",
    "print(\"Стандартное отклонение:\", np.std(arr))\n",
    "print(np.array([[1, 2], [3, 4]]))\n",
    "print(np.linspace(1,5,5))\n",
    "print(np.random.randn())\n",
    "print(np.dot(arr,np.linspace(1,5,5)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "8842dc5e-c96c-4c1a-9c91-9c544456a770",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(array([1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0.,\n",
       "        0., 0., 1.]),\n",
       " array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. , 1.1, 1.2,\n",
       "        1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2. ]),\n",
       " <BarContainer object of 20 artists>)"
      ]
     },
     "execution_count": 79,
     "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": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = np.linspace(0, 10, 100)\n",
    "y = np.sin(x)\n",
    "\n",
    "plt.plot(x, y, label='sin(x)',color =\"red\")\n",
    "plt.plot(x, np.cos(x), label='cos(x)')\n",
    "plt.xlabel(\"X\")\n",
    "plt.ylabel(\"Y\")\n",
    "plt.title(\"График синуса и косиснуса\")\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.show()\n",
    "\n",
    "x = [1, 3, 5, 7, 9]\n",
    "y = [5, 2, 7, 8, 2]\n",
    "plt.bar(x, y)\n",
    "plt.show()\n",
    "plt.scatter(x, y, marker='o', color='b')\n",
    "plt.show()\n",
    "plt.hist(data, bins=20, edgecolor='black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "d640c0ba-ca25-42f4-8c2a-44b7e0dc5cf7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x26d4b3c7020>"
      ]
     },
     "execution_count": 66,
     "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"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 750x750 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\"] # догадайтесь откуда df и её содержимое взялось\n",
    "sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
    "plt.show()\n",
    "tips = sns.load_dataset(\"tips\")\n",
    "sns.scatterplot(x=\"total_bill\", y=\"tip\", hue=\"sex\", data=tips)\n",
    "plt.show()\n",
    "sns.histplot(data=tips, x=\"total_bill\", bins=30, kde=True, color='skyblue')\n",
    "sns.pairplot(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "abfd469b-46b3-4594-b6f8-d9cfd3f3e573",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[A\u001b[Aка:   0%|                                                                                | 0/100 [00:00<?, ?it/s]\n",
      "\n",
      "\u001b[A\u001b[Aка:  10%|███████                                                                | 10/100 [00:00<00:00, 95.23it/s]\n",
      "\n",
      "\u001b[A\u001b[Aка:  20%|██████████████▏                                                        | 20/100 [00:00<00:00, 92.99it/s]\n",
      "\n",
      "\u001b[A\u001b[Aка:  30%|█████████████████████▎                                                 | 30/100 [00:00<00:00, 92.16it/s]\n",
      "\n",
      "\u001b[A\u001b[Aка:  40%|████████████████████████████▍                                          | 40/100 [00:00<00:00, 92.18it/s]\n",
      "\n",
      "\u001b[A\u001b[Aка:  50%|███████████████████████████████████▌                                   | 50/100 [00:00<00:00, 93.18it/s]\n",
      "\n",
      "\u001b[A\u001b[Aка:  60%|██████████████████████████████████████████▌                            | 60/100 [00:00<00:00, 93.54it/s]\n",
      "\n",
      "\u001b[A\u001b[Aка:  70%|█████████████████████████████████████████████████▋                     | 70/100 [00:00<00:00, 93.58it/s]\n",
      "\n",
      "\u001b[A\u001b[Aка:  80%|████████████████████████████████████████████████████████▊              | 80/100 [00:00<00:00, 94.03it/s]\n",
      "\n",
      "\u001b[A\u001b[Aка:  90%|███████████████████████████████████████████████████████████████▉       | 90/100 [00:00<00:00, 93.07it/s]\n",
      "\n",
      "Загрузка: 100%|██████████████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 92.66it/s]\n"
     ]
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "import time\n",
    "\n",
    "for i in tqdm(range(100), desc='Загрузка'):\n",
    "    time.sleep(0.01)  # Симуляция долгого процесса\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "10068b3b-5abc-491c-b152-0bbc697cc60a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[A\u001b[Asing rows:   0%|                                                                         | 0/100 [00:00<?, ?it/s]\n",
      "\n",
      "\u001b[A\u001b[Asing rows:  10%|██████▍                                                         | 10/100 [00:00<00:00, 94.67it/s]\n",
      "\n",
      "\u001b[A\u001b[Asing rows:  20%|████████████▊                                                   | 20/100 [00:00<00:00, 91.79it/s]\n",
      "\n",
      "\u001b[A\u001b[Asing rows:  30%|███████████████████▏                                            | 30/100 [00:00<00:00, 91.11it/s]\n",
      "\n",
      "\u001b[A\u001b[Asing rows:  40%|█████████████████████████▌                                      | 40/100 [00:00<00:00, 91.62it/s]\n",
      "\n",
      "\u001b[A\u001b[Asing rows:  50%|████████████████████████████████                                | 50/100 [00:00<00:00, 92.36it/s]\n",
      "\n",
      "\u001b[A\u001b[Asing rows:  60%|██████████████████████████████████████▍                         | 60/100 [00:00<00:00, 92.86it/s]\n",
      "\n",
      "\u001b[A\u001b[Asing rows:  70%|████████████████████████████████████████████▊                   | 70/100 [00:00<00:00, 92.93it/s]\n",
      "\n",
      "\u001b[A\u001b[Asing rows:  80%|███████████████████████████████████████████████████▏            | 80/100 [00:00<00:00, 92.90it/s]\n",
      "\n",
      "\u001b[A\u001b[Asing rows:  90%|█████████████████████████████████████████████████████████▌      | 90/100 [00:00<00:00, 93.05it/s]\n",
      "\n",
      "Processing rows: 100%|███████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 92.63it/s]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from tqdm import tqdm\n",
    "import time\n",
    "\n",
    "df = pd.DataFrame({'data': range(100)})\n",
    "\n",
    "for index, row in tqdm(df.iterrows(), total=len(df), desc=\"Processing rows\"):\n",
    "    time.sleep(0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aef84631-3802-42dd-b30e-7ca00f0f16f1",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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