JupyterLabDatas/week2_analysis.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": "# Анализ и визуализация данных",
"id": "title"
},
{
"cell_type": "markdown",
"metadata": {},
"source": "## 1. Работа с pandas и numpy",
"id": "section3"
},
{
"cell_type": "markdown",
"metadata": {},
"source": "### 1.1. pandas: работа с таблицами",
"id": "pandas_title"
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:47:59.985559700Z",
"start_time": "2026-05-07T09:47:46.403400Z"
}
},
"source": [
"import pandas as pd\n",
"\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('Пропуски:', df.isnull().sum().to_dict())"
],
"id": "pandas_base",
"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.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 str \n",
" 1 Возраст 4 non-null int64\n",
" 2 Баллы 4 non-null int64\n",
"dtypes: int64(2), str(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",
"Пропуски: {'Имя': 0, 'Возраст': 0, 'Баллы': 0}\n"
]
}
],
"execution_count": 1
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:48:00.128765900Z",
"start_time": "2026-05-07T09:48:00.001295700Z"
}
},
"source": [
"# Добавляем новый столбец с вычисляемыми значениями\n",
"df['Баллы х1.1'] = df['Баллы'] * 1.1\n",
"df"
],
"id": "pandas_new_col",
"outputs": [
{
"data": {
"text/plain": [
" Имя Возраст Баллы Баллы х1.1\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"
],
"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>Имя</th>\n",
" <th>Возраст</th>\n",
" <th>Баллы</th>\n",
" <th>Баллы х1.1</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Анна</td>\n",
" <td>21</td>\n",
" <td>89</td>\n",
" <td>97.9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Борис</td>\n",
" <td>22</td>\n",
" <td>76</td>\n",
" <td>83.6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Виктор</td>\n",
" <td>23</td>\n",
" <td>95</td>\n",
" <td>104.5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Галина</td>\n",
" <td>24</td>\n",
" <td>82</td>\n",
" <td>90.2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 2
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:48:00.217327500Z",
"start_time": "2026-05-07T09:48:00.141128900Z"
}
},
"source": [
"# Добавляем категорию и группируем\n",
"df['Категория'] = ['A', 'B', 'A', 'B']\n",
"\n",
"df.groupby('Категория').agg(\n",
" Средний_возраст=('Возраст', 'mean'),\n",
" Средние_баллы=('Баллы', 'mean'),\n",
" Количество=('Имя', 'count')\n",
")"
],
"id": "pandas_groupby",
"outputs": [
{
"data": {
"text/plain": [
" Средний_возраст Средние_баллы Количество\n",
"Категория \n",
"A 22.0 92.0 2\n",
"B 23.0 79.0 2"
],
"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>Средний_возраст</th>\n",
" <th>Средние_баллы</th>\n",
" <th>Количество</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Категория</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>A</th>\n",
" <td>22.0</td>\n",
" <td>92.0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>B</th>\n",
" <td>23.0</td>\n",
" <td>79.0</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 3
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:48:01.376206300Z",
"start_time": "2026-05-07T09:48:00.741165500Z"
}
},
"source": [
"# Фильтрация: только студенты старше 21 года\n",
"df[df['Возраст'] > 21]"
],
"id": "pandas_filter",
"outputs": [
{
"data": {
"text/plain": [
" Имя Возраст Баллы Баллы х1.1 Категория\n",
"1 Борис 22 76 83.6 B\n",
"2 Виктор 23 95 104.5 A\n",
"3 Галина 24 82 90.2 B"
],
"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>Имя</th>\n",
" <th>Возраст</th>\n",
" <th>Баллы</th>\n",
" <th>Баллы х1.1</th>\n",
" <th>Категория</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Борис</td>\n",
" <td>22</td>\n",
" <td>76</td>\n",
" <td>83.6</td>\n",
" <td>B</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Виктор</td>\n",
" <td>23</td>\n",
" <td>95</td>\n",
" <td>104.5</td>\n",
" <td>A</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Галина</td>\n",
" <td>24</td>\n",
" <td>82</td>\n",
" <td>90.2</td>\n",
" <td>B</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 4
},
{
"cell_type": "markdown",
"metadata": {},
"source": "### 1.2. numpy: массивы и вычисления",
"id": "numpy_title"
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:48:04.315669800Z",
"start_time": "2026-05-07T09:48:04.234172200Z"
}
},
"source": [
"import numpy as np\n",
"\n",
"arr = np.array([1, 2, 3, 4, 5])\n",
"print('Массив:', arr)\n",
"print('Сумма:', np.sum(arr))\n",
"print('Среднее:', np.mean(arr))\n",
"print('Медиана:', np.median(arr))\n",
"print('Стандартное откл.:', np.std(arr))"
],
"id": "numpy_base",
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Массив: [1 2 3 4 5]\n",
"Сумма: 15\n",
"Среднее: 3.0\n",
"Медиана: 3.0\n",
"Стандартное откл.: 1.4142135623730951\n"
]
}
],
"execution_count": 5
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:48:04.481239800Z",
"start_time": "2026-05-07T09:48:04.327464300Z"
}
},
"source": [
"# Двумерный массив\n",
"arr_2d = np.array([[1, 2], [3, 4]])\n",
"print('2D массив:\\n', arr_2d)\n",
"\n",
"# linspace и random\n",
"x = np.linspace(0, 1, 5)\n",
"print('\\nlinspace(0, 1, 5):', x)\n",
"\n",
"rnd = np.random.randn(4)\n",
"print('random.randn(4):', rnd.round(3))\n",
"\n",
"# Скалярное произведение\n",
"a = np.array([1, 2, 3])\n",
"b = np.array([4, 5, 6])\n",
"print('dot([1,2,3],[4,5,6]):', np.dot(a, b))"
],
"id": "numpy_extra",
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2D массив:\n",
" [[1 2]\n",
" [3 4]]\n",
"\n",
"linspace(0, 1, 5): [0. 0.25 0.5 0.75 1. ]\n",
"random.randn(4): [-0.167 1.414 0.544 0.125]\n",
"dot([1,2,3],[4,5,6]): 32\n"
]
}
],
"execution_count": 6
},
{
"cell_type": "markdown",
"metadata": {},
"source": "## 2. Визуализация данных",
"id": "section4"
},
{
"cell_type": "markdown",
"metadata": {},
"source": "### 2.1. matplotlib: базовые графики",
"id": "mpl_title"
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:48:05.151099800Z",
"start_time": "2026-05-07T09:48:04.503011500Z"
}
},
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"x = np.linspace(0, 10, 100)\n",
"\n",
"plt.figure(figsize=(8, 4))\n",
"plt.plot(x, np.sin(x), label='sin(x)', color='steelblue')\n",
"plt.plot(x, np.cos(x), label='cos(x)', color='tomato')\n",
"plt.xlabel('X')\n",
"plt.ylabel('Y')\n",
"plt.title('Графики sin(x) и cos(x)')\n",
"plt.legend()\n",
"plt.grid()\n",
"plt.show()"
],
"id": "mpl_line",
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 800x400 with 1 Axes>"
],
"image/png": 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"
},
"metadata": {},
"output_type": "display_data",
"jetTransient": {
"display_id": null
}
}
],
"execution_count": 7
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:48:06.028204300Z",
"start_time": "2026-05-07T09:48:05.180114500Z"
}
},
"source": [
"fig, axes = plt.subplots(1, 3, figsize=(13, 4))\n",
"\n",
"# Bar chart\n",
"axes[0].bar(df['Имя'], df['Баллы'], color='steelblue', edgecolor='white')\n",
"axes[0].set_title('Баллы студентов (bar)')\n",
"axes[0].set_ylabel('Баллы')\n",
"\n",
"# Scatter\n",
"axes[1].scatter(df['Возраст'], df['Баллы'], color='tomato', s=80)\n",
"for _, row in df.iterrows():\n",
" axes[1].annotate(row['Имя'], (row['Возраст'], row['Баллы']),\n",
" textcoords='offset points', xytext=(5, 5), fontsize=9)\n",
"axes[1].set_title('Возраст vs Баллы (scatter)')\n",
"axes[1].set_xlabel('Возраст')\n",
"axes[1].set_ylabel('Баллы')\n",
"\n",
"# Histogram\n",
"axes[2].hist(np.random.randn(500), bins=20, color='forestgreen', edgecolor='white')\n",
"axes[2].set_title('Случайные данные (hist)')\n",
"axes[2].set_xlabel('Значение')\n",
"\n",
"plt.tight_layout()\n",
"plt.show()"
],
"id": "mpl_multi",
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 1300x400 with 3 Axes>"
],
"image/png": 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},
"metadata": {},
"output_type": "display_data",
"jetTransient": {
"display_id": null
}
}
],
"execution_count": 8
},
{
"cell_type": "markdown",
"metadata": {},
"source": "### 2.2. seaborn: работа с графиками данных",
"id": "sns_title"
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:56:35.903536900Z",
"start_time": "2026-05-07T09:56:35.524474Z"
}
},
"source": [
"import seaborn as sns\n",
"\n",
"fig, axes = plt.subplots(1, 3, figsize=(13, 4))\n",
"\n",
"# Boxplot\n",
"sns.boxplot(x='Категория', y='Баллы', data=df, ax=axes[0])\n",
"axes[0].set_title('Boxplot: Баллы по категориям')\n",
"\n",
"# Histplot\n",
"sns.histplot(df['Баллы'], bins=5, kde=True, ax=axes[1], color='steelblue')\n",
"axes[1].set_title('Histplot: распределение баллов')\n",
"\n",
"# Scatterplot\n",
"sns.scatterplot(x='Возраст', y='Баллы', hue='Категория',\n",
" data=df, ax=axes[2], s=100)\n",
"axes[2].set_title('Scatterplot: возраст vs баллы')\n",
"\n",
"plt.tight_layout()\n",
"plt.show()"
],
"id": "sns_multi",
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 1300x400 with 3 Axes>"
],
"image/png": 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},
"metadata": {},
"output_type": "display_data",
"jetTransient": {
"display_id": null
}
}
],
"execution_count": 17
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:48:07.817143600Z",
"start_time": "2026-05-07T09:48:07.415510300Z"
}
},
"source": [
"# Pairplot и heatmap на числовых столбцах\n",
"df_num = df[['Возраст', 'Баллы', 'Баллы х1.1']]\n",
"\n",
"plt.figure(figsize=(5, 4))\n",
"sns.heatmap(df_num.corr(), annot=True, fmt='.2f', cmap='coolwarm')\n",
"plt.title('Тепловая карта корреляций')\n",
"plt.tight_layout()\n",
"plt.show()"
],
"id": "sns_heatmap",
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 500x400 with 2 Axes>"
],
"image/png": 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"
},
"metadata": {},
"output_type": "display_data",
"jetTransient": {
"display_id": null
}
}
],
"execution_count": 10
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:48:10.010664100Z",
"start_time": "2026-05-07T09:48:07.821688500Z"
}
},
"source": [
"sns.pairplot(df_num)\n",
"plt.suptitle('Pairplot числовых признаков', y=1.02)\n",
"plt.show()"
],
"id": "sns_pairplot",
"outputs": [
{
"data": {
"text/plain": [
"<Figure size 750x750 with 12 Axes>"
],
"image/png": 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"
},
"metadata": {},
"output_type": "display_data",
"jetTransient": {
"display_id": null
}
}
],
"execution_count": 11
},
{
"cell_type": "markdown",
"metadata": {},
"source": "## 3. Прогресс-бар с tqdm",
"id": "section5"
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:52:49.008423300Z",
"start_time": "2026-05-07T09:52:47.890495600Z"
}
},
"source": [
"from tqdm import tqdm\n",
"import time\n",
"\n",
"for i in tqdm(range(100)):\n",
" time.sleep(0.01)"
],
"id": "tqdm_base",
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 100/100 [00:01<00:00, 94.67it/s]\n"
]
}
],
"execution_count": 14
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-07T09:52:52.661150700Z",
"start_time": "2026-05-07T09:52:52.576083Z"
}
},
"source": [
"# tqdm с описанием и обработка строк DataFrame\n",
"results = []\n",
"for idx, row in tqdm(df.iterrows(), total=len(df), desc='Обработка строк'):\n",
" results.append(row['Баллы'] ** 2)\n",
"\n",
"df['Баллы²'] = results\n",
"df"
],
"id": "tqdm_df",
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Обработка строк: 100%|██████████| 4/4 [00:00<00:00, 6283.60it/s]\n"
]
},
{
"data": {
"text/plain": [
" Имя Возраст Баллы Баллы х1.1 Категория Баллы²\n",
"0 Анна 21 89 97.9 A 7921\n",
"1 Борис 22 76 83.6 B 5776\n",
"2 Виктор 23 95 104.5 A 9025\n",
"3 Галина 24 82 90.2 B 6724"
],
"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>Имя</th>\n",
" <th>Возраст</th>\n",
" <th>Баллы</th>\n",
" <th>Баллы х1.1</th>\n",
" <th>Категория</th>\n",
" <th>Баллы²</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Анна</td>\n",
" <td>21</td>\n",
" <td>89</td>\n",
" <td>97.9</td>\n",
" <td>A</td>\n",
" <td>7921</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Борис</td>\n",
" <td>22</td>\n",
" <td>76</td>\n",
" <td>83.6</td>\n",
" <td>B</td>\n",
" <td>5776</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Виктор</td>\n",
" <td>23</td>\n",
" <td>95</td>\n",
" <td>104.5</td>\n",
" <td>A</td>\n",
" <td>9025</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Галина</td>\n",
" <td>24</td>\n",
" <td>82</td>\n",
" <td>90.2</td>\n",
" <td>B</td>\n",
" <td>6724</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 16
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"name": "python",
"version": "3.10.0"
}
},
"nbformat": 4,
"nbformat_minor": 5
}