1346 lines
532 KiB
Plaintext
1346 lines
532 KiB
Plaintext
{
|
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"cells": [
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"id": "17af6bbb-bd17-48d8-9c63-04fb9788c6d6",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
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"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",
|
||
"<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",
|
||
" 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",
|
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"75% 23.250000 90.500000\n",
|
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"max 24.000000 95.000000\n",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
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"dtype: int64\n"
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]
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}
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],
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"source": [
|
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"import pandas as pd\n",
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"\n",
|
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"# Создадим DataFrame\n",
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"data = {\n",
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" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
|
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" \"Возраст\": [21, 22, 23, 24],\n",
|
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" \"Баллы\": [89, 76, 95, 82]\n",
|
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"}\n",
|
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"df = pd.DataFrame(data)\n",
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"\n",
|
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"print(\"Первый взгляд на данные:\")\n",
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"print(df.head())\n",
|
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"print(df.info())\n",
|
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"print(df.describe())\n",
|
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"print(df.isnull().sum())"
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]
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},
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{
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||
"cell_type": "markdown",
|
||
"id": "26aa6af6-3d81-4a14-a95c-184647c89745",
|
||
"metadata": {},
|
||
"source": [
|
||
"Запустил код без изменений\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"id": "16e8e835-cce9-4416-b664-f7c8ab6168d0",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первый взгляд на данные:\n",
|
||
" Имя Возраст Баллы\n",
|
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"0 Анна 21 89\n",
|
||
"1 Борис 22 76\n",
|
||
"2 Виктор 23 95\n",
|
||
"3 Галина 24 82\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",
|
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" 2 Баллы 4 non-null int64 \n",
|
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"dtypes: int64(2), object(1)\n",
|
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"memory usage: 228.0+ bytes\n",
|
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"None\n",
|
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" Возраст Баллы\n",
|
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"count 4.000000 4.000000\n",
|
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"mean 22.500000 85.500000\n",
|
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"std 1.290994 8.266398\n",
|
||
"min 21.000000 76.000000\n",
|
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"25% 21.750000 80.500000\n",
|
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"50% 22.500000 85.500000\n",
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"75% 23.250000 90.500000\n",
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"max 24.000000 95.000000\n",
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"Имя 0\n",
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"Возраст 0\n",
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"Баллы 0\n",
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"dtype: int64\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
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||
"\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",
|
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" <th></th>\n",
|
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" <th>Имя</th>\n",
|
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" <th>Возраст</th>\n",
|
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" <th>Баллы</th>\n",
|
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" </tr>\n",
|
||
" </thead>\n",
|
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>Анна</td>\n",
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" <td>21</td>\n",
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" <td>89</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>Борис</td>\n",
|
||
" <td>22</td>\n",
|
||
" <td>76</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
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" <td>Виктор</td>\n",
|
||
" <td>23</td>\n",
|
||
" <td>95</td>\n",
|
||
" </tr>\n",
|
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" <tr>\n",
|
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" <th>3</th>\n",
|
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" <td>Галина</td>\n",
|
||
" <td>24</td>\n",
|
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" <td>82</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" Имя Возраст Баллы\n",
|
||
"0 Анна 21 89\n",
|
||
"1 Борис 22 76\n",
|
||
"2 Виктор 23 95\n",
|
||
"3 Галина 24 82"
|
||
]
|
||
},
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"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(df.info())\n",
|
||
"print(df.describe())\n",
|
||
"print(df.isnull().sum())\n",
|
||
"df"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "2d87d2ba-845a-487c-bdca-a3097a4855fc",
|
||
"metadata": {},
|
||
"source": [
|
||
"Написали df в конец"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"id": "6fe12ad9-a554-47f1-89c1-68f44809ae67",
|
||
"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",
|
||
"<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",
|
||
" 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",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"dtype: int64\n",
|
||
"\n",
|
||
"DataFrame с новым столбцом:\n",
|
||
" Имя Возраст Баллы Новый столбец\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"
|
||
]
|
||
}
|
||
],
|
||
"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(df.info())\n",
|
||
"print(df.describe())\n",
|
||
"print(df.isnull().sum())\n",
|
||
"\n",
|
||
"# Добавляем новый столбец с вычисляемыми значениями\n",
|
||
"df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
|
||
"\n",
|
||
"print(\"\\nDataFrame с новым столбцом:\")\n",
|
||
"print(df)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "e8b219e2-c663-4fdc-bfd8-0a9fb95f4c60",
|
||
"metadata": {},
|
||
"source": [
|
||
"Добавиили новый столбец\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"id": "c1146a91-a26b-4a8e-a471-3e67b98b5f59",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Исходные данные:\n",
|
||
" Имя Возраст Баллы Баллы с надбавкой\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",
|
||
"Информация о данных:\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 с надбавкой 4 non-null float64\n",
|
||
"dtypes: float64(1), int64(2), object(1)\n",
|
||
"memory usage: 260.0+ bytes\n",
|
||
"None\n",
|
||
"\n",
|
||
"Описательная статистика:\n",
|
||
" Возраст Баллы Баллы с надбавкой\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",
|
||
"Проверка пропущенных значений:\n",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"Баллы с надбавкой 0\n",
|
||
"dtype: int64\n",
|
||
"\n",
|
||
"Средний балл по возрасту:\n",
|
||
" Баллы\n",
|
||
"Возраст \n",
|
||
"21 89.0\n",
|
||
"22 76.0\n",
|
||
"23 95.0\n",
|
||
"24 82.0\n",
|
||
"\n",
|
||
"Расширенная статистика по возрасту:\n",
|
||
" Баллы Баллы с надбавкой\n",
|
||
" mean max min count sum\n",
|
||
"Возраст \n",
|
||
"21 89.0 89 89 1 97.9\n",
|
||
"22 76.0 76 76 1 83.6\n",
|
||
"23 95.0 95 95 1 104.5\n",
|
||
"24 82.0 82 82 1 90.2\n",
|
||
"\n",
|
||
"Максимальный балл по имени:\n",
|
||
" Баллы\n",
|
||
"Имя \n",
|
||
"Анна 89\n",
|
||
"Борис 76\n",
|
||
"Виктор 95\n",
|
||
"Галина 82\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"# Создаем 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",
|
||
"# Добавляем новый столбец (баллы с 10% надбавкой)\n",
|
||
"df[\"Баллы с надбавкой\"] = df[\"Баллы\"] * 1.1\n",
|
||
"\n",
|
||
"print(\"Исходные данные:\")\n",
|
||
"print(df)\n",
|
||
"print(\"\\nИнформация о данных:\")\n",
|
||
"print(df.info())\n",
|
||
"print(\"\\nОписательная статистика:\")\n",
|
||
"print(df.describe())\n",
|
||
"print(\"\\nПроверка пропущенных значений:\")\n",
|
||
"print(df.isnull().sum())\n",
|
||
"\n",
|
||
"# Группировка по возрасту и расчет среднего балла\n",
|
||
"grouped_mean = df.groupby('Возраст').agg({'Баллы': 'mean'})\n",
|
||
"print(\"\\nСредний балл по возрасту:\")\n",
|
||
"print(grouped_mean)\n",
|
||
"\n",
|
||
"# Группировка с несколькими агрегациями\n",
|
||
"grouped_multiple = df.groupby('Возраст').agg({\n",
|
||
" 'Баллы': ['mean', 'max', 'min', 'count'],\n",
|
||
" 'Баллы с надбавкой': 'sum'\n",
|
||
"})\n",
|
||
"print(\"\\nРасширенная статистика по возрасту:\")\n",
|
||
"print(grouped_multiple)\n",
|
||
"\n",
|
||
"# Группировка по имени и поиск максимального балла\n",
|
||
"grouped_name_max = df.groupby('Имя').agg({'Баллы': 'max'})\n",
|
||
"print(\"\\nМаксимальный балл по имени:\")\n",
|
||
"print(grouped_name_max)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "eee05cb0-9db7-4ed3-a51a-9ea72072cdcb",
|
||
"metadata": {},
|
||
"source": [
|
||
"Применили .groupby() и .agg(), чтобы сгруппировать данные."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"id": "95c6cdd0-4f62-4533-a392-9d270b0124e0",
|
||
"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",
|
||
"Информация о DataFrame:\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",
|
||
"Описательная статистика:\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",
|
||
"Проверка на пропущенные значения:\n",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"dtype: int64\n",
|
||
"\n",
|
||
"Студенты старше 21 года:\n",
|
||
" Имя Возраст Баллы\n",
|
||
"1 Борис 22 76\n",
|
||
"2 Виктор 23 95\n",
|
||
"3 Галина 24 82\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"# Создаем 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",
|
||
"# Первоначальный анализ данных\n",
|
||
"print(\"Первый взгляд на данные:\")\n",
|
||
"print(df.head())\n",
|
||
"print(\"\\nИнформация о DataFrame:\")\n",
|
||
"print(df.info())\n",
|
||
"print(\"\\nОписательная статистика:\")\n",
|
||
"print(df.describe())\n",
|
||
"print(\"\\nПроверка на пропущенные значения:\")\n",
|
||
"print(df.isnull().sum())\n",
|
||
"\n",
|
||
"# Фильтрация записей по условию (возраст > 21)\n",
|
||
"print(\"\\nСтуденты старше 21 года:\")\n",
|
||
"filtered_df = df[df[\"Возраст\"] > 21]\n",
|
||
"print(filtered_df)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "6b33c335-549f-43de-ac3e-987b882bf8a6",
|
||
"metadata": {},
|
||
"source": [
|
||
"Отфильтровали по возрасту "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"id": "683fb8f3-a232-4d84-b747-d9f2e493137c",
|
||
"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": "markdown",
|
||
"id": "b7d56771-2c24-4c1d-84db-bdc1570ee89e",
|
||
"metadata": {},
|
||
"source": [
|
||
"Стандартный код\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"id": "26c54461-c049-4c29-bb26-d8011fec90bc",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Одномерный массив: [1 2 3 4 5]\n",
|
||
"Сумма элементов массива: 15\n",
|
||
"Среднее значение: 3.0\n",
|
||
"Медиана: 3.0\n",
|
||
"Стандартное отклонение: 1.4142135623730951\n",
|
||
"\n",
|
||
"Двумерный массив:\n",
|
||
"[[1 2]\n",
|
||
" [3 4]]\n",
|
||
"Сумма элементов по столбцам: [4 6]\n",
|
||
"Сумма элементов по строкам: [3 7]\n",
|
||
"Общая сумма всех элементов: 10\n",
|
||
"Среднее значение всех элементов: 2.5\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"\n",
|
||
"# Работа с одномерным массивом\n",
|
||
"arr = np.array([1, 2, 3, 4, 5])\n",
|
||
"print(\"Одномерный массив:\", arr)\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",
|
||
"\n",
|
||
"# Создание и работа с двумерным массивом\n",
|
||
"arr_2d = np.array([[1, 2], [3, 4]])\n",
|
||
"print(\"\\nДвумерный массив:\")\n",
|
||
"print(arr_2d)\n",
|
||
"print(\"Сумма элементов по столбцам:\", np.sum(arr_2d, axis=0))\n",
|
||
"print(\"Сумма элементов по строкам:\", np.sum(arr_2d, axis=1))\n",
|
||
"print(\"Общая сумма всех элементов:\", np.sum(arr_2d))\n",
|
||
"print(\"Среднее значение всех элементов:\", np.mean(arr_2d))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "a11fc0e0-6dd3-4125-a913-888795e7c81d",
|
||
"metadata": {},
|
||
"source": [
|
||
"Создали двумерный массив\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"id": "ef35550c-44bf-450b-bcd2-867dbdac4d57",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Исходный массив: [1 2 3 4 5]\n",
|
||
"Сумма элементов массива: 15\n",
|
||
"Среднее значение: 3.0\n",
|
||
"Медиана: 3.0\n",
|
||
"Стандартное отклонение: 1.4142135623730951\n",
|
||
"\n",
|
||
"np.linspace(0, 10, 5): [ 0. 2.5 5. 7.5 10. ]\n",
|
||
"\n",
|
||
"Случайные числа (np.random.randn(3)): [-1.86503145 -0.5268375 -0.03655265]\n",
|
||
"\n",
|
||
"Скалярное произведение векторов [1,2,3] и [4,5,6]: 32\n",
|
||
"\n",
|
||
"Умножение матриц:\n",
|
||
"Матрица 1:\n",
|
||
" [[1 2]\n",
|
||
" [3 4]]\n",
|
||
"Матрица 2:\n",
|
||
" [[5 6]\n",
|
||
" [7 8]]\n",
|
||
"Результат умножения:\n",
|
||
" [[19 22]\n",
|
||
" [43 50]]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"\n",
|
||
"# Работа с исходным массивом\n",
|
||
"arr = np.array([1, 2, 3, 4, 5])\n",
|
||
"print(\"Исходный массив:\", arr)\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",
|
||
"\n",
|
||
"# Использование np.linspace()\n",
|
||
"print(\"\\nnp.linspace(0, 10, 5):\", np.linspace(0, 10, 5)) # 5 чисел от 0 до 10 с равным шагом\n",
|
||
"\n",
|
||
"# Использование np.random.randn()\n",
|
||
"random_arr = np.random.randn(3) # 3 случайных числа из стандартного нормального распределения\n",
|
||
"print(\"\\nСлучайные числа (np.random.randn(3)):\", random_arr)\n",
|
||
"\n",
|
||
"# Использование np.dot() для скалярного произведения\n",
|
||
"a = np.array([1, 2, 3])\n",
|
||
"b = np.array([4, 5, 6])\n",
|
||
"dot_product = np.dot(a, b)\n",
|
||
"print(\"\\nСкалярное произведение векторов [1,2,3] и [4,5,6]:\", dot_product)\n",
|
||
"\n",
|
||
"# Демонстрация np.dot() с матрицами\n",
|
||
"matrix1 = np.array([[1, 2], [3, 4]])\n",
|
||
"matrix2 = np.array([[5, 6], [7, 8]])\n",
|
||
"matrix_product = np.dot(matrix1, matrix2)\n",
|
||
"print(\"\\nУмножение матриц:\")\n",
|
||
"print(\"Матрица 1:\\n\", matrix1)\n",
|
||
"print(\"Матрица 2:\\n\", matrix2)\n",
|
||
"print(\"Результат умножения:\\n\", matrix_product)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "f5847c7d-ebf2-4cff-9391-ca72f5ba7b14",
|
||
"metadata": {},
|
||
"source": [
|
||
"Попробовали новые функции\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"id": "f9280d31-f2d9-4500-9192-80f69af7978a",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Matplotlib is building the font cache; this may take a moment.\n"
|
||
]
|
||
},
|
||
{
|
||
"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)')\n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"График синуса\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "8ec915a2-027d-4133-9368-f7abc9d7dfad",
|
||
"metadata": {},
|
||
"source": [
|
||
"Код без изменений\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"id": "bb2ca47d-bc06-42e6-b16c-c09b5bccd855",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"x = np.linspace(0, 10, 100)\n",
|
||
"y = np.sin(x)\n",
|
||
"\n",
|
||
"plt.plot(x, y, color='red')\n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"График синуса\")\n",
|
||
"plt.legend(['sin(x)'])\n",
|
||
"plt.grid()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "8e046d2b-a17c-41b3-9273-5f6b3fdf06de",
|
||
"metadata": {},
|
||
"source": [
|
||
"Красный цвет"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"id": "7a9d6dcb-7a2d-456b-87ee-b29e276b4a14",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"x = np.linspace(0, 10, 100)\n",
|
||
"y_sin = np.sin(x)\n",
|
||
"y_cos = np.cos(x)\n",
|
||
"\n",
|
||
"plt.plot(x, y_sin, label='sin(x)', color='blue')\n",
|
||
"plt.plot(x, y_cos, label='cos(x)', color='red')\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()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "1f52f3fa-11be-419a-b597-500c0b331edb",
|
||
"metadata": {},
|
||
"source": [
|
||
"Добавили несколько графиков\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"id": "95029266-c561-472b-8c0e-c1e7d53ccaec",
|
||
"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"
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"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)')\n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"График синуса\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"plt.bar(np.arange(5), np.random.rand(5))\n",
|
||
"plt.title(\"Столбчатая диаграмма\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"plt.scatter(np.random.rand(50)*10, np.random.rand(50)*2-1)\n",
|
||
"plt.title(\"Точечная диаграмма\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "0ba7e9a2-c467-4d49-8cea-9c14d56bc7cf",
|
||
"metadata": {},
|
||
"source": [
|
||
"Использовать bar, scatter, hist.\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"id": "954cb391-4990-497b-aed0-9ca531fbdfe1",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 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()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "7a74f376-1ed1-4699-9e1b-fd7b0b92dc9b",
|
||
"metadata": {},
|
||
"source": [
|
||
"Код без изменений\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"id": "4a5042c5-0e89-428e-b162-7b599ed54c2d",
|
||
"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"
|
||
}
|
||
],
|
||
"source": [
|
||
"import seaborn as sns\n",
|
||
"import matplotlib.pyplot as plt\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",
|
||
"df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\"]\n",
|
||
"\n",
|
||
"sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"sns.histplot(data=df, x=\"Баллы\", hue=\"Категория\", kde=True)\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"sns.scatterplot(data=df, x=\"Возраст\", y=\"Баллы\", hue=\"Категория\", size=\"Баллы\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "8d3188f6-01e7-49ca-bf26-b6978c48458f",
|
||
"metadata": {},
|
||
"source": [
|
||
"Построить histplot, scatterplot."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"id": "70326b9f-f2a7-4663-a34b-a9b968dc8212",
|
||
"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 588.236x500 with 6 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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nWwoAwNViIzNQqKzAvHnz5JtvvtE3LZo2bZosWrRI3n77bZk9e7bnWwkAwNWegdDuoaW0ZgaOHj2q5xioUaOGhISESGzs+dkDb731Vjlw4PydvAAAQCnODERGRsqxY+cn6lC3LK5SpYp+nJGRIRUrVvRsCwEA8MKNimweWkptZqBnz56SlpbmvM9ALlVIWJjpiAEA8Gl2/0jve30GwvwMGjRILwAAoJQHAxfXDiQlJenH6lbG6hbGAAD4PZt/pPc9pVjvVtUGPPHEE1K9enW57bbb9KIe9+3bV86cOeP5VgIAcLVnILR5aCmtwcCwYcN0fcDSpUt17YBa/vWvf+ltw4cP93wrAQC4mux2zy2ltZvg888/l4ULF8pf/vIX57aOHTtK2bJl5ZFHHtHzDQAAACm9wYDqCqhatWqe7WqIId0EAAC/Z/OPX/SeUqx3GxcXJ/Hx8XL27FnntszMTBk/frx+DgAAv2ZnBsLLmj59unTo0EHPQBgTE6O3ff/99xIcHCxffPGFp9sIAAB8LRho0qSJ/PLLL/Lxxx/Lzz//rLd1795devTooesGAADwaza6CS7r+PHj+o6F/fv3lyFDhkj58uX1fANbtmzxfAsBALjabAwtLNCOHTukTp06ulCwUaNGsn37drn55ptl6tSp+pbG7dq1kyVLlpRcawEAgHeDgZEjR0rTpk1l3bp1eljhvffeK506dZKTJ09KamqqPPnkk/Lqq696vpUAAFxNduYZKNDmzZtlzZo10qxZM104qLIBTz31lNj/+2YHDx4srVu3Lqm2AgBwddj8I73vKUUKWU6cOCFRUVH6cYUKFXStQHh4uPN59fjUqVOebyUAAPCd0QQ2t2jJfR0AAL9n84/0vteCgd69e+v5BBQ16dDAgQN1hkDJysryfAsBALja7AQDBerVq5fL+mOPPZZnn549e155qwAA8CabWVnvIgUDc+bMKbmWAAAA/5mBEACAUs1GNwEAAGazmdVNYFboAwAA8iAzAACAO0YTAABgNotuAgAAYBIyAwAAuGM0AQAAhrOZFQyY9W4BAEAeZAYAADC8gJBgAAAAw7sJCAYAAHBnWGbArNAHAADkQWYAAAB3zEAIAIDZLLoJAACAt8yYMUPq1KkjISEh0qpVK9m0adMl909LS5Onn35aqlWrJsHBwdKgQQNZvnx5kV6TzAAAAD4ymmDBggUybNgweeedd3QgMG3aNOnQoYMkJSVJlSpV8uyfnZ0td911l35u4cKFEh0dLb///rtUqlSpSK9LMAAAgBvLS8HAlClTpH///tKnTx+9roKChIQEmT17towePTrP/mr7iRMnZP369RIYGKi3qaxCUdFNAABACcrKypL09HSXRW3L71d+YmKitG/f3rnNbrfr9Q0bNuR77qVLl0pcXJzuJqhatao0adJEJk6cKDk5OUVqI8EAAADuVAGhh5ZJkyZJWFiYy6K2uTt27Ji+iKuL+sXUenJycr7N/PXXX3X3gDpO1QmMHTtW3njjDXn55ZeL9HbpJgAAoAS7CcaMGaPrAC6mCv08weFw6HqBmTNnSkBAgMTGxsrBgwdl8uTJEh8fX+jzEAwAAODOg0ML1YW/MBf/yMhIfUFPSUlx2a7Wo6Ki8j1GjSBQtQLquFzXX3+9ziSoboegoKBCtZFuAgAAfIC6cKtf9qtXr3b55a/WVV1Aftq0aSN79uzR++XavXu3DhIKGwgoBAMAALhT3QSeWopAdSfMmjVL5s6dK7t27ZJBgwZJRkaGc3RBz549dbdDLvW8Gk0wZMgQHQSokQeqgFAVFBYF3QQAAPjIDITdunWTo0ePyrhx43Sqv3nz5rJixQpnUeH+/fv1CINcNWvWlJUrV8rQoUOlWbNmep4BFRiMGjWqSK9rsyzLEh+QENjQ200AfM6ke2Z6uwmAT/p22e0lev70xJUeO1dobAfxdWQGAABw56VJh7yFYAAAADeWcKMiAABgEDIDAAD4yL0JvIVgAAAAd4YFA2a9WwAAkAeZAQAAfGSeAW8hGAAAwA01AwAAmM5mVmbArNAHAADkQWYAAAA3dBMAAGA4ixkIAQCAScgMAADghm4CAABMZ6ObAAAAGITMAAAAbizDfisTDAAAYPh0xGaFPgAAIA8yAwAAuGE0AQAAhrMMm3SIYAAAAMMzA2a9WwAAkAeZAQAADB9NQDAAAIDhNQN0EwAAYDgyAwAAGF5ASDAAAIAbugkAAIBRyAwAAOCGbgIAAAxn0U0AAABMQmYAAAA3dBMAAGA4y7BuAp8JBibdM9PbTQB8zpgVA7zdBMBHJZXo2S3DpiM2Kw8CAAB8NzMAAICvsCyzMgMEAwAAuLEMS5yb9W4BAEAeZAYAAHDDaAIAAAxnGRYM0E0AAIDhyAwAAGB4ZoBgAAAAw4MBugkAADAcmQEAANww6RAAAIazDOsmIBgAAMDwYICaAQAADEdmAAAAwzMDBAMAABheQEg3AQAAhiMzAACAGwfdBAAAmM0yLBigmwAAAMORGQAAwPACQoIBAADc0E0AAACMQmYAAAA3dBMAAGA4y7BuAoIBAAAMzwxQMwAAgA+ZMWOG1KlTR0JCQqRVq1ayadOmQh03f/58sdls0rVr1yK/JsEAAABuHB5cimLBggUybNgwiY+Pl61bt0pMTIx06NBBjhw5csnjfvvtN/nb3/4mt956qxQHwQAAAPl0E3hqKYopU6ZI//79pU+fPnLDDTfIO++8I+XKlZPZs2cXeExOTo706NFDxo8fL9dee60UB8EAAAAlKCsrS9LT010Wtc1ddna2JCYmSvv27Z3b7Ha7Xt+wYUOB558wYYJUqVJF+vbtW+w2EgwAAJDPaAJPLZMmTZKwsDCXRW1zd+zYMf0rv2rVqi7b1XpycrLk59tvv5X33ntPZs2aJVeC0QQAAJTgaIIxY8boOoCLBQcHX/F5T506JY8//rgOBCIjI6/oXAQDAACUIHXhL8zFX13QAwICJCUlxWW7Wo+Kisqz/969e3XhYOfOnZ3bHI7zJYtlypSRpKQkue666wrVRroJAAAowW6CwgoKCpLY2FhZvXq1y8VdrcfFxeXZv1GjRrJjxw7Zvn27c7nvvvukXbt2+nHNmjUL/dpkBgAAcOOwxCtUd0KvXr2kRYsWcvPNN8u0adMkIyNDjy5QevbsKdHR0brmQM1D0KRJE5fjK1WqpP913345BAMAAPiIbt26ydGjR2XcuHG6aLB58+ayYsUKZ1Hh/v379QgDT7NZluWl+MdV285fe7sJgM8Zs2KAt5sA+KRO55JK9Pxf/3jGY+e6vXE58XVkBgAAMPzeBAQDAAC48Y2c+dXDaAIAAAxHZgAAADeOIgwJLA0IBgAAMLxmgG4CAAAMR2YAAADDCwgJBgAAcFOUaYRLA7oJAAAwHJkBAAB85N4E3kIwAACAG0YTAAAAo5AZAADADaMJAAAwnMOw0QQEAwAAGJ4ZoGYAAADDkRkAAMDw0QQEAwAAGD7PAN0EAAAYjswAAACGFxASDAAA4IYbFQEAAKOQGQAAwPACQoIBAAAMrxmgmwAAAMORGQAAwPDMAMEAAABuHMxACACA2SzDMgPUDAAAYDgyAwAAGJ4ZIBgAAMDweQboJgAAwHBkBgAAcGMxmgAAALNZdBMAAACTkBkAAMDwAsJiBQN2u11stoL7U3Jycq6kTQAAeJVFMHB5ixcv9nxLAACA/wQDXbp0cVlftGiRbN++XZo0aSKPPPKIp9oGAIBXWIZlBq64gPC1116T7t27y4oVK6Rv374yfvx4z7QMAAAv1gw4PLQYEQzMnTtX3n33Xdm0aZP861//kjlz5nimZQAAeDEzYHloMSIYOHTokLRu3Vo/Vv8ePHjQE+0CAAD+MrRQjRwoU+b8aQICAsThcHiiXQAAeI3DsEtZsYKBG2+80Tm0MDMzUzp37ixBQUFi+Us+BACAS7AMu5wVKxjo2rVrgSMLLn4OAACU0mAgPj7e8y0BAMBHWGQGLi89Pf2Sz4eGhha3PQAAeJ2DYODyKlWqlO90xKpmQG1nOmIAAAwYTbBw4UKJiIjwbGsAAPABlkf7CQq+l4/fBwNt2rSRKlWqeLY1AAD4AItugsL56aef5Pjx41K+fHmJiorSQwvhG/r2qCOd746SiuXLyI5d6fL6W7/IH4czL3nMAx2rS/cHakpEeJDs3Xdapv5zj+z65ZTz+RFP15cWMeESGREkZ87myM5d6fL23F9l/x8XzjtkwHXS7PowqVu7vPx+4Iz0GZJYou8TKGkRbVvItcP7SthNTSSkehXZ8uBTkrJ0tbebBfjODIR33nmnNG7cWOrWrasDgqZNm8rUqVM92zoUWY8Ha8pD90brAGDA37ZJ5tkcmTKhqQQFFpymuqPtNfJMv+tkzrzfpO+zibJn32l9TKWwQOc+SXtOy8TpSdLjqc0yPH6HqJKRqROaid3tE5SwKlnWfHOkJN8icNUElC8n6T8kyc6/cs8VEycdcnhoKbWZgX379un+lHPnzumRBWpKYnVvgrFjx8qff/4pI0aM8HxLUSgP3xctH3z6u3z73XG9/vLUn2Xph7fIra0jZfU3R/M95tGuNWTZysOyfHWKXp/81i8S17Ky3HtXlHy08IDetnTlYef+yUeyZNZHv8nc/2shUVVC5FDyWb19+sy9+t9KYbXlujoVSvy9AiXt6Mp1eoF5LLoJLq927dou67GxsXoWwgYNGsiECRMIBryketUQiYwIls3bU53bMs7kyE+706VJo9B8g4EyZWzSoF5F+XDhfpcvwZbtqdK4Yf5DREOC7dKxfZQcSs6UI8eySujdAID3OAgGiu/RRx/VXQeXk5WVpZeLOXKyxR5A3cGVUP39SmraOZftqWnZzufchYUGSpkAm5xIdT3mRNo5qV2jnMu2+ztWl0G9r5VyZQPk9z/OyLNjf5A//zTsGwMApVCxagZU10B+i7pPQb169S57/KRJkyQsLMxl+WPPx8VpitHuur2KfPFpW+eifuWXpC/WpsgTQxLl6dHb5cDBM/LSqBsuWYsAAP7KMuwWxl6ZdGjMmDEybNgwl233PPpdcZpitG83HZefdm9xrgcFno/twisFyvHUbOf28EpBsufX0/me42T6Ofkzx5KI8AvFgkqE2zlyuxwyzmTqkQk/JqXL/5vXRm6Li5Qv1+VfiwAA/sryaD+B7/9o8sqkQ8HBwXq5GF0ERZeZmSMHM10Dr2MnsvQQwD37MvS6Sunf0CBUliw/lO85VJp/955TEtssXL7ZeL7oUMV5sTHhsijh4CU/2mq/wP8GIAAA/8WkQ6XMZ0sPSq9uteTAoUw5nHJW+j1WR46fyJJvNh5z7jPt5WaybsMxWZRwPkCYv+QPeX5oI/l5zynZtfuUPNIlWsqG2CXhy2RnYeIdt14jm7elSlr6ObmmcrA89lBNycpyyIYtJ5znja4WImVDAnR9QnCQXerVLa+3/3bgDLUF8NuhheXr1XKul6tbQ0JjGkn2iZNy9sCFETYofRyG/cli0qFS5uPPD0hISICMfKaBVFCTDv10Us8LkH3uwic7OqqsVAq90C2w5tujek6Bfj3q6Au56lJQx+QWImadc0hM4zB55L4aUrFCGTmRli3f/3hSBo7cJmknLxQejh7cUG5sWsm5/v4/Wuh/H+q7UQ9HBPxNWGwTiVv9oXP9htef0/8e+GCR/NB3jBdbhpJmGRYM2KxiTMBst9t1bUBujYBab9SokTzxxBMydOjQYjWkbeevi3UcUJqNWTHA200AfFKnc0klev7XFnputqBRD/l+d6q9uJMO7d27V5KSkvRkQ4sWLZKuXbvqSYcmT57s+VYCAHAVORyWx5aimjFjhtSpU0dCQkKkVatW+jpbkFmzZsmtt94q4eHhemnfvv0l9/doMKAmHVINrV+/vnPCoZdeeknefvttmTlzZnFOCQCAmD60cMGCBXq0XXx8vGzdulViYmKkQ4cOcuRI/tO8r127Vrp37y5fffWVbNiwQWrWrCl33323HDxYcAG4x7oJCqKmJ96xY4fcdNNNRT6WbgIgL7oJAO90E0xccOkh8kUxvOufeSbay29UnaIyAS1btpQ333xTrzscDn2BHzx4sIwePfqyr6WG9qsMgTq+Z8+ehW6jRzsyAgMDixUIAABQWjMDk/KZaE9tc5ednS2JiYk61Z9L1eSpdfWrvzDOnDmjf5gXdeh/sUYTqMhD3aHw008/lf379+s3cLETJy4MNwMAwN84PDicIL+J9vLLChw7dkxfX6tWreqyXa3//PPPhXqtUaNGSfXq1V0CihLLDIwfP16mTJki3bp1k5MnT+o3+cADD+gI5sUXXyzOKQEA8BmWw3OLuvCHhoa6LPkFA1fq1Vdflfnz58vixYt18WGJBwMff/yxrmAcPny4lClTRhcvvPvuuzJu3DjZuHFjcU4JAIDRIiMjJSAgQFJSzt9OPpdaV/P5XMrrr7+ug4EvvvhCmjVrVuTXLlYwkJycLE2bNtWPK1SooLMDyr333isJCQnFOSUAAD7DsiyPLYWlJu9TI/RWr17t3KYKCNV6XFxcgcf9/e9/1yP6VqxYIS1anJ/s7aoEAzVq1JDDh89PxXndddfpSETZvHlziaQ+AAC4mhwOzy1FobrdVeZ97ty5smvXLhk0aJBkZGRInz599PNqhICqQcj12muv6Tl+Zs+erYf8qx/rajl9Ov+b03m0gPD+++/XkYoaAqGGOzz22GPy3nvv6WLC4s5ACACA6bp16yZHjx7V3e7qot68eXP9iz+3qFBdZ1V9Xi41v48q4n/ooYdczqPmKShKDZ9H5hlQdQLr16/XkxCpCYiKg3kGgLyYZwDwzjwD4+a6jpK7EhN6+f69e654ngHVNbBs2TI9O5IaOwkAgL9zWJ5b/EGRuglq1aol27Ztk8qVK+v1VatWSadOnXSdgEpbqGrGefPmycMPP1xS7QUAAN7MDPzxxx96QoRc6qZEalhhWlqapKamypNPPqmrGgEA8GeWw/LY4g+uqJtAVTqqAkI1LlJlBtTjX375xXOtAwDAoBsV+WUwoDICF89/rG6OcOrUKU+0CwAA+GLNgM1m04v7NgAAShOHn6T3vRIMqFGIvXv3dk4sdPbsWRk4cKCUL19er7vfohEAAH9k+Ut+3xvBQK9evVzW1WRD7opy/2QAAHyRVcSZA40KBubMmVNyLQEAAF5RrOmIAQAozRx0EwAAYDbLsGDgiqcjBgAA/o3MAAAAbhhaCACA4SyzYgG6CQAAMB2ZAQAA3PjLDYY8hWAAAADDhxbSTQAAgOHIDAAA4IZuAgAADGcRDAAAYDaHWbEANQMAAJiOzAAAAG7oJgAAwHAWQwsBAIBJyAwAAOCGGxUBAGA4i24CAABgEjIDAAC4YTQBAACGswwLBugmAADAcGQGAAAw/BbGBAMAABjeTUAwAACAG4YWAgAAo5AZAADADTMQAgBgOMuwYIBuAgAADEdmAAAAwwsICQYAAHBjORxiEroJAAAwHJkBAADcMJoAAADDWYbVDNBNAACA4cgMAABg+DwDBAMAALghGAAAwHAOi6GFAADAIGQGAABwQzcBAACGswwLBugmAADAcGQGAAAwfNIhggEAANw4uFERAAAwCZkBAAAMLyAkGAAAwI3FpEMAAMAkZAYAAHBDNwEAAIazCAYAADCbg5oBAADgLTNmzJA6depISEiItGrVSjZt2nTJ/T/77DNp1KiR3r9p06ayfPnyIr8mwQAAAPl0E3hqKYoFCxbIsGHDJD4+XrZu3SoxMTHSoUMHOXLkSL77r1+/Xrp37y59+/aVbdu2SdeuXfWyc+fOIr2uzfKRORfbdv7a200AfM6YFQO83QTAJ3U6l1Si57+rR6LHzrXq49hC76syAS1btpQ333zTORNizZo1ZfDgwTJ69Og8+3fr1k0yMjLk3//+t3Nb69atpXnz5vLOO+8U+nXJDAAAUIKysrIkPT3dZVHb3GVnZ0tiYqK0b9/euc1ut+v1DRs25Htutf3i/RWVSSho/4IQDAAAUILdBJMmTZKwsDCXRW1zd+zYMcnJyZGqVau6bFfrycnJkh+1vSj7F4TRBAAAlOAMhGPGjNF1ABcLDg4WX0IwAABACVIX/sJc/CMjIyUgIEBSUlJctqv1qKiofI9R24uyf0HoJgAAwI3DYXlsKaygoCCJjY2V1atXX9QOh16Pi4vL9xi1/eL9lVWrVhW4f0HIDAAA4MZyeGfSIdWd0KtXL2nRooXcfPPNMm3aND1aoE+fPvr5nj17SnR0tLPmYMiQIXL77bfLG2+8IZ06dZL58+fLli1bZObMmUV6XYIBAAB8hBoqePToURk3bpwuAlRDBFesWOEsEty/f78eYZDrlltukU8++UReeOEFee6556R+/fqyZMkSadKkSZFel3kGAB/GPAOAd+YZuP2B9R4719eLbhFfR2YAAIASHE3gDwgGAAAw/K6FjCYAAMBwZAYAAPCR0QTe4jMFhPANar5sNWRFzZjlazNkAd7C9wKlHcEAXKgbaKh5s0+ePCmhoaHebg7gE/heoLSjZgAAAMMRDAAAYDiCAQAADEcwABeqOCo+Pp4iKeAifC9Q2lFACACA4cgMAABgOIIBAAAMRzAAAIDhCAYAADAcwQAAAIYjGPADvXv3FpvN5lwqV64s99xzj/zwww/ebhrg89+X3KVGjRrebhrgswgG/IS6+B8+fFgvq1evljJlysi9997r7WYBPv99yV22bdvm7WYBPotgwE+oyU6ioqL00rx5cxk9erQcOHBAjh49qp/fsWOH3HHHHVK2bFmdORgwYICcPn3aebzav3r16hIUFCTR0dEyatQocfz3Fp1r167Vv5wSEhKkWbNmEhISIq1bt5adO3c6jz9+/Lh0795dH1uuXDlp2rSpzJs3z6WN6nx///vfpV69erq9tWrVkldeeUU/l98vtdxFvT5QUt+X3OWaa65xPq8+/w0aNNCf5WuvvVbGjh0r586dcznHb7/9lu/nNS0trdD7vPjii/r7mp8lS5bofQFfQDDgh9RF/qOPPtIXXXXhz8jIkA4dOkh4eLhs3rxZPvvsM/nyyy/lmWeecR5z9913y7///W/Zs2ePvPvuuzJz5kx9jouNGDFC3njjDX0O9Yezc+fOzj+QZ8+eldjYWB0wqCBBBRuPP/64bNq0yXm8ur3rq6++qv+w/vTTT/LJJ59I1apV9XMX/0JTPv/8c+f6LbfccpX+ywHnVaxYUd5//339OZ0+fbrMmjVLpk6d6rJP7nxs6rukPqfqM+uuMPsAfkHNQAjf1qtXLysgIMAqX768XtT/bdWqVbMSExP18zNnzrTCw8Ot06dPO49JSEiw7Ha7lZycnOd8v/76qz5+9uzZev2rr77S55w/f75zn+PHj1tly5a1FixYUGC7OnXqZA0fPlw/Tk9Pt4KDg61Zs2Zd9v2o11KvCVyN70t0dLTVvn17a+XKlQUeM3nyZCs2NtZlW1JSkv6s7ty50+V7kpqaWuh94uPjrZiYmHxfc/HixXpfwBeQGfAT7dq1k+3bt+tF/RpXmYD/+Z//kd9//1127dolMTExUr58eef+bdq00Wn7pKQk57aJEyc606IPPvig9OzZ0+U14uLinI8jIiKkYcOG+txKTk6OvPTSS7p7QD1XoUIFWblypezfv18/r/bLysqSO++88yr81wAK/31ZtGiRVKtWTTp16iTfffedfn7BggX6O6K6D9Rn+YUXXnB+lnOlp6frfy/+XrkrzD6qC0+9RlhYmFx//fU6ewb4mjLebgAKR/2xUd0CuVSqX/1xUenNwho4cKA88MADkpiYKM8++6x+rP5oFsbkyZN1OnXatGk6IFDtUefIzs7Wz6taBcBXvy+zZ8/WQYHqp1dBco8ePWT8+PE6qFbfo/nz5+susosdOnRI7Ha7DhgKUph9VFC9dOlSHVBv3LhR+vfvr9umioABX0FmwE+pwiP1RygzM1P/2vj+++917UCu//znP/p59Ycol/pF36hRI/2HsG3btnn6N9Ufqlypqamye/dufe7c83Xp0kUee+wxnYVQ2QX1fK769evrgECNdAB8jfouqEVdkNevXy+1a9eW559/Xlq0aKE/uyrD5k7VzqjviyqoLUhh9lFFu+rir76LvXr10t8flbEAfAnBgJ9QKfjk5GS9qJT84MGDdSGhKvJTF3f1x0j9oVHFfV999ZV+XhX45RbwvfXWW/Ljjz/q6mdVOLhq1Sq58cYbXV5jwoQJ+mKuzqHGakdGRkrXrl31c+oPpjpG/SFVr//kk09KSkqK81j1+qpCe+TIkfLBBx/I3r17dXDx3nvvXeX/UkDB35eOHTvqz7LqElDZAPU5/cc//iGLFy92HquyXR9++KFMmTJF+vTpk+/5C7NPLlUmowpwVbC+Zs0aXbTYpEkTj79n4Ip4u2gBhSuIUv9X5S4VK1a0WrZsaS1cuNC5zw8//GC1a9fOCgkJsSIiIqz+/ftbp06dcj7fsWNHKzIyUhf51atXz3rllVcsh8PhUvS0bNkyq3HjxlZQUJB18803W99//71LQWGXLl2sChUqWFWqVLFeeOEFq2fPnnpbrpycHOvll1+2ateubQUGBlq1atWyJk6cmOf9UECIq/19uemmm6x58+Y59xkxYoRVuXJl/Xnu1q2bNXXqVCssLEw/t2XLFuvaa6+1Jk2apD/TuS4uDizMPrkFhLntUAW9NWvWtMaOHaufo4AQvsSm/ufKwgn4OzXOX9UOqK6BSpUqebs5AICrjG4CAAAMRzAAAIDh6CYAAMBwZAYAADAcwQAAAIYjGAAAwHAEAwAAGI5gAAAAwxEMAABgOIIBAAAMRzAAAICY7f8DzrsrJhITc3kAAAAASUVORK5CYII=",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import seaborn as sns\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"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",
|
||
"df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\"]\n",
|
||
"\n",
|
||
"sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"sns.pairplot(df, hue=\"Категория\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"numeric_df = df.select_dtypes(include=['int64', 'float64'])\n",
|
||
"sns.heatmap(numeric_df.corr(), annot=True, cmap='coolwarm')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "4731091b-6d6c-49f2-9427-f510c910fd3b",
|
||
"metadata": {},
|
||
"source": [
|
||
"Добавить sns.pairplot(df), sns.heatmap(df.corr(), annot=True)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"id": "1b0e5ea0-e7a4-4c7c-93fb-af32f8133642",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 94.30it/s]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tqdm import tqdm\n",
|
||
"import time\n",
|
||
"\n",
|
||
"for i in tqdm(range(100)):\n",
|
||
" time.sleep(0.01) # Симуляция долгого процесса"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "766d109d-5347-4f03-a72f-c298e55aeafe",
|
||
"metadata": {},
|
||
"source": [
|
||
"Код без изменений"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"id": "a50b4e8f-5483-488c-b53d-83bd18d18fc2",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:02<00:00, 1.98it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
" Имя Возраст Баллы Новый_столбец\n",
|
||
"0 Анна 21 89 178.0\n",
|
||
"1 Борис 22 76 152.0\n",
|
||
"2 Виктор 23 95 190.0\n",
|
||
"3 Галина 24 82 164.0\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tqdm import tqdm\n",
|
||
"import pandas as pd\n",
|
||
"import time\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",
|
||
"for index, row in tqdm(df.iterrows(), total=len(df)):\n",
|
||
" time.sleep(0.5)\n",
|
||
" df.at[index, 'Новый_столбец'] = row['Баллы'] * 2\n",
|
||
"\n",
|
||
"print(df)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "2e49e0b1-b5bb-46d2-99fc-1f6b4a178908",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"Использовать tqdm для обработки данных (tqdm(df.iterrows()))."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"id": "b1790d89-0fd3-4359-90bd-78550f3a07f9",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первые 5 строк:\n",
|
||
" Title Location \\\n",
|
||
"0 ListingTitle District \n",
|
||
"1 2016 AUDİ A3 SPORTBACK 1.0 TFSI BOYASIZ/DEĞİŞE... Aşağısoku Mh. Merkez \n",
|
||
"2 2018 AUDİ A6 2.0 TDI QUATTRO SUNROOF MATRİX VA... Güneşevler Mh. Altındağ \n",
|
||
"3 Sahibinden Audi A4 Sedan 1.8 TFSI 2011 Model Burmalı Mh. Merkez \n",
|
||
"4 2016 AUDI A3 AMBİENTE *CAM TAVAN LED XENON HIZ... Ilıca Mh. Manavgat \n",
|
||
"\n",
|
||
" City Price ID Date Brand Model \\\n",
|
||
"0 City Price(TRY) ListingID ListingDate Brand Series \n",
|
||
"1 Bolu 1.169.000 TL 27812680 07 April 2025 Audi A3 \n",
|
||
"2 Ankara 2.450.000 TL 28816234 07 April 2025 Audi A6 \n",
|
||
"3 Afyonkarahisar 750.000 TL 28781662 08 April 2025 Audi A4 \n",
|
||
"4 Antalya 1.195.000 TL 28731117 03 April 2025 Audi A3 \n",
|
||
"\n",
|
||
" Trim Year ... Body_Type Color \\\n",
|
||
"0 Model Year ... BodyType Color \n",
|
||
"1 A3 Sportback 1.0 TFSI Dynamic 2016.0 ... Hatchback/5 White \n",
|
||
"2 A6 Sedan 2.0 TDI Quattro 2018.0 ... Sedan Black \n",
|
||
"3 A4 Sedan 1.8 TFSI 2011.0 ... Sedan White \n",
|
||
"4 A3 Sportback 1.6 TDI Ambiente 2016.0 ... Hatchback/5 Black \n",
|
||
"\n",
|
||
" Engine_Size Horsepower Drive_Wheels \\\n",
|
||
"0 EngineSize(cc) EnginePower(HP) DriveTrain \n",
|
||
"1 1200 cm3' e kadar 101 - 125 HP FWD \n",
|
||
"2 1968 cc 190 hp AWD \n",
|
||
"3 1798 cc 160 hp FWD \n",
|
||
"4 1598 cc 110 hp FWD \n",
|
||
"\n",
|
||
" Damages Trade_In \\\n",
|
||
"0 PaintAndPartsCondition TradeInAvailable \n",
|
||
"1 Original Right Rear Fender Trunk Lid Left R... Trade-In Accepted \n",
|
||
"2 Original Trunk Lid Right Rear Door Right Fr... Trade-In Not Accepted \n",
|
||
"3 Original Roof Left Front Door Hood Front B... Trade-In Not Accepted \n",
|
||
"4 Original Right Rear Fender Trunk Lid Right ... Trade-In Accepted \n",
|
||
"\n",
|
||
" Seller_Type Tramer_Amount Other_Info \n",
|
||
"0 SellerType VehicleTax(TRY) AccidentHistory \n",
|
||
"1 NaN NaN NaN \n",
|
||
"2 Dealer NaN Amount not specified \n",
|
||
"3 Private Seller 2.013 75.000 \n",
|
||
"4 Dealer 1.606 No tram amount \n",
|
||
"\n",
|
||
"[5 rows x 23 columns]\n",
|
||
"\n",
|
||
"Информация о данных:\n",
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 6676 entries, 0 to 6675\n",
|
||
"Data columns (total 23 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 Title 6676 non-null object\n",
|
||
" 1 Location 6676 non-null object\n",
|
||
" 2 City 6676 non-null object\n",
|
||
" 3 Price 6676 non-null object\n",
|
||
" 4 ID 6676 non-null object\n",
|
||
" 5 Date 6676 non-null object\n",
|
||
" 6 Brand 6676 non-null object\n",
|
||
" 7 Model 6676 non-null object\n",
|
||
" 8 Trim 6675 non-null object\n",
|
||
" 9 Year 6675 non-null object\n",
|
||
" 10 Mileage 6676 non-null object\n",
|
||
" 11 Transmission 6675 non-null object\n",
|
||
" 12 Fuel_Type 6675 non-null object\n",
|
||
" 13 Body_Type 6557 non-null object\n",
|
||
" 14 Color 4221 non-null object\n",
|
||
" 15 Engine_Size 6485 non-null object\n",
|
||
" 16 Horsepower 6478 non-null object\n",
|
||
" 17 Drive_Wheels 6439 non-null object\n",
|
||
" 18 Damages 6676 non-null object\n",
|
||
" 19 Trade_In 2879 non-null object\n",
|
||
" 20 Seller_Type 3578 non-null object\n",
|
||
" 21 Tramer_Amount 1962 non-null object\n",
|
||
" 22 Other_Info 3092 non-null object\n",
|
||
"dtypes: object(23)\n",
|
||
"memory usage: 1.2+ MB\n",
|
||
"None\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
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",
|
||
"text/plain": [
|
||
"<Figure size 2000x1200 with 4 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",
|
||
"# Настройка стиля графиков\n",
|
||
"sns.set(style=\"whitegrid\")\n",
|
||
"\n",
|
||
"# Шаг 1: Определение заголовков колонок\n",
|
||
"columns = [\n",
|
||
" \"Title\", \"Location\", \"City\", \"Price\", \"ID\", \"Date\", \"Brand\", \"Model\",\n",
|
||
" \"Trim\", \"Year\", \"Mileage\", \"Transmission\", \"Fuel_Type\", \"Body_Type\",\n",
|
||
" \"Color\", \"Engine_Size\", \"Horsepower\", \"Drive_Wheels\", \"Damages\",\n",
|
||
" \"Trade_In\", \"Seller_Type\", \"Tramer_Amount\", \"Other_Info\"\n",
|
||
"]\n",
|
||
"\n",
|
||
"# Шаг 2: Чтение CSV файла\n",
|
||
"df = pd.read_csv(\"cars_en.csv\", names=columns, header=None, on_bad_lines='skip')\n",
|
||
"\n",
|
||
"# Шаг 3: Вывод первых строк для проверки\n",
|
||
"print(\"Первые 5 строк:\")\n",
|
||
"print(df.head())\n",
|
||
"\n",
|
||
"print(\"\\nИнформация о данных:\")\n",
|
||
"print(df.info())\n",
|
||
"\n",
|
||
"# Шаг 4: Очистка и преобразование числовых столбцов\n",
|
||
"\n",
|
||
"# Чистка цены: удаление всех символов кроме цифр\n",
|
||
"df[\"Price\"] = df[\"Price\"].str.replace(r\"[^0-9]\", \"\", regex=True)\n",
|
||
"df[\"Price\"] = pd.to_numeric(df[\"Price\"], errors='coerce').fillna(0).astype(int)\n",
|
||
"\n",
|
||
"# Год выпуска\n",
|
||
"df[\"Year\"] = pd.to_numeric(df[\"Year\"], errors='coerce').fillna(0).astype(int)\n",
|
||
"\n",
|
||
"# Пробег\n",
|
||
"df[\"Mileage\"] = df[\"Mileage\"].str.replace(r\"[^0-9]\", \"\", regex=True)\n",
|
||
"df[\"Mileage\"] = pd.to_numeric(df[\"Mileage\"], errors='coerce').fillna(0).astype(int)\n",
|
||
"\n",
|
||
"# Фильтрация некорректных записей\n",
|
||
"df = df[(df[\"Year\"] > 1990) & (df[\"Mileage\"] > 0)]\n",
|
||
"\n",
|
||
"# Шаг 5: Построение графиков\n",
|
||
"plt.figure(figsize=(20, 12))\n",
|
||
"\n",
|
||
"# 1. Распределение цен\n",
|
||
"plt.subplot(2, 2, 1)\n",
|
||
"sns.histplot(df[\"Price\"], bins=30, kde=True, color=\"skyblue\")\n",
|
||
"plt.title(\"Распределение цен на автомобили\")\n",
|
||
"plt.xlabel(\"Цена (TL)\")\n",
|
||
"plt.ylabel(\"Частота\")\n",
|
||
"\n",
|
||
"# 2. Цена vs Пробег\n",
|
||
"plt.subplot(2, 2, 2)\n",
|
||
"sns.scatterplot(x=\"Mileage\", y=\"Price\", data=df, alpha=0.6, color=\"green\")\n",
|
||
"plt.title(\"Зависимость цены от пробега\")\n",
|
||
"plt.xlabel(\"Пробег (км)\")\n",
|
||
"plt.ylabel(\"Цена (TL)\")\n",
|
||
"\n",
|
||
"# 3. Средняя цена по брендам (ТОП-10)\n",
|
||
"plt.subplot(2, 2, 3)\n",
|
||
"top_brands = df.groupby(\"Brand\")[\"Price\"].mean().sort_values(ascending=False).head(10)\n",
|
||
"sns.barplot(x=top_brands.values, y=top_brands.index, palette=\"viridis\", hue=top_brands.index, legend=False)\n",
|
||
"plt.title(\"Средняя цена по брендам (ТОП-10)\")\n",
|
||
"plt.xlabel(\"Средняя цена (TL)\")\n",
|
||
"plt.ylabel(\"Марка автомобиля\")\n",
|
||
"\n",
|
||
"# 4. Количество объявлений по городам (ТОП-10)\n",
|
||
"plt.subplot(2, 2, 4)\n",
|
||
"city_counts = df[\"City\"].value_counts().head(10)\n",
|
||
"sns.barplot(x=city_counts.values, y=city_counts.index, palette=\"coolwarm\", hue=city_counts.index, legend=False)\n",
|
||
"plt.title(\"Количество объявлений по городам (ТОП-10)\")\n",
|
||
"plt.xlabel(\"Количество объявлений\")\n",
|
||
"plt.ylabel(\"Город\")\n",
|
||
"\n",
|
||
"# Отображение графиков\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "7b3141e1-67c8-492e-a08a-89866010a2dc",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3 (ipykernel)",
|
||
"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": "3.13.2"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|