1328 lines
355 KiB
Plaintext
1328 lines
355 KiB
Plaintext
{
|
||
"cells": [
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "c033731f-63ff-45a1-9466-15886f15ae09",
|
||
"metadata": {},
|
||
"source": [
|
||
"Тестовый код"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"id": "bf32d476-0486-4477-aab4-e86965882fdf",
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||
"metadata": {},
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"outputs": [
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||
{
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||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
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||
"3\n"
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]
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||
}
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||
],
|
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"source": [
|
||
"test = 1\n",
|
||
"test2 = 2\n",
|
||
"print(test + test2)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"id": "286caee8-913b-4fa5-ae6e-5be0ba523cb7",
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||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
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"1\n",
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"Hello Sailor!\n"
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]
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}
|
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],
|
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"source": [
|
||
"import random\n",
|
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"\n",
|
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"aa = \"Hello \"\n",
|
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"bb = \"World!\"\n",
|
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"cc = \"Sailor!\"\n",
|
||
"\n",
|
||
"r = random.randint(1, 10)\n",
|
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"\n",
|
||
"if (r > 5):\n",
|
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" zz = aa + bb\n",
|
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"else:\n",
|
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" zz = aa + cc\n",
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"\n",
|
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"print(r)\n",
|
||
"print(zz)"
|
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]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "8757d814-8118-4250-9fe6-8d4c847f4791",
|
||
"metadata": {},
|
||
"source": [
|
||
"Часть 3"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"id": "6e2f0daf-10fe-4892-8438-7a10f5cc05bd",
|
||
"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",
|
||
" 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"
|
||
]
|
||
}
|
||
],
|
||
"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())"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "3b801627-8797-4b4d-8f3d-c3ea9911e1bf",
|
||
"metadata": {},
|
||
"source": [
|
||
"Часть 3 с изменениями"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"id": "f9b40974-e401-451a-8dcb-3aa296931280",
|
||
"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"
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||
]
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{
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"data": {
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"text/html": [
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"<style scoped>\n",
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" <thead>\n",
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" <th></th>\n",
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||
" </tr>\n",
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||
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|
||
" <tbody>\n",
|
||
" <tr>\n",
|
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" <th>0</th>\n",
|
||
" <td>Анна</td>\n",
|
||
" <td>21</td>\n",
|
||
" <td>89</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>Борис</td>\n",
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||
" <td>22</td>\n",
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" <td>76</td>\n",
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" </tr>\n",
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" <tr>\n",
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||
" <th>2</th>\n",
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" <td>Виктор</td>\n",
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||
" <td>23</td>\n",
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||
" <td>95</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>Галина</td>\n",
|
||
" <td>24</td>\n",
|
||
" <td>82</td>\n",
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"text/plain": [
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" Имя Возраст Баллы\n",
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||
"0 Анна 21 89\n",
|
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"1 Борис 22 76\n",
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||
"2 Виктор 23 95\n",
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||
"3 Галина 24 82"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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||
"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",
|
||
"df"
|
||
]
|
||
},
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||
{
|
||
"cell_type": "code",
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"execution_count": 13,
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"id": "9ee10d5f-ba28-45bd-9766-89491bb8d9a1",
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||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первый взгляд на данные:\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",
|
||
"<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 Новый столбец 4 non-null float64\n",
|
||
"dtypes: float64(1), int64(2), object(1)\n",
|
||
"memory usage: 260.0+ bytes\n",
|
||
"None\n",
|
||
" Возраст Баллы Новый столбец\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",
|
||
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|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
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" <td>Анна</td>\n",
|
||
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|
||
" <td>89</td>\n",
|
||
" <td>97.9</td>\n",
|
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" </tr>\n",
|
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" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>Борис</td>\n",
|
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|
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" <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",
|
||
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|
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"text/plain": [
|
||
" 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"
|
||
]
|
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},
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"metadata": {},
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"output_type": "execute_result"
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}
|
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],
|
||
"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",
|
||
"df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\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",
|
||
"df"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"id": "841cffd3-b0f4-4d76-918e-822044d8cda1",
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||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первый взгляд на данные:\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",
|
||
"<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 Новый столбец 4 non-null float64\n",
|
||
"dtypes: float64(1), int64(2), object(1)\n",
|
||
"memory usage: 260.0+ bytes\n",
|
||
"None\n",
|
||
" Возраст Баллы Новый столбец\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",
|
||
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|
||
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||
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|
||
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|
||
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|
||
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||
" <th></th>\n",
|
||
" <th colspan=\"4\" halign=\"left\">Баллы</th>\n",
|
||
" <th>Возраст</th>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th></th>\n",
|
||
" <th>mean</th>\n",
|
||
" <th>sum</th>\n",
|
||
" <th>max</th>\n",
|
||
" <th>min</th>\n",
|
||
" <th>mean</th>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>Баллы</th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" <th></th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>76</th>\n",
|
||
" <td>76.0</td>\n",
|
||
" <td>76</td>\n",
|
||
" <td>76</td>\n",
|
||
" <td>76</td>\n",
|
||
" <td>22.0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>82</th>\n",
|
||
" <td>82.0</td>\n",
|
||
" <td>82</td>\n",
|
||
" <td>82</td>\n",
|
||
" <td>82</td>\n",
|
||
" <td>24.0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>89</th>\n",
|
||
" <td>89.0</td>\n",
|
||
" <td>89</td>\n",
|
||
" <td>89</td>\n",
|
||
" <td>89</td>\n",
|
||
" <td>21.0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>95</th>\n",
|
||
" <td>95.0</td>\n",
|
||
" <td>95</td>\n",
|
||
" <td>95</td>\n",
|
||
" <td>95</td>\n",
|
||
" <td>23.0</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" Баллы Возраст\n",
|
||
" mean sum max min mean\n",
|
||
"Баллы \n",
|
||
"76 76.0 76 76 76 22.0\n",
|
||
"82 82.0 82 82 82 24.0\n",
|
||
"89 89.0 89 89 89 21.0\n",
|
||
"95 95.0 95 95 95 23.0"
|
||
]
|
||
},
|
||
"execution_count": 16,
|
||
"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",
|
||
"df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
|
||
"\n",
|
||
"grouped_df = df.groupby(\"Баллы\").agg({\n",
|
||
" \"Баллы\": [\"mean\", \"sum\", \"max\", \"min\"],\n",
|
||
" \"Возраст\": \"mean\"\n",
|
||
"})\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",
|
||
"grouped_df"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"id": "c7b256e1-c871-4131-bd8d-a0608a18ec28",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первый взгляд на данные:\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",
|
||
"<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 Новый столбец 4 non-null float64\n",
|
||
"dtypes: float64(1), int64(2), object(1)\n",
|
||
"memory usage: 260.0+ bytes\n",
|
||
"None\n",
|
||
" Возраст Баллы Новый столбец\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",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"Новый столбец 0\n",
|
||
"dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"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>Новый столбец</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>"
|
||
],
|
||
"text/plain": [
|
||
" 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"
|
||
]
|
||
},
|
||
"execution_count": 17,
|
||
"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",
|
||
"df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
|
||
"df[df[\"Возраст\"] > 21]\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",
|
||
"df"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "fabc986b-9e8a-4fad-82cf-7e0d22e2d485",
|
||
"metadata": {},
|
||
"source": [
|
||
"Часть 3 - часть 2"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"id": "5a137f99-a29a-4c32-8727-8fe71e93f82f",
|
||
"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": 21,
|
||
"id": "0bff7510-f22b-4335-9596-1ff30cb0f806",
|
||
"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"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"array([3. , 3.02040816, 3.04081633, 3.06122449, 3.08163265,\n",
|
||
" 3.10204082, 3.12244898, 3.14285714, 3.16326531, 3.18367347,\n",
|
||
" 3.20408163, 3.2244898 , 3.24489796, 3.26530612, 3.28571429,\n",
|
||
" 3.30612245, 3.32653061, 3.34693878, 3.36734694, 3.3877551 ,\n",
|
||
" 3.40816327, 3.42857143, 3.44897959, 3.46938776, 3.48979592,\n",
|
||
" 3.51020408, 3.53061224, 3.55102041, 3.57142857, 3.59183673,\n",
|
||
" 3.6122449 , 3.63265306, 3.65306122, 3.67346939, 3.69387755,\n",
|
||
" 3.71428571, 3.73469388, 3.75510204, 3.7755102 , 3.79591837,\n",
|
||
" 3.81632653, 3.83673469, 3.85714286, 3.87755102, 3.89795918,\n",
|
||
" 3.91836735, 3.93877551, 3.95918367, 3.97959184, 4. ])"
|
||
]
|
||
},
|
||
"execution_count": 21,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"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",
|
||
"\n",
|
||
"arr2 = np.array([[1, 2], [3, 4]])\n",
|
||
"np.linspace(3, 4)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"id": "01af748b-1dee-483d-be1d-39d9d39e2daf",
|
||
"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"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"1.063095687089255"
|
||
]
|
||
},
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"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",
|
||
"\n",
|
||
"arr2 = np.array([[1, 2], [3, 4]])\n",
|
||
"np.random.randn()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"id": "6120edc2-d49b-42a8-bf34-606f0b465c63",
|
||
"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"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"np.int64(11)"
|
||
]
|
||
},
|
||
"execution_count": 25,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"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",
|
||
"\n",
|
||
"arr2 = np.array([[1, 2], [3, 4]])\n",
|
||
"np.dot(arr2[0], arr2[1])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "39a7b707-93dd-4586-958f-b4bfa5e23d9c",
|
||
"metadata": {},
|
||
"source": [
|
||
"Matplot"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"id": "03295aee-25dd-48b0-a88e-2182a1213171",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"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": "code",
|
||
"execution_count": 29,
|
||
"id": "264e7d30-72b9-4b2f-8d49-79df44406e84",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"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.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"График синуса\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"id": "f8a4b3e5-6281-4d26-9021-3336319097dd",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"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, np.sin(x), label='sin(x)', color='red')\n",
|
||
"plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"Мультиграфик\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 35,
|
||
"id": "cbf8dfa9-b3f4-4c09-a268-712f18d62733",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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kVwIAAOzCVpWladOmSY8ePaRbt25So0YNE5ri4+MlNTXV6/alS5eWxMRE15KWlma2zx2WNBy5b1eqVKkAvSIAABDqbFNZ0grRli1bZOjQoa51RYoUkRYtWsiGDRt82scrr7wiHTt2lBIlSnisX7t2ralMaUhq1qyZjB8/Xi699NI893P69GmzOGVmZprb7Oxss4QS5/H4/bji4iTSZP/1mp23hfvFQut9ZKv3ZgQKmbYMk58LAf2sF0Swv792fm/mwdfjinI47DGhy8GDB+Wyyy6T9evXS+PGjV3rBw8eLOvWrZONGzdaPl/HNmnXnW7XsGFD1/pFixaZalPlypXlxx9/lGHDhslFF11kAlh0dLTXfY0ePVrGjBlzzvoFCxaYfQEAgNCXlZUl9913n2RkZEjJkiXtX1m6UFpVqlWrlkdQUlppctLHa9euLVdeeaWpNjVv3tzrvrS6pWOn3CtLSUlJ0rJlS8vGDlZq1u7HlJQUiYmJ8d+OExIk0uhfmWmpqZLSvbvEnDpVuF8sI0PCXaG9NyNQyLRlmPxcCOhnPcx/TmSHynszD86eofzYJiyVKVPGVHoOHz7ssV7v6zgjKydPnjQVpLFjx+b7dapUqWK+1q5du/IMSzrGydsgcH0jhOKboVCOLZR/gBQy/eFZ6D9AQ/R9VBhC+XNjN0FvyzD7uRCQz/qFsNHnJibY7808+HpMthngXaxYMalfv76sXr3atS4nJ8fcd++W8+att94yY4zuv//+fL/Ozz//bM6aq1Chgl+OGzjv+WpyLwCAoLBNWFLa9TV37lx57bXXZMeOHdK7d29TNdKz41Tnzp09BoC7d8G1a9funEHbJ06ckEGDBsnnn38ue/bsMcGrbdu2UrVqVTMlAdzwixsAEKFs0w2nOnToIEePHpWRI0dKenq61K1bV1asWCHly5c3j+/bt8+cIedO52D69NNPZdWqVefsT7v1vv76axO+jh8/LhUrVjTjjsaNG8dcSwAAwH5hSfXt29cs3uig7NyuvvpqyeuEv7i4OFm5cqXfjxEAAIQP24UlAEAIoDseEcRWY5YAAAACjbAEAABggbAEAABggbAEAABggbAEAABggbPhAAAIhzMS85gmBxeOyhIAAIAFKkuAXfBXJAAEBZUlAAAAC1SW4B2z8wIAYFBZAgAAsEBlCQCQP6rNiGBUlgAAACwQlgAAACwQlgAAACwQlgAAACwQlgAAACwQlgAAACwwdQAAAOE6vQOXRfILKksAAAAWCEsAAAAW6IYDwqXkTrkdAAoFYQn/xaUMAADwim44AAAAC4QlAAAAC3TDAQDORdc84EJlCQAAwAJhCQAAwAJhCQAAwAJhCQAAIJzC0qxZsyQ5OVmKFy8ujRo1kk2bNuW57auvvipRUVEeiz7PncPhkJEjR0qFChUkLi5OWrRoIT/88EMAXgkAALADW4WlxYsXy8CBA2XUqFGydetWqVOnjrRq1UqOHDmS53NKliwphw4dci179+71eHzKlCkyY8YMmT17tmzcuFFKlChh9vnHH38E4BUBAIBQZ6uwNG3aNOnRo4d069ZNatSoYQJOfHy8pKam5vkcrSYlJia6lvLly3tUlaZPny7Dhw+Xtm3bSu3ateX111+XgwcPytKlSwP0qgAAKMQpINwXhPc8S2fOnJEtW7bI0KFDXeuKFClius02bNiQ5/NOnDghV1xxheTk5Mi1114rEydOlGuuucY8tnv3bklPTzf7cEpISDDde7rPjh07et3n6dOnzeKUmZlpbrOzs80SSpzHk+9xxcUF5oBsLPuvNnLehpwQe+/57b2J4LRlqL7PAyDkP+sXIsCft+wQ/5z7elxRDi2v2IBWey677DJZv369NG7c2LV+8ODBsm7dOtOFlpsGHh1/pBWjjIwMmTp1qnzyySeyfft2qVSpktnX9ddfb/atY5ac7rnnHlOR0m4/b0aPHi1jxow5Z/2CBQtMpQsAAIS+rKwsue+++0xG0GE7tq8snQ8NVe7BqkmTJlK9enWZM2eOjBs37rz3q9UtHTvlXllKSkqSli1bWjZ2sFJzWlqapKSkSExMTN4bJiQE8rBsSf/KTEtNlZTu3SXm1CkJeRkZEsp8fm8iOG0ZwT8TbPdZD+GfC9kh/jl39gzlxzZhqUyZMhIdHS2HDx/2WK/3dSySL/QbVa9ePdm1a5e573ye7sO9sqT369atm+d+YmNjzeJt/6H4ZvDp2MLtB0Ih0h+etvgBGqLvRTt9buzGr21ph/d4IbPNZ70ggvRZiwnRz7mvx2SbAd7FihWT+vXry+rVq13rdByS3nevHlk5e/asfPPNN65gVLlyZROY3PepKVO79HzdZ1gM+GPQHwAA9q8sKe366tKlizRo0EAaNmxozmQ7efKkOTtOde7c2YxrmjRpkrk/duxYue6666Rq1apy/Phxefrpp83UAQ899JB5XMcl9e/fX8aPHy9XXXWVCU8jRoyQihUrSrt27YL6WgEAQGiwVVjq0KGDHD161EwiqWexaVfZihUrXNMB7Nu3z5wh5/Tbb7+ZqQZ021KlSpnKlA7q1mkH3AeIa+Dq2bOnCVRNmzY1+8w9eSUAAIhMtgpLqm/fvmbxZu3atR73n332WbNY0eqSVqB0AYCIRXc8YP8xSwAAAMFAWAIAALBAWAIAALBAWAIAALBAWAIAALBAWAIAAAinqQMAAICfpohwOIJ1JLZCZQkAAMACYQkAAMAC3XBAuKLcDgB+QWUJAADAAmEpUiQk/LfSwPWfAAAoEMISAACABcISAACABQZ4A0Akokse8BmVJQAAAAuEJQAAAAuEJQAAAAuEJQAAAAuEJQAAAAuEJQAAAAuEJQAAAAvMswQAQKTigts+obIEAABggbAEAABggW44IJIvb0HJHQDyRWUJAADAAmEpXCsIziUhIdhHAwCArRGWAAAALBCWAAAALDDAGwAicXA/gPCtLM2aNUuSk5OlePHi0qhRI9m0aVOe286dO1duuOEGKVWqlFlatGhxzvZdu3aVqKgoj6V169YBeCUAAMAObBWWFi9eLAMHDpRRo0bJ1q1bpU6dOtKqVSs5cuSI1+3Xrl0r9957r3z88ceyYcMGSUpKkpYtW8qBAwc8ttNwdOjQIdeycOHCAL0iAAAQ6mwVlqZNmyY9evSQbt26SY0aNWT27NkSHx8vqampXrefP3++PPzww1K3bl2pVq2avPzyy5KTkyOrV6/22C42NlYSExNdi1ahAAAAbDVm6cyZM7JlyxYZOnSoa12RIkVM15pWjXyRlZUl2dnZUrp06XMqUOXKlTMhqVmzZjJ+/Hi59NJL89zP6dOnzeKUmZlpbnXfugRdXJzrv9l//d95i/MXlm0ZxPer87MSEp8Zm8u3LcPpPRsAYflZ95WfP4/ZIf459/W4ohwOe0zhe/DgQbnssstk/fr10rhxY9f6wYMHy7p162Tjxo357kOrTCtXrpTt27ebMU9q0aJFpjpVuXJl+fHHH2XYsGFy0UUXmQAWHR3tdT+jR4+WMWPGnLN+wYIFZl8AACD0aRHlvvvuk4yMDClZsqT9K0sX6qmnnjLBSKtIzqCkOnbs6Pp/rVq1pHbt2nLllVea7Zo3b+51X1rd0rFT7pUl53goq8YOGLeJKPUvo7TUVEnp3l1iTp0K6mHZXVi2ZUZGUP+iS0tLk5SUFImJiQnacYSDfNuSyWkLJCw/60H6mZAd4p9zZ89QfmwTlsqUKWMqPYcPH/ZYr/d1nJGVqVOnmrD00UcfmTBkpUqVKuZr7dq1K8+wpGOcdMlN3wgh8Wbw8uHWD3zEfegLSVi1ZQi8X0PmcxMG8mzLcHm/BlhYfdZ9VUifxZgQ/Zz7eky2GeBdrFgxqV+/vsfgbOdgbfduudymTJki48aNkxUrVkiDBg3y/To///yz/Prrr1KhQgW/HTsAALa7XBbzc9kvLCnt+tK5k1577TXZsWOH9O7dW06ePGnOjlOdO3f2GAA+efJkGTFihDlbTudmSk9PN8uJEyfM43o7aNAg+fzzz2XPnj0meLVt21aqVq1qpiQAAACwTTec6tChgxw9elRGjhxpQo9OCaAVo/Lly5vH9+3bZ86Qc3rxxRfNWXT/+Mc/PPaj8zTpIG3t1vv6669N+Dp+/LhUrFjRjDvSSpS3bjYAABB5bBWWVN++fc3ijQ7KdqfVIitxcXHm7DgAAICwCUsA/Cj3mAR7zCQCAAFFWAoHDMIDAKDQ2GqANwAAQKARlgAAACwQlgAAACwwZgkAwg3jGAG/orIEAABggbAEAABggbAEAABggbAEAABggbAEAABggbAEAABggbAEAABggXmWAACA73N2OSLvgttUlgAAACwQlgAAACzQDQcg75J7BJbbASA3KksAAAAWqCzZDRfIBAAgoKgsAQAAWCAsAQAAWCAsAYDdJST8/y1d9YDfEZYAAAAsEJYAAAAsEJYAAAAsEJYAAAAsEJYAAAAsEJYAAAAsEJYAAAAsEJYAAAD8EZYOHjzo66YAACBcRUV5LhHA57B0zTXXyIIFCyTYZs2aJcnJyVK8eHFp1KiRbNq0yXL7t956S6pVq2a2r1WrlixfvtzjcYfDISNHjpQKFSpIXFyctGjRQn744YdCfhUAACDswtKECRPkn//8p7Rv316OHTsmwbB48WIZOHCgjBo1SrZu3Sp16tSRVq1ayZEjR7xuv379ern33nvlwQcflC+//FLatWtnlm+//da1zZQpU2TGjBkye/Zs2bhxo5QoUcLs848//gjgKwMAALYPSw8//LB8/fXX8uuvv0qNGjVk2bJlEmjTpk2THj16SLdu3cwxaMCJj4+X1NRUr9s/99xz0rp1axk0aJBUr15dxo0bJ9dee608//zzrqrS9OnTZfjw4dK2bVupXbu2vP7666bLcenSpQF+dUAIisByOwDkVlQKoHLlyrJmzRoTNu666y4TQIoW9dyFVnwKw5kzZ2TLli0ydOhQ17oiRYqYbrMNGzZ4fY6u10qUO60aOYPQ7t27JT093ezDKSEhwXTv6XM7duzodb+nT582i1NmZqa5zc7ONkuhiosr0ObZf23vvMX5oy3Nm9yPu/rvvgr9MxMBeG/6F+1ZQNnZtv2c+3pcBQpLau/evfLOO+9IqVKlTDUmd1gqLL/88oucPXtWypcv77Fe73///fden6NByNv2ut75uHNdXtt4M2nSJBkzZsw561etWmUqXYVq4cLzelpaHtU3FFxEt2WuMX/+kJaW5vd9Rpy/3pMR/d4sBLSn/34upIXo5zwrK8un7QqUdObOnSuPPfaYqcRs375dypYtK5FIq1vuFSutLCUlJUnLli2lZMmSEmqpWd+kKSkpEhMTE+zDsbWQa8uEBLEz/atdfxmldO8uMadOBftwbC0obZmRIeEq5D7rNv65kO2v92Yhvd+cPUN+C0s69kfPPNMuuM6dO0uglSlTRqKjo+Xw4cMe6/V+YmKi1+foeqvtnbe6Ts+Gc9+mbt26eR5LbGysWXLTD1WofrBC+djsJmTaMkwChv4AJSzZsC1D4TMQKZ/1ggjRz1LMhb43C+n74Ov31+cB3toFpgO8gxGUVLFixaR+/fqyevVq17qcnBxzv3Hjxl6fo+vdt1f614Jzex2DpYHJfRtNmXpWXF77BICI5HB4LkAE8bmyFAr9jdr11aVLF2nQoIE0bNjQnMl28uRJc3ac0iB32WWXmTFFql+/fnLTTTfJM888I23atJFFixbJF198IS+99JJ5PCoqSvr37y/jx4+Xq666yoSnESNGSMWKFc0UAwAAAIEZne0nHTp0kKNHj5pJJHUAtnaVrVixwjVAe9++feYMOacmTZqYiTR1aoBhw4aZQKRnwtWsWdO1zeDBg03g6tmzpxw/flyaNm1q9qmTWAIAANgqLKm+ffuaxZu1a9ees04n0dQlL1pdGjt2rFkAAABy40K6AAAAFghLAAAAFghLAAAAFghLAAAAFghLAAAA4XQ2HAAAyEPuCUOjooJ1JGGFyhIAAIAFwhIAAIAFuuEAu6LcDgABQWUJAADAAmEJAADAAmEJAADAAmEJAADAAgO8AQD5n0AARDAqSwAAABYISwAAABYISwAAABYISwAAABYISwAAABYISwAAABYISwAAABYISwAAABaYlBIAgEiZXDQqKlhHYmtUlgAAACwQlgAAACzQDQeE87W8KLkDwAWjsgQAAGCBsAQAAGCBsAQAAGCBsAQAAGCBAd4AEOm8nRwAwH6VpWPHjkmnTp2kZMmScskll8iDDz4oJ06csNz+kUcekauvvlri4uLk8ssvl0cffVQyMjI8touKijpnWbRoUQBeEQAAsAPbVJY0KB06dEjS0tIkOztbunXrJj179pQFCxZ43f7gwYNmmTp1qtSoUUP27t0rvXr1Muvefvttj23nzZsnrVu3dt3XMAYAAGCbsLRjxw5ZsWKFbN68WRo0aGDWzZw5U2677TYThipWrHjOc2rWrCn/+te/XPevvPJKmTBhgtx///3y559/StGiRT3CUWJiYoBeDQAAsBNbhKUNGzaYQOMMSqpFixZSpEgR2bhxo9x5550+7Ue74LQbzz0oqT59+shDDz0kVapUMdUnrVppd1xeTp8+bRanzMxMc6sVL11CifN4Qu247MiWbRkXJ6Eq+69jc94iiG1pp/d0ANjys+6rAH/esv31OS+k74Wv32NbhKX09HQpV66cxzoNPKVLlzaP+eKXX36RcePGma47d2PHjpVmzZpJfHy8rFq1Sh5++GEzFkrHN+Vl0qRJMmbMmHPW6/N1P6FIuy8RgW25cKGEurTU1GAfQtg477ZcvtzfhxIWbPVZD/GfCWkX+jkvpPdoVlZW6IelIUOGyOTJk/PtgrtQWvlp06aNGbs0evRoj8dGjBjh+n+9evXk5MmT8vTTT1uGpaFDh8rAgQM99p+UlCQtW7Y0latQoqlZP/ApKSkSExMT7MOxNVu2ZUKChCr9S1N/gKZ07y4xp04F+3Bs7YLbMteJL5HOlp/1EP2ZkO2vz3khvUedPUMhHZYee+wx6dq1q+U22jWm44mOHDnisV7HHekZb/mNNfr999/N4O2LL75YlixZku8bv1GjRqYCpd1ssbGxXrfR9d4e032H6gcrlI/NbmzVljYIIfoDlLAU5La0y/s5wGz1WfdVkD5rMRf6OS+k74Ov39+ghqWyZcuaJT+NGzeW48ePy5YtW6R+/fpm3Zo1ayQnJ8eEG6vE2KpVKxNs3nvvPSlevHi+X2vbtm1SqlSpPIMSAABhM6cWF9sOnzFL1atXN9WhHj16yOzZs02JtG/fvtKxY0fXmXAHDhyQ5s2by+uvvy4NGzY0QUm7xbQ/8o033jD3neU2DWjR0dGybNkyOXz4sFx33XUmSGnZdeLEifL4448H+RUDAIBQYYuwpObPn28CkgYiPQvu7rvvlhkzZrge1wC1c+dO12CtrVu3mjPlVNWqVT32tXv3bklOTjblt1mzZsmAAQPE4XCY7aZNm2ZCGQAAgK3Ckp75ltcElErDjwYep5tvvtnjvjdarXKfjBIIO5TcASByLncCAAAQDIQlAAAAC4QlAAAAC4QlAACAcBjgDQDwk3xOfgHgicoSAACABcISAACABcISAACABcISAACABcISAACABcISAACABcISAACABeZZAgAgUnGxbZ9QWQIAALBAWAIAALBANxwQSSi5A0CBUVkCAACwQFgCAACwQFgCAACwQFgCAACwwABvAIi0gf0ACoTKEgAAgAXCEgAAgAXCEgAAgAXCEgAAgAXCEgAAgAXCEgAAgAXCEgAAgAXmWQIAAHnPyRXFBbepLAEAAFggLAEAAIRDWDp27Jh06tRJSpYsKZdccok8+OCDcuLECcvn3HzzzRIVFeWx9OrVy2Obffv2SZs2bSQ+Pl7KlSsngwYNkj///LOQXw0QQiV39wUAYN8xSxqUDh06JGlpaZKdnS3dunWTnj17yoIFCyyf16NHDxk7dqzrvoYip7Nnz5qglJiYKOvXrzf779y5s8TExMjEiRML9fUAAAB7sEVY2rFjh6xYsUI2b94sDRo0MOtmzpwpt912m0ydOlUqVqyY53M1HGkY8mbVqlXy3XffyUcffSTly5eXunXryrhx4+SJJ56Q0aNHS7FixQrtNQEAAHuwRVjasGGD6XpzBiXVokULKVKkiGzcuFHuvPPOPJ87f/58eeONN0xguv3222XEiBGu6pLut1atWiYoObVq1Up69+4t27dvl3r16nnd5+nTp83ilJmZaW614qVLKHEeT6gdlx1FRFvGxQXsS2X/9bWctyjEtgzn92whiIjPekHExQX/c15I3wtfv8e2CEvp6elmPJG7okWLSunSpc1jebnvvvvkiiuuMJWnr7/+2lSMdu7cKe+8845rv+5BSTnvW+130qRJMmbMGK+VKvduvlCi3Zfwj7Buy4ULA/4l01JTA/41w1Webbl8eaAPJSyE9Wc9wD8X0i70c15I7+GsrKzQD0tDhgyRyZMn59sFd750TJOTVpAqVKggzZs3lx9//FGuvPLK897v0KFDZeDAgR6VpaSkJGnZsqUZgB5KNDXrBz4lJcWMxcL5i4i2TEgI2JfSvzT1B2hK9+4Sc+pUwL5uODqnLTMygn1IthYRn/UA/VzI9tfnvJDe086eoZAOS4899ph07drVcpsqVaqYLrQjR454rNcz1vQMubzGI3nTqFEjc7tr1y4TlvS5mzZt8tjm8OHD5tZqv7GxsWbJTT9UofrBCuVjs5uwbssghBb9AUpY8nNbhuv7M8DC+rNeEKdOBf9zXkjfB1+/v0ENS2XLljVLfho3bizHjx+XLVu2SP369c26NWvWSE5OjisA+WLbtm3mVitMzv1OmDDBBDFnN5/+NaHVoRo1apznqwIAAOHEFvMsVa9eXVq3bm2mAdBK0GeffSZ9+/aVjh07us6EO3DggFSrVs1VKdKuNj2zTQPWnj175L333jPTAtx4441Su3Zts412m2koeuCBB+Srr76SlStXyvDhw6VPnz5eK0cAACDy2CIsOc9q0zCkY450yoCmTZvKSy+95NHHrIO3nYO19LR/nRJAA5E+T7v87r77blm2bJnrOdHR0fL++++bW60y3X///SZQuc/LBAAAIpstzoZTeuab1QSUycnJ4nCbgVgHXK9bty7f/erZcss5UwQAANi9sgQAAELgskiOAizOs9j09kL2E2SEJQAAAAuEJQAAgHAYswQgAHKXu6OignUkABAyqCwBAABYICwBAABYICwBAABYICwBAABYICwBgN3lnssGgF8RlgAAACwQlgAAACwQlgAAACwQlgAAACwQlgAAACwQlgAAACwQlgAAACwQlgAAACwUtXoQQITzNsFhVFQwjgQAgobKEgAAgAXCEgAAgAXCEgAAgAXCEgDYbRxZ7gVAoSIsAQAAWCAsAQAAWCAsAQAAWCAsAQAAWCAsAQAAWCAsAQAAWCAsAQAAWODacAAKJve8PlwrDkCYo7IEAAAQDmHp2LFj0qlTJylZsqRccskl8uCDD8qJEyfy3H7Pnj0SFRXldXnrrbdc23l7fNGiRQF6VQAAINTZphtOg9KhQ4ckLS1NsrOzpVu3btKzZ09ZsGCB1+2TkpLM9u5eeuklefrpp+XWW2/1WD9v3jxp3bq1676GMQAAANuEpR07dsiKFStk8+bN0qBBA7Nu5syZctttt8nUqVOlYsWK5zwnOjpaEhMTPdYtWbJE7rnnHrnooos81ms4yr0tAIQErv0GBJ0twtKGDRtMoHEGJdWiRQspUqSIbNy4Ue68885897FlyxbZtm2bzJo165zH+vTpIw899JBUqVJFevXqZapW2h2Xl9OnT5vFKTMz09xqxUuXUOI8nlA7LjuiLfMQF3deT8v+63nOW+TBh/cb703/oj0jpy2zfTwuW4Sl9PR0KVeunMe6okWLSunSpc1jvnjllVekevXq0qRJE4/1Y8eOlWbNmkl8fLysWrVKHn74YTMW6tFHH81zX5MmTZIxY8acs16fr/sJRdp9Cf+gLXNZuPCCnp6Wmuq3QwlLy5f7vCnvTf+iPcO/LbOyskI/LA0ZMkQmT56cbxfchTp16pQZ2zRixIhzHnNfV69ePTl58qQZ12QVloYOHSoDBw70qCzpGKmWLVuaAeihlpr1TZqSkiIxMTHBPhxboy3zkJBwXk/TipIGpZTu3SXm1Cm/H1bYyMjIdxPem/5Fe0ZOW2b+1TMU0mHpsccek65du1puo11jOp7oyJEjHuv//PNPc4acL2ON3n77bZMeO3funO+2jRo1knHjxpluttjYWK/b6Hpvj+kbIRTfDKF+bHZDW+ZygUFHgxJhyUIB3mu8N/2L9gz/tozx8ZiCGpbKli1rlvw0btxYjh8/bsYd1a9f36xbs2aN5OTkmHDjSxfcHXfc4dPX0nFNpUqVyjMoAQCAyGKLMUs61khP7e/Ro4fMnj3blPX69u0rHTt2dJ0Jd+DAAWnevLm8/vrr0rBhQ9dzd+3aJZ988oks99Lvv2zZMjl8+LBcd911Urx4cVMqnDhxojz++OMBfX0AACB02SIsqfnz55uApIFIz4K7++67ZcaMGa7HNUDt3LnznMFaqampUqlSJTOeyFv5Tc+OGzBggDgcDqlatapMmzbNhDIAPuLyJwDCnG3Ckp75ltcElCo5OdkEnty0UqSLN1qtcp+MEgAAwLaXOwEAAAgGwhIAAEA4dMMBQETg8iZAyKGyBAAAYIGwBAAAYIGwBAAAYIGwBAAAYIGwBAAAYIGz4QD4FzN6AwgzVJYAAAAsEJYAAAAs0A0HAMHEJJRAyKOyBAAAYIGwBAAAYIGwBAAAYIGwBAAAYIGwBAAAYIGz4QAE/mwvJqoEYCNUlgAAACxQWQqQs2fPSnZ2dsC/rn7NokWLyh9//GGOIdzExMRIdHR0sA8D8A1zKgG2RFgKgBMnTsjPP/8sjiD8oNSvmZiYKPv375eoMOz60NdUqVIlueiii4J9KACAMEVYKmRazdGgFB8fL2XLlg14YMnJyTFhTcNEkSLh1euqQfDo0aOmfa+66ioqTACAQkFYCkA3mP5S16AUFxcX8K+vYenMmTNSvHjxsAtLStt1z549pp0JSwCAwhB+vz1DVDh2gYUC2hUAUNgISwACT8fvZWT89//OWwAIUYQlAAAAC4QlFFjXrl2lXbt2BX7e6tWrpXr16j5PYfDdd9+ZM91Onjx5HkcJhACtoLkvAGyJsBQsOtYmAEuR6Gi5pFQpvx76c889J6+++mqBnzd48GAZPny4zwOxa9SoIdddd51MmzbtPI4SAAD/ICyhwBISEuSSSy4p0HM+/fRT+fHHH+Xuu+8u0PO6desmL774ovz5558FPEoAAPyDsIQ8vf3221KrVi0z5cGll14qLVq0MF1iubvhbr75Znn00UdN5ah06dJmEszRo0d77GvRokWSkpJipjBQOp2C7q9Vq1auyTqPHTtmut1Gjhzpep4+R9evW7cuYK8bQUB3FYAQRliCV4cOHZJ7771XunfvLjt27JC1a9fKXXfdlecs5K+99pqUKFFCNm7cKFOmTJGxY8dKWlqa6/F///vf0qBBA49T/vU5mzdvlhkzZph1vXr1kssuu8wjLBUrVkzq1q1rng+EPEIfEJZsE5YmTJggTZo0MTNh+9oFpL/Y9RdvhQoVTHVEKxk//PCDxzZatejUqZOULFnS7PfBBx80M15HOg1L2vWlASk5OdlUmB5++OE8LytSu3ZtGTVqlJlJu3PnziYY6YBup71790rFihU9nqPBaM6cOTJkyBAZOnSoLF++XN544w1zLTt3+jx9PgAAwWCbsKSzULdv31569+7t83O0wqFVi9mzZ5uKh1Y+tNtHLyrrpEFp+/btpgry/vvvyyeffCI9e/aUSFenTh1p3ry5CUna7nPnzpXffvstz+01LLnTgHrkyBHX/VOnTrm64Nzpvu+880556qmnZOrUqSZs5aZBNysr64JfEwAAYR2WxowZIwMGDDC/vH2tKk2fPt2cfdW2bVvzy/z111+XgwcPytKlS8022r20YsUKefnll6VRo0bStGlTmTlzphlfo9tFMj1jTQPkhx9+aM5K03a5+uqrZffu3V63j4mJ8biv3Wx6qRWnMmXKeA1bGoK2bNlivl7uqp979U8va4IIYpfuLLscJ4ALErbXhtNf6unp6abrzf0sLg1FGzZskI4dO5pb7XpzH0uj2+s11LQSpRUPb06fPm0Wp8zMTHOr1yfTxdu14TQ4uIeHQKdU5zEUVOPGjc2iobNy5cryzjvvmH3l3p+3++7rdNyRVvByH8PAgQNNe3/wwQfy97//XW699VZp1qyZxzbffvut6Q70dvy6Tr9OIK4N5/ze5v4eIwDtGYTrKvokRN4LvDf9i/aMnLbM9vG4wjYsaVBS5cuX91iv952P6W25cuU8HtfxMnpGl3MbbyZNmmQqXbmtWrXKjKnKvT89O0zHQWlXolPBTry/cL///nuBtv/iiy/MGWgaXLQqpNWfo0ePyuWXX27+r+OZnCFR/6+vzXnfuU7fhM51N910kyxcuNBjm5UrV8q8efNMu2m33yOPPCJdunSRzz77zDUubd++fXLgwAETct2f66RfV7v4tPs0UNMLuA9cR4Dac+FCCUnLl0so4b3pX7Rn+Ldllo9DPIIalnRg7+TJky230a6yatWqSSjRwchaEXHSX+JJSUnSsmVLM1DcnY6P2r9/vxkY7T5mJ8fHWawvlFZdNChdfPHFBbrorI452rRpkxmAra/viiuuMGOKdJ4kHdulIdD5WvX/etaa+2vXddo151ynZ9XpAHAdOK7deRq8+vXrZ9bdcMMNrhCqoUenINCuUKVfS6cPqFmzptfj1PbVMU033nij1zFR/qThTz/wejy5ux1RcLSn/9CW/kV7Rk5bZnr5IzzkwtJjjz1m5uyxUqVKlfPat1Zz1OHDh80vfie9r11Czm3cByErrU7oGBnn872JjY01S276Rsj9ZtBLe2hI0a4mXQLN2XXlPAZfXXPNNaby442e8u9OpxXI7d133/W4r9Wpvn37mnFkGsDcK3xO2qZa0XKvGum2CxYsyPPYdb2+Nm9tX1gC+bUiAe3pP7Slf9Ge4d+WMT4eU1DDkg7aLayBuzq+RgOPnr7uDEeaIHUskvOMOh2Lc/z4cdOtVL9+fbNuzZo1JmBotw/868knn5QXXnjBtK8vwU274IYNGybXX399QI4PAABbj1nSX5xa8dFbrdZs27bNrK9atapr7h/trtOuHB2YrdWG/v37y/jx483p6BqeRowYYebscc4+rRd1bd26tfTo0cNML6DlQq1+6ODv3HMC4cLpOCQNP77S760uAAAEk23Ckk4u6d79U69ePXP78ccfm8ttqJ07d0pGRoZrGx37opfn0HmTtIKkUwPoVAHuY1vmz59vApLOKaTVDh2T45xRGgAAwDZhSa9yn9+V7nNfikOrS3rZDV3yome+6ZgYAAAAW09KaXd5XVMNF4Z2BQAUNsJSIXNOlOg+xxL8x9muhT0hJQAgctmmG86udL4hnahS5xXSUxQDPX2AnnmmgULnIwrG1AWF/dq0XbV9c198FwAAf+E3TCHTcVM6z5NefmXv3r1B6abSGa514saCTEppFxoAdVbxcHxtAIDQQFgKAJ3dWqcvCEZXnE6HoLNi6wzXoTghmD/aNtwqZgCA0EJYChD9hV7Yl+PwRsfy6Kzk+rXDMSwBAFDY+JMcAADAAmEJAADAAmEJAADAAmOW/Dgxol6oN9ToAO+srCxzbIxZujC0pX/Rnv5DW/oX7Rk5bZn51+/t/CY4Jiz5we+//25uk5KSgn0oAADgPH6PJyQk5Pl4lIPrRfhlcsSDBw/KxRdfHHLz/Whq1hC3f/9+KVmyZLAPx9ZoS/+iPf2HtvQv2jNy2tLhcJigVLFiRctpaKgs+YE2cKVKlSSU6Zs0FN+odkRb+hft6T+0pX/RnpHRlgkWFSUnBngDAABYICwBAABYICyFudjYWBk1apS5xYWhLf2L9vQf2tK/aE//iQ2TtmSANwAAgAUqSwAAABYISwAAABYISwAAABYISwAAABYIS2Fs1qxZkpycLMWLF5dGjRrJpk2bgn1ItjRp0iT529/+ZmZoL1eunLRr10527twZ7MMKC0899ZSZ9b5///7BPhTbOnDggNx///1y6aWXSlxcnNSqVUu++OKLYB+W7Zw9e1ZGjBghlStXNu145ZVXyrhx4/K9Zhj+65NPPpHbb7/dzIStn+mlS5eKO23HkSNHSoUKFUz7tmjRQn744QexC8JSmFq8eLEMHDjQnLK5detWqVOnjrRq1UqOHDkS7EOznXXr1kmfPn3k888/l7S0NHNhyJYtW8rJkyeDfWi2tnnzZpkzZ47Url072IdiW7/99ptcf/315gKlH374oXz33XfyzDPPSKlSpYJ9aLYzefJkefHFF+X555+XHTt2mPtTpkyRmTNnBvvQbOHkyZPm94z+ke6NtuWMGTNk9uzZsnHjRilRooT5nfTHH3+ILejUAQg/DRs2dPTp08d1/+zZs46KFSs6Jk2aFNTjCgdHjhzRPzUd69atC/ah2Nbvv//uuOqqqxxpaWmOm266ydGvX79gH5ItPfHEE46mTZsG+zDCQps2bRzdu3f3WHfXXXc5OnXqFLRjsisRcSxZssR1Pycnx5GYmOh4+umnXeuOHz/uiI2NdSxcuNBhB1SWwtCZM2dky5Ytpszpfv06vb9hw4agHls4yMjIMLelS5cO9qHYllbq2rRp4/EeRcG999570qBBA2nfvr3pIq5Xr57MnTs32IdlS02aNJHVq1fLf/7zH3P/q6++kk8//VRuvfXWYB+a7e3evVvS09M9Pu96PTYdHmKX30lcSDcM/fLLL6b/vXz58h7r9f73338ftOMKBzk5OWZ8jXZ91KxZM9iHY0uLFi0yXcPaDYcL89NPP5muI+1yHzZsmGnTRx99VIoVKyZdunQJ9uHZypAhQyQzM1OqVasm0dHR5mfohAkTpFOnTsE+NNtLT083t95+JzkfC3WEJaCAFZFvv/3W/MWJgtu/f7/069fPjP3SEw9w4eFdK0sTJ04097WypO9PHRdCWCqYN998U+bPny8LFiyQa665RrZt22b+MNIBy7Ql6IYLQ2XKlDF/GR0+fNhjvd5PTEwM2nHZXd++feX999+Xjz/+WCpVqhTsw7El7R7WkwyuvfZaKVq0qFl0AL0O/NT/61/z8J2eWVSjRg2PddWrV5d9+/YF7ZjsatCgQaa61LFjR3NG4QMPPCADBgwwZ8Piwjh/79j5dxJhKQxpCb5+/fqm/939L1C937hx46Aemx3peEUNSkuWLJE1a9aYU4txfpo3by7ffPON+avduWhlRLs69P8a8uE77Q7OPY2Fjrm54oorgnZMdpWVlWXGdrrT96P+7MSF0Z+ZGorcfydpl6eeFWeX30l0w4UpHcOgpWP9RdSwYUOZPn26ObWzW7duwT40W3a9aWn+3XffNXMtOfvYdYCizhcC32n75R7rpacQ6xxBjAErOK186MBk7Ya75557zFxqL730kllQMDpHkI5Ruvzyy0033JdffinTpk2T7t27B/vQbOHEiROya9cuj0Hd+geQngijbapdmuPHj5errrrKhCed00q7OHXeOlsI9ul4KDwzZ850XH755Y5ixYqZqQQ+//zzYB+SLenHxNsyb968YB9aWGDqgAuzbNkyR82aNc1p2NWqVXO89NJLwT4kW8rMzDTvQ/2ZWbx4cUeVKlUcTz75pOP06dPBPjRb+Pjjj73+nOzSpYtr+oARI0Y4ypcvb96rzZs3d+zcudNhF1H6T7ADGwAAQKhizBIAAIAFwhIAAIAFwhIAAIAFwhIAAIAFwhIAAIAFwhIAAIAFwhIAAIAFwhIAAIAFwhIAuNGL+eolRO666y6P9RkZGZKUlCRPPvlk0I4NQHAwgzcA5KIXo61bt67MnTvXXORXde7cWb766ivZvHmzuVg1gMhBWAIAL2bMmCGjR4+W7du3mwvUtm/f3gSlOnXqBPvQAAQYYQkAvNAfjc2aNZPo6Gj55ptv5JFHHpHhw4cH+7AABAFhCQDy8P3330v16tWlVq1asnXrVilatGiwDwlAEDDAGwDykJqaKvHx8bJ79275+eefg304AIKEyhIAeLF+/Xq56aabZNWqVTJ+/Hiz7qOPPpKoqKhgHxqAAKOyBAC5ZGVlSdeuXaV3795yyy23yCuvvGIGec+ePTvYhwYgCKgsAUAu/fr1k+XLl5upArQbTs2ZM0cef/xxM9g7OTk52IcIIIAISwDgZt26ddK8eXNZu3atNG3a1OOxVq1ayZ9//kl3HBBhCEsAAAAWGLMEAABggbAEAABggbAEAABggbAEAABggbAEAABggbAEAABggbAEAABggbAEAABggbAEAABggbAEAABggbAEAABggbAEAAAgefs/TAeNCUsa0oAAAAAASUVORK5CYII=",
|
||
"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.bar(x, np.sin(x), label='sin(x)', color='red')\n",
|
||
"#plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"Мультиграфик\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 36,
|
||
"id": "b80643f9-dba3-45d2-a3ba-d13579fda896",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"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.scatter(x, np.sin(x), label='sin(x)', color='red')\n",
|
||
"#plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"Мультиграфик\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 38,
|
||
"id": "bd42a32b-4bfd-4acc-9974-1b8bd4c55dcc",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"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.hist(np.sin(x), bins=30, label='sin(x)', color='red', edgecolor='black')\n",
|
||
"#plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"Мультиграфик\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 39,
|
||
"id": "8f6279a5-850e-41ef-9920-75b3c9083302",
|
||
"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": "code",
|
||
"execution_count": 41,
|
||
"id": "02e3167e-9694-4932-b7ae-3cf2498d2dde",
|
||
"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\"] = [1, 2, 6, 11] # догадайтесь откуда df и её содержимое взялось\n",
|
||
"sns.histplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 42,
|
||
"id": "fda61745-bc9b-4112-8ef3-9c4fac2f0751",
|
||
"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\"] = [1, 2, 6, 11] # догадайтесь откуда df и её содержимое взялось\n",
|
||
"sns.scatterplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 43,
|
||
"id": "2eac5f2b-f14c-4f51-8de9-9808b7950e70",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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YwctWtOK4in300UeSnJysC5pVzc727dtlxIgRMnnyZElKSipxvgpKTz31lEybNu2Wnuf8+fPSpEkT3a6r0SM1AqQ2OxXKwsLCJDc3VwIDA2/z1QEAgKqkPr9VHXF5Pr8tHQFS4UeNAiUmJur9qKgoOXjwoB6RKR6AvvnmG9m9e7csXrz4lp+nTp060rx5c8nJyXF53M/PT28AAMAMltYAXb58Wby9nbugpsIKCwtLnDtr1ixp27attG7d+paf5+LFi7Jv3z4JCQn5Sf0FAACewdIA1KVLF13zowqbDxw4IEuXLtXTVN27dy8xpLVkyRIZNGiQy3ZiY2MlIyPDsT9q1ChZu3atblOtNFPtqWDVu3fvSn9NAADA/Vk6BaZqedSNEIcOHSqnTp3Sq7YGDx4sY8eOLVErpEqVSgswanTnzJkzjv0jR47oc8+ePSt33nmntG/fXjZu3Kh/BgAAsLQI2hOKqAAAQPX7/Oa7wAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcW7rqzDUF5h6eXmVerygoOCn9AkAAMD9ApD60lIAAACjAlBCQoLT/qeffirbt2+X+++/X3r16lVRfQMAAHDPGqCJEyfqb15fsWKFDBw4UMaPH18xPQMAAHDXADR37lz529/+JtnZ2bJ8+XKZPXt2xfQMAADAXQPQsWPH5NFHH9U/qz+PHj1aEf0CAABw3wCkVnz5+v7/UiIfHx8pLCysiH4BAAC4VxH0Aw884FgGf+XKFenSpYvUrFlTbDZbRfcPAADAPQJQt27dSl0RVvQYAACAO/KyMWxTQl5engQFBUlubq4EBgZa3R0AAFDBn9++t/sEZSE0AAAAd3ZbAahOnTouvwpDDSapx/kqDAAA4HEBSPnkk0+kbt26FdsbAAAAdw5Ajz32mDRo0KBiewMAAODOAeiHH36Qs2fPSkBAgAQHB+tl8AAAAB59I8TY2Fhp2bKlNGvWTIegqKgo+fOf/1yxvQMAAHCXEaD9+/frgufr16/rFWHq6zDUd4GlpKTIjRs3JDk5ueJ7CgAA4I73AZo3b5788Y9/lL1790p1xn2AAACofir9PkClSUxM1NNiAAAA7qzCb4R49913/5T+AAAAVDpuhAgAAIzDjRABAIBxuBEiAAAwDjdCBAAAxrH0RoiqVkjdO0i14e/vLxEREZKamqpriez69eun64qKbk8//fRN254+fbo0bdpUatWqJdHR0fo+RQAAAJbfCHHixIkyY8YMmTt3rg5Tmzdvlv79++s1/MOGDXOcpwLP7NmzHft+fn5ltrt48WIZOXKkzJw5U4efKVOmSOfOnWX37t1M2wEAAGtvhPjMM89Iw4YNZdasWY7HevTooUeD5s+f7xgBOn/+vCxbtqzc/VCh5+GHH5aMjAy9X1hYKGFhYfLKK6/I6NGjb3o9N0IEAKD6uZXP79ueAivtRohq9KW8YmJiJDMzU/bs2aP3d+zYIVlZWRIXF+d03po1a/TITYsWLWTIkCG69qg0165dky1btkjHjh0dj3l7e+v9DRs2uLwmPz9fv2lFNwAA4Lkq9E7QNWrUkAcffLDc56vRGBU2IiMjxcfHR9cEpaWlSZ8+fZymv5599lldJ7Rv3z554403dEBSYUZdU9yZM2d0O2pkqSi1/+OPP7rsR3p6uowfP/6WXisAADAsAKmAoQqeP/74Yzl06JAedSnqf//7X7naUdcvWLBAFi5cqGuAtm/fLiNGjJDQ0FBJSkpyjCrZqULrVq1a6WJpNSqkCrErwpgxY3TNkJ0KZWrKDAAAeKbbmgJToyWTJ0+W559/Xs+zqfCgRmnUVNObb75Z7nZUsbQaBVIhR4WbF198UX73u9/pEZnShIeHS/369SUnJ8flcXVMjQydPHnS6XG1r5bru6KKqtVcYdENAAB4rtsKQGrU5oMPPpBXX31VfH19pXfv3vK3v/1Nxo4dKxs3bix3O5cvX9ahqSgVXlTRcmmOHDmia4BCQkJcHlf3I2rbtq2uLbJT7an9du3albtvAADAc91WADpx4oQesVHuuOMOPQpkX9X15ZdflrudLl266Jofdc2BAwdk6dKlemSpe/fu+vjFixf1KJEKVeq4CjEJCQn6C1fVsnY7NRVmX/GlqBEpFdDU8vpdu3bpwulLly7pJfYAAAC3VQPUqFEjOX78uDRu3FjX4/zrX//Sxc+bNm266T16ipo2bZq+d9DQoUPl1KlTuvZn8ODBeiTJPhr03Xff6SCjlsKr4506ddI3Syz6PKo4WhU/26mpudOnT+t2VFhr06aNrFixokRhNAAAMNNt3QdI1e2oOhm1Ikste3/hhRf0XZdVQbSq4Xn77belOuM+QAAAePbnd4XcCFFNUa1fv17uuecePa1V3RGAAACofqr0Rohq2uvzzz/XU1jqSQEAADyqBkjV/Gzbtk3q1aun91euXCnx8fG6Hket5nr33Xdl0aJF0rNnz8rqLwAAwE92SyNAagm6ugmi3TvvvKOXwKsC5XPnzukC5kmTJv30XgEAAFSinzQFppaYqy8YVau11AiQ+rm8X4QKAABQLQOQGvmpW7euY//nP/+5XLhwoSL6BQAA4B4ByMvLS2/FHwMAAPDYImi1Yr5fv36OmxBevXpVfvOb30hAQIDez8/Pr5xeAgAAWBWA7N/QbqdugFhc3759f3qvAAAA3CUAzZ49u/J6AgAAUEV+8o0QAQAAqhsCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEsDUAFBQWSkpIizZo1E39/f4mIiJDU1FSx2Wz6+PXr1+X111+XqKgoCQgIkNDQUOnbt68cO3aszHbffPNN8fLyctoiIyOr6FUBAAB352vlk0+cOFFmzJghc+fOlZYtW8rmzZulf//+EhQUJMOGDZPLly/L1q1bdUhq3bq1nDt3ToYPHy5du3bV55ZFtbdq1SrHvq+vpS8VAAC4EUtTwfr16yUhIUHi4+P1ftOmTWXRokWSnZ2t91UQWrlypdM1GRkZ8sgjj8ihQ4ekcePGpbatAk9wcHAlvwIAAFAdWToFFhMTI5mZmbJnzx69v2PHDsnKypK4uLhSr8nNzdVTWnXq1Cmz7b179+ops/DwcOnTp48OTKXJz8+XvLw8pw0AAHguS0eARo8ercOGqs/x8fHRNUFpaWk6sLhy9epVXRPUu3dvCQwMLLXd6OhomTNnjrRo0UKOHz8u48ePl8cff1x27twptWvXLnF+enq6PgcAAJjBy2avOLbARx99JMnJyfLOO+/omp3t27fLiBEjZPLkyZKUlOR0riqI7tGjhxw5ckTWrFlTZgAq7vz589KkSRPd7sCBA12OAKnNToWysLAwPdp0K88DAACsoz6/VflMeT6/LR0BUuFHjQIlJibqfbXa6+DBg3pEpmgAUuGnV69e+tjXX399y6FETZc1b95ccnJyXB738/PTGwAAMIOlAUit8vL2di5DUlNhhYWFJcKPqulZvXq11KtX75af5+LFi7Jv3z558cUXxR106Dnc6i7AA61b8p7VXYAH4vcVPPX3laVF0F26dNE1P19++aUcOHBAli5dqqepunfv7gg/zz33nF7yvmDBAl0jdOLECb1du3bN0U5sbKxeHWY3atQoWbt2rW5TrTRT7algpWqHAAAALB0BmjZtmr7Hz9ChQ+XUqVN61dbgwYNl7Nix+vjRo0fls88+0z+3adPG6Vo1GvTEE0/on9XozpkzZxzHVJ2QCjtnz56VO++8U9q3by8bN27UPwMAAFgagNSKrClTpujNFXVfoPLUaKuRnuLF1QAAAKXhu8AAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDiWBqCCggJJSUmRZs2aib+/v0REREhqaqrYbDbHOernsWPHSkhIiD6nY8eOsnfv3pu2PX36dGnatKnUqlVLoqOjJTs7u5JfDQAAqC4sDUATJ06UGTNmSEZGhuzatUvvT5o0SaZNm+Y4R+1PnTpVZs6cKd9++60EBARI586d5erVq6W2u3jxYhk5cqSMGzdOtm7dKq1bt9bXnDp1qopeGQAAcGeWBqD169dLQkKCxMfH69Ga5557Tjp16uQYrVGjP1OmTJE//OEP+rxWrVrJhx9+KMeOHZNly5aV2u7kyZPl17/+tfTv31/uu+8+HZ5+9rOfyd///neX5+fn50teXp7TBgAAPJelASgmJkYyMzNlz549en/Hjh2SlZUlcXFxen///v1y4sQJPe1lFxQUpKe0NmzY4LLNa9euyZYtW5yu8fb21vulXZOenq7btW9hYWEV/EoBAIA78bXyyUePHq1HWyIjI8XHx0fXBKWlpUmfPn30cRV+lIYNGzpdp/btx4o7c+aMbsfVNT/++KPLa8aMGaOnzOxUnwhBAAB4LksD0McffywLFiyQhQsXSsuWLWX79u0yYsQICQ0NlaSkpCrrh5+fn94AAIAZLA1AycnJehQoMTFR70dFRcnBgwf1lJQKQMHBwfrxkydP6lVgdmq/TZs2LtusX7++Hk1S5xSl9u3tAQAAs1laA3T58mVdn1OUCi+FhYX6Z7U8XoUWVSdUdHpKrQZr166dyzZr1qwpbdu2dbpGtaf2S7sGAACYxdIRoC5duuian8aNG+spsG3btukVXAMGDNDHvby89JTYhAkT5J577tGBSN03SE2RdevWzdFObGysdO/eXV5++WW9r+p51AjSQw89JI888oheSXbp0iW9KgwAAMDSAKTu96MCzdChQ/U9elSwGTx4sL7xod1rr72mw8tLL70k58+fl/bt28uKFSv0DQ7t9u3bp4uf7Z5//nk5ffq0bkcVS6vpMnVN8cJoAABgJi9b0dsuwzHNppbD5+bmSmBgYIW336Hn8ApvE1i35D2ruwAPxO8rVKffV7fy+c13gQEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA41gagJo2bSpeXl4ltt/+9rdy4MABl8fUtmTJklLb7NevX4nzn3766Sp9XQAAwL35WvnkmzZtkoKCAsf+zp075amnnpKePXtKWFiYHD9+3On8999/X9555x2Ji4srs10VeGbPnu3Y9/Pzq4TeAwCA6srSAHTnnXc67b/99tsSEREhv/jFL/TITXBwsNPxpUuXSq9eveSOO+4os10VeIpfW5b8/Hy92eXl5ZX7WgAAUP24TQ3QtWvXZP78+TJgwAAdforbsmWLbN++XQYOHHjTttasWSMNGjSQFi1ayJAhQ+Ts2bNlnp+eni5BQUGOTY0+AQAAz+U2AWjZsmVy/vx5XcPjyqxZs+Tee++VmJiYm05/ffjhh5KZmSkTJ06UtWvX6imzolNtxY0ZM0Zyc3Md2+HDh3/y6wEAAO7L0imw4gFHBZXQ0NASx65cuSILFy6UlJSUm7aTmJjo+DkqKkpatWqlp9XUqFBsbGypU2bUCQEAYA63GAE6ePCgrFq1SgYNGuTy+CeffCKXL1+Wvn373nLb4eHhUr9+fcnJyamAngIAAE/gFgFIrdhSNTvx8fGljg517dq1RNF0eRw5ckTXAIWEhFRATwEAgCewPAAVFhbqAJSUlCS+viVn5NTIzbp160odHYqMjNSrw5SLFy9KcnKybNy4Ud9HSNUBJSQkyN133y2dO3eu9NcCAACqB8sDkJr6OnTokF795crf//53adSokXTq1Mnl8d27d+vCZcXHx0e+++47PVrUvHlzvWKsbdu28s0331DjAwAA3KcIWgUbm81W6vG33npLb6Upeq2/v7989dVXFd5HAADgWSwfAQIAAKhqBCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwjpfNZrNZ3Ql3k5eXJ0FBQZKbmyuBgYFWdwcAAFTw5zcjQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADj+FrdAXdks9n0n3l5eVZ3BQAAlJP9c9v+OV4WApALFy5c0H+GhYVZ3RUAAHAbn+NBQUFlnuNlK09MMkxhYaEcO3ZMateuLV5eXmI6lahVGDx8+LAEBgZa3R2PxftcNXifqwbvc9XgfXamIo0KP6GhoeLtXXaVDyNALqg3rVGjRlZ3w+2o/7n4H6zy8T5XDd7nqsH7XDV4n//PzUZ+7CiCBgAAxiEAAQAA4xCAcFN+fn4ybtw4/ScqD+9z1eB9rhq8z1WD9/n2UQQNAACMwwgQAAAwDgEIAAAYhwAEAACMQwACAADGIQDBpfT0dHn44Yf13bAbNGgg3bp1k927d1vdLY/39ttv67uPjxgxwuqueKSjR4/KCy+8IPXq1RN/f3+JioqSzZs3W90tj1JQUCApKSnSrFkz/R5HRERIampqub6bCaVbt26ddOnSRd/hWP2OWLZsmdNx9f6OHTtWQkJC9PvesWNH2bt3r2X9rQ4IQHBp7dq18tvf/lY2btwoK1eulOvXr0unTp3k0qVLVnfNY23atEn++te/SqtWrazuikc6d+6cPPbYY1KjRg355z//KT/88IP86U9/kp///OdWd82jTJw4UWbMmCEZGRmya9cuvT9p0iSZNm2a1V2r1tTv3tatW8v06dNdHlfv8dSpU2XmzJny7bffSkBAgHTu3FmuXr1a5X2tLlgGj3I5ffq0HglSwahDhw5Wd8fjXLx4UR588EH5y1/+IhMmTJA2bdrIlClTrO6WRxk9erT8+9//lm+++cbqrni0Z555Rho2bCizZs1yPNajRw89KjF//nxL++Yp1AjQ0qVL9ci8oj7G1cjQq6++KqNGjdKP5ebm6v8Oc+bMkcTERIt77J4YAUK5qP+ZlLp161rdFY+kRtvi4+P1sDUqx2effSYPPfSQ9OzZU4f5Bx54QD744AOru+VxYmJiJDMzU/bs2aP3d+zYIVlZWRIXF2d11zzW/v375cSJE06/P9T3YUVHR8uGDRss7Zs748tQcVOFhYW6JkVNH9x///1Wd8fjfPTRR7J161Y9BYbK89///ldPzYwcOVLeeOMN/X4PGzZMatasKUlJSVZ3z6NG2tQ3lEdGRoqPj4+uCUpLS5M+ffpY3TWPpcKPokZ8ilL79mMoiQCEco1O7Ny5U/8rDhXr8OHDMnz4cF1nVatWLau74/FBXo0AvfXWW3pfjQCpv9eqZoIAVHE+/vhjWbBggSxcuFBatmwp27dv1/+AUlM0vM9wJ0yBoUwvv/yyfPHFF7J69Wpp1KiR1d3xOFu2bJFTp07p+h9fX1+9qTorVcyoflb/ekbFUKtj7rvvPqfH7r33Xjl06JBlffJEycnJehRI1Z2oVXYvvvii/O53v9MrS1E5goOD9Z8nT550elzt24+hJAIQXFJFdSr8qEK7r7/+Wi9pRcWLjY2V77//Xv8r2b6pUQo1XaB+VlMIqBhqCrf4rRxUnUqTJk0s65Mnunz5snh7O3+0qL/HagQOlUP9flZBR9Ve2alpSLUarF27dpb2zZ0xBYZSp73UEPby5cv1vYDs88iqsE6t5kDFUO9t8boqtXxV3aeGequKpUYhVIGumgLr1auXZGdny/vvv683VBx1rxpV89O4cWM9BbZt2zaZPHmyDBgwwOquVfuVojk5OU6Fz+ofSWphinqv1TSjWkF6zz336ECk7sWkph3tK8XggloGDxSn/mq42mbPnm111zzeL37xC9vw4cOt7oZH+vzzz23333+/zc/PzxYZGWl7//33re6Sx8nLy9N/fxs3bmyrVauWLTw83Pb73//elp+fb3XXqrXVq1e7/J2clJSkjxcWFtpSUlJsDRs21H+/Y2Njbbt377a6226N+wABAADjUAMEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAJQqfr161fi+4hOnz6tv+ssOjpacnNzLesbAHMRgABUKRV+fvnLX+ov1f3Xv/6lv2AXAKoaAQhAlTlz5ozExsaKn5+frFy50hF+1LeFR0VFSUBAgISFhcnQoUP1t18ra9asES8vr1I3u6ysLHn88cd1sFJtDBs2TC5duuQ43rRp0xLXjho1ynF8xowZEhERITVr1pQWLVrIvHnznPquzlfnxMXF6ecIDw+XTz75xHH8wIED+hz1Dd126hu51WNTpkxxPPbjjz/KU089pV+7vR916tSp8PcaQNkIQACqxNmzZ6Vjx47i6+urw0/RD31vb2+ZOnWq/Oc//5G5c+fK119/La+99po+FhMTI8ePH9fbP/7xD/2YfV9tyr59++Tpp5+WHj16yHfffSeLFy/Wgejll1926sMf//hHp2vHjRunH1+6dKkMHz5cXn31Vdm5c6cMHjxY+vfvL6tXr3a6XgUa9Rw7duyQPn36SGJiouzatcvl6z1y5IgOPiosFTVgwAC5fv26/Pvf/9Z9KBqOAFQhq7+OHoBnS0pKsnXo0MHWpk0bW40aNWyPPvqo7caNG2Ves2TJElu9evVKPL569Wqbq19bAwcOtL300ktOj33zzTc2b29v25UrV/R+kyZNbH/+859dPl9MTIzt17/+tdNjPXv2tP3qV79y7Kvn/c1vfuN0TnR0tG3IkCH65/379+tztm3bpvf79u2r+1X8ef39/W0LFixw7M+ePdsWFBRU5vsBoOIxAgSg0q1bt04KCwv19FBOTo5MmjTJ6fiqVav01Nhdd90ltWvXlhdffFGPGF2+fLlc7asRmTlz5sgdd9zh2Dp37qyfc//+/Te9Xo3iPPbYY06Pqf3iozvt2rUrse9qBGjr1q16VCk1NbXEsWbNmulj5X1tACqHbyW1CwAOql4mMzNT6tevL3/5y1/khRdekPj4eGnVqpWunXnmmWdkyJAhkpaWJnXr1tXTVwMHDpRr167Jz372s5u2r+qF1LSVqvsprnHjxlLV1FSaqi8KCQkpcWzWrFmSlJSkg56aHrtx44bUqlWryvsImI4RIACVThU4q/Cj9OzZU5599lnp27evDjhbtmzRIzV/+tOf5NFHH5XmzZvLsWPHbqn9Bx98UH744Qe5++67S2yqqPlm7r33Xl2TU5Tav++++5we27hxY4l9dW1Rn332mezZs8epwLoo9Rq7du0qDz30kGzbtk3XJQGoeowAAahy06dP1/cBGj9+vPTq1UsXBU+bNk26dOmig8fMmTNvqb3XX39dBwtV9Dxo0CC9mkwFIlVsnZGRcdPrk5OTdT8eeOABXaj9+eefy6effqqn5opasmSJDi7t27eXBQsWSHZ2th7RKUpN76nXUtrIlSrkVtN1Kvip0akGDRrc0msFUDEYAQJQ5dQ01wcffCATJ06Uq1ev6mXw6mcVilSwSE9Pv6X21FTa2rVr9ciLWgqvgszYsWMlNDS0XNerGzW+99578u6770rLli3lr3/9q8yePVueeOIJp/NUYPvoo4/083344YeyaNGiEqNEatRJTXG5ovqnAtrChQstmZoD8H+8VCV0kX0AgAvqfj2qeLn4Xa0BVE+MAAEAAOMQgAAAgHEoggaAcqBaAPAsjAABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAGKa/wfFTpisM/Qx6QAAAABJRU5ErkJggg==",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 1000x1000 with 20 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import seaborn as sns\n",
|
||
"\n",
|
||
"df[\"Категория\"] = [1, 2, 6, 11] # догадайтесь откуда df и её содержимое взялось\n",
|
||
"sns.histplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
|
||
"sns.pairplot(df)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 48,
|
||
"id": "9ee43629-88d4-4332-a459-b416539eeb8b",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import seaborn as sns\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",
|
||
"sns.histplot(x=\"Возраст\", y=\"Баллы\", data=df)\n",
|
||
"\n",
|
||
"numeric_df = df.select_dtypes(include=['number'])\n",
|
||
"sns.heatmap(numeric_df.corr(), annot=True)\n",
|
||
"\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 51,
|
||
"id": "3d37f39d-d5d8-4a2a-b2a0-621629ece250",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"4it [00:00, 88.64it/s]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tqdm import tqdm\n",
|
||
"import time\n",
|
||
"\n",
|
||
"for i in tqdm(range(100)):\n",
|
||
" time.sleep(0.01)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 52,
|
||
"id": "f7ef7138-b839-478f-a077-a68f6da7f3b7",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"4it [00:00, 91.89it/s]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tqdm import tqdm\n",
|
||
"import time\n",
|
||
"\n",
|
||
"for i in tqdm(df.iterrows()):\n",
|
||
" time.sleep(0.01)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 53,
|
||
"id": "ce9e095f-8033-4ebf-9719-1cf7f529e59a",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Загрузка: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 92.20it/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)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "f32feeff-c86f-45d8-9049-1c93f319dde4",
|
||
"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
|
||
}
|