1329 lines
456 KiB
Plaintext
1329 lines
456 KiB
Plaintext
{
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"cells": [
|
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{
|
||
"cell_type": "markdown",
|
||
"id": "ae4f4121-843f-4dda-a7c1-1c4ab2022f07",
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"metadata": {},
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"source": [
|
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"# Часть 1. Основы работы с JupyterLab\n",
|
||
"В данном разделе мы знакомимся с Markdown-ячейками."
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||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"id": "fb2051d8-f2d5-49ae-80bf-40316c281dcd",
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||
"metadata": {},
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||
"outputs": [
|
||
{
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||
"name": "stdout",
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"output_type": "stream",
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"text": [
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"22\n"
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]
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}
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],
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"source": [
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"a=10\n",
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"b=12\n",
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"c=a+b\n",
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"print(c)"
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]
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},
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{
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"cell_type": "markdown",
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||
"id": "4a9f9dc3-e309-404b-b624-1060a8a52c1e",
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||
"metadata": {},
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||
"source": [
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"## 1. Задаем значение а\n",
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"a=10\n",
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"## 2. Задаем значение b\n",
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"b=12\n",
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"## 3. Выполняем сложение\n",
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"c=a+b\n",
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"## 4. Выводим результат\n",
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"print(c)"
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]
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},
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{
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"cell_type": "markdown",
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||
"id": "c090044e-68ed-490b-8a00-0b7c103c4b0f",
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||
"metadata": {},
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||
"source": [
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||
"# Часть 2. Работа с pandas и numpy\n",
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"В данном разделе мы знакомимся с pandas: работа с таблицами."
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]
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||
},
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||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "5f0f9420-c0f0-48d7-bac8-ebe151fec7ce",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
},
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||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"id": "9fb0933e-d4e6-447b-8ed6-2b463dc0d2ee",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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"text": [
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"Первый взгляд на данные:\n",
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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\n",
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"<class 'pandas.core.frame.DataFrame'>\n",
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"RangeIndex: 4 entries, 0 to 3\n",
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"Data columns (total 3 columns):\n",
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" # Column Non-Null Count Dtype \n",
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"--- ------ -------------- ----- \n",
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" 0 Имя 4 non-null object\n",
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" 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",
|
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"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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"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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||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "15cb5f06-16e1-4be0-94c9-0a9318db531f",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Помещаем df в последнюю строчку блока."
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||
]
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||
},
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||
{
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||
"cell_type": "code",
|
||
"execution_count": 17,
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||
"id": "af9448a3-aa24-4363-adda-19c0b486926c",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
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||
"output_type": "stream",
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||
"text": [
|
||
"Первый взгляд на данные:\n",
|
||
" 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",
|
||
"3 Галина 24 82\n",
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||
"<class 'pandas.core.frame.DataFrame'>\n",
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||
"RangeIndex: 4 entries, 0 to 3\n",
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||
"Data columns (total 3 columns):\n",
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||
" # Column Non-Null Count Dtype \n",
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||
"--- ------ -------------- ----- \n",
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||
" 0 Имя 4 non-null object\n",
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||
" 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",
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"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",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"dtype: int64\n"
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||
]
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}
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],
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"source": [
|
||
"import pandas as pd\n",
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||
"\n",
|
||
"# 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",
|
||
"}\n",
|
||
"\n",
|
||
"print(\"Первый взгляд на данные:\")\n",
|
||
"print(df.head())\n",
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||
"print(df.info())\n",
|
||
"print(df.describe())\n",
|
||
"print(df.isnull().sum())\n",
|
||
"df = pd.DataFrame(data)"
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||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "ed441692-0e75-4259-8a50-c72893b6976e",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Добавляем новый столбец с вычисляемыми значениями"
|
||
]
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||
},
|
||
{
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||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"id": "e6546d99-b0d4-43a4-8cf4-dc5d14f795f7",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первый взгляд на данные:\n",
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||
" 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",
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||
" 1 Возраст 4 non-null int64 \n",
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||
" 2 Баллы 4 non-null int64 \n",
|
||
" 3 Новый столбец 4 non-null float64\n",
|
||
"dtypes: float64(1), int64(2), object(1)\n",
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||
"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"
|
||
]
|
||
}
|
||
],
|
||
"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",
|
||
"df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\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": "fc1feb69-20b1-4293-8386-0128a6e83465",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Группируем данные"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"id": "6f54aa19-722a-4aa7-8d19-02fd5a3623e3",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Первый взгляд на данные:\n",
|
||
" Имя Возраст Баллы Группа\n",
|
||
"0 Анна 21 89 A\n",
|
||
"1 Борис 22 76 B\n",
|
||
"2 Виктор 23 95 A\n",
|
||
"3 Галина 24 82 B\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 Группа 4 non-null object\n",
|
||
"dtypes: int64(2), object(2)\n",
|
||
"memory usage: 260.0+ 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",
|
||
"Количество пропущенных значений:\n",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"Группа 0\n",
|
||
"dtype: int64\n",
|
||
"\n",
|
||
"Группировка по группам с вычислением статистики:\n",
|
||
" Возраст Баллы \n",
|
||
" mean mean max min\n",
|
||
"Группа \n",
|
||
"A 22.0 92.0 95 89\n",
|
||
"B 23.0 79.0 82 76\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",
|
||
" \"Группа\": [\"A\", \"B\", \"A\", \"B\"]\n",
|
||
"}\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(\"Количество пропущенных значений:\")\n",
|
||
"print(df.isnull().sum()) \n",
|
||
"\n",
|
||
"grouped_df = df.groupby(\"Группа\").agg({\n",
|
||
" \"Возраст\": \"mean\", \n",
|
||
" \"Баллы\": [\"mean\", \"max\", \"min\"] \n",
|
||
"})\n",
|
||
"\n",
|
||
"# Вывод результата\n",
|
||
"print(\"\\nГруппировка по группам с вычислением статистики:\")\n",
|
||
"print(grouped_df)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "4902cd48-d462-466e-b7f0-44ecb7da53e9",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Фильтруем записи по условиям"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"id": "a4973dfc-b152-46a2-a7ef-0fa52e3ce64a",
|
||
"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",
|
||
"Количество пропущенных значений:\n",
|
||
"Имя 0\n",
|
||
"Возраст 0\n",
|
||
"Баллы 0\n",
|
||
"dtype: int64\n",
|
||
"\n",
|
||
"Записи, где возраст больше 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",
|
||
"data = {\n",
|
||
" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
|
||
" \"Возраст\": [21, 22, 23, 24],\n",
|
||
" \"Баллы\": [89, 76, 95, 82]\n",
|
||
"}\n",
|
||
"\n",
|
||
"df = pd.DataFrame(data)\n",
|
||
"\n",
|
||
"print(\"Первый взгляд на данные:\")\n",
|
||
"print(df.head()) \n",
|
||
"print(df.info()) \n",
|
||
"print(df.describe()) \n",
|
||
"print(\"Количество пропущенных значений:\")\n",
|
||
"print(df.isnull().sum()) \n",
|
||
"\n",
|
||
"filtered_df = df[df[\"Возраст\"] > 21]\n",
|
||
"\n",
|
||
"print(\"\\nЗаписи, где возраст больше 21 года:\")\n",
|
||
"print(filtered_df)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "63d73ad2-b89f-4100-a197-852dec09ff9a",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Работа с numpy\n",
|
||
"В данном разделе мы знакомимся с numpy: массивы и вычисления."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"id": "e5bf3999-41fd-491a-8d3a-828ac52e5981",
|
||
"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": "288363dd-6df3-420d-bbd5-26a44ba13d52",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Создаем двумерный массив"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"id": "f514ea57-0722-4a1c-a254-b139baf7fa03",
|
||
"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",
|
||
"\n",
|
||
"Двумерный массив:\n",
|
||
"[[1 2]\n",
|
||
" [3 4]]\n",
|
||
"Сумма всех элементов: 10\n",
|
||
"Среднее значение: 2.5\n",
|
||
"Транспонированный массив:\n",
|
||
"[[1 3]\n",
|
||
" [2 4]]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"\n",
|
||
"arr = np.array([1, 2, 3, 4, 5])\n",
|
||
"\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",
|
||
"arr_2d = np.array([[1, 2], [3, 4]])\n",
|
||
"\n",
|
||
"print(\"\\nДвумерный массив:\")\n",
|
||
"print(arr_2d)\n",
|
||
"\n",
|
||
"print(\"Сумма всех элементов:\", np.sum(arr_2d))\n",
|
||
"print(\"Среднее значение:\", np.mean(arr_2d))\n",
|
||
"print(\"Транспонированный массив:\")\n",
|
||
"print(arr_2d.T)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "edea44c6-d386-4820-8c21-1dc0b58323cc",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Используем np.linspace(), np.random.randn(), np.dot()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"id": "270e2e9b-0191-4c69-9248-f79d15dea793",
|
||
"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",
|
||
"\n",
|
||
"Линейно распределенные значения (linspace):\n",
|
||
"[ 0. 1.11111111 2.22222222 3.33333333 4.44444444 5.55555556\n",
|
||
" 6.66666667 7.77777778 8.88888889 10. ]\n",
|
||
"\n",
|
||
"Случайная матрица (random.randn):\n",
|
||
"[[ 0.96886066 1.36224633 -0.392623 ]\n",
|
||
" [ 0.51813793 0.0839053 0.41006598]\n",
|
||
" [ 0.35214781 -0.32904084 1.1035009 ]]\n",
|
||
"\n",
|
||
"Скалярное произведение (dot product):\n",
|
||
"[[19 22]\n",
|
||
" [43 50]]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"\n",
|
||
"arr = np.array([1, 2, 3, 4, 5])\n",
|
||
"\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",
|
||
"linspace_arr = np.linspace(0, 10, 10)\n",
|
||
"print(\"\\nЛинейно распределенные значения (linspace):\")\n",
|
||
"print(linspace_arr)\n",
|
||
"\n",
|
||
"random_arr = np.random.randn(3, 3) \n",
|
||
"print(\"\\nСлучайная матрица (random.randn):\")\n",
|
||
"print(random_arr)\n",
|
||
"\n",
|
||
"matrix_a = np.array([[1, 2], [3, 4]])\n",
|
||
"matrix_b = np.array([[5, 6], [7, 8]])\n",
|
||
"\n",
|
||
"dot_product = np.dot(matrix_a, matrix_b) \n",
|
||
"print(\"\\nСкалярное произведение (dot product):\")\n",
|
||
"print(dot_product)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "414d23e1-4ca1-4ed1-bd1e-081f464bd8b0",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Часть 4. Визуализация данных"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "bfb21078-8929-4bbe-9b65-20f3b076b710",
|
||
"metadata": {},
|
||
"source": [
|
||
"# matplotlib: построение графиков"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"id": "782a0957-04ed-4f28-9683-5c64e7b0862d",
|
||
"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": "markdown",
|
||
"id": "68e11000-ce49-4694-b9f4-1496fd456c02",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Изменяем цвет"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"id": "8f58829b-dfd1-49d2-8594-b20373f4f6a9",
|
||
"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": "markdown",
|
||
"id": "f4ee8f38-b3b7-4864-8b4f-3b47bc0f4552",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Добавляем несколько графиков"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"id": "ff64b1d2-9106-4a84-8c95-b9f22121ce05",
|
||
"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",
|
||
"\n",
|
||
"y_sin = np.sin(x)\n",
|
||
"y_cos = np.cos(x)\n",
|
||
"\n",
|
||
"plt.plot(x, y_sin, label='sin(x)', color='red') \n",
|
||
"plt.plot(x, y_cos, label='cos(x)', color='blue') \n",
|
||
"\n",
|
||
"plt.xlabel(\"X\") \n",
|
||
"plt.ylabel(\"Y\") \n",
|
||
"plt.title(\"Графики синуса и косинуса\") \n",
|
||
"plt.legend() \n",
|
||
"plt.grid() \n",
|
||
"plt.show() "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "0e303937-c675-48ca-b883-2a13195a6f96",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Используем bar, scatter, hist."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"id": "9d591384-1234-4768-88ab-0964f790c3f9",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 600x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 600x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 600x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"x = np.linspace(0, 10, 10) \n",
|
||
"y = np.sin(x)\n",
|
||
"\n",
|
||
"plt.figure(figsize=(6, 4))\n",
|
||
"plt.bar(x, y, color='blue', alpha=0.7, label='Bar chart')\n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"Bar Chart - sin(x)\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"plt.figure(figsize=(6, 4))\n",
|
||
"plt.scatter(x, y, color='red', label='Scatter plot')\n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"Scatter Plot - sin(x)\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"random_data = np.random.randn(1000) \n",
|
||
"\n",
|
||
"plt.figure(figsize=(6, 4))\n",
|
||
"plt.hist(random_data, bins=30, color='green', alpha=0.7, edgecolor='black', label='Histogram')\n",
|
||
"plt.xlabel(\"Значения\")\n",
|
||
"plt.ylabel(\"Частота\")\n",
|
||
"plt.title(\"Histogram - Random Data\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "ee197d41-534b-4198-8c46-93d3e5eed046",
|
||
"metadata": {},
|
||
"source": [
|
||
"# seaborn: работа с графиками данных"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"id": "10e9769c-8723-447a-bd77-d82c7cdfde31",
|
||
"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": "944d1f67-a93e-42b4-afce-4e719dc86abd",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Строим histplot, scatterplot."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"id": "f6494884-f854-4631-8e9c-9c5a1b1a49c4",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 600x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 600x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 600x400 with 1 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",
|
||
" \"Категория\": [\"A\", \"B\", \"A\", \"B\"]\n",
|
||
"}\n",
|
||
"df = pd.DataFrame(data)\n",
|
||
"\n",
|
||
"plt.figure(figsize=(6, 4))\n",
|
||
"sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
|
||
"plt.title(\"Boxplot - распределение баллов по категориям\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"plt.figure(figsize=(6, 4))\n",
|
||
"sns.histplot(df[\"Баллы\"], bins=5, kde=True, color=\"blue\")\n",
|
||
"plt.xlabel(\"Баллы\")\n",
|
||
"plt.ylabel(\"Частота\")\n",
|
||
"plt.title(\"Histplot - распределение баллов\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"plt.figure(figsize=(6, 4))\n",
|
||
"sns.scatterplot(x=\"Возраст\", y=\"Баллы\", hue=\"Категория\", data=df, palette=\"coolwarm\", s=100)\n",
|
||
"plt.xlabel(\"Возраст\")\n",
|
||
"plt.ylabel(\"Баллы\")\n",
|
||
"plt.title(\"Scatterplot - зависимость баллов от возраста\")\n",
|
||
"plt.legend(title=\"Категория\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "0eb28611-6bcd-4c56-866a-0d7ad49a643d",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Добавляем sns.pairplot(df), sns.heatmap(df.corr(), annot=True)."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 36,
|
||
"id": "ebde9c7e-f26b-4a13-a8ee-47024093aafc",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"100%|████████████████████████████████████████| 100/100 [00:01<00:00, 96.42it/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": "code",
|
||
"execution_count": 38,
|
||
"id": "faf79c28-6caa-4eb6-910f-56ee5cf22e2b",
|
||
"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 500x500 with 6 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 800x600 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import seaborn as sns\n",
|
||
"\n",
|
||
"# Создаём DataFrame \n",
|
||
"df = pd.DataFrame({\n",
|
||
" \"Категория\": [\"A\", \"B\", \"A\", \"B\"],\n",
|
||
" \"Баллы\": [23, 45, 12, 36],\n",
|
||
" \"Другая_Колонка\": [1, 2, 3, 4] # Дополнительный числовой признак\n",
|
||
"})\n",
|
||
"\n",
|
||
"# Визуализация с помощью boxplot\n",
|
||
"sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
|
||
"plt.title('График')\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Визуализация парных графиков\n",
|
||
"sns.pairplot(df)\n",
|
||
"plt.title('Парные графики')\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Убираем категориальные переменные для корреляции\n",
|
||
"df_numerical = df.select_dtypes(include='number') # Оставляем только числовые данные\n",
|
||
"\n",
|
||
"# Визуализация тепловой карты корреляции\n",
|
||
"plt.figure(figsize=(8, 6))\n",
|
||
"sns.heatmap(df_numerical.corr(), annot=True, cmap='coolwarm', fmt='.2f')\n",
|
||
"plt.title('Тепловая карта корреляции')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "b0cbd359-c37c-4a99-b72e-0c71d552f0e2",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Часть 5. Прогресс-бар с tqdm"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "be5f3a0b-311f-4a11-9eb6-3f8febaf1b31",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Использование tqdm для обработки данных"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 39,
|
||
"id": "5f2a633a-4816-43fb-ac87-56e22d1d100e",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 25%|██████▊ | 1/4 [00:00<00:01, 2.00it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обрабатывается: Анна, возраст: 21, баллы: 89\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 50%|█████████████▌ | 2/4 [00:01<00:01, 2.00it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обрабатывается: Борис, возраст: 22, баллы: 76\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 75%|████████████████████▎ | 3/4 [00:01<00:00, 2.00it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обрабатывается: Виктор, возраст: 23, баллы: 95\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 100%|███████████████████████████| 4/4 [00:02<00:00, 2.00it/s]"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обрабатывается: Галина, возраст: 24, баллы: 82\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tqdm import tqdm\n",
|
||
"import pandas as pd\n",
|
||
"import time\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",
|
||
"# Обработка данных с tqdm(iterrows())\n",
|
||
"for index, row in tqdm(df.iterrows(), total=len(df), desc=\"Обработка строк\"):\n",
|
||
" time.sleep(0.5) # Симуляция обработки строки\n",
|
||
" print(f\"Обрабатывается: {row['Имя']}, возраст: {row['Возраст']}, баллы: {row['Баллы']}\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "87fced83-7eea-4b51-97b9-48b583e5da9e",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Добавление кастомной стилизации"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 41,
|
||
"id": "96f57cf0-85a3-4172-b197-6ec98bc7ad3e",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"🔄 Загрузка: 100%|\u001b[32m████████████████████████████\u001b[0m| 100/100 [00:01<00:00, 96.50it/s]\u001b[0m\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tqdm import tqdm\n",
|
||
"import time\n",
|
||
"\n",
|
||
"# Кастомный прогресс-бар с описанием\n",
|
||
"for i in tqdm(range(100), desc=\"🔄 Загрузка\", ascii=\" ░█\", ncols=80, colour=\"green\"):\n",
|
||
" time.sleep(0.01) # Симуляция долгого процесса"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 51,
|
||
"id": "690a2810-affa-484a-81c3-66402565c89d",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 418 entries, 0 to 417\n",
|
||
"Data columns (total 12 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 PassengerId 418 non-null int64 \n",
|
||
" 1 Survived 418 non-null int64 \n",
|
||
" 2 Pclass 418 non-null int64 \n",
|
||
" 3 Name 418 non-null object \n",
|
||
" 4 Sex 418 non-null object \n",
|
||
" 5 Age 332 non-null float64\n",
|
||
" 6 SibSp 418 non-null int64 \n",
|
||
" 7 Parch 418 non-null int64 \n",
|
||
" 8 Ticket 418 non-null object \n",
|
||
" 9 Fare 417 non-null float64\n",
|
||
" 10 Cabin 91 non-null object \n",
|
||
" 11 Embarked 418 non-null object \n",
|
||
"dtypes: float64(2), int64(5), object(5)\n",
|
||
"memory usage: 39.3+ KB\n",
|
||
"None\n",
|
||
" PassengerId Survived Pclass Age SibSp \\\n",
|
||
"count 418.000000 418.000000 418.000000 332.000000 418.000000 \n",
|
||
"mean 1100.500000 0.363636 2.265550 30.272590 0.447368 \n",
|
||
"std 120.810458 0.481622 0.841838 14.181209 0.896760 \n",
|
||
"min 892.000000 0.000000 1.000000 0.170000 0.000000 \n",
|
||
"25% 996.250000 0.000000 1.000000 21.000000 0.000000 \n",
|
||
"50% 1100.500000 0.000000 3.000000 27.000000 0.000000 \n",
|
||
"75% 1204.750000 1.000000 3.000000 39.000000 1.000000 \n",
|
||
"max 1309.000000 1.000000 3.000000 76.000000 8.000000 \n",
|
||
"\n",
|
||
" Parch Fare \n",
|
||
"count 418.000000 417.000000 \n",
|
||
"mean 0.392344 35.627188 \n",
|
||
"std 0.981429 55.907576 \n",
|
||
"min 0.000000 0.000000 \n",
|
||
"25% 0.000000 7.895800 \n",
|
||
"50% 0.000000 14.454200 \n",
|
||
"75% 0.000000 31.500000 \n",
|
||
"max 9.000000 512.329200 \n",
|
||
" PassengerId Survived Pclass \\\n",
|
||
"0 892 0 3 \n",
|
||
"1 893 1 3 \n",
|
||
"2 894 0 2 \n",
|
||
"3 895 0 3 \n",
|
||
"4 896 1 3 \n",
|
||
"\n",
|
||
" Name Sex Age SibSp Parch \\\n",
|
||
"0 Kelly, Mr. James male 34.5 0 0 \n",
|
||
"1 Wilkes, Mrs. James (Ellen Needs) female 47.0 1 0 \n",
|
||
"2 Myles, Mr. Thomas Francis male 62.0 0 0 \n",
|
||
"3 Wirz, Mr. Albert male 27.0 0 0 \n",
|
||
"4 Hirvonen, Mrs. Alexander (Helga E Lindqvist) female 22.0 1 1 \n",
|
||
"\n",
|
||
" Ticket Fare Cabin Embarked \n",
|
||
"0 330911 7.8292 NaN Q \n",
|
||
"1 363272 7.0000 NaN S \n",
|
||
"2 240276 9.6875 NaN Q \n",
|
||
"3 315154 8.6625 NaN S \n",
|
||
"4 3101298 12.2875 NaN S \n",
|
||
"PassengerId 0\n",
|
||
"Survived 0\n",
|
||
"Pclass 0\n",
|
||
"Name 0\n",
|
||
"Sex 0\n",
|
||
"Age 86\n",
|
||
"SibSp 0\n",
|
||
"Parch 0\n",
|
||
"Ticket 0\n",
|
||
"Fare 1\n",
|
||
"Cabin 327\n",
|
||
"Embarked 0\n",
|
||
"dtype: int64\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
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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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diXaYqsnQOSgOdSeoZjPtwPT+2qFp6Ln6LqgPgehITkOXFX7UTq/l1LlaO3J1stSO76233nJlUdPGE0884Wpq1LQRCEKShtPqR0JV0QpQakJSbYl2JGpmUUdp9VvSzkodPnX+IX0+NfPpuXqf3Gi4vvrSqIlGbe3aaevoTbVXCmHqG6UO2IdCO2o1zeVWu6UjO3VM1NBlrRvVMGmHqSNiTdeR4oFqvPJCr6WQqL4Qd9999wG3L9XqqNOmamC0fkePHu1+lLMLr3ml/6N+NIJmLA3l1f8rrxQC1LldR/XahvRDrmlqMlBtiKi8agZSE4g6x6qfi7YxbZ/aHvKbttuuXbu6phf1r9PRub4TsUf0Wt/qQKzvg4ae6/ujPlFarwrkQa1LXreFvKwHLRusW9VYKjgE9D3Ud0/T/vKXv+TLetD3UrVK2i9o36JaC/XB0f9aTWwHS99lBSWti+DM8drn6fuo/Zz2bQfahlUrpOYrbbfa9rRfyFqjqWZaHaxpiLiChw7U1CFfQ8+1zavzcl72o4e63alPk74TealVTilhDwdDYuVliG4w9Pzvf/+7G+KqIenNmzd3wyqzG76r4ZAaqqlhrkWKFIlUq1bNDXsMhogeytDzF198MdKvXz83lFrvr6Gsq1at2u/5X3zxRaR9+/Zu6LyGxWt46FVXXRWZNWtW3Hsf6BY7pFQ01Pfss8+OlCpVyt3q16/vhmquWLHCze/Zs6cb7qrh43kdIq0huhoWrs+j4bKNGjVyw8U1fPZQh55reOzixYvjpmf3P9IQ1X/+859ufWs9VahQwZVl0KBBbihzfgyVvuKKKyJt27bNdjhv1qHnGk774IMPumkqj4ZRT5s2bb/lDnboeXDTEOXjjz/eDfsNhrjnZei5hsufc845kfLly7tyadj2zTffvN/w+meffdad+kDLaNvQ++dWvsMZeq7t4d133400btw4+n5Tp07d7/n6vul7p7IXL148cuaZZ7p1mlVetoW8rAd9jrx8t/Jr6Ll8/vnn7nQTpUuXdkPHzz///Mi8efMiBxI79DyWvs9aV71793aPa9So4U59EPudzGnouU6VcOONN0aOOuooVx6Va/ny5fstJ7/++mukR48e7pQa2jb1Plom6+kMctuPHsx2d6Ch5cbQ84g7sUDYgQupS0fj6iukGo9Dre2IpdoZ9b/REW5OZ3TVWUu1XOzZVYFkoG1WfWY0CifZBGekzu4M5LHfPX5SkIzoswMAALxGnx14RR2HdWr13DoQa4TXkTBsFkgm6isWnMcnt+8ekIwIO/CKhnHHdpzMaQQWgINzzz33HPZ3DwgLfXYAAIDX6LMDAAC8RtgBAABeo8/O/551VWct1cnkCuL0+gAA4PCpJ47O5K5BJ7ldwoSw87+nZ8/viyMCAICCsWbNGqtRo0aO8wk7Zq5GJ1hZebneCgAACJ+uHafKiuB3PCeEHQ1J+9+mKwUdwg4AAEeWA3VBoYMyAADwGmEHAAB4jbADAAC8RtgBAABeI+wAAACvEXYAAIDXCDsAAMBrhB0AAOA1wg4AAPAaZ1BGvti3b5999dVXtnnzZqtYsaI1btzYChUqFHaxAAAg7ODwzZkzx0aOHGnr16+PTqtWrZrddttt1qJFi1DLBgAAzVg47KAzcOBAO+6442zEiBE2ffp0d6/Hmq75AACEKS0SiUQsxemqqeXKlbOMjAwuBHqQTVedOnVywWbIkCGWnv5/2TkzM9P69+9vK1eutAkTJtCkBQAI7febmh0cMvXRUdOVAk9s0BE91vR169a55QAACAthB4dMnZGlTp062c4PpgfLAQAQBsIODplGXYmaqrITTA+WAwAgDIQdHDINL9eoq4kTJ7o+OrH0WNOrV6/ulgMAICyEHRwydTrW8PL58+e7zsjLli2z33//3d3rsaZ369aNzskAgNQNO/fdd5+lpaXF3erXrx+dv3PnTuvevbtVqlTJSpcubR06dLANGzbEvcbq1autXbt2VrJkSatSpYrdeeedtnfv3hA+TWrSeXQGDRpkP/74o/tfXXzxxe5eTViaznl2AACW6icVPPHEE+3999+PPi5c+P+K1Lt3b3v77bdt6tSpbmhZjx49rH379jZ37tzo0GcFHTWlzJs3z438uf76661IkSL24IMPhvJ5UpECTfPmzTmDMgAgKYV6nh3V7Lz++uu2ZMmS/eZpzHzlypVt0qRJ1rFjRzdt+fLl1qBBA9c80rRpU5sxY4ZdcskltnbtWqtatapbZvTo0XbXXXfZpk2brGjRonkqB+fZAQDgyHPEnGfnu+++s6OPPtqdmE7nZVGzlCxevNj27NljrVq1ii6rJq5atWq5sCO6b9SoUTToSJs2bdyHV7+RnOzatcstE3sDAAB+CjXsnHXWWTZu3Dh75513bNSoUa6fxznnnGPbtm1zJ6tTzUz58uXjnqNgE1yDSfexQSeYH8zLydChQ10SDG41a9ZMyOcDAAAp3menbdu20b/Vx0Php3bt2jZlyhQrUaJEwt63X79+1qdPn+hj1ewQeAAA8FPozVixVItTr149+/77712n4927d9uWLVviltFoLM0T3WcdnRU8DpbJTrFixVzbXuwNAAD4KanCzvbt2+2HH35wJ6Jr0qSJG1U1a9as6PwVK1a4Pj3NmjVzj3W/dOlS27hxY3SZmTNnuvDSsGHDUD4DAABILqE2Y91xxx126aWXuqYrjagaOHCgG6587bXXur40Xbt2dc1NGsqsANOzZ08XcDQSS1q3bu1CTefOnW348OGun45OZqfzvKj2BgAAINSw8/PPP7tg8+uvv7ph5meffbYtWLDA/S2PPvqou3q2TiaoEVQaaTVy5Mjo8xWMpk2b5s7SqxBUqlQp69Kliw0ePDjETwUAAJJJqOfZSRacZwcAgCPPEXOeHQAAgEQi7AAAAK8RdgAAgNcIOwAAwGuEHQAA4DXCDgAA8BphBwAAeI2wAwAAvEbYAQAAXiPsAAAArxF2AACA1wg7AADAa4QdAADgNcIOAADwGmEHAAB4jbADAAC8RtgBAABeI+wAAACvEXYAAIDXCDsAAMBrhB0AAOA1wg4AAPAaYQcAAHiNsAMAALxG2AEAAF4j7AAAAK8RdgAAgNcIOwAAwGuEHQAA4DXCDgAA8BphBwAAeI2wAwAAvEbYAQAAXiPsAAAArxF2AACA1wg7AADAa4QdAADgNcIOAADwGmEHAAB4jbADAAC8RtgBAABeI+wAAACvEXYAAIDXCDsAAMBrhB0AAOA1wg4AAPAaYQcAAHiNsAMAALxG2AEAAF4j7AAAAK8RdgAAgNcIOwAAwGuEHQAA4DXCDgAA8FrShJ1hw4ZZWlqa9erVKzpt586d1r17d6tUqZKVLl3aOnToYBs2bIh73urVq61du3ZWsmRJq1Klit155522d+/eED4BAABIRkkRdhYuXGhPPfWUNW7cOG5679697a233rKpU6fa7Nmzbe3atda+ffvo/H379rmgs3v3bps3b56NHz/exo0bZwMGDAjhUwAAgGQUetjZvn27derUyZ5++mmrUKFCdHpGRoY9++yz9sgjj1jLli2tSZMmNnbsWBdqFixY4JZ577337JtvvrEJEybYKaecYm3btrX777/fRowY4QIQAABA6GFHzVSqnWnVqlXc9MWLF9uePXviptevX99q1apl8+fPd49136hRI6tatWp0mTZt2tjWrVtt2bJlBfgpAABAsioc5ptPnjzZPv/8c9eMldX69eutaNGiVr58+bjpCjaaFywTG3SC+cG8nOzatcvdAgpHAADAT6HV7KxZs8Zuv/12mzhxohUvXrxA33vo0KFWrly56K1mzZoF+v4AACAFwo6aqTZu3GinnXaaFS5c2N3UCfmJJ55wf6uGRv1utmzZEvc8jcaqVq2a+1v3WUdnBY+DZbLTr18/1ycouCl4AQAAP4UWdi644AJbunSpLVmyJHo7/fTTXWfl4O8iRYrYrFmzos9ZsWKFG2rerFkz91j3eg2FpsDMmTOtbNmy1rBhwxzfu1ixYm6Z2BsAAPBTaH12ypQpYyeddFLctFKlSrlz6gTTu3btan369LGKFSu6QNKzZ08XcJo2bermt27d2oWazp072/Dhw10/nf79+7tOzwo0AAAAoXZQPpBHH33U0tPT3ckE1aFYI61GjhwZnV+oUCGbNm2adevWzYUghaUuXbrY4MGDQy03AABIHmmRSCRiKU6jsdRRWf13aNICAODIkNff79DPswMAAJBIhB0AAOA1wg4AAPAaYQcAAHiNsAMAALxG2AEAAF4j7AAAAK8RdgAAgNcIOwAAwGuEHQAA4DXCDgAA8BphBwAAeI2wAwAAvEbYAQAAXiPsAAAArxF2AACA1wg7AADAa4QdAADgNcIOAADwGmEHAAB4jbADAAC8RtgBAABeI+wAAACvEXYAAIDXCDsAAMBrhB0AAOA1wg4AAPAaYQcAAHiNsAMAALxG2AEAAF4j7AAAAK8RdgAAgNcIOwAAwGuEHQAA4DXCDgAA8BphBwAAeI2wAwAAvEbYAQAAXiPsAAAArxF2AACA1wg7AADAa4QdAADgNcIOAADwGmEHAAB4jbADAAC8RtgBAABeI+wAAACvEXYAAIDXCDsAAMBrhB0AAOA1wg4AAPAaYQcAAHiNsAMAALxG2AEAAF4j7AAAAK+FGnZGjRpljRs3trJly7pbs2bNbMaMGdH5O3futO7du1ulSpWsdOnS1qFDB9uwYUPca6xevdratWtnJUuWtCpVqtidd95pe/fuDeHTAACAZBRq2KlRo4YNGzbMFi9ebIsWLbKWLVvaZZddZsuWLXPze/fubW+99ZZNnTrVZs+ebWvXrrX27dtHn79v3z4XdHbv3m3z5s2z8ePH27hx42zAgAEhfioAAJBM0iKRSMSSSMWKFe2hhx6yjh07WuXKlW3SpEnub1m+fLk1aNDA5s+fb02bNnW1QJdccokLQVWrVnXLjB492u666y7btGmTFS1aNE/vuXXrVitXrpxlZGS4GiYAAJD88vr7nTR9dlRLM3nyZNuxY4drzlJtz549e6xVq1bRZerXr2+1atVyYUd036hRo2jQkTZt2rgPH9QOZWfXrl1umdgbAADwU+hhZ+nSpa4/TrFixezWW2+11157zRo2bGjr1693NTPly5ePW17BRvNE97FBJ5gfzMvJ0KFDXRIMbjVr1kzIZwMAAOELPeyccMIJtmTJEvv000+tW7du1qVLF/vmm28S+p79+vVzVV7Bbc2aNQl9PwAAEJ7CFjLV3hx//PHu7yZNmtjChQvt8ccft6uvvtp1PN6yZUtc7Y5GY1WrVs39rfvPPvss7vWC0VrBMtlRLZJuAADAf6HX7GSVmZnp+tQo+BQpUsRmzZoVnbdixQo31Fx9ekT3agbbuHFjdJmZM2e6TkpqCgMAAAi1ZkfNSW3btnWdjrdt2+ZGXn300Uf27rvvur40Xbt2tT59+rgRWgowPXv2dAFHI7GkdevWLtR07tzZhg8f7vrp9O/f352bh5obAAAQethRjcz1119v69atc+FGJxhU0Lnwwgvd/EcffdTS09PdyQRV26ORViNHjow+v1ChQjZt2jTX10chqFSpUq7Pz+DBg0P8VAAAIJkk3Xl2wsB5dgAAOPIccefZAQAASATCDgAA8BphBwAAeI2wAwAAvEbYAQAAXiPsAAAArxF2AACA1wg7AADAa4QdAADgNcIOAADwGmEHAAB47ZDDzg8//OCuMH7ttde6C3rKjBkzbNmyZflZPgAAgIIPO7Nnz7ZGjRrZp59+aq+++qpt377dTf/yyy9t4MCBh1ciAACAsMPO3XffbUOGDLGZM2da0aJFo9NbtmxpCxYsyM/yAQAAFHzYWbp0qV1xxRX7Ta9SpYr98ssvh1ciAACAsMNO+fLlbd26dftN/+KLL+yYY47Jj3IBAADki8KH8qRrrrnG7rrrLps6daqlpaVZZmamzZ071+644w67/vrr86dkOCg7d+601atXh12MpFGrVi0rXrx42MUAABypYefBBx+07t27W82aNW3fvn3WsGFDd3/ddde5EVooeAo6t9xyS9jFSBpjxoyxevXqhV0MAEASSItEIpGDeYIWX7NmjVWuXNn1z1H/HY3GOvXUU61u3bp2JNq6dauVK1fOMjIyrGzZsnYkSoaanVWrVtkDDzxg99xzj9WuXTvUslCzAwD+25rH3++DrtlR2Dn++OPd+XQUblS7g/Dphz1ZajIUdJKlLAAAHHQH5fT0dBdyfv3118SUCAAAIOzRWMOGDbM777zTvv766/wsCwAAQHJ0UNaIq99//91OPvlkd1LBEiVKxM3fvHlzfpUPAACg4MPOY489dnjvCgAAkMxhp0uXLvlfEgAAgGQJO1mHPO/evTtu2pE6fBsAAPjnkDoo79ixw3r06OGuhVWqVCmrUKFC3A0AAOCIDjt9+/a1Dz74wEaNGmXFihWzZ555xgYNGmRHH320Pf/88/lfSgAAgIJsxnrrrbdcqDnvvPPsxhtvtHPOOcedaFAnk5s4caJ16tTpUMsDAAAQfs2OhpYfd9xx0f45wVDzs88+2+bMmZO/JQQAACjosKOgs3LlSvd3/fr1bcqUKdEan/Llyx9OeQAAAMILOz/++KNlZma6pqsvv/zSTbv77rttxIgR7tpMvXv3dmdWBgAAOCL77OiaWOvWrXOhRq6++mp74oknbPny5bZ48WLXb6dx48aJKisAAEBia3Z0xfNY06dPd8PQ1TG5ffv2BB0AAOBHnx0AAAAvw05aWpq7ZZ0GAADgRZ8dNWPdcMMN7kSCwaUibr31VncW5Vivvvpq/pYSAACgIMJO1guA/uUvfznU9wUAAEi+sDN27NjElQQAACAB6KAMAAC8RtgBAABeI+wAAACvEXYAAIDXCDsAAMBrhB0AAOA1wg4AAPAaYQcAAHiNsAMAALxG2AEAAF4j7AAAAK8RdgAAgNcIOwAAwGuEHQAA4DXCDgAA8FqoYWfo0KF2xhlnWJkyZaxKlSp2+eWX24oVK+KW2blzp3Xv3t0qVapkpUuXtg4dOtiGDRvillm9erW1a9fOSpYs6V7nzjvvtL179xbwpwEAAMko1LAze/ZsF2QWLFhgM2fOtD179ljr1q1tx44d0WV69+5tb731lk2dOtUtv3btWmvfvn10/r59+1zQ2b17t82bN8/Gjx9v48aNswEDBoT0qQAAQDJJi0QiEUsSmzZtcjUzCjUtWrSwjIwMq1y5sk2aNMk6duzollm+fLk1aNDA5s+fb02bNrUZM2bYJZdc4kJQ1apV3TKjR4+2u+66y71e0aJFD/i+W7dutXLlyrn3K1u2bMI/p6++/fZbu+WWW2zMmDFWr169sIsDAPDc1jz+fidVnx0VVipWrOjuFy9e7Gp7WrVqFV2mfv36VqtWLRd2RPeNGjWKBh1p06aNWwHLli0r8M8AAACSS2FLEpmZmdarVy9r3ry5nXTSSW7a+vXrXc1M+fLl45ZVsNG8YJnYoBPMD+ZlZ9euXe4WUDACAAB+SpqaHfXd+frrr23y5MkF0jFa1V7BrWbNmgl/TwAAkMJhp0ePHjZt2jT78MMPrUaNGtHp1apVcx2Pt2zZEre8RmNpXrBM1tFZweNgmaz69evnmsyC25o1axLwqQAAgKV62FHfaAWd1157zT744AOrU6dO3PwmTZpYkSJFbNasWdFpGpquoebNmjVzj3W/dOlS27hxY3QZjexSR6WGDRtm+77FihVz82NvAADAT4XDbrrSSKs33njDnWsn6GOjpqUSJUq4+65du1qfPn1cp2WFkp49e7qAo5FYoqHqCjWdO3e24cOHu9fo37+/e22FGgAAkNpCDTujRo1y9+edd17c9LFjx9oNN9zg/n700UctPT3dnUxQnYo10mrkyJHRZQsVKuSawLp16+ZCUKlSpaxLly42ePDgAv40AAAgGYUadvJyip/ixYvbiBEj3C0ntWvXtunTp+dz6QAAgA+SooMyAABAohB2AACA1wg7AADAa4QdAADgNcIOAADwGmEHAAB4jbADAAC8RtgBAABeI+wAAACvEXYAAIDXCDsAAMBrhB0AAOA1wg4AAPAaYQcAAHiNsAMAALxG2AEAAF4j7AAAAK8RdgAAgNcIOwAAwGuEHQAA4DXCDgAA8BphBwAAeI2wAwAAvEbYAQAAXiPsAAAArxF2AACA1wg7AADAa4QdAADgNcIOAADwGmEHAAB4jbADAAC8RtgBAABeI+wAAACvEXYAAIDXCDsAAMBrhB0AAOC1wmEXwBcbNmywjIwMS2WrVq2Ku09l5cqVs6pVq4ZdDACAmaVFIpGIpbitW7e6HyeFlbJlyx5S0PlL5+ttz+5dCSkfjjxFihazCS88T+ABgCT4/aZmJx9oJSvo/HHcuZZZvFzYxUHI0ndmmP04220XhB0ACB9hJx8p6GSWOirsYgAAgBh0UAYAAF4j7AAAAK8RdgAAgNcIOwAAwGuEHQAA4DXCDgAA8BphBwAAeI2wAwAAvEbYAQAAXiPsAAAArxF2AACA1wg7AADAa4QdAADgNcIOAADwGmEHAAB4LdSwM2fOHLv00kvt6KOPtrS0NHv99dfj5kciERswYIBVr17dSpQoYa1atbLvvvsubpnNmzdbp06drGzZsla+fHnr2rWrbd++vYA/CQAASFahhp0dO3bYySefbCNGjMh2/vDhw+2JJ56w0aNH26effmqlSpWyNm3a2M6dO6PLKOgsW7bMZs6cadOmTXMB6pZbbinATwEAAJJZ4TDfvG3btu6WHdXqPPbYY9a/f3+77LLL3LTnn3/eqlat6mqArrnmGvv3v/9t77zzji1cuNBOP/10t8yTTz5pF198sT388MOuxggAAKS2pO2zs3LlSlu/fr1rugqUK1fOzjrrLJs/f757rHs1XQVBR7R8enq6qwnKya5du2zr1q1xNwAA4KekDTsKOqKanFh6HMzTfZUqVeLmFy5c2CpWrBhdJjtDhw51wSm41axZMyGfAQAAhC9pw04i9evXzzIyMqK3NWvWhF0kAACQamGnWrVq7n7Dhg1x0/U4mKf7jRs3xs3fu3evG6EVLJOdYsWKudFbsTcAAOCnpA07derUcYFl1qxZ0WnqW6O+OM2aNXOPdb9lyxZbvHhxdJkPPvjAMjMzXd8eAACAUEdj6Xw433//fVyn5CVLlrg+N7Vq1bJevXrZkCFDrG7dui783HvvvW6E1eWXX+6Wb9CggV100UV28803u+Hpe/bssR49eriRWozEAgAAoYedRYsW2fnnnx993KdPH3ffpUsXGzdunPXt29edi0fnzVENztlnn+2GmhcvXjz6nIkTJ7qAc8EFF7hRWB06dHDn5gEAAAg97Jx33nnufDo50VmVBw8e7G45US3QpEmTElRCAABwpEvaPjsAAAD5gbADAAC8RtgBAABeI+wAAACvEXYAAIDXCDsAAMBroQ49B4BE2r17t73xxhu2du1ad6LRyy67zIoWLRp2sQAUMMIOAC/prOpTp061ffv2xU278sor7dZbbw21bAAKFmEHgHcUaiZPnmwVKlSwrl27uuvozZ8/35599lk3XQg8COsySUOHDo3WNvbr189Kly4ddrG8R9gB4F3TlWp0FHR0X7jwf3Zzl1xyibuWnmp2NP2mm26iSQsFSgF7+fLlcdeD1HZZv359F9CROHRQBuAV9dFR05VqdIKgE9BjhRzN13JAQQcdXQapdevW9swzz7h7PdZ0ahoTi5odAF5R84Co6eqPP/6wp556yn7++WerUaOG/fWvf3XTY5cDCqLpKgg6M2bMiF7M+h//+Ie7AHbbtm3dfC1Hk1ZiEHYAeEX9IKRv3772ww8/RKcvWrTIXn/9dfvTn/4UtxyQaOqjIxdeeGE06AT0uFWrVjZz5ky33AMPPBBSKf1GMxYAr2h4uSjoFClSxK677jqbMGGCu9fjIAAFywGJFtQiXnXVVdnOVz+y2OWQ/wg7ALwSO9S8ZMmSVr16dXf0rHs9zm45IJGCWsQpU6ZkO18d5mOXQ/4j7ADwivroSIMGDVwfiH/961/WsWNHd6/HGvkSuxyQaBpeLmqq2rlzZ9w8PX7//ffjlkP+o88OAK+oM7Lcc889VqVKlf3OoLxhwwbr3LlzdDkg0dTpWCFbnZDVGVl9dIJTICjoRCIRN5/OyYlD2AHgFY26Umfk6dOn2y233BLtDxHQ9GA5oKDoPDrB8HPV8OgW4Dw7iUczFgCvaHi56KhZJxiMpccvv/xy3HJAQVEn+aOOOipumh5rOhKLmp18lP7HlrCLgCTAdhCuEiVKWPPmzW3u3LnWrl0711/n4osvdjU6Cjp79uxx87UcUFDmzJljAwcOdOd5GjRokNWpU8edQXnixIluuqa1aNEi7GJ6Ky2ixsIUt3XrVitXrpxlZGRY2bJlD/r53377rasuB2KNGTPG6tWrF3YxUpb67CjwZKWgw7lMUJA08q9Tp0523HHH2ZAhQyw9/f8aVTIzM61///4u+OgUCYUKFQq1rL7+flOzk4/+qNPCMkuUD7sYSIKanRIr54RdjJSnQJPdGZSp0UFB++qrr2z9+vV27733xgUd0WMFoe7du7vlTj311NDK6TPCTj5S0MksFd8eCyA8Cja9evUKuxhIcZs3b3b3arrKTjA9WA75j7ADAEACVaxY0d2rqapu3br7nQ5B02OXQ/4j7AAAkECNGze2atWquaZVnecp9uzdGnJetWpVd4ZvLYfEYOg5AAAJpE7HugCtanPURyf2em16rOnqvEzn5MShZgcAgATS+Z0WLFhgpUqVcrdJkya5m6hWR5cx0XwtV7Ro0bCL6yXCDgAACaQ+Omq66tatm7tchEZdqTOy+uio6UrngNK127Rc1jN+I3/QjAUAQAKpmUp0QsHsBNOD5ZD/qNkBACCBNOpKxo8fb5999pk7505AHZfPPPPMuOWQ/6jZAQAggTS8XB2R33zzTXdOnREjRrimK93rsaZrvpZDYlCzAyBhdu7caatXrw67GEmjVq1aVrx48bCLgQKmUVY6weWOHTvsm2++sdmzZ9t3333nmq30WDSf0ViJQ9gBkDAKOlw37v9wvbTUpA7JCjrqjKy/p0yZEje/UaNGtnTpUi4XkUCEHQAJrcnQD3yYVq1a5U7mpguD1q5dO/T1gdQTXAZCYeaMM86wX3/91V3AUheurFSpki1cuDBuOeQ/wg6AhFGTTbLUZCjoJEtZkFrKl//PBaLLlCkTDTbyyy+/2I8//uimb9u2Lboc8h9hBwCAAqBAU7hwYTv33HOtfv36tnz5ctd/R9ORWIQdAAASaOPGjdG/09LSbNasWe4mRYoUyXY55C+GngMAkECffPJJ9G8NMY8V+zh2OeQvanbyUfrOjLCLgCTAdgAg1h9//BEdXq7+ObE1OOXKlXPNWFomWA75j7CTD7SxFilazOzH2WEXBUlC24O2CwBQyBGFGXXa//vf/+4uETF//nx77rnn4sIQEoOwkw901doJLzxvGRmpfUSfTEN8w6ago+0CAP785z/b3Llzo310dNHPQJUqVeKWQ2IQdvKJftj4cfsPhvgmjw0bNhDCV62Ku09lhPBw/P7779G/f/vtN2vZsqWdcMIJtmLFCvv444+zXQ75i7ADeBx0/tL5etuze1fYRUkKqnVMdWpeVS10KgeeMC5hoveU0qVL2/bt2+2DDz5wt0AwXct9++23BVq2WilyCRPCDuAp1ego6Pxx3LmWWZz+Q6nOdZz/cbbbLlI57IR5CRMFmtymP/vss+5WkMakyCVMCDuA5xR0MksdFXYxgJS9hElmZqbry6gaHI28ir0shC4Xoem6dtaQIUP2G5qeaLVS5BImhB0AQMoI6xImt99+uw0cONCaNm1qxx57rL344ot27bXX2k8//WQLFiywQYMGubMqIzE4qSAAAAnWokULF2hWrlzpgo7oXmFH0zUfiUPNDgAABUCBpnnz5jZ9+nQ3/Fzn27n44outUKFCYRfNe4QdwHPpf2wJuwhIAsmyHXA6hP80pQX3P/zwg6WycgV0OgTCDuC5EivnhF0EwOF0CPE4HYIV2OkQCDuAx0dMhYsUtb17doddFCQJbQ9hXsaE0yEgrNMhEHYAT2nnMXHCCynfZMBlTJLvDMqcDgEFjbADeCzsy5iEcbbaZJYqZ6sFkg1hB4CXZ6tNxv4RqXK22gMplPFz0nSYRnjSdmd/RulEIOwA8OpstcksVc5Wm1szWnp6ISv+P5+HXRQkCW0PBdGPzJuwM2LECHvooYds/fr1dvLJJ9uTTz5pZ555ZtjFAlJaWGerRXJSk+rIkSNszZo1lsrWrVtnzz33nN10001WvXp1S2U1a9Zk6HlevfTSS9anTx8bPXq0nXXWWfbYY49ZmzZtbMWKFValSpWwiwcA+F+6JEKYl0VIpn5kCjphd5qvlSL9yLwIO4888ojdfPPNduONN7rHCj1vv/22S85333132MUDACQJ+pGlZj+yIz7s7N692xYvXmz9+vWLTtNVY1u1amXz58/P9jm7du1yt8DWrVvtSJcMRysa4ht7H6ZUOVoBcHDoR5aa/ciO+LDzyy+/2L59+/Zr89Pj5cuXZ/ucoUOHuguv+YSjldQ8WgFwcOhHlpqO+LBzKFQLpD4+sTU76iR1JONoJTWPVgAAKRB2jjrqKHfFWF1zJZYeV6tWLdvnFCtWzN18wtEKAADZS7cjXNGiRa1JkyY2a9as6LTMzEz3uFmzZqGWDQAAhO+Ir9kRNUl16dLFTj/9dHduHQ0937FjR3R0FgAASF1ehJ2rr77aNm3aZAMGDHAnFTzllFPsnXfeSYoL3gEAgHClRSKRiKU4dVDW6ap1deiyZcuGXRwAAJCPv99HfJ8dAACA3BB2AACA1wg7AADAa4QdAADgNcIOAADwGmEHAAB4jbADAAC8RtgBAABeI+wAAACveXG5iMMVnERaZ2IEAABHhuB3+0AXgyDsmNm2bdvcfc2aNcMuCgAAOITfcV02IidcG8vMMjMzbe3atVamTBlLS0sLuzhHdMJWYFyzZg3XGEPSYLtEsmGbzD+KMAo6Rx99tKWn59wzh5oddVxKT7caNWqEXQxv6MvLFxjJhu0SyYZtMn/kVqMToIMyAADwGmEHAAB4jbCDfFOsWDEbOHCguweSBdslkg3bZMGjgzIAAPAaNTsAAMBrhB0AAOA1wg4AAPAaYQcAAHiNsIPDNmfOHLv00kvdGSx1BurXX3897CIhxQ0dOtTOOOMMd1b0KlWq2OWXX24rVqwIu1hIcaNGjbLGjRtHTybYrFkzmzFjRtjFSgmEHRy2HTt22Mknn2wjRowIuyiAM3v2bOvevbstWLDAZs6caXv27LHWrVu7bRUIi87UP2zYMFu8eLEtWrTIWrZsaZdddpktW7Ys7KJ5j6HnyFeq2XnttdfckTSQLDZt2uRqeBSCWrRoEXZxgKiKFSvaQw89ZF27dg27KF7j2lgAvJeRkRH9YQGSwb59+2zq1KmutlHNWUgswg4Ar2VmZlqvXr2sefPmdtJJJ4VdHKS4pUuXunCzc+dOK126tKsJb9iwYdjF8h5hB4DX1Hfn66+/tk8++STsogB2wgkn2JIlS1xt48svv2xdunRxzasEnsQi7ADwVo8ePWzatGluxKA6hwJhK1q0qB1//PHu7yZNmtjChQvt8ccft6eeeirsonmNsAPAOxp30bNnT9dE8NFHH1mdOnXCLhKQYzPrrl27wi6G9wg7OGzbt2+377//Pvp45cqVrppWnUFr1aoVatmQuk1XkyZNsjfeeMOda2f9+vVuerly5axEiRJhFw8pql+/fta2bVu3X9y2bZvbRhXG33333bCL5j2GnuOw6ct6/vnn7zddbdHjxo0LpUxIbToFQnbGjh1rN9xwQ4GXBxANL581a5atW7fOBW+dYPCuu+6yCy+8MOyieY+wAwAAvMYZlAEAgNcIOwAAwGuEHQAA4DXCDgAA8BphBwAAeI2wAwAAvEbYAQAAXiPsAPDKeeed565yDgABwg6ApKOzHOssyLoFF04cPHiw7d27N+yiATgCcW0sAEnpoosucpd30EUSp0+f7q53VaRIEXd9IQA4GNTsAEhKxYoVs2rVqlnt2rWtW7du1qpVK3vzzTfdvLlz57rmqpIlS1qFChWsTZs29ttvv2X7Oi+88IKdfvrp7oKger3rrrvONm7cGJ2v53Xq1MkqV67sLhJat25dF7Jk9+7d1qNHD6tevboVL17clWXo0KEFtAYA5BdqdgAcERREfv31V1uyZIldcMEFdtNNN9njjz9uhQsXtg8//ND27duX7fP27Nlj999/v51wwgku5PTp08c1k6m2SO6991775ptvbMaMGXbUUUfZ999/b3/88Yeb98QTT7iANWXKFHel6jVr1rgbgCMLYQdAUtO1inWl6Hfffdd69uxpw4cPdzU1I0eOjC5z4okn5vh8haLAcccd5wLMGWecYdu3b7fSpUvb6tWr7dRTT3WvKccee2x0ec1TTc/ZZ5/t+g+pZgfAkYdmLABJadq0aS6MqPmobdu2dvXVV9t9990XrdnJq8WLF9ull17qambUlHXuuedGg4yoiWzy5Ml2yimnWN++fW3evHnR56oGSO+nWqG//e1v9t577yXgkwJINMIOgKR0/vnnu6Dx3XffuWal8ePHW6lSpVxzVl7t2LHD9ecpW7asTZw40RYuXGivvfZatD+OKEitWrXKevfubWvXrnVB6o477nDzTjvtNFu5cqVrBlMZrrrqKuvYsWOCPjGARCHsAEhKCjYacq4aGfXLCTRu3Ng1a+XF8uXLXT+fYcOG2TnnnGP169eP65wcUOfkLl262IQJE+yxxx6zMWPGROcpKKlW6emnn7aXXnrJXnnlFdu8eXM+fUoABYE+OwCOKBp63qhRI7vtttvs1ltvdefhUQflK6+80nUwjqWgpPlPPvmkW/brr792tTSxBgwYYE2aNHH9fjTMXc1nDRo0cPMeeeQRNxJLfXrS09Nt6tSpbkRX+fLlC/QzAzg81OwAOKLUq1fP9Z358ssv7cwzz7RmzZrZG2+8EVf7E1tjM27cOBdSGjZs6Gp4Hn744bhlFIYUoFRj1KJFCytUqJDrwyPq4xN0iFan5p9++smN4lLwAXDkSItoqAMAAICnODwBAABeI+wAAACvEXYAAIDXCDsAAMBrhB0AAOA1wg4AAPAaYQcAAHiNsAMAALxG2AEAAF4j7AAAAK8RdgAAgNcIOwAAwHz2/wGERqPgvUY6SgAAAABJRU5ErkJggg==",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"import seaborn as sns\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"from tqdm import tqdm\n",
|
||
"\n",
|
||
"# 1. Загрузка данных\n",
|
||
"df = pd.read_csv(\"C:\\\\Users\\\\ilyam\\\\Downloads\\\\archive\\\\tested.csv\")\n",
|
||
"\n",
|
||
"# 2. Базовый анализ данных\n",
|
||
"print(df.info()) # Общая информация\n",
|
||
"print(df.describe()) # Основные статистические характеристики\n",
|
||
"print(df.head()) # Первые 5 строк\n",
|
||
"print(df.isnull().sum()) # Количество пропущенных значений\n",
|
||
"\n",
|
||
"# 3. Визуализация данных\n",
|
||
"\n",
|
||
"# Гистограмма (histplot)\n",
|
||
"sns.histplot(df[\"Age\"], bins=20, kde=True)\n",
|
||
"plt.title(\"Распределение возраста\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Scatterplot (Точечная диаграмма)\n",
|
||
"sns.scatterplot(x=df[\"Age\"], y=df[\"Fare\"]) # \"Возраст\" → \"Age\", \"Баллы\" → \"Fare\" (пример)\n",
|
||
"plt.title(\"Зависимость платы за проезд от возраста\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Boxplot (Ящик с усами)\n",
|
||
"sns.boxplot(x=df[\"Pclass\"], y=df[\"Fare\"], data=df) # \"Категория\" → \"Pclass\"\n",
|
||
"plt.title(\"Распределение платы за проезд по классам\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "8890b0d9-f21e-49de-b22a-94758cf77dc9",
|
||
"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
|
||
}
|