708 lines
309 KiB
Plaintext
708 lines
309 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "6e0c84b7-5f42-4ff6-ac77-6f69be5864a0",
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"metadata": {},
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"source": [
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"# Анализ данных за вторую неделю\n",
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"Юпитерлаб Лаба 2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "b853fed9-da00-4a79-aa8c-8f654f12810d",
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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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"ПТУ СКВАД 999999999999\n"
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]
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}
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],
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"source": [
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"print(\"ПТУ СКВАД 999999999999\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "685d0bd5-58ab-4c22-977a-a26821c18b3c",
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"metadata": {},
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"source": [
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"3 ЗАДАНИЕ: \n",
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"Анна, Алексей, Иван, Галина получили баллы за тест!"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "00d6662c-7fd5-4f1a-9acc-caaef86f7ae3",
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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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"Первый взгляд на данные:\n",
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" Имя Возраст Баллы\n",
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"0 Анна 21 49\n",
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"1 Алексей 26 56\n",
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"2 Иван 20 95\n",
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"3 Галина 19 32\n",
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"\n",
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"Информация о данных:\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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"\n",
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"Статистика:\n",
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" Возраст Баллы\n",
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"count 4.000000 4.000000\n",
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"mean 21.500000 58.000000\n",
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"std 3.109126 26.645825\n",
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"min 19.000000 32.000000\n",
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"25% 19.750000 44.750000\n",
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"50% 20.500000 52.500000\n",
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"75% 22.250000 65.750000\n",
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"max 26.000000 95.000000\n",
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"\n",
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"Проверка пропущенных значений:\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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"\n",
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"DataFrame с новым столбцом:\n",
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" Имя Возраст Баллы Новый столбец\n",
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"0 Анна 21 49 53.9\n",
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"1 Алексей 26 56 61.6\n",
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"2 Иван 20 95 104.5\n",
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"3 Галина 19 32 35.2\n",
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"\n",
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"сСреднее значение баллов:\n",
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" Баллы\n",
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"Возраст \n",
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"19 32.0\n",
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"20 95.0\n",
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"21 49.0\n",
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"26 56.0\n",
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"\n",
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"Фильтр: студентs младше 20:\n",
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" Имя Возраст Баллы Новый столбец\n",
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"3 Галина 19 32 35.2\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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"# 1. Создание DataFrame\n",
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"data = {\n",
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" \"Имя\": [\"Анна\", \"Алексей\", \"Иван\", \"Галина\"],\n",
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" \"Возраст\": [21, 26, 20, 19],\n",
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" \"Баллы\": [49, 56, 95, 32]\n",
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"}\n",
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"df = pd.DataFrame(data)\n",
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"\n",
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"#Вывод информации\n",
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"print(\"Первый взгляд на данные:\")\n",
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"print(df.head()) #Вывод первых строк\n",
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"print(\"\\nИнформация о данных:\")\n",
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"print(df.info()) #Общая информация\n",
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"print(\"\\nСтатистика:\")\n",
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"print(df.describe()) #описательная статистика\n",
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"print(\"\\nПроверка пропущенных значений:\")\n",
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"print(df.isnull().sum()) #Проверка на пропуски\n",
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"\n",
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"# 2. Добавление нового столбца\n",
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"df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
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"print(\"\\nDataFrame с новым столбцом:\")\n",
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"print(df)\n",
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"\n",
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"# 3. Группировка данных\n",
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"df_grouped = df.groupby(\"Возраст\").agg({\"Баллы\": \"mean\"})\n",
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"print(\"\\nсСреднее значение баллов:\")\n",
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"print(df_grouped)\n",
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"\n",
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"# 4. Фильтрация данных \n",
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"df_filtered = df[df[\"Возраст\"] < 20]\n",
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"print(\"\\nФильтр: студентs младше 20:\")\n",
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"print(df_filtered)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9b1ee32c-7e2e-444d-9bd6-aa2c66242dd7",
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"metadata": {},
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"source": [
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"ПОРАБОТАЕМ С МАССИВОМ ЧЕРЕЗ NUMPY"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "98395fff-fe72-421b-bbf1-46d84851ac5c",
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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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"Сумма элементов массива: 154\n",
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"Среднее значение: 30.8\n",
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"Медиана: 13.0\n",
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"Стандартное отклонение: 32.652105598261194\n",
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"\n",
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"Двумерный массив:\n",
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"[[12 12]\n",
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" [23 34]]\n",
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"\n",
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"Линейно распределённые значения от 0 до 1 (12):\n",
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"[0. 0.09090909 0.18181818 0.27272727 0.36363636 0.45454545\n",
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" 0.54545455 0.63636364 0.72727273 0.81818182 0.90909091 1. ]\n",
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"\n",
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"Случайные значения из нормального распределения (квадратная, 3x3):\n",
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"[[-0.29296901 -0.49448547 -0.59156976]\n",
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" [-0.38588753 -0.1742459 0.54649204]\n",
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" [-0.78447519 -1.40302717 0.32124449]]\n",
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"\n",
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"Произведение матриц A и B:\n",
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"[[19 22]\n",
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" [43 50]]\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"\n",
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"arr = np.array([13, 12, 30, 94, 5])\n",
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"print(\"Сумма элементов массива:\", np.sum(arr))\n",
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"print(\"Среднее значение:\", np.mean(arr))\n",
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"print(\"Медиана:\", np.median(arr))\n",
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"print(\"Стандартное отклонение:\", np.std(arr))\n",
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"\n",
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"arr_2d = np.array([[12, 12], [23, 34]])\n",
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"print(\"\\nДвумерный массив:\")\n",
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"print(arr_2d)\n",
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"\n",
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"#генерация чисел\n",
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"linspace_arr = np.linspace(0, 1, 12)\n",
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"print(\"\\nЛинейно распределённые значения от 0 до 1 (12):\")\n",
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"print(linspace_arr)\n",
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"\n",
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"random_arr = np.random.randn(3, 3)\n",
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"print(\"\\nСлучайные значения из нормального распределения (квадратная, 3x3):\")\n",
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"print(random_arr)\n",
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"\n",
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"#операции с матрицами\n",
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"A = np.array([[1, 2], [3, 4]])\n",
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"B = np.array([[5, 6], [7, 8]])\n",
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"dot_product = np.dot(A, B)\n",
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"\n",
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"print(\"\\nПроизведение матриц A и B:\")\n",
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"print(dot_product)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c0c40d28-71cd-4e85-9570-09cdc26d77f8",
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"metadata": {},
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"source": [
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"------------------------------------------------------------------------------------"
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]
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},
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{
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"cell_type": "markdown",
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"id": "b5d71e23-ce08-4868-ab8d-b66e7d746524",
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"metadata": {},
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"source": [
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"4 ЗАДАНИЕ - ВИЗУАЛИЗАЦИЯ ДАННЫХ"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"id": "a00594f1-4f6b-4025-bd79-3ce6317c0db9",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 800x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 800x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 800x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 800x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"# 1. Подготовка данных \n",
|
||
"x = np.linspace(0, 10, 100)\n",
|
||
"y_sin = np.sin(x)\n",
|
||
"y_cos = np.tan(x)\n",
|
||
"\n",
|
||
"# 2. Построение графиков sin(x) и cos(x) \n",
|
||
"plt.figure(figsize=(8, 4))\n",
|
||
"plt.plot(x, y_sin, label=\"sin(x)\", color=\"red\") #красный синус\n",
|
||
"plt.plot(x, y_cos, label=\"tan(x)\", color=\"blue\") #синий тангенс\n",
|
||
"plt.xlabel(\"X\")\n",
|
||
"plt.ylabel(\"Y\")\n",
|
||
"plt.title(\"Графики sin(x) и tan(x)\")\n",
|
||
"plt.legend()\n",
|
||
"plt.grid()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# 3. Bar chart \n",
|
||
"np.random.seed(42)\n",
|
||
"data = np.random.randint(1, 12, size=10)\n",
|
||
"\n",
|
||
"plt.figure(figsize=(8, 4))\n",
|
||
"plt.bar(range(len(data)), data, color=\"purple\", alpha=0.7)\n",
|
||
"plt.title(\"Bar chart\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# 4. Scatter plot \n",
|
||
"plt.figure(figsize=(8, 4))\n",
|
||
"plt.scatter(range(len(data)), data, color=\"green\", alpha=0.7)\n",
|
||
"plt.title(\"Scatter plot\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# 5. Histogram \n",
|
||
"plt.figure(figsize=(8, 4))\n",
|
||
"plt.hist(data, bins=5, color=\"black\", alpha=0.7)\n",
|
||
"plt.title(\"Histogram\")\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "9c440cbd-90eb-4dbb-898c-a3fec8b52637",
|
||
"metadata": {},
|
||
"source": [
|
||
"SEABORN: РАБОТА С ГРАФИКАМИ"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"id": "de0ef98a-34e8-4e34-b629-0e94032d23c6",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 800x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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YdfR7iRIXJqI7depkQvLTTz8tTz75pAm12qHB/UC3xx9/3LQuu+++++TkyZPSuXNniY+PNyeqAAAAQPES0MCbnxbAK1euzLbs9ttvNyMnOsv7zDPPmAEAAIDiLSgOWgMAAAAKC4EXAAAAtkbgBQAAgK0ReAEAAGBrBF4AAADYGoEXAAAAtkbgBQAAgK0ReAEAAGBrBF4AAADYGoEXAAAAtkbgBQAAgK0ReAEAAGBrBF4AAADYGoEXAAAAtkbgBQAAgK0ReAEAAGBrBF4AAADYGoEXAAAAtkbgBQAAgK0ReAEAAGBrBF4AAADYGoEXAAAAtkbgBQAAgK0ReAEAAGBrBF4AAADYWkAD79dffy0333yzxMbGSlhYmCxcuDDX9QcPHmzW8x7NmjVzrTNhwoRs9zdu3LgI3g0AAACCUUADb1pamrRq1UqmT5+er/WnTZsmSUlJrnHgwAGpXLmy3H777R7raQB2X2/16tWF9A4AAAAQ7EoG8sV79eplRn5FRUWZYdEZ4RMnTsiQIUM81itZsqRER0f7dVsBAAAQmkK6hve///2v9OjRQ2rXru2xfPfu3aZMom7dunLnnXfK/v37c32e9PR0SUlJ8RgAAACwh5ANvIcPH5Yvv/xShg4d6rG8Q4cOMnv2bImPj5c33nhDEhMTpUuXLnL69Okcn2vSpEmu2WMdNWvWLIJ3AAAAgKIQsoF3zpw5UrFiRenbt6/Hci2R0Jreli1bSs+ePWXx4sVy8uRJWbBgQY7PNWbMGDl16pRraG0wAAAA7CGgNbyXyuFwyKxZs+Tuu++W0qVL57quhuKGDRvKnj17clwnIiLCDAAAANhPSM7wrlq1ygTYe++9N891U1NTZe/evRITE1Mk2wYAAIDgEtDAq2F0y5YtZiitt9Xr1kFmWmowcOBAnweraa1u8+bNs903evRoE4j37dsna9askVtuuUXCw8NlwIABRfCOAAAAEGwCWtKwceNG6datm+v2qFGjzOWgQYPMgWfaQ9e7w4LW2H700UemJ68vBw8eNOH2t99+k6pVq0rnzp1l3bp15joAAACKn4AG3q5du5p63Jxo6PWmXRTOnDmT42PmzZvnt+0DAABA6AvJGl4AAAAgvwi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsLWABt6vv/5abr75ZomNjZWwsDBZuHBhruuvXLnSrOc9jhw54rHe9OnTJS4uTsqUKSMdOnSQDRs2FPI7AQAAQLAKaOBNS0uTVq1amYB6MXbt2iVJSUmuUa1aNdd98+fPl1GjRsn48eNl8+bN5vl79uwpx44dK4R3AAAAgGBXMpAv3qtXLzMulgbcihUr+rxvypQpMmzYMBkyZIi5PWPGDFm0aJHMmjVLnnjiiQJvMwAAAEJLSNbwtm7dWmJiYuT666+Xb7/91rU8IyNDNm3aJD169HAtK1GihLm9du3aHJ8vPT1dUlJSPAYAAADsIaQCr4ZcnbH96KOPzKhZs6Z07drVlC6o48ePS2ZmplSvXt3jcXrbu87X3aRJkyQqKso19HkBAABgDwEtabhYjRo1MsPSqVMn2bt3r7z66qvyzjvvXPLzjhkzxtT9WnSGl9ALAABgDyEVeH1p3769rF692lyvUqWKhIeHy9GjRz3W0dvR0dE5PkdERIQZAAAAsJ+QKmnwZcuWLabUQZUuXVratm0rCQkJrvuzsrLM7Y4dOwZwKwEAAFAsZ3hTU1Nlz549rtuJiYkmwFauXFlq1aplSg0OHTokc+fONfdPnTpV6tSpI82aNZNz587JW2+9JcuXL5elS5e6nkNLEwYNGiTt2rUzs7/6GG1/ZnVtAAAAQPES0MC7ceNG6datm+u2VUergXX27Nmmx+7+/fs9ujA8+uijJgSXLVtWWrZsKV999ZXHc/Tr10+Sk5Nl3Lhx5kA17egQHx+f7UA2AAAAFA9hDofDEeiNCDZ60Jp2azh16pRUqFAh0JuDEKCdQrSc5r77NklMTJtAbw4uQVLSZpk5s61pbdimDT9DALBTXgv5Gl4AAAAgNwReAAAA2BqBFwAAALZG4AUAAICtEXgBAABgawReAAAA2BqBFwAAALZG4AUAAICtEXgBAABgawReAAAA2BqBFwAAALZG4AUAAICtEXgBAABgawReAAAA2BqBFwAAALZG4AUAAICtEXgBAABgawReAAAA2BqBFwAAALZG4AUAAICtEXgBAABgawReAAAA2BqBFwAAALZG4AUAAICtEXgBAABgawReAAAA2FpAA+/XX38tN998s8TGxkpYWJgsXLgw1/U//vhjuf7666Vq1apSoUIF6dixoyxZssRjnQkTJpjnch+NGzcu5HcCAACAYBXQwJuWliatWrWS6dOn5zsga+BdvHixbNq0Sbp162YC8/fff++xXrNmzSQpKck1Vq9eXUjvAAAAAMGuZCBfvFevXmbk19SpUz1u//Of/5RPP/1UPv/8c7nyyitdy0uWLCnR0dH5ft709HQzLCkpKfl+LAAAAIJbSNfwZmVlyenTp6Vy5coey3fv3m3KJOrWrSt33nmn7N+/P9fnmTRpkkRFRblGzZo1C3nLAQAAUFRCOvC+8sorkpqaKnfccYdrWYcOHWT27NkSHx8vb7zxhiQmJkqXLl1MMM7JmDFj5NSpU65x4MCBInoHAAAAsHVJQ0G8//77MnHiRFPSUK1aNddy9xKJli1bmgBcu3ZtWbBggdx7770+nysiIsIMAAAA2E9IBt558+bJ0KFD5cMPP5QePXrkum7FihWlYcOGsmfPniLbPgAAAASPkCtp+OCDD2TIkCHmsnfv3nmuryUPe/fulZiYmCLZPgAAAASXgM7wahh1n3nVetstW7aYg9Bq1aplamsPHTokc+fOdZUxDBo0SKZNm2ZKFY4cOWKWR0ZGmoPN1OjRo02rMi1jOHz4sIwfP17Cw8NlwIABAXqXAAAAKLYzvBs3bjTtxKyWYqNGjTLXx40bZ25rD133DgszZ86UP/74Q4YPH25mbK0xcuRI1zoHDx404bZRo0bmYLbLL79c1q1bZ05WAQAAgOInoDO8Xbt2FYfDkeP92m3B3cqVK/NV3wsAAACEbA0vAAAAcDEIvAAAALA1Ai8AAABsjcALAAAAW7ukwFu3bl357bffsi0/efKkuQ8AAAAI6cC7b98+yczMzLY8PT3d9M0FAAAAQrIt2Weffea6vmTJEtfJHpQG4ISEBImLi/PvFgIAAABFFXj79u1rLsPCwswZz9yVKlXKhN3JkycXZHsAAACAwAXerKwsc1mnTh357rvvpEqVKv7dGgAAACAYzrSWmJjo7+0AAAAAguvUwlqvq+PYsWOumV/LrFmz/LFtAAAAQGAC78SJE+WZZ56Rdu3aSUxMjKnpBQAAAGwTeGfMmCGzZ8+Wu+++2/9bBAAAAAS6D29GRoZ06tTJn9sBAAAABE/gHTp0qLz//vv+3xoAAAAgGEoazp07JzNnzpSvvvpKWrZsaXrwupsyZYq/tg8AAAAo+sC7detWad26tbm+fft2j/s4gA0AAAAhH3hXrFjh/y0BAAAAgqWGFwAAALD1DG+3bt1yLV1Yvnx5QbYJAAAACGzgtep3LefPn5ctW7aYet5Bgwb5a9sAAACAwATeV1991efyCRMmSGpqakG3CQAAAAjOGt677rpLZs2a5c+nBAAAAIIn8K5du1bKlCnjz6cEAAAAir6k4dZbb/W47XA4JCkpSTZu3Chjx44t2BYBAAAAgZ7hjYqK8hiVK1eWrl27yuLFi2X8+PH5fp6vv/5abr75ZomNjTVdHxYuXJjnY1auXClt2rSRiIgIqV+/vsyePTvbOtOnT5e4uDgz29yhQwfZsGHDRb9HAAAAFOMZ3rffftsvL56WliatWrWSe+65J9ussS+JiYnSu3dv+fvf/y7vvfeeJCQkyNChQyUmJkZ69uxp1pk/f76MGjVKZsyYYcLu1KlTzX27du2SatWq+WW7AQAAYPPAa9m0aZPs2LHDXG/WrJlceeWVF/X4Xr16mZFfGmLr1KkjkydPNrebNGkiq1evNl0jrMA7ZcoUGTZsmAwZMsT1mEWLFpmD6Z544omL2j4AAAAU08B77Ngx6d+/vykvqFixoll28uRJc0KKefPmSdWqVaUw6EFxPXr08FimQffhhx821zMyMkwIHzNmjOv+EiVKmMfoY3OSnp5uhiUlJUWK2v79++X48eNF/rrwD+sPPwDApePfwtBXpUoVqVWrltgi8D744INy+vRp+fHHH80sq/rpp5/MSSceeugh+eCDD6QwHDlyRKpXr+6xTG9rQD179qycOHFCMjMzfa6zc+fOHJ930qRJMnHiRAnk/+CNGzeRs2fPBGwb4B+pqacDvQkAEJL4t9AeIiPLys6dO4Iu9F5S4I2Pj5evvvrKFXZV06ZNzcFiN9xwg4QanRHWul+LBuiaNWsW2evrX7P6P/gtt7wrVate2KcIHbt3L5YVK8bKuXPnAr0pABCS+Lcw9CUn75BPPrnL/CxtEXizsrKkVKlS2ZbrMr2vsERHR8vRo0c9luntChUqSGRkpISHh5vhax19bE6044OOQNP/wWNi2gR6M3AJjh+npAEA/IF/CxE0bcn+9Kc/yciRI+Xw4cOuZYcOHZJHHnlEunfvLoWlY8eOpjODu2XLlpnlqnTp0tK2bVuPdTSA621rHQAAABQvlxR4X3/9dfO1v/a6rVevnhnaPUGX/etf/8r386SmpsqWLVvMsNqO6XWt47FKDQYOHOhaX9uR/fLLL/L444+bmtx///vfsmDBAhO0LVqa8Oabb8qcOXPMgUT333+/aX9mdW0AAABA8XJJJQ1a37p582ZTx2sdDKb1vN4dFPKiZ2bTzg4Wq45WD37TE0ro2dus8Ks0VGuLMQ2406ZNkyuuuELeeustV0sy1a9fP0lOTpZx48aZg9xat25tao69D2QDAABA8XBRgXf58uUyYsQIWbdunambvf76681Qp06dMr14te9tly5d8vV8enY2PS1xTnydRU0f8/333+f6vLqNOgAAAICLKmnQs5bpSR007HrTUwz/7W9/Myd+AAAAAEIy8P7www9y44035ni/tiTTEz8AAAAAIRl4tb2Xr3ZklpIlS5r6WQAAACAkA2+NGjVk+/btOd6/detWiYmJ8cd2AQAAAEUfeG+66SYZO9b32aT01L7jx4+XP//5z/7ZMgAAAKCouzQ8/fTT8vHHH0vDhg1NF4RGjRqZ5dqaTE8rnJmZKU899ZQ/tgsAAAAo+sCrvWzXrFljTuagJ4WwWoqFhYWZXrgaeul3CwAAgJA+8UTt2rVl8eLFcuLECdmzZ48JvQ0aNJBKlSoVzhYCAAAARX2mNaUB96qrrirIawMAAADBddAaAAAAEGoIvAAAALA1Ai8AAABsjcALAAAAWyPwAgAAwNYIvAAAALA1Ai8AAABsjcALAAAAWyPwAgAAwNYIvAAAALA1Ai8AAABsjcALAAAAWyPwAgAAwNYIvAAAALA1Ai8AAABsjcALAAAAWyPwAgAAwNaCIvBOnz5d4uLipEyZMtKhQwfZsGFDjut27dpVwsLCso3evXu71hk8eHC2+2+88cYiejcAAAAIJiUDvQHz58+XUaNGyYwZM0zYnTp1qvTs2VN27dol1apVy7b+xx9/LBkZGa7bv/32m7Rq1Upuv/12j/U04L799tuu2xEREYX8TgAAABCMAj7DO2XKFBk2bJgMGTJEmjZtaoJv2bJlZdasWT7Xr1y5skRHR7vGsmXLzPregVcDrvt6lSpVKqJ3BAAAgGAS0MCrM7WbNm2SHj16XNigEiXM7bVr1+brOf773/9K//79pVy5ch7LV65caWaIGzVqJPfff7+ZCc5Jenq6pKSkeAwAAADYQ0AD7/HjxyUzM1OqV6/usVxvHzlyJM/Ha63v9u3bZejQodnKGebOnSsJCQny4osvyqpVq6RXr17mtXyZNGmSREVFuUbNmjUL+M4AAAAQLAJew1sQOrvbokULad++vcdynfG16P0tW7aUevXqmVnf7t27Z3ueMWPGmDpii87wEnoBAADsIaAzvFWqVJHw8HA5evSox3K9rXW3uUlLS5N58+bJvffem+fr1K1b17zWnj17fN6v9b4VKlTwGAAAALCHgAbe0qVLS9u2bU3pgSUrK8vc7tixY66P/fDDD03t7V133ZXn6xw8eNDU8MbExPhluwEAABA6At6lQUsJ3nzzTZkzZ47s2LHDHGCms7fatUENHDjQlBz4Kmfo27evXH755R7LU1NT5bHHHpN169bJvn37THju06eP1K9f37Q7AwAAQPES8Brefv36SXJysowbN84cqNa6dWuJj493Hci2f/9+07nBnfboXb16tSxdujTb82mJxNatW02APnnypMTGxsoNN9wgzz77LL14AQAAiqGAB141YsQIM3zRA828aasxh8Phc/3IyEhZsmSJ37cRAAAAoSngJQ0AAABAYSLwAgAAwNaCoqQBsKOsLD2Ln55RUOT8eZE//sj7Uoc+zhpaueN93f1SaYl7WFj24b08PFykZMn8j9KltWWfc+hjAQAIVQReIBcaQM+cuTDS0pyX5845hwZaHcePdxORtbJsWXNZtsx5n4ZYu9DAq8HXPQRb1/UyMvLCKFs2+20N0AAABAr/DKHY0SB6+nT24SvY6uxs/sSaoc/jKyyWKuUMfXld6rBmZvXS/bqvZcqa7bVGTrf10ppFzmvoPtL3rteVnpXb2jeXQt+XFYT1snx5kXLlPC+t6zq8GrMAAFAgBF7Yis6snjzpHCkpvoOtrnMxNFxqSNMgppc6ypRxDmu2Mzl5jWza9KJ06fK0NGlylVlm3R/K5QDuZRnWbLav62fPOverBmK9rsO6rmFbg7P+PHTkhxWKdVx2mYie/NC6tIauoz8bAADyQuBFyNDg5B5orXHq1IXrGr7yO+NohSgd1uyid7C1wm1ewWrbtkTZtOkzqVr1AbHTCf10ptUqTbjUn5kViK2hs+c6UlMvXFrXdehjrNnkY8dyfm79Q8I7BEdFiVSseGFouQUAAAReBBUNOxqKfvtN5PffLwzrdn4CrYZUDTsafqxA6z105pXZwcKn+9iaDa9UKX8zyvrzt0KwDp2Vt2aHraHBWMssrD908vos6GtbYVivW58PLSUBANgfgRcBoTWix487hxVmrcu8Sg50BtaawfOe0dPbzOqF9oyyVcf7/0+26JOGXV9B2H223yqx0HH4sO/n0Zl9KwSXKqVT8/8n27eXlTp18hfQAQChgcCLQqU1nsnJF4YGXL08cSL3x+nX05UrO8fll1+41HDCrBy0nMH6Iycn7uUv+nmzyl+s6/rZtGaRDx7UR2jgfU8GDXI+Xj9vDRqI1K/vvHQf+ocVACB0EHjhF3pQkgbZI0ecdZdWsNWAkROtC61a9UKYtYKtDkItCkrLKKKjnSOnenAr/Oo3CwcPHpddu36UqlU7SnJyafONg45167I/Xj+3GoQbNhRp0uTC0JlhWrABQPDhVzMuigYFnRE7etQZbvVShwZc60QI3vTraQ0I3oOj7BEo+rmzDsaL1Y5yIpKUtF927eoq8fGbpFGjNrJnj8ju3ReGdVs/99Y3FmvXej6vltPoDLB7CNbRqNGlH/gHACg4Ai9yPYBIZ7i0/tE93ObUi9WaUatWzTk01Fap4gy2QCjRP9JatXIOb1o7bIXfXbtEduwQ2bnTOfSAux9/dA7vgB0XJ9K4cfYwrN9oAAAKF4EXrnCrs7RJSc6Aq5cacn2dLUz/8dbyAz2oyBoadLX7ATO2sDv9nF95pXN4/z+0f78zAHsPLZlITHSOL7/0fJz+/9O8uXO0aOG8bNbMeUAdAMA/CLzF0MWEW62l1b6yGmitcKuzt9TYAtk7TOgsro5evS4s11If/f/NVxA+cODCNycJCZ7Pp/XA7iFYL7VmmC4kAHDxCLzFgPYs1aPQdRw65By+TplrhVtraG2jzuRymlfg0um3Hlbd+rXXet6n9fAafLdtE9m+3Tn0uv4Bas0If/75hfX1gDgti/CeEdaQzf+nAJAzAq8NuyXobJF7wPXVAoxwCwSeli1cdZVzuNMZYfcAbF3XXsPWde+aYy2D0PDbsuWF+mN6CQOAE4E3hOlXpdr2yz3canmCNuX3pgePXXGFc9So4SxLINwCwUn/f+3a1Tnc/3/XEgjvEPzTT85vcTZscA53NWteCL/WqFfP2ccYAIoTAm+I1d7q7K0eGKP/8OmlHjHuTdsfWcHWutQOCgBCuzSiVi3nuOkmz291tGuEhmAdW7eK/PCDyL59zt8TOr744sL62jVFSyHcQ7DOCuvBeABgVwTeIKYHkemsrQZbK+R6197qLK0eUGaFWx36NSbdEoDiwarr1XH77ReW67c/Vvi1hs4Ia1vB9eudw13dutlng7U2mN8lAOyAwBtEzp4taXp5WgFXyxN0VtddRITza0odOtOjQZeOCQC86emPu3RxDouWO2n/YPcQrEP/sP7lF+f45BPPU3y71wTr0DphemsDCDUE3gDTQPv88zVF5Cd5550m2e7Xrxlr174QcKm9BXCptHbXmg3u1+/Ccj3BjHcI1tpgPUhu9WrnsOjvHz2bXOvWnkFYD3xlNhhAsCLwBpj+47FtWzkRqWpua+siq05Ph87S8I8IgMKkHVr+9CfncC+p0m+cvIPwsWPOM8zpmD/f80A79wCsgViDNX2DAQQDAm8Q+NvfkmT06JEycODzUqeOj3OZAkAR01IpPbhNx113XViuPYLdA/CWLc7wq63U9OQZ7ifQ0Odo2jT7bLAGbAAoSgTeINCt2ykRWSRlyjwT6E0BgFzpQbI6eva8sOzcOZEff7wQgK0wrAfOWdfd6cG17jPBtEsDUNgIvACAAtG2h23bOod73+Bff80+G6wHxlm9wxctyt4uzX02WG/TLg2APwTF4U/Tp0+XuLg4KVOmjHTo0EE2eHdPdzN79mwJCwvzGPo4dw6HQ8aNGycxMTESGRkpPXr0kN16aDIAoEjosQfa1qxPH5Fx40Q++khk717nrK8eBPf66yLDhom0b+/sHW61S/vPf0QeeEDkmmucXSL0ALnbbhN59lmRzz5zdrDRMA0AITXDO3/+fBk1apTMmDHDhN2pU6dKz549ZdeuXVJNWxL4UKFCBXO/RUOvu5deeklee+01mTNnjtSpU0fGjh1rnvOnn37KFo4BAEVHQ6yGWR05tUuzyiIOH3aeVEOHBmaL9hrXdmnus8FaK8yvdwBBG3inTJkiw4YNkyFDhpjbGnwXLVoks2bNkieeeMLnYzTgRmsRmQ86u6uh+emnn5Y+OrUgInPnzpXq1avLwoULpX///tkek56eboYlRXvxAAAC2i5ND4TzrgvWdmknToisWuUc7s/RpEn2ThE5zJsAKGYCGngzMjJk06ZNMmbMGNeyEiVKmBKEtWvX5vi41NRUqV27tmRlZUmbNm3kn//8pzRr1szcl5iYKEeOHDHPYYmKijKzx/qcvgLvpEmTZOLEiX5/fwCAS6etzrp3dw6Lzk3s2JF9Nvj3351nktPx3nsX1te5EfdTKGtdcKNGzpP4ACg+Ahp4jx8/LpmZmWb21Z3e3qkNIH1o1KiRmf1t2bKlnDp1Sl555RXp1KmT/Pjjj3LFFVeYsGs9h/dzWvd508CtZRXuM7w19UwPAICgokFVZ251WLSmV88W5z4TrEPLJPTXvo4lSzxPx9ywofOscTo0BOulnl6ZE/sA9hTwkoaL1bFjRzMsGnabNGki//nPf+RZParhEkRERJgBAAg9ehiHtjrT8ec/X1ielqYn9rkwE6yzv3pbD5zT0ggdCxZ4dorQWmArAFthWGeJOQEQENoCGnirVKki4eHhcvToUY/lejunGl1vpUqVkiuvvFL26FEN5uuraNdzaJcG9+ds7T4lAACwtXLlRK6+2jm8Z4Ot8GtdavjVThEbNzqHu8qVs4dgraKrWLHI3xKAUAy8pUuXlrZt20pCQoL07dvXLNO6XL09YsSIfD2HlkRs27ZNbrrpJnNbuzJo6NXnsAKuliisX79e7r///kJ8NwCAUJoNvvFGz04R2jbNPQTrpZZFaH2w90FySivfrBCsM8M69MA77UQBILgEvKRBa2cHDRok7dq1k/bt25sOC2lpaa6uDQMHDpQaNWqYA8vUM888I1dffbXUr19fTp48KS+//LL8+uuvMnToUFcHh4cffliee+45adCggastWWxsrCtUAwDgTrs8aF2vjr/+9cLys2dF9JAS7xlhPXHGgQPO8eWXns+lYVo7RujQEGxd6kF4AIpp4O3Xr58kJyebE0XoQWU6KxsfH+866Gz//v2mc4PlxIkTpo2ZrlupUiUzQ7xmzRppqr9N/r/HH3/chOb77rvPhOLOnTub56QHLwDgYuhJMa680jncnTzpPJ2yFYK1c4SOpKQLZ5JbtszzMRp4vUOwXtaoQY0wYPvAq7R8IacShpUrV3rcfvXVV83Ijc7y6kywDgAA/E3rd71PoGEFYQ2+WhPsfrlvn7Ov8DffOIc7PX2y94ywzjRr14hSpYr0bQG2FRSBFwAAuwRhbSTk1kzI1TFCTxDqHYb1eOvTp0U2bHAO7zILDb1WqYX7YFYYuDgEXgAAiqBjRJs2zuEuI8MZet1DsNYM//yzs2uEHjSnY9Eiz8dpCzVfQVhPqkH3CCA7Ai8AAAFSuvSFDg/utH3a4cPO4GsNnSHWy19+cYZh7S2sw1vVqp4huEEDkXr1nEPLJ4DiiMALAECQ0XIFLVvQ0a2b533nz4skJvoOwxqSk5Od49tvfYdhLZOwArA1dJm2rqdMAnZF4AUAIITogWzW7K231FRnCYR7ENaSCe0xrAfNWWF4/XrfHSm8w7B1Oy7OORsNhCoCLwAANlG+vO82aiolxRl8tSRCL93H/v3OnsPaak2HN+0Oqifa0PBbp44zAOuoXdt5GRvrPMgOCFYEXgAAigE9A1xOYVgPnvv1V99h2KoZ1vt1+FKypEitWhcCsHsY1qGlGboOECh8/AAAKOa0XEEPbtPhTQ+gO3r0QgDWnsI6NPzqpc4O//GHMxjr8EVnf/UMdN5BWK9rUNb7gMJE4AUAADnSA9mio53D+0QbKjPTeYY57yBsXddhzSDnNEOsKlVqISIbZcmSulKtmnNGOirqwqV2mKBsApeKwAsAAC6ZNXuro3Pn7PdnZYkcOZI9CFvXDxxwlkycOKGnlWubazDWGmX3IOwdivV+rTcGvBF4AQBAodEAqge16fA+A51VMnHihMjSpTtkwIDHpHPnf4tILXOQ3alTzoPtdOhMsnah0KHt13KajdbQq7PBGoKtgKy3raG3IyJowVbcEHgBAEDAaPCsXFnbrJ0VkUXStOlxiYmplS0U6yywFYDdg7D7dV1PT9WsI6dQrPQAOu8g7B2K9ZID7eyDHyUAAAj6UKynZ9ahM8W+aOmEzv5agdd7aCDWy3PnnAfZ/f67c+RGexPnFIp16AyyDmqLgx+BFwAA2KJ0wqrrzY2eqc5XEPYeGoq1N7GOY8fyF4ytAGyVVXhf124YlFIEBoEXAAAUqzPVaQmFjpxoaYTOBOcWiq16Yp1Zzm8w1tf2DsPeoVgvy5YlGPsbgRcAAMCNhk2dtdWhLdJyC8YadN0DsPt199vamk1nl/UAPR15vX5Ogdj7OnXG+cNuAgAAuAQaTHU2Vkf16rmvq4HXOxDr9bS0C8v0Ug/Ocz/4Li9lyuSvnCKimHemIPACAAAUMq3fzauUQmn7NQ3B3jPE3uFYh66rpRc6kpNzf96SJT3LJvQAQPfbdi+nIPACAAAECe34kJ+D79zrjPMqp0hPdx6Ed7HlFDmVUVjXQ6k7BYEXAADApnXG7p0pUnMJxb7KKfSU0RfTnSIsTHvGDZdgROAFAAAo5p0pvMsp8grIvrtTRIvIkyJyRIINgRcAAAByMeUUvrpTHD16TLZvnysiN0iwIfACAACgwN0pkpIOyvbtY4Iy8JYI9AYAAAAAhYnACwAAAFsLisA7ffp0iYuLkzJlykiHDh1kw4YNOa775ptvSpcuXaRSpUpm9OjRI9v6gwcPlrCwMI9x4403FsE7AQAAQLAJeOCdP3++jBo1SsaPHy+bN2+WVq1aSc+ePeVYDiekXrlypQwYMEBWrFgha9eulZo1a8oNN9wghw4d8lhPA25SUpJrfPDBB0X0jgAAABBMAh54p0yZIsOGDZMhQ4ZI06ZNZcaMGVK2bFmZNWuWz/Xfe+89eeCBB6R169bSuHFjeeuttyQrK0sSEhI81ouIiJDo6GjX0NlgAAAAFD8BDbwZGRmyadMmU5bg2qASJcxtnb3NjzNnzsj58+elsldzOZ0JrlatmjRq1Ejuv/9++e2333J8jvT0dElJSfEYAAAAsIeABt7jx49LZmamVHfvaSHa4qK6HDmSv6bF//jHPyQ2NtYjNGs5w9y5c82s74svviirVq2SXr16mdfyZdKkSRIVFeUaWiYBAAAAewjpPrwvvPCCzJs3z8zm6gFvlv79+7uut2jRQlq2bCn16tUz63Xv3j3b84wZM8bUEVt0hpfQCwAAYA8BneGtUqWKhIeHy9GjRz2W622tu83NK6+8YgLv0qVLTaDNTd26dc1r7dmzx+f9Wu9boUIFjwEAAAB7CGjgLV26tLRt29bjgDPrALSOHTvm+LiXXnpJnn32WYmPj5d27drl+ToHDx40NbwxMTF+23YAAACEhoB3adBSAu2tO2fOHNmxY4c5wCwtLc10bVADBw40JQcWrckdO3as6eKgvXu11ldHqp7IWfR8zqny2GOPybp162Tfvn0mPPfp00fq169v2p0BAACgeAl4DW+/fv0kOTlZxo0bZ4KrthvTmVvrQLb9+/ebzg2WN954w3R3uO222zyeR/v4TpgwwZRIbN261QTokydPmgPatE+vzghr6QIAAACKl4AHXjVixAgzfNEDzdzprG1uIiMjZcmSJX7dPgAAAISugJc0AAAAAIWJwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbC4rAO336dImLi5MyZcpIhw4dZMOGDbmu/+GHH0rjxo3N+i1atJDFixd73O9wOGTcuHESExMjkZGR0qNHD9m9e3chvwsAAAAEo4AH3vnz58uoUaNk/PjxsnnzZmnVqpX07NlTjh075nP9NWvWyIABA+Tee++V77//Xvr27WvG9u3bXeu89NJL8tprr8mMGTNk/fr1Uq5cOfOc586dK8J3BgAAgGAQ8MA7ZcoUGTZsmAwZMkSaNm1qQmrZsmVl1qxZPtefNm2a3HjjjfLYY49JkyZN5Nlnn5U2bdrI66+/7prdnTp1qjz99NPSp08fadmypcydO1cOHz4sCxcuLOJ3BwAAgEArGcgXz8jIkE2bNsmYMWNcy0qUKGFKENauXevzMbpcZ4Td6eytFWYTExPlyJEj5jksUVFRplRCH9u/f/9sz5menm6G5dSpU+YyJSVFikJqaqq5PHx4k2RkOK8jtCQn7/j/l9vk118jA705uATHj+8yl/o7yfp/EqFF//3IysoK9GbgEu3a5fx/kH8LQ//3aGpqapFkKOs1dLIzqAPv8ePHJTMzU6pXr+6xXG/v3LnT52M0zPpaX5db91vLclrH26RJk2TixInZltesWVOK0hdf3Fekrwf/++abx+SbbwK9FSiI++7j/0MgkPi3MPRdd911Rfp6p0+fNpObQRt4g4XOMLvPGusMwe+//y6XX365hIWF5fqXhYbiAwcOSIUKFYpoa4sf9nPhYx8XDfZz4WMfFw32c+FjH+dNZ3Y17MbGxua5bkADb5UqVSQ8PFyOHj3qsVxvR0dH+3yMLs9tfetSl2mXBvd1Wrdu7fM5IyIizHBXsWLFfL8P/SDyYSx87OfCxz4uGuznwsc+Lhrs58LHPs5dXjO7QXHQWunSpaVt27aSkJDgMbuqtzt27OjzMbrcfX21bNky1/p16tQxodd9Hf0rSbs15PScAAAAsK+AlzRoKcGgQYOkXbt20r59e9NhIS0tzXRtUAMHDpQaNWqYOls1cuRIUxsyefJk6d27t8ybN082btwoM2fONPdrCcLDDz8szz33nDRo0MAE4LFjx5rpbm1fBgAAgOIl4IG3X79+kpycbE4UoQeVadlBfHy866Cz/fv3myNvLZ06dZL333/ftB178sknTajVDg3Nmzd3rfP444+b0KwHn5w8eVI6d+5snlNPVOFPWgah/YO9yyHgX+znwsc+Lhrs58LHPi4a7OfCxz72rzBHfno5AAAAACEq4CeeAAAAAAoTgRcAAAC2RuAFAACArRF4AQAAYGsE3nx44403pGXLlq7mz9rP98svv3Tdf+7cORk+fLg5M1v58uXlr3/9a7aTY+DivPDCC64Wcxb2c8FNmDDB7Ff30bhxY9f97GP/OHTokNx1111mP0ZGRkqLFi1M+0SLHiusnWn05Dh6f48ePWT37t0B3eZQExcXl+2zrEM/v4rPcsFlZmaatp7a3lM/p/Xq1ZNnn33WfH4tfJYLTs8Upv/W1a5d2+xD7Ub13Xffue5nH/uJdmlA7j777DPHokWLHD///LNj165djieffNJRqlQpx/bt2839f//73x01a9Z0JCQkODZu3Oi4+uqrHZ06dQr0ZoesDRs2OOLi4hwtW7Z0jBw50rWc/Vxw48ePdzRr1syRlJTkGsnJya772ccF9/vvvztq167tGDx4sGP9+vWOX375xbFkyRLHnj17XOu88MILjqioKMfChQsdP/zwg+Mvf/mLo06dOo6zZ88GdNtDybFjxzw+x8uWLdMU5lixYoW5n89ywT3//POOyy+/3PHFF184EhMTHR9++KGjfPnyjmnTprnW4bNccHfccYejadOmjlWrVjl2795tfk9XqFDBcfDgQXM/+9g/CLyXqFKlSo633nrLcfLkSRN+9ReBZceOHeYX79q1awO6jaHo9OnTjgYNGph/vK677jpX4GU/+4f+Im3VqpXP+9jH/vGPf/zD0blz5xzvz8rKckRHRztefvllj30fERHh+OCDD4poK+1Hf1fUq1fP7F8+y/7Ru3dvxz333OOx7NZbb3Xceeed5jqf5YI7c+aMIzw83PxR4a5NmzaOp556in3sR5Q0XMJXPHp2Nz2xhZY2bNq0Sc6fP2++YrDoV8S1atWStWvXBnRbQ5F+Baln0HPfn4r97D/6VZieebBu3bpy5513mpO7KPaxf3z22WfmzJG33367VKtWTa688kp58803XfcnJiaak+y472c9F3yHDh3Yz5coIyND3n33XbnnnntMWQOfZf/Qr9YTEhLk559/Nrd/+OEHWb16tfTq1cvc5rNccH/88YfJFd4nxtLSBd3X7GMbnWktVGzbts0EXK0L03qwTz75RJo2bSpbtmyR0qVLS8WKFT3W1zPF6YcU+ad/SGzevNmjdsmi+5L9XHD6S3L27NnSqFEjSUpKkokTJ0qXLl1k+/bt7GM/+eWXX0zdv542Xc8GqZ/nhx56yOxbPY26tS+ts0la2M+XTs+2qWfVHDx4sLnNZ9k/nnjiCUlJSTF/LISHh5tg9vzzz5s/lBWf5YK77LLLTLbQ2ugmTZqYfffBBx+YMFu/fn32sR8RePNJA4KG21OnTsn//vc/8w/XqlWrAr1ZtnHgwAEZOXKkLFu2zO+ngMYF1syM0gMxNQDrgRILFiwwMwoouKysLDPD+89//tPc1hle/YNixowZ5vcG/O+///2v+WzrNxfwH/298N5778n7778vzZo1M/8G6sFVup/5LPvPO++8Y76dqFGjhvnDok2bNjJgwADzTQX8h5KGfNLZAv1rq23btjJp0iRp1aqVTJs2TaKjo83XaTq74E6PBtb7kD/6P/axY8fM/+glS5Y0Q/+geO2118x1/WuW/ex/OgPWsGFD2bNnD59lP9EjqfXbH3c6c2OVjlj70rtjAPv50vz666/y1VdfydChQ13L+Cz7x2OPPWZmefv37286jdx9993yyCOPmH8DFZ9l/9DuF/rvXWpqqpn82bBhgynJ0bIz9rH/EHgLMIuTnp5uAnCpUqVMnZNl165d5h83/ZoC+dO9e3dTNqIzCNbQWTL96sy6zn72P/0Fu3fvXhPS+Cz7xzXXXGP2mzutgdSZdKUtnvQfKvf9rF8br1+/nv18Cd5++21TK621/xY+y/5x5swZKVHCMyboDKT++6f4LPtXuXLlzO/iEydOyJIlS6RPnz7sY3/y5xFwdvXEE0+YdiHalmXr1q3mdlhYmGPp0qWu9je1atVyLF++3LS/6dixoxkoGPcuDYr9XHCPPvqoY+XKleaz/O233zp69OjhqFKlimnxpNjH/mmrV7JkSdPSSVsMvffee46yZcs63n33Xdc62maoYsWKjk8//dT8TunTpw9thi5BZmam+bxqZwxvfJYLbtCgQY4aNWq42pJ9/PHH5vfF448/7lqHz3LBxcfHO7788kvTwlBzhXbS6dChgyMjI8Pczz72DwJvPmhbFu2rWbp0aUfVqlUd3bt3d4VdpR+6Bx54wLQq03/YbrnlFtMXEv4NvOznguvXr58jJibGfJb1HzK97d4fln3sH59//rmjefPmpnVQ48aNHTNnzvS4X1sNjR071lG9enWzjv5O0R7fuDja31jnbXztOz7LBZeSkmJ+B+sfDmXKlHHUrVvXtMpKT093rcNnueDmz59v9q3+XtYWZMOHDzetxyzsY/8I0//4dcoYAAAACCLU8AIAAMDWCLwAAACwNQIvAAAAbI3ACwAAAFsj8AIAAMDWCLwAAACwNQIvAAAAbI3ACwAAAFsj8AIAAMDWCLwAEGQGDx4sYWFh2cYVV1wR6E0DgJBUMtAbAADI7sYbb5S3337bY1l4eHjAtgcAQhkzvAAQhCIiIiQ6OtpjVK1a1XX/P/7xD2nYsKGULVtW6tatK2PHjpXz5897PMe+fft8zhSfPHky3+tMmDBBWrdu7XMbFy5caNYFgGBH4AWAEHTZZZfJ7Nmz5aeffpJp06bJm2++Ka+++qrHOg6Hw1x+9dVXkpSUJB999FG258nPOgAQ6gi8ABCEvvjiCylfvrwZWrt7/fXXy9KlS133P/3009KpUyeJi4uTm2++WUaPHi0LFizweA5rxteaIa5cuXK218nPOgAQ6gi8ABCEunXrJlu2bDHj448/lpiYGOndu7esX7/e3D9//ny55pprTEjVUKwBeP/+/R7PkZKSYi7LlSuX4+vkZ51t27aZ14iKipImTZrICy+84Kd3CQBFg4PWACAIaQCtX7++6/asWbNM8NW62aysLLnzzjtl4sSJ0rNnTxNE582bJ5MnT/Z4jsOHD0uJEiVMKM5JftZp1KiRfPbZZ5KZmSnr1q2TYcOGmW0rWZJ/QgCEBn5bAUAI0FCqQ0PnmjVrpHbt2vLUU0+57v/111+zPea7776Txo0bS5kyZXJ83vysU7p0aVf41vD7+uuvm5nndu3aFfh9AUBRoKQBAIJQenq6HDlyxIwdO3bIgw8+KKmpqXLTTTdJgwYNTPmCzuru3btXXnvtNfnkk09cj83IyJB33nlHpkyZIkOGDPH5/PlZx/3AtnPnzklaWposX77cHCjXvHlzv79nACgszPACQBCKj483dbtWRwYNue+//7507drVLHvkkUdkxIgRJhhrba+2JdMWYlbNrV7XZaNGjfL5/PlZx7J161aJjIw0M8w1atSQRx99VPr372/KKwAgFIQ5rJ40AAAAgA1R0gAAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAsDUCLwAAAGyNwAsAAABbI/ACAADA1gi8AAAAEDv7f4SJ+2GRuoPwAAAAAElFTkSuQmCC",
|
||
"text/plain": [
|
||
"<Figure size 800x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 800x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 588.236x500 with 6 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 800x400 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import pandas as pd\n",
|
||
"import seaborn as sns\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"# 1. Создание DataFrame \n",
|
||
"df = pd.DataFrame({\n",
|
||
" \"Имя\": [\"Анна\", \"Алексей\", \"Иван\", \"Галина\"],\n",
|
||
" \"Возраст\": [21, 26, 20, 19],\n",
|
||
" \"Баллы\": [49, 56, 95, 32],\n",
|
||
" \"Категория\": [\"A\", \"B\", \"A\", \"B\"]\n",
|
||
"})\n",
|
||
"\n",
|
||
"# 2 Boxplot по категориям \n",
|
||
"plt.figure(figsize=(8, 4))\n",
|
||
"sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
|
||
"plt.title(\"Boxplot по категориям\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"#3. Histplot \n",
|
||
"plt.figure(figsize=(8, 4))\n",
|
||
"sns.histplot(df[\"Баллы\"], bins=5, kde=True, color=\"blue\")\n",
|
||
"plt.title(\"Histplot для баллов\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# 4. Scatterplot \n",
|
||
"plt.figure(figsize=(8, 4))\n",
|
||
"sns.scatterplot(x=\"Возраст\", y=\"Баллы\", hue=\"Категория\", data=df, s=100)\n",
|
||
"plt.title(\"Scatterplot: Возраст vs Баллы\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# 5. Pairplot \n",
|
||
"sns.pairplot(df, hue=\"Категория\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# 6. Heatmap (корреляционная матрица)\n",
|
||
"plt.figure(figsize=(8, 4))\n",
|
||
"sns.heatmap(df.select_dtypes(include=[\"number\"]).corr(), annot=True, cmap=\"coolwarm\")\n",
|
||
"plt.title(\"Корреляционная матрица\")\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "a9eba8e6-a7fc-4120-807c-b4d047c9326f",
|
||
"metadata": {},
|
||
"source": [
|
||
"------------------------------------------------------"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "994c8ae5-9525-42a6-9b23-2bfa32210d87",
|
||
"metadata": {},
|
||
"source": [
|
||
"5. Прогресс-бар с tqdm"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"id": "f9813e47-d6cf-4183-b3c0-9f73c3d88eb6",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 90.74it/s]\n",
|
||
"Процесс:: 100%|\u001b[32m████████████████████████████████████████████████████████████\u001b[0m| 100/100 [00:01 < 00:00]\u001b[0m\n",
|
||
"Обработка строк: 25%|\u001b[34m██████████████████████████████████████████████████████▌ \u001b[0m| 1/4 [00:00<00:01, 2.00it/s]\u001b[0m"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработана строка: Анна\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 50%|\u001b[34m█████████████████████████████████████████████████████████████████████████████████████████████████████████████ \u001b[0m| 2/4 [00:01<00:01, 1.99it/s]\u001b[0m"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработана строка: Алексей\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 75%|\u001b[34m███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌ \u001b[0m| 3/4 [00:01<00:00, 1.99it/s]\u001b[0m"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработана строка: Иван\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка строк: 100%|\u001b[34m██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████\u001b[0m| 4/4 [00:02<00:00, 1.99it/s]\u001b[0m"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработана строка: Галина\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tqdm import tqdm\n",
|
||
"import time\n",
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"# --- 1. Обычный прогресс-бар ---\n",
|
||
"for i in tqdm(range(100)):\n",
|
||
" time.sleep(0.01) # Симуляция долгого процесса\n",
|
||
"\n",
|
||
"# --- 2. Кастомный прогресс-бар с измененной стилизацией ---\n",
|
||
"for i in tqdm(range(100), desc='Процесс:', bar_format='{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed} < {remaining}]', ncols=100, colour='green'):\n",
|
||
" time.sleep(0.01) # Симуляция долгого процесса\n",
|
||
"\n",
|
||
"# --- 3. Использование tqdm для обработки строк DataFrame ---\n",
|
||
"df = pd.DataFrame({\n",
|
||
" \"Имя\": [\"Анна\", \"Алексей\", \"Иван\", \"Галина\"],\n",
|
||
" \"Возраст\": [21, 26, 20, 19],\n",
|
||
" \"Баллы\": [49, 56, 95, 32]\n",
|
||
"})\n",
|
||
"\n",
|
||
"# Применение tqdm к обработке строк DataFrame\n",
|
||
"for index, row in tqdm(df.iterrows(), total=df.shape[0], desc=\"Обработка строк\", colour='blue'):\n",
|
||
" time.sleep(0.5) # Симуляция обработки данных\n",
|
||
" print(f\"Обработана строка: {row['Имя']}\")\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "139ca923-73bb-4cd4-89de-dc31b5733d12",
|
||
"metadata": {},
|
||
"source": [
|
||
"----------------------------------------------------------------------------------------------\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "7011e0dc-385e-45f9-a0e5-8373a8520d9d",
|
||
"metadata": {},
|
||
"source": [
|
||
"6666666666 САМОСТОЯТЕЛЬНОЕ ЗАДАНИЕ"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"id": "c99e1106-fe78-409a-8447-1c8d2fd24adf",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Информация о данных:\n",
|
||
"<class 'pandas.core.frame.DataFrame'>\n",
|
||
"RangeIndex: 1436 entries, 0 to 1435\n",
|
||
"Data columns (total 7 columns):\n",
|
||
" # Column Non-Null Count Dtype \n",
|
||
"--- ------ -------------- ----- \n",
|
||
" 0 Year 1436 non-null int64 \n",
|
||
" 1 Rank 1436 non-null object\n",
|
||
" 2 NOC 1436 non-null object\n",
|
||
" 3 Gold 1436 non-null int64 \n",
|
||
" 4 Silver 1436 non-null int64 \n",
|
||
" 5 Bronze 1436 non-null int64 \n",
|
||
" 6 Total 1436 non-null int64 \n",
|
||
"dtypes: int64(5), object(2)\n",
|
||
"memory usage: 78.7+ KB\n",
|
||
"None\n",
|
||
"\n",
|
||
"Статистическое описание данных:\n",
|
||
" Year Gold Silver Bronze Total\n",
|
||
"count 1436.000000 1436.000000 1436.000000 1436.000000 1436.000000\n",
|
||
"mean 1981.899721 4.053621 4.030641 4.392061 12.476323\n",
|
||
"std 34.119053 8.411742 7.115310 6.847175 21.641717\n",
|
||
"min 1896.000000 0.000000 0.000000 0.000000 1.000000\n",
|
||
"25% 1960.000000 0.000000 0.000000 1.000000 2.000000\n",
|
||
"50% 1992.000000 1.000000 2.000000 2.000000 5.000000\n",
|
||
"75% 2008.000000 4.000000 4.000000 5.000000 13.000000\n",
|
||
"max 2024.000000 83.000000 79.000000 78.000000 234.000000\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
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",
|
||
"text/plain": [
|
||
"<Figure size 800x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 800x400 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 2000x1000 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Обработка данных: 100%|█████████████████| 1436/1436 [00:00<00:00, 13163.78it/s]\n"
|
||
]
|
||
}
|
||
],
|
||
"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('Olympics.csv')\n",
|
||
"\n",
|
||
"# 2. Базовый анализ\n",
|
||
"print(\"Информация о данных:\")\n",
|
||
"print(df.info())\n",
|
||
"\n",
|
||
"print(\"\\nСтатистическое описание данных:\")\n",
|
||
"print(df.describe())\n",
|
||
"\n",
|
||
"# 3. Построение графиков\n",
|
||
"\n",
|
||
"# Histplot для общего количества медалей\n",
|
||
"plt.figure(figsize=(8, 4))\n",
|
||
"sns.histplot(df[\"Total\"], kde=True, color=\"blue\") # Гистограмма по Total\n",
|
||
"plt.title(\"Распределение общего количества медалей\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Scatterplot: зависимость золотых медалей от общего количества медалей\n",
|
||
"plt.figure(figsize=(8, 4))\n",
|
||
"sns.scatterplot(x=\"Gold\", y=\"Total\", data=df) # Зависимость между золотыми и общими медалями\n",
|
||
"plt.title(\"Зависимость золотых медалей от общего количества\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Boxplot для отображения распределения по количеству золотых медалей\n",
|
||
"plt.figure(figsize=(20, 10))\n",
|
||
"sns.boxplot(x=\"Rank\", y=\"Gold\", data=df) # Boxplot по рангу и количеству золотых медалей\n",
|
||
"plt.title(\"Boxplot по рангу и количеству золотых медалей\")\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# 4. Использование tqdm для обработки больших данных\n",
|
||
"for index, row in tqdm(df.iterrows(), total=df.shape[0], desc=\"Обработка данных\"):\n",
|
||
" # Симуляция обработки данных\n",
|
||
" pass\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "2dcb5197-75fb-49d3-8bdf-47103653b6d1",
|
||
"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
|
||
}
|