422 lines
118 KiB
Plaintext
422 lines
118 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "4a61b008-0c4c-4ff1-b051-d5b6ad5c4573",
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"metadata": {},
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"source": [
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"Импорт библиотек"
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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": 1,
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"id": "2cdb6e5d-195a-43c6-a5be-da7b1b053e99",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"import seaborn as sns\n",
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"import matplotlib.pyplot as plt\n",
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"from tqdm import tqdm"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ecb168c5-c15c-429d-aede-3f6eeae16cb8",
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"metadata": {},
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"source": [
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"Загрузка 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": 2,
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"id": "ee94e091-5f48-45e8-b1dc-8f09ea0d5d72",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Country Name</th>\n",
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" <th>Country Code</th>\n",
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" <th>Year</th>\n",
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" <th>Value</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>Afghanistan</td>\n",
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" <td>AFG</td>\n",
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" <td>2000</td>\n",
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" <td>3.521418e+09</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>Afghanistan</td>\n",
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" <td>AFG</td>\n",
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" <td>2001</td>\n",
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" <td>2.813572e+09</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>Afghanistan</td>\n",
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" <td>AFG</td>\n",
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" <td>2002</td>\n",
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" <td>3.825701e+09</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>Afghanistan</td>\n",
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" <td>AFG</td>\n",
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" <td>2003</td>\n",
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" <td>4.520947e+09</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>Afghanistan</td>\n",
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" <td>AFG</td>\n",
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" <td>2004</td>\n",
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" <td>5.224897e+09</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" Country Name Country Code Year Value\n",
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"0 Afghanistan AFG 2000 3.521418e+09\n",
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"1 Afghanistan AFG 2001 2.813572e+09\n",
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"2 Afghanistan AFG 2002 3.825701e+09\n",
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"3 Afghanistan AFG 2003 4.520947e+09\n",
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"4 Afghanistan AFG 2004 5.224897e+09"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Загружаем данные\n",
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"df = pd.read_csv('gdp.csv')\n",
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"\n",
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"# Показываем первые строки\n",
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"df.head()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "31116b32-c883-4b9a-9deb-3f074b8d5589",
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"metadata": {},
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"source": [
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"Базовый анализ"
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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": "914d4769-8cf7-4fea-b62b-e731c9cb593d",
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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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"<class 'pandas.core.frame.DataFrame'>\n",
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"RangeIndex: 13979 entries, 0 to 13978\n",
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"Data columns (total 4 columns):\n",
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" # Column Non-Null Count Dtype \n",
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"--- ------ -------------- ----- \n",
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" 0 Country Name 13979 non-null object \n",
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" 1 Country Code 13979 non-null object \n",
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" 2 Year 13979 non-null int64 \n",
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" 3 Value 13979 non-null float64\n",
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"dtypes: float64(1), int64(1), object(2)\n",
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"memory usage: 437.0+ KB\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Year</th>\n",
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" <th>Value</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>count</th>\n",
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" <td>13979.000000</td>\n",
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" <td>1.397900e+04</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>mean</th>\n",
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" <td>1994.672866</td>\n",
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" <td>1.207380e+12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>std</th>\n",
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" <td>17.731413</td>\n",
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" <td>5.537517e+12</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>min</th>\n",
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" <td>1960.000000</td>\n",
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" <td>1.150263e+04</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>25%</th>\n",
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" <td>1980.000000</td>\n",
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" <td>2.233880e+09</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>50%</th>\n",
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" <td>1996.000000</td>\n",
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" <td>1.672591e+10</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>75%</th>\n",
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" <td>2010.000000</td>\n",
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" <td>2.058542e+11</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>max</th>\n",
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" <td>2023.000000</td>\n",
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" <td>1.054350e+14</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" Year Value\n",
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"count 13979.000000 1.397900e+04\n",
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"mean 1994.672866 1.207380e+12\n",
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"std 17.731413 5.537517e+12\n",
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"min 1960.000000 1.150263e+04\n",
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"25% 1980.000000 2.233880e+09\n",
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"50% 1996.000000 1.672591e+10\n",
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"75% 2010.000000 2.058542e+11\n",
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"max 2023.000000 1.054350e+14"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Общая информация\n",
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"df.info()\n",
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"\n",
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"# Описательная статистика\n",
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"df.describe()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "13fb0df4-a42f-4393-bb8c-09b5fc63baac",
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"metadata": {},
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"source": [
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"Построение графиков"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e4ff5ab1-171d-4187-91a0-a9b048e27d75",
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"metadata": {},
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"source": [
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"Гистограмма (histplot) – распределение ВВП"
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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": 4,
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"id": "6877e0cf-1e37-4d02-90be-80daf0124acf",
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"metadata": {},
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"outputs": [
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{
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"data": {
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",
|
||
"text/plain": [
|
||
"<Figure size 1000x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.figure(figsize=(10,6))\n",
|
||
"sns.histplot(df['Value'], bins=30, kde=True)\n",
|
||
"plt.title('Распределение ВВП')\n",
|
||
"plt.xlabel('ВВП (в долларах)')\n",
|
||
"plt.ylabel('Количество стран')\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "3cc4c71c-b0be-4b5a-b58b-a93eae56602d",
|
||
"metadata": {},
|
||
"source": [
|
||
"Точечный график (scatterplot) – год vs ВВП"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"id": "159e026b-b9d4-4d0a-bbf7-64cf2a4d2c02",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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O/fv3D6imdjzsdrveeOMN3XrrrZo3b56Sk5N1+eWXa8qUKaarLx06dFCHDh1Mv4fNZmuy6IKZ5ORkPfXUUxo2bJgeeeQR3XrrrZo0aZIqKir0xBNP6O2331afPn20dOlSLV++PODmuc35z3/+4y+0YLPZ1LFjR1188cWaNWtWk1vVZs6cGTCmM844Q4899liz8xZuKSkpWr16taZNm6Znn31WVVVV6tWrl5YsWRK0ArhkyRLl5eXpT3/6k+68805lZGRo0KBBuuCCC/x95s6dq+7du2vRokWaMWOGHA6H8vLyAgpSNLrvvvuCfj8ebYzfv/kxAEQjm9HczRniiM1m06uvvuq/xuDf//63evXqpZKSEv+WkeY03mywqZLmzz//vK699lq98MILuuyyy0I8cgDRateuXerevbtWrVrlLzpzPP0AAED4xPWKk8fj0eeff+5/vHPnTpWWlqpTp07q2bOnrrrqKk2YMEEPPPCABgwYoP379+vdd99VXl6exowZI0n67LPP5PV6deDAAVVXV6u0tFSS/J9WLlu2TBMnTtTDDz+s8847TxUVFZKOfAJndq8TAAAAANYQ1ytOq1ev1rBhw4KOT5w4UYWFhfL5fPr973+vP//5z/r666/ldDp1/vnna86cOTrrrLMkHbmBYuN9Mr6r8W0dOnSo/waETX0PAPHL5XLp9ttv14wZM5otLtDSfgAAIHziOjgBAAAAQEtQjhwAAAAATBCcAAAAAMBE3BWHaGhoUHl5udLS0kxvwAgAAAAgdhmGoerqauXk5Cghofk1pbgLTuXl5erWrVukhwEAAADAIr766iuddNJJzfaJu+DUeBf1r776KmJ3eo8mPp9P77zzjkaOHCm73R7p4cQ95sN6mBPrYU6shfmwHubEepiTyKmqqlK3bt38GaE5cRecGrfnpaenE5xawOfzyeFwKD09nR9kC2A+rIc5sR7mxFqYD+thTqyHOYm8llzCQ3EIAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAE+0jPQAAAIBY4a71yuXxqqrOp/QUu5wdEpXhSIz0sACEAMEJAAAgBMorD+ruos1aW+byH8vPdWp+QZ5yMlMiODIAocBWPQAAgOPkrvUGhSZJKilzaVrRZrlrvREaGYBQITgBAAAcJ5fHGxSaGpWUueTyEJyAaEdwAgAAOE5Vdb5m26tN2gFYH9c4AQAAHKf0ZHuz7Wkm7YBVUfDkvwhOAAAAx8mZmqj8XKdKmtiul5/rlDM1Pv/QRHSj4EkgtuoBAAAcpwxHouYX5Ck/1xlwPD/XqQUFeXH7CT2iFwVPgrHiBAAAEAI5mSlaNH6AXB6vqut8Sku2y5kav9uaEN1aUvAk3v5tE5wAAABCJMNBUEJsoOBJMLbqAQAAAAhAwZNgBCcAAAAAARoLnjQlXgueEJwAAAAABKDgSTCucQIAAAAQhIIngQhOAAAAAJpEwZP/YqseAAAAAJggOAEAAACACbbqAQCAuOWu9crl8aqqzqf0FLucHdiWBKBpBCcAABCXyisP6u6izVpb5vIfy891an5BnnIyUyI4MgBWxFY9AAAQd9y13qDQJEklZS5NK9osd603QiMDYFUEJwAAEHdcHm9QaGpUUuaSy0NwAhCI4AQAAOJOVZ2v2fZqk3YA8YfgBAAA4k56sr3Z9jSTdgDxh+AEAADijjM1Ufm5zibb8nOdcqZSWQ9AIIITAACIOxmORM0vyAsKT/m5Ti0oyKMkOYAglCMHAABxKSczRYvGD5DL41V1nU9pyXY5U7mPE4CmEZwAAEDcynAQlAC0DFv1AAAAAMAEwQkAAAAATBCcAAAAAMAEwQkAAAAATBCcAAAAAMAEwQkAAAAATBCcAAAAAMAEwQkAAAAATBCcAAAAAMAEwQkAAAAATBCcAAAAAMAEwQkAAAAATBCcAAAAAMAEwQkAAAAATBCcAAAAAMAEwQkAAAAATBCcAAAAAMAEwQkAAAAATBCcAAAAAMBE+0gPAAAAAE1z13rl8nhVVedTeopdzg6JynAkRnpYQFwiOAEAAFhQeeVB3V20WWvLXP5j+blOzS/IU05mSgRHBsQntuoBAABYjLvWGxSaJKmkzKVpRZvlrvVGaGRA/GLFCQAARIV42rbm8niDQlOjkjKXXB5vzJ47YFUEJwAAYHnxtm2tqs7XbHu1STuA0GOrHgAAsLR43LaWnmxvtj3NpB1A6BGcAACApbVk21qscaYmKj/X2WRbfq5TzlS26QFtjeAEAAAsLR63rWU4EjW/IC8oPOXnOrWgII/rm4AI4BonAABgafG6bS0nM0WLxg+Qy+NVdZ1Pacl2OVNjtyAG4kM0F3khOAEAAEtr3LZW0sR2vVjftpbhiJ4/KgEz0V7kha16AADA0ti2BkS/WCjywooTAACwPLatAdEtFu5NFtEVp3nz5umcc85RWlqasrOzNW7cOG3fvt30ecuXL9cZZ5yh5ORknXXWWXrrrbfaYLQAACCSMhyJ6pGdqv4nd1SP7FTL/5EF4L9iochLRIPTmjVrNHnyZL3//vsqLi6Wz+fTyJEjVVNTc9TnvPfeexo/fryuu+46bdq0SePGjdO4ceO0devWNhw5AAAAgJaKhSIvEd2q9/e//z3gcWFhobKzs7Vx40bl5+c3+ZyHH35Yo0aN0p133ilJuueee1RcXKxHHnlEjz/+eNjHDAAAAKB1YqHIi6WucXK73ZKkTp06HbXPhg0bNHXq1IBjl1xyiVasWNFk//r6etXX1/sfV1VVSZJ8Pp98PusvCUZa43vEe2UNzIf1MCfWw5xYC/NhPcyJ9cTDnDjsNt17WR/Nen2r1u/4xn/8wh6dNffSPnLYbRE5/9Z8T5thGEYYx9JiDQ0NuvTSS1VZWal169YdtV9iYqKeffZZjR8/3n/s0Ucf1Zw5c7R3796g/rNnz9acOXOCji9btkwOhyM0gwcAAAAQdWpra/Wzn/1Mbrdb6enpzfa1zIrT5MmTtXXr1mZD07GYPn16wApVVVWVunXrppEjR5q+OTiSwouLizVixAjZ7dbfexrrmA/rYU6shzmxFubDepgT62FOIqdxN1pLWCI4TZkyRX/9619VUlKik046qdm+Xbt2DVpZ2rt3r7p27dpk/6SkJCUlJQUdt9vt/MNsBd4va2E+rIc5sR7mxFqYD+thTqyHOWl7rXm/I1pVzzAMTZkyRa+++qpWrlyp7t27mz5n8ODBevfddwOOFRcXa/DgweEaJgAAAIA4F9EVp8mTJ2vZsmV67bXXlJaWpoqKCklSRkaGUlJSJEkTJkzQiSeeqHnz5kmSbrvtNl188cV64IEHNGbMGL3wwgv6+OOP9eSTT0bsPAAAAADEtoiuOD322GNyu90aOnSoTjjhBP/Xiy++6O+ze/du7dmzx//4ggsu0LJly/Tkk0+qX79+evnll7VixQr17ds3EqcAAAAAIA5EdMWpJQX9Vq9eHXTsJz/5iX7yk5+EYUQAAAAAECyiK04AAAAAEA0ITgAAAABgguAEAAAAACYITgAAAABgguAEAAAAACYITgAAAABgguAEAAAAACYITgAAAABgguAEAAAAACYITgAAAABgguAEAAAAACYITgAAAABgguAEAAAAACYITgAAAABgguAEAAAAACYITgAAAABgguAEAAAAACYITgAAAABgguAEAAAAACYITgAAAABgguAEAAAAACbaR3oAAAAAAELDXeuVy+NVVZ1P6Sl2OTskKsORGOlhxQSCEwAAABADyisP6u6izVpb5vIfy891an5BnnIyUyI4stjAVj0AAAAgyrlrvUGhSZJKylyaVrRZ7lpvhEYWOwhOAAAAQJRzebxBoalRSZlLLg/B6XgRnAAAAIAoV1Xna7a92qQd5ghOAAAAQJRLT7Y3255m0g5zBCcAAAAgyjlTE5Wf62yyLT/XKWcqlfWOF8EJAAAAiHIZjkTNL8gLCk/5uU4tKMijJHkIUI4cAAAAiAE5mSlaNH6AXB6vqut8Sku2y5nKfZxCheAEAAAAxIgMB0EpXNiqBwAAAAAmCE4AAAAAYILgBAAAAAAmCE4AAAAAYILgBAAAAAAmCE4AAAAAYILgBAAAAAAmCE4AAAAAYILgBAAAAAAmCE4AAAAAYILgBAAAAAAmCE4AAAAAYILgBAAAAAAmCE4AAAAAYILgBAAAAAAmCE4AAAAAYILgBAAAAAAmCE4AAAAAYILgBAAAAAAmCE4AAAAAYKJ9pAcAAAAARAt3rVcuj1dVdT6lp9jl7JCoDEdipIeFNkBwAgAAAFqgvPKg7i7arLVlLv+x/Fyn5hfkKSczJYIjQ1tgqx4AAABgwl3rDQpNklRS5tK0os1y13ojNDK0FYITAAAAYMLl8QaFpkYlZS65PASnWEdwAgAAAExU1fmaba82aUf0IzgBAAAAJtKT7c22p5m0I/oRnAAAiFLuWq927PNo0+5vtWO/h2ssgDBypiYqP9fZZFt+rlPOVCrrxTqq6gEAEIWo7gWYC2Xp8AxHouYX5Gla0WaVfO/nbkFBHiXJ4wDBCQCAKGNW3WvR+AH8EYe4F44PF3IyU7Ro/AC5PF5V1/mUlmyXM5X7OMULtuoBABBlqO4FNC+cpcMzHInqkZ2q/id3VI/sVEJTHCE4AQAQZajuBTSPDxcQDgQnAACiDNW9gObx4QLCgeAEAECUoboX0Dw+XEA4EJwAAIgyjdW9vh+eqO4FHMGHCwgHquoBABCFqO4FHB2lwxEOBCcAAKJUhoOgBBwNHy4g1AhOAAAAiEl8uIBQ4honAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADDBfZwAAABgCe5ar1wer6rqfEpPscvZgfswwToITgAAAIi48sqDurtos9aWufzH8nOdml+Qp5zMlAiODDiCrXoAAACIKHetNyg0SVJJmUvTijbLXeuN0MiA/yI4AQAAIKJcHm9QaGpUUuaSy0NwQuQRnAAAABBRVXW+ZturTdqBtkBwAgAAQESlJ9ubbU8zaQfaAsEJAAAAEeVMTVR+rrPJtvxcp5ypVNZD5BGcAAAAEFEZjkTNL8gLCk/5uU4tKMijJDksgXLkAAAAiLiczBQtGj9ALo9X1XU+pSXb5UzlPk6wDoITAAAIC3etV3srayVJO1016pLh4I9gNCvDQVCCdbFVDwAAhFx55UFNeX6Txi5eJ0ka+8g63fL8JpVXHozwyADg2BCcAABASHEzUwCxiOAEAABCipuZAohFBCcAABBS3MwUQCwiOAEAgJDiZqYAYlFEg1NJSYnGjh2rnJwc2Ww2rVixotn+q1evls1mC/qqqKhomwEDAABT3MwUQCyKaHCqqalRv379tHjx4lY9b/v27dqzZ4//Kzs7O0wjBAAArcXNTIGWc9d6tXN/jaQjZfspnmJdEb2P0+jRozV69OhWPy87O1uZmZkt6ltfX6/6+nr/46qqKkmSz+eTz8ceazON7xHvlTUwH9bDnFgPc2INWR3aa+FP+mqf+6D+/cl6rbj5fGVnpCg9pT1zE2H8jFhHhbtOM1/fqo07XbpnkPQ/j67VoO5Ozbm0r7pmJEd6eHGhNT8HNsMwjDCOpcVsNpteffVVjRs37qh9Vq9erWHDhumUU05RfX29+vbtq9mzZ+vCCy886nNmz56tOXPmBB1ftmyZHA5HKIYOAAAAIArV1tbqZz/7mdxut9LT05vtG1XBafv27Vq9erUGDRqk+vp6Pf3003ruuef0wQcf6Oyzz27yOU2tOHXr1k0ul8v0zcGRFF5cXKwRI0bIbudi3khjPqyHObEe5sRamA/rYU6sYef+Gv8NopMSDN0zqEG/+zhB9Q02SdIbky9S96wOkRxiXKiqqpLT6WxRcIroVr3W6tWrl3r16uV/fMEFF2jHjh1auHChnnvuuSafk5SUpKSkpKDjdrud/1m0Au+XtTAf1sOcWA9zYi3Mh/UwJ5FVc8hQ/WFbwLH6Bpv/WO0hg/lpA615j6O+HPm5556rzz//PNLDAAAAAFqMsv3RJ+qDU2lpqU444YRIDwMAAABoMcr2R5+IbtXzeDwBq0U7d+5UaWmpOnXqpJNPPlnTp0/X119/rT//+c+SpIceekjdu3fXmWeeqbq6Oj399NNauXKl3nnnnUidAgAAANBqjWX7pxVt1gdf7Pcfp2y/dUU0OH388ccaNmyY//HUqVMlSRMnTlRhYaH27Nmj3bt3+9u9Xq/uuOMOff3113I4HMrLy9M//vGPgNcAAAAAokFOZooWjR+gvZW12vbRGr0x+SJ1yXQQmiwqosFp6NChaq6oX2FhYcDju+66S3fddVeYRwUAAAC0jQxHohx2m7ZJ6p7VgYIQFhb11zgBAAAAQLgRnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAgTrhrvdq5v0aStNNVI3etN8IjAqIHwQkAACAOlFce1JTnN2ns4nWSpLGPrNMtz29SeeXBCI8MiA4EJwAAgBjnrvXq7qLNWlvmCjheUubStKLNrDwBLUBwAgAAiHEujzcoNDUqKXPJ5SE4AWYITgAAADGuqs7XbHu1STsAghMAAEDMS0+2N9ueZtIOgOAEAAAQ85ypicrPdTbZlp/rlDM1sY1HBEQfghMAAECMy3Akan5BXlB4ys91akFBnjIcBCfATPtIDwAAAADhl5OZokXjB2hvZa22fbRGb0y+SF0yHYQmoIUITgAAAHEiw5Eoh92mbZK6Z3WQ3c61TUBLsVUPAAAAAEwQnAAAAADABMEJAAAAAExwjRMAAG3EXeuVy+NVVZ1P6Sl2OTskcmE+AEQJghMAAG2gvPKg7i7arLVlLv+x/Fyn5hfkKSczJYIjAwC0BFv1AAAIM3etNyg0SVJJmUvTijbLXeuN0MgAAC1FcAIAIMxcHm9QaGpUUuaSy0NwAgCra9VWvddff71F/S699NJjGgwAALGoqs7XbHu1STtgVVy3h3jSquA0btw40z42m02HDx8+1vEAABBz0pObv8lomkk7YEVct4d40+qtehUVFWpoaDjqF6EJAIBAztRE5ec6m2zLz3XKmcon9IguXLeHeMQ1TgAAhFmGI1HzC/KCwlN+rlMLCvLY2oSow3V7iEeUIwcAoA3kZKZo0fgBcnm8qq7zKS3ZLmcq14MgOnHdHuIRwQkAgDaS4SAoITZw3R7iUau26tlsNtlstnCNBQAAAFGA6/YQj1q14mQYhnr27Gkang4cOHBcgwIAAIB1NV63N61os0q+V1WP6/YQq1oVnJYsWRKucQAAACCKcN0e4k2rgtPEiRPDNQ4AAABEGa7bQzwJSTnyL774Qp9++qkaGhpC8XIAAAAAYCmtCk5er1ezZs3S2LFjde+99+rw4cMaP368cnNzlZeXp759+2rXrl1hGioAAAgnd61XO/Z5tGn3t9qx38NNTAHgO1q1VW/69Ol67rnndNlll+mZZ57Rhx9+qO3bt2vZsmVKSEjQPffcoxkzZugvf/lLuMYLAADCoLzyoO4u2hxwU9P8XKfmF+QpJzMlgiMDAGtoVXB6+eWXVVhYqB/96Ef697//rTPOOENvvvmmRo8eLUnKzs7WVVddFZaBAgCA8HDXeoNCkySVlLk0rWizFo0fwHUsAOJeq7bqlZeXq1+/fpKknj17KikpSaeffrq/vWfPnqqoqAjtCAEAQFi5PN6g0NSopMwll4ctewDQquB0+PBh2e3/vRN0+/bt1a5du/++WEKCDMMI3egAAEDYVdX5mm2vNmkHgHjQqq16kvT2228rIyNDktTQ0KB3331XW7dulSRVVlaGdHAAACD80pPtzbanmbQDQDxodXD6/r2cbrrppoDHNpvt+EYEAADalDM1Ufm5TpU0sV0vP9cpZyrXNwFAq7bqNTQ0mH4dPnw4XGMFAABhkOFI1PyCPOXnOgOO5+c6taAgj8IQAKBjWHGSpG+++UadO3eWJH311Vd66qmnVFdXp7Fjx2rIkCEhHSAAAAi/nMwULRo/QC6PV9V1PqUl2+VMTSQ0AcD/16rgtGXLFo0dO1ZfffWVcnNz9cILL2jUqFGqqalRQkKCHnzwQb388ssaN25cmIYLAADCJcNBUAKAo2nVVr277rpLZ511lkpKSjR06FD9+Mc/1pgxY+R2u/Xtt9/qpptu0vz588M1VgAAAACIiFatOH300UdauXKl8vLy1K9fPz355JP65S9/qYSEI/nrlltu0fnnnx+WgQIAAABApLRqxenAgQPq2rWrJCk1NVUdOnRQx44d/e0dO3ZUdXV1aEcIAAAAABHWquAkBZcbp/w4AAAAgFjX6qp6kyZNUlJSkiSprq5ON998szp06CBJqq+vD+3oAAAAAMACWhWcvn/z25///OdBfSZMmHB8IwIAAAAAi2lVcFqyZEm4xgEAAAAAltXqa5wAAAAAIN4QnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADABMEJAAAAAEwQnAAAAADARESDU0lJicaOHaucnBzZbDatWLHC9DmrV6/W2WefraSkJJ1++ukqLCwM+zgBAAAAxLeIBqeamhr169dPixcvblH/nTt3asyYMRo2bJhKS0t1++236/rrr9fbb78d5pECAAAAiGftI/nNR48erdGjR7e4/+OPP67u3bvrgQcekCT17t1b69at08KFC3XJJZeEa5gAgDjlrvXK5fGqqs6n9BS7nB0SleFIjPSwAAARENHg1FobNmzQ8OHDA45dcskluv3224/6nPr6etXX1/sfV1VVSZJ8Pp98Pl9YxhlLGt8j3itrYD6shzmxnlDNSYW7TjNf36r3dnzjP3Zhj86ac2lfdc1IPq7Xjif8jFgPc2I9zEnktOY9j6rgVFFRoS5dugQc69Kli6qqqnTw4EGlpKQEPWfevHmaM2dO0PF33nlHDocjbGONNcXFxZEeAr6D+bAe5sR6QjEn4zof+fqvffpk/crjft14xM+I9TAn1sOctL3a2toW942q4HQspk+frqlTp/ofV1VVqVu3bho5cqTS09MjOLLo4PP5VFxcrBEjRshut0d6OHGP+bAe5sR6QjEnO/fXaOzidUdtf2PyReqe1eFYhxhX+BmxHubEepiTyGncjdYSURWcunbtqr179wYc27t3r9LT05tcbZKkpKQkJSUlBR232+38w2wF3i9rYT6shzmxnuOZk5pDhuoP247aXnvIYL5biZ8R62FOrIc5aXuteb+j6j5OgwcP1rvvvhtwrLi4WIMHD47QiAAAsSg9uflfpGkm7QCA2BPR4OTxeFRaWqrS0lJJR8qNl5aWavfu3ZKObLObMGGCv//NN9+sL774QnfddZf+9a9/6dFHH9VLL72kX/3qV5EYPgAgRjlTE5Wf62yyLT/XKWcqlfUAIN5ENDh9/PHHGjBggAYMGCBJmjp1qgYMGKCZM2dKkvbs2eMPUZLUvXt3vfnmmyouLla/fv30wAMP6Omnn6YUOQAgpDIciZpfkBcUnvJznVpQkEdJcgCIQxG9xmno0KEyDOOo7YWFhU0+Z9OmTWEcFQAAUk5mihaNHyCXx6vqOp/Sku1ypnIfJwCIV1FVHAIAgLaU4SAoAQCOiKriEAAAAAAQCQQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAEDMcNd6tXN/jSRpp6tG7lpvhEcEAIgVBCcAQEworzyoKc9v0tjF6yRJYx9Zp1ue36TyyoMRHhkAIBYQnAAAUc9d69XdRZu1tswVcLykzKVpRZtZeQIAHDeCEwAg6rk83qDQ1KikzCWXh+AEADg+BCcAQNSrqvM1215t0g4AgBmCEwAg6qUn25ttTzNpBwDADMEJABD1nKmJys91NtmWn+uUMzWxjUcEAIg1BCcAQNTLcCRqfkFeUHjKz3VqQUGeMhwEJwDA8Wkf6QEAABAKOZkpWjR+gPZW1mrbR2v0xuSL1CXTQWgCAIQEwQkAEDMyHIly2G3aJql7VgfZ7VzbBAAIDbbqAQAAAIAJghMAAAAAmCA4AQAAAIAJghMAAAAAmCA4AQAAAIAJghMAAAAAmCA4AQAAAIAJghMAAAAAmCA4AQAAAIAJghMAAAAAmCA4AQAAAIAJghMAAAAAmCA4AQAAAIAJghMAAAAAmCA4AQAAAIAJghMAAAAAmCA4AQAAAIAJghMAAAAAmCA4AQAAAIAJghMAAAAAmCA4AQAAAIAJghMAAAAAmCA4AQAAAIAJghMAAAAAmCA4AQAAAICJ9pEeAAAgfrlrvXJ5vKqq8yk9xS5nh0RlOBIjPSwAAIIQnAAAEVFeeVB3F23W2jKX/1h+rlPzC/KUk5kSwZEBABCMrXoAgDbnrvUGhSZJKilzaVrRZrlrvREaGQAATSM4AQDanMvjDQpNjUrKXHJ5CE4AAGshOAEA2lxVna/Z9mqTdgAA2hrBCQDQ5tKT7c22p5m0AwDQ1ghOAIA250xNVH6us8m2/FynnKlU1gMAWAvBKYLctV7t2OfRpt3fasd+DxdDA4gbGY5EzS/ICwpP+blOLSjIoyQ5AMByKEceIZThBRDvcjJTtGj8ALk8XlXX+ZSWbJczlfs4AQCsiRWnCKAMLwAckeFIVI/sVPU/uaN6ZKcSmgAAlkVwigDK8AIAAADRheAUAZThBQAAAKILwSkCKMMLAAAARBeCUwRQhhcAAACILgSnCIiWMrzuWq927q+RJO101Rx30QrKrwMAACBaUY48QqxehrexXPqHX+zX/50rjX1knc47LeuYy6VTfh0AAADRjBWnCAp1Gd5QreiEulw65dcBAAAQ7VhxihGhXNFpSbn01oS8UL8eAAAA0NYsseK0ePFinXrqqUpOTtZ5552nDz/88Kh9CwsLZbPZAr6Sk5PbcLTWE+oVnVCXS6f8OgAAAKJdxIPTiy++qKlTp2rWrFn65JNP1K9fP11yySXat2/fUZ+Tnp6uPXv2+L++/PLLNhyx9YT6hrqhLpdO+XUAAABEu4gHpwcffFA33HCDrrnmGvXp00ePP/64HA6HnnnmmaM+x2azqWvXrv6vLl26tOGIrSfUKzqhLpdO+XUAAABEu4he4+T1erVx40ZNnz7dfywhIUHDhw/Xhg0bjvo8j8ejU045RQ0NDTr77LN133336cwzz2yyb319verr6/2Pq6qqJEk+n08+X2xsEevQ3qakdsZR2x3tba06V4fdpnsv66NZr2/VxzuPrGQlJRi6sEdnzb20jxz2Y3+99Tu+8R8/1teLZ43vE++XdTAn1sOcWAvzYT3MifUwJ5HTmvfcZhjG0f/iDrPy8nKdeOKJeu+99zR48GD/8bvuuktr1qzRBx98EPScDRs2qKysTHl5eXK73frDH/6gkpISffrppzrppJOC+s+ePVtz5swJOr5s2TI5HI7QnhAAAACAqFFbW6uf/exncrvdSk9Pb7Zv1FXVGzx4cEDIuuCCC9S7d2898cQTuueee4L6T58+XVOnTvU/rqqqUrdu3TRy5EjTNyeaVLjrjrKi01ddMo69eIbP51NxcbFGjBghu51rkSKN+bAe5sR6mBNrYT6shzmxHuYkchp3o7VERIOT0+lUu3bttHfv3oDje/fuVdeuXVv0Gna7XQMGDNDnn3/eZHtSUpKSkpKafF4s/cPs5rRr4f8ODNsNdWPt/Yp2zIf1MCfWw5xYC/NhPcyJ9TAnba8173dEi0MkJiZq4MCBevfdd/3HGhoa9O677wasKjXn8OHD2rJli0444YRwDTNqhPqGugAAAACOiPhWvalTp2rixIkaNGiQzj33XD300EOqqanRNddcI0maMGGCTjzxRM2bN0+SNHfuXJ1//vk6/fTTVVlZqfvvv19ffvmlrr/++kieBiLAXeuVy+NVVZ1P6Sl2OTuEboUNAAAA+K6IB6crr7xS+/fv18yZM1VRUaH+/fvr73//u7/E+O7du5WQ8N+FsW+//VY33HCDKioq1LFjRw0cOFDvvfee+vTpE6lTQASUVx4Muulvfq5T8wvylJOZEsGRAQAAIBZFPDhJ0pQpUzRlypQm21avXh3weOHChVq4cGEbjApW5a71BoUm6cjNfqcVbdai8QNYeQIAAEBIRfwGuEBruTzeoNDUqKTMJZfH28YjAgAAQKwjOCHqVNU1f6OyapN2AAAAoLUssVUPaI305ObLRqaZtB8NxSYAAABwNAQnRB1naqLyc50qaWK7Xn6uU87U1ocdik0A5vhwAQAQz9iqh6iT4UjU/II85ec6A47n5zq1oCCv1X/ImRWbcNdyzRRQXnlQU57fpB8+uEaXP/qefvjAGt3y/CaVVx6M9NAAAGgTrDghKuVkpmjR+AFyebyqrvMpLdkuZ+qxffrdkmITfKqOeEYlSwAACE6IYhmO0GwTotgE0Dw+XAAAgK16QNiKTQCxgg8XAAAgOAH+YhNNOdZiE/HKXevVjn0ebdr9rXbs93B9WIzgwwUAANiqB/iLTUwr2hxQqe9Yi03EKyoTxq5wVLIEACDaEJwAhbbYRKNQl25213q1t7JWkrTTVaMuGY7jDnWhGiPFA2IbHy4AAEBwAvxCVWxCCv3qS+PrffjFfv3fudLYR9bpvNOyjms1J5RjpHhA7AvHhwsAAEQTrnECQizU94UKx32mQv2aFA+IDxmORPXITlX/kzuqR3YqoQkAEFcITkCItWT1JZKvF47XpHgAAACIdQQnIMRCvfoSjtWcUL8mlQkBAECsIzgBIRbq1ZdwrOaE+jUbiwd8PzxRPAAAAMQKikMAIRbq0s3hKAUdjtekeAAAAIhlrDgBIRbq1ZdwrOaEa4WI4gEAACBWseIEhEGoV18aX29vZa22fbRGb0y+SF0yj+8+TqwQAQAAtBzBCQiTUN4XqvH1HHabtknqntVBdvvxV6oL9RgBAABiFcEJAGKUu9Yrl8erqjqf0lPscnYgKAMAcKwITgAQg8orDwbd5Dg/16n5BXnKyUyJ4MgAAIhOFIcAgBjjrvUGhSbpyM2NpxVtlru29TdNBgAg3hGcACDGuDzeoNDUqKTMJZeH4AQAQGsRnAAgxlTV+ZptrzZpBwAAwQhOABBj0pObr7iYZtIOAACCEZwAIMY4UxODbm7cKD/XKWcqlfUAAGgtghMAxJgMR6LmF+QFhaf8XKcWFORRkhwAgGNAOXIAsIhQ3ncpJzNFi8YPkMvjVXWdT2nJdjlTuY8TAADHiuAEABYQjvsuZTgISgAAhApb9QAgwrjvEgAA1kdwAoAI475LAABYH8EJACKM+y4BAGB9BCcAiDDuuwQAgPURnAAgwrjvEgAA1kdwAmBZ7lqvduzzaNPub7VjvydmiyRw3yUAAKyPcuQALCkc5bmtjPsuAQBgbaw4AbCcaCnP7a71auf+GknSTlfNcY8rw5GoHtmp6n9yR/XITiU0AQBgIQQnAJYTDeW5yysPasrzmzR28TpJ0thH1umW5zepvPJghEcGAADCgeAEwHKsXp47WlbEAABA6BCcAFiO1ctzR8OKGAAACC2CEwDLsXp5bquviAEAgNAjOAGwHKuX57b6ihgAAAg9ypEDsCQrl+duXBEraWK7nhVWxAAAQOix4gTAsqxantvqK2IAACD0WHECgGPQuCK2t7JW2z5aozcmX6QumQ5CEwAAMYrgBADHKMORKIfdpm2Sumd1kN3OtU0AAMQqtuoBAAAAgAmCEwAAAACYIDgBAAAAgAmucQIQN9y1Xrk8XlXV+ZSeYpezgzXKmwMAAOsjOAGIC+WVB3V30Wat/c69l/JznZpfkKeczJQIjgwAAEQDtuoBiHnuWm9QaJKkkjKXphVtlrvWG6GRAQCAaEFwAhDzXB5vUGhqVFLmkstDcAIAAM0jOAGIeVV1vmbbq03aAQAACE4AYl56cvM3pk0zaQcAACA4AYh5ztRE5ec6m2zLz3XKmUplPQAA0DyCE4CYl+FI1PyCvKDwlJ/r1IKCPEqSAwAAU5QjBxAXcjJTtGj8ALk8XlXX+ZSWbJczlfs4AQCAliE4AYgbGQ6CEgAAODZs1QMAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADDRPtIDaGuGYUiSqqqqIjyS6ODz+VRbW6uqqirZ7fZIDyfuMR/Ww5xYD3NiLcyH9TAn1sOcRE5jJmjMCM2Ju+BUXV0tSerWrVuERwIAAADACqqrq5WRkdFsH5vRkngVQxoaGlReXq60tDTZbLZID8fyqqqq1K1bN3311VdKT0+P9HDiHvNhPcyJ9TAn1sJ8WA9zYj3MSeQYhqHq6mrl5OQoIaH5q5jibsUpISFBJ510UqSHEXXS09P5QbYQ5sN6mBPrYU6shfmwHubEepiTyDBbaWpEcQgAAAAAMEFwAgAAAAATBCc0KykpSbNmzVJSUlKkhwIxH1bEnFgPc2ItzIf1MCfWw5xEh7grDgEAAAAArcWKEwAAAACYIDgBAAAAgAmCEwAAAACYIDgBAAAAgAmCUxwoKSnR2LFjlZOTI5vNphUrVgS07927V5MmTVJOTo4cDodGjRqlsrKygD47duzQ5ZdfrqysLKWnp+unP/2p9u7dG9DnwIEDuuqqq5Senq7MzExdd9118ng84T69qNNW83HqqafKZrMFfM2fPz/cpxeV5s2bp3POOUdpaWnKzs7WuHHjtH379oA+dXV1mjx5sjp37qzU1FQVFBQEvee7d+/WmDFj5HA4lJ2drTvvvFOHDh0K6LN69WqdffbZSkpK0umnn67CwsJwn17Uaav5WL16ddDPiM1mU0VFRZucZzQJ1ZzceuutGjhwoJKSktS/f/8mv9fmzZs1ZMgQJScnq1u3bvq///u/cJ1W1Gqr+di1a1eTPyPvv/9+OE8vKoViTv75z39q/Pjx6tatm1JSUtS7d289/PDDQd+L3yORQ3CKAzU1NerXr58WL14c1GYYhsaNG6cvvvhCr732mjZt2qRTTjlFw4cPV01Njf/5I0eOlM1m08qVK7V+/Xp5vV6NHTtWDQ0N/te66qqr9Omnn6q4uFh//etfVVJSohtvvLHNzjNatNV8SNLcuXO1Z88e/9ctt9zSJucYbdasWaPJkyfr/fffV3FxsXw+n0aOHOl/zyXpV7/6ld544w0tX75ca9asUXl5ua644gp/++HDhzVmzBh5vV699957evbZZ1VYWKiZM2f6++zcuVNjxozRsGHDVFpaqttvv13XX3+93n777TY9X6trq/lotH379oCfk+zs7DY5z2gSijlpdO211+rKK69s8vtUVVVp5MiROuWUU7Rx40bdf//9mj17tp588smwnVs0aqv5aPSPf/wj4Gdk4MCBIT+naBeKOdm4caOys7O1dOlSffrpp5oxY4amT5+uRx55xN+H3yMRZiCuSDJeffVV/+Pt27cbkoytW7f6jx0+fNjIysoynnrqKcMwDOPtt982EhISDLfb7e9TWVlp2Gw2o7i42DAMw/jss88MScZHH33k7/O3v/3NsNlsxtdffx3ms4pe4ZoPwzCMU045xVi4cGHYzyEW7du3z5BkrFmzxjCMI++v3W43li9f7u+zbds2Q5KxYcMGwzAM46233jISEhKMiooKf5/HHnvMSE9PN+rr6w3DMIy77rrLOPPMMwO+15VXXmlccskl4T6lqBau+Vi1apUhyfj222/b7mRixLHMyXfNmjXL6NevX9DxRx991OjYsaN/jgzDMO6++26jV69eoT+JGBKu+di5c6chydi0aVO4hh6zjndOGv3yl780hg0b5n/M75HIYsUpztXX10uSkpOT/ccSEhKUlJSkdevW+fvYbLaAm7IlJycrISHB32fDhg3KzMzUoEGD/H2GDx+uhIQEffDBB21xKjEhVPPRaP78+ercubMGDBig+++/P2jbGJrmdrslSZ06dZJ05FNAn8+n4cOH+/ucccYZOvnkk7VhwwZJR34GzjrrLHXp0sXf55JLLlFVVZU+/fRTf5/vvkZjn8bXQNPCNR+N+vfvrxNOOEEjRozQ+vXrw306MeFY5qQlNmzYoPz8fCUmJvqPXXLJJdq+fbu+/fbbEI0+9oRrPhpdeumlys7O1kUXXaTXX389NIOOcaGaE7fb7X8Nid8jkUZwinONP7TTp0/Xt99+K6/XqwULFug///mP9uzZI0k6//zz1aFDB919992qra1VTU2Nfv3rX+vw4cP+PhUVFUHbW9q3b69OnTpxvUArhGo+pCN711944QWtWrVKN910k+677z7dddddkTq1qNHQ0KDbb79dF154ofr27SvpyL/vxMREZWZmBvTt0qWL/993RUVFwB/pje2Nbc31qaqq0sGDB8NxOlEvnPNxwgkn6PHHH1dRUZGKiorUrVs3DR06VJ988kmYzyq6HeuctERL5g2BwjkfqampeuCBB7R8+XK9+eabuuiiizRu3DjCk4lQzcl7772nF198MeCyB36PRFb7SA8AkWW32/XKK6/ouuuuU6dOndSuXTsNHz5co0ePlmEYkqSsrCwtX75cv/jFL/THP/5RCQkJGj9+vM4++2wlJJC9QymU8zF16lT/f+fl5SkxMVE33XST5s2bF7BahUCTJ0/W1q1bg1bvEBnhnI9evXqpV69e/scXXHCBduzYoYULF+q5554L+feLFfyMWEs458PpdAb8LjnnnHNUXl6u+++/X5deemnIv1+sCMWcbN26VZdddplmzZqlkSNHhnB0OB4EJ2jgwIEqLS2V2+2W1+tVVlaWzjvvvIBtdyNHjtSOHTvkcrnUvn17ZWZmqmvXrjrttNMkSV27dtW+ffsCXvfQoUM6cOCAunbt2qbnE+1CMR9NOe+883To0CHt2rUr4I9F/NeUKVP8hU1OOukk//GuXbvK6/WqsrIy4NPCvXv3+v99d+3aVR9++GHA6zVWS/pun+9Xtdq7d6/S09OVkpISjlOKauGej6ace+65BIJmHM+ctMTRfkYa2xAo3PPRlPPOO0/FxcXH9RqxLBRz8tlnn+mHP/yhbrzxRv32t78NaOP3SGSxXAC/jIwMZWVlqaysTB9//LEuu+yyoD5Op1OZmZlauXKl9u3b5//EafDgwaqsrNTGjRv9fVeuXKmGhgadd955bXYOseR45qMppaWlSkhIoGJYEwzD0JQpU/Tqq69q5cqV6t69e0D7wIEDZbfb9e677/qPbd++Xbt379bgwYMlHfkZ2LJlS8AHCMXFxUpPT1efPn38fb77Go19Gl8DR7TVfDSltLRUJ5xwQojPKPqFYk5aYvDgwSopKZHP5/MfKy4uVq9evdSxY8fjP5EY0Vbz0RR+RpoWqjn59NNPNWzYME2cOFH33ntv0Pfh90iERbAwBdpIdXW1sWnTJmPTpk2GJOPBBx80Nm3aZHz55ZeGYRjGSy+9ZKxatcrYsWOHsWLFCuOUU04xrrjiioDXeOaZZ4wNGzYYn3/+ufHcc88ZnTp1MqZOnRrQZ9SoUcaAAQOMDz74wFi3bp2Rm5trjB8/vs3OM1q0xXy89957xsKFC43S0lJjx44dxtKlS42srCxjwoQJbXqu0eIXv/iFkZGRYaxevdrYs2eP/6u2ttbf5+abbzZOPvlkY+XKlcbHH39sDB482Bg8eLC//dChQ0bfvn2NkSNHGqWlpcbf//53Iysry5g+fbq/zxdffGE4HA7jzjvvNLZt22YsXrzYaNeunfH3v/+9Tc/X6tpqPhYuXGisWLHCKCsrM7Zs2WLcdtttRkJCgvGPf/yjTc83GoRiTgzDMMrKyoxNmzYZN910k9GzZ0///wsbq+hVVlYaXbp0Ma6++mpj69atxgsvvGA4HA7jiSeeaNPztbq2mo/CwkJj2bJlxrZt24xt27YZ9957r5GQkGA888wzbXq+0SAUc7JlyxYjKyvL+PnPfx7wGvv27fP34fdIZBGc4kBjyd3vf02cONEwDMN4+OGHjZNOOsmw2+3GySefbPz2t78NKAVrGEfKwXbp0sWw2+1Gbm6u8cADDxgNDQ0Bfb755htj/PjxRmpqqpGenm5cc801RnV1dVudZtRoi/nYuHGjcd555xkZGRlGcnKy0bt3b+O+++4z6urq2vJUo0ZT8yHJWLJkib/PwYMHjV/+8pdGx44dDYfDYVx++eXGnj17Al5n165dxujRo42UlBTD6XQad9xxh+Hz+QL6rFq1yujfv7+RmJhonHbaaQHfA0e01XwsWLDA6NGjh5GcnGx06tTJGDp0qLFy5cq2Os2oEqo5ufjii5t8nZ07d/r7/POf/zQuuugiIykpyTjxxBON+fPnt9FZRo+2mo/CwkKjd+/ehsPhMNLT041zzz03oJw2/isUczJr1qwmX+OUU04J+F78Hokcm2H8/yvOAQAAAABN4honAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAEDMmDRpkmw2W9DX9ddfH+mhAQCiXPtIDwAAgFAaNWqUlixZEnDM4XBEaDQAgFjBihMAIKYkJSWpa9euAV/p6emSpKKiIp155plKSkrSqaeeqgceeCDo+YWFhUErVv3792/jswAAWA3BCQAQFzZu3Kif/vSn+t///V9t2bJFs2fP1u9+9zsVFhYG9U1PT9eePXu0Z88e3XHHHW0/WACA5bBVDwAQFx588EH98Ic/1O9+9ztJUs+ePfXZZ5/p/vvv16RJk/z96uvrlZiYqK5du0qSUlNTIzFcAIDFsOIEAIgL27Zt04UXXhhw7MILL1RZWZkOHz7sP/bNN9/4t/YBANCI4AQAwHd88cUX6t69e6SHAQCwGIITACAu9O7dW+vXrw84tn79evXs2VPt2rXzHyspKdGQIUPaengAAIvjGicAQFy44447dM455+iee+7RlVdeqQ0bNuiRRx7Ro48+Kkk6ePCgnn76ae3YsUOjR49WRUWFJMnj8ejQoUM6cOCAOnXqFMlTAABEkM0wDCPSgwAAIBQmTZqkyspKrVixosn2oqIizZw5U2VlZTrhhBN0yy236Ne//rWkI2XIr7nmmqO+9sUXX6zVq1eHYdQAgGhAcAIAQEeC0+rVq5ssT15aWqrbb7+d4AQAcYxrnAAAkJSSkqKMjIwm2+x2O9v0ACDOseIEAAAAACZYcQIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADBBcAIAAAAAEwQnAAAAADDx/wA6ofnuHLle/AAAAABJRU5ErkJggg==",
|
||
"text/plain": [
|
||
"<Figure size 1000x600 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Возьмём одну страну для наглядности\n",
|
||
"country_data = df[df['Country Name'] == 'Russian Federation']\n",
|
||
"\n",
|
||
"plt.figure(figsize=(10,6))\n",
|
||
"sns.scatterplot(data=country_data, x='Year', y='Value')\n",
|
||
"plt.title('Динамика ВВП России')\n",
|
||
"plt.xlabel('Год')\n",
|
||
"plt.ylabel('ВВП')\n",
|
||
"plt.grid(True)\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "c5415e8e-4b8f-4248-b918-3c0391cec943",
|
||
"metadata": {},
|
||
"source": [
|
||
"Boxplot – разброс ВВП по годам "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"id": "53f733b9-1f23-4422-8072-7d256a9f1032",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 1200x800 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Чтобы не перегружать график, возьмём подвыборку по годам\n",
|
||
"sampled_years = df[df['Year'].isin(range(2000, 2021, 5))]\n",
|
||
"\n",
|
||
"plt.figure(figsize=(12,8))\n",
|
||
"sns.boxplot(data=sampled_years, x='Year', y='Value')\n",
|
||
"plt.title('Разброс ВВП по годам')\n",
|
||
"plt.yscale('log') # Логарифмическая шкала для лучшего восприятия\n",
|
||
"plt.show()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"id": "960f5e83-0238-4766-86d7-743a4730c91e",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"100%|██████████████████| 100000/100000 [00:00<00:00, 4990961.23it/s]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from tqdm import tqdm\n",
|
||
"\n",
|
||
"# Пример обработки с прогресс-баром\n",
|
||
"for _ in tqdm(range(100000)):\n",
|
||
" pass # Здесь может быть тяжёлая операция"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "88aa9152-cb1b-4dcb-9a4f-a7f76ba2dc8a",
|
||
"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": "3.12.3"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|