From 770f3e7f3a607e055256b37e9dfde81a1b58b97b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=94=D0=BC=D0=B8=D1=82=D1=80=D0=B8=D0=B9?=
 <stud178860@vyatsu.ru>
Date: Fri, 16 May 2025 15:47:27 +0300
Subject: [PATCH] =?UTF-8?q?=D1=80=D0=B0=D0=B1=D0=BE=D1=82=D0=B0?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .gitignore                                    |    0
 .../week2_analysis-checkpoint.ipynb           | 1294 +++++++++++++++++
 .../week2_task-checkpoint.ipynb               |    6 +
 README.md                                     |    1 +
 data.csv                                      |    1 +
 week2_analysis.ipynb                          | 1294 +++++++++++++++++
 week2_task.ipynb                              |  222 +++
 7 files changed, 2818 insertions(+)
 create mode 100644 .gitignore
 create mode 100644 .ipynb_checkpoints/week2_analysis-checkpoint.ipynb
 create mode 100644 .ipynb_checkpoints/week2_task-checkpoint.ipynb
 create mode 100644 README.md
 create mode 100644 data.csv
 create mode 100644 week2_analysis.ipynb
 create mode 100644 week2_task.ipynb

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..e69de29
diff --git a/.ipynb_checkpoints/week2_analysis-checkpoint.ipynb b/.ipynb_checkpoints/week2_analysis-checkpoint.ipynb
new file mode 100644
index 0000000..7152115
--- /dev/null
+++ b/.ipynb_checkpoints/week2_analysis-checkpoint.ipynb
@@ -0,0 +1,1294 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "c033731f-63ff-45a1-9466-15886f15ae09",
+   "metadata": {},
+   "source": [
+    "Тестовый код"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "bf32d476-0486-4477-aab4-e86965882fdf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "9\n"
+     ]
+    }
+   ],
+   "source": [
+    "test = 4\n",
+    "test2 = 5\n",
+    "print(test + test2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8757d814-8118-4250-9fe6-8d4c847f4791",
+   "metadata": {},
+   "source": [
+    "Часть 3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "6e2f0daf-10fe-4892-8438-7a10f5cc05bd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первый взгляд на данные:\n",
+      "      Имя  Возраст  Баллы\n",
+      "0    Анна       21     89\n",
+      "1   Борис       22     76\n",
+      "2  Виктор       23     95\n",
+      "3  Галина       24     82\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4 entries, 0 to 3\n",
+      "Data columns (total 3 columns):\n",
+      " #   Column   Non-Null Count  Dtype \n",
+      "---  ------   --------------  ----- \n",
+      " 0   Имя      4 non-null      object\n",
+      " 1   Возраст  4 non-null      int64 \n",
+      " 2   Баллы    4 non-null      int64 \n",
+      "dtypes: int64(2), object(1)\n",
+      "memory usage: 228.0+ bytes\n",
+      "None\n",
+      "         Возраст      Баллы\n",
+      "count   4.000000   4.000000\n",
+      "mean   22.500000  85.500000\n",
+      "std     1.290994   8.266398\n",
+      "min    21.000000  76.000000\n",
+      "25%    21.750000  80.500000\n",
+      "50%    22.500000  85.500000\n",
+      "75%    23.250000  90.500000\n",
+      "max    24.000000  95.000000\n",
+      "Имя        0\n",
+      "Возраст    0\n",
+      "Баллы      0\n",
+      "dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Создадим DataFrame\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "print(\"Первый взгляд на данные:\")\n",
+    "print(df.head())\n",
+    "print(df.info())\n",
+    "print(df.describe())\n",
+    "print(df.isnull().sum())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3b801627-8797-4b4d-8f3d-c3ea9911e1bf",
+   "metadata": {},
+   "source": [
+    "Часть 3 с изменениями"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "f9b40974-e401-451a-8dcb-3aa296931280",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первый взгляд на данные:\n",
+      "      Имя  Возраст  Баллы\n",
+      "0    Анна       21     89\n",
+      "1   Борис       22     76\n",
+      "2  Виктор       23     95\n",
+      "3  Галина       24     82\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4 entries, 0 to 3\n",
+      "Data columns (total 3 columns):\n",
+      " #   Column   Non-Null Count  Dtype \n",
+      "---  ------   --------------  ----- \n",
+      " 0   Имя      4 non-null      object\n",
+      " 1   Возраст  4 non-null      int64 \n",
+      " 2   Баллы    4 non-null      int64 \n",
+      "dtypes: int64(2), object(1)\n",
+      "memory usage: 228.0+ bytes\n",
+      "None\n",
+      "         Возраст      Баллы\n",
+      "count   4.000000   4.000000\n",
+      "mean   22.500000  85.500000\n",
+      "std     1.290994   8.266398\n",
+      "min    21.000000  76.000000\n",
+      "25%    21.750000  80.500000\n",
+      "50%    22.500000  85.500000\n",
+      "75%    23.250000  90.500000\n",
+      "max    24.000000  95.000000\n",
+      "Имя        0\n",
+      "Возраст    0\n",
+      "Баллы      0\n",
+      "dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Имя</th>\n",
+       "      <th>Возраст</th>\n",
+       "      <th>Баллы</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Анна</td>\n",
+       "      <td>21</td>\n",
+       "      <td>89</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Борис</td>\n",
+       "      <td>22</td>\n",
+       "      <td>76</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Виктор</td>\n",
+       "      <td>23</td>\n",
+       "      <td>95</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Галина</td>\n",
+       "      <td>24</td>\n",
+       "      <td>82</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Имя  Возраст  Баллы\n",
+       "0    Анна       21     89\n",
+       "1   Борис       22     76\n",
+       "2  Виктор       23     95\n",
+       "3  Галина       24     82"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Создадим DataFrame\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "print(\"Первый взгляд на данные:\")\n",
+    "print(df.head())\n",
+    "print(df.info())\n",
+    "print(df.describe())\n",
+    "print(df.isnull().sum())\n",
+    "\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "9ee10d5f-ba28-45bd-9766-89491bb8d9a1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первый взгляд на данные:\n",
+      "      Имя  Возраст  Баллы  Новый столбец\n",
+      "0    Анна       21     89           97.9\n",
+      "1   Борис       22     76           83.6\n",
+      "2  Виктор       23     95          104.5\n",
+      "3  Галина       24     82           90.2\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4 entries, 0 to 3\n",
+      "Data columns (total 4 columns):\n",
+      " #   Column         Non-Null Count  Dtype  \n",
+      "---  ------         --------------  -----  \n",
+      " 0   Имя            4 non-null      object \n",
+      " 1   Возраст        4 non-null      int64  \n",
+      " 2   Баллы          4 non-null      int64  \n",
+      " 3   Новый столбец  4 non-null      float64\n",
+      "dtypes: float64(1), int64(2), object(1)\n",
+      "memory usage: 260.0+ bytes\n",
+      "None\n",
+      "         Возраст      Баллы  Новый столбец\n",
+      "count   4.000000   4.000000       4.000000\n",
+      "mean   22.500000  85.500000      94.050000\n",
+      "std     1.290994   8.266398       9.093038\n",
+      "min    21.000000  76.000000      83.600000\n",
+      "25%    21.750000  80.500000      88.550000\n",
+      "50%    22.500000  85.500000      94.050000\n",
+      "75%    23.250000  90.500000      99.550000\n",
+      "max    24.000000  95.000000     104.500000\n",
+      "Имя              0\n",
+      "Возраст          0\n",
+      "Баллы            0\n",
+      "Новый столбец    0\n",
+      "dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Имя</th>\n",
+       "      <th>Возраст</th>\n",
+       "      <th>Баллы</th>\n",
+       "      <th>Новый столбец</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Анна</td>\n",
+       "      <td>21</td>\n",
+       "      <td>89</td>\n",
+       "      <td>97.9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Борис</td>\n",
+       "      <td>22</td>\n",
+       "      <td>76</td>\n",
+       "      <td>83.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Виктор</td>\n",
+       "      <td>23</td>\n",
+       "      <td>95</td>\n",
+       "      <td>104.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Галина</td>\n",
+       "      <td>24</td>\n",
+       "      <td>82</td>\n",
+       "      <td>90.2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Имя  Возраст  Баллы  Новый столбец\n",
+       "0    Анна       21     89           97.9\n",
+       "1   Борис       22     76           83.6\n",
+       "2  Виктор       23     95          104.5\n",
+       "3  Галина       24     82           90.2"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Создадим DataFrame\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
+    "\n",
+    "print(\"Первый взгляд на данные:\")\n",
+    "print(df.head())\n",
+    "print(df.info())\n",
+    "print(df.describe())\n",
+    "print(df.isnull().sum())\n",
+    "\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "841cffd3-b0f4-4d76-918e-822044d8cda1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первый взгляд на данные:\n",
+      "      Имя  Возраст  Баллы  Новый столбец\n",
+      "0    Анна       21     89           97.9\n",
+      "1   Борис       22     76           83.6\n",
+      "2  Виктор       23     95          104.5\n",
+      "3  Галина       24     82           90.2\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4 entries, 0 to 3\n",
+      "Data columns (total 4 columns):\n",
+      " #   Column         Non-Null Count  Dtype  \n",
+      "---  ------         --------------  -----  \n",
+      " 0   Имя            4 non-null      object \n",
+      " 1   Возраст        4 non-null      int64  \n",
+      " 2   Баллы          4 non-null      int64  \n",
+      " 3   Новый столбец  4 non-null      float64\n",
+      "dtypes: float64(1), int64(2), object(1)\n",
+      "memory usage: 260.0+ bytes\n",
+      "None\n",
+      "         Возраст      Баллы  Новый столбец\n",
+      "count   4.000000   4.000000       4.000000\n",
+      "mean   22.500000  85.500000      94.050000\n",
+      "std     1.290994   8.266398       9.093038\n",
+      "min    21.000000  76.000000      83.600000\n",
+      "25%    21.750000  80.500000      88.550000\n",
+      "50%    22.500000  85.500000      94.050000\n",
+      "75%    23.250000  90.500000      99.550000\n",
+      "max    24.000000  95.000000     104.500000\n",
+      "Имя              0\n",
+      "Возраст          0\n",
+      "Баллы            0\n",
+      "Новый столбец    0\n",
+      "dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr:last-of-type th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Баллы</th>\n",
+       "      <th>Возраст</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>mean</th>\n",
+       "      <th>sum</th>\n",
+       "      <th>max</th>\n",
+       "      <th>min</th>\n",
+       "      <th>mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Баллы</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>76</th>\n",
+       "      <td>76.0</td>\n",
+       "      <td>76</td>\n",
+       "      <td>76</td>\n",
+       "      <td>76</td>\n",
+       "      <td>22.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>82</th>\n",
+       "      <td>82.0</td>\n",
+       "      <td>82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>24.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>89</th>\n",
+       "      <td>89.0</td>\n",
+       "      <td>89</td>\n",
+       "      <td>89</td>\n",
+       "      <td>89</td>\n",
+       "      <td>21.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>95.0</td>\n",
+       "      <td>95</td>\n",
+       "      <td>95</td>\n",
+       "      <td>95</td>\n",
+       "      <td>23.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Баллы             Возраст\n",
+       "       mean sum max min    mean\n",
+       "Баллы                          \n",
+       "76     76.0  76  76  76    22.0\n",
+       "82     82.0  82  82  82    24.0\n",
+       "89     89.0  89  89  89    21.0\n",
+       "95     95.0  95  95  95    23.0"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Создадим DataFrame\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
+    "\n",
+    "grouped_df = df.groupby(\"Баллы\").agg({\n",
+    "    \"Баллы\": [\"mean\", \"sum\", \"max\", \"min\"],\n",
+    "    \"Возраст\": \"mean\"\n",
+    "})\n",
+    "\n",
+    "print(\"Первый взгляд на данные:\")\n",
+    "print(df.head())\n",
+    "print(df.info())\n",
+    "print(df.describe())\n",
+    "print(df.isnull().sum())\n",
+    "\n",
+    "grouped_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "c7b256e1-c871-4131-bd8d-a0608a18ec28",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первый взгляд на данные:\n",
+      "      Имя  Возраст  Баллы  Новый столбец\n",
+      "0    Анна       21     89           97.9\n",
+      "1   Борис       22     76           83.6\n",
+      "2  Виктор       23     95          104.5\n",
+      "3  Галина       24     82           90.2\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4 entries, 0 to 3\n",
+      "Data columns (total 4 columns):\n",
+      " #   Column         Non-Null Count  Dtype  \n",
+      "---  ------         --------------  -----  \n",
+      " 0   Имя            4 non-null      object \n",
+      " 1   Возраст        4 non-null      int64  \n",
+      " 2   Баллы          4 non-null      int64  \n",
+      " 3   Новый столбец  4 non-null      float64\n",
+      "dtypes: float64(1), int64(2), object(1)\n",
+      "memory usage: 260.0+ bytes\n",
+      "None\n",
+      "         Возраст      Баллы  Новый столбец\n",
+      "count   4.000000   4.000000       4.000000\n",
+      "mean   22.500000  85.500000      94.050000\n",
+      "std     1.290994   8.266398       9.093038\n",
+      "min    21.000000  76.000000      83.600000\n",
+      "25%    21.750000  80.500000      88.550000\n",
+      "50%    22.500000  85.500000      94.050000\n",
+      "75%    23.250000  90.500000      99.550000\n",
+      "max    24.000000  95.000000     104.500000\n",
+      "Имя              0\n",
+      "Возраст          0\n",
+      "Баллы            0\n",
+      "Новый столбец    0\n",
+      "dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Имя</th>\n",
+       "      <th>Возраст</th>\n",
+       "      <th>Баллы</th>\n",
+       "      <th>Новый столбец</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Анна</td>\n",
+       "      <td>21</td>\n",
+       "      <td>89</td>\n",
+       "      <td>97.9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Борис</td>\n",
+       "      <td>22</td>\n",
+       "      <td>76</td>\n",
+       "      <td>83.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Виктор</td>\n",
+       "      <td>23</td>\n",
+       "      <td>95</td>\n",
+       "      <td>104.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Галина</td>\n",
+       "      <td>24</td>\n",
+       "      <td>82</td>\n",
+       "      <td>90.2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Имя  Возраст  Баллы  Новый столбец\n",
+       "0    Анна       21     89           97.9\n",
+       "1   Борис       22     76           83.6\n",
+       "2  Виктор       23     95          104.5\n",
+       "3  Галина       24     82           90.2"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Создадим DataFrame\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
+    "df[df[\"Возраст\"] > 21]\n",
+    "\n",
+    "print(\"Первый взгляд на данные:\")\n",
+    "print(df.head())\n",
+    "print(df.info())\n",
+    "print(df.describe())\n",
+    "print(df.isnull().sum())\n",
+    "\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fabc986b-9e8a-4fad-82cf-7e0d22e2d485",
+   "metadata": {},
+   "source": [
+    "Часть 3 - часть 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "5a137f99-a29a-4c32-8727-8fe71e93f82f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Сумма элементов массива: 15\n",
+      "Среднее значение: 3.0\n",
+      "Медиана: 3.0\n",
+      "Стандартное отклонение: 1.4142135623730951\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "arr = np.array([1, 2, 3, 4, 5])\n",
+    "print(\"Сумма элементов массива:\", np.sum(arr))\n",
+    "print(\"Среднее значение:\", np.mean(arr))\n",
+    "print(\"Медиана:\", np.median(arr))\n",
+    "print(\"Стандартное отклонение:\", np.std(arr))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "0bff7510-f22b-4335-9596-1ff30cb0f806",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Сумма элементов массива: 15\n",
+      "Среднее значение: 3.0\n",
+      "Медиана: 3.0\n",
+      "Стандартное отклонение: 1.4142135623730951\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([3.        , 3.02040816, 3.04081633, 3.06122449, 3.08163265,\n",
+       "       3.10204082, 3.12244898, 3.14285714, 3.16326531, 3.18367347,\n",
+       "       3.20408163, 3.2244898 , 3.24489796, 3.26530612, 3.28571429,\n",
+       "       3.30612245, 3.32653061, 3.34693878, 3.36734694, 3.3877551 ,\n",
+       "       3.40816327, 3.42857143, 3.44897959, 3.46938776, 3.48979592,\n",
+       "       3.51020408, 3.53061224, 3.55102041, 3.57142857, 3.59183673,\n",
+       "       3.6122449 , 3.63265306, 3.65306122, 3.67346939, 3.69387755,\n",
+       "       3.71428571, 3.73469388, 3.75510204, 3.7755102 , 3.79591837,\n",
+       "       3.81632653, 3.83673469, 3.85714286, 3.87755102, 3.89795918,\n",
+       "       3.91836735, 3.93877551, 3.95918367, 3.97959184, 4.        ])"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "arr = np.array([1, 2, 3, 4, 5])\n",
+    "print(\"Сумма элементов массива:\", np.sum(arr))\n",
+    "print(\"Среднее значение:\", np.mean(arr))\n",
+    "print(\"Медиана:\", np.median(arr))\n",
+    "print(\"Стандартное отклонение:\", np.std(arr))\n",
+    "\n",
+    "arr2 = np.array([[1, 2], [3, 4]])\n",
+    "np.linspace(3, 4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "01af748b-1dee-483d-be1d-39d9d39e2daf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Сумма элементов массива: 15\n",
+      "Среднее значение: 3.0\n",
+      "Медиана: 3.0\n",
+      "Стандартное отклонение: 1.4142135623730951\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "1.063095687089255"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "arr = np.array([1, 2, 3, 4, 5])\n",
+    "print(\"Сумма элементов массива:\", np.sum(arr))\n",
+    "print(\"Среднее значение:\", np.mean(arr))\n",
+    "print(\"Медиана:\", np.median(arr))\n",
+    "print(\"Стандартное отклонение:\", np.std(arr))\n",
+    "\n",
+    "arr2 = np.array([[1, 2], [3, 4]])\n",
+    "np.random.randn()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "6120edc2-d49b-42a8-bf34-606f0b465c63",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Сумма элементов массива: 15\n",
+      "Среднее значение: 3.0\n",
+      "Медиана: 3.0\n",
+      "Стандартное отклонение: 1.4142135623730951\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "np.int64(11)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "arr = np.array([1, 2, 3, 4, 5])\n",
+    "print(\"Сумма элементов массива:\", np.sum(arr))\n",
+    "print(\"Среднее значение:\", np.mean(arr))\n",
+    "print(\"Медиана:\", np.median(arr))\n",
+    "print(\"Стандартное отклонение:\", np.std(arr))\n",
+    "\n",
+    "arr2 = np.array([[1, 2], [3, 4]])\n",
+    "np.dot(arr2[0], arr2[1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "39a7b707-93dd-4586-958f-b4bfa5e23d9c",
+   "metadata": {},
+   "source": [
+    "Matplot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "03295aee-25dd-48b0-a88e-2182a1213171",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.plot(x, y, label='sin(x)')\n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"График синуса\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "264e7d30-72b9-4b2f-8d49-79df44406e84",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.plot(x, y, label='sin(x)', color='red')\n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"График синуса\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "f8a4b3e5-6281-4d26-9021-3336319097dd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.plot(x, np.sin(x), label='sin(x)', color='red')\n",
+    "plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"Мультиграфик\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "cbf8dfa9-b3f4-4c09-a268-712f18d62733",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.bar(x, np.sin(x), label='sin(x)', color='red')\n",
+    "#plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"Мультиграфик\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "b80643f9-dba3-45d2-a3ba-d13579fda896",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAksAAAHHCAYAAACvJxw8AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAAVXJJREFUeJzt3QmUE1XWwPHb7IuigKza2iCoOLIJI6KMyo4yCKIii2wijAsOghsoOyiiiAzIiIPgzuI+gzIIIoLsCuPggnziNKJCg4KA0Mqa79wXKyTpdDrdnUpSVf/fOSF0Ul1Uvw7Jrfvuu5Xm8/l8AgAAgIiKRH4YAAAAimAJAAAgCoIlAACAKAiWAAAAoiBYAgAAiIJgCQAAIAqCJQAAgCgIlgAAAKIgWAIAAIiCYAkAACAKgiUAMXn++eclLS3N3FauXJnjeb1yUnp6unn+z3/+c1KO0Qs++eQTM8b6+wCQGARLAPKlVKlSMmfOnByPL1++XL7//nspWbJkUo4LAOxCsAQgX6655hp57bXX5NixYyGPawDVqFEjqVq1atKODQDsQLAEIF+6desme/bskSVLlgQeO3LkiLz++uvSvXv3kGm5jIwM6dixY459/Pbbb3LaaafJX/7yl5DH+/TpE5jqC76NHj06ZJtTTjkl6jHqvxtpP9ZNn1fbtm2LOKV15513msf134o0DRl+04xa8LH973//k7Zt20rZsmWlevXqMnbsWDMewSZNmiSXXXaZVKxYUUqXLm0CTR3DcD/99JMZQ93mkksukczMTPP4gQMHpEOHDubxZs2ayTfffJNjDIKPX2mQG/zz5zYGv/zyizmeGjVqyM6dO6OONeAFxZJ9AACcRT9omzZtKnPnzpWrr77aPPbvf/9b9u/fL127dpWpU6eax/QD+Oabb5bHHntM9u7dKxUqVAjsY8GCBebDXp8Pd8YZZ8iTTz4Z+Lpnz575PsYpU6bIwYMHzd83b94sjzzyiDz44INSp04d81i0YGvr1q0yc+bMXJ/XwEeDiGDBP9vx48elXbt2cumll5qffdGiRTJq1CiTidPvtfztb3+Ta6+9Vnr06GGCzXnz5smNN94o77zzjrRv3z6wnT6vU5z33nuvFC1aVO6++27z+Pjx4832um/9dzRw+vzzz6VIkcjnwPrvP/TQQ3mO3dGjR+X666+X7du3y6pVq6RatWp5fg/gej4AiMFzzz2nqRHfxx9/7Hvqqad8p556qi87O9s8d+ONN/qaN29u/n7OOef42rdvb/6+ZcsW8z1PP/10yL6uvfZaX0ZGhu/EiRMhj/fo0cNXo0aNkMf0+0eNGhX4unfv3r6yZcvGfNzLli0z+9D7cJmZmeY5/dksXbp08V100UW+9PR0829F+vlzo9vrNnfddVfgMf0ZdTxKlCjh+/HHHwOPW2NnOXLkiPl3W7RoEXhs48aNZn/PPPNM4DEde33s9ttvDzz23nvvmcfeeuutwGP6ewg+/r///e++kiVLmt+TPhdpDPRY9XdQpkwZ37p163L9OQGvYRoOQL516dJFfv31V5MF0SkbvQ+egrOcd9550qRJE3nllVcCj2mWSTNRmjHR7FMwzbDEWiCu01N60ym9eNmwYYOZqpowYUKuGZpYDBw4MPB3/Rn1a/3Z3n///cDjOn1m+fnnn01m7k9/+pNs3Lgx8PjSpUvNfefOnQOP6XgqnZKztG7d2mTLrO3DZWdnm6yWHsfZZ5+d63Hfd9995nf16quvhuwf8DqCJQD5VqlSJWnVqpUp6n7zzTfN1NMNN9wQcdtevXqZ6Zxvv/3WfK3BiE71RJpe27dvX571SOrQoUPmGPSmQYcGADqtVVhDhw41AUthWh9okFWzZs0cQaNVH2TRAFOn6nR1oU7j6c/y9NNPm6DJ8t1330mJEiXM1GQ0GpBpbZRuH8nkyZNNUKlTkbl55pln5IknnggEbwBOIlgCUCCaSdIM0YwZM0zt0umnnx5xO61jKl68eCC79PLLL0vjxo3l/PPPz7FtVlZWTKvpNMDQAnO9abBWv359U8ujGZGCWrx4scn8TJw4Uez20UcfmXol/Tn+/ve/y8KFC83PomMaXAie36yZZvvCafbt8ccflwceeCCktirc2rVr5eGHH5ZOnTrJ4MGDzfcB8CNYAlAg1113ncmi6IdspCk4i35Aa8GyBkuaXdIsU6SskmabtLjaKsKORgudNbOlNz2ON954w6w802LqgtAARbNKui/N9hTGiRMnzGq4YP/3f/9n7q1VaHq8Gii99957csstt5hgU3+WcFpcrdN3uvowr+PXVWuaXQqnheCnnnqqDBo0KOo+9Dg08zR9+nTzu9CACYAfwRKAAtHpMp020mX9uhIrGg2OvvzyS1MTo4GOZpvC/fOf/zSZkRYtWuT7WKxsjO67IHQl2qZNm0ytUjw89dRTIcemX2t2rWXLloHj1Kkznb606BTd22+/HbKfK664wty/9dZbgcfWrVtn7tevXx94TGuVtHbM2j54n9bvKLhGKhKdflQacGl2TTOAmm0DQOsAAIXQu3fvmLbTzJL2E9J6Jc2iVK5cOaT4WJe/63SU9h1q06ZNnvvTIMPKImmQ8Nxzz5k6Jp1CKggNCvr37x9xajC/NGOkx6Zjo8XYOlX57rvvmqyN1iVZ46F1RNpiQLNyu3fvNhmdWrVqmaDN0rx5c9Om4a677jJZOQ2ynn322UB2SjN7eokZbR2g7QzCg1BtOaCZur59++brZxgwYICpR7vttttMO4IyZcoUelwAJyOzBMB2WqR80003mb+HT8FpMfH8+fPNB7QGFrGsQtNaHg269KbTR7t27ZKXXnoppD9RfmjWJbjxZWFoQKPBktZfaSbt448/NsHguHHjAtto9mzWrFlmG6210p5Vms3RacBgmn3SrJJmpLSJpdY2aQ8ppT2TNIDS49YCch27SNkj7TGV34yb/rvaa0qn9oYPH17gsQDcIk37ByT7IAC4n9bAWAGCWzMV2jFbu3BbDTHtupDuH//4R5NNC+/QDcAeZJYA2E4zQVoDo52h3RooAXAvapYA2EZrcXQ5vmZbdEVXXiuyACAVESwBsI2ugNNO3VrQrdeMa9CgQbIPCQDyjZolAACAKKhZAgAAiIJgCQAAIApqluJAL2+wY8cOc0mB8KuoAwCA1KSVSNrYVjvXR+vxRrAUBxooaRddAADgPN99952cddZZuT5PsBQHmlGyBrtcuXJx269ezFIvw6CXf9DrSsEejHPiMNaJwTgnBuPs/HE+cOCASXZYn+O5IViKA2vqTQOleAdL2sBP98l/RPswzonDWCcG45wYjLN7xjmvEhoKvAEAAKIgWAIAAIiCYAkAACAKapYAAEgBx48fN/U5CKVjUqxYMXNBbh2j/NAap6JFi0phESwBAJDkXj9ZWVmyb9++ZB9Kyo5P1apVzYrzgvQyPP300833F6YPIsESAABJZAVKesFpXfVFc+OcjZ8PHjwop5xyStTGkZGCrOzsbNm9e7f5ulq1alJQBEsAACSJTitZgVLFihWTfTgpGywdOXJESpUqla9gSZUuXdrca8CkY1zQKTkKvAEASBKrRkkzSrCHNbaFqQcjWAIAIMmYekvtsWUaDs6hqyA++khk506dfBa57DKR1atPfv2nP4nEYdUDAA/jfQZOzyytWLFCOnToYK4OrJHi22+/nef3fPjhh3LxxRdLyZIlpVatWvL888/n2Gb69OmSkZFh5kObNGki69evt+knQIG9+aZIRoZI8+Yi3bv77zW1Gvy1Pq/bAYCd7zOvvaYfLiKvv+7/vnwuZ3e7Pn36SKdOnfL9fUuXLpU6derE3B7gyy+/NBe/PXTokNjNUcGSDkj9+vVNcBOLzMxMad++vTRv3lw+/fRTufvuu+XWW2+V9957L7DN/PnzZciQITJq1CjZuHGj2X/btm0D1fNIEv3Pom9Gc+eKjB0rcsMNIt9/n3ObYD/8IHL99f7t9fv0+3kTAxBroBTL+4w+36WLP3Dq18//WN26nKgF+dvf/hYxMZGX+++/X4YPHx5zEfaFF14ol156qUyePFns5qhpuKuvvtrcYjVjxgypUaOGPPHEE+ZrjVhXrlwpTz75pAmIlA5y//79pW/fvoHveffdd2X27NkydOhQm34SRKVvOoMG5XzTyovP578fNerkY2edpf9zRTp3ju8xAnDPlJueaA0efPI9JL927PAHWpppStZ7Tfj0YRKnC0877bR8f49+Nn/zzTdyvZ7w5oN+dutn+LBhw0zjSrs4KljKrzVr1kirVq1CHtMgSTNMSpcibtiwwQyyRZcl6vfo9+bm8OHD5mY5cOBAoNI+nt1XrX15qqPrggUiPXv637R+X/JZKHv3+venOnSIuIknxzlJGOvEYJxjfK954AF/oGTJ53vO0d+3P1qqlP89Sz9bfv1VpHp1kaZNYwpW9Hek/YB0ebzeCuTNNyVt8GBJCzrB9J11lviefNLW4O3111+XcePGydatW82Ks4YNG8pbb70lAwcONO0Q9O+qRYsWUrduXVPqMmvWLClRooT85S9/MTM6lrlz55rPXn1Ox0HHRD+v9TN54cKFZps9e/aYf0MDpDFjxpjHWrZsKXv37pVly5aZv0di7U/HOjxrFev/kWJub/RVpUqVkMf0aw1ufv31V/n555/N3Gikbb766qtc9zthwoTALyrY4sWLbVn+uWTJEvEMfSHPmWPPvn//D5cbT41zkjHWicE45/FeM2lSXHa1ZPbs0Af0BDqo3CMazYZod2ltuqgn8PlVfMECKdO7d86s2A8/SFqXLpL9wgtyNJcTxcJ+vvbo0cN8Fv75z3+WX375xSQZ9u/fbwKQY8eOBRIJ+vcXXnhB7rzzTvOa/Pjjj+WOO+6QBg0amDIZtXz5crnhhhsC36OmTp0ql19+uUyaNEluu+02GTBggBmrQYMGhWyngZjWO/3xj3+MeKw6rvqZr3XPeizBtGmleD1YsotmorTOyaK/tPT0dGnTpo2UK1cubv+OvuD0hdW6dWtzfRvPnN3Z6cwzRSZODMkyeWKcUwRjnRiMc5SpqpUrRTS4+PnnQu9OM0saKLW+5RYprhmlYNZy9ZdeyjWrrfR6Z3oZD+1OrZmXfDl+XNIefNAESuGL49N8PvGlpUmZhx4SX9eucZ+S27p1qwk8unXrJuecc455rKlm036/HpsGgdbnof5d64Effvhh87Vmh7TUZe3atdKxY0fz2Pfff2/KZoI/Q/XvWhqjBeO7du0yr2mdDapQoULIsWiRtwZvuX3+6hhrc8orrrgixxgHB12eDZY0AtUBDqZf64DqwGk6Tm+RttHvzY2urNNbOH2B2PHGZNd+U6agsqB1AgXxzTe51ha4dpxTEGOdGIxzHGohY6CBUo5gyQqYdGpOA4JcghWd3dDV3TrdlN/u1LJiRdSfRwMm0euprVolctVVEk8NGzY0017WoihNFmhmqHz58ubnsX4mS7169UK+1kuP/Pjjj4HHNPOjMzPhY3DTTTeZle9Tpkwxi7vOP//8HMei36ffn9v46eN6PJH+P8T6/8NRq+HyS6NcTc0F08jUin51brRRo0Yh2+jcpn5tbQMbz/D0jSuRgZKy/j19A2OlHODtlW52+z1YMYXXdtBi7nhulw9FixY1n6f//ve/zaq0adOmmUBGV6FHEh6UaPASXKN1xhlnmNKYcDpNpivV9d/TbFYkWrNUqVIlsZOjgiWd09UWAHpT+kvRv2/fvj0wPdarV6/A9jrH+b///c8sR9QapL///e/y6quvymBd9fA7nU6bOXOmmU/dvHmz3H777aZFgbU6DjbRN4/CvnEVNK1s9xsYAPecmMVj+kpPyO04OYv1wrCFuIBsNGlpaaamSOuW/vOf/5gEhFXUXZBMlfZNCnfPPfeYzNBrr71mArIPPvggxzaff/65+X47OWoa7pNPPgkUgymrbqh3796mp8POnTsDgZPS+U9tA6DBkfZ90HnNZ599NtA2wErxaSpw5MiRZs5TC84WLVqUo+gbcZbfMx1NZ+ubnRbW166ds7Pu11+LjB7t3zbWN8U33vDfX3ppPg8egKtPzDRLoSvJtMYxvIP3Tz/52wzkZ5/jx4to36F4tzHR9gDaHkVrPiO97+n7pj6v28XZunXrzCyMTr/pBWr1a/0s1RY9mzZtyvf+9HNZkxbBrDY+q1atMk2l7733XvN5r/vX6T61bds2+eGHH3KsfI87Hwpt//79+io19/F05MgR39tvv23uXeXYMZ/vySf1v3bst/R0n++NN6LvV58/66z87VfEd6RWLXeOcwpy7Ws6xTDOQebMif39IC3Nf8vrvUbfw5Yt8x15+WX/OJcpU+B9//rrr74vv/zS3BeI7s/ad0F+lgL68ssvfW3btvVVqlTJV7JkSd95553nmzZtmnmud+/evo4dOwa2vfLKK32DBg0K+X59Xrez7Nmzx1eqVCnfV199Zb7evXu3r0qVKr5HHnnEd/z4cd/PP//s++2333yNGjXydenSJfB9+rweRzTRxjjWz2+CpTggWMqH/AQ0lSr5fC+/bN6UzJtTLHS799/3+SpUiD1YKlPGP842vanA5a/pFMQ4nwxofMOHx/ekLNI4a7AUHqzkFjDpvxH0flboYCm399V8/iyp4N577/UNGDAgx+NWsKT3wQ4fPuw7++yzfStXrrQ9WHJUzRI8UmSpqWO9zZgh0qOHfxVHrHUDup02Jps58+R+8mKlr7VjO0XfgLuu8aZTYHnRpejvv6+FsAWbJtP2ADpll6x6ST3mbdtEli3z96nT+4L+LEn00EMPmTYEsTbn1LKbBx980NRN2Y1gCalXZKlz7IW9bIB+r+4jljcwiwZxFH0D3ln5Zp1Q6cmVnmQVtJhb+yhpsDJ8eNJWp5lj1xPLbt3yd4KZQk4//XQT/MTaQkHrmLQTeCIQLCG1iiy1qDJeZ0TBZ1sDBybvTQxAaq58i8eJWXhWOxa66osLfTsKwRISI9YgRFchxvOMyDrbivXijDYtsQWQQidlmgGyY6rKWp2W1/S/Tg3qFKFOFS5eHL9/H7YhWIK99MxJz6Ai9M9IaLASy5uYLkXV4+VsD3D3SdmFF9ozVaX70/YAKpZ6SV3y/9e/audFc6FX2CMeY0uwhNQostQ3lvR0W/qBxPwmpt1jtVeHHrMeOwBnSXKTxnzXS/p8UnzPHr0qrWQfOmTfMXlc9u8Xyy3MpX8c1ZQSLr3umxW8TJlib1Gi9SaW1/Wh9Gwvl+vHAUhRVlZYV7bt3Rt5GxubNIbQ9w29HpxOC2r37igni0UPHpTT33xTdmtwpRe+LVPGdMbGSbo67siRI+aCuPm5fp5mlDRQ2r17tyke10umFBTBElKjyFIDpUQEJtabmE4NdukS+U1VjzuGC2ACcNBFchN1UhZeLxnD1GDV554z70e7I1ygHWKCHr1QbunSpQsUSGqgVLVq1UIdA8ESkltkqatH9CwvkQGJ/lt6y+3sM7wfSpyv1g0gCVnsRJ6U5XPKT9tZVitZUiqfd54cPXo0IYflJEePHpUVK1bIFVdcke+pNN2+MBklC8ESkl9kmQxJvFo3gARmsXVa7tVXk9d7KB/Xb9MP9Xh8sLtN0aJF5dixY1KqVKlC1R0VBgXecGeRZbz+bVoJAM7OYmsG2comJ0Nei0s0gNLWJvqzsBI3ZREsIfHL9O1e+eaWYwTgjgxxbivkrABOpwetvkusxE1JBEtI7JlUoossC3qMerZ3663+9D2ddoHU5KQMcfAVBXTxiAp/X7FW4hIwpRyCJdjThPLwYZHRo3OeScXz8gLxOturXj1njUPFiiKjRol0784ZH5CqnJYh1pM0PRZ934nEqmnSYIoTtJRCsAR7mlBqkKHBhv7nHzMmda+Ercfy2Wf+v8+a5T9WrXHQRnHBOOMDUu+kTDO//fundhY7v3VWwStxkTJYDQd7l+/u2OHPMOmZVKouwbfeSK+7TqR27cgrVui9BKRuTyXNBKvgk5xktQpwS50VQhAswd7lu04KMtasif2ML1UDP8CLJ2WaDbay2HrCozVKie7f5sY6KwQQLCGxaeVUDjKysmLbjjM+IDVPyp591j/Vn4pBUgH6LiF1ULOEwnNLWjnWdvic8QGJ55ZaHyesFkYOBEsoPLeklZs2ddbKGsBL3HJSFq3vkr7/zJ/vX5E7dy5tS1II03AoPLekla0zPq2JsHotWTjjA5LLLSdl4Rf11kyYBnh63D/9JDJ4cGgGTd879X0p1QrVPYbMEgrPTWnl3M749Gtd1af9ozjbAxLPaT2VYqHviVrH2a2bv0i9S5ecU420LUkJBEsofK8TTRdbF6tM5SaUBem0q/2hdIWNokklkDxuOinLb/G6olFlUjENh/j1OtHAaPJkkUqVTqaVU3X5bqxnfPpzakYp/E3MOttzWiAIOJmV+Y303pOKPZW8tqLYxQiWEL9eJxpA3HST/81M08pO55b+UYAb/i8G1/Z8843I6tXOPylzY/G6SzENh/zxUrrYLUuVATddRknvzz3XX+OjJ2WaaXFyoOTG4nUXIlhC/ngpgOBsD0iNLLbbi57dWLzuMgRLyB8vBRCc7QHJ46UstpuL112CYAn546UAgrM9IHm8lMXOq1ElC0mSjgJveLMBZSxoUgkkj5ey2NEaVTq9eN0lHJdZmj59umRkZEipUqWkSZMmsn79+ly3veqqqyQtLS3HrX379oFt+vTpk+P5du3aJeincSCvpYs52wOSw0tZ7NwaVVptAqx+djTETRpHBUvz58+XIUOGyKhRo2Tjxo1Sv359adu2rezevTvi9m+++abs3LkzcPv888+laNGicuONN4Zsp8FR8HZz9UWJ3HktgAhvUqn3emVzt/2cQCphGjzySkAa4iaFo6bhJk+eLP3795e+ffuar2fMmCHvvvuuzJ49W4YOHZpj+wraVTrIvHnzpEyZMjmCpZIlS0rVWK84D2+mi62zvWi9X9z88wOJ5vVp8Gj97GiIm3COCZaOHDkiGzZskGHDhgUeK1KkiLRq1UrWrFkT0z5mzZolXbt2lbJly4Y8/uGHH0rlypWlfPny0qJFCxk/frxUrFgx1/0cPnzY3CwHDhww90ePHjW3eLH2Fc99FooGBzrWWVkiGlw2bSpy+eUnnz9xwn9zmAKN84IFIg884H/jsmimbeJEkQ4dbDhKd0i517RLuWac9f+SBgXh/9c04/Too/7nk/gz2jbO+l6rP3OpUpGf12BREwTXXOPeYDFBr+dY95nm80Wq0k09O3bskDPPPFNWr14tTfVD+nf333+/LF++XNatWxf1+7W2SWucdLtLLrkkR7apRo0a8s0338iDDz4op5xyignAdMouktGjR8sY63phQebMmWP2BQAAUl92drZ0795d9u/fL+XKlXN+ZqmwNKtUt27dkEBJaabJos/Xq1dPzj33XJNtatmyZcR9aXZLa6eCM0vp6enSpk2bqINdkIh3yZIl0rp1aylevLgkjWZRevbMmQ62UuEvveTobEq+xlnP+OrWDT3LDR8TzTBt2uSJMz7HvqZdjnF2+DhrNq1fv7y3mzXLPyXnckdtfD1bM0N5cUywdMYZZ5hMz65du0Ie16/zqjc6dOiQySCNHTs2z3+nZs2a5t/aunVrrsGS1jjpLZz+Eu14Y7Jrv/lqDJedHfl5F10fLaZxXrVKZOvW6Nt8/bXI2rVc8DJVX9Me4shxdmAtYNzHWX/uX3+NbTun/X5T7PUc6/4csxquRIkS0qhRI1m6dGngsRMnTpivg6flInnttddMjdHNN9+c57/z/fffy549e6Sa25ajFpTXGsPlxYu9X4BEYfWXHysBU45jgiWlU18zZ86UF154QTZv3iy33367yRpZq+N69eoVUgAePAXXqVOnHEXbBw8elPvuu0/Wrl0r27ZtM4FXx44dpVatWqYlAQgOcvBq7xfAbl65DlwsvNbPzgEcMw2nbrrpJvnxxx9l5MiRkpWVJQ0aNJBFixZJlSpVzPPbt283K+SCbdmyRVauXCmLFy/OsT+d1tu0aZMJvvbt2yfVq1c3dUfjxo2LOM3mSQQH3u1gDqTKdeBcNN2f7352Oi7BAaS+v2igRNuAhHJUsKQGDhxobpFoUXa4888/X3Jb8Fe6dGl577334n6MrkJwEMrrvV+AZE/3e6kW0Gv97FKYo6bhkASkg3PyWgdzwG5M98d++RMvvdemEMdllpAEpINz4owPiB+m+12/YtDpCJYQG4KD2C6BAiD/mO6PnRa6Rzpx1RkAL564JgjBEmJHcJA3zviA/KMWMDZcLy5pqFkC4oUeMUDBUQtYuBWDSlcM6naIOzJLiIwMSf5wxgcUHtP9uWPFYFIRLCEn5sTzhx4xQPww3R8ZKwaTimk4hKKLbv5xSRig4Cca2h9v7lz/PVNIuWPFYFIRLOEk5sQLhjM+IP+o8csfrheXVARLOIkMScFwxgfkDxns/KNBcFIRLOEkMiQFwxkfEDsy2AXHisGkIVjCSWRICoYzPiB2ZLALRwOibdtEli0TmTPHf5+ZSaBkM4IlnESGpOA44wNiQwa78LheXMLROgAn0UW3cOgRA+SNDDYciGAJobhobuHQIwaIjuvAxR9NhG1HsIScyJAAsAsZ7PiiiXBCULOEyJgTB2AXavzigxYMCUNmCbAT6XEgMjLYhcNllhKKYAl+fKjHH+lxIDpq/AqOC+smFNNw4LIDdiA9DsBOtGBIKIIlr+NDPf7oUAzAbrRgSCiCJS/jQ90edCgGItP3kg8/FJk713/Pe0vB0UQ4oQiWvIwPdXuQHgdyYro/vrjMUkIRLHkZH+r2ID0OhGK63x60YEgYVsN5GR/q9qBDMXASS9ztRQuGhCCz5GXMeduD9DhwEtP99qOJsO0IlryMD3X7kB4H/JjuhwsQLHkdH+r20bHbtk1k2TKROXP895mZjCm8hel+uAA1S2DO2050KIbXUcOXHFyVIa4IluDHhzoAO6f7ddWbBkbBARPT/fbgUktxxzQcAMBeTPcnDm0abOG4YGn69OmSkZEhpUqVkiZNmsj69etz3fb555+XtLS0kJt+XzCfzycjR46UatWqSenSpaVVq1by9ddfJ+AngWfRxRheRA2f/bgqg20cFSzNnz9fhgwZIqNGjZKNGzdK/fr1pW3btrJ79+5cv6dcuXKyc+fOwO3bb78Nef6xxx6TqVOnyowZM2TdunVStmxZs8/ffvstAT8RPIcuxvAylrjbizYNtnFUsDR58mTp37+/9O3bVy688EIT4JQpU0Zmz56d6/doNqlq1aqBW5UqVUKySlOmTJHhw4dLx44dpV69evLiiy/Kjh075O233xbXIrORHKTHAdiJNg22cUyB95EjR2TDhg0ybNiwwGNFihQx02Zr1qzJ9fsOHjwo55xzjpw4cUIuvvhieeSRR+QPf/iDeS4zM1OysrLMPiynnXaamd7TfXbt2jXiPg8fPmxulgMHDpj7o0ePmlu8WPuK5z5lwQKRBx7wf0BbtI5g4kSRDh3Ei2wZ53AakOq4h00DhxS6Dh0qcs01rj7bTshYg3H26jhXrSpSunRs26XKMSd5nGPdZ5pP0ysOoNmeM888U1avXi1NmzYNPH7//ffL8uXLzRRaOA14tP5IM0b79++XSZMmyYoVK+SLL76Qs846y+zr8ssvN/vWmiVLly5dTEZKp/0iGT16tIwZMybH43PmzDGZLgAAkPqys7Ole/fuJkbQsh3HZ5YKQoOq4MDqsssukzp16sgzzzwj48aNK/B+NbultVPBmaX09HRp06ZN1MEuSMS7ZMkSad26tRQvXrzwmY26dUMzSuGZDc0wbdrk6syG7eOcG13x069f3tvNmuWfknOphIw1UmOc9T1Hs/5ZWf5Mhr4Xu+y9JSXGOdLsQc+e/r9HatPw0kuOm0U4auM4WzNDeXFMsHTGGWdI0aJFZdeuXSGP69daixQLHeSGDRvK1q1bzdfW9+k+gjNL+nWDBg1y3U/JkiXNLdL+7fgPE5f9rlol8vvPnStdBbh2rWf7Ldn1+zP09fXrr7Ftlypvuk4dayR/nD3W5yelXs/W+IaPv17nU/tZOXj8i9swzrHuzzEF3iVKlJBGjRrJ0qVLA49pHZJ+HZw9iub48ePy2WefBQKjGjVqmIApeJ8aZeqUXqz7dAwK/5KLixbDK1jIkHy0aYg7x2SWlE599e7dWxo3biyXXHKJWcl26NAhszpO9erVy9Q1TZgwwXw9duxYufTSS6VWrVqyb98+efzxx03rgFtvvdU8r3VJd999t4wfP15q165tgqcRI0ZI9erVpVOnTuIqXJ8puehiDC/Iq8+Pvta1z49eXonXur24KoN3g6WbbrpJfvzxR9NEUlex6VTZokWLAu0Atm/fblbIWX7++WfTakC3LV++vMlMaVG3th0ILhDXgGvAgAEmoGrWrJnZZ3jzSsfj+kyp08U40vSEw9PjQL77/PBBDgdxVLCkBg4caG6RfKg9g4I8+eST5haNZpc0A6U3VyOzkRq4aDHcjOl+uJTjgiUUApmN1EB6HG7FdD9cimDJa8hsALAL0/2pX1PGe3+BECx5EZkNAHZguj91eaydQ7w5pnUAAMBB0/3a5DaYfjDr43wwJx7tHAqNzBKQbKTG4TZM96cO2jnEBcESkEykxuFWTPenBto5xAXTcF44q9CWCnPn+u/1a6QGUuMA7EY7h7ggWHIz/bDNyBBp3lyke3f/vX7Nh3Dqp8aVpsYJbgEUBu0c4oJgya3IWrgnNQ4ABcV1KeOCYMmNyFqkPlLjcBum/FO7nYMKD5ho5xAzgiU3ImuR+kiNw02Y8k9ttHMoNFbDuRFZi9RHp2O4bco//HVsTfnzYZwaaOdQKGSW3IisReojNQ43YMrfme0cunXz3/P+EjOCJTeioM8ZSI3D6Zjyh0cwDedGXJ/JOUiNw8mY8odHECy5PWsRqTu0BkpkLVIHnY7hVEz5wyMIltyMrAUAO7FQAR5BsOR2ZC0A2IUpf2fjIt4xo8AbAFBwLFRwJnpj5QuZJQBA4TDl7yz0xso3giUgFZEeh9Mw5e+O3lg6faq9sTT45T0ngGk4INWQHgdgF3pjFQjBkttwMUt3pMfD38ys9DgBE4DCoDdWgRAsuQkZCWfj0hEA7EZvrAIhWHILMhLOR3ocgN24HFaBECy5ARkJdyA9Dqdgut+5uIh3gRAsuQEZCXcgPQ4nYLrf+eiNlW+0DnADMhLuwKUjkOroz+Me9MbKFzJLbkBGwh1IjyOVMd3v3t5Y3br573lvyRXBkhtQsOcepMeRqpjuh4cxDecGXMzSXUiPIxUx3Q8Pc1xmafr06ZKRkSGlSpWSJk2ayPr163PddubMmfKnP/1Jypcvb26tWrXKsX2fPn0kLS0t5NauXTtxHDIS7kJ6HKmG6X54mKOCpfnz58uQIUNk1KhRsnHjRqlfv760bdtWdu/eHXH7Dz/8ULp16ybLli2TNWvWSHp6urRp00Z+0GLEIBoc7dy5M3Cbq8thnUgDom3bRJYtE5kzx3+fmUmgBKDwmO6HhzlqGm7y5MnSv39/6du3r/l6xowZ8u6778rs2bNl6NChObZ/5ZVXQr5+9tln5Y033pClS5dKr169Ao+XLFlSqlatKq7AxSwB2IHpfm/gIt7ODpaOHDkiGzZskGHDhgUeK1KkiJla06xRLLKzs+Xo0aNSoUKFHBmoypUrm6m6Fi1ayPjx46VixYq57ufw4cPmZjlw4IC5133rLV6sfcVzn8iJcU4cxtrh49yhg39a/4EH/O0CLJpxevRR//Me+t267vW8YEHO362Wdkyc6P/dunCcY91nms8XaR1o6tmxY4eceeaZsnr1amnatGng8fvvv1+WL18u69aty3Mfd9xxh7z33nvyxRdfmJonNW/ePClTpozUqFFDvvnmG3nwwQfllFNOMQFY0Vyi6dGjR8uYMWNyPD5nzhyzLwAAkPo0idK9e3fZv3+/lCtXzvmZpcJ69NFHTWCkWSQrUFJdu3YN/L1u3bpSr149Offcc812LVu2jLgvzW5p7VRwZsmqh4o22AWJeJcsWSKtW7eW4sWLx22/CMU4Jw5jnRiMc2K4Zpx16q1u3dCMUrC0NH+GadOmpEzJ2TnO1sxQXhwTLJ1xxhkm07Nr166Qx/XrvOqNJk2aZIKl999/3wRD0dSsWdP8W1u3bs01WNIaJ72F01+iHf9h7NovHDTOLqsjSOmxdhHGOTEcP86rVols3Rp9m6+/Flm7Nqk1sXaMc6z7c8xquBIlSkijRo1McbblxIkT5uvgablwjz32mIwbN04WLVokjRs3zvPf+f7772XPnj1SzQnLX7mYpTdwLS4AdqKHlnuCJaVTX9o76YUXXpDNmzfL7bffLocOHQqsjtMVbsEF4BMnTpQRI0aY1XLamykrK8vcDh48aJ7X+/vuu0/Wrl0r27ZtM4FXx44dpVatWqYlQUrjA9Rb1+IK75xsXYuL3zeAwqKHlruCpZtuuslMqY0cOVIaNGggn376qckYValSxTy/fft20yfJ8vTTT5tVdDfccIPJFFk33YfSab1NmzbJtddeK+edd57069fPZK8++uijiNNsKYMPUG/gWlwAEoEeWu6pWbIMHDjQ3CLRouxgmi2KpnTp0mZ1nKs+QPVFrR+gerkMB9e0IJ/X4qK3FoCCooeWuzJL4GKWnkIdAVIF9ZHuxyWz3JVZ8jw+QL2DOgKkAp3W12x28EmafoBqJsLjH6Cuw0W8c0Ww5DR8gHqvjkBr0SJNu2p6XJ/3cB0BElQfGf76s+ojyTi4D5fMiohpOKehEM97dQQq/PdNHQHsxgIDIIBgyWn4APUW6giQLNRHAgEES07EB6i36O9TV3YuW6YXIPTfZ2bye4a9qI8EAqhZcioK8byFOgIkGvWRQADBkpPxAQrALiwwAAKYhgMA5ER9JBQ9tgyCJQBAZNRHehvXIA1gGg4AkDvqI72JHlshCJYAp9J0OB9gSATqI72Fa5DmwDQc4ESkxwHYhR5bORAsOQmFdghOj4e/mVnpcQImAIVBj60cCJacgkwCFJegAGA3emzlQLDkBAsWkEmAH+lxAHbjGqQ5ECw5wQMPkEmAH+lx2I3pftBjKweCJSfQDFJuyCR4C+lx2InpfljosRWC1gFuQSbBG7gEBexCXx2Eo8dWAJkltyCT4A2kx2EHFg4grx5b3br57z363kKw5ASaBqXQDhbS44g3Fg4AUTEN5wQTJ/rT4BoYBZ/5kUnwLtLjiCcWDgBRESw5QYcO/oyBpsmDz/40k6CBEpkEb+ISFIgXFg4AUREsOQWZBAB2YeEAEBXBkpOQSQBg58IBpvuBiCjwBgCwcACxO+69xqVklgAAfkz3I5Z+XIMi1M9qZtLFATXBEgDgJKb7kZs3vdu4lGk4wC08mBoHkCDHvd24lGAJcAOu6QXATh95u3FpzMHSjh077D0ShNLofOVK/9/13qXROuKYGg9/I7NS4wRMAAprp7cbl8YcLP3hD3+QOXPmSLJNnz5dMjIypFSpUtKkSRNZv3591O1fe+01ueCCC8z2devWlYULF4Y87/P5ZOTIkVKtWjUpXbq0tGrVSr7++mtJiSxB+/b+r/WeLAEi8XhqHECCVPN249KYg6WHH35Y/vKXv8iNN94oe/fulWSYP3++DBkyREaNGiUbN26U+vXrS9u2bWX37t0Rt1+9erV069ZN+vXrJ//5z3+kU6dO5vb5558Htnnsscdk6tSpMmPGDFm3bp2ULVvW7PO3336TpCBLgPzweGocQIIbl6Z58zqlMQdLd9xxh2zatEn27NkjF154oSxYsEASbfLkydK/f3/p27evOQYNcMqUKSOzZ8+OuP3f/vY3adeundx3331Sp04dGTdunFx88cXy1FNPBbJKU6ZMkeHDh0vHjh2lXr168uKLL5opx7fffjvBPx1ZAhSAx1PjiAMWBiA/jUtVeMDkgcal+WodUKNGDfnggw9MsNG5c2cTgBQrFroLzfjY4ciRI7JhwwYZNmxY4LEiRYqYabM1a9ZE/B59XDNRwTRrZAVCmZmZkpWVZfZhOe2008z0nn5v165dI+738OHD5mY5cOCAuT969Ki5FZjWJu3ZI1K6tH9/YffGTz+JrFgh0qxZwf8dhLB+Z4X63SVL1aqB10ue26XAz+fosXaQmMdZT3ofeMCfubZoU0q9eLdekxJRee713OH365SGv2Y04/Too/7nbRgLO8c51n3mu8/St99+K2+++aaUL1/eZGPCgyW7/PTTT3L8+HGpUqVKyOP69VdffRXxezQQirS9Pm49bz2W2zaRTJgwQcaMGZPj8cWLF5tMV6Ho2V2YJeGZMw3OwmqvUHhLliwRR4rwmskhxV4zjh1rh8lznDULMGlS5OdS6PWS6jz1ei6avNeMHeOcnZ0d03b5inRmzpwp99xzj8nEfPHFF1KpUiXxIs1uBWesNLOUnp4ubdq0kXLlyhUus2QVdf+eUdJAqfUtt0jxX389ud2775JZivOZhf4nbN26tRQvXlwcR7MDPXv6/x7pml4vvZQyWQLHj7VD5DnOOtVWt25odiCYvnY0w7Rpk2unVeKB17Pzx9maGYpbsKS1P7ryTKfgevXqJYl2xhlnSNGiRWXXrl0hj+vXVXWKIQJ9PNr21r0+pqvhgrdp0KBBrsdSsmRJcwunv8RC/SKvuEKkYsUcV/7WQMkES9aVv3U73sDirtC/v2SxOuaGX4JAiy21hiAFO+o6dqwdJtdxXrVKZOvW6N+sq4LXrqWbdwx4PTt3nGPdX8wF3joFpgXeyQiUVIkSJaRRo0aydOnSwGMnTpwwXzdt2jTi9+jjwdsrjU6t7bUGSwOm4G00ytRVcbnt01YeL6BDIWhAtG2byLJlItriQ+8zM1MyUEIKYGEAkC/FnDQnq1NfvXv3lsaNG8sll1xiVrIdOnTIrI5TGsideeaZpqZIDRo0SK688kp54oknpH379jJv3jz55JNP5B//+Id5Pi0tTe6++24ZP3681K5d2wRPI0aMkOrVq5sWA0m98rdmCbTY26IZpRTNEiBFcE0vxMrjPXMAV19I96abbpIff/zRNJHUAmydKlu0aFGgQHv79u1mhZzlsssuM400tTXAgw8+aAIiXQl30UUXBba5//77TcA1YMAA2bdvnzRr1szsU5tYJv3K37rqTedTtUaJqTcA8e6ZEzblH2BN+bu0Zw7g6mBJDRw40Nwi+VB7hITRJpp6y41ml8aOHWtuKUUDIy3i1tUFek+gBCDeU/7a6FYDo0gLA5jyBwK4kC4AeJE15a+r3oJpRkkfZ8ofsTru/samjsssAQDiPOWvl8PRYm6tUdKpNzJKiNWbb+ZciasBt2YuXRRwEywBgJexMACFvZapzxf5WqYuylAyDQe4mQfS4wCS4Li3rmVKsAS4+awvI0OkeXOR7t399/q1Pg4AhfHRR6FTb5ECpu++82/nAgRLgJvT4+FvZlZ6nIAJQGHs9FZjU4IlwG08lh4HkATVvNXYlGAJcBuPpccBJLGxaVrYpbks+rhen9IljU0JlgC38Vh6HPlAwT/ipai3rmVKsAS4jcfS44gRBf+It87eaWxKnyXAbbjuFzzcDwcJ1tkbjU3JLAFu47H0OPJAwT8S1di0Wzf/vQvfWwiWADfyUHoceaDgHyg0puEAt/JIehx5oOAfKDSCJcDNuO4XKPgHCo1pOABwM4/1wwHsQLAEAG5GwT9QaARLAOB2FPwj0Y67qwEqNUsA4AUU/CORfb0GDQpdhamBuWY4HRqYEywBgFdQ8A+7venOBqhMwwFe47L0OIAUcdy9DVAJlgAv4fpgAOzykXsboBIsAV5Lj4e/mVnpcQImAIWx070NUAmWAC9wcXocQIqo5t4GqARLgBe4OD0OIEX8yb0NUAmWAC9wcXocUaxcSSE/EqeoexugEiwBXuDi9DgiWLDAf9++PYX8SKzO7myASrAEeIGL0+MIowFRz545H6eQH4nSubPItm0iy5aJzJnjv8/MdGygpAiWAC9wcXocQSjkR6o1QO3WzX/v8PcWgiXAK1yaHkcQCvkBW3C5E8BLuD6Yu1HID3g7s7R3717p0aOHlCtXTk4//XTp16+fHDx4MOr2d911l5x//vlSunRpOfvss+Wvf/2r7N+/P2S7tLS0HLd58+Yl4CcCksRl6XEEoZAf8HZmSQOlnTt3ypIlS+To0aPSt29fGTBggMzR4rEIduzYYW6TJk2SCy+8UL799lu57bbbzGOv65RDkOeee07atWsX+FqDMQBwbCH/3r2Rn9f6NH2eQn7AfcHS5s2bZdGiRfLxxx9L48aNzWPTpk2Ta665xgRD1atXz/E9F110kbzxxhuBr88991x5+OGH5eabb5Zjx45JsWLFQoKjqlWrJuinAQCbC/kjrYajkB/JdPy4o6f/HREsrVmzxgQ0VqCkWrVqJUWKFJF169bJddddF9N+dApOp/GCAyV15513yq233io1a9Y02SfNWul0XG4OHz5sbpYDBw6Ye8146S1erH3Fc5/IiXFOHMY6ATp0kKMvvWT+erR06ZOPa0bp0UfN88L4xwWv53z0/XrgAX/7CosuNJk40f96TOI4x7pPRwRLWVlZUrly5ZDHNOCpUKGCeS4WP/30k4wbN85M3QUbO3astGjRQsqUKSOLFy+WO+64w9RCaX1TbiZMmCBjxozJ8bh+v+4n3nTqEfZjnBOHsbbZ72fsS2bPzvncwoWJPx6X4/Ucw+tx0qTIz+Xj9WjHOGdnZ6d+sDR06FCZqJFlHlNwhaWZn/bt25vapdGjR4c8N2LEiMDfGzZsKIcOHZLHH388arA0bNgwGTJkSMj+09PTpU2bNiZzFc+IV18crVu3luLFi8dtvwjl+XHW9PiaNXpWIqLT0U2b2pYe9/xYJwjjnBiMcwzvLXXrhmaUgukMjmaYNm2K+p5j5zhbM0MpHSzdc8890qdPn6jb6NSY1hPt3r075HGtO9IVb3nVGv3yyy+mePvUU0+Vt956K8+BbtKkiclA6TRbyZIlI26jj0d6Tvdtx38Yu/aLUJ4cZ+3mrE0Mg3vz6HSN1r3Y2HfJk2OdBIxzYjDOuVi1SmTrVonq669F1q71r8xNwjjHur+kBkuVKlUyt7w0bdpU9u3bJxs2bJBGjRqZxz744AM5ceKECW6iRYxt27Y1gc2//vUvKVWqVJ7/1qeffirly5fPNVACXBUo6eUvwrs9W5fFoFElgMLY6Z6+X47os1SnTh2THerfv7+sX79eVq1aJQMHDpSuXbsGVsL98MMPcsEFF5jnrUBJp8V0Wm3WrFnma61v0tvx31v9L1iwQJ599ln5/PPPZevWrfL000/LI488YvozAa7GZTEA2K2ae/p+OaLAW73yyismQGrZsqVZBXf99dfL1KlTQ+Y0t2zZEijW2rhxo1kpp2rVqhWyr8zMTMnIyDDpt+nTp8vgwYPF5/OZ7SZPnmyCMsDV8nNZjBjS4wCQa98vzVZHOjFzUN8vxwRLuvIttwaUSoMfDXgsV111VcjXkWi2KrgZJeAZLkqPI0IfG/rGIZX6ft1wgz8wCv5MdljfL0dMwwGIMxelx/F7/VlGhkjz5iLdu4u0b3+yvw2QTJ3dcQFvx2SWAMSRi9Ljnpdbob6yOnk75AMJLtXZ+RfwJrMEeDk9rsK71TssPe5p0Qr1LRTqIxUUdfYFvAmWAK9ySXrc0/JTqA+gwJiGA7zMBelxT6NQH0gIgiXA66z0OJyHQn0gIZiGAwCnF+qH151Z9PH0dAr1gUIiWAIANxbqWyjUR6o6flzkww9F5s7136fwQgSCJQBwY6G+euklCvXhjN5gzZv7v9bHUxA1SwDgtkJ97eB94IBIhw7JPjLAFRfxJlgCEP3SGayQc16h/tGjIgsXJvuIgPxfxFunk7U3mAb/KfSewzQcAEenxwE4yEfO7A1GsAQgZ3o8/M3MSo8TMAHwYG8wgiUAsaXHFZfOAODB3mAESwAcnR4H4CB/cmZvMIIlAI5Oj3uSg/rTAG64iDfBEgBHp8c9hwJ8OF1n513Em9YBAELT41rMHaluSc/69PkUS497igP70wBuuIg3mSUAjk6PewYF+HBrb7Bu3fz3KfzeQrAEwNHpcc+gAB9IGqbhADg6Pe4ZFOADSUOwBCD6pTOQGijAB5KGaTgAcAKH9qcB3IBgCQCcgAJ8eMHx1OwhRrAEAE5BAT682ENswYJkHxk1SwDgKBTgw2s9xHr2FJkzR5KJYAlA3jQVzodz6qAAH17rIWZtV7y4JAPTcACi4/IaAJLdQ0ytWSPJQrAEIO/UePgbmXV5DQImAIUVa2+wrCxJFoIlAJFxeQ0AiVAtxt5gVatKshAsAYiMy2ukjhRdTg0krIeYatpUksUxwdLevXulR48eUq5cOTn99NOlX79+cvDgwajfc9VVV0laWlrI7bbbbgvZZvv27dK+fXspU6aMVK5cWe677z45duyYzT8N4ABcXiM1UDMGtysaQw8xa7skcUywpIHSF198IUuWLJF33nlHVqxYIQMGDMjz+/r37y87d+4M3B577LHAc8ePHzeB0pEjR2T16tXywgsvyPPPPy8jR460+acBHIDLayQfNWPwis5Reoi99JIkmyOCpc2bN8uiRYvk2WeflSZNmkizZs1k2rRpMm/ePNmxY0fU79WMUdWqVQM3zUxZFi9eLF9++aW8/PLL0qBBA7n66qtl3LhxMn36dBNAAZ7G5TWSi5oxeDFg2rZNZNkyf18lvc/MFOnQIdlH5ow+S2vWrDFTb40bNw481qpVKylSpIisW7dOrrvuuly/95VXXjHBkAZKHTp0kBEjRpgAytpv3bp1pUqVKoHt27ZtK7fffrvJYjVs2DDiPg8fPmxulgMHDpj7o0ePmlu8WPuK5z6RE+MchabGtSGcCv7QDr68xokT/lsMGOt8WLlSZM8ekdKlc9/mp59EVqwQadYs5GHGOTEYZ5tcfvnJv584Yes4x7pPRwRLWVlZpp4oWLFixaRChQrmudx0795dzjnnHKlevbps2rRJHnjgAdmyZYu8+XvqWr83OFBS1tfR9jthwgQZM2ZMjsc1U2UFYvGkU4+wH+McgdYI5NU5d+HCfO+WsY6RFnTnRU/WcvkdMM6JwTg7d5yzs7NTP1gaOnSoTJw4Mc8puIIKrmnSDFK1atWkZcuW8s0338i5555b4P0OGzZMhgwZEpJZSk9PlzZt2oRM88Uj4tUXR+vWraV4krqWegHjHAOd6tGGcHoSoct3dVVKAYotGet8Zpbat897u3ffjZhZYpztxzg7f5ytmaGUDpbuuece6dOnT9RtatasaabQdu/eHfK4rljTFXL6XKy03klt3brVBEv6vevXrw/ZZteuXeY+2n5LlixpbuH0l2jHfxi79otQjHMUOi66Cituu2Os83TFFSIVK/qLuSPVLelUqNaU6Xa5BK6Mc2IwzjafqK1bZ/5afN06KR7l9V4Qsf7eklrgXalSJbngggui3kqUKCFNmzaVffv2yYYNGwLf+8EHH8iJEycCAVAsPv30U3OvGSal+/3ss89CAjGNXjU7dOGFF8b1ZwWAuC+n1poxrtEHt7fNaP97hlXvk9Q2wxGr4erUqSPt2rUzbQA0E7Rq1SoZOHCgdO3a1dQjqR9++MEEV1amSKfadGWbBljbtm2Tf/3rX9KrVy+54oorpF69emYbnTbToKhnz57y3//+V9577z0ZPny43HnnnREzRwCQMsup9XF9HnCjN1OrbYYjCrytVW0aIGnNka6Cu/7662Xq1Kkhc5pavG0Va2lG6v3335cpU6bIoUOHTE2Rfo8GQ5aiRYuank26+k2zTGXLlpXevXvL2LFjk/IzAo5Lj2v3bm1KqdlabSFAliP+NCDq2JGxhnccz6NthmZWtW2G/r9I0P8DxwRLuvJtTpRVORkZGeILGlgNjpYvX57nfnW13MICrOYBPE3P6vTNLPisT7MdOm1EtiP+9APhqquSfRRA6l1qKUH/LxwxDQcghaRYehyAy+xMvUstESwBiB1dpQF48FJLBEsA7EmPA4BLLrVEsATA0elx19Gs3Icf+rt36z1ZOnhN0dRrm0GwBMDR6XFX9pXRBqDdu/vvk9RXBkiqzqnVNoNgCYCj0+OuQeE8EEoDom3b/Jf0UXqfmZmUFbcESwAcnR53BQrngcj0vcS69qHeJ+m9hWAJgKPT465A4TyQ0hzTlBJACqGrdHxROA+kNIIlAAVDV+n4oXAeSGlMwwFAslE4D6Q0giUASDYK54GURrAEID5oplg4FM4DKYuaJQCFpz2AdOl78Iou/ZDXbAkf8rGjcB5ISQRLAOLTTDG8R5DVTJGsSP5QOA+kHKbhABQczRQBeADBEoCCo5li4VHrBaQ8puEAFBzNFAuHWi/AEcgsASg4mikWHBfOBRyDYAlAwdFMsWCo9QIchWAJQMHRTLFgqPUCHIVgCUDh0Ewx/6j1AhyFAm8AhUczxfyh1gtwFIIlAPFBM8X813ppMXekuiWdwtTnqfUCUgLTcADsQw+hyKj1AhyFYAmAPXTpe0aGSPPmIt27++/r1k32UaUOar0Ax2AaDkDirhe3Y4f/fsECggFFrRfgCARLABLfQ2joUH+QQFBArRfgAEzDAUhsDyGlz3uxhxA1XIAjkVkCEF/0EIqM68ABjkVmCUB80UMoJ64DBziaY4KlvXv3So8ePaRcuXJy+umnS79+/eTgwYO5br9t2zZJS0uLeHvttdcC20V6ft68eQn6qQAPXi9OeamHENeBAxzPMcGSBkpffPGFLFmyRN555x1ZsWKFDBgwINft09PTZefOnSG3MWPGyCmnnCJXX311yLbPPfdcyHadOnVKwE8EeLiH0KOPeqe4m+vAAY7niJqlzZs3y6JFi+Tjjz+Wxo0bm8emTZsm11xzjUyaNEmqV6+e43uKFi0qVatWDXnsrbfeki5dupiAKZhmqsK3BRCHHkLhNTpWT6EOHcQzqOECHM8RwdKaNWtMQGMFSqpVq1ZSpEgRWbdunVx33XV57mPDhg3y6aefyvTp03M8d+edd8qtt94qNWvWlNtuu0369u1rpuNyc/jwYXOzHDhwwNwfPXrU3OLF2lc894mcGGebaEB0zTX6H1gkK0ukalU5+sc/iixd6q2x1hOx0qVj2y5O48JrOjEYZ+ePc6z7dESwlJWVJZUrVw55rFixYlKhQgXzXCxmzZolderUkcsuuyzk8bFjx0qLFi2kTJkysnjxYrnjjjtMLdRf//rXXPc1YcIEM6UXTr9f9xNvOvUI+zHONtL/F3pSsXSpN8daWwXkRcdn4cK4/rOeG+ckYZydO87Z2dmpHywNHTpUJk6cmOcUXGH9+uuvMmfOHBkxYkSO54Ifa9iwoRw6dEgef/zxqMHSsGHDZMiQISGZJa2RatOmjSlAj2fEqy+O1q1bS/HixeO2X4RinBNkwQI5OnKkLHn4YWl9yy1S/Ndf/dNy+h7g9mk57Vjes6f/78GF3lYG+6WX4joGvKYTg3F2/jhbM0MpHSzdc8890qdPn6jb6NSY1hPt3r075PFjx46ZFXKx1Bq9/vrrJnrs1atXnts2adJExo0bZ6bZSpYsGXEbfTzSc/pLtOM/jF37RSjGOQFL50uVMl9qoGSCpW++8T/u9muhWT9beA1Xerr/grk2/ey8phODcXbuOMe6v6QGS5UqVTK3vDRt2lT27dtn6o4aNWpkHvvggw/kxIkTJriJZQru2muvjenf0rqm8uXL5xooAYjz0nnNrujSebdf/oTrwAGO5YiaJa01ateunfTv319mzJhhUnIDBw6Url27BlbC/fDDD9KyZUt58cUX5ZJLLgl879atW02bgYURagEWLFggu3btkksvvVRKlSpl0nyPPPKI3HvvvQn9+QBXy8/SebddI00DxfDgyG0/I+ABjgiW1CuvvGICJA2IdBXc9ddfL1OnTg08rwHUli1bchRrzZ49W8466yxTTxQp/aar4wYPHiw+n09q1aolkydPNkEZgDjx6tJ5Lm8CuIZjgiVd+aZF2rnJyMgwAU84zRTpLRLNVukNgI28ePkTq0Yr/D3JuryJ22u0AJdxTAdvAC69/Ik+roXObrn8CZc3AVyHYAlA8i9/oivC3FLozOVNANchWAKQuMufhF+aSDNObpuS8mqNFuBijqlZAuBwGhDp5U/ee0/7eZxcHaY+/NA9y+m9WKMFuBzBEoDEsYIgLXLWZnBuXDFm1WhpMXekuiWdetTn3VKjBXgA03AAkrtiLLy+x1oxps87kddqtAAPIFgCkHhuXDGmx6rTiXrR3AoVRF591X/tO7fXaAEewDQcgMRbs8ZdXb1zm06cPFmv6+SeeizAowiWACReVpZ7VoxFa0B5003+TFK3bsk6OgBxwDQcgMSrWtUdK8bcOJ0IIAeCJQCJ17SpO7p604AS8ASCJQCJ55YVYzSgBDyBYAlAcrt6h68Y069HjxY5fNi/uiyVp7BoQAl4AgXeAJIbMHXs6J+m0uzL11+LzJwpMmqUM5pU0oAS8AQySwCSS6fatD1AyZL+jJITmlRaPZW0l1L//s6fTgQQFZklAKm/qkwDD11VplmoZAcekXoqVazov9+z5+RjmlHSQCkVM2IA8oVgCYCzVpUls0llbj2V9u71PzZmjEjt2jSgBFyGYAlA8jlhVVks2a9nnxXJzCRIAlyGmiUAyeeEVWX0VAI8i2AJQOqsKsutSaXSa6xpsXey2gk4IfsFwBYESwBSu0ml5ccfRW6+WaR5c5GMjMSvjnNC9guALQiWAKR2k8pIEt1OQDNZeqtQIfdtnHKJFgD5RrAEILUCpm3bRJYtE3n5Zf/UWySJvEitBmSayWrVyr/qLRJ6KgGuRrAEIDWbVGqGSafekllQbbUKiFbYrbTeSrNi9FQCXInWAQBSU6yF0m+84b+Pd1+jaK0CLDotp128NbgjowS4FpklAKkp1kLpp56Kb9G3dSmTSJdeCafTchokESgBrkawBMC57QTiXfRt1Sdp8DV+fGzfQ6sAwPUIlgA4t51APIu+Y61PCkerAMD1CJYAuKOdQHDR97RpsQdMut3SpSL9+0evTwpHqwDAMwiWADinncDAgbF9z+DBsdUwxdIWIBJaBQCewmo4AM5pJ2AVdMdaw3T99SJjxojUru2fLrvsMpHVq/11Rl9/7S/izk82yaK1VBoo0SoA8ATHZJYefvhhueyyy6RMmTJy+umnx/Q9Pp9PRo4cKdWqVZPSpUtLq1at5Gt9gwyyd+9e6dGjh5QrV87st1+/fnLw4EGbfgoACSv6toKgUaNEunf3F22XKeO/16/18fwGSsOH+zNcmZkESoCHOCZYOnLkiNx4441y++23x/w9jz32mEydOlVmzJgh69atk7Jly0rbtm3lt99+C2yjgdIXX3whS5YskXfeeUdWrFghAwYMsOmnAJDQou9wBe32bdUnaSaKnkqA5zgmWBozZowMHjxY6tatG3NWacqUKTJ8+HDp2LGj1KtXT1588UXZsWOHvP3222abzZs3y6JFi+TZZ5+VJk2aSLNmzWTatGkyb948sx0AFxR9Fxb1SYDnubZmKTMzU7KysszUm+W0004zQdGaNWuka9eu5l6n3ho3bhzYRrcvUqSIyURdd911Efd9+PBhc7McOHDA3B89etTc4sXaVzz3iZwYZweOdYcOItdcI/LMMyLDhomtdNrv0Uf9/6ZDXiO8phODcXb+OMe6T9cGSxooqSpVqoQ8rl9bz+l95cqVQ54vVqyYVKhQIbBNJBMmTDCZrnCLFy82NVXxplOEsB/j7MCx1pVsc+dKQixcKE7DazoxGGfnjnN2dnbqB0tDhw6ViRMnRt1Gp8ouuOACSSXDhg2TIUOGhGSW0tPTpU2bNqZQPJ4Rr744WrduLcWLF4/bfhGKcXb4WC9YINKzp//vBVnZltu020sv+bNJDsRrOjEYZ+ePszUzlNLB0j333CN9+vSJuk3NmjULtO+qVaua+127dpnVcBb9ukGDBoFtdu/eHfJ9x44dMyvkrO+PpGTJkuYWTn+JdvyHsWu/CMU4O3SsrVVpetHb/HbfjkQLuV3SFoDXdGIwzs4d51j3l9RgqVKlSuZmhxo1apiAZ+nSpYHgSCNIrUWyVtQ1bdpU9u3bJxs2bJBGjRqZxz744AM5ceKEqW0C4BAa2HTsKPLRR6E9lPLKNmkWSZ8P7sWk7Qko5AbgxJql7du3m4yP3h8/flw+/fRT83itWrXklFNOMX/X6TqtJ9LC7LS0NLn77rtl/PjxUrt2bRM8jRgxQqpXry6dOnUy29epU0fatWsn/fv3N+0FNNU3cOBAU/yt2wFwaONKddFFObNNuk1w+wCaSwJwU7CkzSVfeOGFwNcNGzY098uWLZOrfn+D3LJli+zfvz+wzf333y+HDh0yfZM0g6StAbRVQKlSpQLbvPLKKyZAatmypVkFd/3115veTAAcLjzbFN7BmywSALcFS88//7y55dVbKZhml8aOHWtuudGVb3PmzInbcQJI4WyTCv8aANzSlBIAACAZCJYAAACiIFgCAACIgmAJAAAgCoIlAACAKAiWAAAAoiBYAgAAiIJgCQAAIAqCJQAAADd08E5lVudwvVBvPOm16rKzs81+uaK1fRjnxGGsE4NxTgzG2fnjbH1uh18BJBzBUhz88ssv5j49PT3ZhwIAAArwOX7aaafl+nyaL69wCnk6ceKE7NixQ0499VRzPbp4RrwagH333XdSrly5uO0XoRjnxGGsE4NxTgzG2fnjrCGQBkrVq1eXIkVyr0wisxQHOsBnnXWWbfvXFwf/Ee3HOCcOY50YjHNiMM7OHudoGSULBd4AAABRECwBAABEQbCUwkqWLCmjRo0y97AP45w4jHViMM6JwTh7Z5wp8AYAAIiCzBIAAEAUBEsAAABRECwBAABEQbAEAAAQBcFSCps+fbpkZGRIqVKlpEmTJrJ+/fpkH5KrTJgwQf74xz+azuuVK1eWTp06yZYtW5J9WK736KOPmk73d999d7IPxXV++OEHufnmm6VixYpSunRpqVu3rnzyySfJPixXOX78uIwYMUJq1Khhxvjcc8+VcePG5XltMeRtxYoV0qFDB9NNW98j3n777ZDndYxHjhwp1apVM2PfqlUr+frrryURCJZS1Pz582XIkCFmueTGjRulfv360rZtW9m9e3eyD801li9fLnfeeaesXbtWlixZYi7W2KZNGzl06FCyD821Pv74Y3nmmWekXr16yT4U1/n555/l8ssvNxca/fe//y1ffvmlPPHEE1K+fPlkH5qrTJw4UZ5++ml56qmnZPPmzebrxx57TKZNm5bsQ3O8Q4cOmc86TRREouM8depUmTFjhqxbt07Kli1rPhd/++03+w9OWwcg9VxyySW+O++8M/D18ePHfdWrV/dNmDAhqcflZrt379ZTQ9/y5cuTfSiu9Msvv/hq167tW7Jkie/KK6/0DRo0KNmH5CoPPPCAr1mzZsk+DNdr376975Zbbgl5rHPnzr4ePXok7ZjcSER8b731VuDrEydO+KpWrep7/PHHA4/t27fPV7JkSd/cuXNtPx4ySynoyJEjsmHDBpNiDL7+nH69Zs2apB6bm+3fv9/cV6hQIdmH4kqaxWvfvn3I6xrx869//UsaN24sN954o5lWbtiwocycOTPZh+U6l112mSxdulT+7//+z3z93//+V1auXClXX311sg/N1TIzMyUrKyvk/UOv6aYlKon4XORCuinop59+MvPiVapUCXlcv/7qq6+SdlxuduLECVNDo9MYF110UbIPx3XmzZtnppN1Gg72+N///memh3T6/sEHHzRj/de//lVKlCghvXv3TvbhucbQoUPlwIEDcsEFF0jRokXNe/XDDz8sPXr0SPahuVpWVpa5j/S5aD1nJ4Il4Pesx+eff27OEBFf3333nQwaNMjUheliBdgX8Gtm6ZFHHjFfa2ZJX9Na30GwFD+vvvqqvPLKKzJnzhz5wx/+IJ9++qk50dKiZMbZvZiGS0FnnHGGOWPZtWtXyOP6ddWqVZN2XG41cOBAeeedd2TZsmVy1llnJftwXEenlHVhwsUXXyzFihUzNy2u10JN/buemaPwdIXQhRdeGPJYnTp1ZPv27Uk7Jje67777THapa9euZrVhz549ZfDgwWZ1LexjffYl63ORYCkFadq8UaNGZl48+KxRv27atGlSj81NtIZQA6W33npLPvjgA7MUGPHXsmVL+eyzz8wZuHXTDIhOW+jf9cQAhadTyOGtL7Su5pxzzknaMblRdna2qSENpq9hfY+GffT9WYOi4M9FnQ7VVXGJ+FxkGi5Fad2BpnT1Q+WSSy6RKVOmmGWVffv2TfahuWrqTVPp//znP02vJWveW4sGtYcH4kPHNrwOTJf8ai8g6sPiR7MbWnys03BdunQxfdn+8Y9/mBviR/sAaY3S2Wefbabh/vOf/8jkyZPllltuSfahOd7Bgwdl69atIUXdekKli250vHW6c/z48VK7dm0TPGm/K53+1B55trN9vR0KbNq0ab6zzz7bV6JECdNKYO3atck+JFfRl3+k23PPPZfsQ3M9WgfYY8GCBb6LLrrILKe+4IILfP/4xz+SfUiuc+DAAfPa1ffmUqVK+WrWrOl76KGHfIcPH072oTnesmXLIr4n9+7dO9A+YMSIEb4qVaqY13jLli19W7ZsScixpekf9odkAAAAzkTNEgAAQBQESwAAAFEQLAEAAERBsAQAABAFwRIAAEAUBEsAAABRECwBAABEQbAEAAAQBcESAATRC/vqZUM6d+4c8vj+/fslPT1dHnrooaQdG4DkoIM3AITRC9A2aNBAZs6caS74q3r16iX//e9/5eOPPzYXuwbgHQRLABDB1KlTZfTo0fLFF1+Yi9LeeOONJlCqX79+sg8NQIIRLAFABPrW2KJFCylatKh89tlnctddd8nw4cOTfVgAkoBgCQBy8dVXX0mdOnWkbt26snHjRilWrFiyDwlAElDgDQC5mD17tpQpU0YyMzPl+++/T/bhAEgSMksAEMHq1avlyiuvlMWLF8v48ePNY++//76kpaUl+9AAJBiZJQAIk52dLX369JHbb79dmjdvLrNmzTJF3jNmzEj2oQFIAjJLABBm0KBBsnDhQtMqQKfh1DPPPCP33nuvKfbOyMhI9iECSCCCJQAIsnz5cmnZsqV8+OGH0qxZs5Dn2rZtK8eOHWM6DvAYgiUAAIAoqFkCAACIgmAJAAAgCoIlAACAKAiWAAAAoiBYAgAAiIJgCQAAIAqCJQAAgCgIlgAAAKIgWAIAAIiCYAkAACAKgiUAAIAoCJYAAAAkd/8PNSFEIaZbqvIAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.scatter(x, np.sin(x), label='sin(x)', color='red')\n",
+    "#plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"Мультиграфик\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "bd42a32b-4bfd-4acc-9974-1b8bd4c55dcc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.hist(np.sin(x), bins=30, label='sin(x)', color='red', edgecolor='black')\n",
+    "#plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"Мультиграфик\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "8f6279a5-850e-41ef-9920-75b3c9083302",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "\n",
+    "df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\"] # догадайтесь откуда df и её содержимое взялось\n",
+    "sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "02e3167e-9694-4932-b7ae-3cf2498d2dde",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "\n",
+    "df[\"Категория\"] = [1, 2, 6, 11] # догадайтесь откуда df и её содержимое взялось\n",
+    "sns.histplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "fda61745-bc9b-4112-8ef3-9c4fac2f0751",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "\n",
+    "df[\"Категория\"] = [1, 2, 6, 11] # догадайтесь откуда df и её содержимое взялось\n",
+    "sns.scatterplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "2eac5f2b-f14c-4f51-8de9-9808b7950e70",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkAAAAGwCAYAAABB4NqyAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAALGpJREFUeJzt3QtUlVX+//EvF0WGBEdNgcQLlFKGWlYkmVODaQwpmmm4LPE2OTqljklpM2gOEmmNY4qjU+OoectsUrussVHyEqOG93IyFcf7XUfBKyqc/9r7v875ceCAaMBzOPv9WutZ8pznefbZ52Scj3t/93O8bDabTQAAAAzibXUHAAAAqhoBCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOL5Wd8AdFRYWyrFjx6R27dri5eVldXcAAEA5qFsbXrhwQUJDQ8Xbu+wxHgKQCyr8hIWFWd0NAABwGw4fPiyNGjUq8xwCkAtq5Mf+BgYGBlrdHQAAUA55eXl6AMP+OV4WApAL9mkvFX4IQAAAVC/lKV+hCBoAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjGNpAFLf2DpixAhp0qSJ+Pv7S0xMjGzatMlxvF+/fvp21kW3p59++qbtTp8+XZo2bSq1atWS6Ohoyc7OruRXAgAAqhNLA9CgQYNk5cqVMm/ePPn++++lU6dO0rFjRzl69KjjHBV4jh8/7tgWLVpUZpuLFy+WkSNHyrhx42Tr1q3SunVr6dy5s5w6daoKXhEAAKgOvGw2m82KJ75y5Yr+ttbly5dLfHy84/G2bdtKXFycTJgwQY8AnT9/XpYtW1budtWIz8MPPywZGRl6v7CwUH8z7CuvvCKjR48u97fJBgUFSW5uLl+GCgBANXErn9+WjQDduHFDCgoK9DRVUWoqLCsry7G/Zs0aadCggbRo0UKGDBkiZ8+eLbXNa9euyZYtW/Qokp23t7fe37BhQ6nX5efn6zet6AYAADyXr1VPrEZ/2rVrJ6mpqXLvvfdKw4YN9fSWCip33323Y/rr2WeflWbNmsm+ffvkjTfe0KND6hwfH58SbZ45c0aHKtVWUWr/xx9/LLUv6enpMn78eKkqHXoOr7LnAoCfYt2S96zuAuB5NUCq9kfNwN11113i5+cnU6dOld69e+tRGyUxMVG6du0qUVFR0q1bN/niiy90kbQaFapIY8aM0cNl9u3w4cMV2j4AAHAvlgagiIgIWbt2rVy8eFGHDrVa6/r16xIeHu7yfPV4/fr1JScnx+VxdUyNDJ08edLpcbUfHBxcaj9U+FJzhUU3AADgudziPkABAQESEhIi586dk6+++koSEhJcnnfkyBFdA6TOdaVmzZq6iDozM9PxmCqCVvtqug0AAMDyAKTCzooVK2T//v16OfyTTz4pkZGR0r9/fz0qlJycLBs3bpQDBw7oEKOCkaoPUsva7WJjYx0rvhS1BP6DDz6QuXPnyq5du3Th9KVLl3SbAAAAlhZBK6reRtXfqJGdunXrSo8ePSQtLU1q1KihV4l99913OsiopfChoaH6PkGqaFpNWdmp4mhV/Gz3/PPPy+nTp2Xs2LFy4sQJadOmjQ5ZxQujAQCAuSy7D5A7q+z7ALEKDEB1wSowVCfV4j5AAAAAViEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjWBqALly4ICNGjJAmTZqIv7+/xMTEyKZNm/Sx69evy+uvvy5RUVESEBAgoaGh0rdvXzl27FiZbb755pvi5eXltEVGRlbRKwIAANWBr5VPPmjQINm5c6fMmzdPB5z58+dLx44d5YcffpA77rhDtm7dKikpKdK6dWs5d+6cDB8+XLp27SqbN28us92WLVvKqlWrHPu+vpa+TAAA4GYsSwZXrlyRf/zjH7J8+XLp0KGDY/Tm888/lxkzZsiECRNk5cqVTtdkZGTII488IocOHZLGjRuX2rYKPMHBweXuS35+vt7s8vLybus1AQCA6sGyKbAbN25IQUGB1KpVy+lxNRWWlZXl8prc3Fw9pVWnTp0y2967d68eUQoPD5c+ffrowFSW9PR0CQoKcmxhYWG38YoAAEB1YVkAql27trRr105SU1N1XY8KQ2oKbMOGDXL8+PES51+9elXXBPXu3VsCAwNLbTc6OlrmzJkjK1as0CNJ+/fvl8cff1zXG5VmzJgxOlzZt8OHD1fY6wQAAO7H0uIYVfszYMAAueuuu8THx0cefPBBHXC2bNnidJ4qiO7Vq5fYbDYdasoSFxfn+LlVq1Y6EKki648//lgGDhzo8ho/Pz+9AQAAM1i6CiwiIkLWrl0rFy9e1KMu2dnZOuyoqavi4efgwYO6Jqis0R9X1HRZ8+bNJScnpxJeAQAAqI7c4j5Aapl7SEiIXun11VdfSUJCglP4UTU9alVXvXr1brltFa727dun2wcAALA8AKmwo2p1VJ2OGt158skn9T17+vfvr8PPc889p5e8L1iwQNcInThxQm/Xrl1ztBEbG6tXh9mNGjVKjyodOHBA1q9fL927d9fTa2pqDQAAwPIaIFVwrAqQjxw5InXr1pUePXpIWlqa1KhRQweYzz77TJ/Xpk0bp+tWr14tTzzxhP5Zje6cOXPGcUy1pcLO2bNn5c4775T27dvLxo0b9c8AAACKl01VFsOJug+QWg6vAtqt1hyVR4eewyu8TQCoDOuWvGd1F4BK+fx2ixogAACAqkQAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMY2kAunDhgowYMUKaNGki/v7+EhMTI5s2bXIct9lsMnbsWAkJCdHHO3bsKHv37r1pu9OnT5emTZtKrVq1JDo6WrKzsyv5lQAAgOrE0gA0aNAgWblypcybN0++//576dSpkw45R48e1ccnTZokU6dOlZkzZ8q3334rAQEB0rlzZ7l69WqpbS5evFhGjhwp48aNk61bt0rr1q31NadOnarCVwYAANyZl00Ns1jgypUrUrt2bVm+fLnEx8c7Hm/btq3ExcVJamqqhIaGyquvviqjRo3Sx3Jzc6Vhw4YyZ84cSUxMdNmuGvF5+OGHJSMjQ+8XFhZKWFiYvPLKKzJ69GiX1+Tn5+vNLi8vT1+jni8wMLCCX7lIh57DK7xNAKgM65a8Z3UXgHJTn99BQUHl+vy2bAToxo0bUlBQoKepilJTXVlZWbJ//345ceKEHhGyUy9KBZwNGza4bPPatWuyZcsWp2u8vb31fmnXKOnp6bpt+6bCDwAA8FyWBSA1+tOuXTs90nPs2DEdhubPn6+DyvHjx3X4UdSIT1Fq336suDNnzuh2buUaZcyYMTot2rfDhw9XyGsEAADuydIaIFX7o2bg7rrrLvHz89P1Pr1799ajNlVJPbcaKiu6AQAAz2VpAIqIiJC1a9fKxYsX9aiLWq11/fp1CQ8Pl+DgYH3OyZMnna5R+/ZjxdWvX198fHxu6RoAAGAet7gPkFrdpZa6nzt3Tr766itJSEiQZs2a6dCSmZnpVNykVoOpqTNXatasqYuoi16jiqDVfmnXAAAA8/ha+eQq7KgpsBYtWkhOTo4kJydLZGSk9O/fX7y8vPQ9giZMmCD33HOPDkQpKSl6ZVi3bt0cbcTGxkr37t3l5Zdf1vtqCXxSUpI89NBD8sgjj8iUKVPk0qVLuk0AAADLA5AqOFYFyEeOHJG6detKjx49JC0tTWrUqKGPv/baazq8vPTSS3L+/Hlp3769rFixwmnl2L59+3Txs93zzz8vp0+f1jdQVIXPbdq00dcUL4wGAADmsuw+QJ5yH4HbwX2AAFQX3AcI1Um1uA8QAACAVQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOP4Wt0BE61b8p7VXQAAwGiMAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGsTQAFRQUSEpKijRr1kz8/f0lIiJCUlNTxWazOc7x8vJyub3zzjultvvmm2+WOD8yMrKKXhUAAHB3vlY++cSJE2XGjBkyd+5cadmypWzevFn69+8vQUFBMmzYMH3O8ePHna755z//KQMHDpQePXqU2bZqb9WqVY59X19LXyoAAHAjlqaC9evXS0JCgsTHx+v9pk2byqJFiyQ7O9txTnBwsNM1y5cvlyeffFLCw8PLbFsFnuLXAgAAWD4FFhMTI5mZmbJnzx69v2PHDsnKypK4uDiX5588eVK+/PJLPQJ0M3v37pXQ0FAdlPr06SOHDh0q9dz8/HzJy8tz2gAAgOeydARo9OjROmyo+hwfHx9dE5SWlqYDiytqqqx27dry7LPPltludHS0zJkzR1q0aKGn0MaPHy+PP/647Ny5U19fXHp6uj4HAACYwctWtOK4in300UeSnJysC5pVzc727dtlxIgRMnnyZElKSipxvgpKTz31lEybNu2Wnuf8+fPSpEkT3a6r0SM1AqQ2OxXKwsLCJDc3VwIDA2/z1QEAgKqkPr9VHXF5Pr8tHQFS4UeNAiUmJur9qKgoOXjwoB6RKR6AvvnmG9m9e7csXrz4lp+nTp060rx5c8nJyXF53M/PT28AAMAMltYAXb58Wby9nbugpsIKCwtLnDtr1ixp27attG7d+paf5+LFi7Jv3z4JCQn5Sf0FAACewdIA1KVLF13zowqbDxw4IEuXLtXTVN27dy8xpLVkyRIZNGiQy3ZiY2MlIyPDsT9q1ChZu3atblOtNFPtqWDVu3fvSn9NAADA/Vk6BaZqedSNEIcOHSqnTp3Sq7YGDx4sY8eOLVErpEqVSgswanTnzJkzjv0jR47oc8+ePSt33nmntG/fXjZu3Kh/BgAAsLQI2hOKqAAAQPX7/Oa7wAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcW7rqzDUF5h6eXmVerygoOCn9AkAAMD9ApD60lIAAACjAlBCQoLT/qeffirbt2+X+++/X3r16lVRfQMAAHDPGqCJEyfqb15fsWKFDBw4UMaPH18xPQMAAHDXADR37lz529/+JtnZ2bJ8+XKZPXt2xfQMAADAXQPQsWPH5NFHH9U/qz+PHj1aEf0CAABw3wCkVnz5+v7/UiIfHx8pLCysiH4BAAC4VxH0Aw884FgGf+XKFenSpYvUrFlTbDZbRfcPAADAPQJQt27dSl0RVvQYAACAO/KyMWxTQl5engQFBUlubq4EBgZa3R0AAFDBn9++t/sEZSE0AAAAd3ZbAahOnTouvwpDDSapx/kqDAAA4HEBSPnkk0+kbt26FdsbAAAAdw5Ajz32mDRo0KBiewMAAODOAeiHH36Qs2fPSkBAgAQHB+tl8AAAAB59I8TY2Fhp2bKlNGvWTIegqKgo+fOf/1yxvQMAAHCXEaD9+/frgufr16/rFWHq6zDUd4GlpKTIjRs3JDk5ueJ7CgAA4I73AZo3b5788Y9/lL1790p1xn2AAACofir9PkClSUxM1NNiAAAA7qzCb4R49913/5T+AAAAVDpuhAgAAIzDjRABAIBxuBEiAAAwDjdCBAAAxrH0RoiqVkjdO0i14e/vLxEREZKamqpriez69eun64qKbk8//fRN254+fbo0bdpUatWqJdHR0fo+RQAAAJbfCHHixIkyY8YMmTt3rg5Tmzdvlv79++s1/MOGDXOcpwLP7NmzHft+fn5ltrt48WIZOXKkzJw5U4efKVOmSOfOnWX37t1M2wEAAGtvhPjMM89Iw4YNZdasWY7HevTooUeD5s+f7xgBOn/+vCxbtqzc/VCh5+GHH5aMjAy9X1hYKGFhYfLKK6/I6NGjb3o9N0IEAKD6uZXP79ueAivtRohq9KW8YmJiJDMzU/bs2aP3d+zYIVlZWRIXF+d03po1a/TITYsWLWTIkCG69qg0165dky1btkjHjh0dj3l7e+v9DRs2uLwmPz9fv2lFNwAA4Lkq9E7QNWrUkAcffLDc56vRGBU2IiMjxcfHR9cEpaWlSZ8+fZymv5599lldJ7Rv3z554403dEBSYUZdU9yZM2d0O2pkqSi1/+OPP7rsR3p6uowfP/6WXisAADAsAKmAoQqeP/74Yzl06JAedSnqf//7X7naUdcvWLBAFi5cqGuAtm/fLiNGjJDQ0FBJSkpyjCrZqULrVq1a6WJpNSqkCrErwpgxY3TNkJ0KZWrKDAAAeKbbmgJToyWTJ0+W559/Xs+zqfCgRmnUVNObb75Z7nZUsbQaBVIhR4WbF198UX73u9/pEZnShIeHS/369SUnJ8flcXVMjQydPHnS6XG1r5bru6KKqtVcYdENAAB4rtsKQGrU5oMPPpBXX31VfH19pXfv3vK3v/1Nxo4dKxs3bix3O5cvX9ahqSgVXlTRcmmOHDmia4BCQkJcHlf3I2rbtq2uLbJT7an9du3albtvAADAc91WADpx4oQesVHuuOMOPQpkX9X15ZdflrudLl266Jofdc2BAwdk6dKlemSpe/fu+vjFixf1KJEKVeq4CjEJCQn6C1fVsnY7NRVmX/GlqBEpFdDU8vpdu3bpwulLly7pJfYAAAC3VQPUqFEjOX78uDRu3FjX4/zrX//Sxc+bNm266T16ipo2bZq+d9DQoUPl1KlTuvZn8ODBeiTJPhr03Xff6SCjlsKr4506ddI3Syz6PKo4WhU/26mpudOnT+t2VFhr06aNrFixokRhNAAAMNNt3QdI1e2oOhm1Ikste3/hhRf0XZdVQbSq4Xn77belOuM+QAAAePbnd4XcCFFNUa1fv17uuecePa1V3RGAAACofqr0Rohq2uvzzz/XU1jqSQEAADyqBkjV/Gzbtk3q1aun91euXCnx8fG6Hket5nr33Xdl0aJF0rNnz8rqLwAAwE92SyNAagm6ugmi3TvvvKOXwKsC5XPnzukC5kmTJv30XgEAAFSinzQFppaYqy8YVau11AiQ+rm8X4QKAABQLQOQGvmpW7euY//nP/+5XLhwoSL6BQAA4B4ByMvLS2/FHwMAAPDYImi1Yr5fv36OmxBevXpVfvOb30hAQIDez8/Pr5xeAgAAWBWA7N/QbqdugFhc3759f3qvAAAA3CUAzZ49u/J6AgAAUEV+8o0QAQAAqhsCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEsDUAFBQWSkpIizZo1E39/f4mIiJDU1FSx2Wz6+PXr1+X111+XqKgoCQgIkNDQUOnbt68cO3aszHbffPNN8fLyctoiIyOr6FUBAAB352vlk0+cOFFmzJghc+fOlZYtW8rmzZulf//+EhQUJMOGDZPLly/L1q1bdUhq3bq1nDt3ToYPHy5du3bV55ZFtbdq1SrHvq+vpS8VAAC4EUtTwfr16yUhIUHi4+P1ftOmTWXRokWSnZ2t91UQWrlypdM1GRkZ8sgjj8ihQ4ekcePGpbatAk9wcHAlvwIAAFAdWToFFhMTI5mZmbJnzx69v2PHDsnKypK4uLhSr8nNzdVTWnXq1Cmz7b179+ops/DwcOnTp48OTKXJz8+XvLw8pw0AAHguS0eARo8ercOGqs/x8fHRNUFpaWk6sLhy9epVXRPUu3dvCQwMLLXd6OhomTNnjrRo0UKOHz8u48ePl8cff1x27twptWvXLnF+enq6PgcAAJjBy2avOLbARx99JMnJyfLOO+/omp3t27fLiBEjZPLkyZKUlOR0riqI7tGjhxw5ckTWrFlTZgAq7vz589KkSRPd7sCBA12OAKnNToWysLAwPdp0K88DAACsoz6/VflMeT6/LR0BUuFHjQIlJibqfbXa6+DBg3pEpmgAUuGnV69e+tjXX399y6FETZc1b95ccnJyXB738/PTGwAAMIOlAUit8vL2di5DUlNhhYWFJcKPqulZvXq11KtX75af5+LFi7Jv3z558cUXxR106Dnc6i7AA61b8p7VXYAH4vcVPPX3laVF0F26dNE1P19++aUcOHBAli5dqqepunfv7gg/zz33nF7yvmDBAl0jdOLECb1du3bN0U5sbKxeHWY3atQoWbt2rW5TrTRT7algpWqHAAAALB0BmjZtmr7Hz9ChQ+XUqVN61dbgwYNl7Nix+vjRo0fls88+0z+3adPG6Vo1GvTEE0/on9XozpkzZxzHVJ2QCjtnz56VO++8U9q3by8bN27UPwMAAFgagNSKrClTpujNFXVfoPLUaKuRnuLF1QAAAKXhu8AAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDiWBqCCggJJSUmRZs2aib+/v0REREhqaqrYbDbHOernsWPHSkhIiD6nY8eOsnfv3pu2PX36dGnatKnUqlVLoqOjJTs7u5JfDQAAqC4sDUATJ06UGTNmSEZGhuzatUvvT5o0SaZNm+Y4R+1PnTpVZs6cKd9++60EBARI586d5erVq6W2u3jxYhk5cqSMGzdOtm7dKq1bt9bXnDp1qopeGQAAcGeWBqD169dLQkKCxMfH69Ga5557Tjp16uQYrVGjP1OmTJE//OEP+rxWrVrJhx9+KMeOHZNly5aV2u7kyZPl17/+tfTv31/uu+8+HZ5+9rOfyd///neX5+fn50teXp7TBgAAPJelASgmJkYyMzNlz549en/Hjh2SlZUlcXFxen///v1y4sQJPe1lFxQUpKe0NmzY4LLNa9euyZYtW5yu8fb21vulXZOenq7btW9hYWEV/EoBAIA78bXyyUePHq1HWyIjI8XHx0fXBKWlpUmfPn30cRV+lIYNGzpdp/btx4o7c+aMbsfVNT/++KPLa8aMGaOnzOxUnwhBAAB4LksD0McffywLFiyQhQsXSsuWLWX79u0yYsQICQ0NlaSkpCrrh5+fn94AAIAZLA1AycnJehQoMTFR70dFRcnBgwf1lJQKQMHBwfrxkydP6lVgdmq/TZs2LtusX7++Hk1S5xSl9u3tAQAAs1laA3T58mVdn1OUCi+FhYX6Z7U8XoUWVSdUdHpKrQZr166dyzZr1qwpbdu2dbpGtaf2S7sGAACYxdIRoC5duuian8aNG+spsG3btukVXAMGDNDHvby89JTYhAkT5J577tGBSN03SE2RdevWzdFObGysdO/eXV5++WW9r+p51AjSQw89JI888oheSXbp0iW9KgwAAMDSAKTu96MCzdChQ/U9elSwGTx4sL7xod1rr72mw8tLL70k58+fl/bt28uKFSv0DQ7t9u3bp4uf7Z5//nk5ffq0bkcVS6vpMnVN8cJoAABgJi9b0dsuwzHNppbD5+bmSmBgYIW336Hn8ApvE1i35D2ruwAPxO8rVKffV7fy+c13gQEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA41gagJo2bSpeXl4ltt/+9rdy4MABl8fUtmTJklLb7NevX4nzn3766Sp9XQAAwL35WvnkmzZtkoKCAsf+zp075amnnpKePXtKWFiYHD9+3On8999/X9555x2Ji4srs10VeGbPnu3Y9/Pzq4TeAwCA6srSAHTnnXc67b/99tsSEREhv/jFL/TITXBwsNPxpUuXSq9eveSOO+4os10VeIpfW5b8/Hy92eXl5ZX7WgAAUP24TQ3QtWvXZP78+TJgwAAdforbsmWLbN++XQYOHHjTttasWSMNGjSQFi1ayJAhQ+Ts2bNlnp+eni5BQUGOTY0+AQAAz+U2AWjZsmVy/vx5XcPjyqxZs+Tee++VmJiYm05/ffjhh5KZmSkTJ06UtWvX6imzolNtxY0ZM0Zyc3Md2+HDh3/y6wEAAO7L0imw4gFHBZXQ0NASx65cuSILFy6UlJSUm7aTmJjo+DkqKkpatWqlp9XUqFBsbGypU2bUCQEAYA63GAE6ePCgrFq1SgYNGuTy+CeffCKXL1+Wvn373nLb4eHhUr9+fcnJyamAngIAAE/gFgFIrdhSNTvx8fGljg517dq1RNF0eRw5ckTXAIWEhFRATwEAgCewPAAVFhbqAJSUlCS+viVn5NTIzbp160odHYqMjNSrw5SLFy9KcnKybNy4Ud9HSNUBJSQkyN133y2dO3eu9NcCAACqB8sDkJr6OnTokF795crf//53adSokXTq1Mnl8d27d+vCZcXHx0e+++47PVrUvHlzvWKsbdu28s0331DjAwAA3KcIWgUbm81W6vG33npLb6Upeq2/v7989dVXFd5HAADgWSwfAQIAAKhqBCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwjpfNZrNZ3Ql3k5eXJ0FBQZKbmyuBgYFWdwcAAFTw5zcjQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADj+FrdAXdks9n0n3l5eVZ3BQAAlJP9c9v+OV4WApALFy5c0H+GhYVZ3RUAAHAbn+NBQUFlnuNlK09MMkxhYaEcO3ZMateuLV5eXmI6lahVGDx8+LAEBgZa3R2PxftcNXifqwbvc9XgfXamIo0KP6GhoeLtXXaVDyNALqg3rVGjRlZ3w+2o/7n4H6zy8T5XDd7nqsH7XDV4n//PzUZ+7CiCBgAAxiEAAQAA4xCAcFN+fn4ybtw4/ScqD+9z1eB9rhq8z1WD9/n2UQQNAACMwwgQAAAwDgEIAAAYhwAEAACMQwACAADGIQDBpfT0dHn44Yf13bAbNGgg3bp1k927d1vdLY/39ttv67uPjxgxwuqueKSjR4/KCy+8IPXq1RN/f3+JioqSzZs3W90tj1JQUCApKSnSrFkz/R5HRERIampqub6bCaVbt26ddOnSRd/hWP2OWLZsmdNx9f6OHTtWQkJC9PvesWNH2bt3r2X9rQ4IQHBp7dq18tvf/lY2btwoK1eulOvXr0unTp3k0qVLVnfNY23atEn++te/SqtWrazuikc6d+6cPPbYY1KjRg355z//KT/88IP86U9/kp///OdWd82jTJw4UWbMmCEZGRmya9cuvT9p0iSZNm2a1V2r1tTv3tatW8v06dNdHlfv8dSpU2XmzJny7bffSkBAgHTu3FmuXr1a5X2tLlgGj3I5ffq0HglSwahDhw5Wd8fjXLx4UR588EH5y1/+IhMmTJA2bdrIlClTrO6WRxk9erT8+9//lm+++cbqrni0Z555Rho2bCizZs1yPNajRw89KjF//nxL++Yp1AjQ0qVL9ci8oj7G1cjQq6++KqNGjdKP5ebm6v8Oc+bMkcTERIt77J4YAUK5qP+ZlLp161rdFY+kRtvi4+P1sDUqx2effSYPPfSQ9OzZU4f5Bx54QD744AOru+VxYmJiJDMzU/bs2aP3d+zYIVlZWRIXF2d11zzW/v375cSJE06/P9T3YUVHR8uGDRss7Zs748tQcVOFhYW6JkVNH9x///1Wd8fjfPTRR7J161Y9BYbK89///ldPzYwcOVLeeOMN/X4PGzZMatasKUlJSVZ3z6NG2tQ3lEdGRoqPj4+uCUpLS5M+ffpY3TWPpcKPokZ8ilL79mMoiQCEco1O7Ny5U/8rDhXr8OHDMnz4cF1nVatWLau74/FBXo0AvfXWW3pfjQCpv9eqZoIAVHE+/vhjWbBggSxcuFBatmwp27dv1/+AUlM0vM9wJ0yBoUwvv/yyfPHFF7J69Wpp1KiR1d3xOFu2bJFTp07p+h9fX1+9qTorVcyoflb/ekbFUKtj7rvvPqfH7r33Xjl06JBlffJEycnJehRI1Z2oVXYvvvii/O53v9MrS1E5goOD9Z8nT550elzt24+hJAIQXFJFdSr8qEK7r7/+Wi9pRcWLjY2V77//Xv8r2b6pUQo1XaB+VlMIqBhqCrf4rRxUnUqTJk0s65Mnunz5snh7O3+0qL/HagQOlUP9flZBR9Ve2alpSLUarF27dpb2zZ0xBYZSp73UEPby5cv1vYDs88iqsE6t5kDFUO9t8boqtXxV3aeGequKpUYhVIGumgLr1auXZGdny/vvv683VBx1rxpV89O4cWM9BbZt2zaZPHmyDBgwwOquVfuVojk5OU6Fz+ofSWphinqv1TSjWkF6zz336ECk7sWkph3tK8XggloGDxSn/mq42mbPnm111zzeL37xC9vw4cOt7oZH+vzzz23333+/zc/PzxYZGWl7//33re6Sx8nLy9N/fxs3bmyrVauWLTw83Pb73//elp+fb3XXqrXVq1e7/J2clJSkjxcWFtpSUlJsDRs21H+/Y2Njbbt377a6226N+wABAADjUAMEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAJQqfr161fi+4hOnz6tv+ssOjpacnNzLesbAHMRgABUKRV+fvnLX+ov1f3Xv/6lv2AXAKoaAQhAlTlz5ozExsaKn5+frFy50hF+1LeFR0VFSUBAgISFhcnQoUP1t18ra9asES8vr1I3u6ysLHn88cd1sFJtDBs2TC5duuQ43rRp0xLXjho1ynF8xowZEhERITVr1pQWLVrIvHnznPquzlfnxMXF6ecIDw+XTz75xHH8wIED+hz1Dd126hu51WNTpkxxPPbjjz/KU089pV+7vR916tSp8PcaQNkIQACqxNmzZ6Vjx47i6+urw0/RD31vb2+ZOnWq/Oc//5G5c+fK119/La+99po+FhMTI8ePH9fbP/7xD/2YfV9tyr59++Tpp5+WHj16yHfffSeLFy/Wgejll1926sMf//hHp2vHjRunH1+6dKkMHz5cXn31Vdm5c6cMHjxY+vfvL6tXr3a6XgUa9Rw7duyQPn36SGJiouzatcvl6z1y5IgOPiosFTVgwAC5fv26/Pvf/9Z9KBqOAFQhq7+OHoBnS0pKsnXo0MHWpk0bW40aNWyPPvqo7caNG2Ves2TJElu9evVKPL569Wqbq19bAwcOtL300ktOj33zzTc2b29v25UrV/R+kyZNbH/+859dPl9MTIzt17/+tdNjPXv2tP3qV79y7Kvn/c1vfuN0TnR0tG3IkCH65/379+tztm3bpvf79u2r+1X8ef39/W0LFixw7M+ePdsWFBRU5vsBoOIxAgSg0q1bt04KCwv19FBOTo5MmjTJ6fiqVav01Nhdd90ltWvXlhdffFGPGF2+fLlc7asRmTlz5sgdd9zh2Dp37qyfc//+/Te9Xo3iPPbYY06Pqf3iozvt2rUrse9qBGjr1q16VCk1NbXEsWbNmulj5X1tACqHbyW1CwAOql4mMzNT6tevL3/5y1/khRdekPj4eGnVqpWunXnmmWdkyJAhkpaWJnXr1tXTVwMHDpRr167Jz372s5u2r+qF1LSVqvsprnHjxlLV1FSaqi8KCQkpcWzWrFmSlJSkg56aHrtx44bUqlWryvsImI4RIACVThU4q/Cj9OzZU5599lnp27evDjhbtmzRIzV/+tOf5NFHH5XmzZvLsWPHbqn9Bx98UH744Qe5++67S2yqqPlm7r33Xl2TU5Tav++++5we27hxY4l9dW1Rn332mezZs8epwLoo9Rq7du0qDz30kGzbtk3XJQGoeowAAahy06dP1/cBGj9+vPTq1UsXBU+bNk26dOmig8fMmTNvqb3XX39dBwtV9Dxo0CC9mkwFIlVsnZGRcdPrk5OTdT8eeOABXaj9+eefy6effqqn5opasmSJDi7t27eXBQsWSHZ2th7RKUpN76nXUtrIlSrkVtN1Kvip0akGDRrc0msFUDEYAQJQ5dQ01wcffCATJ06Uq1ev6mXw6mcVilSwSE9Pv6X21FTa2rVr9ciLWgqvgszYsWMlNDS0XNerGzW+99578u6770rLli3lr3/9q8yePVueeOIJp/NUYPvoo4/083344YeyaNGiEqNEatRJTXG5ovqnAtrChQstmZoD8H+8VCV0kX0AgAvqfj2qeLn4Xa0BVE+MAAEAAOMQgAAAgHEoggaAcqBaAPAsjAABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAGKa/wfFTpisM/Qx6QAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 20 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "\n",
+    "df[\"Категория\"] = [1, 2, 6, 11] # догадайтесь откуда df и её содержимое взялось\n",
+    "sns.histplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
+    "sns.pairplot(df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "9ee43629-88d4-4332-a459-b416539eeb8b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "sns.histplot(x=\"Возраст\", y=\"Баллы\", data=df)\n",
+    "\n",
+    "numeric_df = df.select_dtypes(include=['number'])\n",
+    "sns.heatmap(numeric_df.corr(), annot=True)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "3d37f39d-d5d8-4a2a-b2a0-621629ece250",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "4it [00:00, 88.64it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tqdm import tqdm\n",
+    "import time\n",
+    "\n",
+    "for i in tqdm(range(100)):\n",
+    "    time.sleep(0.01)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "f7ef7138-b839-478f-a077-a68f6da7f3b7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "4it [00:00, 91.89it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tqdm import tqdm\n",
+    "import time\n",
+    "\n",
+    "for i in tqdm(df.iterrows()):\n",
+    "    time.sleep(0.01)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "ce9e095f-8033-4ebf-9719-1cf7f529e59a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Загрузка: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 92.20it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tqdm import tqdm\n",
+    "import time\n",
+    "\n",
+    "for i in tqdm(range(100), desc='Загрузка'):\n",
+    "    time.sleep(0.01)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f32feeff-c86f-45d8-9049-1c93f319dde4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/.ipynb_checkpoints/week2_task-checkpoint.ipynb b/.ipynb_checkpoints/week2_task-checkpoint.ipynb
new file mode 100644
index 0000000..363fcab
--- /dev/null
+++ b/.ipynb_checkpoints/week2_task-checkpoint.ipynb
@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..afa1200
--- /dev/null
+++ b/README.md
@@ -0,0 +1 @@
+Лабораторная работа 2
\ No newline at end of file
diff --git a/data.csv b/data.csv
new file mode 100644
index 0000000..a6a45af
--- /dev/null
+++ b/data.csv
@@ -0,0 +1 @@
+WarNum,WarName,WarType,CcodeA,SideA,CcodeB,SideB,Intnl,StartMonth1,StartDay1,StartYear1,EndMonth1,EndDay1,EndYear1,StartMonth2,StartDay2,StartYear2,EndMonth2,EndDay2,EndYear2,TransFrom,WhereFought,Initiator,Outcome,TransTo,SideADeaths,SideBDeaths,Version
500,First Caucasus,5,365,Russia,-8,"Georgians, Dhagestania, Chechens",0,6,10,1818,-9,-9,1822,-8,-8,-8,-8,-8,-8,-8,2,Chechens,1,-8,5000,6000,4.1
501,Sidon-Damascus,6,-8,Sidon,-8,Damascus & Aleppo,0,6,-9,1820,7,21,1821,-8,-8,-8,-8,-8,-8,-8,6,Sidon,2,-8,-9,-9,4.1
502,First Two Sicilies,4,300,Austria,-8,-8,1,3,-9,1821,3,23,1821,-8,-8,-8,-8,-8,-8,-8,2,Liberals,1,-8,-9,-8,4.1
502,First Two Sicilies,4,329,Two Sicilies,-8,Liberals,1,7,2,1820,3,23,1821,-8,-8,-8,-8,-8,-8,-8,2,Liberals,1,-8,-9,-9,4.1
503,Spanish Royalists,4,230,Spain,-8,Royalists,0,12,1,1821,4,6,1823,-8,-8,-8,-8,-8,-8,-8,2,Royalists,4,1,-9,-9,4.1
505,Sardinian Revolt,4,300,Austria,-8,-8,1,3,10,1821,5,8,1821,-8,-8,-8,-8,-8,-8,-8,2,Carbonari,1,-8,-9,-8,4.1
505,Sardinian Revolt,4,325,Sardinia,-8,Carbonari,1,3,10,1821,5,8,1821,-8,-8,-8,-8,-8,-8,-8,2,Carbonari,1,-8,-9,-9,4.1
506,Greek Independence,5,640,Ottoman Empire,-8,Greeks,1,3,25,1821,4,25,1828,-8,-8,-8,-8,-8,-8,-8,2,Greeks,4,4,6000,3000,4.1
506,Greek Independence,5,-8,-8,200,United Kingdom,1,10,20,1827,10,27,1827,-8,-8,-8,-8,-8,-8,-8,2,Greeks,4,4,-8,80,4.1
506,Greek Independence,5,-8,-8,220,France,1,10,20,1827,10,27,1827,-8,-8,-8,-8,-8,-8,-8,2,Greeks,4,4,-8,40,4.1
506,Greek Independence,5,-8,-8,365,Russia,1,10,20,1827,4,25,1828,-8,-8,-8,-8,-8,-8,-8,2,Greeks,4,4,-8,60,4.1
507,Egypt-Mehdi,6,-8,Egypt,-8,Mehdi army,0,3,20,1824,4,-9,1824,-8,-8,-8,-8,-8,-8,-8,6,Mehdi army,1,-8,-9,-9,4.1
508,Janissari Revolt,4,640,Ottoman Empire,-8,Janissaries,0,6,14,1826,9,30,1826,-8,-8,-8,-8,-8,-8,-8,6,Janissaries,1,-8,300,6000,4.1
510,Miguelite War,4,-8,-8,200,United Kingdom,1,7,1,1831,5,26,1834,-8,-8,-8,-8,-8,-8,-8,2,Constitutionalists,2,-8,-8,100,4.1
510,Miguelite War,4,235,Portugal,-8,Constitutionalists,1,7,11,1828,5,26,1834,-8,-8,-8,-8,-8,-8,-8,2,Constitutionalists,2,-8,12000,8000,4.1
511,First Murid War,5,365,Russia,-8,Ghazi Muhammad,0,-9,-9,1830,10,17,1832,-8,-8,-8,-8,-8,-8,-8,2,Ghazi Muhammad,1,-8,1000,500,4.1
512,First Albanian Revolt,5,640,Ottoman Empire,-8,Albanians,0,2,-9,1830,11,-9,1831,-8,-8,-8,-8,-8,-8,-8,2,Albanians,1,-8,5000,"10,000",4.1
513,First French Insurrection,4,220,France,-8,Liberals,0,7,25,1830,7,29,1830,-8,-8,-8,-8,-8,-8,-8,2,Liberals,2,-8,400,1800,4.1
515,Belgian Independence,5,210,Netherlands,-8,Belgians,0,8,25,1830,11,4,1830,-8,-8,-8,-8,-8,-8,-8,2,Belgians,2,-8,500,600,4.1
516,Egyptian Taka Expedition,6,-8,Egypt,-8,Hadendowa,0,-9,-9,1831,-9,-9,1832,-8,-8,-8,-8,-8,-8,-8,6,Egypt,2,-8,"1,500",-9,4.1
517,First Polish,5,365,Russia,-8,Poles,0,2,7,1831,10,18,1831,-8,-8,-8,-8,-8,-8,-8,2,Poles,1,-8,15000,20000,4.1
518,First Syrian,5,640,Ottoman Empire,-8,Egyptians & Bashir,0,10,1,1831,12,27,1832,-8,-8,-8,-8,-8,-8,-8,6,Egyptians,2,-8,8000,4000,4.1
520,First Mexican,4,70,Mexico,-8,Liberals,0,1,2,1832,12,11,1832,-8,-8,-8,-8,-8,-8,-8,1,Liberals,2,-8,-9,-9,4.1
521,Egypt- Palestinian Anti-Conscription Revolt,6,-8,Palestinians,-8,Egypt,0,4,19,1834,10,-9,1834,-8,-8,-8,-8,-8,-8,-8,6,Palestinians,2,-8,1500,500,4.1
522,First Carlist War,4,235,Portugal,-8,-8,1,10,15,1835,2,15,1836,-8,-8,-8,-8,-8,-8,-8,2,Carlists,1,-8,50,-8,4.1
522,First Carlist War,4,230,Spain,-8,Carlists,1,7,15,1834,7,15,1840,-8,-8,-8,-8,-8,-8,-8,2,Carlists,1,-8,65000,60000,4.1
522,First Carlist War,4,220,France,-8,-8,1,10,31,1835,1,17,1839,-8,-8,-8,-8,-8,-8,-8,2,Carlists,1,-8,7700,-8,4.1
522,First Carlist War,4,200,United Kingdom,-8,-8,1,7,10,1835,9,1,1837,-8,-8,-8,-8,-8,-8,-8,2,Carlists,1,-8,2500,-8,4.1
523,Second Murid,5,365,Russia,-8,Shamil,0,9,26,1834,10,27,1834,-8,-8,-8,-8,-8,-8,-8,2,Shamil,7,-8,-9,-9,4.1
525,Cabanos Revolt,5,140,Brazil,-8,Cabanos,0,1,6,1835,5,-9,1837,-8,-8,-8,-8,-8,-8,-8,1,Cabanos,1,-8,-9,-9,4.1
526,Farroupilha War,5,140,Brazil,-8,Farrapos,0,9,19,1835,3,1,1845,-8,-8,-8,-8,-8,-8,-8,1,Farrapos,1,-8,-9,-9,4.1
527,Texan,5,70,Mexico,-8,Texans,0,10,1,1835,4,22,1836,-8,-8,-8,-8,-8,-8,-8,1,Texans,2,-8,1500,700,4.1
528,First Bosnian,5,640,Ottoman Empire,-8,Bosnians,0,-9,-9,1836,-9,-9,1837,-8,-8,-8,-8,-8,-8,-8,2,Bosnians,1,-8,-9,-9,4.1
530,Third Murid,5,365,Russia,-8,Shamil,0,7,-9,1836,-9,-9,1852,-8,-8,-8,-8,-8,-8,-8,2,Shamil,1,-8,15000,-9,4.1
531,Sabinada Rebellion,5,140,Brazil,-8,Bahian Sabinada,0,11,7,1837,3,13,1838,-8,-8,-8,-8,-8,-8,-8,1,Bahian Sabinada,1,-8,600,1200,4.1
532,Druze Rebellion,6,-8,Egypt & Bashir,-8,Druze,0,9,27,1837,8,22,1838,-8,-8,-8,-8,-8,-8,-8,6,Druze,1,-8,15000,-9,4.1
533,"Second Syrian, Phase 1",5,640,Ottoman Empire,-8,Egypt,0,6,10,1839,6,24,1839,-8,-8,-8,-8,-8,-8,-8,6,Mehmet Ali,2,-8,2000,1000,4.1
535,Lebanon Insurgency,6,-8,Lebanese Maronites,-8,Amir Bashir & Egypt,0,5,27,1840,7,13,1840,-8,-8,-8,-8,-8,-8,-8,6,Amir Bashir & Egypt,2,-8,3500,1000,4.1
536,First Colombian,4,100,Colombia,-8,Progressives,0,7,15,1840,7,15,1842,-8,-8,-8,-8,-8,-8,-8,1,Progressives,2,-8,-9,-9,4.1
537,"Second Syrian, Phase 2",5,200,United Kingdom,-8,-8,1,9,9,1840,11,27,1840,-8,-8,-8,-8,-8,-8,-8,6,United Kingdom,1,-8,14,-8,4.1
537,"Second Syrian, Phase 2",5,640,Ottoman Empire,-8,Egypt,1,9,9,1840,11,27,1840,-8,-8,-8,-8,-8,-8,-8,6,United Kingdom,1,-8,8000,19000,4.1
538,"First Argentina War, Phase 2",4,160,Argentina,-8,Unitarios,0,1,1,1841,12,6,1842,-8,-8,-8,-8,-8,-8,1527,1,Unitarios,1,-8,300,3000,4.1
540,Second Bosnian,5,640,Ottoman Empire,-8,Bosnians,0,-9,-9,1841,-9,-9,1841,-8,-8,-8,-8,-8,-8,-8,2,Bosnians,1,-8,-9,-9,4.1
541,Triangular Revolt,4,70,Mexico,-8,Military,0,9,4,1841,10,6,1841,-8,-8,-8,-8,-8,-8,-8,1,Military,2,-8,-9,-9,4.1
542,Karbala Revolt,5,640,Ottoman Empire,-8,Karbala,0,12,19,1842,1,13,1843,-8,-8,-8,-8,-8,-8,-8,6,Ottomans,1,-8,1600,3000,4.1
543,First Maronite-Druze,7,-8,Maronites,-8,Druze,0,4,30,1845,5,31,1845,-8,-8,-8,-8,-8,-8,-8,6,Maronites,2,-8,2000,1000,4.1
545,"Mayan Caste War, Phase 1",6,-8,Mayans,-8,Yucutan,0,1,15,1847,8,16,1848,-8,-8,-8,-8,-8,-8,-8,1,Mayans,4,553,-9,1800,4.1
546,Second Carlist,4,230,Spain,-8,Carlists,0,5,15,1847,5,1,1849,-8,-8,-8,-8,-8,-8,-8,2,Carlists,1,-8,3000,7000,4.1
547,Second Two Sicilies,4,329,Two Sicilies,-8,Liberals,0,1,12,1848,1,27,1848,5,15,1848,5,15,1849,-8,2,Liberals,1,-8,1500,-9,4.1
548,First Venezuelan,4,101,Venezuela,-8,Paez led Conservatives ,0,2,4,1848,8,15,1849,-8,-8,-8,-8,-8,-8,-8,1,Former Pres. Paez,1,-8,1500,-9,4.1
550,Viennese Revolt,4,300,Austria,-8,Viennese,0,3,13,1848,10,31,1848,-8,-8,-8,-8,-8,-8,-8,2,Viennese,1,-8,249,3000,4.1
551,Milan Five Day Revolt,5,300,Austria,-8,Milan,0,3,18,1848,3,23,1848,-8,-8,-8,-8,-8,-8,-8,2,Milan,4,10,600,430,4.1
552,Second French Insurrection,4,220,France,-8,Radicals,0,6,23,1848,6,26,1848,-8,-8,-8,-8,-8,-8,-8,2,Radicals,1,-8,1200,1600,4.1
553,"Mayan Caste War, Phase 2",5,70,Mexico,-8,Yucatan Maya,0,8,17,1848,3,4,1855,-8,-8,-8,-8,-8,-8,545,1,Mexico,1,-8,-9,-9,4.1
554,Hungarian,5,300,Austria,-8,Hungary,1,9,9,1848,8,13,1849,-8,-8,-8,-8,-8,-8,-8,2,Magyars,1,-8,46000,20000,4.1
554,Hungarian,5,365,Russia,-8,-8,1,7,16,1849,8,13,1849,-8,-8,-8,-8,-8,-8,-8,2,Magyars,1,-8,14500,-8,4.1
555,First Chilean,4,155,Chile,-8,Liberals,0,9,5,1851,12,15,1851,-8,-8,-8,-8,-8,-8,-8,1,Liberals,1,-8,1500,2500,4.1
556,First Turco-Montenegrin,5,640,Ottoman Empire,-8,Montenegro & Hercegovina,0,12,2,1852,3,13,1853,-8,-8,-8,-8,-8,-8,-8,2,Turkey,2,-8,-9,-9,4.1
557,First Peru,4,135,Peru,-8,Liberals,0,12,21,1853,1,7,1855,-8,-8,-8,-8,-8,-8,-8,1,Liberals,2,-8,-9,-9,4.1
558,Puebla War,4,70,Mexico,-8,Puebla,0,12,11,1855,3,21,1856,-8,-8,-8,-8,-8,-8,-8,1,Military,1,-8,600,3000,4.1
560,Second Peru,4,135,Peru,-8,Conservatives,0,10,31,1856,3,7,1858,-8,-8,-8,-8,-8,-8,-8,1,Conservatives,1,-8,-9,-9,4.1
561,Mexican Reform,4,70,Mexico,-8,Liberals,0,2,15,1858,1,1,1861,-8,-8,-8,-8,-8,-8,-8,1,Liberals,4,-8,-9,-9,4.1
562,Second Turco-Montenegrin,5,640,Ottoman Empire,-8,Montenegrins,0,5,4,1858,6,1,1859,-8,-8,-8,-8,-8,-8,-8,2,Montenegrins,2,-8,3000,1400,4.1
563,Second Venezuelan/Federalist,4,101,Venezuela,-8,Liberals,0,2,1,1859,5,23,1863,-8,-8,-8,-8,-8,-8,-8,1,Liberals,2,-8,15000,5000,4.1
565,Second Colombian,4,100,Colombia,-8,Liberals,0,5,15,1860,7,18,1861,-8,-8,-8,-8,-8,-8,-8,1,Liberals,2,-8,-9,-9,4.1
566,Second Maronite-Druze,7,-8,Maronites,-8,Druze,0,5,26,1860,7,12,1860,-8,-8,-8,-8,-8,-8,-8,6,Maronites,2,-8,8000,1500,4.1
567,"Taiping Rebellion, Phase 2",4,710,China,-8,Taipings,1,10,25,1860,2,9,1866,-8,-8,-8,-8,-8,-8,1534,7,Taipings,1,-8,26000,85000,4.1
567,"Taiping Rebellion, Phase 2",4,200,United Kingdom,-8,-8,1,3,1,1862,8,1,1862,-8,-8,-8,-8,-8,-8,1534,7,Taipings,1,-8,25,-8,4.1
568,Second Nien Revolt,5,710,China,-8,Niens,0,10,25,1860,8,16,1868,-8,-8,-8,-8,-8,-8,,7,Niens,1,-8,-9,-9,4.1
570,Miao Revolt Phase 2,5,710,China,-8,Miaos,0,10,25,1860,5,1,1872,-8,-8,-8,-8,-8,-8,1537,7,Miaos,1,-8,-9,-9,4.1
571,Panthay Rebellion Phase 2,5,710,China,-8,Muslims (Hui),0,10,25,1860,12,26,1872,-8,-8,-8,-8,-8,-8,1542,7,Muslims,1,-8,-9,-9,4.1
572,U.S. Civil War,5,2,United States of America,-8,Confederacy,0,4,10,1861,4,9,1865,-8,-8,-8,-8,-8,-8,-8,1,Confederacy,1,-8,360000,258000,4.1
573,Third Buenos Aires,5,160,Argentina,-8,Buenos Aires,0,8,20,1861,12,2,1861,-8,-8,-8,-8,-8,-8,-8,1,Buenos Aires,2,-8,500,500,4.1
575,Third Turco-Montenegrin,5,640,Turkey,-8,Montenegro,0,12,-9,1861,8,31,1862,-8,-8,-8,-8,-8,-8,-8,2,Ottoman Empire,3,-8,-9,-9,4.1
576,Tungan Rebellion,5,710,China,-8,Muslims  in Sinkiang,0,5,-9,1862,10,24,1873,-8,-8,-8,-8,-8,-8,-8,7,Muslims  in Sinkiang,1,-8,-9,-9,4.1
577,Sioux-Minnesota,6,-8,Santee Sioux,-8,Settlers & militia,0,8,17,1862,9,26,1862,-8,-8,-8,-8,-8,-8,-8,1,Santee Sioux,2,-8,217,851,4.1
578,Bolivan Perez Rebellion,4,145,Boliva,-8,Gregorio Perez's followers,0,9,15,1862,9,15,1862,-8,-8,-8,-8,-8,-8,-8,1,Gregorio Perez,1,-8,-9,-9,4.1
580,Second Polish,5,365,Russia,-8,Poles,0,1,22,1863,4,19,1864,-8,-8,-8,-8,-8,-8,-8,2,Poles,1,-8,10000,6500,4.1
581,Second Argentina,4,160,Argentina,-8,Montoneros,0,4,2,1863,11,12,1863,-8,-8,-8,-8,-8,-8,-8,1,Montoneros,1,-8,-9,-9,4.1
582,Xinjiang Muslim Revolt,5,365,Russia,-8,-8,1,6,24,1871,7,3,1871,-8,-8,-8,-8,-8,-8,-8,7,Muslims,2,-8,-9,-8,4.1
582,Xinjiang Muslim Revolt,5,710,China,-8,Muslims,1,7,-9,1864,7,3,1871,-8,-8,-8,-8,-8,-8,-8,7,Muslims,2,-8,-9,-9,4.1
583,First  Cretan,5,640,Ottoman Empire,-8,Cretans,0,5,29,1866,2,22,1867,-8,-8,-8,-8,-8,-8,-8,2,Cretans,1,-8,-9,-9,4.1
585,Yellow Cliff Revolt,5,710,China,-8,Zhang Jizhong's followers,0,10,-9,1866,10,-91866,,-8,-8,-8,-8,-8,-8,-8,7,Zhang Jizhong,1,-8,-9,-9,4.1
586,Third Argentina,4,160,Argentina,-8,Montoneros,0,12,15,1866,10,15,1867,-8,-8,-8,-8,-8,-8,-8,1,Federalists,1,-8,-9,-9,4.1
587,Queretaro,4,70,Mexico,-8,Liberals,0,2,6,1867,5,14,1867,-8,-8,-8,-8,-8,-8,40,1,Liberals,2,-8,1500,1000,4.1
588,Meiji Restoration,4,740,Japan,-8,Tokugawa,0,1,3,1868,7,4,1868,-8,-8,-8,-8,-8,-8,-8,7,Japan,1,-8,-9,-9,4.1
590,Third Venezuelan,4,101,Venezuela,-8,Conservatives,0,1,11,1868,8,14,1868,8,14,1869,1,7,1871,-8,1,Conservatives,2,-8,-9,-9,4.1
591,Spanish Liberals,4,230,Spain,-8,Liberals,0,9,18,1868,9,29,1868,-8,-8,-8,-8,-8,-8,-8,2,Liberals,2,-8,-9,-9,4.1
592,Guerre des Cacos,4,41,Haiti,-8,Black peasants,0,2,-9,1869,12,18,1869,-8,-8,-8,-8,-8,-8,-8,1,Black peasants,2,-8,-9,-9,4.1
593,Fourth Argentina,5,160,Argentina,-8,Entre Rios Province,0,5,20,1870,3,13,1871,-8,-8,-8,-8,-8,-8,-8,1,Entre Rios Province,1,-8,-9,-9,4.1
595,Bolivia-Criollos,4,145,Bolivia,-8,Crillos,0,11,24,1870,1,15,1871,-8,-8,-8,-8,-8,-8,-8,1,Crillos,2,-8,-9,-9,4.1
596,Paris Commune,4,220,France,-8,Communards,0,4,2,1871,5,29,1871,-8,-8,-8,-8,-8,-8,-8,2,Communards,1,-8,879,25000,4.1
597,Third Carlist,4,230,Spain,-8,Carlists,0,4,20,1872,2,20,1876,-8,-8,-8,-8,-8,-8,-8,2,Carlists,1,-8,7000,43000,4.1
598,Catonalist Uprising,5,230,Spain,-8,Rebel cities (cantons),0,-9,-9,1874,1,-9,1875,-8,-8,-8,-8,-8,-8,-8,2,Rebel cities (cantons),1,-8,-9,-9,4.1
600,Fifth Argentina,4,160,Argentina,-8,Mitre led Rebels,0,9,-9,1874,11,6,1874,-8,-8,-8,-8,-8,-8,-8,1,Mitre led Rebels,1,-8,-9,-9,4.1
601,Bosnia & Bulgaria Revolt,5,640,Ottoman Empire,-8,Bosnia & Bulgaria,0,6,30,1875,6,29,1876,-8,-8,-8,-8,-8,-8,-8,2,Bosnia & Bulgaria,4,373,6000,3000,4.1
602,Diaz Revolt,4,70,Mexico,-8,Rebels,0,3,-9,1876,11,23,1876,-8,-8,-8,-8,-8,-8,-8,1,Rebels,2,-8,1900,-9,4.1
603,Defeat of Xinjiang Muslims,5,710,China,-8,Muslims,0,4,-9,1876,12,1,1877,-8,-8,-8,-8,-8,-8,-8,7,China,1,-8,-9,-9,4.1
605,Third Colombian,4,100,Colombia,-8,Conservatives,0,7,26,1876,7,1,1877,-8,-8,-8,-8,-8,-8,-8,1,Conservatives,1,-8,2100,1770,4.1
607,Satsuma Rebellion,5,740,Japan,-8,Satsumas,0,1,29,1877,9,24,1877,-8,-8,-8,-8,-8,-8,-8,7,Satsumas,1,-8,7000,10000,4.1
608,Argentine Indians,5,160,Argentina,-8,Indians,0,4,6,1879,7,8,1880,-8,-8,-8,-8,-8,-8,-8,1,Argentina,1,-8,200,1500,4.1
610,Fourth Buenos Aires,5,160,Argentina,-8,Buenos Aires,0,6,21,1880,7,21,1880,-8,-8,-8,-8,-8,-8,-8,1,Buenos Aires,1,-8,400,800,4.1
611,Haitian Civil War,4,41,Haiti,-8,Liberals,0,3,27,1883,1,8,1884,-8,-8,-8,-8,-8,-8,-8,1,Liberals,1,-8,8000,100,4.1
612,Fourth Colombian,4,100,Colombia,-8,Liberals,0,11,15,1884,8,26,1885,-8,-8,-8,-8,-8,-8,-8,1,Liberals,1,-8,300,700,4.1
613,Peru's National Problem,5,135,Peru,-8,Indians,0,3,2,1885,5,25,1885,-8,-8,-8,-8,-8,-8,-8,1,Indians,1,-8,200,2000,4.1
616,First Yemen Rebellion,5,640,Ottoman Empire,-8,Zaidi Imam,0,4,-9,1890,9,-9,1892,-8,-8,-8,-8,-8,-8,-8,6,Zaidi Imam,1,-8,-9,-9,4.1
617,Second Chilean,4,155,Chile,-8,Congressists,0,1,7,1891,8,29,1891,-8,-8,-8,-8,-8,-8,-8,1,Congressists,2,-8,1000,700,4.1
618,Zaili-Jinden Revolt,5,710,China,-8,Zaili & Jindan Sects,0,11,11,1891,12,27,1891,-8,-8,-8,-8,-8,-8,-8,7,Zaili & Jindan Sects,1,-8,500,10000,4.1
620,Brazil Federalists,5,140,Brazil,-8,Rio Grande do Sul,0,2,2,1893,8,31,1894,-8,-8,-8,-8,-8,-8,-8,1,Rio Grande do Sul,1,-8,1500,-9,4.1
621,Brazil Naval,4,140,Brazil,-8,Naval Royalists,0,9,6,1893,4,16,1894,-8,-8,-8,-8,-8,-8,-8,1,Naval Royalists,1,-8,1000,-9,4.1
623,Tonghak Rebellion,4,740,Japan,-8,-8,1,10,24,1894,11,28,1894,-8,-8,-8,-8,-8,-8,-8,7,Tonghak Society,1,-8,-9,-8,4.1
623,Tonghak Rebellion,4,730,Korea,-8,Tonghak Society,1,2,29,1894,5,6,1894,9,14,1894,11,28,1894,-8,7,Tonghak Society,1,-8,-9,-9,4.1
625,Third Peru,4,135,Peru,-8,Liberals,0,10,15,1894,3,19,1895,-8,-8,-8,-8,-8,-8,-8,1,Liberals,2,-8,-9,-9,4.1
626,Fifth Colombian,4,100,Colombia,-8,Liberals,0,1,22,1895,3,15,1895,-8,-8,-8,-8,-8,-8,-8,1,Liberals,1,-8,400,800,4.1
627,Ecuador Liberals,4,130,Ecuador,-8,liberal caudillos,0,2,18,1895,9,22,1895,-8,-8,-8,-8,-8,-8,-8,1,liberal caudillos,2,-8,900,100,4.1
628,First Gansu Muslim,5,710,China,-8,Gansu Muslims,0,4,-9,1895,4,-9,1896,-8,-8,-8,-8,-8,-8,-8,7,Gansu Muslims,1,-8,-9,-9,4.1
630,Druze-Turkish,5,640,Ottoman Empire,-8,Druze,0,10,-9,1895,-9,-9,1896,-8,-8,-8,-8,-8,-8,-8,6,Druze,1,-8,-9,-9,4.1
631,Second Cretan,5,640,Ottoman Empire,-8,Cretan Muslims,0,3,10,1896,2,14,1897,-8,-8,-8,-8,-8,-8,-8,2,Cretan Muslims,4,76,-9,-9,4.1
632,Third Brazil-Canudos,5,140,Brazil,-8,Canudos,0,10,1,1896,10,5,1897,-8,-8,-8,-8,-8,-8,-8,1,Brazil,1,-8,2200,3000,4.1
633,Fourth Venezuelan,4,101,Venezuela,-8,Castro Led Rebels,0,5,24,1899,10,22,1899,-8,-8,-8,-8,-8,-8,-8,1,Castro Led Rebels,2,-8,1200,900,4.1
635,Second Yaqui War,5,70,Mexico,-8,Yaqui Indians,0,7,21,1899,1,18,1900,-8,-8,-8,-8,-8,-8,-8,1,Yaqui Indians,1,-8,100,1500,4.1
636,Sixth Colombian (War of the 1000 Days),4,100,Colombia,-8,Liberals,0,10,17,1899,11,21,1902,-8,-8,-8,-8,-8,-8,-8,1,Liberals,1,-8,47000,53000,4.1
638,Fifth Venezuelan,4,101,Venezuela,-8,Matos Led Rebels,0,12,19,1901,7,19,1903,-8,-8,-8,-8,-8,-8,-8,1,Matos Led Rebels,1,-8,1000,3000,4.1
640,Ilinden,5,640,Ottoman Empire,-8,IMRO Rebels,0,8,2,1903,11,2,1903,-8,-8,-8,-8,-8,-8,-8,2,IMRO Rebels,1,-8,5330,1000,4.1
641,First Uruguay,4,165,Uruguay,-8,Blancos,0,1,1,1904,9,1,1904,-8,-8,-8,-8,-8,-8,-8,1,Blancos,1,-8,-9,-9,4.1
642,Second Yemen Rebellion,5,640,Ottoman Empire,-8,Imam Yahya's forces,0,11,8,1904,1,10,1906,-8,-8,-8,-8,-8,-8,-8,6,Yemen,6,-8,30000,-9,4.1
643,Bloody Sunday,4,365,Russia,-8,Workers/Peasants,0,1,22,1905,1,1,1906,-8,-8,-8,-8,-8,-8,-8,2,Workers/Peasants,1,-8,1500,-9,4.1
645,Romanian Peasant Revolt,4,360,Romania,-8,Peasants,0,3,15,1907,4,30,1907,-8,-8,-8,-8,-8,-8,-8,2,Peasants,1,-8,2000,-9,4.1
646,Overthrow of Abd el-Aziz,4,220,France,-8,-8,1,8,7,1907,6,15,1908,-8,-8,-8,-8,-8,-8,-8,6,Mulai el-Hafid,2,-8,200,-8,4.1
646,Overthrow of Abd el-Aziz,4,600,Morocco,-8,Mulai el-Hafid,1,8,1,1907,9,1,1908,-8,-8,-8,-8,-8,-8,-8,6,Mulai el-Hafid,2,-8,400,800,4.1
647,Iranian Constitution War,4,365,Russia,-8,-8,1,4,30,1909,7,17,1909,-8,-8,-8,-8,-8,-8,-8,6,Constitutionalists,2,-8,100,-8,4.1
647,Iranian Constitution War,4,630,Iran,-8,Constitutionalists,1,6,23,1908,7,17,1909,-8,-8,-8,-8,-8,-8,-8,6,Constitutionalists,2,-8,-9,-9,4.1
648,Young Turks Counter-coup,4,640,Ottoman Empire,-8,Anti-government troops,0,4,14,1909,4,28,1909,-8,-8,-8,-8,-8,-8,-8,6,Anti-government troops,1,-8,-9,-9,4.1
650,Second Albanian Revolt,5,640,Ottoman Empire,-8,Albania,0,3,-9,1910,10,16,1912,-8,-8,-8,-8,-8,-8,-8,2,Albania,4,100,-9,-9,4.1
651,Asir-Yemen Revolt,5,640,Ottoman Empire,-8,Yemen & Asir Imam Ibn Idris & Sayyid Muhammad,0,10,15,1910,10,9,1911,-8,-8,-8,-8,-8,-8,-8,6,Yemen & Asir,6,-8,7000,2000,4.1
652,Third Mexican,4,70,Mexico,-8,Liberals & Radicals,0,11,20,1910,7,15,1914,-8,-8,-8,-8,-8,-8,-8,1,Liberals & Radicals,2,-8,56250,37500,4.1
656,Paraguay,4,150,Paraguay,-8,Radicals,0,7,15,1911,5,11,1912,-8,-8,-8,-8,-8,-8,-8,1,Radicals,2,-8,4000,1000,4.1
657,First Nationalist,4,710,China,-8,Nat. Rel. Alliance,0,10,11,1911,12,31,1911,-8,-8,-8,-8,-8,-8,-8,7,Republicans,2,-8,800,200,4.1
658,Cuban Black Uprising,5,40,Cuba,-8,Patri do Indepentente,0,5,20,1912,6,27,1912,-8,-8,-8,-8,-8,-8,-8,1,Patri do Indepentente,1,-8,50,1000,4.1
670,Ecuadorian Civil War,5,130,Ecuador,-8,Esmeraldas province,0,-9,-9,1912,-9,-9,1914,-8,-8,-8,-8,-8,-8,-8,1,Esmeraldas province,1,-8,-9,-9,4.1
671,Second Nationalist,4,710,China,-8,Republicans,0,7,12,1913,9,1,1913,-8,-8,-8,-8,-8,-8,-8,7,Republicans,1,-8,-9,-9,4.1
672,China Pai Ling (White Wolf),5,710,China,-8,Pai-Lings,0,3,15,1914,9,15,1914,-8,-8,-8,-8,-8,-8,-8,7,Pai-Lings,1,-8,-9,-9,4.1
673,Fourth Mexican,4,2,United States,-8,-8,1,3,15,1915,2,5,1917,-8,-8,-8,-8,-8,-8,-8,1,Conventionists,1,-8,15,-8,4.1
673,Fourth Mexican,4,70,Mexico,-8,Conventionists,1,11,19,1914,7,28,1920,-8,-8,-8,-8,-8,-8,-8,1,Conventionists,1,-8,18750,12500,4.1
675,Southern China Revolt,5,710,China,-8,Yunnan Rebels,0,1,-9,1916,11,17,1918,-8,-8,-8,-8,-8,-8,-8,7,Yunnan Rebels,1,-8,-9,-9,4.1
676,Russia-Turkestan,5,365,Russia,-8,Kirghiz & Kazaks,0,7,4,1916,2,27,1917,-8,-8,-8,-8,-8,-8,-8,2,Kirghiz & Kazables,1,-8,350,1000,4.1
677,Russian Civil War,4,-8,-8,375,Finland,1,4,15,1919,4,30,1919,-8,-8,-8,-8,-8,-8,-8,2,,1,-8,-8,50,4.1
677,Russian Civil War,4,-8,-8,740,Japan,1,8,3,1918,10,15,1920,-8,-8,-8,-8,-8,-8,-8,2,,1,-8,-8,1500,4.1
677,Russian Civil War,4,365,USSR,-8,Anti-Bolsheviks,1,12,9,1917,3,18,1921,-8,-8,-8,-8,-8,-8,-8,2,Anti-Bolsheviks,1,-8,475000,325000,4.1
677,Russian Civil War,4,-8,-8,200,United Kingdom,1,6,23,1918,3,15,1920,-8,-8,-8,-8,-8,-8,-8,2,,1,-8,-8,350,4.1
677,Russian Civil War,4,-8,-8,2,United States of America,1,7,1,1918,4,20,1920,-8,-8,-8,-8,-8,-8,-8,2,,1,-8,-8,275,4.1
677,Russian Civil War,4,-8,-8,220,France,1,6,23,1918,9,30,1919,-8,-8,-8,-8,-8,-8,-8,2,,1,-8,-8,50,4.1
680,Finnish Civil War,4,255,Germany,-8,-8,1,4,3,1918,5,16,1918,-8,-8,-8,-8,-8,-8,-8,2,,1,-8,950,-8,4.1
680,Finnish Civil War,4,-8,-8,365,USSR,1,1,28,1918,5,16,1918,-8,-8,-8,-8,-8,-8,-8,2,,1,-8,-8,400,4.1
680,Finnish Civil War,4,375,Finland,-8,Red Guard,1,1,28,1918,4,30,1918,-8,-8,-8,-8,-8,-8,-8,2,Communists,1,-8,5300,8500,4.1
681,Western Ukrainian,6,-8,Ukraine Poles,-8,Ukrainians,0,11,1,1918,2,13,1919,-8,-8,-8,-8,-8,-8,-8,2,Poles,4,109,-9,-9,4.1
682,Sparticist Rising,7,-8,Socialists,-8,German Freikorps,0,1,6,1919,5,1919,,-8,-8,-8,-8,-8,-8,-8,2,Socialists,2,-8,"2,100",70,4.1
683,Hungary's Red Terror,4,310,Hungary,-8,Anti-Communists,0,3,25,1919,2,15,1920,-8,-8,-8,-8,-8,-8,-8,2,Anti-Communists,2,-8,1000,500,4.1
685,First Chinese Warlord,7,-8,Anhui army,-8,Chihli & Fengtien,0,7,14,1920,7,19,1920,-8,-8,-8,-8,-8,-8,-8,7,Chihli army,2,-8,-9,-9,4.1
686,Green Rebellion,5,365,USSR,-8,Peasants in Ta,0,8,-9,1920,8,-9,1921,-8,-8,-8,-8,-8,-8,-8,2,Peasants in Ta,1,-8,1700,5000,4.1
687,Gilan Marxists,4,-8,-8,365,USSR,1,8,10,1920,11,11,1921,-8,-8,-8,-8,-8,-8,-8,6,SSRI,1,-8,-8,-9,4.1
687,Gilan Marxists,4,630,Iran,-8,SSRI,1,8,10,1920,11,11,1921,-8,-8,-8,-8,-8,-8,-8,6,SSRI,1,-8,-9,-9,4.1
688,Italian Fascist,7,-8,Blackshirts,-8,Leftists,0,10,-9,1920,10,1,1922,-8,-8,-8,-8,-8,-8,-8,2,Blackshirts,1,-8,300,"3,000",4.1
690,Kronstadt Rebellion,5,365,USSR,-8,Sailors,0,3,7,1921,3,18,1921,-8,-8,-8,-8,-8,-8,-8,2,Sailors,1,-8,2000,600,4.1
691,Bashmachi in Turkestan,5,365,USSR,-8,Basmachi/Enver Pasha,0,11,10,1921,7,-9,1923,-8,-8,-8,-8,-8,-8,-8,2,Muslims/Enver Pasha,1,-8,1000,2500,4.1
692,Second Chinese Warlord,7,-8,Chihli army,-8,Fengtien army,0,4,8,1922,5,5,1922,-8,-8,-8,-8,-8,-8,-8,7,Fengtien army,1,-8,-9,-9,4.1
693,Agrarian Rising,4,355,Bulgaria,-8,Agrarian League,0,9,23,1923,9,28,1923,-8,-8,-8,-8,-8,-8,-8,2,Agrarian League,1,-8,-9,-9,4.1
695,De La Huerta Rebellion,4,70,Mexico,-8,Huerta Led Rebels,0,12,4,1923,2,-9,1924,-8,-8,-8,-8,-8,-8,-8,1,Huerta Led Rebels,1,-8,-9,-9,4.1
696,Honduran Conservative,4,91,Honduras,-8,Conservatives,0,2,9,1924,3,31,1924,-8,-8,-8,-8,-8,-8,-8,1,Conservatives,2,-8,-9,-9,4.1
697,First Afghan Anti-Reform,4,700,Afghanistan,-8,Khost rebels (anti-reformists),0,3,15,1924,1,15,1925,-8,-8,-8,-8,-8,-8,-8,7,Khost rebels (anti-reformists),1,-8,-9,-9,4.1
698,Third Chinese Warlord,6,-8,Feng Yu-Lxiang army,-8,Chang Tso-lin army,0,10,15,1925,4,20,1926,-8,-8,-8,-8,-8,-8,-8,7,Chang Tso-lin army,2,-8,-9,-9,4.1
700,Chinese Northern Expedition,4,710,War Lord Gov't.,-8,Guomindang,1,7,1,1926,6,30,1928,-8,-8,-8,-8,-8,-8,-8,7,Guomindang,2,-8,78000,48000,4.1
700,Chinese Northern Expedition,4,-8,-8,740,Japan,1,6,1,1927,6,1,1928,-8,-8,-8,-8,-8,-8,-8,7,Guomindang,2,-8,-8,500,4.1
701,Cristeros Revolt,4,70,Mexico,-8,Cristeros,0,8,31,1926,6,21,1929,-8,-8,-8,-8,-8,-8,-8,1,Cristeros,3,-8,6000,4000,4.1
702,Ethiopian Northern Resistance,5,530,Ethiopia,-8,Northern Resistance,0,8,-9,1928,4,-9,1930,-8,-8,-8,-8,-8,-8,-8,6,Northern Resistance,1,-8,-9,-9,4.1
703,Second Gansu Muslim,5,710,China,-8,Gansu Muslims,0,-9,-9,1928,-9,-9,1930,-8,-8,-8,-8,-8,-8,-8,7,Muslims,1,-8,-9,-9,4.1
705,Second Afghan Anti-Reform,4,700,Afghanistan,-8,Habibullah (anti-reformists),0,11,10,1928,10,15,1929,-8,-8,-8,-8,-8,-8,-8,7,Habibullah (anti-reformists),1,-8,7500,7500,4.1
706,Intra-Guomindang,4,710,China,-8,War Lords,0,3,1,1929,11,4,1930,-8,-8,-8,-8,-8,-8,-8,7,War Lords,1,-8,-9,-9,4.1
707,Escobar Rebellion,4,70,Mexico,-8,Escobar Led Rebels,0,3,3,1929,5,4,1929,-8,-8,-8,-8,-8,-8,-8,1,Escoban Led Rebels,1,-8,400,1600,4.1
708,Ikhwan Revolt,4,670,Saudi Arabia,-8,Ikhwan,0,3,30,1929,1,10,1930,-8,-8,-8,-8,-8,-8,-8,6,Ikhwan,1,-8,500,5000,4.1
710,"Chinese Civil War, Phase 1",4,710,China,-8,Communists,0,11,15,1930,12,31,1936,-8,-8,-8,-8,-8,-8,-8,7,Communists,6,-8,200000,300000,4.1
711,Xinjiang Muslim Revolt,5,365,USSR,-8,-8,1,1,-9,1934,8,-9,1934,-8,-8,-8,-8,-8,-8,-8,7,Central 7n Rebels,1,-8,1000,-8,4.1
711,Xinjiang Muslim Revolt,5,710,China,-8,Central Asian Rebels,1,2,-9,1931,7,7,1934,-8,-8,-8,-8,-8,-8,-8,7,Central Asian Rebels,1,-8,10000,10000,4.1
712,Matanza,4,92,El Salvador,-8,Leftists,0,1,20,1932,1,29,1932,-8,-8,-8,-8,-8,-8,-8,1,Leftists,1,-8,100,2500,4.1
713,Aprista Revolt,4,135,Peru,-8,Aprista Rebels,0,5,7,1932,7,17,1932,-8,-8,-8,-8,-8,-8,-8,1,Aprista Rebels,1,-8,100,1000,4.1
715,Paulista Rebellion,4,140,Brazil,-8,Paolistas,0,6,9,1932,8,31,1932,-8,-8,-8,-8,-8,-8,-8,1,Paolistas,1,-8,-9,-9,4.1
716,Fukien Revolt,4,710,China,-8,19th Route Army,0,1,5,1934,1,15,1934,-8,-8,-8,-8,-8,-8,-8,7,19th Route Army,1,-8,-9,-9,4.1
717,Spanish Miners,5,230,Spain,-8,Asturian Miners,0,10,4,1934,10,8,1934,-8,-8,-8,-8,-8,-8,-8,2,Asturian Miners,1,-8,284,1051,4.1
718,Spanish Civil War,4,230,Spain,-8,Falange,1,7,18,1936,3,29,1939,-8,-8,-8,-8,-8,-8,-8,2,Fascists,2,-8,286000,174000,4.1
718,Spanish Civil War,4,-8,-8,235,Portugal,1,8,1,1936,3,29,1939,-8,-8,-8,-8,-8,-8,-8,2,Fascists,2,-8,-8,2000,4.1
718,Spanish Civil War,4,-8,-8,255,Germany,1,8,27,1936,3,29,1939,-8,-8,-8,-8,-8,-8,-8,2,Fascists,2,-8,-8,300,4.1
718,Spanish Civil War,4,-8,-8,325,Italy,1,7,30,1936,3,29,1939,-8,-8,-8,-8,-8,-8,-8,2,Fascists,2,-8,-8,4000,4.1
720,Greek Civil War,4,200,United Kingdom,-8,-8,1,12,5,1944,1,11,1945,-8,-8,-8,-8,-8,-8,-8,2,Communists,1,-8,237,-8,4.1
720,Greek Civil War,4,350,Greece,-8,Communists,1,12,3,1944,2,12,1945,2,12,1946,10,16,1949,-8,2,Communists,1,-8,17970,50000,4.1
721,Polish Ukrainians,5,290,Poland,-8,UPA,1,5,8,1945,11,18,1947,-8,-8,-8,-8,-8,-8,-8,2,UPA,1,-8,11000,8700,4.1
721,Polish Ukrainians,5,365,USSR,-8,-8,1,5,8,1945,11,18,1947,-8,-8,-8,-8,-8,-8,-8,2,UPA,1,-8,5000,-8,4.1
722,Ukrainian Partisans,5,365,USSR,-8,UPA,0,5,8,1945,12,31,1947,-8,-8,-8,-8,-8,-8,-8,2,UPA,1,-8,35000,-9,4.1
723,Forest Brethren,5,365,USSR,-8,Baltic Guerillas,0,5,8,1945,12,31,1951,-8,-8,-8,-8,-8,-8,-8,2,Baltic Guerillas,1,-8,14700,17700,4.1
725,"Chinese Civil War, Phase 2",4,710,China,-8,Communists,0,3,15,1946,4,21,1950,-8,-8,-8,-8,-8,-8,-8,7,Communists,2,-8,327600,872400,4.1
726,Taiwan Revolt,5,710,China,-8,Taiwanese,0,2,28,1947,3,21,1947,-8,-8,-8,-8,-8,-8,-8,7,Taiwanese,1,-8,250,1000,4.1
727,Paraguay,4,150,Paraguay,-8,Leftists,0,3,7,1947,8,20,1947,-8,-8,-8,-8,-8,-8,-8,1,Leftists,1,-8,-9,-9,4.1
728,Yemeni Imamate,4,678,Yemen,-8,Anti-Imam Coalition,0,2,17,1948,3,20,1948,-8,-8,-8,-8,-8,-8,-8,6,Anti-Imam Coalition,1,-8,-9,-9,4.1
730,Costa Rica,4,94,Costa Rica,-8,National Union Party,0,3,12,1948,4,17,1948,-8,-8,-8,-8,-8,-8,-8,1,National Union Party,2,-8,1500,500,4.1
731,"Seventh Colombian ""La Violencia""",4,100,Colombia,-8,Liberals,0,4,9,1948,8,7,1958,-8,-8,-8,-8,-8,-8,-8,1,Liberals,1,-8,9800,20000,4.1
732,First Burmese,5,775,Burma,-8,Karens & Communists,0,8,15,1948,7,31,1951,-8,-8,-8,-8,-8,-8,-8,7,Karens & Communists,1,-8,-9,-9,4.1
733,South Moluccas,5,850,Indonesia,-8,Moluccans,0,5,31,1950,11,3,1950,-8,-8,-8,-8,-8,-8,-8,7,Moluccans,1,-8,-9,-9,4.1
735,Hukbalahap Rebellion,4,840,Philippines,-8,Huks,0,9,1,1950,5,-9,1954,-8,-8,-8,-8,-8,-8,-8,7,Huks,1,-8,1600,9700,4.1
737,Bolivia,4,145,Bolivia,-8,Leftists,0,4,8,1952,4,11,1952,-8,-8,-8,-8,-8,-8,-8,1,Leftists,2,-8,-9,-9,4.1
738,Indonesia Darul Islam,4,850,Indonesia,-8,Darul Islam,0,9,20,1953,11,23,1953,-8,-8,-8,-8,-8,-8,-8,7,Darul Islam,1,-8,1700,1000,4.1
740,Argentine Military,4,160,Argentina,-8,Military,0,6,15,1955,9,19,1955,-8,-8,-8,-8,-8,-8,-8,1,Army,2,-8,-9,-9,4.1
741,Tibetan Khamba Rebellion,5,710,China,-8,Khamba Tibetans,0,3,1,1956,4,14,1959,-8,-8,-8,-8,-8,-8,-8,7,Khamba Tibetans,1,-8,4000,12000,4.1
742,Indonesian Leftists,4,850,Indonesia,-8,Leftists,0,12,15,1956,6,4,1962,-8,-8,-8,-8,-8,-8,-8,7,Leftists,1,-8,3700,23500,4.1
743,First Lebanese,4,2,United States of America,-8,-8,1,7,16,1958,9,15,1958,-8,-8,-8,-8,-8,-8,-8,6,Leftists,1,-8,1,-8,4.1
743,First Lebanese,4,660,Lebanon,-8,National Front,1,5,9,1958,9,15,1958,-8,-8,-8,-8,-8,-8,-8,6,Leftists,1,-8,-9,-9,4.1
745,Cuban Revolution,4,40,Cuba,-8,Castroites,0,5,24,1958,1,2,1959,-8,-8,-8,-8,-8,-8,-8,1,Castroites,2,-8,2000,1000,4.1
746,Second Burmese,4,775,Burma,-8,Karens & Communists,0,11,-9,1958,4,-9,1960,-8,-8,-8,-8,-8,-8,-8,7,Karens & Communists,7,-8,850,2300,4.1
747,Iraq-Shammar,4,645,Iraq,-8,Shammar Tribe & Pro-WesternOfficers,0,3,6,1959,3,10,1959,-8,-8,-8,-8,-8,-8,-8,6,Shammar Tribe & Pro-WesternOfficers,1,-8,-9,-9,4.1
748,Vietnam Phase 1,4,2,United States of America,-8,-8,1,1,1,1961,2,6,1965,-8,-8,-8,-8,-8,-8,-8,7,NLF,4,163,506,-8,4.1
748,Vietnam Phase 1,4,817,"Vietnam, Republic of",-8,NLF,1,1,1,1960,2,6,1965,-8,-8,-8,-8,-8,-8,-8,7,NLF,4,163,23300,76900,4.1
750,First DRC (Zaire),5,-8,-8,211,Belgium,1,7,11,1960,9,14,1960,-8,-8,-8,-8,-8,-8,-8,4,Katanga & Leftists,1,-8,-8,50,4.1
750,First DRC (Zaire),5,490,Zaire,-8,Katanga & Leftists,1,7,4,1960,1,14,1963,-8,-8,-8,-8,-8,-8,-8,4,Katanga & Leftists,1,-8,-9,-9,4.1
751,First Laotian,4,-8,-8,816,"Vietnam, Democratic Rep.",1,5,1,1961,6,15,1962,-8,-8,-8,-8,-8,-8,-8,7,Pathet Lao,3,-8,-8,-9,4.1
751,First Laotian,4,812,Laos,-8,Pathet Lao,1,10,15,1960,7,15,1962,-8,-8,-8,-8,-8,-8,-8,7,Pathet Lao,3,-8,4000,1000,4.1
752,First Iraqi Kurd,5,645,Iraq,-8,Kurds,0,9,11,1961,11,22,1963,-8,-8,-8,-8,-8,-8,-8,6,Kurds,6,-8,500,2000,4.1
753,Algerian Revolutionaries,4,615,Algeria,-8,ALN,0,7,28,1962,1,15,1963,-8,-8,-8,-8,-8,-8,-8,6,ALN,2,-8,800,700,4.1
755,North Yemen,4,651,Egypt/United Arab Republic,-8,-8,1,12,15,1962,10,16,1967,-8,-8,-8,-8,-8,-8,-8,6,Royalists,1,-8,10000,-8,4.1
755,North Yemen,4,678,Yemen Arab Republic,-8,Royalists,1,11,15,1962,9,3,1969,-8,-8,-8,-8,-8,-8,-8,6,Royalists,1,-8,-9,-9,4.1
756,Second Laotian Phase 1,4,2,United States of America,-8,-8,1,5,19,1964,1,12,1968,-8,-8,-8,-8,-8,-8,-8,7,Pathet Lao,4,170,200,-8,4.1
756,Second Laotian Phase 1,4,812,Laos,-8,Pathet Lao,1,3,19,1963,1,12,1968,-8,-8,-8,-8,-8,-8,-8,7,Pathet Lao,4,170,11250,7250,4.1
756,Second Laotian Phase 1,4,-8,-8,816,"Vietnam, Democratic Rep.",1,3,19,1963,1,12,1968,-8,-8,-8,-8,-8,-8,-8,7,Pathet Lao,4,170,-8,2250,4.1
757,First Ogaden,5,-8,-8,520,Somalia,1,11,-9,1963,3,30,1964,-8,-8,-8,-8,-8,-8,-8,4,Ogaden,1,-8,-8,-9,4.1
757,First Ogaden,5,530,Ethiopia,-8,Ogaden,1,6,-9,1963,3,30,1964,-8,-8,-8,-8,-8,-8,-8,4,Ogaden,1,-8,-9,-9,4.1
758,First South Sudan,5,625,Sudan,-8,Anya Nya,0,10,1,1963,2,28,1972,-8,-8,-8,-8,-8,-8,-8,6,Anya Nya,3,-8,-9,-9,4.1
760,Second DRC (Jeunesse),5,490,Congo,-8,Juenesse warriors,0,10,-9,1963,1,1,1965,-8,-8,-8,-8,-8,-8,-8,4,Juenesse warriors,1,-8,-9,-9,4.1
761,First Rwanda,4,517,Rwanda,-8,Watusi,0,11,15,1963,2,6,1964,-8,-8,-8,-8,-8,-8,-8,4,Watusi,1,-8,100,900,4.1
762,Third DRC (Simba) Rebellion,4,211,Belgium,-8,-8,1,11,24,1964,9,14,1965,-8,-8,-8,-8,-8,-8,-8,4,Gbenye followers,1,-8,4,-8,4.1
762,Third DRC (Simba) Rebellion,4,490,Congo,-8,Gbenye followers,1,1,1,1964,9,14,1965,-8,-8,-8,-8,-8,-8,-8,4,Gbenye followers,1,-8,250,4000,4.1
763,Zanzibar Arab-African,4,511,Zanzibar,-8,Africans,0,1,12,1964,1,15,1964,-8,-8,-8,-8,-8,-8,-8,4,Africans,2,-8,-9,-9,4.1
765,Second Iraqi Kurds,5,645,Iraq,-8,Kurds,0,4,3,1965,6,21,1966,-8,-8,-8,-8,-8,-8,-8,6,Iraq,3,-8,500,2500,4.1
766,Dominican Republic,4,2,United States of America,-8,-8,1,4,29,1965,9,6,1965,-8,-8,-8,-8,-8,-8,-8,1,Leftists,7,-8,27,-8,4.1
766,Dominican Republic,4,42,Dominican Republic,-8,Leftists,1,4,25,1965,9,6,1965,-8,-8,-8,-8,-8,-8,-8,1,Leftists,7,-8,2500,-9,4.1
767,First West Papua,5,850,Indonesia,-8,"OPM, West Papua",0,7,26,1965,7,17,1969,-8,-8,-8,-8,-8,-8,-8,7,"OPM, West Papua",6,-8,-9,-9,4.1
768,First Uganda,5,500,Uganda,-8,Buganda Tribe,0,5,23,1966,6,1,1966,-8,-8,-8,-8,-8,-8,-8,4,Buganda Tribe,1,-8,-9,-9,4.1
770,First Guatemala,4,2,United States,-8,-8,1,10,-9,1966,8,-9,1968,-8,-8,-8,-8,-8,-8,-8,1,Leftists,1,-8,28,-8,4.1
770,First Guatemala,4,90,Guatemala,-8,Leftists,1,10,-9,1966,8,-9,1968,-8,-8,-8,-8,-8,-8,-8,1,Leftists,1,-8,200,800,4.1
771,First Chad (FROLINAT) Rebellion,5,220,France,-8,-8,1,8,-9,1968,6,16,1971,-8,-8,-8,-8,-8,-8,-8,4,Frolinat Rebels,1,-8,50,-8,4.1
771,First Chad (FROLINAT) Rebellion,5,483,Chad,-8,Frolinat Rebels,1,11,-9,1966,6,16,1971,-8,-8,-8,-8,-8,-8,-8,4,Frolinat Rebels,1,-8,500,3000,4.1
772,Cultural Revolution Phase 1,6,-8,Red Guard,-8,Regional military,0,1,9,1967,9,4,1967,-8,-8,-8,-8,-8,-8,-8,7,Regional military,4,776,-9,-9,4.1
773,Third Burmese,5,775,Burma,-8,Karens & Communists,0,6,-9,1967,10,22,1980,-8,-8,-8,-8,-8,-8,-8,7,Karens,7,-8,6800,22400,4.1
775,Biafra,5,475,Nigeria,-8,Biafrans,0,7,6,1967,1,12,1970,-8,-8,-8,-8,-8,-8,-8,4,Nigeria,1,-8,-9,-9,4.1
776,Cultural Revolution Phase 2,4,710,China,-8,Red Guard,0,9,5,1967,9,1,1968,-8,-8,-8,-8,-8,-8,772,7,Red Guard,1,-8,-9,-9,4.1
777,Third Iraqi Kurds,5,645,Iraq,-8,Kurds,0,1,3,1969,3,11,1970,-8,-8,-8,-8,-8,-8,-8,6,Iraq,3,-8,800,3200,4.1
778,Naxalite Rebellion,5,750,India,-8,Naxalite Marxists,0,2,-9,1970,11,-9,1971,-8,-8,-8,-8,-8,-8,-8,7,Naxalite Marxists,1,-8,100,2000,4.1
780,Black September,4,-8,-8,652,Syria,1,9,20,1970,9,23,1970,-8,-8,-8,-8,-8,-8,-8,6,Jordan,1,-8,-8,100,4.1
780,Black September,4,663,Jordan,-8,Palestinians,1,9,13,1970,9,24,1970,-8,-8,-8,-8,-8,-8,-8,6,Jordan,1,-8,750,2690,4.1
781,Second Guatemala,4,90,Guatemala,-8,Leftists,0,11,15,1970,9,15,1971,-8,-8,-8,-8,-8,-8,-8,1,Guatemala,1,-8,50,950,4.1
782,Pakistan-Bengal,5,770,Pakistan,-8,Bengalis,0,3,25,1971,12,2,1971,-8,-8,-8,-8,-8,-8,-8,7,Pakistan,4,178,2500,-9,4.1
783,First Sri Lanka-JVP,4,780,Sri Lanka,-8,Janatha Vimukthi- JVP,0,4,6,1971,5,16,1971,-8,-8,-8,-8,-8,-8,-8,7,Janatha Vimukthi- JVP,1,-8,53,4000,4.1
785,Khmer Rouge,4,2,United States of America,-8,-8,1,7,3,1971,8,15,1973,-8,-8,-8,-8,-8,-8,176,7,Khmer Rouge,2,-8,375,-8,4.1
785,Khmer Rouge,4,811,Cambodia,-8,Khmer Rouge,1,7,3,1971,4,17,1975,-8,-8,-8,-8,-8,-8,176,7,Khmer Rouge,2,-8,45000,40000,4.1
786,First Philippine-Moro,5,840,Philippines,-8,MNLF Moros,0,1,1,1972,4,19,1981,-8,-8,-8,-8,-8,-8,-8,7,MNLF Moros,1,-8,10000,20000,4.1
787,Communist Insurgency,4,800,Thailand,-8,Communists,0,1,-9,1972,10,15,1973,-8,-8,-8,-8,-8,-8,-8,7,Communists,6,-8,1500,700,4.1
788,Eritrean Split,7,-8,ELF,-8,EPLF,0,2,-9,1972,-9,-9,1974,-8,-8,-8,-8,-8,-8,-8,4,ELF,6,-8,-9,-9,4.1
789,First Burundi,4,516,Burundi,-8,Hutu,0,4,29,1972,5,25,1972,-8,-8,-8,-8,-8,-8,-8,4,Hutu,1,-8,500,1500,4.1
790,Philippines-NPA,4,840,Philippines,-8,NPA,0,10,1,1972,12,31,1992,-8,-8,-8,-8,-8,-8,-8,7,NPA,6,-8,9000,22000,4.1
791,Rhodesia,4,552,Rhodesia,-8,Patriotic Front,0,12,28,1972,12,28,1979,-8,-8,-8,-8,-8,-8,-8,4,Patriotic Front,2,-8,1000,10000,4.1
792,Baluchi Separatists,5,770,Pakistan,-8,Baluchi Rebels,0,1,23,1973,7,-9,1977,-8,-8,-8,-8,-8,-8,-8,7,Baluchi Rebels,1,-8,3300,5300,4.1
793,Chilean Coup of 1973,4,155,Chile,-8,Pinochet led military,0,9,11,1973,9,15,1973,-8,-8,-8,-8,-8,-8,-8,1,Pinochet,2,-8,400,3000,4.1
795,Dhofar Rebellion Phase 2,5,200,United Kingdom,-8,-8,1,10,-9,1973,12,11,1975,-8,-8,-8,-8,-8,-8,-8,6,Oman,1,-8,35,-8,4.1
795,Dhofar Rebellion Phase 2,5,630,Iran,-8,-8,1,10,-9,1973,12,11,1975,-8,-8,-8,-8,-8,-8,-8,6,Oman,1,-8,100,-8,4.1
795,Dhofar Rebellion Phase 2,5,698,Oman,-8,PFLOAG,1,10,-9,1973,12,11,1975,-8,-8,-8,-8,-8,-8,-8,6,Oman,1,-8,370,2500,4.1
797,Fourth Iraqi Kurds,5,-8,-8,630,Iran,1,3,18,1974,3,6,1975,-8,-8,-8,-8,-8,-8,-8,6,Iraq,1,-8,-8,-9,4.1
797,Fourth Iraqi Kurds,5,645,Iraq,-8,Kurds,1,3,18,1974,4,3,1975,-8,-8,-8,-8,-8,-8,-8,6,Iraq,1,-8,7000,13000,4.1
798,Eritrean War,5,40,Cuba,-8,-8,1,12,5,1976,12,-9,1978,-8,-8,-8,-8,-8,-8,-8,4,Eritrean Peo. Lib.,1,-8,-9,-8,4.1
798,Eritrean War,5,530,Ethiopia,-8,Eritrean Peo. Lib.,1,1,31,1975,12,-9,1978,-8,-8,-8,-8,-8,-8,-8,4,Eritrean Peo. Lib.,1,-8,6100,6400,4.1
800,Argentine Leftists,4,160,Argentina,-8,"Montoneros, ERP",0,2,-9,1975,3,-9,1977,-8,-8,-8,-8,-8,-8,-8,1,"Montoneros, ERP",1,-8,250,2600,4.1
801,Second Lebanese,7,660,Maronite militias,-8,Lebanese National Movement,1,4,13,1975,11,15,1976,-8,-8,-8,-8,-8,-8,-8,6,Lebanese National Movement,3,-8,-9,-9,4.1
801,Second Lebanese,7,652,Syria,-8,-8,1,5,31,1976,11,15,1976,-8,-8,-8,-8,-8,-8,-8,6,Lebanese National Movement,3,-8,500,-8,4.1
802,Second West Papua,5,850,Indonesia,-8,"OPR, West Papua",0,1,1,1976,4,14,1978,-8,-8,-8,-8,-8,-8,-8,7,"OPR, West Papua",6,-8,100,2000,4.1
803,Third Laotian,5,812,Laos,,Hmong,1,4,-9,1976,5,-9,1979,-8,-8,-8,-8,-8,-8,-8,7,Hmong,1,-8,1000,5000,4.1
803,Third Laotian,5,816,Vietnam,-8,-8,1,1,-9,1976,5,-9,1979,-8,-8,-8,-8,-8,-8,-8,7,Hmong,1,-8,1000,-8,4.1
804,Angolan Control,4,40,Cuba,-8,-8,1,2,13,1976,5,15,1991,-8,-8,-8,-8,-8,-8,186,4,UNITA,3,-8,5500,-8,4.1
804,Angolan Control,4,540,Angola,-8,UNITA,1,2,13,1976,5,15,1991,-8,-8,-8,-8,-8,-8,186,4,UNITA,3,-8,-9,-9,4.1
804,Angolan Control,4,-8,-8,560,South Africa,1,2,13,1976,6,-9,1989,-8,-8,-8,-8,-8,-8,186,4,UNITA,3,-8,-8,800,4.1
805,Second Ogaden Phase 1,5,40,Cuba,-8,-8,1,7,1,1976,7,22,1977,-8,-8,-8,-8,-8,-8,-8,4,WSLF,4,187,1500,-8,4.1
805,Second Ogaden Phase 1,5,-8,-8,520,Somalia,1,7,1,1976,7,22,1977,-8,-8,-8,-8,-8,-8,-8,4,WSLF,4,187,-8,1900,4.1
805,Second Ogaden Phase 1,5,530,Ethiopia,-8,WSLF,1,7,1,1976,7,22,1977,-8,-8,-8,-8,-8,-8,-8,4,WSLF,4,187,9000,20000,4.1
806,East Timorese War Phase 3,5,850,Indonesia,-8,Fretilin,0,7,18,1976,5,26,1979,-8,-8,-8,-8,-8,-8,472,7,Fretelin,1,-8,1800,-9,4.1
807,Third Lebanese,7,,Lebanese Forces,-8,PLO & Shiite militia,1,2,1,1978,10,4,1978,-8,-8,-8,-8,-8,-8,-8,6,Syria & PLO,6,-8,1500,800,4.1
807,Third Lebanese,7,-8,-8,652,Syria,1,2,1,1978,10,4,1978,-8,-8,-8,-8,-8,-8,-8,6,Syria & PLO,6,-8,-8,800,4.1
807,Third Lebanese,7,666,Israel,-8,-8,1,3,14,1978,10,4,1978,-8,-8,-8,-8,-8,-8,-8,6,Syria & PLO,6,-8,-9,-8,4.1
808,Second Ogaden Phase 3,5,40,Cuba,-8,-8,1,3,10,1978,12,3,1980,-8,-8,-8,-8,-8,-8,187,4,"Ogaden, WSLF",1,-8,-9,-8,4.1
808,Second Ogaden Phase 3,5,530,Ethiopia,-8,"Ogaden, WSLF",1,3,10,1978,12,3,1980,-8,-8,-8,-8,-8,-8,187,4,"Ogaden, WSLF",1,-8,2000,20000,4.1
808,Second Ogaden Phase 3,5,-8,-8,520,Somalia,1,11,22,1980,12,3,1980,-8,-8,-8,-8,-8,-8,187,4,"Ogaden, WSLF",1,-8,-8,2000,4.1
809,Third Guatemala,4,90,Guatemala,-8,The Democratic Front Against Repression (FDCR),0,3,12,1978,4,13,1984,-8,-8,-8,-8,-8,-8,-8,1,Guatemala,1,-8,1250,4750,4.1
810,Saur Revolution,4,700,Afghanistan,-8,Leftist Military,0,4,27,1978,4,28,1978,-8,-8,-8,-8,-8,-8,-8,7,Leftist Military,2,-8,1800,1200,4.1
811,Fourth DRC (Shaba),4,211,Belgium,-8,-8,1,5,20,1978,6,6,1978,-8,-8,-8,-8,-8,-8,-8,4,FNLC,1,-8,-9,-8,4.1
811,Fourth DRC (Shaba),4,220,France,-8,-8,1,5,18,1978,6,6,1978,-8,-8,-8,-8,-8,-8,-8,4,FNLC,1,-8,5,-8,4.1
811,Fourth DRC (Shaba),4,490,DRC,-8,FNLC,1,5,1,1978,6,6,1978,-8,-8,-8,-8,-8,-8,-8,4,FNLC,1,-8,100,900,4.1
812,First Afghan Mujahideen Uprising,4,365,Russia,-8,-8,1,3,15,1979,2,21,1980,-8,-8,-8,-8,-8,-8,-8,7,Mujahedin,4,476,2000,-8,4.1
812,First Afghan Mujahideen Uprising,4,700,Afghanistan,-8,Mujahideen,1,9,1,1978,2,21,1980,-8,-8,-8,-8,-8,-8,-8,7,Mujahedin,4,476,11800,21200,4.1
813,Overthrow of the Shah,4,630,Iran,-8,Anti-Shah Coalition,0,9,3,1978,2,11,1979,-8,-8,-8,-8,-8,-8,-8,6,Iran,2,-8,100,1000,4.1
815,Sandinista Rebellion,4,93,Nicaragua,-8,Sandinistas,0,9,9,1978,7,18,1979,-8,-8,-8,-8,-8,-8,-8,1,Sandinistas,2,-8,1000,3000,4.1
816,Anti-Khomeini Coalition,4,630,Iran,-8,Anti-Khmoneini Coalition: Fedayeen Kalq & Kurds,0,2,12,1979,3,-9,1984,-8,-8,-8,-8,-8,-8,-8,6,Coalition,1,-8,-9,-9,4.1
817,El Salvador,4,92,El Salvador,-8,Salvadorean Democratic Front,0,7,1,1979,2,1,1992,-8,-8,-8,-8,-8,-8,-8,1,Salvadorean Democratic Front,3,-8,-9,-9,4.1
818,Mozambique,4,510,Tanzania,-8,-8,1,-9,-9,1985,10,4,1992,-8,-8,-8,-8,-8,-8,-8,4,Renamo,1,-8,50,-8,4.1
818,Mozambique,4,541,Mozambique,-8,Renamo,1,10,21,1979,10,4,1992,-8,-8,-8,-8,-8,-8,-8,4,Renamo,1,-8,-9,-9,4.1
818,Mozambique,4,552,Zimbabwe,-8,-8,1,-9,-9,1982,10,4,1992,-8,-8,-8,-8,-8,-8,-8,4,Renamo,1,-8,500,-8,4.1
820,Second Chad (Habre Revolt),5,-8,-8,220,France,1,8,9,1983,9,-9,1984,-8,-8,-8,-8,-8,-8,-8,4,FAN,2,-8,-8,200,4.1
820,Second Chad (Habre Revolt),5,483,Chad,-8,FAN,1,3,22,1980,9,-9,1984,-8,-8,-8,-8,-8,-8,-8,4,FAN,2,-8,3500,1500,4.1
820,Second Chad (Habre Revolt),5,620,Libya,-8,-8,1,12,-9,1980,10,-9,1981,6,-9,1983,9,-9,1984,-8,4,FAN,2,-8,1000,-8,4.1
822,Second Uganda,5,500,Uganda,-8,National Resistance Army,0,12,8,1980,3,19,1986,-8,-8,-8,-8,-8,-8,-8,4,National Resistance Army,2,-8,40000,6000,4.1
823,Nigeria-Muslim,5,475,Nigeria,-8,Muslim fundamentalists,0,12,18,1980,1,1,1981,-8,-8,-8,-8,-8,-8,-8,4,Muslim fundamentalists,1,-8,50,1000,4.1
825,Hama,4,652,Syria,-8,Muslim Brotherhood,0,11,-9,1981,2,23,1982,-8,-8,-8,-8,-8,-8,-8,6,Muslim Brotherhood,1,-8,1000,2000,4.1
826,Tigrean and Eritrean,5,530,Ethiopia,-8,Tigray & Eritrea,0,1,23,1982,5,28,1991,-8,-8,-8,-8,-8,-8,-8,4,Tigray & Eritrea,2,-8,10000,65000,4.1
827,Shining Path,4,135,Peru,-8,Shining Path & TARM,0,3,4,1982,9,12,1992,-8,-8,-8,-8,-8,-8,-8,1,Shining Path,1,-8,4000,12000,4.1
828,Contra War,4,93,Nicaragua,-8,Contras,0,3,18,1982,4,19,1990,-8,-8,-8,-8,-8,-8,-8,1,Contras,6,-8,7000,25200,4.1
831,Matabeleland,4,552,Zimbabwe,-8,ZAPU,0,1,-9,1983,12,27,1987,-8,-8,-8,-8,-8,-8,-8,4,Zimbabwe,1,-8,-9,-9,4.1
832,Fourth Burmese,5,775,Burma,-8,Karen & Kachin Rebels,0,2,1,1983,1,-9,1988,-8,-8,-8,-8,-8,-8,-8,7,Kachin Rebels,1,-8,2800,1200,4.1
833,Fourth Lebanese Civil,4,2,United States,-8,-8,1,4,18,1983,2,29,1984,-8,-8,-8,-8,-8,-8,-8,6,Druze,2,-8,273,-8,4.1
833,Fourth Lebanese Civil,4,220,France,-8,-8,1,4,18,1983,2,29,1984,-8,-8,-8,-8,-8,-8,-8,6,Druze,2,-8,95,-8,4.1
833,Fourth Lebanese Civil,4,660,Lebanon,-8,Shi'ites & Druze,1,4,18,1983,2,29,1984,-8,-8,-8,-8,-8,-8,-8,6,Druze,2,-8,-9,-9,4.1
835,First Sri Lanka Tamil,5,750,India,-8,-8,1,7,25,1987,5,24,1990,-8,-8,-8,-8,-8,-8,-8,7,Tamils,3,-8,1155,-8,4.1
835,First Sri Lanka Tamil,5,780,Sri Lanka,-8,Tamils,1,7,25,1983,2,22,2002,-8,-8,-8,-8,-8,-8,-8,7,Tamils,3,-8,8500,17000,4.1
836,Second South Sudan,4,625,Sudan,-8,SPLA-Garang faction,0,11,17,1983,8,27,1991,4,15,1992,1,10,2005,-8,6,SPLA-Garang faction,3,-8,-9,-9,4.1
837,Indian Golden Temple,5,750,India,-8,Sikhs,0,6,1,1984,7,30,1984,-8,-8,-8,-8,-8,-8,-8,7,India,6,-8,-9,1200,4.1
838,First Turkish Kurds,5,640,Turkey,-8,"Kurds, PKK",0,8,14,1984,3,-9,1986,-8,-8,-8,-8,-8,-8,-8,6,"Kurds, PKK",7,-8,1500,9000,4.1
840,Fifth Iraqi  Kurds,5,-8,-8,630,Iran,1,1,-9,1985,7,17,1988,-8,-8,-8,-8,-8,-8,-8,6,Kurds,1,-8,-8,-9,4.1
840,Fifth Iraqi  Kurds,5,645,Iraq,-8,Kurds,1,1,-9,1985,9,6,1988,-8,-8,-8,-8,-8,-8,-8,6,Kurds,1,-8,-9,-9,4.1
842,South Yemen,4,680,Yemen People's Republic,-8,Leftist Factions,0,1,13,1986,1,29,1986,-8,-8,-8,-8,-8,-8,-8,6,PDRY,2,-8,4200,8800,4.1
843,Holy Spirit Movement,4,500,Uganda,-8,HSMF,0,8,-9,1986,10,-9,1987,-8,-8,-8,-8,-8,-8,-8,4,HSMF,1,-8,2000,5000,4.1
845,Second Sri Lanka-JVP,4,780,Sri Lanka,-8,JVP,0,7,29,1987,12,29,1989,-8,-8,-8,-8,-8,-8,-8,7,JVP,1,-8,-9,-9,4.1
846,Inkatha-ANC,7,-8,Inkatha,-8,ANC,0,12,20,1987,4,26,1994,-8,-8,-8,-8,-8,-8,-8,4,Inkatha,6,-8,-9,-9,4.1
847,Fifth Burmese,4,775,Burma,-8,Pro-democracy,0,3,-9,1988,10,3,1988,-8,-8,-8,-8,-8,-8,-8,7,Pro-democracy,1,-8,-9,-9,4.1
848,First Somalia,4,520,Somalia,-8,rebel clans,0,5,26,1988,1,26,1991,-8,-8,-8,-8,-8,-8,-8,4,USC,2,-8,-9,-9,4.1
850,Fifth Lebanese,4,-8,-8,652,Syria,1,2,-9,1989,10,13,1990,-8,-8,-8,-8,-8,-8,-8,6,Lebanon,2,-8,-8,150,4.1
850,Fifth Lebanese,4,660,Lebanon,-8,militias,1,2,-9,1989,10,13,1990,-8,-8,-8,-8,-8,-8,-8,6,Lebanon,2,-8,-9,2500,4.1
851,Second Afghan Mujahideen Uprising,4,700,Afghanistan,-8,Mujahadin,0,2,16,1989,10,6,2001,-8,-8,-8,-8,-8,-8,476,7,Mujahadin,4,225,-9,-9,4.1
852,Third Chad (Deby Coup),4,483,Chad,-8,Deby's MPS,0,3,-9,1989,12,4,1990,-8,-8,-8,-8,-8,-8,-8,4,Deby,2,-8,3000,800,4.1
853,First Aceh,5,850,Indonesia,-8,GAM,0,6,-9,1989,6,-9,1991,-8,-8,-8,-8,-8,-8,-8,7,GAM,1,-8,-9,-9,4.1
854,Bougainville Secession,5,910,Papua New Guinea,-8,BRA,0,7,14,1989,9,-9,1992,-8,-8,-8,-8,-8,-8,-8,7,P.N.G.,7,-8,-9,-9,4.1
856,Eighth Colombia,5,100,Colombia,-8,FARC & Drug Lords,0,8,19,1989,-7,-7,-7,-8,-8,-8,-8,-8,-8,-8,1,Drug Lords & FARC,5,-8,"10,480","17,681",4.1
857,First Cambodian Civil War,4,811,Cambodia,-8,Khmer Rouge & KPNFL,0,9,26,1989,10,23,1991,-8,-8,-8,-8,-8,-8,475,7,Khmer Rouge & KPNFL,3,-8,-9,-9,4.1
858,Romania,4,360,Romania,-8,Anti-Ceaucescu Rebels,0,12,18,1989,12,26,1989,-8,-8,-8,-8,-8,-8,-8,2,Anti-Ceaucescu Rebels,2,-8,300,700,4.1
860,First Liberia,4,450,Liberia,-8,NPFL,1,12,24,1989,11,28,1990,-8,-8,-8,-8,-8,-8,-8,4,NPFL,7,-8,-9,-9,4.1
860,First Liberia,4,475,Nigeria,-8,-8,1,11,-9,1990,11,28,1990,-8,-8,-8,-8,-8,-8,-8,4,NPFL,7,-8,0,-8,4.1
861,Kashmir Insurgents,5,750,India,-8,Kashmiri Guerillas,0,9,19,1990,10,8,2005,-8,-8,-8,-8,-8,-8,-8,7,Kashmiri Guerillas,7,-8,6000,21700,4.1
862,Shiite and Kurdish,5,645,Iraq,-8,Shiites & Kurds,0,3,1,1991,3,31,1991,-8,-8,-8,-8,-8,-8,-8,6,Shiites,1,-8,-9,-9,4.1
863,First Sierra Leone,4,451,Sierra Leone,-8,RUF,0,3,23,1991,4,23,1996,-8,-8,-8,-8,-8,-8,-8,4,RUF,1,-8,-9,-9,4.1
864,Croatian Independence,5,345,Yugoslavia/Serbia,-8,Croatia,0,5,2,1991,1,2,1992,-8,-8,-8,-8,-8,-8,-8,2,Yugoslavia,2,-8,-9,-9,4.1
865,Second Turkish Kurds,5,640,Turkey,-8,"Kurds, PKK",0,7,10,1991,2,16,1999,-8,-8,-8,-8,-8,-8,-8,6,"Kurds, PKK",6,-8,3500,13000,4.1
866,The SPLA Division (Dinka-Nuer) War,7,-8,Garang faction,-8,Nuer faction,0,8,28,1991,11,-9,1992,-8,-8,-8,-8,-8,-8,-8,4,Nuer faction,7,-8,-9,-9,4.1
868,Jukun-Tiv War,7,-8,Jukun,-8,Tiv,0,10,-9,1991,3,-9,1992,-8,-8,-8,-8,-8,-8,-8,4,Tiv,6,-8,-9,-9,4.1
870,Second Somalia,4,475,Nigeria,-8,-8,1,12,13,1992,3,1,1995,-8,-8,-8,-8,-8,-8,-8,4,Aideed Faction,3,-8,-9,-8,4.1
870,Second Somalia,4,520,Somalia,-8,Aideed Faction,1,11,-9,1991,1,-9,1997,-8,-8,-8,-8,-8,-8,-8,4,Aideed Faction,3,-8,-9,-9,4.1
870,Second Somalia,4,770,Pakistan,-8,-8,1,12,13,1992,3,1,1995,-8,-8,-8,-8,-8,-8,-8,4,Aideed Faction,3,-8,24,-8,4.1
870,Second Somalia,4,900,Australia,-8,-8,1,12,13,1992,3,1,1995,-8,-8,-8,-8,-8,-8,-8,4,Aideed Faction,3,-8,-9,-8,4.1
870,Second Somalia,4,220,France,-8,-8,1,12,13,1992,3,1,1995,-8,-8,-8,-8,-8,-8,-8,4,Aideed Faction,3,-8,2,-8,4.1
870,Second Somalia,4,2,United States of America,-8,-8,1,12,13,1992,3,25,1994,-8,-8,-8,-8,-8,-8,-8,4,Aideed Faction,3,-8,44,-8,4.1
870,Second Somalia,4,325,Italy,-8,-8,1,12,13,1992,3,1,1995,-8,-8,-8,-8,-8,-8,-8,4,Aideed Faction,3,-8,-9,-8,4.1
871,Georgia,4,372,Georgia,-8,Reform,0,12,26,1991,3,-9,1992,-8,-8,-8,-8,-8,-8,-8,2,Reform,2,-8,-9,-9,4.1
872,Nagorno-Karabakh,5,-8,-8,371,Armenia,1,12,26,1991,2,5,1993,-8,-8,-8,-8,-8,-8,-8,2,Nagorno-Karabakh,4,216,-8,1000,4.1
872,Nagorno-Karabakh,5,373,Azerbaijan,-8,Nagorno-Karabakh,1,12,26,1991,2,5,1993,-8,-8,-8,-8,-8,-8,-8,2,Nagorno-Karabakh,4,216,7000,3000,4.1
873,Dniestrian Independence,5,359,Moldova,-8,Dniestria,0,12,26,1991,7,2,1992,-8,-8,-8,-8,-8,-8,-8,2,Dniestria,3,-8,-9,-9,4.1
875,Algerian Islamic Front,4,615,Algeria,-8,Islamic Front,0,2,7,1992,6,-9,1999,-8,-8,-8,-8,-8,-8,-8,6,Algeria,3,-8,-9,-9,4.1
876,Tajikistan,4,365,Russia,-8,-8,1,3,-9,1993,6,27,1997,-8,-8,-8,-8,-8,-8,-8,7,United Tajik Opposition,3,-8,-9,-8,4.1
876,Tajikistan,4,702,Tadzhikistan,-8,United Tajik Opposition,1,5,1,1992,6,27,1997,-8,-8,-8,-8,-8,-8,-8,7,United Tajik Opposition,3,-8,-9,-9,4.1
877,Bosnian-Serb Rebellion,5,346,Bosnia,-8,Bosnian Serbs,1,6,6,1992,12,31,1994,3,20,1995,12,14,1995,215,2,Bosnian Serbs,1,-8,27500,18543,4.1
877,Bosnian-Serb Rebellion,5,2,United States,-8,-8,1,8,30,1995,9,20,1995,-8,-8,-8,-8,-8,-8,215,2,Bosnian Serbs,1,-8,0,-8,4.1
877,Bosnian-Serb Rebellion,5,-8,-8,344,Croatia,1,2,23,1994,12,31,1994,3,20,1995,12,14,1995,215,2,Bosnian Serbs,1,-8,-8,185,4.1
877,Bosnian-Serb Rebellion,5,344,Croatia,-8,-8,1,10,19,1992,2,22,1994,-8,-8,-8,-8,-8,-8,215,2,Bosnian Serbs,1,-8,-9,-8,4.1
878,Second Liberia,4,450,Liberia,-8,NPFL & ULIMO,1,10,15,1992,8,19,1995,-8,-8,-8,-8,-8,-8,-8,4,NPFL & ULIMO,3,-8,-9,-9,4.1
878,Second Liberia,4,475,Nigeria,-8,-8,1,10,15,1992,12,31,1992,-8,-8,-8,-8,-8,-8,-8,4,NPFL & ULIMO,3,-8,-9,-8,4.1
880,Angolan War of the Cities,4,540,Angola,-8,UNITA,0,10,28,1992,11,15,1994,-8,-8,-8,-8,-8,-8,-8,4,UNITA,3,-8,-9,-9,4.1
881,Second Cambodia Civil,4,811,Cambodia,-8,Khmer Rouge,0,1,29,1993,7,1,1997,-8,-8,-8,-8,-8,-8,-8,7,Khmer Rouge,1,-8,-9,-9,4.1
882,Abkhazia Revolt,5,372,Georgia,-8,Abkhazia,0,8,18,1993,4,14,1994,-8,-8,-8,-8,-8,-8,-8,2,Georgia,2,-8,5000,3000,4.1
883,Second Burundi,4,516,Burundi,-8,Tutsi army,0,10,21,1993,6,-9,1998,-8,-8,-8,-8,-8,-8,-8,4,Tutsi army,7,-8,-9,-9,4.1
885,South Yemeni Secessionist,5,679,Yemen,-8,South Yemen,0,2,21,1994,7,7,1994,-8,-8,-8,-8,-8,-8,-8,6,South Yemen,1,-8,-9,-9,4.1
886,Second Rwanda,4,517,Rwanda,-8,Patriotic Front,0,4,6,1994,7,18,1994,-8,-8,-8,-8,-8,-8,-8,4,Patriotic Front,2,-8,-9,-9,4.1
888,First Chechnya,5,365,Russia,-8,Chechnya,0,12,11,1994,8,31,1996,-8,-8,-8,-8,-8,-8,-8,2,Chechnya,2,-8,4000,6000,4.1
890,Iraqi Kurd Internecine,7,-8,PUK,-8,KDP,0,12,20,1994,8,11,1995,-8,-8,-8,-8,-8,-8,-8,6,KDP,6,-8,-9,-9,4.1
891,Croatia-Krajina War,5,344,Croatia,-8,Krajinia Serbs,0,5,-9,1995,11,-9,1995,-8,-8,-8,-8,-8,-8,-8,2,Krajinian Serba,1,-8,-9,-9,4.1
892,Third Liberia,4,450,Liberia,-8,NPFL,0,4,5,1996,8,20,1996,-8,-8,-8,-8,-8,-8,-8,4,National Patriotic Forces,3,-8,-9,-9,4.1
893,Sixth Iraqi Kurds,5,645,Iraq,-8,PUK,0,8,31,1996,10,23,1996,-8,-8,-8,-8,-8,-8,-8,6,PUK,6,-8,-9,-9,4.1
895,Fifth DRC,4,-8,-8,500,Uganda,1,1,1,1997,1,30,1997,-8,-8,-8,-8,-8,-8,-8,4,Kabila-ADFL,2,-8,-8,-9,4.1
895,Fifth DRC,4,-8,-8,517,Rwanda,1,1,1,1997,5,17,1997,-8,-8,-8,-8,-8,-8,-8,4,Kabila-ADFL,2,-8,-8,-9,4.1
895,Fifth DRC,4,-8,-8,540,Angola,1,4,28,1997,5,17,1997,-8,-8,-8,-8,-8,-8,-8,4,Kabila-ADFL,2,-8,-8,-9,4.1
895,Fifth DRC,4,490,DRC,-8,ADFL,1,10,8,1996,5,17,1997,-8,-8,-8,-8,-8,-8,-8,4,Kabila-ADFL,2,-8,-9,-9,4.1
896,Third Rwanda,4,517,Rwanda,-8,Hutu rebels,0,3,17,1997,10,30,1998,-8,-8,-8,-8,-8,-8,-8,4,Hutu rebels,1,-8,300,3000,4.1
897,First Congo (Brazzaville),4,-8,-8,540,Angola,1,10,10,1997,10,15,1997,-8,-8,-8,-8,-8,-8,-8,4,FDU,2,-8,-8,-9,4.1
897,First Congo (Brazzaville),4,484,Congo,-8,FDU (Cobra militia),1,6,5,1997,10,15,1997,-8,-8,-8,-8,-8,-8,-8,4,FDU (Cobra militia),2,-8,-9,-9,4.1
898,Second Sierra Leone,4,451,Sierra Leone,-8,Kabbah faction,1,2,6,1998,7,7,1999,5,11,2000,11,10,2000,-8,4,Kabbah faction,2,-8,-9,-9,4.1
898,Second Sierra Leone,4,-8,-8,452,Ghana,1,2,6,1998,7,7,1999,5,11,2000,11,10,2000,-8,4,Kabbah faction,2,-8,-8,-9,4.1
898,Second Sierra Leone,4,-8,-8,475,Nigeria,1,2,6,1998,7,7,1999,5,11,2000,11,10,2000,-8,4,Kabbah faction,2,-8,-8,-9,4.1
898,Second Sierra Leone,4,-8,-8,438,Guinea,1,2,6,1998,7,7,1999,5,11,2000,11,10,2000,-8,4,Kabbah faction,2,-8,-8,-9,4.1
898,Second Sierra Leone,4,-8,-8,200,United Kingdom,1,5,8,2000,11,10,2000,-8,-8,-8,-8,-8,-8,-8,4,Kabbah faction,2,-8,-8,-9,4.1
900,Kosovo Independence,5,345,Yugoslavia,-8,KLA,0,2,28,1998,3,23,1999,-8,-8,-8,-8,-8,-8,-8,2,Yugoslavia,4,221,400,800,4.1
902,Guinea-Bissau Military,4,438,Guinea,-8,-8,1,6,9,1998,11,1,1998,-8,-8,-8,-8,-8,-8,-8,4,Man� Junta,2,-8,-9,-8,4.1
902,Guinea-Bissau Military,4,404,Guinea-Bissau,-8,Man� Junta,1,6,7,1998,5,6,1999,-8,-8,-8,-8,-8,-8,-8,4,Man� Junta,2,-8,-9,-9,4.1
902,Guinea-Bissau Military,4,433,Senegal,-8,-8,1,6,9,1998,11,1,1998,-8,-8,-8,-8,-8,-8,-8,4,Man� Junta,2,-8,-9,-8,4.1
905,Africa's World War,4,540,Angola,-8,-8,1,8,24,1998,11,4,2002,-8,-8,-8,-8,-8,-8,-8,4,,3,-8,-9,-8,4.1
905,Africa's World War,4,625,Sudan,-8,-8,1,9,17,1998,7,22,2002,-8,-8,-8,-8,-8,-8,-8,4,,3,-8,-9,-8,4.1
905,Africa's World War,4,565,Namibia,-8,-8,1,8,28,1998,8,4,2001,-8,-8,-8,-8,-8,-8,-8,4,,3,-8,-9,-8,4.1
905,Africa's World War,4,552,Zimbabwe,-8,-8,1,8,21,1998,9,13,2002,-8,-8,-8,-8,-8,-8,-8,4,,3,-8,-9,-8,4.1
905,Africa's World War,4,-8,-8,517,Rwanda,1,8,11,1998,7,22,2002,-8,-8,-8,-8,-8,-8,-8,4,,3,-8,-8,-9,4.1
905,Africa's World War,4,-8,-8,516,Burundi,1,9,17,1998,7,22,2002,-8,-8,-8,-8,-8,-8,-8,4,,3,-8,-8,-9,4.1
905,Africa's World War,4,-8,-8,500,Uganda,1,8,26,1998,7,22,2002,-8,-8,-8,-8,-8,-8,-8,4,,3,-8,-8,-9,4.1
905,Africa's World War,4,483,Chad,-8,-8,1,9,30,1998,4,18,1999,-8,-8,-8,-8,-8,-8,-8,4,,3,-8,-9,-8,4.1
905,Africa's World War,4,490,Democratic Republic of Congo,-8,"RCD, MLC, et al",1,8,2,1998,12,17,2002,-8,-8,-8,-8,-8,-8,-8,4,"RCD, MLC, et al",3,-8,-9,-9,4.1
906,Fourth Chad (Togoimi Revolt),4,483,Chad,-8,MDD & MDJT,0,10,16,1998,4,28,2000,-8,-8,-8,-8,-8,-8,-8,4,MDD & MDJT,7,-8,-9,-9,4.1
907,Third Angolan,4,540,Angola,-8,UNITA,0,12,4,1998,2,22,2002,-8,-8,-8,-8,-8,-8,-8,4,Angola,1,-8,-9,-9,4.1
908,Second Congo (Brazzaville),4,484,Congo (Brazzaville),-8,Ninjas and Cocoye militias,0,12,15,1998,11,16,1999,-8,-8,-8,-8,-8,-8,-8,4,Ninjas and Cocoye militias,1,-8,-9,-9,4.1
910,Moluccas Sectarian,7,-8,Laskar Jihad,-8,FKM & RMS,0,1,-9,1999,8,22,2000,-8,-8,-8,-8,-8,-8,-8,7,Laskar Jihad,7,-8,-9,1800,4.1
911,First Nigeria Christian-Muslim,7,-8,Christian Tarok,-8,Muslim Fulani,0,5,-9,1999,5,31,2000,-8,-8,-8,-8,-8,-8,-8,4,Muslim Fulani,1,-8,-9,-9,4.1
912,Second Aceh,5,850,Indonesia,-8,GAM,0,5,3,1999,12,9,2002,-8,-8,-8,-8,-8,-8,-8,7,GAM,3,-8,330,3500,4.1
913,Oromo Liberation,5,530,Ethiopia,-8,Oromo Lib. Front,0,5,30,1999,8,18,1999,-8,-8,-8,-8,-8,-8,-8,4,Oromo Lib. Front,1,-8,200,800,4.1
915,Second Chechen,5,365,Russia,-8,Chechnya,0,8,7,1999,10,3,2003,-8,-8,-8,-8,-8,-8,-8,2,Cechnya,1,-8,5000,15000,4.1
916,Second Philippine-Moro,5,840,Philippines,-8,MILF,0,4,23,2000,6,22,2001,-8,-8,-8,-8,-8,-8,-8,7,Phillippines,3,-8,-9,-9,4.1
917,Guinean,4,438,Guinea ,-8,RDFG,0,9,11,2000,4,-9,2001,-8,-8,-8,-8,-8,-8,-8,4,RDFG,6,-8,-9,-9,4.1
918,Third Burundi,4,516,Burundi,-8,FNL & FROLINA,0,3,21,2001,10,8,2003,-8,-8,-8,-8,-8,-8,-8,4,FNL,3,-8,150,3000,4.1
920,Fourth Rwanda,4,517,Rwanda,-8,Army for the Liberation of Rwanda,0,5,21,2001,9,4,2001,-8,-8,-8,-8,-8,-8,-8,4,ALIR,1,-8,-9,1800,4.1
921,First Nepal Maoist Insurgency,4,790,Nepal ,-8,CPN,0,11,23,2001,1,29,2003,-8,-8,-8,-8,-8,-8,-8,7,CPN,6,-8,680,3100,4.1
922,Fourth Liberian,4,450,Liberia,-8,LURD & MODEL,0,2,-9,2002,8,11,2003,-8,-8,-8,-8,-8,-8,-8,4,LURD & MODEL,2,-8,-9,-9,4.1
923,Ethiopian Anyuaa-Nuer,7,,Anyuaa,-8,Nuer,0,8,-9,2002,1,-9,2003,-8,-8,-8,-8,-8,-8,-8,4,Nuer,7,-8,-9,-9,4.1
925,Cote d'Ivoire Military,4,220,France,-8,-8,1,12,11,2002,11,16,2004,-8,-8,-8,-8,-8,-8,-8,4,"MPCI, MPIGO, MJP",2,-8,9,-8,4.1
925,Cote d'Ivoire Military,4,437,Cote d'Ivoire,-8,"MPCI, MPIGO, MJP",1,9,19,2002,11,16,2004,-8,-8,-8,-8,-8,-8,-8,4,"MPCI, MPIGO, MJP",2,-8,200,2500,4.1
926,Third Philippine-Moro,5,840,Phillippines,-8,MILF & ASG,0,2,11,2003,7,-9,2003,-8,-8,-8,-8,-8,-8,-8,7,Phillippines,7,-8,410,590,4.1
927,Darfur,5,625,Sudan,-8,SLA & JEM,0,2,26,2003,12,11,2006,-8,-8,-8,-8,-8,-8,-8,6,SLA,6,-8,-9,-9,4.1
930,Third Aceh,5,850,Indonesia,-8,GAM,0,5,18,2003,11,18,2003,-8,-8,-8,-8,-8,-8,-8,7,Indonesia,1,-8,150,1400,4.1
931,Second Nepal Maoists,4,790,Nepal,-8,CPN,0,8,27,2003,4,26,2006,-8,-8,-8,-8,-8,-8,-8,7,CPN,3,-8,1260,5770,4.1
932,Waziristan,5,2,United States,-8,-8,1,2,20,2004,9,5,2006,-8,-8,-8,-8,-8,-8,-8,7,US & Pakistan,2,-8,-9,-8,4.1
932,Waziristan,5,770,Pakistan,-8,Waziri tribes,1,2,20,2004,9,5,2006,-8,-8,-8,-8,-8,-8,-8,7,US & Pakistan,2,-8,1200,1800,4.1
933,Second Nigeria Christian-Muslim,7,,Christian Tarok,-8,Muslim Fulani,0,3,-9,2004,9,16,2004,-8,-8,-8,-8,-8,-8,-8,4,Muslim Fulani,6,-8,-9,-9,4.1
935,First Yemeni Cleric,4,679,Yemen,-8,Zaidi Muslims,0,6,21,2004,4,8,2005,-8,-8,-8,-8,-8,-8,-8,6,Zaidi Muslims,1,-8,900,1350,4.1
936,Philippine Joint Offensive,5,840,Phillippines,-8,MILF & NPA,0,1,17,2005,7,11,2006,-8,-8,-8,-8,-8,-8,-8,7,Phillippines,7,-8,723,2100,4.1
937,Fifth Chad,4,483,Chad,-8,FUDC,0,12,18,2005,12,20,2006,-8,-8,-8,-8,-8,-8,-8,4,FUDC,1,-8,100,1000,4.1
938,Third Somalia,4,2,United States,-8,-8,1,1,7,2007,6,3,2007,-8,-8,-8,-8,-8,-8,-8,4,SCIC,1,-8,-9,-8,4.1
938,Third Somalia,4,520,Somalia,-8,SCIC,1,3,6,2006,6,1,2008,-8,-8,-8,-8,-8,-8,-8,4,SCIC,1,-8,-9,-9,4.1
938,Third Somalia,4,530,Ethiopia,-8,-8,1,10,9,2006,6,11,2008,-8,-8,-8,-8,-8,-8,-8,4,SCIC,1,-8,-9,-8,4.1
938,Third Somalia,4,-8,-8,531,Eritrea,1,10,19,2006,6,11,2008,-8,-8,-8,-8,-8,-8,-8,4,SCIC,1,-8,-8,-9,4.1
940,Second Sri Lanka Tamil,5,780,Sri Lanka,-8,LTTE,0,10,11,2006,-7,-7,-7,-8,-8,-8,-8,-8,-8,-8,7,Sri Lanka,5,-8,-9,-9,4.1
941,Second Yemeni Cleric,4,679,Yemen,-8,Zaidi Muslims,0,1,29,2007,6,16,2007,-8,-8,-8,-8,-8,-8,-8,6,Zaidi Muslims,6,-8,1500,2000,4.1
\ No newline at end of file
diff --git a/week2_analysis.ipynb b/week2_analysis.ipynb
new file mode 100644
index 0000000..7152115
--- /dev/null
+++ b/week2_analysis.ipynb
@@ -0,0 +1,1294 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "c033731f-63ff-45a1-9466-15886f15ae09",
+   "metadata": {},
+   "source": [
+    "Тестовый код"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "bf32d476-0486-4477-aab4-e86965882fdf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "9\n"
+     ]
+    }
+   ],
+   "source": [
+    "test = 4\n",
+    "test2 = 5\n",
+    "print(test + test2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8757d814-8118-4250-9fe6-8d4c847f4791",
+   "metadata": {},
+   "source": [
+    "Часть 3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "6e2f0daf-10fe-4892-8438-7a10f5cc05bd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первый взгляд на данные:\n",
+      "      Имя  Возраст  Баллы\n",
+      "0    Анна       21     89\n",
+      "1   Борис       22     76\n",
+      "2  Виктор       23     95\n",
+      "3  Галина       24     82\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4 entries, 0 to 3\n",
+      "Data columns (total 3 columns):\n",
+      " #   Column   Non-Null Count  Dtype \n",
+      "---  ------   --------------  ----- \n",
+      " 0   Имя      4 non-null      object\n",
+      " 1   Возраст  4 non-null      int64 \n",
+      " 2   Баллы    4 non-null      int64 \n",
+      "dtypes: int64(2), object(1)\n",
+      "memory usage: 228.0+ bytes\n",
+      "None\n",
+      "         Возраст      Баллы\n",
+      "count   4.000000   4.000000\n",
+      "mean   22.500000  85.500000\n",
+      "std     1.290994   8.266398\n",
+      "min    21.000000  76.000000\n",
+      "25%    21.750000  80.500000\n",
+      "50%    22.500000  85.500000\n",
+      "75%    23.250000  90.500000\n",
+      "max    24.000000  95.000000\n",
+      "Имя        0\n",
+      "Возраст    0\n",
+      "Баллы      0\n",
+      "dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Создадим DataFrame\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "print(\"Первый взгляд на данные:\")\n",
+    "print(df.head())\n",
+    "print(df.info())\n",
+    "print(df.describe())\n",
+    "print(df.isnull().sum())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3b801627-8797-4b4d-8f3d-c3ea9911e1bf",
+   "metadata": {},
+   "source": [
+    "Часть 3 с изменениями"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "f9b40974-e401-451a-8dcb-3aa296931280",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первый взгляд на данные:\n",
+      "      Имя  Возраст  Баллы\n",
+      "0    Анна       21     89\n",
+      "1   Борис       22     76\n",
+      "2  Виктор       23     95\n",
+      "3  Галина       24     82\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4 entries, 0 to 3\n",
+      "Data columns (total 3 columns):\n",
+      " #   Column   Non-Null Count  Dtype \n",
+      "---  ------   --------------  ----- \n",
+      " 0   Имя      4 non-null      object\n",
+      " 1   Возраст  4 non-null      int64 \n",
+      " 2   Баллы    4 non-null      int64 \n",
+      "dtypes: int64(2), object(1)\n",
+      "memory usage: 228.0+ bytes\n",
+      "None\n",
+      "         Возраст      Баллы\n",
+      "count   4.000000   4.000000\n",
+      "mean   22.500000  85.500000\n",
+      "std     1.290994   8.266398\n",
+      "min    21.000000  76.000000\n",
+      "25%    21.750000  80.500000\n",
+      "50%    22.500000  85.500000\n",
+      "75%    23.250000  90.500000\n",
+      "max    24.000000  95.000000\n",
+      "Имя        0\n",
+      "Возраст    0\n",
+      "Баллы      0\n",
+      "dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Имя</th>\n",
+       "      <th>Возраст</th>\n",
+       "      <th>Баллы</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Анна</td>\n",
+       "      <td>21</td>\n",
+       "      <td>89</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Борис</td>\n",
+       "      <td>22</td>\n",
+       "      <td>76</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Виктор</td>\n",
+       "      <td>23</td>\n",
+       "      <td>95</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Галина</td>\n",
+       "      <td>24</td>\n",
+       "      <td>82</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Имя  Возраст  Баллы\n",
+       "0    Анна       21     89\n",
+       "1   Борис       22     76\n",
+       "2  Виктор       23     95\n",
+       "3  Галина       24     82"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Создадим DataFrame\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "print(\"Первый взгляд на данные:\")\n",
+    "print(df.head())\n",
+    "print(df.info())\n",
+    "print(df.describe())\n",
+    "print(df.isnull().sum())\n",
+    "\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "9ee10d5f-ba28-45bd-9766-89491bb8d9a1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первый взгляд на данные:\n",
+      "      Имя  Возраст  Баллы  Новый столбец\n",
+      "0    Анна       21     89           97.9\n",
+      "1   Борис       22     76           83.6\n",
+      "2  Виктор       23     95          104.5\n",
+      "3  Галина       24     82           90.2\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4 entries, 0 to 3\n",
+      "Data columns (total 4 columns):\n",
+      " #   Column         Non-Null Count  Dtype  \n",
+      "---  ------         --------------  -----  \n",
+      " 0   Имя            4 non-null      object \n",
+      " 1   Возраст        4 non-null      int64  \n",
+      " 2   Баллы          4 non-null      int64  \n",
+      " 3   Новый столбец  4 non-null      float64\n",
+      "dtypes: float64(1), int64(2), object(1)\n",
+      "memory usage: 260.0+ bytes\n",
+      "None\n",
+      "         Возраст      Баллы  Новый столбец\n",
+      "count   4.000000   4.000000       4.000000\n",
+      "mean   22.500000  85.500000      94.050000\n",
+      "std     1.290994   8.266398       9.093038\n",
+      "min    21.000000  76.000000      83.600000\n",
+      "25%    21.750000  80.500000      88.550000\n",
+      "50%    22.500000  85.500000      94.050000\n",
+      "75%    23.250000  90.500000      99.550000\n",
+      "max    24.000000  95.000000     104.500000\n",
+      "Имя              0\n",
+      "Возраст          0\n",
+      "Баллы            0\n",
+      "Новый столбец    0\n",
+      "dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Имя</th>\n",
+       "      <th>Возраст</th>\n",
+       "      <th>Баллы</th>\n",
+       "      <th>Новый столбец</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Анна</td>\n",
+       "      <td>21</td>\n",
+       "      <td>89</td>\n",
+       "      <td>97.9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Борис</td>\n",
+       "      <td>22</td>\n",
+       "      <td>76</td>\n",
+       "      <td>83.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Виктор</td>\n",
+       "      <td>23</td>\n",
+       "      <td>95</td>\n",
+       "      <td>104.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Галина</td>\n",
+       "      <td>24</td>\n",
+       "      <td>82</td>\n",
+       "      <td>90.2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Имя  Возраст  Баллы  Новый столбец\n",
+       "0    Анна       21     89           97.9\n",
+       "1   Борис       22     76           83.6\n",
+       "2  Виктор       23     95          104.5\n",
+       "3  Галина       24     82           90.2"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Создадим DataFrame\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
+    "\n",
+    "print(\"Первый взгляд на данные:\")\n",
+    "print(df.head())\n",
+    "print(df.info())\n",
+    "print(df.describe())\n",
+    "print(df.isnull().sum())\n",
+    "\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "841cffd3-b0f4-4d76-918e-822044d8cda1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первый взгляд на данные:\n",
+      "      Имя  Возраст  Баллы  Новый столбец\n",
+      "0    Анна       21     89           97.9\n",
+      "1   Борис       22     76           83.6\n",
+      "2  Виктор       23     95          104.5\n",
+      "3  Галина       24     82           90.2\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4 entries, 0 to 3\n",
+      "Data columns (total 4 columns):\n",
+      " #   Column         Non-Null Count  Dtype  \n",
+      "---  ------         --------------  -----  \n",
+      " 0   Имя            4 non-null      object \n",
+      " 1   Возраст        4 non-null      int64  \n",
+      " 2   Баллы          4 non-null      int64  \n",
+      " 3   Новый столбец  4 non-null      float64\n",
+      "dtypes: float64(1), int64(2), object(1)\n",
+      "memory usage: 260.0+ bytes\n",
+      "None\n",
+      "         Возраст      Баллы  Новый столбец\n",
+      "count   4.000000   4.000000       4.000000\n",
+      "mean   22.500000  85.500000      94.050000\n",
+      "std     1.290994   8.266398       9.093038\n",
+      "min    21.000000  76.000000      83.600000\n",
+      "25%    21.750000  80.500000      88.550000\n",
+      "50%    22.500000  85.500000      94.050000\n",
+      "75%    23.250000  90.500000      99.550000\n",
+      "max    24.000000  95.000000     104.500000\n",
+      "Имя              0\n",
+      "Возраст          0\n",
+      "Баллы            0\n",
+      "Новый столбец    0\n",
+      "dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr th {\n",
+       "        text-align: left;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead tr:last-of-type th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th colspan=\"4\" halign=\"left\">Баллы</th>\n",
+       "      <th>Возраст</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th></th>\n",
+       "      <th>mean</th>\n",
+       "      <th>sum</th>\n",
+       "      <th>max</th>\n",
+       "      <th>min</th>\n",
+       "      <th>mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Баллы</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>76</th>\n",
+       "      <td>76.0</td>\n",
+       "      <td>76</td>\n",
+       "      <td>76</td>\n",
+       "      <td>76</td>\n",
+       "      <td>22.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>82</th>\n",
+       "      <td>82.0</td>\n",
+       "      <td>82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>82</td>\n",
+       "      <td>24.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>89</th>\n",
+       "      <td>89.0</td>\n",
+       "      <td>89</td>\n",
+       "      <td>89</td>\n",
+       "      <td>89</td>\n",
+       "      <td>21.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>95.0</td>\n",
+       "      <td>95</td>\n",
+       "      <td>95</td>\n",
+       "      <td>95</td>\n",
+       "      <td>23.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Баллы             Возраст\n",
+       "       mean sum max min    mean\n",
+       "Баллы                          \n",
+       "76     76.0  76  76  76    22.0\n",
+       "82     82.0  82  82  82    24.0\n",
+       "89     89.0  89  89  89    21.0\n",
+       "95     95.0  95  95  95    23.0"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Создадим DataFrame\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
+    "\n",
+    "grouped_df = df.groupby(\"Баллы\").agg({\n",
+    "    \"Баллы\": [\"mean\", \"sum\", \"max\", \"min\"],\n",
+    "    \"Возраст\": \"mean\"\n",
+    "})\n",
+    "\n",
+    "print(\"Первый взгляд на данные:\")\n",
+    "print(df.head())\n",
+    "print(df.info())\n",
+    "print(df.describe())\n",
+    "print(df.isnull().sum())\n",
+    "\n",
+    "grouped_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "c7b256e1-c871-4131-bd8d-a0608a18ec28",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Первый взгляд на данные:\n",
+      "      Имя  Возраст  Баллы  Новый столбец\n",
+      "0    Анна       21     89           97.9\n",
+      "1   Борис       22     76           83.6\n",
+      "2  Виктор       23     95          104.5\n",
+      "3  Галина       24     82           90.2\n",
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 4 entries, 0 to 3\n",
+      "Data columns (total 4 columns):\n",
+      " #   Column         Non-Null Count  Dtype  \n",
+      "---  ------         --------------  -----  \n",
+      " 0   Имя            4 non-null      object \n",
+      " 1   Возраст        4 non-null      int64  \n",
+      " 2   Баллы          4 non-null      int64  \n",
+      " 3   Новый столбец  4 non-null      float64\n",
+      "dtypes: float64(1), int64(2), object(1)\n",
+      "memory usage: 260.0+ bytes\n",
+      "None\n",
+      "         Возраст      Баллы  Новый столбец\n",
+      "count   4.000000   4.000000       4.000000\n",
+      "mean   22.500000  85.500000      94.050000\n",
+      "std     1.290994   8.266398       9.093038\n",
+      "min    21.000000  76.000000      83.600000\n",
+      "25%    21.750000  80.500000      88.550000\n",
+      "50%    22.500000  85.500000      94.050000\n",
+      "75%    23.250000  90.500000      99.550000\n",
+      "max    24.000000  95.000000     104.500000\n",
+      "Имя              0\n",
+      "Возраст          0\n",
+      "Баллы            0\n",
+      "Новый столбец    0\n",
+      "dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Имя</th>\n",
+       "      <th>Возраст</th>\n",
+       "      <th>Баллы</th>\n",
+       "      <th>Новый столбец</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Анна</td>\n",
+       "      <td>21</td>\n",
+       "      <td>89</td>\n",
+       "      <td>97.9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Борис</td>\n",
+       "      <td>22</td>\n",
+       "      <td>76</td>\n",
+       "      <td>83.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Виктор</td>\n",
+       "      <td>23</td>\n",
+       "      <td>95</td>\n",
+       "      <td>104.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Галина</td>\n",
+       "      <td>24</td>\n",
+       "      <td>82</td>\n",
+       "      <td>90.2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Имя  Возраст  Баллы  Новый столбец\n",
+       "0    Анна       21     89           97.9\n",
+       "1   Борис       22     76           83.6\n",
+       "2  Виктор       23     95          104.5\n",
+       "3  Галина       24     82           90.2"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Создадим DataFrame\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "df[\"Новый столбец\"] = df[\"Баллы\"] * 1.1\n",
+    "df[df[\"Возраст\"] > 21]\n",
+    "\n",
+    "print(\"Первый взгляд на данные:\")\n",
+    "print(df.head())\n",
+    "print(df.info())\n",
+    "print(df.describe())\n",
+    "print(df.isnull().sum())\n",
+    "\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fabc986b-9e8a-4fad-82cf-7e0d22e2d485",
+   "metadata": {},
+   "source": [
+    "Часть 3 - часть 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "5a137f99-a29a-4c32-8727-8fe71e93f82f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Сумма элементов массива: 15\n",
+      "Среднее значение: 3.0\n",
+      "Медиана: 3.0\n",
+      "Стандартное отклонение: 1.4142135623730951\n"
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "arr = np.array([1, 2, 3, 4, 5])\n",
+    "print(\"Сумма элементов массива:\", np.sum(arr))\n",
+    "print(\"Среднее значение:\", np.mean(arr))\n",
+    "print(\"Медиана:\", np.median(arr))\n",
+    "print(\"Стандартное отклонение:\", np.std(arr))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "0bff7510-f22b-4335-9596-1ff30cb0f806",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Сумма элементов массива: 15\n",
+      "Среднее значение: 3.0\n",
+      "Медиана: 3.0\n",
+      "Стандартное отклонение: 1.4142135623730951\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([3.        , 3.02040816, 3.04081633, 3.06122449, 3.08163265,\n",
+       "       3.10204082, 3.12244898, 3.14285714, 3.16326531, 3.18367347,\n",
+       "       3.20408163, 3.2244898 , 3.24489796, 3.26530612, 3.28571429,\n",
+       "       3.30612245, 3.32653061, 3.34693878, 3.36734694, 3.3877551 ,\n",
+       "       3.40816327, 3.42857143, 3.44897959, 3.46938776, 3.48979592,\n",
+       "       3.51020408, 3.53061224, 3.55102041, 3.57142857, 3.59183673,\n",
+       "       3.6122449 , 3.63265306, 3.65306122, 3.67346939, 3.69387755,\n",
+       "       3.71428571, 3.73469388, 3.75510204, 3.7755102 , 3.79591837,\n",
+       "       3.81632653, 3.83673469, 3.85714286, 3.87755102, 3.89795918,\n",
+       "       3.91836735, 3.93877551, 3.95918367, 3.97959184, 4.        ])"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "arr = np.array([1, 2, 3, 4, 5])\n",
+    "print(\"Сумма элементов массива:\", np.sum(arr))\n",
+    "print(\"Среднее значение:\", np.mean(arr))\n",
+    "print(\"Медиана:\", np.median(arr))\n",
+    "print(\"Стандартное отклонение:\", np.std(arr))\n",
+    "\n",
+    "arr2 = np.array([[1, 2], [3, 4]])\n",
+    "np.linspace(3, 4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "01af748b-1dee-483d-be1d-39d9d39e2daf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Сумма элементов массива: 15\n",
+      "Среднее значение: 3.0\n",
+      "Медиана: 3.0\n",
+      "Стандартное отклонение: 1.4142135623730951\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "1.063095687089255"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "arr = np.array([1, 2, 3, 4, 5])\n",
+    "print(\"Сумма элементов массива:\", np.sum(arr))\n",
+    "print(\"Среднее значение:\", np.mean(arr))\n",
+    "print(\"Медиана:\", np.median(arr))\n",
+    "print(\"Стандартное отклонение:\", np.std(arr))\n",
+    "\n",
+    "arr2 = np.array([[1, 2], [3, 4]])\n",
+    "np.random.randn()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "6120edc2-d49b-42a8-bf34-606f0b465c63",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Сумма элементов массива: 15\n",
+      "Среднее значение: 3.0\n",
+      "Медиана: 3.0\n",
+      "Стандартное отклонение: 1.4142135623730951\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "np.int64(11)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "arr = np.array([1, 2, 3, 4, 5])\n",
+    "print(\"Сумма элементов массива:\", np.sum(arr))\n",
+    "print(\"Среднее значение:\", np.mean(arr))\n",
+    "print(\"Медиана:\", np.median(arr))\n",
+    "print(\"Стандартное отклонение:\", np.std(arr))\n",
+    "\n",
+    "arr2 = np.array([[1, 2], [3, 4]])\n",
+    "np.dot(arr2[0], arr2[1])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "39a7b707-93dd-4586-958f-b4bfa5e23d9c",
+   "metadata": {},
+   "source": [
+    "Matplot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "03295aee-25dd-48b0-a88e-2182a1213171",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.plot(x, y, label='sin(x)')\n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"График синуса\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "264e7d30-72b9-4b2f-8d49-79df44406e84",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.plot(x, y, label='sin(x)', color='red')\n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"График синуса\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "f8a4b3e5-6281-4d26-9021-3336319097dd",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.plot(x, np.sin(x), label='sin(x)', color='red')\n",
+    "plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"Мультиграфик\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "cbf8dfa9-b3f4-4c09-a268-712f18d62733",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.bar(x, np.sin(x), label='sin(x)', color='red')\n",
+    "#plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"Мультиграфик\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "b80643f9-dba3-45d2-a3ba-d13579fda896",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.scatter(x, np.sin(x), label='sin(x)', color='red')\n",
+    "#plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"Мультиграфик\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "bd42a32b-4bfd-4acc-9974-1b8bd4c55dcc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjIAAAHHCAYAAACle7JuAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAAN9xJREFUeJzt3Ql0FFXa//EngZB0kLBFJWgQ3BAFQxx3nQwIiAyiDO5BRfDghiiiqKhIUFxQx0EFARkR33cEXAbQd0QEF4wOiKxxwwgOiiioQQ1LQghJ/c9zh84/nbW70+mu2/39nNPGVKqq71PV3fXj1q3qOMdxHAEAALBQfKQbAAAAECyCDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGiAKzZ8+WuLg48/joo4+q/V2/iSQ9Pd38/fzzz49IG2PB6tWrzTbW/QEgPAgyQBRJSkqSOXPmVJv+wQcfyNatWyUxMTEi7QKAxkKQAaLIn//8Z3n11Vdl//79PtM13PzhD3+Qdu3aRaxtANAYCDJAFLniiitkx44dsnTp0opp+/btk9dee02ys7N9TjV17NhRLrzwwmrr2Lt3r7Rs2VKuv/56n+nXXHNNxemryo+cnByfeQ466KA626jPW9N6vA/9u/r2229rPE0zYsQIM12fq6ZTa1Uf2hNVuW3/+c9/pG/fvtK8eXNp3769PPDAA2Z7VPbEE0/ImWeeKW3bthWPx2NCoG7DqgoKCsw21HlOPfVU2bx5s5m+c+dOGTBggJl+9tlnyzfffFNtG1Ruv9IAWrn+2rbBrl27THs6deok27Ztq3NbA7GgaaQbACB09CB4xhlnyNy5c6Vfv35m2ltvvSWFhYVy+eWXy9NPP22m6cHxyiuvlMcee0x+/fVXadOmTcU6/u///s8ciPXvVaWmpsrf/va3it+vuuqqgNs4efJk2b17t/n/DRs2yMMPPyz33HOPdOnSxUyrKwht2rRJZs6cWevfNZToAb6yyrWVlZXJeeedJ6effrqpffHixTJ+/HjTg6XLej311FNywQUXyODBg00QnDdvnlxyySXyr3/9S/r3718xn/5dT9vdcccd0qRJExk1apSZPnHiRDO/rlufR0PN559/LvHxNf/bUZ//3nvvrXfblZaWykUXXSRbtmyRf//735KWllbvMkDUcwBY74UXXtAuBWfVqlXOlClTnBYtWjhFRUXmb5dcconTs2dP8/9HHHGE079/f/P/+fn5Zplp06b5rOuCCy5wOnbs6JSXl/tMHzx4sNOpUyefabr8+PHjK34fMmSI07x5c7/b/f7775t16M+qNm/ebP6mtXldeumlTteuXZ309HTzXDXVXxudX+cZOXJkxTStUbdHs2bNnF9++aViunfbee3bt8887znnnFMxbe3atWZ9M2bMqJim216n3XjjjRXT3n77bTNtwYIFFdN0P1Ru/7PPPuskJiaa/aR/q2kbaFt1HyQnJzsrV66stU4g1nBqCYgyl156qRQXF5veAz0NoT8rn1byOvbYY+W0006Tl156qWKa9s5oD472NGivTWXaM+HvYGE95aIPPU0VKmvWrDGnXx555JFaezb8cfPNN1f8v9aov2tt77zzTsV0PSXk9dtvv5kerT/+8Y+ydu3aiunvvvuu+Tlo0KCKabo9lZ5m8urTp4/pZfLOX1VRUZHpDdJ2dOjQodZ2jxkzxuyrV155xWf9QKwjyABR5uCDD5bevXubAb7z5883p1MuvvjiGue9+uqrzSmK7777zvyuQUFPX9R0yuj333+vd/yL2rNnj2mDPjQQ6MFZT9U01N13323CREMuH9cAdOSRR1YLdN7xKF4a/vT0k14FpqemtJZp06aZQOP1/fffS7NmzczptrpoWNKxODp/TZ588kkT+PT0Wm1mzJghf/3rXyuCFYD/jyADRCHtgdGelenTp5uxMq1atapxPh03k5CQUNEr849//ENOPvlk6dy5c7V5t2/f7tdVT3rw18HG+tAglZGRYcaOaE9CsJYsWWJ6TCZNmiSN7cMPPzTjY7SOZ599VhYtWmRq0W1aeVBwoL1N2ktWlfZaPf7443LXXXf5jOWp6uOPP5aHHnpIBg4cKLfddptZDsB/EWSAKPSXv/zF9D7oAbCm00peevDUwasaZLRXRntnauqN0V4aHWjrHZBbFx30qj1C+tB2/POf/zRXCOnA2mBoeNDeGF2X9pI0RHl5ublqqbKvv/7a/PReLaTt1RDz9ttvy7Bhw0wQ1Fqq0oG2ekpKrxKrr/16dZH2ylSlg4JbtGght956a53r0HZoj83UqVPNvtAwA+C/CDJAFNJTQHoqRC+N1itm6qLB5csvvzRjMDSEaC9NVa+//rrpUTjnnHMCbou3F0PXHQy9YujTTz81Y2NCYcqUKT5t09+1V6pXr14V7dTTQXpKzktPOy1cuNBnPVlZWebnggULKqatXLnS/Pzkk08qpunYGB2r5J2/8jq9+6jymJya6Ck1pWFIe6W050x7qQBw+TUQtYYMGeLXfNojo/dL0fEx2vtwyCGH+AxE1UuI9RSL3lfl3HPPrXd9GgC8vS96AH/hhRfMuBk9LRIMPWAPHz68xtNdgdKeFm2bbhsdmKun3958803T26HjYLzbQ8et6GXa2pv1888/m56Qo48+2gQqr549e5pL3UeOHGl6szQA/f3vf6/o1dEeMf1aCL38Wi8JrxoQ9bJt7eEaOnRoQDVcd911ZvzTDTfcYC7pTk5ObvB2AWxGjwwQ43TA6mWXXWb+v+ppJR1Y+vLLL5uDpx70/blaSMeOaCDSh54S+emnn+R///d/fe6/Egjtrah8072G0LChQUbH+2gP1KpVq0xQe/DBByvm0V6n559/3syjY3v0njzaC6KntirTXhvtjdGeHL2Bno6l0XvkKL0njIYbbbcOJtZtV1Ovi95DJ9CeKn1evZeOnq667777gt4WQLSI02uwI90IAJGlYy68B+9o/Re+3klX787rvRlfY31p5CmnnGJ6oareuRdA46BHBohx2oOiYy70jrHRGmIARC/GyAAxSsd+6CXN2kuhV97Ud+UMALgRQQaIUXqlkt7BVwf36ncwde/ePdJNAoCAMUYGAABYizEyAADAWgQZAABgragfI6O3JP/xxx/NbcCrfpsvAABwJx35ojfV1Dta13UPq6gPMhpi9O6aAADAPvrN8YcffnjsBhntifFuiJSUlJCtV7+4TW+drrds1+9piUbRXiP12S/aa4z2+mKhRuoL3s6dO01HhPc4HrNBxns6SUNMqIOM3jxM1xmNL85YqJH67BftNUZ7fbFQI/U1XH3DQhjsCwAArEWQAQAA1iLIAAAAa0X9GBl/lZWVmXN9/tJ5mzZtar5wT5eNRg2tUc+XNmnSpFHaBgCAivkgo9epb9++XX7//feAl2vXrp25Gipa708TihpbtWpl1hGt2wgAEFkxH2S8IUa/OE9HXvt7wNUb7e3evVsOOuigOm/UY7OG1KghqKioyHzDskpLS2ukVgIAYllMBxk9XeINMW3btg34IL9v3z5JSkqK6iDTkBo9Ho/5qWFGtzGnmQAAoRadR2A/ecfEaE8MGod32wYy/ggAAH/FdJDxYvxG42HbAgAaE0EGAABYK6bHyNRmy5YtUlBQUO/4kT179kjz5s0bPEYmNTVVOnToIKFwzTXXmHE/CxcuDGi5d999V26++Wb5/PPP/RrL8uWXX5rv1sjPzzfbAACASCDI1BBiunTuLEV794btOZOTkmRDfn5IwsxTTz1lrhgK1J133in33Xef3wNyjz/+eDn99NPlySeflHHjxgXRUgAAGo4gU4X2xGiI+YeIdAnD820QkSv37jXPG4og07Jly4CX+eijj+Sbb76Riy66KKDlhg4dKsOHD5exY8eaG+cBABBuHH1qoSHmJHGv1157TSZMmCCbNm0yVwZlZmbK66+/LiNGjPA5tdSjRw858cQTzSXUf//736VZs2Zyww03SE5OTsW65s2bJ3369DHzKO3R0d/1lNnLL79spv36669mPcOGDZMHHnjATNN5dPoHH3wgvXr1ish2AADENoKMhbZt2yZXXHGFPPbYY/KXv/xFdu3aJR9++GGtp5RefPFFGT16tKxcuVJWrFhhxtGcddZZJogoXTY7O9vnSiNdplu3bjJjxgxz2knDz2GHHSb3339/xXwairp3726WJ8gAQHSPDa1tvGikEWQsDTL79++XQYMGyRFHHGGmaeiojfakjB8/3vz/McccI1OmTDGDe71B5rvvvpP27dv7LKOhZdq0aRWDhxctWiTr1q2rdgpJl9PlAQCxNzbU4/HI3LlzZevWrdKpUyeJBIKMhTIyMkwPiIaXvn37mquHLr74YmndunWtQaYy/boA71cHqOLi4orTSpVdcskl8uqrr8qkSZNMqNEQVNOLWL+KAAAQe2NDNxz4uWPHDoIM/KdXFi1dulSWL18uS5YskWeeeUbuvfdec+qotm+hrkxPHVXuDtTLv3/77bdqy2lAycvLM8+3cePGGtetY2SOOuqoBtcEALBvbGi5iPwgkcUN8SylYUTHueiAXz3lo+NVFixYENS6dKCw3hemqjvuuMMM+H3zzTfl6aeflvfee6/aPHrfGV0eAIBIIMhYSHteHn74YVm9erU5tzl//nz55ZdfpEuX4C4Y19NTegl2ZRpeXnjhBXnuuefMWJoxY8bIkCFDfHpuvv32W/nhhx+kd+/eDa4JAIBgcGqpnvN+bnyelJQUyc3NlcmTJ8vOnTvNgN+//vWv0q9fv4rLpQMxePBgc2WS3qW3c+fOJhRde+21ZoCwjsdR2vOjp7H06iXvc+gALx2f4x1wDABAuBFkqtDxInqnXb1JXbjo8+nz+kt7XhYvXlzj32bPnu3z+7Jly6rNU/XrC9q0aWO+nkDv0quXWx988MGyfft2M45Gg5J3nI32AHnt27dPpk+fLnPmzPG73QAAhBpBpgq9u65+XYCt37UULB0s/Oyzz5q6/KlHT2ndc889ZpwOAACRQpCpgYaK+oKFt7dCT/M0NMi4QatWrUww8dfRRx9tHgAARJL9R2AAABCzCDIAAMBaBJkDX5KIxsG2BQA0ppgOMt473nKL/cbj3bZV7y4MAEAoxPRgX731vg5y9X7vUHJysrljrj90sK9egrx3796oGOwb6hq1J0ZDjG5b3ca6rQEACLWYDjKqXbt25mflL1H090CtX7aoX5rob/ixTShq1BDj3cYAAIRazAcZPUDrt0EfcsghUlpa6vdyOq/eXTcrKytqT5s0tEZdhp4YAEBjivkg46UH3EAOujrv/v37JSkpKWqDTCzUCACwW3QO7gAAADGBIAMAAKwV0SCj4y8GDBgg7du3N2NVqn6ZYWX6rcs6j37jMwAAQMSDjH7pYkZGhkydOrXO+RYsWCAff/yxCTwAAACuGOzbr18/86jLDz/8ICNHjpS3335b+vfvH7a2AQAA92vq9huyXXXVVTJmzBg54YQT/FqmpKTEPLz0G6q9lxIHcnl1fbzrCuU63Sbaa6Q++0V7jdFeXyzUaEN95eXl5n5h5drOQJf1eCrWEeoa/V1fnOOSL8PR8S96CmngwIEV0x555BF5//33TW+M/r1jx44yatQo86hNTk6OTJgwodr0OXPmmDv3AgAA99O7w2dnZ0thYaGkpKTY1yOzZs0aeeqpp2Tt2rUB3VV27NixMnr0aJ8emfT0dDn33HPr3BDBJMWlS5dKnz59ovYeK9FeI/XZL9prjPb6YqFGG+rLy8szNz7NFZGMAJdd5/HItlmzzI1lMzMzQ9ou7xmV+rg2yHz44YfmawM6dOhQMa2srExuv/12c+XSt99+W+NyiYmJ5lGVvoAa40XUWOt1k2ivkfrsF+01Rnt9sVCjm+uLj483X0ejV/8kBHnFkK4j1PX5uz7XBhkdG9O7d2+faX379jXThw4dGrF2AQAA94hokNm9e7ds2rSp4vfNmzfL+vXrpU2bNqYnpm3bttXSmX4BYefOnSPQWgAA4DYRDTKrV6+Wnj17VvzuHdsyZMgQmT17dgRbBgAAbBDRINOjRw8J5KKp2sbFAACA2MR3LQEAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACsRZABAADWIsgAAABrEWQAAIC1CDIAAMBaBBkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgrYgGmdzcXBkwYIC0b99e4uLiZOHChRV/Ky0tlbvuuku6desmzZs3N/NcffXV8uOPP0ayyQAAwEUiGmT27NkjGRkZMnXq1Gp/KyoqkrVr18q4cePMz/nz50t+fr5ccMEFEWkrAABwn6aRfPJ+/fqZR01atmwpS5cu9Zk2ZcoUOfXUU2XLli3SoUOHMLUSAAC4VUSDTKAKCwvNKahWrVrVOk9JSYl5eO3cubPiVJU+QsW7rlCu022ivUbqs1+01xjt9cVCjTbUV15eLh6PR8q1nYEu6/FUrCPUNfq7vjjHcRxxAQ0oCxYskIEDB9b4971798pZZ50lxx13nLz00ku1ricnJ0cmTJhQbfqcOXMkOTk5pG0GAACNQ4eYZGdnm06MlJQUu4OMprKLLrpItm7dKsuWLauzoJp6ZNLT06WgoKDO5QKlbdJTX3369JGEhASJRtFeI/XZL9prjPb6YqFGG+rLy8uTrKwsyRWRjACXXefxyLZZsyQtLU0yMzND2i49fqemptYbZJra8CK49NJL5bvvvpP33nuv3jCSmJhoHlXpC6gxXkSNtV43ifYaqc9+0V5jtNcXCzW6ub74+HgpLi42V/8kBHnFkK4j1PX5u76mNoSYjRs3yvvvvy9t27aNdJMAAICLRDTI7N69WzZt2lTx++bNm2X9+vXSpk0b00118cUXm0uv//Wvf0lZWZls377dzKd/b9asWQRbDgAAJNaDzOrVq6Vnz54Vv48ePdr8HDJkiBm0+8Ybb5jfu3fv7rOc9s706NEjzK0FAABuE9Ego2GkrrHGLhmHDAAAXIrvWgIAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACsRZABAADWIsgAAABrEWQAAIC1CDIAAMBaBBkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWhENMrm5uTJgwABp3769xMXFycKFC33+7jiO3H///ZKWliYej0d69+4tGzdujFh7AQCAu0Q0yOzZs0cyMjJk6tSpNf79sccek6efflqmT58uK1eulObNm0vfvn1l7969YW8rAABwn6aRfPJ+/fqZR020N2by5Mly3333yYUXXmim/c///I8ceuihpufm8ssvD3NrAQCA20Q0yNRl8+bNsn37dnM6yatly5Zy2mmnyYoVK2oNMiUlJebhtXPnTvOztLTUPELFu65QrtNtor1G6rNftNcY7fXFQo021FdeXm6Gb5RrOwNd1uOpWEeoa/R3fXGOdn24gI6RWbBggQwcOND8vnz5cjnrrLPkxx9/NGNkvC699FIz78svv1zjenJycmTChAnVps+ZM0eSk5MbsQIAABAqRUVFkp2dLYWFhZKSkmJfj0ywxo4dK6NHj/bpkUlPT5dzzz23zg0RTFJcunSp9OnTRxISEiQaRXuN1Ge/aK8x2uuLhRptqC8vL0+ysrIkV0QyAlx2nccj22bNMh0OmZmZIW2X94xKfVwbZNq1a2d+/vTTTz49Mvp79+7da10uMTHRPKrSF1BjvIgaa71uEu01Up/9or3GaK8vFmp0c33x8fFSXFxsrv5JCPKKIV1HqOvzd32uvY9Mp06dTJh59913fdKZXr10xhlnRLRtAADAHSLaI7N7927ZtGmTzwDf9evXS5s2baRDhw4yatQomThxohxzzDEm2IwbN87cc8Y7jgYAAMS2iAaZ1atXS8+ePSt+945tGTJkiMyePVvuvPNOc6+Z6667Tn7//Xc5++yzZfHixZKUlBTBVgMAALeIaJDp0aOHuV9MbfTqpAceeMA8AAAArBkjAwAAUB+CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACsRZABAADWIsgAAABrEWQAAIC1CDIAAMBaBBkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACs5eogU1ZWJuPGjZNOnTqJx+ORo446Sh588EFxHCfSTQMAAC7QVFxs0qRJMm3aNHnxxRflhBNOkNWrV8vQoUOlZcuWcsstt0S6eQAAwJYg8+OPP0r79u0lnJYvXy4XXnih9O/f3/zesWNHmTt3rnzyySdhbQcAALA8yGiPyNSpUyU7O1vC5cwzz5TnnntOvv76azn22GMlLy9PPvroI3nyySdrXaakpMQ8vHbu3Gl+lpaWmkeoeNcVynW6TbTXSH32i/Yao72+WKjRhvrKy8vN8I1ybWegy3o8FesIdY3+ri/O8XPAybPPPit33XWXnHfeeTJjxgxp06aNNDbdMPfcc4889thj0qRJEzNm5qGHHpKxY8fWukxOTo5MmDCh2vQ5c+ZIcnJyI7cYAACEQlFRkek8KSwslJSUlIYHGbV582a59tpr5csvv5SZM2fKgAEDpDHNmzdPxowZI48//rjpEVq/fr2MGjXK9MgMGTLE7x6Z9PR0KSgoqHNDBJMUly5dKn369JGEhASJRtFeI/XZL9prjPb6YqFGG+rLy8uTrKwsyRWRjACXXefxyLZZsyQtLU0yMzND2i49fqemptYbZAIa7KtXD7333nsyZcoUGTRokHTp0kWaNvVdxdq1ayVUNMTcfffdcvnll5vfu3XrJt9995088sgjtQaZxMRE86hKX0CN8SJqrPW6SbTXSH32i/Yao72+WKjRzfXFx8dLcXGxuYw5IchLn3Udoa7P3/UFfNWSBon58+dL69atzUDcqkEm1N1KunEq01NMesoJAAAgoBSip5Nuv/126d27t3zxxRdy8MEHN17LRMypKx0T06FDB3Nqad26dea00rBhwxr1eQEAQJQFGR3kq5c962mlq6++WsLhmWeeMTfEu+mmm+Tnn382l39ff/31cv/994fl+QEAQJQEGb1i6NNPP5XDDz9cwqVFixYyefJk8wAAAAg6yOioawAAADdx9XctAQAA1IUgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACsRZABAADWIsgAAABrEWQAAIC1CDIAAMBaTSPdANvl5eVJfHzgeTA1NVU6dOjQKG0CACBWEGSCtHXrVvMzKytLiouLA14+OSlJNuTnE2YAAGgAgkyQduzYYX7OFJEuAS67QUSu3LtXCgoKCDIAADQAQaaBOovISZFuBAAAMYrBvgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACsRZABAADWIsgAAABrEWQAAIC1CDIAAMBarg8yP/zwg1x55ZXStm1b8Xg80q1bN1m9enWkmwUAAFygqbjYb7/9JmeddZb07NlT3nrrLTn44INl48aN0rp160g3DQAAuICrg8ykSZMkPT1dXnjhhYppnTp1imibAACAe7g6yLzxxhvSt29fueSSS+SDDz6Qww47TG666SYZPnx4rcuUlJSYh9fOnTvNz9LSUvMIlfLy8v/+9Hgk0LXqkp4D6whlm0LN2zY3t7EhqM9+0V5jtNcXCzXaUF95ebkZuqHHpoCPZx49mjXO8czf9cU5juOISyUlJZmfo0ePNmFm1apVcuutt8r06dNlyJAhNS6Tk5MjEyZMqDZ9zpw5kpyc3OhtBgAADVdUVCTZ2dlSWFgoKSkpdgaZZs2aycknnyzLly+vmHbLLbeYQLNixQq/e2T09FRBQUGdGyJQ69atk23btknasGGSWVwc0LJ5IpIlIrm5uZKRkSFupWl46dKl0qdPH0lISJBoQ332i/Yao72+WKjRhvry8vIkKytLckUk0CPSOo9Hts2aJWlpaZKZmRnSdunxOzU1td4g4+pTS7phjj/+eJ9pXbp0kX/+85+1LpOYmGgeVekLKJQvovj4/17wFV9cLAkBBhldsvjAOtz6wm7Mbec21Ge/aK8x2uuLhRrdXF98fLwUFxebY1NCkJc+N8bxzN/1ufrya71iKT8/32fa119/LUcccUTE2gQAANzD1UHmtttuk48//lgefvhh2bRpkxnn8txzz8mIESMi3TQAAOACrg4yp5xyiixYsEDmzp0rXbt2lQcffFAmT54sgwcPjnTTAACAC7h6jIw6//zzzQMAAMCqHhkAAIC6EGQAAIC1CDIAAMBaBBkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArNU00g0AAAD/tWXLFikoKAhq2ZKSEklMTAx4uQ0bNojNCDIAALgkxHTp3FmK9u4NavkmIlImsYcgAwCAC2hPjIaYf4hIlwCXXSQi40QatKytCDIAALiIBpGTAlxmQwiWtRWDfQEAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACsRZABAADWIsgAAABrEWQAAIC1rAoyjz76qMTFxcmoUaMi3RQAAOAC1gSZVatWyYwZM+TEE0+MdFMAAIBLWBFkdu/eLYMHD5aZM2dK69atI90cAADgEk3FAiNGjJD+/ftL7969ZeLEiXXOW1JSYh5eO3fuND9LS0vNI1TKy8v/+9PjkUDXqkt6DqwjlG0KNW/b3NzGhqA++zW0xq1bt8qOHTuCWrZt27Zy+OGHS7jrc3ubQ70PI1VvQ55Xj0GJiYk+x4p169ZJfHzdfQf5+fni8XjMMSKYV7TnwPElnMvqMVAa6Xjm7/riHMdxxMXmzZsnDz30kDm1lJSUJD169JDu3bvL5MmTa5w/JydHJkyYUG36nDlzJDk5OQwtBgAADVVUVCTZ2dlSWFgoKSkpdgaZ77//Xk4++WRZunRpxdiY+oJMTT0y6enpUlBQUOeGCJSm623btknasGGSWVwc0LJ5IpIlIrm5uZKRkSFupWlYt32fPn0kISFBog31xXaNeXl5kpWVJTNFpHOAz5svIsPD8B6uWp8NbQ7lPoxUvQ153iUioucNvMtqj8W2WbPMsSK+nmOFd9lcEQl0D73irTfMy67z1peWJpmZmRJKevxOTU2tN8i4+tTSmjVr5Oeff5aTTjqpYlpZWZl5YU6ZMsUEliZNmvgso9153i69yvQNEsoPc28Xob4wEwIMMrpk8YF12HCACfW2cxvqi80a9f1XXFwsXUTk/3/CuPM97K3PpjaHYh9Gqt6GPG/+gef1LqsnR7aJmH/w1nes8C6rbQ9mDxVHYFnvybLGeF35uz5XB5levXrJZ5995jNt6NChctxxx8ldd91VLcQAAIDY4uog06JFC+natavPtObNm5sBXFWnAwCA2GPF5dcAAADW9cjUZNmyZZFuAgAAcAl6ZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACsRZABAADWahrpBsSyDRs2BL1sSUmJJCYmBrVsamqqdOjQQWyyZcsWKSgoCGpZ6g0PG9scKf5uq/LycvMzLy9P4uPjG/SZEcn9W9fnVdUaKwtFvcGsI5LbGYEjyETAtgNdYVdeeWXQ62giImVBLpuclCQb8vOtOXDoB2iXzp2laO/eoJaP1XrT0tIkXGJtH4VrW3k8Hpk7d65kZWVJcXGxREpD929dn1eNVWMoPmdhB4JMBPyu/woRkX+ISJcgll8kIuOCXF7/nXHl3r3mX1a2HDS0rfoBSr2B1RvOIBNr+yhc20o/J34QkdwDB2Xvez/cGrJ/6/u8qlpjTcuG+3M2UtsZwSHIRJC+uU4KYrkNDVzeVtTrfja22c3bqvTAQT5DRBIqvfdt2r/1fV5VrbGmZSPVZtiBwb4AAMBaBBkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtVwdZB555BE55ZRTpEWLFnLIIYfIwIEDJT8/P9LNAgAALuHqIPPBBx/IiBEj5OOPP5alS5dKaWmpnHvuubJnz55INw0AALhAU3GxxYsX+/w+e/Zs0zOzZs0aycrKili7AACAO7i6R6aqwsJC87NNmzaRbgoAAHABV/fIVFZeXi6jRo2Ss846S7p27VrrfCUlJebhtXPnTvNTT0vpI5TtMT89HglmrR5dVtsV5PMHu3z5gWU3bNhQUUOt8x74+7p16yQ+/r+Zt23btnL44YcH1eatW7fKjh07Al5Ox0V5PJ6Q11tTfVXpaykxMTHgNjdk2VDUq7V5X++BvO7dto/qXdaPfRiu7ez3suXlfj9vqcfj8zNc7/1Qbqv62lxTjf4u25DnDdey9dXXWM8bqKBfVwfqCua9UB9/1xfnOI4jFrjxxhvlrbfeko8++qjOA2lOTo5MmDCh2vQ5c+ZIcnJyI7cSAACEQlFRkWRnZ5uzMSkpKXYHmZtvvllef/11yc3NlU6dOtU5b009Munp6VJQUFDnhgiU/gtw27ZtkjZsmGQWFwe07CsiMlxEckUkI4jnbsjy3mVnikhnP5L2tlmzTI3xxcWS733e3FzJyAjsmfPy8sy4Jn+et6olIjKxEeqtWl9tz9uQNoe73jwRyTqwj44//ngzSL5Pnz6SkJBg5T6qzzsej3SZNUt2DxsmnQN8H4ZqOwf7XvDnefVf8UtnzZI+w4ZJQnFx2N77jbF/a1u2ao2BLNuQ5w3XsnXV59Y2B2Kd93M0LU0yMzMllPT4nZqaWm+QcfWpJc1YI0eOlAULFsiyZcvqDTFKu/Jr6s7XD3J/Psz95e3G1gNgfS/OmugSuoZgW9SQ5XXZLiJyUj3zaafeNhET1LTGeO/zxscHvC11meLiYr+et6r8Rqq3an21PW9D2hzuemvaR/6+9t24j/x5XqUh5uQA34eh3s5+L3tgOwfyvAmVXqOR2s4Nfd76lq1cY6DLNuR5w7VsbfU19vP6qyHvBQnyvVAff9fn6iCjl17rKSHtjdF7yWzfvt1Mb9mypTlfCwAAYpurr1qaNm2a6VLq0aOH6bbyPl5++eVINw0AALiAq3tkLBi+AwAAIsjVPTIAAAB1IcgAAABrEWQAAIC1CDIAAMBaBBkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAArNU00g2AfTZs2BCWZRA83d7l5eXm//Py8iQ+vv5/s7CPAsd7AYg8ggz8tu1AF96VV14Z6abAj33k8Xhk7ty5kpWVJcXFxZFuWlThvQC4B0EGfvtdRPTf+P8QkS4BLrtIRMY1UrtQ8z7qLCI/iEiun+eQ2Uf+470AuAdBBgHTD+6TAlyGzvTw76NuB4JMhogk+LEM+yhwvBeAyGOwLwAAsBZBBgAAWIsgAwAArEWQAQAA1iLIAAAAaxFkAACAtQgyAADAWgQZAABgLYIMAACwFkEGAABYiyADAACsRZABAADWIsgAAABrEWQAAIC1CDIAAMBaBBkAAGAtK4LM1KlTpWPHjpKUlCSnnXaafPLJJ5FuEgAAcAHXB5mXX35ZRo8eLePHj5e1a9dKRkaG9O3bV37++edINw0AAESY64PMk08+KcOHD5ehQ4fK8ccfL9OnT5fk5GSZNWtWpJsGAAAizNVBZt++fbJmzRrp3bt3xbT4+Hjz+4oVKyLaNgAAEHlNxcUKCgqkrKxMDj30UJ/p+vtXX31V4zIlJSXm4VVYWGh+/vrrr1JaWhqytu3cuVOKiopkXVKS7HacgJbNF5EkEVmj6wniuRuyfCDLliclmRo/TEqSeMcJ2/OGa9mq9dnQ5kCW/b2e+tzY5kCX3ZiUJJ0j8D7kPRi6Zet6H7q1zYEsW9/njBvbHOh78KCiInNM3LFjh4TSrl27zE+nvve242I//PCDtt5Zvny5z/QxY8Y4p556ao3LjB8/3izDgwcPHjx48BDrH99//32dWcHVPTKpqanSpEkT+emnn3ym6+/t2rWrcZmxY8eawcFe5eXlpjembdu2EhcXF7K2afpMT0+X77//XlJSUiQaRXuN1Ge/aK8x2uuLhRqpL3jaE6O9Mu3bt69zPlcHmWbNmskf/vAHeffdd2XgwIEVwUR/v/nmm2tcJjEx0Twqa9WqVaO1UXdcNL44Y6lG6rNftNcY7fXFQo3UF5yWLVvWO4+rg4zS3pUhQ4bIySefLKeeeqpMnjxZ9uzZY65iAgAAsc31Qeayyy6TX375Re6//37Zvn27dO/eXRYvXlxtADAAAIg9rg8ySk8j1XYqKVL09JXepK/qaaxoEu01Up/9or3GaK8vFmqkvsYXpyN+I/bsAAAA0XpDPAAAgLoQZAAAgLUIMgAAwFoEGQAAYC2CTB0eeughOfPMM823bft7Uz0dO62XiqelpYnH4zFfcLlx40afefROw4MHDzY3D9L1XnvttbJ7924Jt0Db8e2335q7I9f0ePXVVyvmq+nv8+bNk3ALZjv36NGjWttvuOEGn3m2bNki/fv3N6+LQw45RMaMGSP79++XSAi0Rp1/5MiR0rlzZ/P67NChg9xyyy0V30kW6X04depU6dixoyQlJclpp50mn3zySZ3z6+vuuOOOM/N369ZNFi1aFPD7MdwCqXHmzJnyxz/+UVq3bm0e2v6q819zzTXV9tV5550nNtQ3e/bsam3X5aJpH9b0maIP/Qxx4z7Mzc2VAQMGmLvpajsWLlxY7zLLli2Tk046yVy5dPTRR5v92tD3dkBC+d1I0eb+++93nnzySWf06NFOy5Yt/Vrm0UcfNfMuXLjQycvLcy644AKnU6dOTnFxccU85513npORkeF8/PHHzocffugcffTRzhVXXOGEW6Dt2L9/v7Nt2zafx4QJE5yDDjrI2bVrV8V8+rJ64YUXfOarXH+4BLOd//SnPznDhw/3aXthYaHPNujatavTu3dvZ926dc6iRYuc1NRUZ+zYsU4kBFrjZ5995gwaNMh54403nE2bNjnvvvuuc8wxxzgXXXSRz3yR2Ifz5s1zmjVr5syaNcv54osvzH5o1aqV89NPP9U4/7///W+nSZMmzmOPPeZ8+eWXzn333eckJCSYGgN5P4ZToDVmZ2c7U6dONa+1DRs2ONdcc42pZ+vWrRXzDBkyxLwOKu+rX3/91bGhPn2NpaSk+LR9+/btPvPYvg937NjhU9/nn39uXrdauxv34aJFi5x7773XmT9/vvkcWLBgQZ3z/+c//3GSk5PNcVLfh88884ypb/HixUFvs0ARZPygLzh/gkx5ebnTrl075/HHH6+Y9vvvvzuJiYnO3Llzze+6o/XFsWrVqop53nrrLScuLs58SWa4hKod3bt3d4YNG+YzzZ8Xv1vr0yBz66231vkmj4+P9/mwnTZtmvkwLikpccIpVPvwlVdeMR8ypaWlEd2H+kWwI0aMqPi9rKzMad++vfPII4/UOP+ll17q9O/f32faaaed5lx//fV+vx/DLdAaq9Ig3aJFC+fFF1/0OQheeOGFjhsEWl99n63RuA//9re/mX24e/duV+7Dyvz5HLjzzjudE044wWfaZZdd5vTt2zdk26w+nFoKoc2bN5u7D2vXZ+XvidButBUrVpjf9aeeAtCvXPDS+ePj42XlypVha2so2rFmzRpZv369OZ1R1YgRI8yXfurXSsyaNav+r2F3UX0vvfSSaXvXrl3Nl5AWFRX5rFdPYVS+s3Tfvn3NF6d98cUXEk6hei3paSU9NdW0adOI7cN9+/aZ11Pl947Wob973ztV6fTK83v3hXd+f96P4RRMjVXpa7G0tFTatGlTrWtfT3PqKcMbb7xRduzYIbbUp6dCjzjiCPPFgxdeeKHP+yga9+Hzzz8vl19+uTRv3tx1+zAY9b0PQ7HNouLOvrbQN5yq+vUJ+rv3b/pTX6yV6QFEP5i884SrrQ1th74hu3TpYsYRVfbAAw/IOeecY8aQLFmyRG666SbzYaVjMdxeX3Z2tvlQ1fPDn376qdx1112Sn58v8+fPr1hvTfvX+7dwCsU+LCgokAcffFCuu+66iO5DbUdZWVmN2/arr76qcZna9kXl95p3Wm3zhFMwNValr0d9bVY+KOhYikGDBkmnTp3km2++kXvuuUf69etnDhJNmjQRN9enB20NySeeeKIJ1E888YT5PNEwc/jhh0fdPtRxIZ9//rn57KzMLfswGLW9D/Ufd8XFxfLbb781+HVfn5gLMnfffbdMmjSpznk2bNhgBhBGc30NpS/QOXPmyLhx46r9rfK0zMxM8yWfjz/+eEgOgo1dX+UDuva86ADDXr16mQ+Xo446SqJpH+oHjQ44PP744yUnJyds+xDBefTRR82Aa/2Xe+UBsfqv+8qvWQ0F+lrV+fS162ZnnHGGeXhpiNF/HM2YMcME7GijAUb3kfZyVmbzPnSDmAsyt99+uxkhXpcjjzwyqHW3a9fO/Pzpp5/MAdBLf9cvu/TO8/PPP/ssp1e86NUk3uXDUV9D2/Haa6+Zbu6rr7663nm1G1g/lEpKShr8fRzhqq9y29WmTZvMB4suW3W0ve5fFYr9F64ad+3aZf4V2KJFC1mwYIEkJCSEbR/WRE9h6b88vdvSS3+vrRadXtf8/rwfwymYGr20p0KDzDvvvGMOcvW9NvS59DUbzoNgQ+rz0tehBmdte7TtQ/3HgAZR7e2sT6T2YTBqex/q6Wq9yky3V0NfF/UKyUibKBfoYN8nnniiYppe8VLTYN/Vq1dXzPP2229HbLBvsO3QQbFVr3SpzcSJE53WrVs74RSq7fzRRx+Z9ejVEpUH+1YebT9jxgwz2Hfv3r2ODTXqa/L00083+3DPnj2u2Yc6IPDmm2/2GRB42GGH1TnY9/zzz/eZdsYZZ1Qb7FvX+zHcAq1RTZo0yby+VqxY4ddzfP/99+Y18Prrrzs21Fd1MHPnzp2d2267Lar2ofc4ou0uKChw9T4MZrCvXslZmV45WXWwb0NeF/UhyNThu+++M5c9ei8x1v/XR+VLjfVNp5epVb5UUC8r0xfgp59+akai13T5dWZmprNy5UpzoNTLXyN1+XVd7dBLPLU+/XtlGzduNG8yvUKmKr2sd+bMmeYSWJ3v2WefNZfm6aXsbq9PL0d+4IEHTDDYvHmz2YdHHnmkk5WVVe3y63PPPddZv369ucTw4IMPjujl14HUqAcBvbKnW7dupt7Kl3tqbZHch3qJpn7Qz54924S06667zryXvFeIXXXVVc7dd9/tc/l106ZNzUFOL00eP358jZdf1/d+DKdAa9T26xVlr732ms++8n4G6c877rjDhBx9zb7zzjvOSSedZF4H4Q7WwdSnn60avr/55htnzZo1zuWXX+4kJSWZS3SjZR96nX322eZqnqrctg937dpVcazTIKO3INH/1+Oh0tq0xqqXX48ZM8a8D/V2ATVdfl3XNmsogkwd9JI43ZFVH++//361+2146b8gxo0b5xx66KFmx/Xq1cvJz8+vdl8BPdhoONJ/aQ0dOtQnHIVLfe3QN1XVepUetNPT002qrkrDjV6Srets3ry5ucfJ9OnTa5zXbfVt2bLFhJY2bdqYfaf3ZNE3Z+X7yKhvv/3W6devn+PxeMw9ZG6//XafS5fDKdAa9WdNr2l96LyR3od6D4oOHTqYg7f+K07vj+OlPUj6nqx66fixxx5r5tdLQN98802fv/vzfgy3QGo84ogjatxXGtpUUVGRCdUapjXE6fx6j45QHSAau75Ro0ZVzKv76M9//rOzdu3aqNqH6quvvjL7bcmSJdXW5bZ9+H4tnxHemvSn1lh1Gf3M0O2h//irfEz0Z5s1VJz+JzQnqQAAAMKL+8gAAABrEWQAAIC1CDIAAMBaBBkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyACwSllZmfmW5EGDBvlMLywslPT0dLn33nsj1jYA4cedfQFY5+uvvzbffjxz5kwZPHiwmabfxJ6XlyerVq2SZs2aRbqJAMKEIAPASk8//bTk5OTIF198IZ988olccsklJsRkZGREumkAwoggA8BK+tF1zjnnSJMmTeSzzz6TkSNHyn333RfpZgEIM4IMAGt99dVX0qVLF+nWrZusXbtWmjZtGukmAQgzBvsCsNasWbMkOTlZNm/eLFu3bo10cwBEAD0yAKy0fPly+dOf/iRLliyRiRMnmmnvvPOOxMXFRbppAMKIHhkA1ikqKpJrrrlGbrzxRunZs6c8//zzZsDv9OnTI900AGFGjwwA69x6662yaNEic7m1nlpSM2bMkDvuuMMM/O3YsWOkmwggTAgyAKzywQcfSK9evWTZsmVy9tln+/ytb9++sn//fk4xATGEIAMAAKzFGBkAAGAtggwAALAWQQYAAFiLIAMAAKxFkAEAANYiyAAAAGsRZAAAgLUIMgAAwFoEGQAAYC2CDAAAsBZBBgAAWIsgAwAAxFb/D58o0B83IzTfAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "x = np.linspace(0, 10, 100)\n",
+    "y = np.sin(x)\n",
+    "\n",
+    "plt.hist(np.sin(x), bins=30, label='sin(x)', color='red', edgecolor='black')\n",
+    "#plt.plot(x, np.cos(x), label='cos(x)', color='blue') \n",
+    "plt.xlabel(\"X\")\n",
+    "plt.ylabel(\"Y\")\n",
+    "plt.title(\"Мультиграфик\")\n",
+    "plt.legend()\n",
+    "plt.grid()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "8f6279a5-850e-41ef-9920-75b3c9083302",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkAAAAGwCAYAAABB4NqyAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAALFxJREFUeJzt3Ql4FVWa//E3CyQxkCCgJNFASDCkpVlabCNptNUgkEaIiLIMyi4I48LQoqDN1pBJo920I9A4KLLLpo3L+Aw2pAVlgA6LQDOoQBqCSFgHEpYsQO487/n/cychNyFAkrrJ+X6epx5St6rOPYXe3B/nvFXl43K5XAIAAGARX6c7AAAAUN0IQAAAwDoEIAAAYB0CEAAAsA4BCAAAWIcABAAArEMAAgAA1vF3ugPeqLCwUI4ePSr169cXHx8fp7sDAAAqQG9teO7cOYmIiBBf3/LHeAhAHmj4iYyMdLobAADgBvzwww9y5513lrsPAcgDHfkp+gsMCQlxujsAAKACcnJyzABG0fd4eQhAHhRNe2n4IQABAFCzVKR8hSJoAABgHQIQAACwDgEIAABYhwAEAACsQwACAADWIQABAADrEIAAAIB1CEAAAMA6BCAAAGAdAhAAALCOowFIn9g6evRoadasmQQFBUlCQoJs3brVvX3QoEHmdtbFl65du16z3dmzZ0tUVJQEBgZKfHy8pKenV/GZAACAmsTRADRs2DBZu3atLF68WP7+979L586dpVOnTvLjjz+699HAk5WV5V6WLVtWbpsrVqyQMWPGyKRJk2THjh3Stm1b6dKli5w4caIazggAANQEPi6Xy+XEG+fm5pqntX7yySfSrVs39+vt27eXpKQkmTZtmhkBOnv2rHz88ccVbldHfH7+85/LrFmzzHphYaF5MuwLL7wg48aNq/DTZENDQyU7O5uHoQIAUENcz/e3Y0+Dv3z5sly5csVMUxWnU2EbN250r69fv15uv/12ufXWW+WRRx4xwahRo0Ye2ywoKJDt27fL+PHj3a/5+vqaUaXNmzeX2Zf8/HyzFP8LxLXl5eXJ4cOHne4GrtK0adNSnysAgJcEIB396dChg0ydOlV+8pOfSJMmTcz0lgaVFi1auKe/nnjiCWnevLlkZGTIa6+9ZkaHdB8/P79SbZ46dcqEKm2rOF3/7rvvyuxLamqqTJkypQrOsnbT8DN8+HCnu4GrzJ07V2JjY53uBgB4NccCkNLanyFDhsgdd9xhAs0999wj/fr1M6M4qm/fvu59W7duLW3atJGYmBgzKpSYmFhp/dARI60bKj4CpNNmuPZIg37Z1nSZmZmSkpIir7/+uinIrw3/XQAAXhyANMxs2LBBLly4YEJHeHi49OnTR6Kjoz3ur683btxYDhw44DEA6TYNUsePHy/xuq6HhYWV2Y+AgACz4ProNEttGmnQ8FObzgcA4OX3AQoODjbh58yZM/LFF19IcnKyx/2OHDkip0+fNvt6UrduXVNEnZaW5n5Ni6B1XafbAAAAHA9AGnbWrFkjBw8eNJfDP/zwwxIXFyeDBw+W8+fPy9ixY2XLli1y6NAhE2I0GGl9kF7WXkRHgoqu+FI6lfXuu+/KwoUL5dtvv5WRI0eaESZtEwAAwPEpML1MTetvdGSnYcOG0qtXL1OLUadOHXOV2O7du02Q0UvhIyIizH2CtGi6+HSVFkdr8XMRnUI7efKkTJw4UY4dOybt2rUzIevqwmgAAGAvx+4D5M24D5Bd9u3bZ65m4+opALDn+9sraoAAAACqEwEIAABYhwAEAACsQwACAADWIQABAADrEIAAAIB1CEAAAMA6BCAAAGAdAhAAALAOAQgAAFiHAAQAAKxDAAIAANYhAAEAAOsQgAAAgHUIQAAAwDoEIAAAYB0CEAAAsA4BCAAAWMff6Q7Y7Pjx45Kdne10N6yXmZlZ4k84KzQ0VJo0aeJ0NwDUcj4ul8vldCe8TU5OjvklrOEkJCSkysLP088MkEsF+VXSPlBT1akbIEsWLyIEAajS729GgByi/3E0/ORG/1IKA0Od7g7gFXzzskX+scF8PghAAKoSAchhGn4Kgxs73Q0AAKxCETQAALAOAQgAAFiHAAQAAKxDAAIAANYhAAEAAOsQgAAAgHUIQAAAwDoEIAAAYB0CEAAAsA4BCAAAWIcABAAArEMAAgAA1nE0AJ07d05Gjx4tzZo1k6CgIElISJCtW7eabZcuXZJXX31VWrduLcHBwRIRESEDBgyQo0ePltvm5MmTxcfHp8QSFxdXTWcEAABqAkefBj9s2DDZs2ePLF682AScJUuWSKdOnWTv3r1Sr1492bFjh0yYMEHatm0rZ86ckZdeekl69Ogh27ZtK7fdVq1aybp169zr/v489B4AAPwfx5JBbm6ufPTRR/LJJ5/Igw8+6B69+eyzz2TOnDkybdo0Wbt2bYljZs2aJffdd58cPnxYmjZtWmbbGnjCwsIq3Jf8/HyzFMnJybmhcwIAADWDY1Ngly9flitXrkhgYGCJ13UqbOPGjR6Pyc7ONlNaDRo0KLft/fv3mxGl6Oho6d+/vwlM5UlNTZXQ0FD3EhkZeQNnBAAAagrHAlD9+vWlQ4cOMnXqVFPXo2FIp8A2b94sWVlZpfbPy8szNUH9+vWTkJCQMtuNj4+XBQsWyJo1a8xI0sGDB+WBBx4w9UZlGT9+vAlXRcsPP/xQaecJAAC8j6PFMVr7M2TIELnjjjvEz89P7rnnHhNwtm/fXmI/LYju3bu3uFwuE2rKk5SU5P65TZs2JhBpkfXKlStl6NChHo8JCAgwCwAAsIOjV4HFxMTIhg0b5Pz582bUJT093YQdnbq6OvxkZmaamqDyRn880emy2NhYOXDgQBWcAQAAqIm84j5Aepl7eHi4udLriy++kOTk5BLhR2t69KquRo0aXXfbGq4yMjJM+wAAAI4HIA07WqujdTo6uvPwww+be/YMHjzYhJ8nn3zSXPK+dOlSUyN07NgxsxQUFLjbSExMNFeHFXn55ZfNqNKhQ4dk06ZN0rNnTzO9plNrAAAAjtcAacGxFiAfOXJEGjZsKL169ZKUlBSpU6eOCTCffvqp2a9du3Yljvvyyy/loYceMj/r6M6pU6fc27QtDTunT5+W2267TTp27ChbtmwxPwMAADgegHR6SxdPoqKiTNHztWhQKm758uWV1j8AAFA7cYtkh/nmnnW6C4DX4PMAoLoQgBwWdPArp7sAAIB1CEAOy23+oBQGlX9na8CmESD+UQCgOhCAHKbhpzC4sdPdAADAKl5xHyAAAIDqRAACAADWIQABAADrEIAAAIB1CEAAAMA6BCAAAGAdAhAAALAOAQgAAFiHAAQAAKxDAAIAANYhAAEAAOsQgAAAgHUIQAAAwDoEIAAAYB0CEAAAsA4BCAAAWIcABAAArEMAAgAA1iEAAQAA6xCAAACAdQhAAADAOgQgAABgHQIQAACwjr/THbCdb162010AvAafBwDVhQDkkNDQUKlTN0DkHxuc7grgVfRzoZ8PAKhKBCCHNGnSRJYsXiTZ2fyL12mZmZmSkpIir7/+ujRr1szp7lhPw49+PgCgKhGAHKS/5PlF7z00/MTGxjrdDQBANaAIGgAAWIcABAAArONoADp37pyMHj3aTD0EBQVJQkKCbN261b3d5XLJxIkTJTw83Gzv1KmT7N+//5rtzp49W6KioiQwMFDi4+MlPT29is8EAADUJI4GoGHDhsnatWtl8eLF8ve//106d+5sQs6PP/5otr/xxhvy9ttvyzvvvCN/+9vfJDg4WLp06SJ5eXlltrlixQoZM2aMTJo0SXbs2CFt27Y1x5w4caIazwwAAHgzxwJQbm6ufPTRRybkPPjgg9KiRQuZPHmy+XPOnDlm9Oett96S3/zmN5KcnCxt2rSRRYsWydGjR+Xjjz8us90ZM2bIs88+K4MHD5a7777bhKdbbrlF3n///TKPyc/Pl5ycnBILAACovRwLQJcvX5YrV66YaaridKpr48aNcvDgQTl27JgZESp+eaxOaW3evNljmwUFBbJ9+/YSx/j6+pr1so5Rqamppu2iJTIyslLOEQAAeCfHAlD9+vWlQ4cOMnXqVDOqo2FoyZIlJqhkZWWZ8KOuvkxc14u2Xe3UqVOmnes5Ro0fP97cj6do+eGHHyrlHAEAgHdytAZIa390quuOO+6QgIAAU+/Tr18/M2pTnfS9Q0JCSiwAAKD2cjQAxcTEyIYNG+T8+fNm1EWv1rp06ZJER0dLWFiY2ef48eMljtH1om1Xa9y4sfj5+V3XMQAAwD5ecR8gvbpLL3U/c+aMfPHFF6bouXnz5ia0pKWluffT4mS9GkynzjypW7eutG/fvsQxhYWFZr2sYwAAgH0cfRSGhh2dAmvZsqUcOHBAxo4dK3FxceYKLh8fH3OPoGnTpsldd91lAtGECRMkIiJCHn/8cXcbiYmJ0rNnT3n++efNul4CP3DgQLn33nvlvvvuM1eSXbhwwbQJAADgeADSgmMtQD5y5Ig0bNhQevXqZR5KWadOHbP9lVdeMeFl+PDhcvbsWenYsaOsWbOmxJVjGRkZpvi5SJ8+feTkyZPmBopa+NyuXTtzDM/cAgAARXxcOgSDEnSqTS+H14BGQXTtt2/fPhOy586dy8NQAcCS72+vqAECAACoTgQgAABgHQIQAACwDgEIAABYhwAEAACsQwACAADWIQABAADrEIAAAIB1CEAAAMA6jj4KAzVbXl6eHD58WGq6zMzMEn/WdE2bNi3xuBgAQGkEINwwDT/6CInaQp9DVxvwSA8AuDYCEG5qpEG/bOF9/10AAOUjAOGG6TQLIw0AgJqIImgAAGAdAhAAALAOAQgAAFiHAAQAAKxDAAIAANYhAAEAAOsQgAAAgHUIQAAAwDoEIAAAYB0CEAAAsA4BCAAAWIcABAAArEMAAgAA1iEAAQAA6xCAAACAdQhAAADAOgQgAABgHQIQAACwDgEIAABYhwAEAACs42gAunLlikyYMEGaN28uQUFBEhMTI1OnThWXy+Xex8fHx+Py5ptvltnu5MmTS+0fFxdXTWcFAAC8nb+Tbz59+nSZM2eOLFy4UFq1aiXbtm2TwYMHS2hoqLz44otmn6ysrBLH/Od//qcMHTpUevXqVW7b2t66devc6/7+jp4qAADwIo6mgk2bNklycrJ069bNrEdFRcmyZcskPT3dvU9YWFiJYz755BN5+OGHJTo6uty2NfBcfSwAAIDjU2AJCQmSlpYm+/btM+u7du2SjRs3SlJSksf9jx8/Lp9//rkZAbqW/fv3S0REhAlK/fv3l8OHD5e5b35+vuTk5JRYAABA7eXoCNC4ceNM2ND6HD8/P1MTlJKSYgKLJzpVVr9+fXniiSfKbTc+Pl4WLFggLVu2NFNoU6ZMkQceeED27Nljjr9aamqq2QcAANjBx1W84riaLV++XMaOHWsKmrVmZ+fOnTJ69GiZMWOGDBw4sNT+GpQeffRRmTlz5nW9z9mzZ6VZs2amXU+jRzoCpEsRDWWRkZGSnZ0tISEhN3h2AACgOun3t9YRV+T729ERIA0/OgrUt29fs966dWvJzMw0IzJXB6Cvv/5avv/+e1mxYsV1v0+DBg0kNjZWDhw44HF7QECAWQAAgB0crQG6ePGi+PqW7IJOhRUWFpbad968edK+fXtp27btdb/P+fPnJSMjQ8LDw2+qvwAAoHZwNAB1797d1PxoYfOhQ4dk9erVZpqqZ8+epYa0Vq1aJcOGDfPYTmJiosyaNcu9/vLLL8uGDRtMm3qlmbanwapfv35Vfk4AAMD7OToFprU8eiPEUaNGyYkTJ8xVWyNGjJCJEyeWqhXSUqWyAoyO7pw6dcq9fuTIEbPv6dOn5bbbbpOOHTvKli1bzM8AAACOFkHXhiIqAABQ876/eRYYAACwDgEIAABYhwAEAACsQwACAADWIQABAADrEIAAAIB1CEAAAMA6BCAAAGAdAhAAALDODT0KQx9g6uPjU+b2K1eu3EyfAAAAvC8A6UNLAQAArApAycnJJdb//Oc/y86dO+WnP/2p9O7du7L6BgAA4J01QNOnTzdPXl+zZo0MHTpUpkyZUjk9AwAA8NYAtHDhQnnvvfckPT1dPvnkE5k/f37l9AwAAMBbA9DRo0fl/vvvNz/rnz/++GNl9AsAAMB7A5Be8eXv//9Kifz8/KSwsLAy+gUAAOBdRdA/+9nP3JfB5+bmSvfu3aVu3bricrkqu38AAADeEYAef/zxMq8IK74NAADAG/m4GLYpJScnR0JDQyU7O1tCQkKc7g4AAKjk72//G32D8hAaAACAN7uhANSgQQOPj8LQwSR9nUdhAACAWheA1IcffigNGzas3N4AAAB4cwD6xS9+Ibfffnvl9gYAAMCbA9DevXvl9OnTEhwcLGFhYeYyeAAAgFp9I8TExERp1aqVNG/e3ISg1q1byx//+MfK7R0AAIC3jAAdPHjQFDxfunTJXBGmj8PQZ4FNmDBBLl++LGPHjq38ngIAAHjjfYAWL14sv/3tb2X//v1Sk3EfIAAAap4qvw9QWfr27WumxQAAALxZpd8IsUWLFjfTHwAAgCrHjRABAIB1uBEiAACwDjdCBAAA1uFGiAAAwDqO3ghRa4X03kHaRlBQkMTExMjUqVNNLVGRQYMGmbqi4kvXrl2v2fbs2bMlKipKAgMDJT4+3tynCAAAwPEbIU6fPl3mzJkjCxcuNGFq27ZtMnjwYHMN/4svvujeTwPP/Pnz3esBAQHltrtixQoZM2aMvPPOOyb8vPXWW9KlSxf5/vvvmbYDAADO3gjxsccekyZNmsi8efPcr/Xq1cuMBi1ZssQ9AnT27Fn5+OOPK9wPDT0///nPZdasWWa9sLBQIiMj5YUXXpBx48Zd83huhAgAQM1zPd/fNzwFVtaNEHX0paISEhIkLS1N9u3bZ9Z37dolGzdulKSkpBL7rV+/3ozctGzZUkaOHGlqj8pSUFAg27dvl06dOrlf8/X1NeubN2/2eEx+fr75Syu+AACA2qtS7wRdp04dueeeeyq8v47GaNiIi4sTPz8/UxOUkpIi/fv3LzH99cQTT5g6oYyMDHnttddMQNIwo8dc7dSpU6YdHVkqTte/++47j/1ITU2VKVOmXNe5AgAAywKQBgwteF65cqUcPnzYjLoU9z//8z8VakePX7p0qXzwwQemBmjnzp0yevRoiYiIkIEDB7pHlYpooXWbNm1MsbSOCmkhdmUYP368qRkqoqFMp8wAAEDtdENTYDpaMmPGDOnTp4+ZZ9PwoKM0OtU0efLkCrejxdI6CqQhR8PNM888I//yL/9iRmTKEh0dLY0bN5YDBw543K7bdGTo+PHjJV7Xdb1c3xMtqta5wuILAACovW4oAOmozbvvviu//vWvxd/fX/r16yfvvfeeTJw4UbZs2VLhdi5evGhCU3EaXrRouSxHjhwxNUDh4eEet+v9iNq3b29qi4poe7reoUOHCvcNAADUXjcUgI4dO2ZGbFS9evXMKFDRVV2ff/55hdvp3r27qfnRYw4dOiSrV682I0s9e/Y028+fP29GiTRU6XYNMcnJyeaBq3pZexGdCiu64kvpiJQGNL28/ttvvzWF0xcuXDCX2AMAANxQDdCdd94pWVlZ0rRpU1OP85e//MUUP2/duvWa9+gpbubMmebeQaNGjZITJ06Y2p8RI0aYkaSi0aDdu3ebIKOXwuv2zp07m5slFn8fLY7W4uciOjV38uRJ046GtXbt2smaNWtKFUYDAAA73dB9gLRuR+tk9Iosvez96aefNndd1oJoreH53e9+JzUZ9wECAKB2f39Xyo0QdYpq06ZNctddd5lprZqOAAQAQM1TrTdC1Gmvzz77zExh6ZsCAADUqhogrfn55ptvpFGjRmZ97dq10q1bN1OPo1dz/f73v5dly5bJU089VVX9BQAAuGnXNQKkl6DrTRCLvPnmm+YSeC1QPnPmjClgfuONN26+VwAAAFXopqbA9BJzfcCoXq2lI0D6c0UfhAoAAFAjA5CO/DRs2NC9fuutt8q5c+cqo18AAADeEYB8fHzMcvVrAAAAtbYIWq+YHzRokPsmhHl5efLcc89JcHCwWc/Pz6+aXgIAADgVgIqe0F5Eb4B4tQEDBtx8rwAAALwlAM2fP7/qegIAAFBNbvpGiAAAADUNAQgAAFiHAAQAAKxDAAIAANYhAAEAAOsQgAAAgHUIQAAAwDoEIAAAYB0CEAAAsA4BCAAAWIcABAAArEMAAgAA1iEAAQAA6xCAAACAdQhAAADAOgQgAABgHQIQAACwDgEIAABYhwAEAACsQwACAADWIQABAADrEIAAAIB1CEAAAMA6jgagK1euyIQJE6R58+YSFBQkMTExMnXqVHG5XGb7pUuX5NVXX5XWrVtLcHCwREREyIABA+To0aPltjt58mTx8fEpscTFxVXTWQEAAG/n7+SbT58+XebMmSMLFy6UVq1aybZt22Tw4MESGhoqL774oly8eFF27NhhQlLbtm3lzJkz8tJLL0mPHj3MvuXR9tatW+de9/d39FQBAIAXcTQVbNq0SZKTk6Vbt25mPSoqSpYtWybp6elmXYPQ2rVrSxwza9Ysue++++Tw4cPStGnTMtvWwBMWFlbFZwAAAGoiR6fAEhISJC0tTfbt22fWd+3aJRs3bpSkpKQyj8nOzjZTWg0aNCi37f3795sps+joaOnfv78JTGXJz8+XnJycEgsAAKi9HB0BGjdunAkbWp/j5+dnaoJSUlJMYPEkLy/P1AT169dPQkJCymw3Pj5eFixYIC1btpSsrCyZMmWKPPDAA7Jnzx6pX79+qf1TU1PNPgAAwA4+rqKKYwcsX75cxo4dK2+++aap2dm5c6eMHj1aZsyYIQMHDiyxrxZE9+rVS44cOSLr168vNwBd7ezZs9KsWTPT7tChQz2OAOlSRENZZGSkGW26nvcBAADO0e9vLZ+pyPe3oyNAGn50FKhv375mXa/2yszMNCMyxQOQhp/evXubbX/961+vO5TodFlsbKwcOHDA4/aAgACzAAAAOzhaA6RXefn6luyCToUVFhaWCj9a06NXdTVq1Oi63+f8+fOSkZEh4eHhldJvAABQszkagLp3725qfj7//HM5dOiQrF692kxT9ezZ0x1+nnzySXPJ+9KlS02N0LFjx8xSUFDgbicxMdFcHVbk5Zdflg0bNpg29UozbU+DldYOAQAAODoFNnPmTHOPn1GjRsmJEyfMVVsjRoyQiRMnmu0//vijfPrpp+bndu3alTj2yy+/lIceesj8rKM7p06dcm/TOiENO6dPn5bbbrtNOnbsKFu2bDE/AwAAOFoEXRuKqAAAQM37/uZZYAAAwDo8HwIA4PG+a+XdQBbO0CcgBAYGOt2NWoEABAAoRcPP8OHDne4GrjJ37lxzWxfcPAIQAMDjSIN+2dZ0ev84vdr49ddfNzfErenKewYmrg8BCABQik6z1KaRBg0/tel8cPMoggYAANYhAAEAAOsQgAAAgHUIQAAAwDoEIAAAYB0CEAAAsA4BCAAAWIcABAAArEMAAgAA1iEAAQAA6xCAAACAdQhAAADAOgQgAABgHQIQAACwDgEIAABYhwAEAACsQwACAADWIQABAADrEIAAAIB1CEAAAMA6BCAAAGAdAhAAALCOv9MdAIDa6Pjx45Kdne10N6yXmZlZ4k84KzQ0VJo0aSLewMflcrmc7oS3ycnJMf+R9JdXSEiI090BUAPDz9PPDJBLBflOdwXwKnXqBsiSxYuqLARdz/c3I0AAUMn0l6+Gn9zoX0phYKjT3QG8gm9etsg/NpjPhzeMAhGAAKCKaPgpDG7sdDcAeEARNAAAsA4BCAAAWIcABAAArONoALpy5YpMmDBBmjdvLkFBQRITEyNTp06V4hem6c8TJ06U8PBws0+nTp1k//7912x79uzZEhUVJYGBgRIfHy/p6elVfDYAAKCmcDQATZ8+XebMmSOzZs2Sb7/91qy/8cYbMnPmTPc+uv7222/LO++8I3/7298kODhYunTpInl5eWW2u2LFChkzZoxMmjRJduzYIW3btjXHnDhxoprODAAAeDNHA9CmTZskOTlZunXrZkZrnnzySencubN7tEZHf9566y35zW9+Y/Zr06aNLFq0SI4ePSoff/xxme3OmDFDnn32WRk8eLDcfffdJjzdcsst8v7773vcPz8/39w7oPgCAABqL0cDUEJCgqSlpcm+ffvM+q5du2Tjxo2SlJRk1g8ePCjHjh0z015F9AZHOqW1efNmj20WFBTI9u3bSxzj6+tr1ss6JjU11bRbtERGRlbymQIAAG/i6H2Axo0bZ0Zb4uLixM/Pz9QEpaSkSP/+/c12DT/q6hsm6XrRtqudOnXKtOPpmO+++87jMePHjzdTZkW0T4QgAABqL0cD0MqVK2Xp0qXywQcfSKtWrWTnzp0yevRoiYiIkIEDB1ZbPwICAswCAADs4GgAGjt2rBkF6tu3r1lv3bq1eWCdTklpAAoLC3M/V0evAiui6+3atfPYZuPGjc1oku5TnK4XtQcAAOzmaA3QxYsXTX1OcRpeCgsLzc96ebyGFq0TKj49pVeDdejQwWObdevWlfbt25c4RtvT9bKOAQAAdnF0BKh79+6m5qdp06ZmCuybb74xV3ANGTLEbPfx8TFTYtOmTZO77rrLBCK9b5BOkT3++OPudhITE6Vnz57y/PPPm3Wt59ERpHvvvVfuu+8+cyXZhQsXzFVhAAAAjgYgvd+PBppRo0aZe/RosBkxYoS58WGRV155xYSX4cOHy9mzZ6Vjx46yZs0ac4PDIhkZGab4uUifPn3k5MmTph0tltbpMj3GG54+CwAAnOfjKn7bZbin2fRy+OzsbAkJCXG6OwBqGL21h/6j7cLdPXgaPPD/+V44JcF7P5W5c+dKbGysOP39zbPAAACAdQhAAADAOgQgAABgHQIQAACwDgEIAABYhwAEAACsQwACAADWIQABAADrEIAAAIB1HH0UBgDUZr65Z53uAuA1fL3s80AAAoAqEnTwK6e7AKAMBCAAqCK5zR+UwqAGTncD8JoRoCAv+kcBAQgAqoiGHx6GCngniqABAIB1CEAAAMA6BCAAAGAdAhAAALAOAQgAAFiHAAQAAKxDAAIAANYhAAEAAOsQgAAAgHUIQAAAwDoEIAAAYB0CEAAAsA4BCAAAWIcABAAArEMAAgAA1iEAAQAA6xCAAACAdQhAAADAOgQgAABgHQIQAACwjqMBKCoqSnx8fEot//zP/yyHDh3yuE2XVatWldnmoEGDSu3ftWvXaj0vAADg3fydfPOtW7fKlStX3Ot79uyRRx99VJ566imJjIyUrKysEvvPnTtX3nzzTUlKSiq3XQ088+fPd68HBARUQe8BAEBN5WgAuu2220qs/+53v5OYmBj55S9/aUZuwsLCSmxfvXq19O7dW+rVq1duuxp4rj62PPn5+WYpkpOTU+FjAaAsvnnZTncB8Bq+XvZ5cDQAFVdQUCBLliyRMWPGmPBzte3bt8vOnTtl9uzZ12xr/fr1cvvtt8utt94qjzzyiEybNk0aNWpU5v6pqakyZcqUmz4HAFChoaFSp26AyD82ON0VwKvUqRtgPh/ewMflcrnEC6xcuVL+6Z/+SQ4fPiwRERGlto8aNcoEm71795bbzvLly+WWW26R5s2bS0ZGhrz22mtmxGjz5s3i5+dX4REgnYLLzs6WkJCQSjg7ALY5fvy4+R0CZ2VmZkpKSoq8/vrr0qxZM6e7Y73Q0FBp0qRJlbWv39/6HhX5/vaaEaB58+aZ2h5P4Sc3N1c++OADmTBhwjXb6du3r/vn1q1bS5s2bcy0moanxMTEMqfMqBMCUJn0l3xV/qLH9dHwExsb63Q34EV8vSWhr1u3ToYNG+Zx+4cffigXL16UAQMGXHfb0dHR0rhxYzlw4EAl9BQAANQGXhGA9Iotrdnp1q1bmaNDPXr0KFU0XRFHjhyR06dPS3h4eCX0FAAA1AaOB6DCwkITgAYOHCj+/qVn5HTk5quvvipzdCguLs5cHabOnz8vY8eOlS1btpj7CKWlpUlycrK0aNFCunTpUuXnAgAAagbHA5BOfWnh85AhQzxuf//99+XOO++Uzp07e9z+/fffuwsNtch59+7dZrRI53qHDh0q7du3l6+//poaHwAA4D1F0BpsyrsQ7V//9V/NUpbixwYFBckXX3xR6X0EAAC1i+MjQAAAANWNAAQAAKxDAAIAANYhAAEAAOsQgAAAgHUIQAAAwDoEIAAAYB0CEAAAsA4BCAAAWIcABAAArEMAAgAA1iEAAQAA6xCAAACAdQhAAADAOgQgAABgHQIQAACwDgEIAABYhwAEAACs4+90BwAA3icvL08OHz4sNV1mZmaJP2u6pk2bSmBgoNPdqBUIQACAUjT8DB8+XGqLlJQUqQ3mzp0rsbGxTnejViAAAQA8jjToly28778LKgcBCABQik6zMNKA2owiaAAAYB0CEAAAsA4BCAAAWIcABAAArEMAAgAA1iEAAQAA6xCAAACAdQhAAADAOgQgAABgHQIQAACwDgEIAABYhwAEAACsQwACAADW4WnwHrhcLvNnTk6O010BAAAVVPS9XfQ9Xh4CkAfnzp0zf0ZGRjrdFQAAcAPf46GhoeXu4+OqSEyyTGFhoRw9elTq168vPj4+TncH1fAvBg27P/zwg4SEhDjdHQCViM+3XVwulwk/ERER4utbfpUPI0Ae6F/anXfe6XQ3UM30lyO/IIHaic+3PUKvMfJThCJoAABgHQIQAACwDgEI1gsICJBJkyaZPwHULny+URaKoAEAgHUYAQIAANYhAAEAAOsQgAAAgHUIQAAAwDoEIFht8+bN4ufnJ926dXO6KwAq0aBBg8yd/IuWRo0aSdeuXWX37t1Odw1eggAEq82bN09eeOEF+eqrr8zjTwDUHhp4srKyzJKWlib+/v7y2GOPOd0teAkCEKx1/vx5WbFihYwcOdKMAC1YsMDpLgGoRHrvn7CwMLO0a9dOxo0bZ54JdvLkSae7Bi9AAIK1Vq5cKXFxcdKyZUt5+umn5f333zcP0gNQO//Bs2TJEmnRooWZDgN4GCqsnv7S4FM0VJ6dnS0bNmyQhx56yOmuAagE//Ef/yH16tUzP1+4cEHCw8PNa9d6SjjswP8FsNL3338v6enp0q9fP7OutQF9+vQxoQhA7fDwww/Lzp07zaKf9y5dukhSUpJkZmY63TV4AUaAYCUNOpcvX5aIiAj3azr9pTUDs2bNktDQUEf7B+DmBQcHmymvIu+99575bL/77rsybdo0R/sG5zECBOto8Fm0aJH84Q9/cP/rUJddu3aZQLRs2TKnuwigCujl8Dr9lZub63RX4AUYAYJ1tAbgzJkzMnTo0FIjPb169TKjQ88995xj/QNQOfLz8+XYsWPmZ/3M6+iuFkN3797d6a7BCzACBOtowOnUqZPHaS4NQNu2beNmaUAtsGbNGlP4rEt8fLxs3bpVVq1axYUOMHxcXPcLAAAswwgQAACwDgEIAABYhwAEAACsQwACAADWIQABAADrEIAAAIB1CEAAAMA6BCAAAGAdAhAAALAOAQhAlRo0aJA8/vjjJV47efKk/PSnPzWPJ8jOznasbwDsRQACUK00/DzyyCMSFBQkf/nLXzw+kw0AqhoBCEC1OXXqlCQmJkpAQICsXbvWHX5mzJghrVu3luDgYImMjJRRo0aZp3ar9evXi4+PT5lLkY0bN8oDDzxggpW28eKLL8qFCxfc26Oiokod+/LLL7u3z5kzR2JiYqRu3brSsmVLWbx4cYm+6/66T1JSknmP6Oho+fDDD93bDx06ZPbZuXOn+7UJEyaY19566y33a9999508+uij5tyL+tGgQYNK/7sGUD4CEIBqcfr0aenUqZP4+/ub8FP8S9/X11fefvtt+e///m9ZuHCh/PWvf5VXXnnFbEtISJCsrCyzfPTRR+a1onVdVEZGhnTt2lV69eolu3fvlhUrVphA9Pzzz5fow29/+9sSx06aNMm8vnr1annppZfk17/+tezZs0dGjBghgwcPli+//LLE8Rpo9D127dol/fv3l759+8q3337r8XyPHDligo+GpeKGDBkily5dkv/6r/8yfSgejgBUI30aPABUlYEDB7oefPBBV7t27Vx16tRx3X///a7Lly+Xe8yqVatcjRo1KvX6l19+6fL0a2vo0KGu4cOHl3jt66+/dvn6+rpyc3PNerNmzVx//OMfPb5fQkKC69lnny3x2lNPPeX61a9+5V7X933uuedK7BMfH+8aOXKk+fngwYNmn2+++casDxgwwPTr6vcNCgpyLV261L0+f/58V2hoaLl/HwAqHyNAAKrcV199JYWFhWZ66MCBA/LGG2+U2L5u3TozNXbHHXdI/fr15ZlnnjEjRhcvXqxQ+zois2DBAqlXr5576dKli3nPgwcPXvN4HcX5xS9+UeI1Xb96dKdDhw6l1j2NAO3YscOMKk2dOrXUtubNm5ttFT03AFXDv4raBQA3rZdJS0uTxo0by5/+9Cd5+umnpVu3btKmTRtTO/PYY4/JyJEjJSUlRRo2bGimr4YOHSoFBQVyyy23XLN9rRfSaSut+7la06ZNpbrpVJrWF4WHh5faNm/ePBk4cKAJejo9dvnyZQkMDKz2PgK2YwQIQJXTAmcNP+qpp56SJ554QgYMGGACzvbt281IzR/+8Ae5//77JTY2Vo4ePXpd7d9zzz2yd+9eadGiRalFi5qv5Sc/+YmpySlO1+++++4Sr23ZsqXUuh5b3Keffir79u0rUWBdnJ5jjx495N5775VvvvnG1CUBqH6MAAGodrNnzzb3AZoyZYr07t3bFAXPnDlTunfvboLHO++8c13tvfrqqyZYaNHzsGHDzNVkGoi02HrWrFnXPH7s2LGmHz/72c9MofZnn30mf/7zn83UXHGrVq0ywaVjx46ydOlSSU9PNyM6xen0np5LWSNXWsit03Ua/HR06vbbb7+ucwVQORgBAlDtdJrr3XfflenTp0teXp65DF5/1lCkwSI1NfW62tOptA0bNpiRF70UXoPMxIkTJSIiokLH640a/+3f/k1+//vfS6tWreTf//3fZf78+fLQQw+V2E8D2/Lly837LVq0SJYtW1ZqlEhHnXSKyxPtnwa0Dz74wJGpOQD/x0croYutAwA80Pv1aPHy1Xe1BlAzMQIEAACsQwACAADWoQgaACqAagGgdmEECAAAWIcABAAArEMAAgAA1iEAAQAA6xCAAACAdQhAAADAOgQgAABgHQIQAAAQ2/wvURTgvj3F7RcAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "\n",
+    "df[\"Категория\"] = [\"A\", \"B\", \"A\", \"B\"] # догадайтесь откуда df и её содержимое взялось\n",
+    "sns.boxplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "02e3167e-9694-4932-b7ae-3cf2498d2dde",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkAAAAGwCAYAAABB4NqyAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAALGpJREFUeJzt3QtUlVX+//EvF0WGBEdNgcQLlFKGWlYkmVODaQwpmmm4LPE2OTqljklpM2gOEmmNY4qjU+OoectsUrussVHyEqOG93IyFcf7XUfBKyqc/9r7v875ceCAaMBzOPv9WutZ8pznefbZ52Scj3t/93O8bDabTQAAAAzibXUHAAAAqhoBCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOL5Wd8AdFRYWyrFjx6R27dri5eVldXcAAEA5qFsbXrhwQUJDQ8Xbu+wxHgKQCyr8hIWFWd0NAABwGw4fPiyNGjUq8xwCkAtq5Mf+BgYGBlrdHQAAUA55eXl6AMP+OV4WApAL9mkvFX4IQAAAVC/lKV+hCBoAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjGNpAFLf2DpixAhp0qSJ+Pv7S0xMjGzatMlxvF+/fvp21kW3p59++qbtTp8+XZo2bSq1atWS6Ohoyc7OruRXAgAAqhNLA9CgQYNk5cqVMm/ePPn++++lU6dO0rFjRzl69KjjHBV4jh8/7tgWLVpUZpuLFy+WkSNHyrhx42Tr1q3SunVr6dy5s5w6daoKXhEAAKgOvGw2m82KJ75y5Yr+ttbly5dLfHy84/G2bdtKXFycTJgwQY8AnT9/XpYtW1budtWIz8MPPywZGRl6v7CwUH8z7CuvvCKjR48u97fJBgUFSW5uLl+GCgBANXErn9+WjQDduHFDCgoK9DRVUWoqLCsry7G/Zs0aadCggbRo0UKGDBkiZ8+eLbXNa9euyZYtW/Qokp23t7fe37BhQ6nX5efn6zet6AYAADyXr1VPrEZ/2rVrJ6mpqXLvvfdKw4YN9fSWCip33323Y/rr2WeflWbNmsm+ffvkjTfe0KND6hwfH58SbZ45c0aHKtVWUWr/xx9/LLUv6enpMn78eKkqHXoOr7LnAoCfYt2S96zuAuB5NUCq9kfNwN11113i5+cnU6dOld69e+tRGyUxMVG6du0qUVFR0q1bN/niiy90kbQaFapIY8aM0cNl9u3w4cMV2j4AAHAvlgagiIgIWbt2rVy8eFGHDrVa6/r16xIeHu7yfPV4/fr1JScnx+VxdUyNDJ08edLpcbUfHBxcaj9U+FJzhUU3AADgudziPkABAQESEhIi586dk6+++koSEhJcnnfkyBFdA6TOdaVmzZq6iDozM9PxmCqCVvtqug0AAMDyAKTCzooVK2T//v16OfyTTz4pkZGR0r9/fz0qlJycLBs3bpQDBw7oEKOCkaoPUsva7WJjYx0rvhS1BP6DDz6QuXPnyq5du3Th9KVLl3SbAAAAlhZBK6reRtXfqJGdunXrSo8ePSQtLU1q1KihV4l99913OsiopfChoaH6PkGqaFpNWdmp4mhV/Gz3/PPPy+nTp2Xs2LFy4sQJadOmjQ5ZxQujAQCAuSy7D5A7q+z7ALEKDEB1wSowVCfV4j5AAAAAViEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjWBqALly4ICNGjJAmTZqIv7+/xMTEyKZNm/Sx69evy+uvvy5RUVESEBAgoaGh0rdvXzl27FiZbb755pvi5eXltEVGRlbRKwIAANWBr5VPPmjQINm5c6fMmzdPB5z58+dLx44d5YcffpA77rhDtm7dKikpKdK6dWs5d+6cDB8+XLp27SqbN28us92WLVvKqlWrHPu+vpa+TAAA4GYsSwZXrlyRf/zjH7J8+XLp0KGDY/Tm888/lxkzZsiECRNk5cqVTtdkZGTII488IocOHZLGjRuX2rYKPMHBweXuS35+vt7s8vLybus1AQCA6sGyKbAbN25IQUGB1KpVy+lxNRWWlZXl8prc3Fw9pVWnTp0y2967d68eUQoPD5c+ffrowFSW9PR0CQoKcmxhYWG38YoAAEB1YVkAql27trRr105SU1N1XY8KQ2oKbMOGDXL8+PES51+9elXXBPXu3VsCAwNLbTc6OlrmzJkjK1as0CNJ+/fvl8cff1zXG5VmzJgxOlzZt8OHD1fY6wQAAO7H0uIYVfszYMAAueuuu8THx0cefPBBHXC2bNnidJ4qiO7Vq5fYbDYdasoSFxfn+LlVq1Y6EKki648//lgGDhzo8ho/Pz+9AQAAM1i6CiwiIkLWrl0rFy9e1KMu2dnZOuyoqavi4efgwYO6Jqis0R9X1HRZ8+bNJScnpxJeAQAAqI7c4j5Aapl7SEiIXun11VdfSUJCglP4UTU9alVXvXr1brltFa727dun2wcAALA8AKmwo2p1VJ2OGt158skn9T17+vfvr8PPc889p5e8L1iwQNcInThxQm/Xrl1ztBEbG6tXh9mNGjVKjyodOHBA1q9fL927d9fTa2pqDQAAwPIaIFVwrAqQjxw5InXr1pUePXpIWlqa1KhRQweYzz77TJ/Xpk0bp+tWr14tTzzxhP5Zje6cOXPGcUy1pcLO2bNn5c4775T27dvLxo0b9c8AAACKl01VFsOJug+QWg6vAtqt1hyVR4eewyu8TQCoDOuWvGd1F4BK+fx2ixogAACAqkQAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMY2kAunDhgowYMUKaNGki/v7+EhMTI5s2bXIct9lsMnbsWAkJCdHHO3bsKHv37r1pu9OnT5emTZtKrVq1JDo6WrKzsyv5lQAAgOrE0gA0aNAgWblypcybN0++//576dSpkw45R48e1ccnTZokU6dOlZkzZ8q3334rAQEB0rlzZ7l69WqpbS5evFhGjhwp48aNk61bt0rr1q31NadOnarCVwYAANyZl00Ns1jgypUrUrt2bVm+fLnEx8c7Hm/btq3ExcVJamqqhIaGyquvviqjRo3Sx3Jzc6Vhw4YyZ84cSUxMdNmuGvF5+OGHJSMjQ+8XFhZKWFiYvPLKKzJ69GiX1+Tn5+vNLi8vT1+jni8wMLCCX7lIh57DK7xNAKgM65a8Z3UXgHJTn99BQUHl+vy2bAToxo0bUlBQoKepilJTXVlZWbJ//345ceKEHhGyUy9KBZwNGza4bPPatWuyZcsWp2u8vb31fmnXKOnp6bpt+6bCDwAA8FyWBSA1+tOuXTs90nPs2DEdhubPn6+DyvHjx3X4UdSIT1Fq336suDNnzuh2buUaZcyYMTot2rfDhw9XyGsEAADuydIaIFX7o2bg7rrrLvHz89P1Pr1799ajNlVJPbcaKiu6AQAAz2VpAIqIiJC1a9fKxYsX9aiLWq11/fp1CQ8Pl+DgYH3OyZMnna5R+/ZjxdWvX198fHxu6RoAAGAet7gPkFrdpZa6nzt3Tr766itJSEiQZs2a6dCSmZnpVNykVoOpqTNXatasqYuoi16jiqDVfmnXAAAA8/ha+eQq7KgpsBYtWkhOTo4kJydLZGSk9O/fX7y8vPQ9giZMmCD33HOPDkQpKSl6ZVi3bt0cbcTGxkr37t3l5Zdf1vtqCXxSUpI89NBD8sgjj8iUKVPk0qVLuk0AAADLA5AqOFYFyEeOHJG6detKjx49JC0tTWrUqKGPv/baazq8vPTSS3L+/Hlp3769rFixwmnl2L59+3Txs93zzz8vp0+f1jdQVIXPbdq00dcUL4wGAADmsuw+QJ5yH4HbwX2AAFQX3AcI1Um1uA8QAACAVQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOP4Wt0BE61b8p7VXQAAwGiMAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGsTQAFRQUSEpKijRr1kz8/f0lIiJCUlNTxWazOc7x8vJyub3zzjultvvmm2+WOD8yMrKKXhUAAHB3vlY++cSJE2XGjBkyd+5cadmypWzevFn69+8vQUFBMmzYMH3O8ePHna755z//KQMHDpQePXqU2bZqb9WqVY59X19LXyoAAHAjlqaC9evXS0JCgsTHx+v9pk2byqJFiyQ7O9txTnBwsNM1y5cvlyeffFLCw8PLbFsFnuLXAgAAWD4FFhMTI5mZmbJnzx69v2PHDsnKypK4uDiX5588eVK+/PJLPQJ0M3v37pXQ0FAdlPr06SOHDh0q9dz8/HzJy8tz2gAAgOeydARo9OjROmyo+hwfHx9dE5SWlqYDiytqqqx27dry7LPPltludHS0zJkzR1q0aKGn0MaPHy+PP/647Ny5U19fXHp6uj4HAACYwctWtOK4in300UeSnJysC5pVzc727dtlxIgRMnnyZElKSipxvgpKTz31lEybNu2Wnuf8+fPSpEkT3a6r0SM1AqQ2OxXKwsLCJDc3VwIDA2/z1QEAgKqkPr9VHXF5Pr8tHQFS4UeNAiUmJur9qKgoOXjwoB6RKR6AvvnmG9m9e7csXrz4lp+nTp060rx5c8nJyXF53M/PT28AAMAMltYAXb58Wby9nbugpsIKCwtLnDtr1ixp27attG7d+paf5+LFi7Jv3z4JCQn5Sf0FAACewdIA1KVLF13zowqbDxw4IEuXLtXTVN27dy8xpLVkyRIZNGiQy3ZiY2MlIyPDsT9q1ChZu3atblOtNFPtqWDVu3fvSn9NAADA/Vk6BaZqedSNEIcOHSqnTp3Sq7YGDx4sY8eOLVErpEqVSgswanTnzJkzjv0jR47oc8+ePSt33nmntG/fXjZu3Kh/BgAAsLQI2hOKqAAAQPX7/Oa7wAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcW7rqzDUF5h6eXmVerygoOCn9AkAAMD9ApD60lIAAACjAlBCQoLT/qeffirbt2+X+++/X3r16lVRfQMAAHDPGqCJEyfqb15fsWKFDBw4UMaPH18xPQMAAHDXADR37lz529/+JtnZ2bJ8+XKZPXt2xfQMAADAXQPQsWPH5NFHH9U/qz+PHj1aEf0CAABw3wCkVnz5+v7/UiIfHx8pLCysiH4BAAC4VxH0Aw884FgGf+XKFenSpYvUrFlTbDZbRfcPAADAPQJQt27dSl0RVvQYAACAO/KyMWxTQl5engQFBUlubq4EBgZa3R0AAFDBn9++t/sEZSE0AAAAd3ZbAahOnTouvwpDDSapx/kqDAAA4HEBSPnkk0+kbt26FdsbAAAAdw5Ajz32mDRo0KBiewMAAODOAeiHH36Qs2fPSkBAgAQHB+tl8AAAAB59I8TY2Fhp2bKlNGvWTIegqKgo+fOf/1yxvQMAAHCXEaD9+/frgufr16/rFWHq6zDUd4GlpKTIjRs3JDk5ueJ7CgAA4I73AZo3b5788Y9/lL1790p1xn2AAACofir9PkClSUxM1NNiAAAA7qzCb4R49913/5T+AAAAVDpuhAgAAIzDjRABAIBxuBEiAAAwDjdCBAAAxrH0RoiqVkjdO0i14e/vLxEREZKamqpriez69eun64qKbk8//fRN254+fbo0bdpUatWqJdHR0fo+RQAAAJbfCHHixIkyY8YMmTt3rg5Tmzdvlv79++s1/MOGDXOcpwLP7NmzHft+fn5ltrt48WIZOXKkzJw5U4efKVOmSOfOnWX37t1M2wEAAGtvhPjMM89Iw4YNZdasWY7HevTooUeD5s+f7xgBOn/+vCxbtqzc/VCh5+GHH5aMjAy9X1hYKGFhYfLKK6/I6NGjb3o9N0IEAKD6uZXP79ueAivtRohq9KW8YmJiJDMzU/bs2aP3d+zYIVlZWRIXF+d03po1a/TITYsWLWTIkCG69qg0165dky1btkjHjh0dj3l7e+v9DRs2uLwmPz9fv2lFNwAA4Lkq9E7QNWrUkAcffLDc56vRGBU2IiMjxcfHR9cEpaWlSZ8+fZymv5599lldJ7Rv3z554403dEBSYUZdU9yZM2d0O2pkqSi1/+OPP7rsR3p6uowfP/6WXisAADAsAKmAoQqeP/74Yzl06JAedSnqf//7X7naUdcvWLBAFi5cqGuAtm/fLiNGjJDQ0FBJSkpyjCrZqULrVq1a6WJpNSqkCrErwpgxY3TNkJ0KZWrKDAAAeKbbmgJToyWTJ0+W559/Xs+zqfCgRmnUVNObb75Z7nZUsbQaBVIhR4WbF198UX73u9/pEZnShIeHS/369SUnJ8flcXVMjQydPHnS6XG1r5bru6KKqtVcYdENAAB4rtsKQGrU5oMPPpBXX31VfH19pXfv3vK3v/1Nxo4dKxs3bix3O5cvX9ahqSgVXlTRcmmOHDmia4BCQkJcHlf3I2rbtq2uLbJT7an9du3albtvAADAc91WADpx4oQesVHuuOMOPQpkX9X15ZdflrudLl266Jofdc2BAwdk6dKlemSpe/fu+vjFixf1KJEKVeq4CjEJCQn6C1fVsnY7NRVmX/GlqBEpFdDU8vpdu3bpwulLly7pJfYAAAC3VQPUqFEjOX78uDRu3FjX4/zrX//Sxc+bNm266T16ipo2bZq+d9DQoUPl1KlTuvZn8ODBeiTJPhr03Xff6SCjlsKr4506ddI3Syz6PKo4WhU/26mpudOnT+t2VFhr06aNrFixokRhNAAAMNNt3QdI1e2oOhm1Ikste3/hhRf0XZdVQbSq4Xn77belOuM+QAAAePbnd4XcCFFNUa1fv17uuecePa1V3RGAAACofqr0Rohq2uvzzz/XU1jqSQEAADyqBkjV/Gzbtk3q1aun91euXCnx8fG6Hket5nr33Xdl0aJF0rNnz8rqLwAAwE92SyNAagm6ugmi3TvvvKOXwKsC5XPnzukC5kmTJv30XgEAAFSinzQFppaYqy8YVau11AiQ+rm8X4QKAABQLQOQGvmpW7euY//nP/+5XLhwoSL6BQAA4B4ByMvLS2/FHwMAAPDYImi1Yr5fv36OmxBevXpVfvOb30hAQIDez8/Pr5xeAgAAWBWA7N/QbqdugFhc3759f3qvAAAA3CUAzZ49u/J6AgAAUEV+8o0QAQAAqhsCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEsDUAFBQWSkpIizZo1E39/f4mIiJDU1FSx2Wz6+PXr1+X111+XqKgoCQgIkNDQUOnbt68cO3aszHbffPNN8fLyctoiIyOr6FUBAAB352vlk0+cOFFmzJghc+fOlZYtW8rmzZulf//+EhQUJMOGDZPLly/L1q1bdUhq3bq1nDt3ToYPHy5du3bV55ZFtbdq1SrHvq+vpS8VAAC4EUtTwfr16yUhIUHi4+P1ftOmTWXRokWSnZ2t91UQWrlypdM1GRkZ8sgjj8ihQ4ekcePGpbatAk9wcHAlvwIAAFAdWToFFhMTI5mZmbJnzx69v2PHDsnKypK4uLhSr8nNzdVTWnXq1Cmz7b179+ops/DwcOnTp48OTKXJz8+XvLw8pw0AAHguS0eARo8ercOGqs/x8fHRNUFpaWk6sLhy9epVXRPUu3dvCQwMLLXd6OhomTNnjrRo0UKOHz8u48ePl8cff1x27twptWvXLnF+enq6PgcAAJjBy2avOLbARx99JMnJyfLOO+/omp3t27fLiBEjZPLkyZKUlOR0riqI7tGjhxw5ckTWrFlTZgAq7vz589KkSRPd7sCBA12OAKnNToWysLAwPdp0K88DAACsoz6/VflMeT6/LR0BUuFHjQIlJibqfbXa6+DBg3pEpmgAUuGnV69e+tjXX399y6FETZc1b95ccnJyXB738/PTGwAAMIOlAUit8vL2di5DUlNhhYWFJcKPqulZvXq11KtX75af5+LFi7Jv3z558cUXxR106Dnc6i7AA61b8p7VXYAH4vcVPPX3laVF0F26dNE1P19++aUcOHBAli5dqqepunfv7gg/zz33nF7yvmDBAl0jdOLECb1du3bN0U5sbKxeHWY3atQoWbt2rW5TrTRT7algpWqHAAAALB0BmjZtmr7Hz9ChQ+XUqVN61dbgwYNl7Nix+vjRo0fls88+0z+3adPG6Vo1GvTEE0/on9XozpkzZxzHVJ2QCjtnz56VO++8U9q3by8bN27UPwMAAFgagNSKrClTpujNFXVfoPLUaKuRnuLF1QAAAKXhu8AAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDiWBqCCggJJSUmRZs2aib+/v0REREhqaqrYbDbHOernsWPHSkhIiD6nY8eOsnfv3pu2PX36dGnatKnUqlVLoqOjJTs7u5JfDQAAqC4sDUATJ06UGTNmSEZGhuzatUvvT5o0SaZNm+Y4R+1PnTpVZs6cKd9++60EBARI586d5erVq6W2u3jxYhk5cqSMGzdOtm7dKq1bt9bXnDp1qopeGQAAcGeWBqD169dLQkKCxMfH69Ga5557Tjp16uQYrVGjP1OmTJE//OEP+rxWrVrJhx9+KMeOHZNly5aV2u7kyZPl17/+tfTv31/uu+8+HZ5+9rOfyd///neX5+fn50teXp7TBgAAPJelASgmJkYyMzNlz549en/Hjh2SlZUlcXFxen///v1y4sQJPe1lFxQUpKe0NmzY4LLNa9euyZYtW5yu8fb21vulXZOenq7btW9hYWEV/EoBAIA78bXyyUePHq1HWyIjI8XHx0fXBKWlpUmfPn30cRV+lIYNGzpdp/btx4o7c+aMbsfVNT/++KPLa8aMGaOnzOxUnwhBAAB4LksD0McffywLFiyQhQsXSsuWLWX79u0yYsQICQ0NlaSkpCrrh5+fn94AAIAZLA1AycnJehQoMTFR70dFRcnBgwf1lJQKQMHBwfrxkydP6lVgdmq/TZs2LtusX7++Hk1S5xSl9u3tAQAAs1laA3T58mVdn1OUCi+FhYX6Z7U8XoUWVSdUdHpKrQZr166dyzZr1qwpbdu2dbpGtaf2S7sGAACYxdIRoC5duuian8aNG+spsG3btukVXAMGDNDHvby89JTYhAkT5J577tGBSN03SE2RdevWzdFObGysdO/eXV5++WW9r+p51AjSQw89JI888oheSXbp0iW9KgwAAMDSAKTu96MCzdChQ/U9elSwGTx4sL7xod1rr72mw8tLL70k58+fl/bt28uKFSv0DQ7t9u3bp4uf7Z5//nk5ffq0bkcVS6vpMnVN8cJoAABgJi9b0dsuwzHNppbD5+bmSmBgYIW336Hn8ApvE1i35D2ruwAPxO8rVKffV7fy+c13gQEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA41gagJo2bSpeXl4ltt/+9rdy4MABl8fUtmTJklLb7NevX4nzn3766Sp9XQAAwL35WvnkmzZtkoKCAsf+zp075amnnpKePXtKWFiYHD9+3On8999/X9555x2Ji4srs10VeGbPnu3Y9/Pzq4TeAwCA6srSAHTnnXc67b/99tsSEREhv/jFL/TITXBwsNPxpUuXSq9eveSOO+4os10VeIpfW5b8/Hy92eXl5ZX7WgAAUP24TQ3QtWvXZP78+TJgwAAdforbsmWLbN++XQYOHHjTttasWSMNGjSQFi1ayJAhQ+Ts2bNlnp+eni5BQUGOTY0+AQAAz+U2AWjZsmVy/vx5XcPjyqxZs+Tee++VmJiYm05/ffjhh5KZmSkTJ06UtWvX6imzolNtxY0ZM0Zyc3Md2+HDh3/y6wEAAO7L0imw4gFHBZXQ0NASx65cuSILFy6UlJSUm7aTmJjo+DkqKkpatWqlp9XUqFBsbGypU2bUCQEAYA63GAE6ePCgrFq1SgYNGuTy+CeffCKXL1+Wvn373nLb4eHhUr9+fcnJyamAngIAAE/gFgFIrdhSNTvx8fGljg517dq1RNF0eRw5ckTXAIWEhFRATwEAgCewPAAVFhbqAJSUlCS+viVn5NTIzbp160odHYqMjNSrw5SLFy9KcnKybNy4Ud9HSNUBJSQkyN133y2dO3eu9NcCAACqB8sDkJr6OnTokF795crf//53adSokXTq1Mnl8d27d+vCZcXHx0e+++47PVrUvHlzvWKsbdu28s0331DjAwAA3KcIWgUbm81W6vG33npLb6Upeq2/v7989dVXFd5HAADgWSwfAQIAAKhqBCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAMYhAAEAAOMQgAAAgHEIQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwjpfNZrNZ3Ql3k5eXJ0FBQZKbmyuBgYFWdwcAAFTw5zcjQAAAwDgEIAAAYBwCEAAAMA4BCAAAGIcABAAAjEMAAgAAxiEAAQAA4xCAAACAcQhAAADAOAQgAABgHAIQAAAwDgEIAAAYhwAEAACMQwACAADGIQABAADj+FrdAXdks9n0n3l5eVZ3BQAAlJP9c9v+OV4WApALFy5c0H+GhYVZ3RUAAHAbn+NBQUFlnuNlK09MMkxhYaEcO3ZMateuLV5eXmI6lahVGDx8+LAEBgZa3R2PxftcNXifqwbvc9XgfXamIo0KP6GhoeLtXXaVDyNALqg3rVGjRlZ3w+2o/7n4H6zy8T5XDd7nqsH7XDV4n//PzUZ+7CiCBgAAxiEAAQAA4xCAcFN+fn4ybtw4/ScqD+9z1eB9rhq8z1WD9/n2UQQNAACMwwgQAAAwDgEIAAAYhwAEAACMQwACAADGIQDBpfT0dHn44Yf13bAbNGgg3bp1k927d1vdLY/39ttv67uPjxgxwuqueKSjR4/KCy+8IPXq1RN/f3+JioqSzZs3W90tj1JQUCApKSnSrFkz/R5HRERIampqub6bCaVbt26ddOnSRd/hWP2OWLZsmdNx9f6OHTtWQkJC9PvesWNH2bt3r2X9rQ4IQHBp7dq18tvf/lY2btwoK1eulOvXr0unTp3k0qVLVnfNY23atEn++te/SqtWrazuikc6d+6cPPbYY1KjRg355z//KT/88IP86U9/kp///OdWd82jTJw4UWbMmCEZGRmya9cuvT9p0iSZNm2a1V2r1tTv3tatW8v06dNdHlfv8dSpU2XmzJny7bffSkBAgHTu3FmuXr1a5X2tLlgGj3I5ffq0HglSwahDhw5Wd8fjXLx4UR588EH5y1/+IhMmTJA2bdrIlClTrO6WRxk9erT8+9//lm+++cbqrni0Z555Rho2bCizZs1yPNajRw89KjF//nxL++Yp1AjQ0qVL9ci8oj7G1cjQq6++KqNGjdKP5ebm6v8Oc+bMkcTERIt77J4YAUK5qP+ZlLp161rdFY+kRtvi4+P1sDUqx2effSYPPfSQ9OzZU4f5Bx54QD744AOru+VxYmJiJDMzU/bs2aP3d+zYIVlZWRIXF2d11zzW/v375cSJE06/P9T3YUVHR8uGDRss7Zs748tQcVOFhYW6JkVNH9x///1Wd8fjfPTRR7J161Y9BYbK89///ldPzYwcOVLeeOMN/X4PGzZMatasKUlJSVZ3z6NG2tQ3lEdGRoqPj4+uCUpLS5M+ffpY3TWPpcKPokZ8ilL79mMoiQCEco1O7Ny5U/8rDhXr8OHDMnz4cF1nVatWLau74/FBXo0AvfXWW3pfjQCpv9eqZoIAVHE+/vhjWbBggSxcuFBatmwp27dv1/+AUlM0vM9wJ0yBoUwvv/yyfPHFF7J69Wpp1KiR1d3xOFu2bJFTp07p+h9fX1+9qTorVcyoflb/ekbFUKtj7rvvPqfH7r33Xjl06JBlffJEycnJehRI1Z2oVXYvvvii/O53v9MrS1E5goOD9Z8nT550elzt24+hJAIQXFJFdSr8qEK7r7/+Wi9pRcWLjY2V77//Xv8r2b6pUQo1XaB+VlMIqBhqCrf4rRxUnUqTJk0s65Mnunz5snh7O3+0qL/HagQOlUP9flZBR9Ve2alpSLUarF27dpb2zZ0xBYZSp73UEPby5cv1vYDs88iqsE6t5kDFUO9t8boqtXxV3aeGequKpUYhVIGumgLr1auXZGdny/vvv683VBx1rxpV89O4cWM9BbZt2zaZPHmyDBgwwOquVfuVojk5OU6Fz+ofSWphinqv1TSjWkF6zz336ECk7sWkph3tK8XggloGDxSn/mq42mbPnm111zzeL37xC9vw4cOt7oZH+vzzz23333+/zc/PzxYZGWl7//33re6Sx8nLy9N/fxs3bmyrVauWLTw83Pb73//elp+fb3XXqrXVq1e7/J2clJSkjxcWFtpSUlJsDRs21H+/Y2Njbbt377a6226N+wABAADjUAMEAACMQwACAADGIQABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAJQqfr161fi+4hOnz6tv+ssOjpacnNzLesbAHMRgABUKRV+fvnLX+ov1f3Xv/6lv2AXAKoaAQhAlTlz5ozExsaKn5+frFy50hF+1LeFR0VFSUBAgISFhcnQoUP1t18ra9asES8vr1I3u6ysLHn88cd1sFJtDBs2TC5duuQ43rRp0xLXjho1ynF8xowZEhERITVr1pQWLVrIvHnznPquzlfnxMXF6ecIDw+XTz75xHH8wIED+hz1Dd126hu51WNTpkxxPPbjjz/KU089pV+7vR916tSp8PcaQNkIQACqxNmzZ6Vjx47i6+urw0/RD31vb2+ZOnWq/Oc//5G5c+fK119/La+99po+FhMTI8ePH9fbP/7xD/2YfV9tyr59++Tpp5+WHj16yHfffSeLFy/Wgejll1926sMf//hHp2vHjRunH1+6dKkMHz5cXn31Vdm5c6cMHjxY+vfvL6tXr3a6XgUa9Rw7duyQPn36SGJiouzatcvl6z1y5IgOPiosFTVgwAC5fv26/Pvf/9Z9KBqOAFQhq7+OHoBnS0pKsnXo0MHWpk0bW40aNWyPPvqo7caNG2Ves2TJElu9evVKPL569Wqbq19bAwcOtL300ktOj33zzTc2b29v25UrV/R+kyZNbH/+859dPl9MTIzt17/+tdNjPXv2tP3qV79y7Kvn/c1vfuN0TnR0tG3IkCH65/379+tztm3bpvf79u2r+1X8ef39/W0LFixw7M+ePdsWFBRU5vsBoOIxAgSg0q1bt04KCwv19FBOTo5MmjTJ6fiqVav01Nhdd90ltWvXlhdffFGPGF2+fLlc7asRmTlz5sgdd9zh2Dp37qyfc//+/Te9Xo3iPPbYY06Pqf3iozvt2rUrse9qBGjr1q16VCk1NbXEsWbNmulj5X1tACqHbyW1CwAOql4mMzNT6tevL3/5y1/khRdekPj4eGnVqpWunXnmmWdkyJAhkpaWJnXr1tXTVwMHDpRr167Jz372s5u2r+qF1LSVqvsprnHjxlLV1FSaqi8KCQkpcWzWrFmSlJSkg56aHrtx44bUqlWryvsImI4RIACVThU4q/Cj9OzZU5599lnp27evDjhbtmzRIzV/+tOf5NFHH5XmzZvLsWPHbqn9Bx98UH744Qe5++67S2yqqPlm7r33Xl2TU5Tav++++5we27hxY4l9dW1Rn332mezZs8epwLoo9Rq7du0qDz30kGzbtk3XJQGoeowAAahy06dP1/cBGj9+vPTq1UsXBU+bNk26dOmig8fMmTNvqb3XX39dBwtV9Dxo0CC9mkwFIlVsnZGRcdPrk5OTdT8eeOABXaj9+eefy6effqqn5opasmSJDi7t27eXBQsWSHZ2th7RKUpN76nXUtrIlSrkVtN1Kvip0akGDRrc0msFUDEYAQJQ5dQ01wcffCATJ06Uq1ev6mXw6mcVilSwSE9Pv6X21FTa2rVr9ciLWgqvgszYsWMlNDS0XNerGzW+99578u6770rLli3lr3/9q8yePVueeOIJp/NUYPvoo4/083344YeyaNGiEqNEatRJTXG5ovqnAtrChQstmZoD8H+8VCV0kX0AgAvqfj2qeLn4Xa0BVE+MAAEAAOMQgAAAgHEoggaAcqBaAPAsjAABAADjEIAAAIBxCEAAAMA4BCAAAGAcAhAAADAOAQgAABiHAAQAAIxDAAIAAGKa/wfFTpisM/Qx6QAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "\n",
+    "df[\"Категория\"] = [1, 2, 6, 11] # догадайтесь откуда df и её содержимое взялось\n",
+    "sns.histplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "fda61745-bc9b-4112-8ef3-9c4fac2f0751",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "\n",
+    "df[\"Категория\"] = [1, 2, 6, 11] # догадайтесь откуда df и её содержимое взялось\n",
+    "sns.scatterplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "2eac5f2b-f14c-4f51-8de9-9808b7950e70",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1000x1000 with 20 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "\n",
+    "df[\"Категория\"] = [1, 2, 6, 11] # догадайтесь откуда df и её содержимое взялось\n",
+    "sns.histplot(x=\"Категория\", y=\"Баллы\", data=df)\n",
+    "sns.pairplot(df)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "9ee43629-88d4-4332-a459-b416539eeb8b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgMAAAGiCAYAAAB6c8WBAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAALeFJREFUeJzt3Qd8VFX2wPETSgqBUAxJqCJFcKUpHUQXZY0SEdb9K7JiAgqKBZEgTYGAihFQyi4gC0hxFQgqVRBkUdcCCIQunSggkEYxECAo8/6fe9mMzCSBZJgwM7m/7//z/uS9efPmxk0yZ8459z4/y7IsAQAAxirm6QEAAADPIhgAAMBwBAMAABiOYAAAAMMRDAAAYDiCAQAADEcwAACA4QgGAAAwHMEAAACGIxgAAMBwBAMAAHiJb775Rjp27CiVK1cWPz8/Wbx48TWf8/XXX8udd94pAQEBUrt2bZk9e3aBX5dgAAAAL5GZmSmNGjWSyZMn5+v8n376SaKioqRdu3aydetWefnll6Vnz56yatWqAr2uHzcqAgDA+6jMwKJFi6Rz5855njNo0CBZvny57Ny5037s8ccfl9OnT8vKlSvz/VpkBgAAKERZWVmSkZHhsKlj7rBu3Tpp3769w7HIyEh9vCBKiJf4LT3J00MAvE5Q5baeHgLglX6/eNRn3pPiJ30gI0eOdDgWFxcnI0aMuO5rJycnS3h4uMMxta8CjvPnz0tQUJBvBQMAAHgN2yW3XWrIkCESGxvrcEw1+3kTggEAAAqReuMvrDf/iIgISUlJcTim9kNCQvKdFVAIBgAAcGbZxBe0atVKVqxY4XBs9erV+nhB0EAIAIAzm819WwGcPXtWTxFUW/bUQfX14cOH7SWH6Oho+/m9e/eWpKQkGThwoOzZs0emTJkiCxYskH79+hXodckMAADgxPJQZmDTpk16zYBs2b0GMTExejGh48eP2wMD5ZZbbtFTC9Wb/8SJE6Vq1aoyY8YMPaPAJ9cZYDYBkBOzCQDPzCa4eOxHt13Lv/Lt4u3IDAAA4KyA6X1fRzAAAICPNhC6Cw2EAAAYjswAAACFuOiQLyAYAADAGWUCAABgEjIDAAA4YzYBAABmsygTAAAAk5AZAADAGWUCAAAMZxEMAABgNptZ6wzQMwAAgOHIDAAA4IwyAQAAhrOZFQxQJgAAwHBkBgAAcEaZAAAAw9nMCgYoEwAAYDgyAwAAOLEss9YZIBgAAMDwngHKBAAAGI7MAAAAhjcQEgwAAGB4mYBgAAAAZ9yoCAAAmITMAAAAzigTAABgOJtZwQBlAgAADEdmAAAAZ5QJAAAwnM2sYIAyAQAAhiMzAACA4ZkBggEAAAy/ayFlAgAADEdmAAAAZ5QJAAAwnEUwAACA2WxmBQP0DAAAYDgyAwAAOKNMAACA4WxmBQOUCQAAMByZAQAAnFEmAADAcDazggHKBAAAGI7MAAAAhmcGCAYAADC8Z4AyAQAAhiMzAACAM8oEAAAYziIYAADAbDazggF6BgAAMByZAQAAnFEmAADAcDazggHKBAAAGI7MAAAAhmcGCAYAAHBmWWISygQAABiOzAAAAIaXCVzKDHzzzTfy+++/u380AAB4SzBgc9NWVIOBdu3aycmTJ90/GgAA4BvBgGVYYwUAwMBFhyw3bQU0efJkqVGjhgQGBkqLFi1kw4YNVz1/woQJUrduXQkKCpJq1apJv3795MKFCzemZ2DdunVSvnz5XB+7++67Xb0sAACeZ/NMej8hIUFiY2Nl6tSpOhBQb/SRkZGyd+9eCQsLy3H+3LlzZfDgwTJz5kxp3bq17Nu3T7p37y5+fn4ybty4fL+un+XCx/xixfJOKKgBXLp0qaCXlN/Skwr8HKCoC6rc1tNDALzS7xePFur1z88Z7LZrFXt8pGRlZTkcCwgI0JszFQA0a9ZMJk2apPdtNpv+tN+nTx/9pu/sxRdflN27d8uaNWvsx/r37y8//PCDfPfdd/kfo7goOTlZD9J5cyUQAACgqIqPj5eyZcs6bOqYs4sXL0piYqK0b9/e4cO32lfZ+NyobIB6TnYpISkpSVasWCEdOnQo/DKB+vQPAECRZXNfmWDIkCE69X+l3LIC6enp+gN1eHi4w3G1v2fPnlyv/fe//10/76677tL9fGqmX+/eveXVV18t0BhpIAQAoBCnFqo3/pCQEIctt2DAFV9//bW89dZbMmXKFNm8ebMsXLhQli9fLm+88UbhZwZUOQAAALhPaGioFC9eXFJSUhyOq/2IiIhcnzNs2DB58sknpWfPnnq/QYMGkpmZKc8884y89tprV+3xu+7MgKp1qM5FZ+rY6NGjXbkkAABGTy309/eXJk2aODQDqg/far9Vq1a5PufcuXM53vBVQFHQLL5LwcC//vUvqVevXo7jt99+u54OAQCAL7Nsltu2glC9BdOnT5c5c+boWQLPPfec/qTfo0cP/Xh0dLTuQcjWsWNHee+992T+/Pny008/yerVq3W2QB3PDgoKrUygZhJUqlQpx/GKFSvK8ePHXbkkAADG69Kli6Slpcnw4cP1e23jxo1l5cqV9qbCw4cPO2QChg4dqpv61b9Hjx7V78MqEBg1alSBXteldQbq1KkjcXFx0q1bN4fj//73v/VxNbWhoFhnAMiJdQYAz6wzcG5qX7ddq1TvieLtXMoM9OrVS15++WX57bff5N5779XHVE1j4MCBerEDAAB8mmVWo7xLwcCAAQPkxIkT8vzzz+tFEhS1hvKgQYMcahkAAMD7uVQmyHb27Fnd4KBujqBKB9czb5IyAZATZQLAQ2WCyS+67VqlXri8tLA3c/lGRUrp0qX1GsoAABQpNsoE+bJp0yZZsGCB7mzMLhVkUysgAQDgs2xmBQMurTOg5jOqmyOoEsGiRYt0I+GPP/4oX375pb4BAwAAKOLBgFoHefz48bJs2TK9YtLEiRP1TRQee+wxqV69uvtHCQDAjWRZ7tuKajBw8OBBiYqK0l+rYECtjqQWPejXr59MmzbN3WMEAMBnb1RUZIOB8uXLy5kzZ/TXVapUkZ07d+qvT58+rddJhu/ZtHWHvDAwTto9/ITUb/OgrPlmraeHBLjdiLhX5MihzXLm1wOy6vP5Urv2Ldd8znO9Y+TAvvVyNuOgrP1umTRr2tjh8SmTR8ve3d/rax4/ul0WfjpT6tat5XDO+HGvyw/rP5fMM0myaeMXbv++AI8EA3fffbde/1h59NFHpW/fvnohoq5du8p999133YPCjXf+/AWpW7umvNb/eU8PBSgUA155Xl584Sl5/sXB0vqujpJ57pys+Oyjq06JfvTRh+WdsXHyxpvjpFmLB2Tb9l2yYvlHUrHiTfZzNm/eLj17xUr9hn+WDlF/11nSz5fPy3HzmNmz58uCj5cV6vcIN7JZ7tuK6joDJ0+elAsXLkjlypX1HZXGjBkja9eu1WsNqPWRVeagoFhnwHuozMDE+GFy392tPT0U47HOgPuojMD4Cf+SceP/pfdDQsrIsV+2ylM9+8mCBUtzfY7KBGzctE36vjxU76s3+p+TNsrkKbNkzNjJuT6nQYPbZEvif+TWeq0lKemQw2PDh8XKww8/IE2b3e/27880hb7OwNin3HatUgNy3uW3SEwtrFChgv1rFf0OHjzYnWMCALe65ZbqUqlSuKz58jv7sYyMM7JhwxZp2aJJrsFAyZIl5c47G8rbY/5YMEZ9dlLXaNmySa6vU6pUkHSP7qKDgCNHjhXSdwN40ToDly5d0tMK1fRC5U9/+pN06tRJSpS49iWzsrL0dqViWVnXtYIhAOQlIjxM/5uSkuZwPCU1XSIiLj/mLDS0gv57lpqS7nA8NTVN6jn1BPR+Nkbejn9NSpcOlj17D8gDHbrqKdfwYTbfSO97tGdArSlw6623SkxMjA4I1Ka+VmWC7GbCq4mPj9frEVy5jZ441ZWhAEAOXbv+VU6f3GffSpa8rsVWr2nuvIXStHmktLv3Edm/P0nmzZ3KhxsfZ9lsbtt8gUu/IT179pTbb79dr0KY3R9w6tQp6d69uzzzzDO6f+Bq1M2MYmNjHY4VO1O49R8A5li27AtdAsgWEOCv/w0PryjJyan24+FhobJ124+5XiM9/aT8/vvvEhYe6nA8LKyiJDtlGFTJQW0HDvwk63/YLOmpu6Rz5wckIWGJm78zwIuCga1btzoEAor6etSoUfm6V4GKmJ2j5t8uOqbiAMBVZ89m6u1Kx4+nyL3t7pJt/3vzL1OmtDRvfodMnfZBrtdQaX41U0A9Z+nSVfYGQrU/5b1Zeb62OkdtAf5kBnyazawygUvBgCoRpKSk6OzAlVJTU6V27druGhtuoHPnzsvhX/5oeDp6LEX27DsoZUPKSKU8aqqAL/nHP2fIq0Nekv0HkuTnn4/IyBED5NixFFmy5PIbvfLFygRZvORzmfLebL0/fuJ0mfX+eEncvF02btwiL/XpJcHBQTJ7ToK9MfGxRx+W1av/K2npJ6RqlcoycOALeqru5yvX2K9bq1YN3U8QHh4mQUGB0qjR5b+du3bto7fAW1m+kd73aDCgav4vvfSSjBgxQlq2bKmPrV+/Xl5//XUZPXq0ZGRk2M8NCQlx32hRaHbu2S9P9Rlk3x/zz8srSXZ6sL2MGtrfgyMD3GPsO1MkOLiUTJ0yRsqVC5Hvv98oUR27OTQz16x5s24czPbxx0ulYmgFGTH8FYmIqKizClEPdZPU1MuZzAsXsuSuNs3lpT49pXz5spKSki7ffrde2t7TSdLSTtivM23qWLnnnj+m6ib+b+GhWnVayKFDv9yg/wIoEJtZmQGX1hm4cjENlQ5Tsi9z5b76Ws06yA/WGQByYp0BwDPrDGS+/oTbrhU8/CMpkpmBr776yv0jAQDAW9goE1zTPffc4/6RAADgLWxmlQlcWmdA+fDDD2XOnDm6HPDf//5X9xDMnn256QYAABTxzIBafljdqrhUqVKyefNmmT9/vrRp00ZmzZqlZxkMGvRHIxoAAD7HMqtMUMzVrMC8efPk22+/lUmTJsmECRNk4cKF8t5778nMmd5/QwYAAK7KZtZdC13KDKSlpek1BqpWrSqBgYHSpMnlm3a0bdtWjhw54u4xAgAAbwsGQkNDJT09XQcD6pbFYWGXF6XJzMyUMmXKuHuMAADcUBazCa4tOjpaTp8+bb/PQDbVSJif5YgBAPBqNt9I73t00aHCwKJDQE4sOgR4ZtGhs4Mecdu1So9eKN7uuu7rqXoH9u7dq7+uW7euVKxY0V3jAgDAc2xe8TnZu2cTqN6Ap556SipXrix333233tTXTz/9tJw7d879owQA4EZPLbTctBXVYCA2Nlb3ByxdulT3DqhtyZIl+lj//tzUBgDg42xMLbymTz/9VD755BP585//bD/WoUMHCQoKkscee0yvNwAAAKToBgOqFBAeHp7juJpiSJkAAODrLB/5RO/RMkGrVq0kLi5OLly4YD92/vx5GTlypH4MAACfZqNMcE0TJ06UyMhIvehQo0aN9LFt27ZJQECAfPHFF+4eIwAA8LZgoH79+rJ//3756KOPZM+ePfpY165d5YknntB9AwAA+DSbb8wC8GiZ4MSJE/qOhb169ZK+fftKcHCwXm9g06ZN7h8hAAA3ms2sMkGBgoEdO3ZIjRo1dKNgvXr1ZOvWrdK8eXMZP368vqVxu3btZPHixYU3WgAA4NlgYODAgdKgQQP55ptv9LTChx56SKKiouTXX3+VU6dOybPPPitvv/22+0cJAMCNZDMrM1CgexOouxV++eWX0rBhQzl79qyEhITIxo0b7bcwVv0DLVu2tN/EqCC4NwGQE/cmADxzb4KMZyPddq2Qf62SIpUZOHnypEREROivS5curXsFypcvb39cfX3mzBn3jxIAAHjPbAI/P7+r7gMA4PNsvpHe91gw0L17d72egKIWHerdu7fOEChZWVnuHyEAADeajWAgTzExMQ773bp1y3FOdHT09Y8KAAAPsggG8jZr1qzCGwkAAPCdFQgBACjSbGQGAAAwm02M4tJyxAAAoOggMwAAgBMaCAEAMJ3NrGCAMgEAAIYjMwAAgOENhAQDAAAY3jNAmQAAAMORGQAAwBllAgAAzGYZViYgGAAAwPDMAD0DAAAYjswAAABOLMMyAwQDAAA4MywYoEwAAIAXmTx5stSoUUMCAwOlRYsWsmHDhquef/r0aXnhhRekUqVKEhAQILfeequsWLGiQK9JZgAAAC8pEyQkJEhsbKxMnTpVBwITJkyQyMhI2bt3r4SFheU4/+LFi/KXv/xFP/bJJ59IlSpV5NChQ1KuXLkCva6fZVleMX/it/QkTw8B8DpBldt6egiAV/r94tFCvX565D1uu1boqv/m+1wVADRr1kwmTZqk9202m1SrVk369OkjgwcPznG+ChrGjh0re/bskZIlS7o8RsoEAAAUoqysLMnIyHDY1LHcPuUnJiZK+/bt7ceKFSum99etW5frtZcuXSqtWrXSZYLw8HCpX7++vPXWW3Lp0qUCjZFgAACAXMoE7tri4+OlbNmyDps65iw9PV2/ias39Sup/eTk5FzHmZSUpMsD6nmqT2DYsGHy7rvvyptvvlmg75eeAQAACrFnYMiQIboP4Eqq0c8dVBlB9QtMmzZNihcvLk2aNJGjR4/q0kFcXFy+r0MwAABAIQYD6o0/P2/+oaGh+g09JSXF4bjaj4iIyPU5agaB6hVQz8t222236UyCKjv4+/vna4yUCQAA8ALqjVt9sl+zZo3DJ3+1r/oCctOmTRs5cOCAPi/bvn37dJCQ30BAIRgAAMCZ5ee+rQBUOWH69OkyZ84c2b17tzz33HOSmZkpPXr00I9HR0frskM29fjJkyelb9++OghYvny5biBUDYUFQZkAAAAvWWegS5cukpaWJsOHD9ep/saNG8vKlSvtTYWHDx/WMwyyqWmHq1atkn79+knDhg31OgMqMBg0aFCBXpd1BgAvxjoDgGfWGUi++89uu1bEN1+LtyMzAACAE8tWsPS+ryMYAADA8LsW0kAIAIDhyAwAAODEKuAsAF9HMAAAgBPKBAAAwChkBgAAcMJsAgAADGd5xQo8Nw7BAAAAhmcG6BkAAMBwZAYAADA8M0AwAACA4T0DlAkAADAcmQEAAJxQJgAAwHCWYcsRUyYAAMBwZAYAADD83gQEAwAAOLFRJgAAACYhMwAAgOENhAQDAAA4YWohAACGs1iBEAAAmITMAAAATigTAABgOJthDYSUCQAAMByZAQAAnDC1EAAAw1nMJgAAACYhMwAAgOENhAQDAAAY3jNAmQAAAMORGQAAwPAGQoIBAACc0DPgIUGV23p6CIDXOX/sW08PATCSZVgwQM8AAACG85rMAAAA3sJmWGaAYAAAACeG9Q9SJgAAwHRkBgAAcEKZAAAAw1mGBQOUCQAAMByZAQAAnNjELAQDAAA4sYQyAQAAMAiZAQAAnNgMW2iAYAAAACc2w8oEBAMAADihZwAAABiFzAAAAE6YWggAgOEsygQAAMAkZAYAAHBCmQAAAMPZxCyUCQAAMByZAQAADG8gJBgAAMCJzaxYgDIBAACmIzMAAIAT7k0AAIDhLDELwQAAAE6YWggAADxm8uTJUqNGDQkMDJQWLVrIhg0b8vW8+fPni5+fn3Tu3LnAr0kwAACAE5ufn9u2gkhISJDY2FiJi4uTzZs3S6NGjSQyMlJSU1Ov+ryff/5ZXnnlFWnbtq24gmAAAIBcegbctRXEuHHjpFevXtKjRw/505/+JFOnTpVSpUrJzJkz83zOpUuX5IknnpCRI0dKzZo1xRUEAwAAFKKsrCzJyMhw2NQxZxcvXpTExERp3769/VixYsX0/rp16/K8/uuvvy5hYWHy9NNPuzxGggEAAHJpIHTXFh8fL2XLlnXY1DFn6enp+lN+eHi4w3G1n5ycLLn57rvv5P3335fp06fL9WA2AQAAhbgC4ZAhQ3QfwJUCAgKu+7pnzpyRJ598UgcCoaGh13UtggEAAAqReuPPz5u/ekMvXry4pKSkOBxX+xERETnOP3jwoG4c7Nixo/2YzXZ5UmSJEiVk7969UqtWrXyNkTIBAAC5rEDori2//P39pUmTJrJmzZo/xmGz6f1WrVrlOL9evXqyY8cO2bp1q317+OGHpV27dvrratWq5fu1yQwAAOAlKxCqckJMTIw0bdpUmjdvLhMmTJDMzEw9u0CJjo6WKlWq6J4DtQ5B/fr1HZ5frlw5/a/z8WshGAAAwEt06dJF0tLSZPjw4bppsHHjxrJy5Up7U+Hhw4f1DAN387MsyyuWYC7hX8XTQwC8zvlj33p6CIBXKhnq2nz6/PqgSje3XSv66Ifi7cgMAABg+L0JCAYAAHDiFSnzG4jZBAAAGI7MAAAAhbjokC8gGAAAwPCeAcoEAAAYjswAAACGZwYIBgAAcGIZ1jNAmQAAAMORGQAAwAllAgAADGcTs1AmAADAcGQGAAAwfDliggEAAJywAiEAAIaziVnoGQAAwHBkBgAAMDwzQDAAAIDhDYSUCQAAMByZAQAAnDCbAAAAw9nELJQJAAAwHJkBAAAMbyAkGAAAwInNsHCAMgEAAIYjMwAAgOENhAQDAAA4MatIQDAAAICYnhmgZwAAAMORGQAAwAkrEAIAYDibYV0DlAkAADAcmQEAAJyYlRcgGAAAIAdmEwAAAKOQGQAAwPAGQpeCgWLFiomfX97zLi5dunQ9YwIAwKMsMYtLwcCiRYvcPxIAAOA7wUCnTp0c9hcuXChbt26V+vXry2OPPeausQEA4BE2Mct1NxCOHj1aunbtKitXrpSnn35aRo4c6Z6RAQDgwZ4Bm5s2I4KBOXPmyIwZM2TDhg2yZMkSmTVrlntGBgCAh1hu3IwIBo4dOyYtW7bUX6t/jx496o5xAQAAX5laqGYOlChx+TLFixcXm820SgsAoKixiVlcCgbuuOMO+9TC8+fPS8eOHcXf318sy1cSIgAA5M3ymQS/B4OBzp075zmz4MrHAABAEQ0G4uLi3D8SAAC8hE3M4lIwkJGRcdXHQ0JCXB0PAAAeZ6NMcG3lypXLdTli1TOgjrMcMQAABswm+OSTT6RChQruHQ0AAF7AErO4HAy0adNGwsLC3DsaAAC8gM2wcMDlRYd27dolu3fvlsOHD8vFixfdOypclxFxr8iRQ5vlzK8HZNXn86V27Vuu+ZznesfIgX3r5WzGQVn73TJp1rSxw+NTJo+Wvbu/19c8fnS7LPx0ptStW8vhnPHjXpcf1n8umWeSZNPGL9z+fQE32qatO+SFgXHS7uEnpH6bB2XNN2s9PSTAu4KB++67T26//Xa55ZZbJDg4WBo0aCDjx4937+hQYANeeV5efOEpef7FwdL6ro6See6crPjsIwkICMjzOY8++rC8MzZO3nhznDRr8YBs275LViz/SCpWvMl+zubN26Vnr1ip3/DP0iHq77o35PPl8/TtrK80e/Z8WfDxskL9HoEb5fz5C1K3dk15rf/znh4KPDCbwOamrciWCX766SfdLPjbb7/pmQVqSWJ1b4Jhw4bJ77//LgMGDHD/SJEvL/XpKW/FT5Rlyy5/Mu/eo68c+2WrdOoUKQsWLM31Of369pIZ78+VOR8s0PvPvzBYOjx4n/To/riMGTtZH5vx/kf28w8d+kWGx42RLYn/kRo1qklS0qHL14kdrv9VQUSDBrcV+vcKFLa2rZrpDeaxKBNc28033yw1atSQOnXqSJMmTfQKhG+88Ya89957Mm3aNPePEvlyyy3VpVKlcFnz5Xf2YxkZZ2TDhi3SskWTXJ9TsmRJufPOhrLmy2/tx1Sgp67RsmXuzylVKki6R3fRQcCRI8cK4TsBAM+ykRlw3eOPP65LB9eSlZWlt9ymJcJ1EeGXGzpTUtIcjqekpktERO7NnqGhFfS9JVJT0h2Op6amST2nnoDez8bI2/GvSenSwbJn7wF5oENXnR0CABiYGVClgdw2dZ+C2rVrX/P58fHxUrZsWYfNsp1xZShG69r1r3L65D77VrKkW2O7HObOWyhNm0dKu3sfkf37k2Te3KlX7UUAAF8uE1hu+j9f4JFFh4YMGSKxsbEOx8rfVM+VoRhN9QWoEkC2gAB//W94eEVJTk61Hw8PC5Wt237M9Rrp6Sd1n0dYeKjD8bCwipLslGFQJQe1HTjwk6z/YbOkp+6Szp0fkISEJW7+zgDAs2xiFo8sOqQ+TTp/oqREUHBnz2bq7UrHj6fIve3ukm3/e/MvU6a0NG9+h0yd9kGu11BpfjVTQD1n6dJV9v8t1P6U92bl+drqHLUF+JMZAABfx6JDRcw//jlDXh3ykuw/kCQ//3xERo4YIMeOpciSJZff6JUvVibI4iWfy5T3Zuv98ROny6z3x0vi5u2yceMWealPLwkODpLZcxLsjYmPPfqwrF79X0lLPyFVq1SWgQNf0NOuPl+5xn7dWrVq6H6C8PAwCQoKlEaNLveP7Nq1j94C+KRz587L4V/+aJI9eixF9uw7KGVDykilPPpwUDTYLN9I73s8GFCLDp04cUKvMRARESH+/pdT1PCsse9MkeDgUjJ1yhgpVy5Evv9+o0R17ObQsFmz5s26cTDbxx8vlYqhFWTE8FckIqKizipEPdRNUlMvNxVeuJAld7Vprqctli9fVlJS0uXb79ZL23s6SVraCft1pk0dK/fc09q+n/i/hYdq1WmhpyMCvmbnnv3yVJ9B9v0x/7w8W6rTg+1l1ND+HhwZCpslZvGzVKG/gNRCMypFnN0joPbr1asnTz31lPTr18+lgZTwr+LS84Ci7PyxP6Z8AvhDydCahXr9bjc/4rZrfXhooRTJ2QRq0aGDBw/K3r179WJDCxculM6dO+tFh8aOHev+UQIAcIPvTWBz01ZQkydP1mv5BAYGSosWLfT7bF6mT58ubdu2lfLly+utffv2Vz0/Lyw6BACAl0wtTEhI0LPt4uLiZPPmzdKoUSOJjIyU1NQ/Zohd6euvv5auXbvKV199JevWrZNq1arJ/fffL0ePHi38MkFeVJPYjh075M477yzwcykTADlRJgA8UyboenNnt11r9r6EHAvt5TarTlGZgGbNmsmkSZP0vs1m02/wffr0kcGDB1/ztdTUfpUhUM+Pjo4u/BsV5b20bcEDAQAAiupyxPG5LLSnjjlTdwBOTEzUqf5sqidP7atP/flx7tw5/cG8oFP/XZpNoCIPdYfCBQsW5HoL45MnT7pyWQAAvILNjfMJcltoL7esQHp6un5/DQ8Pdziu9vfs2ZOv1xo0aJBUrlzZIaAotMzAyJEjZdy4cdKlSxf59ddf9Tf5yCOP6AhmxIgRrlwSAIAi2TMQEBAgISEhDlthLOX+9ttvy/z582XRokW6+bDQg4GPPvpIdzD2799f3+RGNS/MmDFDhg8fLuvXr3flkgAAGC00NFSKFy8uKSkpDsfVvlrP52reeecdHQx88cUX0rBhwwK/tkvBQHJysjRo0EB/Xbp0aZ0dUB566CFZvny5K5cEAMDoWxj7+/vrGXpr1vyxsqtqIFT7rVq1yvN5Y8aM0TP6Vq5cKU2bNnXp+3UpGKhataocP35cf12rVi0diSgbN27kLnYAAJ9nWZbbtoJQZXeVeZ8zZ47s3r1bnnvuOcnMzJQePXrox9UMAdWDkG306NF6jZ+ZM2fqKf/qw7razp49W/gNhH/96191pKKmQKjpDt26dZP3339fNxO6ugIhAACm69Kli6Slpemyu3pTb9y4sf7En91UqN5nVX9eNrW+j2ri/7//+z+H66h1CgrSw+eWdQZUn8DatWv1IkRqASJXsM4AkBPrDACeWWegU/WH3HatJYc/E2933esMqNLAsmXL9OpIau4kAAC+zuaBngFPKlCZoHr16rJlyxa56aab9P7q1aslKipK9wmotIXqZpw3b548+uijhTVeAADgyczAL7/8ohdEyKZuSqSmFZ4+fVpOnTolzz77rO5qBADAl1keujeBT5YJVKejaiBU8yJVZkB9vX//fveNDgAAw+5a6HPBgMoIXLn+sbo5wpkzZ9wxLgAA4I09A35+fnpzPgYAQFFiue+GvkUvGFD/cbp3725fWOjChQvSu3dvCQ4O1vvOt2gEAMAX2cQsBQoGYmJiHPbVYkPOCnL/ZAAAvJHlI7V+jwQDs2bNKryRAAAAj3BpOWIAAIoyG5kBAADMZhnWQHjdyxEDAADfRmYAAAAnlAkAADCcZVgwQJkAAADDkRkAAMCJzbAGQoIBAACcmBUKUCYAAMB4ZAYAAHDCbAIAAAxnIxgAAMBslmENhPQMAABgODIDAAA4oUwAAIDhLMOCAcoEAAAYjswAAACGNxASDAAAYHjPAGUCAAAMR2YAAAAnlAkAADCcjTIBAAAwCZkBAAAMX2eAYAAAACc2egYAADCbZVhmgJ4BAAAMR2YAAAAnlAkAADCcRZkAAACYhMwAAABOKBMAAGA4izIBAAAwCZkBAACcUCYAAMBwFmUCAABgEjIDAAA4sSybmIRgAAAAJzbDygQEAwAAOLEMayCkZwAAAMORGQAAwAllAgAADGdRJgAAACYhMwAAgBNWIAQAwHCWYT0DlAkAADAcmQEAAAxvICQYAADA8KmFlAkAADAcmQEAAJxQJgAAwHA2ggEAAMxmGRYM0DMAAIAXmTx5stSoUUMCAwOlRYsWsmHDhque//HHH0u9evX0+Q0aNJAVK1YU+DUJBgAAyGU2gbu2gkhISJDY2FiJi4uTzZs3S6NGjSQyMlJSU1NzPX/t2rXStWtXefrpp2XLli3SuXNnve3cubNAr+tneUkupIR/FU8PAfA654996+khAF6pZGjNQr1+SLD7rp+RmZTvc1UmoFmzZjJp0iS9b7PZpFq1atKnTx8ZPHhwjvO7dOkimZmZ8tlnn9mPtWzZUho3bixTp07N9+uSGQAAoBBlZWVJRkaGw6aOObt48aIkJiZK+/bt7ceKFSum99etW5frtdXxK89XVCYhr/PzQjAAAEAuswnctcXHx0vZsmUdNnXMWXp6uly6dEnCw8Mdjqv95ORkyY06XpDz88JsAgAACvFGRUOGDNF9AFcKCAgQb0IwAABAIVJv/Pl58w8NDZXixYtLSkqKw3G1HxERketz1PGCnJ8XygQAABRimSC//P39pUmTJrJmzZo/xmGz6f1WrVrl+hx1/MrzldWrV+d5fl7IDAAA4MRTE+1UOSEmJkaaNm0qzZs3lwkTJujZAj169NCPR0dHS5UqVew9B3379pV77rlH3n33XYmKipL58+fLpk2bZNq0aQV6XYIBAAC8hJoqmJaWJsOHD9dNgGqK4MqVK+1NgocPH9YzDLK1bt1a5s6dK0OHDpVXX31V6tSpI4sXL5b69esX6HVZZwDwYqwzAHhmnYGAwGpuu1bWhSPi7cgMAADgxEs+J98wBAMAABgeDDCbAAAAw5EZAADAiVl5AS9qIIR3UOtlqykrasUsb1shC/AUfi9Q1BEMwIG6gYZaN/vXX3+VkJAQTw8H8Ar8XqCoo2cAAADDEQwAAGA4ggEAAAxHMAAHqjkqLi6OJingCvxeoKijgRAAAMORGQAAwHAEAwAAGI5gAAAAwxEMAABgOIIBAAAMRzDgA7p37y5+fn727aabbpIHHnhAtm/f7umhAV7/+5K9Va1a1dNDA7wWwYCPUG/+x48f19uaNWukRIkS8tBDD3l6WIDX/75kb1u2bPH0sACvRTDgI9RiJxEREXpr3LixDB48WI4cOSJpaWn68R07dsi9994rQUFBOnPwzDPPyNmzZ+3PV+dXrlxZ/P39pUqVKjJo0CCx2Wz6sa+//lp/clq+fLk0bNhQAgMDpWXLlrJz507780+cOCFdu3bVzy1VqpQ0aNBA5s2b5zBGdb0xY8ZI7dq19XirV68uo0aN0o/l9kkte1OvDxTW70v2VrFiRfvj6uf/1ltv1T/LNWvWlGHDhslvv/3mcI2ff/4515/X06dP5/ucESNG6N/X3CxevFifC3gDggEfpN7kP/zwQ/2mq974MzMzJTIyUsqXLy8bN26Ujz/+WP7zn//Iiy++aH/O/fffL5999pkcOHBAZsyYIdOmTdPXuNKAAQPk3Xff1ddQfzg7duxo/wN54cIFadKkiQ4YVJCggo0nn3xSNmzYYH++ur3r22+/rf+w7tq1S+bOnSvh4eH6sSs/oSmffvqpfb9169Y36L8ccFmZMmVk9uzZ+ud04sSJMn36dBk/frzDOdnrsanfJfVzqn5mneXnHMAnqBUI4d1iYmKs4sWLW8HBwXpT/7NVqlTJSkxM1I9PmzbNKl++vHX27Fn7c5YvX24VK1bMSk5OznG9pKQk/fyZM2fq/a+++kpfc/78+fZzTpw4YQUFBVkJCQl5jisqKsrq37+//jojI8MKCAiwpk+ffs3vR72Wek3gRvy+VKlSxWrfvr21atWqPJ8zduxYq0mTJg7H9u7dq39Wd+7c6fB7curUqXyfExcXZzVq1CjX11y0aJE+F/AGZAZ8RLt27WTr1q16U5/GVSbgwQcflEOHDsnu3bulUaNGEhwcbD+/TZs2Om2/d+9e+7G33nrLnhb929/+JtHR0Q6v0apVK/vXFSpUkLp16+prK5cuXZI33nhDlwfUY6VLl5ZVq1bJ4cOH9ePqvKysLLnvvvtuwH8NIP+/LwsXLpRKlSpJVFSU/PDDD/rxhIQE/TuiygfqZ3no0KH2n+VsGRkZ+t8rf6+c5eccVcJTr1G2bFm57bbbdPYM8DYlPD0A5I/6Y6PKAtlUql/9cVHpzfzq3bu3PPLII5KYmCgvv/yy/lr90cyPsWPH6nTqhAkTdECgxqOucfHiRf246lUAvPX3ZebMmTooUHV6FSQ/8cQTMnLkSB1Uq9+j+fPn6xLZlY4dOybFihXTAUNe8nOOCqqXLl2qA+r169dLr1699NhUEzDgLcgM+CjVeKT+CJ0/f15/2ti2bZvuHcj2/fff68fVH6Js6hN9vXr19B/Cu+66K0d9U/2hynbq1CnZt2+fvnb29Tp16iTdunXTWQiVXVCPZ6tTp44OCNRMB8DbqN8Ftak35LVr18rNN98sr732mjRt2lT/7KoMmzPVO6N+X1RDbV7yc45q2lVv/up3MSYmRv/+qIwF4E0IBnyESsEnJyfrTaXk+/TpoxsJVZOfenNXf4zUHxrV3PfVV1/px1WDX3YD35QpU+THH3/U3c+qcXD16tVyxx13OLzG66+/rt/M1TXUXO3Q0FDp3Lmzfkz9wVTPUX9I1es/++yzkpKSYn+uen3VoT1w4ED54IMP5ODBgzq4eP/992/wfykg79+XDh066J9lVRJQ2QD1c/qPf/xDFi1aZH+uynb9+9//lnHjxkmPHj1yvX5+zsmm2mRUA64K1r/88kvdtFi/fn23f8/AdfF00wLy1xCl/qfK3sqUKWM1a9bM+uSTT+znbN++3WrXrp0VGBhoVahQwerVq5d15swZ++MdOnSwQkNDdZNf7dq1rVGjRlk2m82h6WnZsmXW7bffbvn7+1vNmze3tm3b5tBQ2KlTJ6t06dJWWFiYNXToUCs6Olofy3bp0iXrzTfftG6++WarZMmSVvXq1a233norx/dDAyFu9O/LnXfeac2bN89+zoABA6ybbrpJ/zx36dLFGj9+vFW2bFn92KZNm6yaNWta8fHx+mc625XNgfk5J7uBMHscqqG3WrVq1rBhw/RjNBDCm/ip/3d94QR8nZrnr3oHVGmgXLlynh4OAOAGo0wAAIDhCAYAADAcZQIAAAxHZgAAAMMRDAAAYDiCAQAADEcwAACA4QgGAAAwHMEAAACGIxgAAMBwBAMAAIjZ/h9IjDEi1cTuEQAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "\n",
+    "data = {\n",
+    "    \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
+    "    \"Возраст\": [21, 22, 23, 24],\n",
+    "    \"Баллы\": [89, 76, 95, 82]\n",
+    "}\n",
+    "df = pd.DataFrame(data)\n",
+    "sns.histplot(x=\"Возраст\", y=\"Баллы\", data=df)\n",
+    "\n",
+    "numeric_df = df.select_dtypes(include=['number'])\n",
+    "sns.heatmap(numeric_df.corr(), annot=True)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "3d37f39d-d5d8-4a2a-b2a0-621629ece250",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "4it [00:00, 88.64it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tqdm import tqdm\n",
+    "import time\n",
+    "\n",
+    "for i in tqdm(range(100)):\n",
+    "    time.sleep(0.01)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "f7ef7138-b839-478f-a077-a68f6da7f3b7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "4it [00:00, 91.89it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tqdm import tqdm\n",
+    "import time\n",
+    "\n",
+    "for i in tqdm(df.iterrows()):\n",
+    "    time.sleep(0.01)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "ce9e095f-8033-4ebf-9719-1cf7f529e59a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Загрузка: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [00:01<00:00, 92.20it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from tqdm import tqdm\n",
+    "import time\n",
+    "\n",
+    "for i in tqdm(range(100), desc='Загрузка'):\n",
+    "    time.sleep(0.01)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f32feeff-c86f-45d8-9049-1c93f319dde4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/week2_task.ipynb b/week2_task.ipynb
new file mode 100644
index 0000000..0991594
--- /dev/null
+++ b/week2_task.ipynb
@@ -0,0 +1,222 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "64e62512-3707-4054-91b6-86439e33c7ca",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 11039 entries, 0 to 11038\n",
+      "Data columns (total 4 columns):\n",
+      " #   Column        Non-Null Count  Dtype  \n",
+      "---  ------        --------------  -----  \n",
+      " 0   Country       11039 non-null  object \n",
+      " 1   Country Code  11039 non-null  object \n",
+      " 2   Year          11039 non-null  int64  \n",
+      " 3   Inflation     11039 non-null  float64\n",
+      "dtypes: float64(1), int64(1), object(2)\n",
+      "memory usage: 345.1+ KB\n",
+      "None\n",
+      "               Year     Inflation\n",
+      "count  11039.000000  11039.000000\n",
+      "mean    1997.128725     19.825504\n",
+      "std       16.961565    288.054102\n",
+      "min     1960.000000    -17.640424\n",
+      "25%     1984.000000      2.409180\n",
+      "50%     1999.000000      4.944324\n",
+      "75%     2011.000000      9.702161\n",
+      "max     2023.000000  23773.131774\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Обработка стран: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:00<00:00, 261.25it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from tqdm import tqdm\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "\n",
+    "df = pd.read_csv(\"data.csv\")\n",
+    "print(df.info())\n",
+    "print(df.describe())\n",
+    "\n",
+    "region_mapping = {\n",
+    "    \"Северная Америка\": [\"United States\", \"Canada\", \"Mexico\", \"Belize\", \"Costa Rica\", \"Cuba\", \"Dominican Republic\", \n",
+    "                        \"El Salvador\", \"Guatemala\", \"Honduras\", \"Jamaica\", \"Nicaragua\", \"Panama\", \"Puerto Rico\", \n",
+    "                        \"Trinidad and Tobago\", \"Bermuda\", \"Greenland\", \"Saint Pierre and Miquelon\", \"Bahamas\", \"Bahamas, The\"],\n",
+    "    \"Eвропа\": [\"Germany\", \"France\", \"United Kingdom\", \"Italy\", \"Spain\", \"Netherlands\", \"Belgium\", \"Sweden\", \n",
+    "                \"Switzerland\", \"Poland\", \"Austria\", \"Norway\", \"Denmark\", \"Finland\", \"Ireland\", \"Portugal\", \n",
+    "                \"Greece\", \"Czech Republic\", \"Hungary\", \"Slovakia\", \"Ukraine\", \"Romania\", \"Bulgaria\", \"Serbia\", \n",
+    "                \"Croatia\", \"Slovenia\", \"Lithuania\", \"Latvia\", \"Estonia\", \"Luxembourg\", \"Iceland\", \"Malta\", \n",
+    "                \"Andorra\", \"Belarus\", \"Monaco\", \"Liechtenstein\", \"Kosovo\", \"Faroe Islands\", \"Isle of Man\", \n",
+    "                \"Gibraltar\", \"Channel Islands\", \"Albania\", \"Armenia\", \"Azerbaijan\", \"Bosnia and Herzegovina\", \n",
+    "                \"Cyprus\", \"Czechia\", \"Estonia\", \"Georgia\", \"Kazakhstan\", \"Kyrgyz Republic\", \"Moldova\", \n",
+    "                \"Montenegro\", \"North Macedonia\", \"Russian Federation\", \"Serbia\", \"Tajikistan\", \"Turkmenistan\", \n",
+    "                \"Ukraine\", \"Uzbekistan\"],\n",
+    "    \"Азия\": [\"China\", \"India\", \"Japan\", \"South Korea\", \"Indonesia\", \"Vietnam\", \"Turkey\", \"Iran\", \"Thailand\", \n",
+    "              \"Saudi Arabia\", \"Pakistan\", \"Malaysia\", \"Philippines\", \"United Arab Emirates\", \"Bangladesh\", \"Iraq\", \n",
+    "              \"Kuwait\", \"Kazakhstan\", \"Uzbekistan\", \"Qatar\", \"Sri Lanka\", \"Oman\", \"Azerbaijan\", \"Lebanon\", \n",
+    "              \"Jordan\", \"Myanmar\", \"Turkmenistan\", \"Bahrain\", \"Yemen\", \"Armenia\", \"Georgia\", \"Kyrgyzstan\", \n",
+    "              \"Tajikistan\", \"Mongolia\", \"Nepal\", \"Bhutan\", \"Lao PDR\", \"Korea, Dem. People's Rep.\", \"Brunei Darussalam\", \n",
+    "              \"Cambodia\", \"Maldives\", \"Timor-Leste\", \"Afghanistan\"],\n",
+    "    \"Африка\": [\"Nigeria\", \"South Africa\", \"Egypt\", \"Kenya\", \"Ethiopia\", \"Algeria\", \"Morocco\", \"Angola\", \"Ghana\", \n",
+    "                \"Sudan\", \"Tunisia\", \"Cameroon\", \"Zimbabwe\", \"Senegal\", \"Zambia\", \"Uganda\", \"Mozambique\", \n",
+    "                \"Botswana\", \"Namibia\", \"Madagascar\", \"Mali\", \"Niger\", \"Chad\", \"Burkina Faso\", \"Malawi\", \n",
+    "                \"Cabo Verde\", \"Sao Tome and Principe\", \"Gambia\", \"Liberia\", \"Eritrea\", \"Djibouti\", \"Comoros\", \n",
+    "                \"Equatorial Guinea\", \"Central African Republic\", \"Benin\", \"Guinea\", \"Togo\", \"Mauritania\", \n",
+    "                \"Sierra Leone\", \"Seychelles\", \"Somalia\", \"Congo, Dem. Rep.\", \"Congo, Rep.\", \"Gabon\", \"Cote d'Ivoire\", \n",
+    "                \"Burundi\", \"Rwanda\", \"Tanzania\", \"Lesotho\", \"Mauritius\", \"Swaziland\", \"Africa Eastern and Southern\", \n",
+    "                \"Africa Western and Central\", \"Arab World\"],\n",
+    "    \"Южная Америка\": [\"Brazil\", \"Argentina\", \"Colombia\", \"Chile\", \"Peru\", \"Venezuela\", \"Ecuador\", \"Bolivia\", \n",
+    "                       \"Paraguay\", \"Uruguay\", \"Guyana\", \"Suriname\"],\n",
+    "    \"Океания\": [\"Australia\", \"New Zealand\", \"Fiji\", \"Papua New Guinea\", \"Solomon Islands\", \"Vanuatu\", \"Samoa\", \n",
+    "                 \"Tonga\", \"French Polynesia\", \"New Caledonia\", \"Micronesia, Fed. Sts.\", \"Cook Islands\", \"Niue\", \n",
+    "                 \"Tokelau\", \"Pacific island small states\", \"Antigua and Barbuda\", \"Aruba\", \"Barbados\", \"Dominica\", \n",
+    "                 \"Grenada\", \"Saint Lucia\", \"Saint Vincent and the Grenadines\", \"Curacao\"]\n",
+    "}\n",
+    "\n",
+    "def get_region(country):\n",
+    "    for region, countries in region_mapping.items():\n",
+    "        if country in countries:\n",
+    "            return region\n",
+    "    return \"Другие\"\n",
+    "\n",
+    "df[\"Region\"] = df[\"Country\"].apply(get_region)\n",
+    "\n",
+    "region_inflation = df.groupby(\"Region\")[\"Inflation\"].mean().reset_index()\n",
+    "plt.figure(figsize=(12, 6))\n",
+    "plt.bar(region_inflation[\"Region\"], region_inflation[\"Inflation\"], color='skyblue')\n",
+    "plt.xlabel(\"Регион\")\n",
+    "plt.ylabel(\"Средний уровень инфляции (%)\")\n",
+    "plt.title(\"Средний уровень инфляции по регионам\")\n",
+    "plt.xticks(rotation=45)\n",
+    "plt.show()\n",
+    "\n",
+    "top_countries = df[df[\"Year\"] == 2023].nlargest(5, \"Inflation\")[\"Country\"].tolist()\n",
+    "df_top = df[df[\"Country\"].isin(top_countries)]\n",
+    "\n",
+    "plt.figure(figsize=(12, 6))\n",
+    "for country in tqdm(top_countries, desc=\"Обработка стран\"):\n",
+    "    country_data = df_top[df_top[\"Country\"] == country]\n",
+    "    plt.plot(country_data[\"Year\"], country_data[\"Inflation\"], label=country)\n",
+    "\n",
+    "plt.xlabel(\"Год\")\n",
+    "plt.ylabel(\"Уровень инфляции (%)\")\n",
+    "plt.title(\"Изменение инфляции в странах с самой высокой инфляцией (2023)\")\n",
+    "plt.legend()\n",
+    "plt.show()\n",
+    "\n",
+    "plt.figure(figsize=(12, 6))\n",
+    "for region in df[\"Region\"].unique():\n",
+    "    region_data = df[df[\"Region\"] == region]\n",
+    "    plt.hist(region_data[\"Inflation\"], bins=30, alpha=0.5, label=region)\n",
+    "\n",
+    "plt.xlabel(\"Уровень инфляции (%)\")\n",
+    "plt.ylabel(\"Частота\")\n",
+    "plt.title(\"Распределение уровней инфляции по регионам\")\n",
+    "plt.legend()\n",
+    "plt.show()\n",
+    "\n",
+    "plt.figure(figsize=(12, 6))\n",
+    "for region in df[\"Region\"].unique():\n",
+    "    region_data = df[df[\"Region\"] == region]\n",
+    "    yearly_avg = region_data.groupby(\"Year\")[\"Inflation\"].mean().reset_index()\n",
+    "    plt.plot(yearly_avg[\"Year\"], yearly_avg[\"Inflation\"], label=region)\n",
+    "\n",
+    "plt.xlabel(\"Год\")\n",
+    "plt.ylabel(\"Средний уровень инфляции (%)\")\n",
+    "plt.title(\"Динамика средней инфляции по регионам\")\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ce7d3279-527e-44e7-b0b7-5badf20707b2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bff1a08b-92e8-4d38-b474-6b5d123ee3df",
+   "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
+}