diff --git a/.gitignore b/.gitignore
index 207d123..d4bab93 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,21 @@
+# ---> VisualStudioCode
+.vscode/*
+!.vscode/settings.json
+!.vscode/tasks.json
+!.vscode/launch.json
+!.vscode/extensions.json
+!.vscode/*.code-snippets
+
+aimenv
+
+static
+
+# Local History for Visual Studio Code
+.history/
+
+# Built Visual Studio Code Extensions
+*.vsix
+
 # ---> JupyterNotebooks
 # gitignore template for Jupyter Notebooks
 # website: http://jupyter.org/
@@ -12,3 +30,167 @@ ipython_config.py
 # Remove previous ipynb_checkpoints
 #   git rm -r .ipynb_checkpoints/
 
+# virtual
+/mai
+
+# ---> Python
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
\ No newline at end of file
diff --git a/README.md b/README.md
index 740694f..900820c 100644
--- a/README.md
+++ b/README.md
@@ -1,2 +1,6 @@
-# AIM-PIbd-32-Chernyshev-G-Y
+ПИбд-32
+Чернышев Георгий Янович
+Вариант 1 (26)
+Объекты вокруг Земли
+https://www.kaggle.com/datasets/sameepvani/nasa-nearest-earth-objects
 
diff --git a/lab_1/Lab1.ipynb b/lab_1/Lab1.ipynb
new file mode 100644
index 0000000..87ddb0b
--- /dev/null
+++ b/lab_1/Lab1.ipynb
@@ -0,0 +1,208 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## **НАЧАЛО ЛАБЫ**\n",
+    "\n",
+    "Выгрузка данных из csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['id', 'name', 'est_diameter_min', 'est_diameter_max',\n",
+      "       'relative_velocity', 'miss_distance', 'orbiting_body', 'sentry_object',\n",
+      "       'absolute_magnitude', 'hazardous'],\n",
+      "      dtype='object')\n"
+     ]
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "df = pd.read_csv(\"..//static//csv//neo.csv\", nrows=15000)\n",
+    "print(df.columns)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## **СТОЛБЦЫ ДАТАСЕТА:**\n",
+    "\n",
+    "**Id**\n",
+    "\n",
+    "**name**\n",
+    "\n",
+    "**est_diameter_min** – минимальный радиус косм. объекта (астероид, комета) рядом с Землёй (км)\n",
+    "\n",
+    "**est_diameter_max** – максимальный радиус косм. объекта\n",
+    "\n",
+    "**relative_velocity** – скорость относительно Земли (км/с)\n",
+    "\n",
+    "**miss_distance** – расстояние, на кот. проходит рядом с Землёй (км)\n",
+    "\n",
+    "**orbiting_body** – тело, вокруг которого вращается (везде Земля)\n",
+    "\n",
+    "**sentry_object** – ведётся ли за ним авто мониторинг, как за телом, кот. может столкнуться с Землёй (везде  false)\n",
+    "\n",
+    "**absolute_magnitude** – звёздная величина (яркость)\n",
+    "\n",
+    "**hazardous** – опасный для Земли / нет"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Диаграмма ниже показывает разницу между максимальным вероятным диаметром космического объекта и минамальным (на срезе первых 100 объектов). С помощью неё можно увидеть, что у большинства объектов разница между этими двумя значениями составляет меньше 1 км, что говорит о достаточно хорошей точности измерения размера объекта"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: title={'center': 'Разница между макс. диаметром (est_diameter_max) и мин диаметром (est_diameter_min) объекта (первые 100 записей)'}, xlabel='Порядковый номер объекта в датасете', ylabel='Разница'>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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ly0prdyghUaEBBS6vU5VgBwAAAADA85VKwOO1115Tp06ddMMNN+ill15S27Zt9eGHH+r666/X+++/Xxq7RAmpGx6kdg3C5X3BQLPeNpvaNQindQcAAAAAoEwolYDH1KlTNWfOHK1atUqjR4/Wc889p40bN+rVV19lfI8yYHJsc8XUD3NIi6kfpsmxzd2UIwAAAAAAisZmjDElvVE/Pz/t3r1btWrVUkBAgDZu3KjLLrtM8fHxaty4sVJTU0t6ly6TkpKikJAQJScnKzg42N3ZKVXxiWnaezxNdaoG0rIDAAAAANykPN2HlqRSGbQ0JCRESUlJqlWrluLi4hQW9k9rgczMTPn6+pbGLlEKosMIdAAAUNbsSUjVvhPpPLAAAJR7pRLw6Nq1qw4cOKArr7xSU6dOtaevWbNGTZo0KY1dAgAAlGtJ6ZkaOm+zw/Ty7RqEa3Jsc4UEVHRjzgAAcI9S6dKSn+TkZBljVLlyZVftssTRlAgAAHii/jPWadXuRGWdd2nnbbMppn6YZg9q5cacAQAuFvehxVNq09LmJSQkpEwHOwAAADzRnoRUrdiV4BDskKQsY7RiV4LiE9PclDMAANynVLq0SNL69ev16aefav/+/crMzHRY9sUXX5TWbgEAAMqdfSfSC1y+93ga43kAAMqdUmnh8fHHH+uaa67Rjh07tGDBAp09e1bbtm3TTz/9pJCQkNLYJQAAQLkVFRpQ4PI6VQl2AADKn1IJeLz44ot644039NVXX8nHx0eTJk3SH3/8oT59+uiSSy4pjV0CAACUW3XDg9SuQbi8bTaHdG+bTe0ahNO6AwBQLpVKwOOvv/5Sjx49JEk+Pj5KS0uTzWbTww8/rHfeeac0dgkAAFCuTY5trpj6YQ5pMfXDNDm2uZtyBACAe5XKGB5VqlTRqVOnJEk1a9bU1q1b1bhxYyUlJSk9veA+pgAAACi6kICKmj2oleIT07T3eJrqVA2kZQcAoFwrlYBHu3bttHjxYjVu3Fi33367hg0bpp9++kmLFy/WddddVxq7BAAAgKToMAIdAABIpRTwmDJlis6cOSNJeuqpp1SxYkX98ssvuvXWW/X000+Xxi4BAAAAAADsSjTgkZ2drQkTJuh///ufMjMzdd1112nMmDEaOXJkSe4GAAAAAACgQCU6aOkLL7ygJ598UkFBQapZs6YmTZqkwYMHl+QuAAAAAAAAClWiAY/Zs2fr7bff1vfff6+FCxfqq6++0ty5c5WdnV2SuwEAAAAAAChQiQY89u/frxtuuMH+unPnzrLZbDp06FBJ7gYAAAAAAKBAJRrwOHfunPz8/BzSKlasqLNnz5bkbgAAAAAAAApUooOWGmM0YMAA+fr62tPOnDmjBx98UIGB/06P9sUXX5TkbgEAAAAAAByUaMAjLi4uV9pdd91VkrsAAAAAAMvZk5CqfSfSVadqoKLDAgt/A4BClWjAY+bMmSW5OQAAAACwtKT0TA2dt1krdiXY09o1CNfk2OYKCajoxpwBZV+JjuEBAAAAAHDe0HmbtWp3okPaqt2JemjeJjflCLAOAh4AAAAA4AZ7ElK1YleCsoxxSM8yRit2JSg+Mc1NOQOsgYAHAAAAALjBvhPpBS7fe5yAB3AxCHgAAAAAgBtEhQYUuLxOVQYvBS4GAQ8AAAAAcIO64UFq1yBc3jabQ7q3zaZ2DcKZrQW4SB4f8JgyZYrq1KkjPz8/tW7dWuvWrct33Q4dOshms+X669Gjh32dAQMG5FrerVs3VxwKAAAAADiYHNtcMfXDHNJi6odpcmxzN+UIsI4SnZa2pH3yyScaMWKEpk2bptatW2vixInq2rWrdu7cqWrVquVa/4svvlBmZqb99fHjx9W0aVPdfvvtDut169bNYQpdX1/f0jsIAAAAAMhHSEBFzR7USvGJadp7PE11qgbSsgMoIR4d8Hj99dd13333aeDAgZKkadOm6ZtvvtH777+vkSNH5lo/NDTU4fXHH3+sgICAXAEPX19fVa9e3ak8ZGRkKCMjw/46JSWlqIcBAAAAAAWKDiPQAZQ0j+3SkpmZqQ0bNqhz5872NC8vL3Xu3FmrV692ahszZsxQ3759FRjoWHEsW7ZM1apVU8OGDfV///d/On78eL7bGD9+vEJCQux/tWvXLt4BAQAAAAAAl/HYgEdiYqKysrIUERHhkB4REaEjR44U+v5169Zp69atuvfeex3Su3XrptmzZ2vJkiV6+eWXtXz5cnXv3l1ZWVl5bmfUqFFKTk62/x04cKD4BwUAAAC40Z6EVC3deUzxiUx3CsD6PLpLy8WYMWOGGjdurFatWjmk9+3b1/7/xo0bq0mTJqpXr56WLVum6667Ltd2fH19GeMDAAAAZVpSeqaGztusFbsS7GntGoRrcmxzhQRUdGPOAKD0eGwLj7CwMHl7e+vo0aMO6UePHi10/I20tDR9/PHHGjRoUKH7qVu3rsLCwrR79+6Lyi8AoOziiScAqxs6b7NW7U50SFu1O1EPzdvkphwBQOnz2BYePj4+atGihZYsWaLevXtLkrKzs7VkyRINGTKkwPfOnz9fGRkZuuuuuwrdz99//63jx4+rRo0aJZFtAEAZwhNPAOXBnoRUh3ouR5YxWrErQfGJaQyWCcCSPLaFhySNGDFC7777rj744APt2LFD//d//6e0tDT7rC39+/fXqFGjcr1vxowZ6t27t6pWreqQnpqaqscee0xr1qzR3r17tWTJEvXq1Uv169dX165dXXJMAADPwRNPAOXBvhPpBS7fe5zWbQCsyWNbeEjSHXfcoYSEBI0ePVpHjhxRs2bNtGjRIvtApvv375eXl2PMZufOnVq5cqV++OGHXNvz9vbW77//rg8++EBJSUmKjIzU9ddfr3HjxjFOBwCUMzzxBFBeRIUGFLi8TlXqOgDWZDPGGHdnoixJSUlRSEiIkpOTFRwc7O7sAACKaenOYxo489d8l88ceLU6NqzmwhwBQOnpP2OdVu1OVNZ5l/7eNpti6odp9qBWBbwTgCfgPrR4PLpLCwAApYUnngDKk8mxzRVTP8whLaZ+mCbHNndTjgCg9Hl0lxYAAEpL3fAgtWsQnu8TT7qzALCSkICKmj2oleIT07T3eJrqVA2kngNgebTwAACUWzzxBFDeRIcFqmPDagQ7AJQLtPAAAJRbPPEEPNuehFTtO5HOdxMAUCwEPAAA5V50GDdTgCdJSs/U0HmbHWZSatcgXJNjmyskoKIbcwYAKEvo0gIAAACPMnTeZq3aneiQtmp3oh6at8lNOQIAlEUEPAAAAOAx9iSkasWuBIfBhCUpyxit2JWg+MQ0N+UMAFDWEPAAAACAx9h3Ir3A5XuPE/AAADiHgAcAAAA8RlRoQIHL61RlvB0AgHMIeAAAAMBj1A0PUrsG4fK22RzSvW02tWsQzgDDAACnEfAAAACAR5kc21wx9cMc0mLqh2lybHM35QgAUBYxLS0AAAA8SkhARc0e1ErxiWnaezxNdaoydTQAoOgIeAAAAMAjRYcR6PBEexJSte9EOoEoAB6PgAcAAACAQiWlZ2rovM1asSvBntauQbgmxzZXSEBFN+YMAPLGGB4AAAAACjV03mat2p3okLZqd6IemrfJTTkCgIIR8AAAAABQoD0JqVqxK0FZxjikZxmjFbsSFJ+Y5qacAUD+CHgAAAAAKNC+E+kFLt97nIAHAM9DwAMAAABAgaJCAwpcXqcqg5cC8DwEPAAAAAAUqG54kNo1CJe3zeaQ7m2zqV2DcGZrAeCRCHgAAAAAKNTk2OaKqR/mkBZTP0yTY5u7KUcAUDCmpQUAAABQqJCAipo9qJXiE9O093ia6lQNpGUHAI9GwAMAAACA06LDCHQAKBvo0gIAAAAAACyHFh6ABe1JSNW+E+k0NQUAAABQbhHwACwkKT1TQ+dt1opdCfa0dg3CNTm2uUICKroxZwAAAADgWnRpASxk6LzNWrU70SFt1e5EPTRvk5tyBAAAAADuQcADsIg9CalasStBWcY4pGcZoxW7EhSfmOamnAEAAACA6xHwACxi34n0ApfvPU7AAwAAAED5QcADsIio0IACl9epyuClAAAAAMoPAh6ARdQND1K7BuHyttkc0r1tNrVrEO622Vr2JKRq6c5jdKkBAAAA4FLM0gJYyOTY5npo3iaHWVpi6odpcmxzl+eFGWMAAAAAuJPNmAtGOESBUlJSFBISouTkZAUHB7s7O0Ce4hPTtPd4mupUDXRby47+M9Zp1e5Eh0FUvW02xdQP0+xBrdySJwAAAKAs4j60eGjhAVhQdJj7Ah3SvzPGXOj8GWPcmT8AAAAA1scYHgBKHDPGAAAAAHA3WngAKHFWnTFmT0Kq9p1Id2tXIQAAAADOIeABoMTlzBiT3xgeZS1YwACsAAAAQNlDlxYApWJybHPF1A9zSHPXjDEXa+i8zVq1O9EhbdXuRD00b5ObcgQAAACgMLTwAFAqQgIqavagVh4xY8zFYABWAAAAoGwi4AGgVLl7xpiL5cwArGX5+AAAAACrIuABAAWw6gCsAGAFDCYNACgIAQ8AKIDVBmAFACtgMGnPRzAKgCewGXPeFTwKlZKSopCQECUnJys4ONjd2QHgAsnpZ/XQvE1cWAOAh+g/Y12+gejZg1q5MWcgGAWUDu5Di4cWHgBQCKsMwAoAVsBg0p6toJnNCEYBcDUCHgDgpLI+ACsAWAGDSXsuglEAPI2XuzMAAAAAOIvBpD2XM8EoAHAljw94TJkyRXXq1JGfn59at26tdevW5bvurFmzZLPZHP78/Pwc1jHGaPTo0apRo4b8/f3VuXNn7dq1q7QPAwAAACUgZzBpb5vNId3bZlO7BuG0IHCjogSj9iSkaunOY4pPJAgCoPR4dMDjk08+0YgRIzRmzBht3LhRTZs2VdeuXXXs2LF83xMcHKzDhw/b//bt2+ew/JVXXtGbb76padOmae3atQoMDFTXrl115syZ0j4cAAAAlIDJsc0VUz/MIS2mfpgmxzZ3U44gOReMSkrPVP8Z69TpteUaOPNXdXx1mfrPWKfk9LNuyjUAK/PoWVpat26tq6++Wm+99ZYkKTs7W7Vr19ZDDz2kkSNH5lp/1qxZGj58uJKSkvLcnjFGkZGReuSRR/Too49KkpKTkxUREaFZs2apb9++heaJ0XEBAAA8A4NJe57CZjZjhh2geLgPLR6PHbQ0MzNTGzZs0KhRo+xpXl5e6ty5s1avXp3v+1JTUxUVFaXs7GxdddVVevHFF9WoUSNJUnx8vI4cOaLOnTvb1w8JCVHr1q21evXqPAMeGRkZysjIsL9OSUkpicMDAADARWIwac9T0MxmDGoKwNU8tktLYmKisrKyFBER4ZAeERGhI0eO5Pmehg0b6v3339eXX36pDz/8UNnZ2brmmmv0999/S5L9fUXZ5vjx4xUSEmL/q1279sUeGgAAAGBp0WGB6tiwmkMAg0FNAbiaxwY8iqNNmzbq37+/mjVrpvbt2+uLL75QeHi4pk+fXuxtjho1SsnJyfa/AwcOlGCOAQAAgPKBGXYAuJrHBjzCwsLk7e2to0ePOqQfPXpU1atXd2obFStWVPPmzbV7925Jsr+vKNv09fVVcHCwwx8AAACAomGGHQCu5rEBDx8fH7Vo0UJLliyxp2VnZ2vJkiVq06aNU9vIysrSli1bVKNGDUlSdHS0qlev7rDNlJQUrV271ultAgAAACgeZtgB4EoeO2ipJI0YMUJxcXFq2bKlWrVqpYkTJyotLU0DBw6UJPXv3181a9bU+PHjJUljx47Vf/7zH9WvX19JSUmaMGGC9u3bp3vvvVeSZLPZNHz4cD3//PNq0KCBoqOj9cwzzygyMlK9e/d212ECAAAAHmNPQqr2nUgvldlvChrUFABKmkcHPO644w4lJCRo9OjROnLkiJo1a6ZFixbZBx3dv3+/vLz+baRy8uRJ3XfffTpy5IiqVKmiFi1a6JdfftEVV1xhX+fxxx9XWlqa7r//fiUlJalt27ZatGiR/Pz8XH58AAAAgKdISs/U0Hmb851StiQxww4AV7AZc94k2CgU8x8DAMqD0nzCC8Az9Z+xTqt2JyrrvNsDb5tNMfXDNHtQKzfmDAD3ocXj0S08AACAa7nyCS8Az7EnIdXhe58jyxit2JWg+MQ0gp8AyhyPHbQUAAC43tB5m7Vqd6JD2qrdiXpo3iY35QiAK+w7kV7g8r3H01yUEwAoOQQ8AACApH+f8GZd0Nv1/Ce8AKwpKjSgwOV1qtK6A0DZQ8ADAABI4gkvUJ7VDQ9Suwbh8rbZHNK9bTa1axBOdxYAZRIBD5QbexJStXTnMZ5QAkA+eMILlG+TY5srpn6YQ1pM/TBNjm3uphwBwMVh0FJYHgPwAYBzcp7w5jdLA094AWsLCaio2YNaKT4xTXuPpzFLE4AyjxYesDwG4AMA5/GEF0B0WKA6NqxGsANAmUcLD1gaU6wBKCl7ElK170S65Z948oQXAABYBQEPWJozA/BxIQ+gIOW1W1x0mHUCHeUlWAUAABwR8IClMQAfgItVULe42YNauSlXcEZ5DVYBAIB/MIYHLI0p1gBcjJxucecP4Ck5douD52IMJwAAyjcCHrA8BuADUFzOdIuDZyJYBQAA6NICy2MAPgDFRbe4sosxnAAAAAEPlBtWGoAPgGvkdItbtTvRoaWAt82mmPph1CkejGAVAACgSwsAAAWgW1zZxBhOAADAZswFnVtRoJSUFIWEhCg5OVnBwcHuzg4AwEXoFlf2JKef1UPzNjFLCwCgzOM+tHgIeBQRBQ0AnLcnIVX7TqQTJPAw5e1zIVgFACjruA8tHsbwAACUuKT0TA2dt5kn6x6mvH4ujOEEAED5xBgeAIASN3TeZq3aneiQtmp3oh6at8lNOYLE5wIAAMoXAh4AgBK1JyFVK3YlOMxqIklZxmjFrgTFJ6a5KWflG58LAAAobwh4AABK1L4T6QUu33ucG2t34HMBgLJtT0Kqlu48RoAaKALG8ADKoPI24CDKlqjQgAKX16lKmXUHPhcAKJvK6/hLQEkg4AGUIfzgoSyoGx6kdg3CtWp3okP3CW+bTTH1wwjSuQmfC1B8PGiAOxU0/tLsQa3clCugbKBLC1CGMOAgyorJsc0VUz/MIS2mfpgmxzZ3U44g8bkARZWUnqn+M9ap02vLNXDmr+r46jL1n7FOyeln3Z01lBOMvwRcHFp4AGVEzg/ehc7/weOpEzxFSEBFzR7USvGJadp7PI2noh6CzwUoGp6sw92cGX+JehzIHwEPoIzgBw9lUXQYN9SeiM8FKBwPGuAJGH8JuDh0aQHKCH7wAABwHWY2gifIGX/J22ZzSPe22dSuQThBN6AQBDzKMaa2Klv4wQMAwHV40ABPwfhLQPHRpaUcYqaPsmtybHM9NG+Tw2fHDx4AACWPmY3gKRh/CSg+mzEXDPmLAqWkpCgkJETJyckKDg52d3aKpf+Mdfn+eDMAV9nADx4AAKUvOf1srgcNPCQC4A5WuA91B1p4lDOuHoCLeetLBwMOAgBQ+niyDgBlGwGPcsZVM31YtdsMARwAAMofHjQAQNlEwKOccdUAXFabt96qARwAAAAAsCpmaSlnXDHTR063mawLhoc5v9tMWVNQAAcAAAAA4HkIeJRDpT21ldXmrbdiAAdAyWOqbwAAAM9Cl5ZyqLQH4LLavPWuGvcEQNlElzcAAADPRAuPciw6LFAdG1Yr8Zt1V3SbcSWrBXAAlCy6vAEAAHgmAh4oFaXdbcaVrBbAAVBy6PIGAADguejSglJhtXnrJ8c210PzNjk0WS+rARwAJYcubwAAAJ6LgAdKlVXmrbdaAAfwFHsSUrXvRHqZ/U7R5Q0AAMBzEfAAisAqARzAGaUZjLDKQJ85Xd5W7U506NbibbMppn4Y9QUAAIAb2Yy5oOMxCpSSkqKQkBAlJycrODjY3dkBgBLnimBE/xnr8g0SzB7UqkT24SrJ6WdzdXkri8EbAADgubgPLR5aeAAAHBQ060hJBCNyBvq80PkDfZallhF0eQMAAPBMBDwAAHauCEZYdaBPurwVXVkfwwUAAHg2Ah4AADtXBCMY6BNWGcMFAAB4Ni93Z6AwU6ZMUZ06deTn56fWrVtr3bp1+a777rvv6tprr1WVKlVUpUoVde7cOdf6AwYMkM1mc/jr1q1baR8GADfbk5CqpTuPKT4xzd1Z8WhFCUYU95zmDPTpbbM5pHvbbGrXIJwn/eVAQd2mAAAASopHt/D45JNPNGLECE2bNk2tW7fWxIkT1bVrV+3cuVPVqlXLtf6yZcsUGxura665Rn5+fnr55Zd1/fXXa9u2bapZs6Z9vW7dumnmzJn2176+vi45HgCux5PkonFm1pGSOKeTY5vnGugzpn6YJsc2L7mDgdvl1WXFamO4AAAAz+XRs7S0bt1aV199td566y1JUnZ2tmrXrq2HHnpII0eOLPT9WVlZqlKlit566y31799f0j8tPJKSkrRw4cJi5YnRcYGyxUqzgbhKYbOOlOQ5ZaBPayooKLbxwEkNnPlrvu+dOfBqdWyY+6EGAADlGfehxeOxLTwyMzO1YcMGjRo1yp7m5eWlzp07a/Xq1U5tIz09XWfPnlVoaKhD+rJly1StWjVVqVJFnTp10vPPP6+qVavmuY2MjAxlZGTYX6ekpBTjaAC4A0+Si6egWUdK+pwy0Kc1FdRl5dmbrijwvYzhAgAASorHjuGRmJiorKwsRUREOKRHREToyJEjTm3jiSeeUGRkpDp37mxP69atm2bPnq0lS5bo5Zdf1vLly9W9e3dlZWXluY3x48crJCTE/le7du3iHxQAl3JmAE7kLzosUB0bVnMISHBOUZicoFjWBQ1Ic4Jitv8/VgtjuAAAgNLmsQGPi/XSSy/p448/1oIFC+Tn52dP79u3r2666SY1btxYvXv31tdff61ff/1Vy5Yty3M7o0aNUnJysv3vwIEDLjoCABeL2UBKHucUhXEmKDY5trli6oc5pDOGCwAAKGke26UlLCxM3t7eOnr0qEP60aNHVb169QLf++qrr+qll17Sjz/+qCZNmhS4bt26dRUWFqbdu3fruuuuy7Xc19eXQU2BMsqZAThRNJxTFMaZoFhB3aYAAABKise28PDx8VGLFi20ZMkSe1p2draWLFmiNm3a5Pu+V155RePGjdOiRYvUsmXLQvfz999/6/jx46pRo0aJ5BuAZ3Hlk+TyMvUtT+dRkKJMO5xXtykAAICS4tGztHzyySeKi4vT9OnT1apVK02cOFGffvqp/vjjD0VERKh///6qWbOmxo8fL0l6+eWXNXr0aH300UeKiYmxbycoKEhBQUFKTU3Vc889p1tvvVXVq1fXX3/9pccff1ynTp3Sli1bnGrJwei4QNlUmk+Sy+vUtzydR34Km+kHAAAUDfehxePRAQ9JeuuttzRhwgQdOXJEzZo105tvvqnWrVtLkjp06KA6depo1qxZkqQ6depo3759ubYxZswYPfvsszp9+rR69+6tTZs2KSkpSZGRkbr++us1bty4XIOj5oeC5h57ElK170Q6N1bwSEx9C+SNoBgAACWD+9Di8fiAh6ehoLlWeX1yjrJjT0KqOr22PN/lSx/twI0e7Ajelm98/p6Lzwb4F98Hz8R9aPF47KClgCQNnbdZq3YnOqSt2p2oh+Zt4sk5PIIzM1JwsQCCt+Ubn7/n4rMB/sX3AVbksYOWAnsSUrViV4JDNwFJyjJGK3YlWH5gSJQNTNMKZxQUvIX18fl7Lj4b4F98H2BFBDzgsZx5cg64W1FmpED5RPC2fOPz91x8NsC/rPp9KC8z6CF/dGmBxyqLT87p81g+TY5tnmtGCqZpRQ53dHuiLvIcdHtzv/y+D3w2wL+s9n2gew5yEPCAx8p5cp7f7BeeVOlSqZZvIQEVNXtQK2akQJ5cGbylLvI8ZTF4bxWFfR/4bIB/We37wDiAyEGXFni0ybHNFVM/zCHNE5+c0+cRkhQdFqiODasR7IADV3Z7oi7yPHR7c5/Cvg+u/mxoWg9PZqW6yqrdc1A8tPCARysLT85zKtULnV+pelqeAbiWK7o9URd5Lrq9uZ6z3wdXfDa0vEJZYZW6ymrdc3BxCHigTIgO87xARw4qVbga4zOUPa4I3lIXea6yELy3Gme/D674bGhaj7KiJL8PJXGtUtxtFLV7DtdV1kbAA7hIVuvzCM/FU8KyrzSDt9RFns+Tg/dWU9TvQ2l9NrS8Qll0Md+HkrhWudhtODsOINdV5QNjeAAXyUp9HuHZGJ8BBaEuAv7lKd8HZ1qaAFZSEtcqJbENZ8YB5LqqfCDgAZSAsjK4KsouBuCCM6iLgH95wveBllcoT0riWqWkrndyuucsfbSDZg68Wksf7aDZg1rZW25wXVV+0KUFKAH0z0ZpY3wGOIO6CPiXJ3wfnG1aD1hBSVyrlPT1Tn7dc7iuKj8IeAAliP7ZKC08JURRUBcB/3L398EqM18AhSmJaxVXXe9wXVV+EPAAgDKAp4QAUDZ5QksTwBVK4lrFVdc7XFeVH4zhAQBlhCf0RwcAFE90WKA6NqzGjRQsrSSuVVx1vcN1VflgM+aCkVpQoJSUFIWEhCg5OVnBwcHuzg6AMqYk5nrnKSEAACWnJH6b4agkrlVcdb1TVq6ruA8tHgIeRURBsy5+7FCamOsdAADPwm8zyhLuQ4uHgEcRUdCshx87uEL/Gevy7Sc6e1ArN+YMAIDyid9mlCXchxYPY3ig3Bs6b7NW7U50SFu1O1EPzdvkphzBapjrHQAAz8JvM1A+EPDARdmTkKqlO4+V2R8FfuzgCs7M9Q4AAFyH32agfGBaWhSLVbqBOPNjx3geuFjM9Q4AgGfhtxkoH2jhgWKxSjcQfuzgCjlzvXvbbA7p3jab2jUIJ6gGwKXKeutMoCTw2wyUDwQ8UGRW6gbCjx1chbneAbhbUnqm+s9Yp06vLdfAmb+q46vL1H/GOiWnn3V31gC34LcZsD5maSkiRseVlu48poEzf813+cyBV6tjw2ouzNHFSU4/q4fmbSrz3XNQNpSVud4BWA8zUgB547cZZQH3ocXDGB4oMqt1AwkJqKjZg1rxYweXiA6jfAFwvZzWmRc6v3UmdRPKK36bAeuiSwuKzKrdQKLDAtWxYbUym38AAPLDjBQAgPKIgAeKhT6PxcdgcQAAV7Na60wAAJxBlxYUC91Ais4qU/kCAMqenNaZ+Y3hwW84AMCKaOGBi0I3EOdZZSpfAKWHFmBF56pzZoXPhtaZKI+s8N0tivJ2vEBhaOEBuACDxQEoCC3Ais5V58xKnw2tM1GeWOm764zydryAs2jhAbgAg8UBKAgtwIrOVefM1Z+NK57O0joT5UF5q1fL2/ECzqKFB+ACDBbn+fYkpGrfiXRLPPG00rGUB7QAKzpXnTNXfjY8nQVKTnmrV8vb8QJFQcADcAEGi/NcVrrJsNKxlCfOtACjjnDkqnPmys+moKezswe1KpF9AOVFeatXy9vxAkVBlxbARcraYHHlZdArKzUBtdKxlCe0ACs6V50zV+0n5+ns+QFxyfHpLMqH8vLbW9rKW71a3o4XKApaeAAuUlYGiytPrQSs1ATUSsdS3tACrOhcdc5ctR+ezlrDxXQnLE+/va5Q3urVohwv3V5R3tDCA25X3p5mePpgceWplYCVBpO10rGUR2WtBZgncNU5c8V+eDpbtiWlZ6r/jHXq9NpyDZz5qzq+ukz9Z6xTcvpZp7dRnn57S1p+15GurlfdfT1b2PGWRDkFyiJaeMBteJrhecpbKwEr3WRY6VjKo7LSAsyTuOqcuWI/5e1pdA6rPGm+2PFXyttvb0kp7DrSVXWEp1zPFna8jBOE8ooWHnAbnmZ4nqK2EnD304yLlXOT4W2zOaR722xq1yDcLReYxT2nnngsKDpPbwHmiVx1zkp7P+WplY+VnjSXxPgrtNArHmevI0v7u+tp17N5HW9JjxNU1q//UL7QwgNuwdMMz+RsKwFPeZpREibHNtdD8zY5HIs7bjJK4px6yrEAKLry1MrHSk+aS2L8FVro5S+/VkCuvo70lHwUV0mNE2Sl6z+UHwQ84BYM0OaZnG1WbaWLVU+5ySiJc+opxwKg+KLDPON7W1rdTcrKDaKzSiJYUV67NBWksBtrV11Heko+LlZJBdWsdP2H8oMuLXALnmZ4rsKaVVt1+kR3diUo6XNKtwigaMpS8+zSzquz3U2Kmw+rdd8oqe6E5alLkzMK6ybiqutIT8nHxSqJcmrV6z9YHy084BY8zfBchbUSKCtPM8oSzmnBrDKwITxPWWqe7aq8FvYE92LzUVZuEIuiJLoT0kLvX860AnLFdaSn5KOkXGw55VoFZRUBD7gN4w14tvyaVVvxYtXdOKd5K0s3o+WRFQJRZal5tivy6swN3pgvt11UPsrSDaKzSjJY4SldmtzJ2Rvr0r6O9JR8lJSLLadcq6CsIuABt+FpRtlU0herztw0WeHGqiBWvAEoCWXpZrQ8sUogqjTGkijr414UdoO3Zs/xIuUjv/NRVm4Qi8oVwYry8Jvp7I11aV9Heko+Slpxy2lpXKuU9bKKsoGAB9yuJC4QrFRhuupYLmY/JXGx6sxNk1VurJxh1RuA4irKDZ6Vvv/OcPfxWiUQVZLNs0u7rnJVU/LCbvBsBS79Nx+FnY+ydoPoCcrTb2ZRb6xLK9BU0vlwd91dEkrqWsUqZRVlg82YC0aeQYFSUlIUEhKi5ORkBQcHuzs75Z6VKkxXHUtJ7udiLlb7z1iX70VEzk2TM+tI1riIyMENwD+W7jymgTN/zXf5zIFXq3ntypb5/jvDE+q7PQmp6vTa8nyXL320Q5kptyV5LM7WVZ6Q18IUdCzP3nSFU/ko7fNRHpXkb2ZZkJx+NteNtTvq95LIhyfU3SXtYq9VrFRWXYn70OLx+FlapkyZojp16sjPz0+tW7fWunXrClx//vz5uuyyy+Tn56fGjRvr22+/dVhujNHo0aNVo0YN+fv7q3Pnztq1a1dpHgJKUWGjZ5clrjqWktxPcWcDcWakb2fWcXY2gbKEGVb+4UxTYit9/53hCcdrpRk2Smp2DVfMXFBSeXVGQbOFOJMPZnIoeSX1m1mW5LQCWvpoB80ceLWWPtpBswe1cnmAoCTy4Ql1d0m7mGsVq5VVeD6PDnh88sknGjFihMaMGaONGzeqadOm6tq1q44dO5bn+r/88otiY2M1aNAgbdq0Sb1791bv3r21detW+zqvvPKK3nzzTU2bNk1r165VYGCgunbtqjNnzrjqsFBCrFRhuupYPOWcOXPT5Mw6VryIwD8Ku7Ey/7/Murssu4qnfHetNmhdSUwF6qogkKumLS3sBq+wfFgpKOYpSuo3syzylIcApfmAp7yxalmF5/LoMTxef/113XfffRo4cKAkadq0afrmm2/0/vvva+TIkbnWnzRpkrp166bHHntMkjRu3DgtXrxYb731lqZNmyZjjCZOnKinn35avXr1kiTNnj1bERERWrhwofr27ZtrmxkZGcrIyLC/TklJKY1DRTFYaXosVx2Lp5wzZ26aCutt522zuWQQP7hPQX2FNx44WeB7y9L33xme8t212gC7JTGWhKuCQK4e9yK/8QgKy4fVgmKeoCR+Mznv7uEpdbcnoY6Aq3lsC4/MzExt2LBBnTt3tqd5eXmpc+fOWr16dZ7vWb16tcP6ktS1a1f7+vHx8Tpy5IjDOiEhIWrdunW+2xw/frxCQkLsf7Vr177YQ0MJsVKF6apj8ZRz5kyz6MLWufBpyYV4QlD2FfSk2VPKsqt40vG6qqWBK13MU2RXdjeRPP+Jt6vPR3lQEr+ZnHf38KS621NQVuFqHhvwSExMVFZWliIiIhzSIyIidOTIkTzfc+TIkQLXz/m3KNscNWqUkpOT7X8HDhwo1vGg5FmpwnTVsXjSOXPmpqmgdbiIKD/yurHypLLsCp50vJ7St96TWDEIdDE4HyXvYn8z4R6eVHd7EsoqXMmju7R4Al9fX/n6+ro7G8iHlabydNWxeMo5c6Z5dkHrhARUtFTTehSdp5RlV/G04y2tqSDLIqZZdcT5KHkX+5sJ9/G0utsTUFbhSh4b8AgLC5O3t7eOHj3qkH706FFVr149z/dUr169wPVz/j169Khq1KjhsE6zZs1KMPdwFStVmK46Fk87Z87cNOW3DhcR5ZunleXSVt6OtywiCOSI81HyLuY3E+5B3Z0/yipcwWMDHj4+PmrRooWWLFmi3r17S5Kys7O1ZMkSDRkyJM/3tGnTRkuWLNHw4cPtaYsXL1abNm0kSdHR0apevbqWLFliD3CkpKRo7dq1+r//+7/SPByUMitVmK46FiucMy4iIFmjLBdFeTteALAC6m7APTw24CFJI0aMUFxcnFq2bKlWrVpp4sSJSktLs8/a0r9/f9WsWVPjx4+XJA0bNkzt27fXa6+9ph49eujjjz/W+vXr9c4770iSbDabhg8frueff14NGjRQdHS0nnnmGUVGRtqDKgDKHi4iAAAAAFzIowMed9xxhxISEjR69GgdOXJEzZo106JFi+yDju7fv19eXv+Ou3rNNdfoo48+0tNPP60nn3xSDRo00MKFC3XllVfa13n88ceVlpam+++/X0lJSWrbtq0WLVokPz8/lx8fAAAAAAAoHTZT2MTdcJCSkqKQkBAlJycrODjY3dkBAAAAAFgc96HF47HT0gIAAAAAABQXAQ8AAAAAAGA5BDwAAAAAAIDlEPAAAAAAAACWQ8ADAAAAAABYDgEPAAAAAABgOQQ8AAAAAACA5RDwAAAAAAAAlkPAAwAAAAAAWA4BDwAAAAAAYDkEPAAAAAAAgOUQ8AAAAAAAAJZTwd0ZKGuMMZKklJQUN+cEAAAAAFAe5Nx/5tyPwjkEPIro1KlTkqTatWu7OScAAAAAgPLk1KlTCgkJcXc2ygybIURUJNnZ2Tp06JAqVaokm83m7uzkKyUlRbVr19aBAwcUHBzs7uwA+aKsoqygrKKsoKyiLKCcoqzwlLJqjNGpU6cUGRkpLy9GpnAWLTyKyMvLS7Vq1XJ3NpwWHBzMjwjKBMoqygrKKsoKyirKAsopygpPKKu07Cg6QkMAAAAAAMByCHgAAAAAAADLIeBhUb6+vhozZox8fX3dnRWgQJRVlBWUVZQVlFWUBZRTlBWU1bKNQUsBAAAAAIDl0MIDAAAAAABYDgEPAAAAAABgOQQ8AAAAAACA5RDwAAAAAAAAlkPAw6KmTJmiOnXqyM/PT61bt9a6devcnSWUY+PHj9fVV1+tSpUqqVq1aurdu7d27tzpsM6ZM2c0ePBgVa1aVUFBQbr11lt19OhRN+UY+MdLL70km82m4cOH29Moq/AUBw8e1F133aWqVavK399fjRs31vr16+3LjTEaPXq0atSoIX9/f3Xu3Fm7du1yY45RHmVlZemZZ55RdHS0/P39Va9ePY0bN07nz5tAWYU7rFixQj179lRkZKRsNpsWLlzosNyZcnnixAn169dPwcHBqly5sgYNGqTU1FQXHgUKQ8DDgj755BONGDFCY8aM0caNG9W0aVN17dpVx44dc3fWUE4tX75cgwcP1po1a7R48WKdPXtW119/vdLS0uzrPPzww/rqq680f/58LV++XIcOHdItt9zixlyjvPv11181ffp0NWnSxCGdsgpPcPLkScXExKhixYr67rvvtH37dr322muqUqWKfZ1XXnlFb775pqZNm6a1a9cqMDBQXbt21ZkzZ9yYc5Q3L7/8sqZOnaq33npLO3bs0Msvv6xXXnlFkydPtq9DWYU7pKWlqWnTppoyZUqey50pl/369dO2bdu0ePFiff3111qxYoXuv/9+Vx0CnGFgOa1atTKDBw+2v87KyjKRkZFm/PjxbswV8K9jx44ZSWb58uXGGGOSkpJMxYoVzfz58+3r7Nixw0gyq1evdlc2UY6dOnXKNGjQwCxevNi0b9/eDBs2zBhDWYXneOKJJ0zbtm3zXZ6dnW2qV69uJkyYYE9LSkoyvr6+Zt68ea7IImCMMaZHjx7mnnvucUi75ZZbTL9+/YwxlFV4BklmwYIF9tfOlMvt27cbSebXX3+1r/Pdd98Zm81mDh486LK8o2C08LCYzMxMbdiwQZ07d7aneXl5qXPnzlq9erUbcwb8Kzk5WZIUGhoqSdqwYYPOnj3rUG4vu+wyXXLJJZRbuMXgwYPVo0cPhzIpUVbhOf73v/+pZcuWuv3221WtWjU1b95c7777rn15fHy8jhw54lBWQ0JC1Lp1a8oqXOqaa67RkiVL9Oeff0qSfvvtN61cuVLdu3eXRFmFZ3KmXK5evVqVK1dWy5Yt7et07txZXl5eWrt2rcvzjLxVcHcGULISExOVlZWliIgIh/SIiAj98ccfbsoV8K/s7GwNHz5cMTExuvLKKyVJR44ckY+PjypXruywbkREhI4cOeKGXKI8+/jjj7Vx40b9+uuvuZZRVuEp9uzZo6lTp2rEiBF68skn9euvv2ro0KHy8fFRXFycvTzmdT1AWYUrjRw5UikpKbrsssvk7e2trKwsvfDCC+rXr58kUVbhkZwpl0eOHFG1atUclleoUEGhoaGUXQ9CwAOASw0ePFhbt27VypUr3Z0VIJcDBw5o2LBhWrx4sfz8/NydHSBf2dnZatmypV588UVJUvPmzbV161ZNmzZNcXFxbs4d8K9PP/1Uc+fO1UcffaRGjRpp8+bNGj58uCIjIymrAEodXVosJiwsTN7e3rlmDDh69KiqV6/uplwB/xgyZIi+/vprLV26VLVq1bKnV69eXZmZmUpKSnJYn3ILV9uwYYOOHTumq666ShUqVFCFChW0fPlyvfnmm6pQoYIiIiIoq/AINWrU0BVXXOGQdvnll2v//v2SZC+PXA/A3R577DGNHDlSffv2VePGjXX33Xfr4Ycf1vjx4yVRVuGZnCmX1atXzzUpxLlz53TixAnKrgch4GExPj4+atGihZYsWWJPy87O1pIlS9SmTRs35gzlmTFGQ4YM0YIFC/TTTz8pOjraYXmLFi1UsWJFh3K7c+dO7d+/n3ILl7ruuuu0ZcsWbd682f7XsmVL9evXz/5/yio8QUxMTK7pvf/8809FRUVJkqKjo1W9enWHspqSkqK1a9dSVuFS6enp8vJyvOXw9vZWdna2JMoqPJMz5bJNmzZKSkrShg0b7Ov89NNPys7OVuvWrV2eZ+SNLi0WNGLECMXFxally5Zq1aqVJk6cqLS0NA0cONDdWUM5NXjwYH300Uf68ssvValSJXu/xpCQEPn7+yskJESDBg3SiBEjFBoaquDgYD300ENq06aN/vOf/7g59yhPKlWqZB9bJkdgYKCqVq1qT6eswhM8/PDDuuaaa/Tiiy+qT58+Wrdund555x298847kiSbzabhw4fr+eefV4MGDRQdHa1nnnlGkZGR6t27t3szj3KlZ8+eeuGFF3TJJZeoUaNG2rRpk15//XXdc889kiircJ/U1FTt3r3b/jo+Pl6bN29WaGioLrnkkkLL5eWXX65u3brpvvvu07Rp03T27FkNGTJEffv2VWRkpJuOCrm4e5oYlI7JkyebSy65xPj4+JhWrVqZNWvWuDtLKMck5fk3c+ZM+zqnT582//3vf02VKlVMQECAufnmm83hw4fdl2ng/zt/WlpjKKvwHF999ZW58sorja+vr7nsssvMO++847A8OzvbPPPMMyYiIsL4+vqa6667zuzcudNNuUV5lZKSYoYNG2YuueQS4+fnZ+rWrWueeuopk5GRYV+Hsgp3WLp0aZ7Xp3FxccYY58rl8ePHTWxsrAkKCjLBwcFm4MCB5tSpU244GuTHZowxboq1AAAAAAAAlArG8AAAAAAAAJZDwAMAAAAAAFgOAQ8AAAAAAGA5BDwAAAAAAIDlEPAAAAAAAACWQ8ADAAAAAABYDgEPAAAAAABgOQQ8AABAmXD27Fl3ZwEAAJQhBDwAAHCTRx55RHPmzJExRo8//rjeeustd2fJoyxbtky33Xab6tWrp5CQEEVFRckY4+5sAQCAMsJmuHIAABTBgAED9MEHH+S7/OTJk6pcubLrMlSGbdu2Tdddd52OHz+uOnXq6JdfflF4eLi7s+UR5s6dqwcffFBPPfWUbrjhBgUEBKhSpUqKiIhwd9YAAEAZQcADAFAkAwYM0NGjRzVz5kyH9F9++UW33norAY8iOnfunI4dO6bq1avLy4uGl5KUmpqq2rVr69NPP1WXLl3cnR0AAFBGcWUFACgyX19fVa9e3eEvNDQ013qff/65GjVqJF9fX9WpU0evvfaaw/I6depo3Lhxio2NVWBgoGrWrKkpU6Y4rPPHH3+oS5cuCgkJkc1mk81myxVQ2bt3r33Z+X9JSUn2dWw2mxYuXChJMsaof//+atKkiU6ePGlfZ+rUqapXr558fHzUsGFDzZkzx2E/5287ODhYXbp00V9//eVwPBMnTszznPXu3VsDBgzItW6FChUUGRmppUuXymazqXfv3nm+X5JmzZqV77Fv3rzZnrZ8+XK1atVKvr6+qlGjhkaOHKlz587Zl3fo0EE2m01ffPGFw7aaN28um82mZcuW2dO2bt2q7t27KygoSBEREbr77ruVmJjosK0hQ4ZoyJAhCgkJUVhYmJ555plCu54UdK5//vln+fv7a8GCBYqMjFRAQIA6d+6sbdu2SZLWr1/v8FkMHz68wH19+eWXuuqqq+Tn56e6devqueeeczgfBZWNWbNm5Vm2bDab6tSpI0n666+/1KtXL0VERCgoKEhXX321fvzxxwLz9Oyzz9q3U6FChTy/H4W9L+fv/DJz/PhxxcbGqmbNmgoICFDjxo01b948+/IBAwbkezw55XPRokVq27atKleurKpVq+rGG290KOeS9Pfffys2NlahoaEKDAxUy5YttXbtWqfOeZ06dfLNw6xZsyRJSUlJuvfeexUeHq7g4GB16tRJv/32W6HnBwCA8xHwAACUig0bNqhPnz7q27evtmzZomeffVbPPPOM/YYmx4QJE9S0aVNt2rRJI0eO1LBhw7R48WL78nvuuUdnz57VqlWrdPjw4XwDCpL0448/6vDhw/r8888LzNvQoUP1yy+/6IcfflCVKlUkSQsWLNCwYcP0yCOPaOvWrXrggQc0cOBALV261OG9M2fO1OHDh7VixQodO3ZMTz75ZNFOTB6ys7P1yCOPKCgo6KK3dfDgQd1www26+uqr9dtvv2nq1KmaMWOGnn/+eYf1atasqXfeecf+et26dUpISHBYJykpSZ06dVLz5s21fv16LVq0SEePHlWfPn0c1vvggw9UoUIFrVu3TpMmTdLrr7+u9957L988FnauExISdPjwYS1btkwff/yx1q5dq0qVKqlbt246ffq0mjVrpsOHD+vw4cNq06ZNgefj559/Vv/+/TVs2DBt375d06dP16xZs/TCCy/kuf6FZeOOO+6w72vixImqVauW/fWvv/4q6Z8WKTfccIOWLFmiTZs2qVu3burZs6f2799fYN4aNWqkw4cPa+/evRo2bJgeffRR7dixo8D3nP++w4cP5/oszpw5oxYtWuibb77R1q1bdf/99+vuu+/WunXrJEmTJk1yeG+fPn3srydNmiRJSktL04gRI7R+/XotWbJEXl5euvnmm5WdnW0/3vbt2+vgwYP63//+p99++02PP/64fXlh5/zXX3+177NWrVqaOHGi/fUdd9whSbr99tt17Ngxfffdd9qwYYOuuuoqXXfddTpx4kSh5wcAADsDAEARxMXFmV69euVKX7p0qZFkTp48aYwx5s477zRdunRxWOexxx4zV1xxhf11VFSU6datm8M6d9xxh+nevbv9tb+/v5k7d6799cyZM01ISIjDe/744w8jyWzdujXPvBhjjCSzYMEC89RTT5maNWua+Ph4h21cc8015r777nNIu/32280NN9yQaxvGGJOUlGRiYmIc3hMVFWXeeOONXOfGGGN69epl4uLi8lz3/fffN5dddpnp169fnue2oGOPj483ksymTZuMMcY8+eSTpmHDhiY7O9u+zpQpU0xQUJDJysoyxhjTvn1783//93+mWrVqZu/evcYYYwYNGmSeeeYZI8ksXbrUGGPMuHHjzPXXX++wvwMHDhhJZufOnfZtXX755Q77e+KJJ8zll1+e73EUdq5nzpxpJJlVq1bZl6ekpJjKlSubd9991+F97du3N8OGDct3X9ddd5158cUXHdLmzJljatSoYX9dWNnIMXPmTBMVFZXvvs7XqFEjM3ny5HyXjxkzxjRt2tT++rPPPjPe3t5m3759BW535MiRpmXLlvbX+X0fz9ejRw/zyCOP5EqPi4tzKJP5SUhIMJLMli1bjDHGTJ8+3VSqVMkcP348z/WdOec5oqKizMyZMx3Sfv75ZxMcHGzOnDnjkF6vXj0zffr0QvMLAEAOWngAAErFjh07FBMT45AWExOjXbt2KSsry5524RP6Nm3aODzljo6O1oIFC5Senp7vvo4fPy5JCg4OLjBPb731ll544QU1bNjQ3h2hsPxe+MQ9NjZWQUFBqlKlik6dOqXx48c7LH/iiScUFBSkatWqqUOHDlq1alWBeUpPT9fTTz+tV155RRUqVChwXUlKTk5WUFCQ/a9Ro0a5jqNNmzay2WwOx5Gamqq///7bnubj46O7775b7733nlJSUrRgwQL179/fYVu//fabli5d6rC/yy67TJIcujj85z//cdhfmzZtcn3OF+axsHNdoUIFtW7d2v66UqVKatq0qbZv355re2+//baCgoIUGhqqli1bav78+Q7HMHbsWIdjuO+++3T48GGHMlVQ2ShMamqqHn30UV1++eWqXLmygoKCtGPHjkJbeGzZskVBQUHy8/NT37599eabb+qSSy4p8D3Hjx8vsJxnZWVp3Lhxaty4sUJDQxUUFKTvv/++0Lycb9euXYqNjVXdunUVHBxsPx8529i8ebOaN2+eZzc2yflznp/ffvtNqampqlq1qsM24uPjc3WtAQCgIIVfWQEA4EYzZsxQXFycKlWqJH9/f507d05+fn4O6+zZs0c+Pj6KjIwscFvr1q3Tt99+qwEDBmj69Ol64IEHipyfN954Q507d1ZSUpKeeuopDRgwQF999ZV9+WOPPaYBAwYoLS1NEyZMUM+ePXXkyJF8tzdhwgQ1bNhQPXv2LLQrjvTPjf/GjRvtrw8ePKgOHToU+Tgk6f7771enTp0UERGh66+/XmFhYQ7LU1NT1bNnT7388su53lujRo1i7dMZOd2M8nJ+YCVHv3799NRTTykjI0OfffaZYmNj1aRJEzVs2FCpqal67rnndMstt+R63/nl6GLKxqOPPqrFixfr1VdfVf369eXv76/bbrtNmZmZBb6vYcOG+t///qesrCytWbNGgwcP1lVXXaX//Oc/+b5nz549io6Oznf5hAkTNGnSJE2cOFGNGzdWYGCghg8fXmheztezZ09FRUXp3XffVWRkpLKzs3XllVfat+Hv71/g+5095wW9v0aNGg5jyeRgQGQAQFEQ8AAAlIrLL788V+uGVatW6dJLL5W3t7c9bc2aNQ7rrFmzRpdffrn99X/+8//au7eQqNYwDMDvNsYaUUepbIimRBpPF1KSsZNCBS+0Cw9JF1pZglAYklgRmXkgCioIwxPYAZNOIGMGXZSSqDWG2UUiYjOdhhFqKjSjKEPl2xfiYpYz47jbJOR+HxgE/7V+v/XNf+M/s971N9LS0tDd3Y3r16/jzp07OHPmjOqcrq4uxMfHq+Z1p6qqCqmpqairq0NeXh5SU1OVT9Rn6t27d6+q3ujoaNUcer0e69evBwAUFhYiLS0NExMT0Gg0AIAVK1Yo48ePH8eNGzc8frr+/v171NfXo6ura866nfn4+CjzA3D5VkhUVBRMJhNERNkcMJvNCAgIwJo1a1THhoeHw2g0oqSkRAntdBYbGwuTyYTQ0NA5v33iHFYJTL+HRqPR4/vhrdeRkZGYnJxEb28v4uPjAQBfv35Ff38/9uzZ4zKfTqdTehIdHY3Tp09jYGAAERERiI2NhcViUfXMnbnWhjdmsxn79u1DZmYmgOl/2G02m9fzfH19lboiIiJQXV2Ne/fuedzwGB8fx9OnT932wLmW9PR07N69G8B0PozVanVZx56MjIzAYrHg0qVL2LZtGwDg8ePHqmNiYmJw+fJljI6Ouv2Wx3x77klsbCwcDocS5kpERPSreEsLERH9FocPH8bDhw9x6tQpWK1WXLt2DTU1NThy5IjqOLPZjHPnzsFqtaK2thbNzc04dOiQMm4ymdDY2Ijm5mYYjUaEhIQoY1NTU+ju7sbNmzexY8cOOBwOOBwOJdjw48ePqr81889ZVlYWtm/fjvz8fGXs6NGjaGxsRH19PV6+fIkLFy6gpaXFpd6xsTE4HA5YLBZcuXIFYWFhymYHMP2Y2fHxcYyMjODq1avQ6XQwGAxue1RbW4vMzExs3Ljx37R2TgUFBRgeHkZhYSFevHiBu3fvory8HMXFxW4fe3v27FlUVFQgKSnJZezgwYMYHR1FdnY2+vr68Pr1azx48AB5eXmq21XsdjuKi4thsVhw69YtVFdXq97D2bz1OiIiAqmpqcjPz8ejR48wMDCA3Nxc+Pv7Iycnx2W+79+/w+FwwG63o6qqClNTU8qtPmVlZWhqakJlZSUGBwcxNDSE27dvo7S0VDXHXGvDG6PRiJaWFjx//hz9/f3IyclRAjznMjk5CYfDgXfv3qG1tRWDg4PKLUOzffv2DWVlZQCArVu3Kmv9x48f+PnzJ758+aLU0t7ejp6eHgwNDWH//v348OHDvK8lODgYy5cvR0NDA169eoWOjg4UFxerjsnOzoZer0dGRgbMZjPevHkDk8mEJ0+eAJh/zz1JTk7Gli1bkJGRgba2NthsNvT09ODEiRN49uzZvK+FiIiIoaVERPSvzDe0VGQ6iDE6Olo0Go2sXbtWzp8/rzpn3bp1UllZKTt37hQ/Pz/R6/Vy8eJFZdxisUhQUJC0tbUpv3MO7pwJ7JzrNQNOgaMi00GMISEhqhDEuro6CQsLE41GI+Hh4dLU1KSq13negIAASUhIUMJCZ65nZlyr1UpcXJx0dHSIiPvQUq1WK8PDw1576+7aZ8wOLRUR6ezslLi4OPH19RW9Xi/Hjh2TiYkJZdxT0Ofnz59VoaUiIlarVTIzMyUoKEi0Wq1ERkZKUVGRElKakJAgBQUFcuDAAQkMDJTg4GApKSlRhZi6463Xnz59kpycHNHpdKLVaiU5OVkGBwdd5klISFB67uvrK1FRUS5z3b9/X+Lj40Wr1UpgYKBs3rxZGhoalPH5rA0Rz6Glb9++laSkJNFqtWIwGKSmpsZrmGp5eblSt4+PjxgMBjl58qTHvjkf7+41s7ZGRkYkPT1d/P39JSQkREpLSyU3N9ftuvIUWtre3i5RUVGydOlSiYmJkc7OTpce2Ww2ycrKksDAQPHz85NNmzZJb2+vMu6t5zPchZaKTIfUFhYWyurVq0Wj0YjBYJBdu3aJ3W732FMiIqLZ/hIRWYiNFSIiotlCQ0NRVFSEoqKiXzrfZrMhMTHR4+0DQUFBGBsb++X6yLvExERs2LBhzscF039XUVGh+umstbUVra2tLo98JiIi+r9jhgcREf2xlixZgpUrV3ocX7Vq1QJWQ/T7+Pv7exxbtmwZdDrdAlZDRET0Z+CGBxER/bEMBgP6+vo8jlsslgWshuj3mZ0l4ywlJQUpKSkLWA0REdGfgbe0EBEREREREdGiw6e0EBEREREREdGiww0PIiIiIiIiIlp0uOFBRERERERERIsONzyIiIiIiIiIaNHhhgcRERERERERLTrc8CAiIiIiIiKiRYcbHkRERERERES06HDDg4iIiIiIiIgWnX8AE2okAYkr0U0AAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data1 = df[:100].copy()\n",
+    "data1['diameter_dif'] = data1['est_diameter_max'] - data1['est_diameter_min']\n",
+    "data1['index'] = data1.index\n",
+    "data1.plot(kind='scatter', x='index', xlabel='Порядковый номер объекта в датасете', y='diameter_dif', ylabel='Разница', figsize=(12, 6), title='Разница между макс. диаметром (est_diameter_max) и мин диаметром (est_diameter_min) объекта (первые 100 записей)')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## На диаграмме ниже показана средняя скорость относительно Земли для космических объектов, которые потенциально опасны (hazardous=true) и неопасны (hazardous=false). С помощью неё можно сделать вывод о том, что потенциально опасны те космические объекты, у которых относительная скорость в среднем больше 60 000 км/с"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x22b94809250>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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mTp2qhIQESdJHH31knr2KiopSfHy8+XncuHGSLl6WlZycrGXLlum7775T79691bVr16sGhetVVFSk+Ph4eXt7O8w/f/684uLitGPHDiUlJcnFxUUPP/ywioqKHOoMw9Dw4cPN/alTp84N73HIkCHasWOHVq9ereTkZBmGoYceekj5+fll7lOPHj106tQpbdq0SevXr9ePP/6ovn37OtQ1a9bsimcWc3JyFBERoTVr1mjPnj168sknNXDgQG3bts2smTx5smbNmqWpU6dq3759Wrp0qQICAm74MSjN+fPnNXXq1BI/OwAAgDsF90BVUK+++qoeeOABTZ06VZLUuHFj7du3T3PmzNGQIUMczli5ubnJ29tbgYGB5ry0tDQtXrxYaWlpCgoKkiSNGzdOiYmJWrx4sV566aWb1vuSJUuUm5urHj166Ny5c+b8Xr16OdS9++67qlGjhvbt26fmzZub8/Pz8+Xr62vuj6ur6w3t79ChQ1q9erU2b96se++9V5L0/vvvKzg4WKtWrVLv3r1LrJOUlKTdu3fryJEjCg4OliT961//UrNmzbR9+3bdc889kqRKlSo5/BwuP7NYu3ZtM+BK0qhRo7Ru3TqtWLFCbdu21dmzZzVv3jzNnz9fgwcPliTddddd6tChww09BmWZPXu2wsLCVFBQcEu2BwAAcKNxBqqC2r9/v9q3b+8wr3379jp06JAKCwuvuv7u3btVWFioxo0by9vb25w2bdrkcNlcVlaWw/JmzZpdV9+///67pkyZotmzZ6tSJcf8f+jQIfXv318NGzaU3W5X/fr1JV0Me5fKzs5WlSpVrride++9Vz4+PgoODlbfvn31yy+/OCzv37+/w3599dVX5rL9+/erUqVKioyMNOf5+/urSZMm2r9/f6nb279/v4KDg83wJElhYWHy8/Mrc53SFBYWasaMGQoPD1e1atXk7e2tdevWmcdg//79ys3N1QMPPHDV/b90/y4/hpceg1q1aik2Nlb79u274pjHjh3Tq6++6nCpKAAAwJ2m3AHq119/1WOPPSZ/f395enoqPDxcO3bsMJcbhqFp06apVq1a8vT0VHR0dIlLuk6dOqUBAwbIbrfLz89Pw4YNcziTIEnfffed7rvvPnl4eCg4OFizZ88u0cvKlSvVtGlTeXh4KDw8XGvXri3v7uAanTt3Tq6urkpJSVFqaqo57d+/X/PmzTPrfHx8HJZf789ozpw5atKkibp3715iWffu3XXq1CktWrRIW7du1datWyVJeXl5DnXHjh0zz5qVZfny5fr222/1n//8R4cOHdJTTz3lsPy1115z2K82bdpc137dKHPmzNG8efM0ceJEffHFF0pNTVVMTIx5DDw9PS2Ns3z5cof9K+14FR+DTz/9VPn5+erTp88Vx3z22WfVu3dvtWjRovw7BgAAcJso1yV8p0+fVvv27dW5c2d9/vnnqlGjhg4dOqSqVauaNbNnz9brr7+uJUuWqEGDBpo6dapiYmK0b98+88lbAwYM0PHjx7V+/Xrl5+dr6NChevLJJ7V06VJJF88QdOnSRdHR0Vq4cKF2796txx9/XH5+fnryySclSVu2bFH//v01c+ZMdevWTUuXLlXPnj21c+dOh8u1ULrQ0FBt3rzZYd7mzZvVuHFjS5e0tWrVSoWFhTpx4oTuu+++MutcXFwUEhJifr78rFF5HD9+XG+++aY2bdpUYtnJkyd18OBBLVq0yOzn66+/LlF3+PBhnT59Wq1atbritoKDgxUSEqKQkBANGzZMM2fOdFgeGBjosF+XBpPQ0FAVFBRo69at5iV8xf2FhYWVur3Q0FAdPXpUR48eNc9C7du3T2fOnClzndJs3rxZPXr00GOPPSbp4r1V33//vTlGo0aN5OnpqaSkJD3xxBNX3f9ipf3cLj0Go0ePVvfu3cu8xys1NVUffPCBDh48aHlfAAAAbkfl+tfsP/7xDwUHB2vx4sXmvAYNGpi/NgxDc+fO1ZQpU9SjRw9JF+/jCAgI0KpVq9SvXz/t379fiYmJ2r59u/m/9v/85z/10EMP6eWXX1ZQUJDef/995eXl6d1335Wbm5uaNWum1NRUvfrqq2aAmjdvnrp27arx48dLkmbMmKH169dr/vz5Wrhw4fUdlQogPj5e99xzj2bMmKG+ffsqOTlZ8+fP1xtvvGFp/caNG2vAgAEaNGiQXnnlFbVq1UqZmZlKSkrS3XffrdjY2HL1k5ubq5zLHhGfn5+voqIiubhcPFG6YMEC9erVq9TwU7VqVfn7++vtt99WrVq1lJaWpkmTJjnU7NixQ88884zCw8OvesYoLy9POTk5ysjI0AcffFCuUN6oUSP16NFDw4cP11tvvSUfHx9NmjRJtWvXNv9cXC46Olrh4eEaMGCA5s6dq4KCAv3tb39Tx44dy3V2q1GjRvrggw+0ZcsWVa1aVa+++qoyMjLMAOXh4aGJEydqwoQJcnNzU/v27ZWZmam9e/dq2LBhlrcjXfz55OTk6MyZM/r3v/+txo0bq3LlyqXWvvzyy4qPj7/qmT8AAIDbXbku4Vu9erXatGmj3r17q2bNmmrVqpUWLVpkLj9y5IjS09MdXpLp6+uryMhIJScnS5KSk5Pl5+fn8I/C6Ohoubi4mJdcJScn6/7775ebm5tZExMTo4MHD+r06dNmzeUv44yJiTG3U5rc3FxlZ2c7TOVSvfrFF9veSh4eF7d7g7Vu3VorVqzQsmXL1Lx5c02bNk0vvPCChgwZYnmMxYsXa9CgQYqPj1eTJk3Us2dPbd++XXUtvvT3UoGBgfL09DQnSerTp4++/PJLs6aoqMh83PblXFxctGzZMqWkpKh58+YaO3as5syZ41AzduxY1alTR2vXrpXNZrtiP5GRkfL09FTLli3l7e2tt956q1z7s3jxYkVERKhbt26KioqSYRhau3ZtmQHDZrPpk08+UdWqVXX//fcrOjpaDRs21PLly8u13SlTpqh169aKiYlRp06dFBgY6PCod0maOnWq4uPjNW3aNIWGhqpv3746ceJEubYjXfz5eHp6qnHjxjp+/PgVe/Xx8dGECRPKvQ0AAIDbjc0wDMNqcfEleHFxcerdu7e2b9+u0aNHa+HChRo8eLC2bNmi9u3b69ixY6pVq5a5Xp8+fWSz2bR8+XK99NJLWrJkSYlLeWrWrKnnn39eTz/9tLp06aIGDRo4/KN13759atasmfbt26fQ0FC5ublpyZIl6t+/v1nzxhtv6Pnnn3d4d86lpk+frueff77E/KysLNntdod5OTk5OnLkiBo0aOD40s+0tHK/2Pa6VK8uXUMg+SPo2bOnxowZo06dOjm7FfwBlPlnGsDt4Sr/sQVUCNb/WY6bIDs7W76+vqVmg0uV6xK+oqIitWnTxnxEdatWrbRnzx4zQN3uJk+erLi4OPNzdna2w1PPLKlbt8IGmlvNzc3NvHwPAAAAuB2UK0DVqlWrxA3toaGh5ss8i99Pk5GR4XAGKiMjQy1btjRrLr9cqKCgQKdOnTLXDwwMLHEWqfjz1WoufUfO5dzd3eXu7m5pX+F8K1ascHYLAAAAgINy/fd++/btS1x69/3336tevXqSLj5QIjAwUElJSeby7Oxsbd26VVFRUZKkqKgonTlzRikpKWbNhg0bVFRUZL43JyoqSl9++aXDE73Wr1+vJk2amE/8i4qKcthOcU3xdgAAAADgRitXgBo7dqy++eYbvfTSS/rhhx+0dOlSvf322xoxYoSkizfCjxkzRn//+9+1evVq7d69W4MGDVJQUJB5I3toaKi6du2q4cOHa9u2bdq8ebNGjhypfv36mU/oevTRR+Xm5qZhw4Zp7969Wr58uebNm+dw+d3o0aOVmJioV155RQcOHND06dO1Y8cOjRw58gYdGgAAAAC4jFFOn376qdG8eXPD3d3daNq0qfH22287LC8qKjKmTp1qBAQEGO7u7sYDDzxgHDx40KHm5MmTRv/+/Q1vb2/DbrcbQ4cONc6ePetQs2vXLqNDhw6Gu7u7Ubt2bWPWrFklelmxYoXRuHFjw83NzWjWrJmxZs2acu1LVlaWIcnIysoqsezChQvGvn37jN9//71cYwK4Pf3+++/Gvn37jAsXLji7FQCluXj7PBNTxZ7gVFfKBpcq11P4/miu9KSN/Px8/fDDDwoKCpKvr6+TOgRwo2RlZenYsWMKCQkp83HyAJyIp/ABF2MUnOamPIWvIqlUqZK8vLyUmZmpypUr8zQ44A5WVFSkzMxMeXl5qVIl/toDAADXjn9JlMFms6lWrVo6cuSIfv75Z2e3A+A6ubi4qG7duld9iTIAAMCVEKCuwM3NTY0aNVJeXp6zWwFwnXivGAAAuBEIUFfh4uIiDw8PZ7cBAAAA4DbAf8cCAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAi8oVoKZPny6bzeYwNW3a1Fyek5OjESNGyN/fX97e3urVq5cyMjIcxkhLS1NsbKy8vLxUs2ZNjR8/XgUFBQ41GzduVOvWreXu7q6QkBAlJCSU6GXBggWqX7++PDw8FBkZqW3btpVnVwAAAACg3Mp9BqpZs2Y6fvy4OX399dfmsrFjx+rTTz/VypUrtWnTJh07dkyPPPKIubywsFCxsbHKy8vTli1btGTJEiUkJGjatGlmzZEjRxQbG6vOnTsrNTVVY8aM0RNPPKF169aZNcuXL1dcXJyee+457dy5Uy1atFBMTIxOnDhxrccBAAAAAK7KZhiGYbV4+vTpWrVqlVJTU0ssy8rKUo0aNbR06VL95S9/kSQdOHBAoaGhSk5OVrt27fT555+rW7duOnbsmAICAiRJCxcu1MSJE5WZmSk3NzdNnDhRa9as0Z49e8yx+/XrpzNnzigxMVGSFBkZqXvuuUfz58+XJBUVFSk4OFijRo3SpEmTLO98dna2fH19lZWVJbvdbnk9AABwg9lszu4AcD7r/yzHTWA1G5T7DNShQ4cUFBSkhg0basCAAUpLS5MkpaSkKD8/X9HR0WZt06ZNVbduXSUnJ0uSkpOTFR4eboYnSYqJiVF2drb27t1r1lw6RnFN8Rh5eXlKSUlxqHFxcVF0dLRZAwAAAAA3Q6XyFEdGRiohIUFNmjTR8ePH9fzzz+u+++7Tnj17lJ6eLjc3N/n5+TmsExAQoPT0dElSenq6Q3gqXl687Eo12dnZunDhgk6fPq3CwsJSaw4cOHDF/nNzc5Wbm2t+zs7Otr7zAAAAACq8cgWoBx980Pz13XffrcjISNWrV08rVqyQp6fnDW/uRps5c6aef/55Z7cBAAAA4A51XY8x9/PzU+PGjfXDDz8oMDBQeXl5OnPmjENNRkaGAgMDJUmBgYElnspX/PlqNXa7XZ6enqpevbpcXV1LrSkeoyyTJ09WVlaWOR09erTc+wwAAACg4rquAHXu3DkdPnxYtWrVUkREhCpXrqykpCRz+cGDB5WWlqaoqChJUlRUlHbv3u3wtLz169fLbrcrLCzMrLl0jOKa4jHc3NwUERHhUFNUVKSkpCSzpizu7u6y2+0OEwAAAABYVa4ANW7cOG3atEk//fSTtmzZoocffliurq7q37+/fH19NWzYMMXFxemLL75QSkqKhg4dqqioKLVr106S1KVLF4WFhWngwIHatWuX1q1bpylTpmjEiBFyd3eXJD311FP68ccfNWHCBB04cEBvvPGGVqxYobFjx5p9xMXFadGiRVqyZIn279+vp59+WufPn9fQoUNv4KEBAAAAAEflugfql19+Uf/+/XXy5EnVqFFDHTp00DfffKMaNWpIkl577TW5uLioV69eys3NVUxMjN544w1zfVdXV3322Wd6+umnFRUVpSpVqmjw4MF64YUXzJoGDRpozZo1Gjt2rObNm6c6deronXfeUUxMjFnTt29fZWZmatq0aUpPT1fLli2VmJhY4sESuP3x1FqAp9YCAHAnKdd7oP5oeA+U8xGgAAIUIIkvBEDiC8HJbtp7oAAAAACgoiJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALDougLUrFmzZLPZNGbMGHNeTk6ORowYIX9/f3l7e6tXr17KyMhwWC8tLU2xsbHy8vJSzZo1NX78eBUUFDjUbNy4Ua1bt5a7u7tCQkKUkJBQYvsLFixQ/fr15eHhocjISG3btu16dgcAAAAAruiaA9T27dv11ltv6e6773aYP3bsWH366adauXKlNm3apGPHjumRRx4xlxcWFio2NlZ5eXnasmWLlixZooSEBE2bNs2sOXLkiGJjY9W5c2elpqZqzJgxeuKJJ7Ru3TqzZvny5YqLi9Nzzz2nnTt3qkWLFoqJidGJEyeudZcAAAAA4MqMa3D27FmjUaNGxvr1642OHTsao0ePNgzDMM6cOWNUrlzZWLlypVm7f/9+Q5KRnJxsGIZhrF271nBxcTHS09PNmjfffNOw2+1Gbm6uYRiGMWHCBKNZs2YO2+zbt68RExNjfm7btq0xYsQI83NhYaERFBRkzJw50/J+ZGVlGZKMrKws6zuPG0piYmICYDj/DyIT0+0wwamsZoNrOgM1YsQIxcbGKjo62mF+SkqK8vPzHeY3bdpUdevWVXJysiQpOTlZ4eHhCggIMGtiYmKUnZ2tvXv3mjWXjx0TE2OOkZeXp5SUFIcaFxcXRUdHmzWlyc3NVXZ2tsMEAAAAAFZVKu8Ky5Yt086dO7V9+/YSy9LT0+Xm5iY/Pz+H+QEBAUpPTzdrLg1PxcuLl12pJjs7WxcuXNDp06dVWFhYas2BAwfK7H3mzJl6/vnnre0oAAAAAFymXGegjh49qtGjR+v999+Xh4fHzerpppk8ebKysrLM6ejRo85uCQAAAMAdpFwBKiUlRSdOnFDr1q1VqVIlVapUSZs2bdLrr7+uSpUqKSAgQHl5eTpz5ozDehkZGQoMDJQkBQYGlngqX/Hnq9XY7XZ5enqqevXqcnV1LbWmeIzSuLu7y263O0wAAAAAYFW5AtQDDzyg3bt3KzU11ZzatGmjAQMGmL+uXLmykpKSzHUOHjyotLQ0RUVFSZKioqK0e/duh6flrV+/Xna7XWFhYWbNpWMU1xSP4ebmpoiICIeaoqIiJSUlmTUAAAAAcKOV6x4oHx8fNW/e3GFelSpV5O/vb84fNmyY4uLiVK1aNdntdo0aNUpRUVFq166dJKlLly4KCwvTwIEDNXv2bKWnp2vKlCkaMWKE3N3dJUlPPfWU5s+frwkTJujxxx/Xhg0btGLFCq1Zs8bcblxcnAYPHqw2bdqobdu2mjt3rs6fP6+hQ4de1wEBAAAAgLKU+yESV/Paa6/JxcVFvXr1Um5urmJiYvTGG2+Yy11dXfXZZ5/p6aefVlRUlKpUqaLBgwfrhRdeMGsaNGigNWvWaOzYsZo3b57q1Kmjd955RzExMWZN3759lZmZqWnTpik9PV0tW7ZUYmJiiQdLAAAAAMCNYjMMw3B2E86SnZ0tX19fZWVlcT+Uk9hszu4AcL6K+7cwcAm+EAC+EJzMaja4pvdAAQAAAEBFRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLyhWg3nzzTd19992y2+2y2+2KiorS559/bi7PycnRiBEj5O/vL29vb/Xq1UsZGRkOY6SlpSk2NlZeXl6qWbOmxo8fr4KCAoeajRs3qnXr1nJ3d1dISIgSEhJK9LJgwQLVr19fHh4eioyM1LZt28qzKwAAAABQbuUKUHXq1NGsWbOUkpKiHTt26L/+67/Uo0cP7d27V5I0duxYffrpp1q5cqU2bdqkY8eO6ZFHHjHXLywsVGxsrPLy8rRlyxYtWbJECQkJmjZtmllz5MgRxcbGqnPnzkpNTdWYMWP0xBNPaN26dWbN8uXLFRcXp+eee047d+5UixYtFBMToxMnTlzv8QAAAACAMtkMwzCuZ4Bq1appzpw5+stf/qIaNWpo6dKl+stf/iJJOnDggEJDQ5WcnKx27drp888/V7du3XTs2DEFBARIkhYuXKiJEycqMzNTbm5umjhxotasWaM9e/aY2+jXr5/OnDmjxMRESVJkZKTuuecezZ8/X5JUVFSk4OBgjRo1SpMmTbLce3Z2tnx9fZWVlSW73X49hwHXyGZzdgeA813f38LAHwRfCABfCE5mNRtc8z1QhYWFWrZsmc6fP6+oqCilpKQoPz9f0dHRZk3Tpk1Vt25dJScnS5KSk5MVHh5uhidJiomJUXZ2tnkWKzk52WGM4priMfLy8pSSkuJQ4+LioujoaLMGAAAAAG6GSuVdYffu3YqKilJOTo68vb318ccfKywsTKmpqXJzc5Ofn59DfUBAgNLT0yVJ6enpDuGpeHnxsivVZGdn68KFCzp9+rQKCwtLrTlw4MAVe8/NzVVubq75OTs72/qOAwAAAKjwyn0GqkmTJkpNTdXWrVv19NNPa/Dgwdq3b9/N6O2Gmzlzpnx9fc0pODjY2S0BAAAAuIOUO0C5ubkpJCREERERmjlzplq0aKF58+YpMDBQeXl5OnPmjEN9RkaGAgMDJUmBgYElnspX/PlqNXa7XZ6enqpevbpcXV1LrSkeoyyTJ09WVlaWOR09erS8uw8AAACgArvu90AVFRUpNzdXERERqly5spKSksxlBw8eVFpamqKioiRJUVFR2r17t8PT8tavXy+73a6wsDCz5tIximuKx3Bzc1NERIRDTVFRkZKSksyasri7u5uPYC+eAAAAAMCqct0DNXnyZD344IOqW7euzp49q6VLl2rjxo1at26dfH19NWzYMMXFxalatWqy2+0aNWqUoqKi1K5dO0lSly5dFBYWpoEDB2r27NlKT0/XlClTNGLECLm7u0uSnnrqKc2fP18TJkzQ448/rg0bNmjFihVas2aN2UdcXJwGDx6sNm3aqG3btpo7d67Onz+voUOH3sBDAwAAAACOyhWgTpw4oUGDBun48ePy9fXV3XffrXXr1ulPf/qTJOm1116Ti4uLevXqpdzcXMXExOiNN94w13d1ddVnn32mp59+WlFRUapSpYoGDx6sF154waxp0KCB1qxZo7Fjx2revHmqU6eO3nnnHcXExJg1ffv2VWZmpqZNm6b09HS1bNlSiYmJJR4sAQAAAAA30nW/B+pOxnugnI/XfgC89gOQxBcCIPGF4GQ3/T1QAAAAAFDREKAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWFSuADVz5kzdc8898vHxUc2aNdWzZ08dPHjQoSYnJ0cjRoyQv7+/vL291atXL2VkZDjUpKWlKTY2Vl5eXqpZs6bGjx+vgoICh5qNGzeqdevWcnd3V0hIiBISEkr0s2DBAtWvX18eHh6KjIzUtm3byrM7AAAAAFAu5QpQmzZt0ogRI/TNN99o/fr1ys/PV5cuXXT+/HmzZuzYsfr000+1cuVKbdq0SceOHdMjjzxiLi8sLFRsbKzy8vK0ZcsWLVmyRAkJCZo2bZpZc+TIEcXGxqpz585KTU3VmDFj9MQTT2jdunVmzfLlyxUXF6fnnntOO3fuVIsWLRQTE6MTJ05cz/EAAAAAgDLZDMMwrnXlzMxM1axZU5s2bdL999+vrKws1ahRQ0uXLtVf/vIXSdKBAwcUGhqq5ORktWvXTp9//rm6deumY8eOKSAgQJK0cOFCTZw4UZmZmXJzc9PEiRO1Zs0a7dmzx9xWv379dObMGSUmJkqSIiMjdc8992j+/PmSpKKiIgUHB2vUqFGaNGmSpf6zs7Pl6+urrKws2e32az0MuA42m7M7AJzv2v8WBv5A+EIA+EJwMqvZ4LrugcrKypIkVatWTZKUkpKi/Px8RUdHmzVNmzZV3bp1lZycLElKTk5WeHi4GZ4kKSYmRtnZ2dq7d69Zc+kYxTXFY+Tl5SklJcWhxsXFRdHR0WZNaXJzc5Wdne0wAQAAAIBV1xygioqKNGbMGLVv317NmzeXJKWnp8vNzU1+fn4OtQEBAUpPTzdrLg1PxcuLl12pJjs7WxcuXNBvv/2mwsLCUmuKxyjNzJkz5evra07BwcHl33EAAAAAFdY1B6gRI0Zoz549WrZs2Y3s56aaPHmysrKyzOno0aPObgkAAADAHaTStaw0cuRIffbZZ/ryyy9Vp04dc35gYKDy8vJ05swZh7NQGRkZCgwMNGsuf1pe8VP6Lq25/Ml9GRkZstvt8vT0lKurq1xdXUutKR6jNO7u7nJ3dy//DgMAAACAynkGyjAMjRw5Uh9//LE2bNigBg0aOCyPiIhQ5cqVlZSUZM47ePCg0tLSFBUVJUmKiorS7t27HZ6Wt379etntdoWFhZk1l45RXFM8hpubmyIiIhxqioqKlJSUZNYAAAAAwI1WrjNQI0aM0NKlS/XJJ5/Ix8fHvN/I19dXnp6e8vX11bBhwxQXF6dq1arJbrdr1KhRioqKUrt27SRJXbp0UVhYmAYOHKjZs2crPT1dU6ZM0YgRI8yzQ0899ZTmz5+vCRMm6PHHH9eGDRu0YsUKrVmzxuwlLi5OgwcPVps2bdS2bVvNnTtX58+f19ChQ2/UsQEAAAAAR0Y5SCp1Wrx4sVlz4cIF429/+5tRtWpVw8vLy3j44YeN48ePO4zz008/GQ8++KDh6elpVK9e3YiPjzfy8/Mdar744gujZcuWhpubm9GwYUOHbRT75z//adStW9dwc3Mz2rZta3zzzTfl2R0jKyvLkGRkZWWVaz3cOBef18nEVLEnAIbz/yAyMd0OE5zKaja4rvdA3el4D5Tz8doP4OK3JlDh8YUA8IXgZLfkPVAAAAAAUJEQoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwKJyB6gvv/xS3bt3V1BQkGw2m1atWuWw3DAMTZs2TbVq1ZKnp6eio6N16NAhh5pTp05pwIABstvt8vPz07Bhw3Tu3DmHmu+++0733XefPDw8FBwcrNmzZ5foZeXKlWratKk8PDwUHh6utWvXlnd3AAAAAMCycgeo8+fPq0WLFlqwYEGpy2fPnq3XX39dCxcu1NatW1WlShXFxMQoJyfHrBkwYID27t2r9evX67PPPtOXX36pJ5980lyenZ2tLl26qF69ekpJSdGcOXM0ffp0vf3222bNli1b1L9/fw0bNkzffvutevbsqZ49e2rPnj3l3SUAAAAAsMRmGIZxzSvbbPr444/Vs2dPSRfPPgUFBSk+Pl7jxo2TJGVlZSkgIEAJCQnq16+f9u/fr7CwMG3fvl1t2rSRJCUmJuqhhx7SL7/8oqCgIL355pt69tlnlZ6eLjc3N0nSpEmTtGrVKh04cECS1LdvX50/f16fffaZ2U+7du3UsmVLLVy40FL/2dnZ8vX1VVZWlux2+7UeBlwHm83ZHQDOd+1/CwN/IHwhAHwhOJnVbHBD74E6cuSI0tPTFR0dbc7z9fVVZGSkkpOTJUnJycny8/Mzw5MkRUdHy8XFRVu3bjVr7r//fjM8SVJMTIwOHjyo06dPmzWXbqe4png7pcnNzVV2drbDBAAAAABW3dAAlZ6eLkkKCAhwmB8QEGAuS09PV82aNR2WV6pUSdWqVXOoKW2MS7dRVk3x8tLMnDlTvr6+5hQcHFzeXQQAAABQgVWop/BNnjxZWVlZ5nT06FFntwQAAADgDnJDA1RgYKAkKSMjw2F+RkaGuSwwMFAnTpxwWF5QUKBTp0451JQ2xqXbKKumeHlp3N3dZbfbHSYAAAAAsOqGBqgGDRooMDBQSUlJ5rzs7Gxt3bpVUVFRkqSoqCidOXNGKSkpZs2GDRtUVFSkyMhIs+bLL79Ufn6+WbN+/Xo1adJEVatWNWsu3U5xTfF2AAAAAOBGK3eAOnfunFJTU5Wamirp4oMjUlNTlZaWJpvNpjFjxujvf/+7Vq9erd27d2vQoEEKCgoyn9QXGhqqrl27avjw4dq2bZs2b96skSNHql+/fgoKCpIkPfroo3Jzc9OwYcO0d+9eLV++XPPmzVNcXJzZx+jRo5WYmKhXXnlFBw4c0PTp07Vjxw6NHDny+o8KAAAAAJTGKKcvvvjCkFRiGjx4sGEYhlFUVGRMnTrVCAgIMNzd3Y0HHnjAOHjwoMMYJ0+eNPr37294e3sbdrvdGDp0qHH27FmHml27dhkdOnQw3N3djdq1axuzZs0q0cuKFSuMxo0bG25ubkazZs2MNWvWlGtfsrKyDElGVlZW+Q4CbpiLz+tkYqrYEwDD+X8QmZhuhwlOZTUbXNd7oO50vAfK+XjtB3DxWxOo8PhCAPhCcDKnvAcKAAAAAP7ICFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAAAAWEaAAAAAAwCICFAAAAABYRIACAAAAAIsIUAAAAABgEQEKAAAAACwiQAEAAACARQQoAAAAALCIAAUAAAAAFhGgAAAAAMAiAhQAAAAAWESAAgAAAACLCFAAAAAAYBEBCgAAAAAsIkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGDRHR+gFixYoPr168vDw0ORkZHatm2bs1sCAAAA8Ad1Rweo5cuXKy4uTs8995x27typFi1aKCYmRidOnHB2awAAAAD+gO7oAPXqq69q+PDhGjp0qMLCwrRw4UJ5eXnp3XffdXZrAAAAAP6A7tgAlZeXp5SUFEVHR5vzXFxcFB0dreTkZCd2BgAAAOCPqpKzG7hWv/32mwoLCxUQEOAwPyAgQAcOHCh1ndzcXOXm5pqfs7KyJEnZ2dk3r1EAuAr+CgIASOILwcmKM4FhGFesu2MD1LWYOXOmnn/++RLzg4ODndANAFzk6+vsDgAAtwW+EG4LZ8+ele8VfhZ3bICqXr26XF1dlZGR4TA/IyNDgYGBpa4zefJkxcXFmZ+Liop06tQp+fv7y2az3dR+gdtRdna2goODdfToUdntdme3AwBwEr4PgItnns6ePaugoKAr1t2xAcrNzU0RERFKSkpSz549JV0MRElJSRo5cmSp67i7u8vd3d1hnp+f303uFLj92e12vjABAHwfoMK70pmnYndsgJKkuLg4DR48WG3atFHbtm01d+5cnT9/XkOHDnV2awAAAAD+gO7oANW3b19lZmZq2rRpSk9PV8uWLZWYmFjiwRIAAAAAcCPc0QFKkkaOHFnmJXsArszd3V3PPfdciUtbAQAVC98HgHU242rP6QMAAAAASLqDX6QLAAAAALcaAQoAAAAALCJAAQAAAIBFBCgAAAAAsIgABQAAUAF99dVXeuyxxxQVFaVff/1VkvTee+/p66+/dnJnwO2NAAUAAFDBfPjhh4qJiZGnp6e+/fZb5ebmSpKysrL00ksvObk74PZGgAIqsLy8PB08eFAFBQXObgUAcAv9/e9/18KFC7Vo0SJVrlzZnN++fXvt3LnTiZ0Btz8CFFAB/f777xo2bJi8vLzUrFkzpaWlSZJGjRqlWbNmObk7AMDNdvDgQd1///0l5vv6+urMmTO3viHgDkKAAiqgyZMna9euXdq4caM8PDzM+dHR0Vq+fLkTOwMA3AqBgYH64YcfSsz/+uuv1bBhQyd0BNw5CFBABbRq1SrNnz9fHTp0kM1mM+c3a9ZMhw8fdmJnAIBbYfjw4Ro9erS2bt0qm82mY8eO6f3339e4ceP09NNPO7s94LZWydkNALj1MjMzVbNmzRLzz58/7xCoAAB/TJMmTVJRUZEeeOAB/f7777r//vvl7u6ucePGadSoUc5uD7itcQYKqIDatGmjNWvWmJ+LQ9M777yjqKgoZ7UFALhFbDabnn32WZ06dUp79uzRN998o8zMTM2YMcPZrQG3Pc5AARXQSy+9pAcffFD79u1TQUGB5s2bp3379mnLli3atGmTs9sDANwibm5uCgsLc3YbwB3FZhiG4ewmANx6hw8f1qxZs7Rr1y6dO3dOrVu31sSJExUeHu7s1gAAN1nnzp2veMn2hg0bbmE3wJ2FM1BABXXXXXdp0aJFzm4DAOAELVu2dPicn5+v1NRU7dmzR4MHD3ZOU8AdggAFVEA7d+5U5cqVzbNNn3zyiRYvXqywsDBNnz5dbm5uTu4QAHAzvfbaa6XOnz59us6dO3eLuwHuLDxEAqiA/vrXv+r777+XJP3444/q27evvLy8tHLlSk2YMMHJ3QEAnOWxxx7Tu+++6+w2gNsaAQqogL7//nvz8o2VK1eqY8eOWrp0qRISEvThhx86tzkAgNMkJyc7vGAdQElcwgdUQIZhqKioSJL0f//3f+rWrZskKTg4WL/99pszWwMA3AKPPPKIw2fDMHT8+HHt2LFDU6dOdVJXwJ2BAAVUQG3atNHf//53RUdHa9OmTXrzzTclSUeOHFFAQICTuwMA3Gy+vr4On11cXNSkSRO98MIL6tKli5O6Au4MBCigApo7d64GDBigVatW6dlnn1VISIgk6YMPPtC9997r5O4AADdTYWGhhg4dqvDwcFWtWtXZ7QB3HN4DBcCUk5MjV1dXVa5c2dmtAABuIg8PD+3fv18NGjRwdivAHYeHSAAweXh4EJ4AoAJo3ry5fvzxR2e3AdyROAMFVBBVq1a94lvnL3Xq1Kmb3A0AwJkSExM1efJkzZgxQxEREapSpYrDcrvd7qTOgNsfAQqoIJYsWWK5lrfQA8Af0wsvvKD4+Hj5+PiY8y79zzXDMGSz2VRYWOiM9oA7AgEKAACggnB1ddXx48e1f//+K9Z17NjxFnUE3HkIUEAFl5OTo7y8PId5XLoBAH9MLi4uSk9PV82aNZ3dCnDH4iESQAV0/vx5jRw5UjVr1lSVKlVUtWpVhwkA8Mdl9X5YAKXjPVBABTRhwgR98cUXevPNNzVw4EAtWLBAv/76q9566y3NmjXL2e0BAG6ixo0bXzVE8TAhoGxcwgdUQHXr1tW//vUvderUSXa7XTt37lRISIjee+89/ec//9HatWud3SIA4CZwcXHR3Llz5evre8U6HiYElI0zUEAFdOrUKTVs2FDSxfudiv+nsUOHDnr66aed2RoA4Cbr168f90AB14F7oIAKqGHDhjpy5IgkqWnTplqxYoUk6dNPP5Wfn58TOwMA3Ezc/wRcPwIUUIH8+OOPKioq0tChQ7Vr1y5J0qRJk7RgwQJ5eHho7NixGj9+vJO7BADcLNy5AVw/7oECKpDi938UX7rRt29fvf7668rJyVFKSopCQkJ09913O7lLAACA2xcBCqhALn//h4+Pj3bt2mXeDwUAAIAr4xI+AAAAALCIAAVUIDabrcQNxNxQDAAAYB2PMQcqEMMwNGTIELm7u0uScnJy9NRTT6lKlSoOdR999JEz2gMAALjtEaCACuTyFyM+9thjTuoEAADgzsRDJAAAAADAIu6BAgAAAACLCFAAAAAAYBEBCgCA/19+fr6zWwAA3OYIUACACuvjjz9WbGys6tevL29vb913331O7WfIkCHq2bOnU3soj06dOmnMmDHObgMAbikCFADcIE888YQaNWokLy8vVa1aVVFRUfr3v//t7LZQhpkzZ2r48OHq1q2b1qxZo9TUVK1du/aWbNtms+mnn35SQkKCOnXqdEu2+Udw6fHq1KmTEhISnNoPgIqJx5gDwA3i7++vd955RyEhIfr999+VnJysp556SufOndNTTz3l7PZwiR9//FEvvfSSvvnmGzVr1szZ7dzWDMNQYWGhKlXinwwAIHEGCgBumH/84x/q2LGjateurUaNGmnQoEHq0qWLvvzyS7Omfv36mjt3rsN6l1+2lZiYqA4dOsjPz0/+/v7q1q2bDh8+bC5PSEiQn5+fwxiXX0qVm5urcePGqXbt2qpSpYoiIyO1cePGK47x008/yWazKTU1VZK0ceNG2Ww2nTlzxqwZOHCgbDabVq1aZc47evSo+vTpIz8/P1WrVk09evTQTz/9dMVjtXfvXnXr1k12u10+Pj667777dPjwYU2fPl02m63UqfjMQ1FRkV544QXVqVNH7u7uatmypRITE0tso1OnTiXGKD7269at01133aUXX3xRNWrUkI+Pjx555BH98ssv5vrTp09Xy5YtHcYs7ZhMnDhRjRs3lpeXlxo2bKipU6de971UL7/8smrVqiV/f3+NGDHCYbz33ntPbdq0kY+PjwIDA/Xoo4/qxIkT5vIhQ4aUevyKf/5XW794Hz///HNFRETI3d1dX3/9tc6fP69BgwbJ29tbtWrV0iuvvFKi79OnT2vQoEGqWrWqvLy89OCDD+rQoUNXPKZz585V/fr1Hbbftm1bValSRX5+fmrfvr1+/vnn6zqeAHAjEaAA4CYwDEMpKSnasmWLunbtWq51z58/r7i4OO3YsUNJSUlycXHRww8/rKKiIstjjBw5UsnJyVq2bJm+++479e7dW127dnX4x2x5paSkaPXq1Q7z8vPzFRMTIx8fH3311VfavHmzvL291bVrV+Xl5ZU6zq+//qr7779f7u7u2rBhg1JSUvT444+roKBA48aN0/Hjx3X8+HHFx8crKirK/PzRRx9JkubNm6dXXnlFL7/8sr777jvFxMToz3/+c4l9MwxDw4cPN9evU6eOuSwzM1O7du3S0aNH9fnnn+uLL75QRkaGevbsqfK+HtHHx0cJCQnat2+f5s2bp0WLFum1114r1xiX+uKLL3T48GF98cUXWrJkiRISEhwuVcvPz9eMGTO0a9curVq1Sj/99JOGDBliLp83b565z8ePH9fo0aNVs2ZNNW3a1NL6xSZNmqRZs2Zp//79uvvuuzV+/Hht2rRJn3zyif73f/9XGzdu1M6dOx3WGTJkiHbs2KHVq1crOTlZhmHooYceshwoCwoK1LNnT3Xs2FHfffedkpOT9eSTT8pms5X7OALATWMAAG6Yjz/+2KhSpYpRqVIlw2azGdOmTXNYXq9ePeO1115zmDd48GCjR48eZY6ZmZlpSDJ2795tGIZhLFu2zHB3d3eo6dixozF69GjDMAzj559/NlxdXY1ff/3VoeaBBx4wJk+ebBiGYSxevNjw9fV1WH7kyBFDkvHtt98ahmEYX3zxhSHJOH36tGEYhnH//fcbM2bMMCQZH3/8sWEYhvHee+8ZTZo0MYqKisxxcnNzDU9PT2PdunWl7s/kyZONBg0aGHl5eWXus2EYxnPPPWd07NixxPygoCDjxRdfdJh3zz33GH/7298c5kVFRRnjxo0zP1967J977jnD1dXVSEtLM5f/9NNPhqurq7F+/XqzpkWLFg5jXn5MSjNnzhwjIiLiivtWlsGDBxv16tUzCgoKzHm9e/c2+vbtW+Y627dvNyQZZ8+eLbHsww8/NDw8PIyvv/7a8vrF+7hq1Sqz5uzZs4abm5uxYsUKc97JkycNT09P8/fd999/b0gyNm/ebNb89ttvhqenp7leacf0tddeM+rVq2eOKcnYuHFjmf0CgLNxBgoAbqA//elPSk1N1fbt2/Xmm29q3rx5WrhwoUPNxIkT5e3tbU7vv/++w/JDhw6pf//+atiwoex2u3l5U1pamiSpWbNmys3N1YcfflhqD7t371ZhYaEaN27ssJ1NmzY5XAqYlZXlsPxK9wKtWrVKP/74o+Lj4x3m79q1Sz/88IN8fHzMcapVq6acnByHbV0qNTVV9913nypXrlzm9sqSnZ2tY8eOqX379g7z27dvr/3795eorVKlSpljBQcHKzg42Pxcr1491alTR/v27StXT8uXL1f79u0VGBgob29vTZkyxfxZXYtmzZrJ1dXV/FyrVi2HS+xSUlLUvXt31a1bVz4+PurYsaMkldjmt99+q4EDB2r+/PkOx8vq+m3atDF/ffjwYeXl5SkyMtKcV61aNTVp0sT8vH//flWqVMmhxt/fX02aNCnxsylLtWrVNGTIEMXExKh79+7m2TQAuJ1wRygA3EBVqlRRSEiIJKlly5bKzMzUyy+/7PAQifHjxztcMjVx4kQVFhaan7t376569epp0aJFCgoKUlFRkZo3b25eEte8eXNNnDhRvXv3loeHh1xcXHThwgXz3pJz587J1dVVKSkpDv8QlyRvb2/z1z4+Pg6XYP3666+lPhEuPz9fEyZM0IsvvihPT0+HZefOnVNERESJEChJNWrUKPUYXT7GzXLs2DEFBQWVuqxq1aplrleey8WSk5M1YMAAPf/884qJiZGvr6+WLVtW6v1BVl0eLG02m3n55vnz5xUTE6OYmBi9//77qlGjhtLS0hQTE+NwyWR6err+/Oc/64knntCwYcPM+VbXl3TF8HmtXFxcSlwiefnlfYsXL9YzzzyjxMRELV++XFOmTNH69evVrl27G94PAFwLAhQA3ESGYZS4d6l69epmyJIuBpnihxKcPHlSBw8e1KJFi8x3En399dclxp01a5b++7//2zwzMWDAAHNZq1atVFhYqBMnTlzxvUYuLi4OfZT1lLU333xT3t7eGjhwYIllrVu31vLly1WzZk3Z7fYyt3Wpu+++W0uWLFF+fn65z0LZ7XYFBQVp8+bN5pkTSdq8ebPatm1rfj58+LBOnz6tVq1alTpO06ZNdfToUR09etQ8C/Xzzz/rl19+UVhYmOV+tmzZonr16unZZ581593MBx4cOHBAJ0+e1KxZs8y+d+zY4VCTk5OjHj16qGnTpnr11VfLvX5p7rrrLlWuXFlbt25V3bp1JV18YMT3339v/hxCQ0NVUFCgrVu36t5775X0/34/Fx/TGjVqKD09XYZhmEG1+KEll2rVqpVatWqlyZMnKyoqSkuXLiVAAbhtcAkfANwA2dnZ6tOnj/7v//5PR48e1ffff6//+Z//0Zw5c8r1CPOqVavK399fb7/9tn744Qdt2LBBcXFxpdba7XaFhIQoJCTE4axO48aNNWDAAA0aNEgfffSRjhw5om3btmnmzJlas2ZNufdt9uzZeuWVV0o9MzNgwABVr15dPXr00FdffaUjR45o48aNeuaZZxyeaHepkSNHKjs7W/369dOOHTt06NAhvffeezp48KClfsaPH69//OMfWr58uQ4ePKhJkyYpNTVVo0ePlnQxEAwcOFDh4eEOl6Fd6k9/+pNCQ0P16KOPaseOHdqxY4ceffRRtWzZUv/1X/9l1hmGoZycHHMqPkuTm5srSWrUqJHS0tK0bNkyHT58WK+//ro+/vhjS/txLerWrSs3Nzf985//1I8//qjVq1drxowZDjV//etfdfToUb3++uvKzMxUenq60tPTlZeXZ2n90nh7e2vYsGEaP368NmzYoD179mjIkCFycfl//4xo1KiRevTooeHDh+vrr7/Wrl279Nhjj6l27drq0aOHpItPRszMzNTs2bN1+PBhLViwQJ9//rk5xpEjRzR58mQlJyfr559/1v/+7//q0KFDCg0NvUFHEACuHwEKAG4ADw8P+fv7Kz4+Xs2bN1e7du30r3/9S//zP/+jCRMmWB7HxcVFy5YtU0pKipo3b66xY8dqzpw55e5n8eLFGjRokOLj49WkSRP17NlT27dvN88elEfnzp3VuXPnUpd5eXnpyy+/VN26dfXII48oNDRUw4YNU05OTplnpPz9/bVhwwadO3dOHTt2VEREhBYtWmT5bNQzzzyjuLg4xcfHKzw8XImJiVq9erUaNWokSRo7dqzq1KmjtWvXlnk5nouLiz755BP5+vqqY8eO6ty5swICAvTJJ584rPPdd9/J09PTnGJiYiRJgYGBkqQ///nPGjt2rEaOHKmWLVtqy5Ytmjp1qqX9uBY1atRQQkKCVq5cqbCwMM2aNUsvv/yyQ82mTZt0/PhxhYWFqVatWua0ZcsWS+uXZc6cObrvvvvUvXt3RUdHq0OHDoqIiHCoWbx4sSIiItStWzdFRUXJMAytXbvW/NmGhobqjTfe0IIFC9SiRQtt27ZN48aNM9f38vLSgQMH1KtXLzVu3FhPPvmkRowYob/+9a/XeeQA4MaxGZdfjAwAAK7Iz8/P4V1QAICKgzNQAACUk4eHh7NbAAA4CWegAAAAAMAizkABAAAAgEUEKAAAAACwiAAFAAAAABYRoAAAAADAIgIUAAAAAFhEgAIAAAAAiwhQAAAAAGARAQoAAAAALCJAAQAAAIBFBCgAAAAAsOj/A87iKEbIDvcNAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Группировка данных по значению 'hazardous' и вычисление средней относительной скорости\n",
+    "data2 = df.groupby('hazardous')['relative_velocity'].mean()\n",
+    "handles = [plt.Rectangle((0,0),1,1, color='blue'), plt.Rectangle((0,0),1,1, color='red')]\n",
+    "labels = ['Потенциально не опасный', 'Потенциально опасный']\n",
+    "data2.plot(kind='bar', figsize=(10, 6), color=['blue', 'red'], xlabel='Значение столбца \"hazardous\"')\n",
+    "plt.legend(handles, labels)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Диаграмма ниже показывает процентное соотношение космических объектов, за которыми ведётся автоматическое наблюдение, т.к. они представляют серьёзную угрозу, и космических объектов, за которыми такое наблюдение не ведётся. На диаграмме видно, что за всеми космическими объектами наблюдения не ведётся. Это означает, что в данном датасете нет настолько опасных космических объектов, которые требовали бы постоянных наблюдений"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x22b9486a180>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data3=df['sentry_object'].value_counts()\n",
+    "labels=['Не происходит автомониторинг, как за опасным объектом', 'Происходит автомониторинг, как за опасным объектом']\n",
+    "colors=['blue', 'red']\n",
+    "data3.plot(kind='pie', figsize=(8, 8), labels=None, colors=colors, autopct='%1.1f%%')\n",
+    "handles = [plt.Line2D([0], [0], color=colors[0], lw=4), plt.Line2D([0], [0], color=colors[1], lw=4)]\n",
+    "plt.legend(handles, labels)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "aimenv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/lab_1/lab1.png b/lab_1/lab1.png
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diff --git a/lab_1/requirements.txt b/lab_1/requirements.txt
new file mode 100644
index 0000000..5e76aa1
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