02.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "eed4b4c6-9729-4282-9a0f-96b06e09f7be",
   "metadata": {},
   "source": [
    "# Data exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "131ff9e4-f40c-4c0b-bae1-9438e17a8ec5",
   "metadata": {},
   "source": [
    "To better understand and interpret the results of various metrices applied on our network, we decided to see the distribution of various attribute's values and what are the average values. \n",
    "\n",
    "Let's start by importing the csv data of the two weeks of April 07 and 08."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6f591ecc-4ab5-4ddd-83a2-59b65f4cf6ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from matplotlib import colors\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "c52199bb-003a-46cd-8d73-5131dafad240",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/yq/sryk517930l66t3h_fdc8w040000gn/T/ipykernel_16784/2967964717.py:2: DtypeWarning: Columns (1,3) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  data1 = pd.read_csv(\"node07data.csv\",delimiter=',')\n",
      "/var/folders/yq/sryk517930l66t3h_fdc8w040000gn/T/ipykernel_16784/2967964717.py:3: DtypeWarning: Columns (1,3) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  data2 = pd.read_csv(\"node08data.csv\",delimiter=',')\n"
     ]
    }
   ],
   "source": [
    "data0 = pd.read_csv(\"last.csv\",delimiter=',',low_memory=False)\n",
    "data1 = pd.read_csv(\"node07data.csv\",delimiter=',') \n",
    "data2 = pd.read_csv(\"node08data.csv\",delimiter=',')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16e24bcf-1131-49ae-a429-7309cf5b77c5",
   "metadata": {},
   "source": [
    "### <span style=\"color:teal\">Exploring data for April '07</span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "d1efe0e6-d390-4be2-85cb-84e09e39f8a6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "age_values = data1['age']\n",
    "uploader_values = data1['uploader']\n",
    "category_values = data1['category']\n",
    "length_values = data1['length']\n",
    "views_values = data1['views']\n",
    "rate_values = data1['rate']\n",
    "ratings_values = data1['ratings']\n",
    "comments_values = data1['comments']\n",
    "\n",
    "def distribution_Frequency(data,x_label):\n",
    "    title = 'Distribution chart of {0}'\n",
    "    \n",
    "    plt.figure(figsize=(9, 4))  # Adjust the width and height as desired\n",
    "    plt.hist(data, bins=160)  # Adjust the number of bins as needed\n",
    "\n",
    "    # Add labels and title\n",
    "    plt.xlabel(x_label)\n",
    "    plt.ylabel('Frequency')\n",
    "    plt.title(title.format(x_label))\n",
    "\n",
    "\n",
    "    # Display the plot\n",
    "    plt.show()\n",
    "    \n",
    "def plot_video_length_barchart(data,label):\n",
    "    # Extract video lengths from the DataFrame\n",
    "    video_lengths = data\n",
    "\n",
    "    # Set the figure size\n",
    "    plt.figure(figsize=(10, 3))  # Adjust the width and height as desired\n",
    "\n",
    "    # Get unique video lengths and their counts\n",
    "    unique_lengths, counts = np.unique(video_lengths, return_counts=True)\n",
    "\n",
    "    # Create bar chart\n",
    "    plt.bar(unique_lengths, counts)\n",
    "\n",
    "    # Add labels and title\n",
    "    plt.xlabel(label)\n",
    "    plt.ylabel('Frequency')\n",
    "    plt.title('Distribution of Variable')\n",
    "    \n",
    "    ax.ticklabel_format(useOffset=False)\n",
    "\n",
    "    # Display the plot\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d662d3b-2c9b-4fae-87da-e8f3958a1681",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### <span style=\"color:teal\">Exploring data for April '07</span>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76a8db4e-16a1-4047-a958-7def94248b78",
   "metadata": {},
   "source": [
    "#### Distribution of `AGE` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "c06be65c-6860-4c26-855d-50335d215907",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distribution_Frequency(age_values,'age of video')\n",
    "#plot_video_length_barchart(age_values,'age of video')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c038e0ec-ccc0-4761-9cb4-fe42925743db",
   "metadata": {},
   "source": [
    "#### Distribution of `CATEGORY` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "eb4d221b-711e-4a1d-bdf0-a7308d3ed58e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution_Frequency(category_values,'category of video')\n",
    "\n",
    "def plot_categorical_frequency(data, label):\n",
    "    # Extract the categorical variable from the DataFrame\n",
    "    categorical_variable = data\n",
    "\n",
    "    # Get unique categories and their counts\n",
    "    unique_categories, counts = categorical_variable.value_counts().index, categorical_variable.value_counts().values\n",
    "\n",
    "    # Set the figure size\n",
    "    plt.figure(figsize=(8, 6))  # Adjust the width and height as desired\n",
    "\n",
    "    # Create bar chart\n",
    "    plt.bar(unique_categories, counts)\n",
    "\n",
    "    # Add labels and title\n",
    "    plt.xlabel(label)\n",
    "    plt.ylabel('Frequency')\n",
    "    plt.title('Frequency of Categorical Variable')\n",
    "\n",
    "    # Rotate x-axis labels if needed\n",
    "    plt.xticks(rotation=75)  # Adjust the rotation angle as desired\n",
    "\n",
    "    # Display the plot\n",
    "    plt.show()\n",
    "\n",
    "plot_categorical_frequency(category_values,'category of video')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "694f9ba5-4c0d-41ac-ada3-7f0cf93f64cd",
   "metadata": {},
   "source": [
    "#### Distribution of `RATING` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "9831cb3f-e6c6-4f68-ae6b-f5e9382cb387",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distribution_Frequency(rate_values,'rate of video')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e5d5949-cc7a-4abc-9864-42778ea48be1",
   "metadata": {},
   "source": [
    "#### Distribution of `RATING count` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "66ed9ce4-c3d5-4cc4-bb26-6800b049e356",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/yq/sryk517930l66t3h_fdc8w040000gn/T/ipykernel_16784/1639936872.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  ratings_values[i] = 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution_Frequency(ratings_values,'rate count of video')\n",
    "\n",
    "for i in range(len(rate_values)):\n",
    "    if pd.isna(rate_values[i]) or rate_values[i] is None:\n",
    "        rate_values[i] = 0\n",
    "        \n",
    "for i in range(len(ratings_values)):\n",
    "    if pd.isna(ratings_values[i]) or ratings_values[i] is None:\n",
    "        ratings_values[i] = 0\n",
    "\n",
    "fig, axs = plt.subplots(2, 1, figsize=(20, 10), sharex=True, sharey=True,\n",
    "                        tight_layout=True)\n",
    "\n",
    "# We can increase the number of bins on each axis\n",
    "#axs[0].hist2d(rate_values, ratings_values, bins=40)\n",
    "\n",
    "# As well as define normalization of the colors\n",
    "axs[0].hist2d(rate_values, ratings_values, bins=40, norm=colors.LogNorm())\n",
    "\n",
    "# We can also define custom numbers of bins for each axis\n",
    "axs[1].hist2d(rate_values, ratings_values, bins=(80, 20), norm=colors.LogNorm())\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "655414e2-7bbb-4221-8b9f-7618edc7a2ab",
   "metadata": {},
   "source": [
    "#### Distribution of `LENGTH` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "73e564e6-1d72-4564-a9f6-dafe03a92dc8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/yq/sryk517930l66t3h_fdc8w040000gn/T/ipykernel_16784/3819613709.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  length_values[i] = 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(len(length_values)):\n",
    "    if pd.isna(length_values[i]) or length_values[i] is None:\n",
    "        length_values[i] = 0\n",
    "\n",
    "#plot_video_length_barchart(length_values,'length of videos')\n",
    "#distribution_Frequency(length_values,'length of video')\n",
    "\n",
    "fig, axs = plt.subplots(2, 1, figsize=(20, 10), sharex=True, sharey=True,\n",
    "                        tight_layout=True)\n",
    "\n",
    "# We can increase the number of bins on each axis\n",
    "#axs[0].hist2d(length_values,rate_values, bins=40)\n",
    "\n",
    "# As well as define normalization of the colors\n",
    "axs[0].hist2d(length_values,rate_values, bins=40, norm=colors.LogNorm())\n",
    "\n",
    "# We can also define custom numbers of bins for each axis\n",
    "axs[1].hist2d(length_values,rate_values, bins=(80, 20), norm=colors.LogNorm())\n",
    "plt.ticklabel_format(useOffset=False, style='plain', axis='x')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8871d046-70e5-4ac2-a284-e0b65f503721",
   "metadata": {},
   "source": [
    "#### Distribution of `COMMENTS count` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "c1782d29-2e23-4ea2-9f11-c8247a06fc1d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/yq/sryk517930l66t3h_fdc8w040000gn/T/ipykernel_16784/555845301.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comments_values[i] = 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution_Frequency(comments_values,'comments of video')\n",
    "for i in range(len(comments_values)):\n",
    "    if pd.isna(comments_values[i]) or comments_values[i] is None:\n",
    "        comments_values[i] = 0\n",
    "\n",
    "\n",
    "fig, axs = plt.subplots(2, 1, figsize=(20, 10), sharex=True, sharey=True,\n",
    "                        tight_layout=True)\n",
    "\n",
    "# We can increase the number of bins on each axis\n",
    "#axs[0].hist2d(comments_values,rate_values, bins=40)\n",
    "\n",
    "# As well as define normalization of the colors\n",
    "axs[0].hist2d(comments_values,rate_values, bins=40, norm=colors.LogNorm())\n",
    "\n",
    "# We can also define custom numbers of bins for each axis\n",
    "axs[1].hist2d(comments_values,rate_values, bins=(80, 20), norm=colors.LogNorm())\n",
    "plt.ticklabel_format(useOffset=False, style='plain', axis='x')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2436531f-7fa2-40fe-93b3-52e25939acb4",
   "metadata": {},
   "source": [
    "#### Distribution of `UPLOADER` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2d32d0f-77a9-499a-95bc-268309bb4179",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "plot_categorical_frequency(uploader_values,'uploader of video')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2288d436-34f2-487d-9c3d-7341dcad2367",
   "metadata": {},
   "source": [
    "#### Distribution of `VIEWS` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "14305728-fe65-4afb-967e-edfb4b04dfc0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/yq/sryk517930l66t3h_fdc8w040000gn/T/ipykernel_16784/2737248733.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  views_values[i] = 0\n"
     ]
    },
    {
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      "text/plain": [
       "<Figure size 2000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution_Frequency(views_values,'views of video')\n",
    "\n",
    "for i in range(len(views_values)):\n",
    "    if pd.isna(views_values[i]) or views_values[i] is None:\n",
    "        views_values[i] = 0\n",
    "\n",
    "fig, axs = plt.subplots(2, 1, figsize=(20, 10), sharex=True, sharey=True,\n",
    "                        tight_layout=True)\n",
    "\n",
    "# We can increase the number of bins on each axis\n",
    "#axs[0].hist2d(comments_values,rate_values, bins=40)\n",
    "\n",
    "# As well as define normalization of the colors\n",
    "axs[0].hist2d(comments_values,views_values, bins=40, norm=colors.LogNorm())\n",
    "\n",
    "# We can also define custom numbers of bins for each axis\n",
    "axs[1].hist2d(comments_values,views_values, bins=(80, 20), norm=colors.LogNorm())\n",
    "plt.ticklabel_format(useOffset=False, style='plain', axis='y')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71c4194b-7fcb-4176-8ce8-41a5ebef5b97",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### <span style=\"color:teal\">Exploring data for April '08</span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "8a2b0f17-73f7-4104-bdf3-edf191182b99",
   "metadata": {},
   "outputs": [],
   "source": [
    "age_values2 = data2['age']\n",
    "uploader_values2 = data2['uploader']\n",
    "category_values2 = data2['category']\n",
    "length_values2 = data2['length']\n",
    "views_values2 = data2['views']\n",
    "rate_values2 = data2['rate']\n",
    "ratings_values2 = data2['ratings']\n",
    "comments_values2 = data2['comments']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "456edcd5-5e44-4f4b-8d16-dfe9299bcd09",
   "metadata": {},
   "source": [
    "#### Distribution of `CATEGORY` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "298d17f6-8738-463b-a5f8-dcc89e2545ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_categorical_frequency(category_values2,'category of video')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f22a80d-96ff-4b92-8d64-01cb67563723",
   "metadata": {},
   "source": [
    "#### Distribution of `RATING` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "f4a0be2d-110c-4d55-9c2b-d311c04ffa92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1lo+7dOnSql+/vubOnWtTt2fPHq1YsULt2rXLwaOxVaNGDdWpU0dhYWEKCwtT6dKl1bx581veJzAwUEWKFNFnn31m85xk9Zo///zz2rBhg5YvX55p38WLF3X16lVJ5r33AWQPMx8A7mnLli3T/v37dfXqVZ0+fVqrVq1SRESEypUrp19++UVFixa96X3ff/99RUVFqX379ipXrpzOnDmjGTNmqEyZMmratKmka0HAw8NDs2bNkqurq1xcXNS4ceNcry0oWbKkmjZtql69eun06dOaPHmyKleubHM54FdeeUU//vij2rRpo+eff16HDx/Wt99+a7MAPKe9PfXUU2rZsqXeffddHTt2TPXq1dOKFSu0ePFiDRo0KNOxc6tHjx76+uuvFRoaqs2bN6tZs2ZKSkrSypUr9frrr6tDhw7ZPpabm5uaN2+ucePGKTU1VQ888IBWrFiho0eP5qinBg0aSJIGDBigoKAgOTg43PRf4L28vDR8+HCNHj1abdq00dNPP60DBw5oxowZatSokV588cUcnft2qlevrkqVKmno0KH6+++/5ebmpp9++inLtTU3exwtWrRQnz59NHbsWEVHR6t169YqUqSIDh48qAULFmjKlCl69tlnb9rD+PHj1bZtWwUEBCgkJMR6qV13d/db/nZJdnTp0kUjRoxQ0aJFFRISkulrZzfy8vLS0KFDNXbsWD355JNq166dduzYoWXLlsnT09Om9s0339Qvv/yiJ598Uj179lSDBg2UlJSk3bt368cff9SxY8fk6elp2nsfQDbZ5yJbAHBnMi7RmXFzdHQ0fH19jSeeeMKYMmWKzeVsM9x4qd3IyEijQ4cOhp+fn+Ho6Gj4+fkZ3bp1y3TpzsWLFxs1a9Y0ChcubHNp2xYtWhi1atXKsr+bXWr3+++/N4YPH254e3sbzs7ORvv27W0up5phwoQJxgMPPGA4OTkZTZo0MbZu3ZrpmLfq7cZL7RqGYVy6dMkYPHiw4efnZxQpUsSoUqWKMX78eJtLmhrGtUvt9uvXL1NPN7sE8I0uX75svPvuu0aFChWMIkWKGL6+vsazzz5rHD582DCM/11qd/z48ZnuK8kYOXKkdfvkyZPGM888Y3h4eBju7u7Gc889Z5w6dSpT3a0ue3v16lXjjTfeMLy8vAyLxZKty+5OmzbNqF69ulGkSBHDx8fH6Nu3r/HPP//Y1OT0UrsuLi5Z7vvzzz+NwMBAo3jx4oanp6fRu3dv66WNr7+M8u0exxdffGE0aNDAcHZ2NlxdXY06deoYb731lnHq1Knb9rdy5UqjSZMmhrOzs+Hm5mY89dRTxp9//mlTk5NL7WY4ePCg9c/oH3/8kWn/jZfaNQzDSEtLM0aPHm2ULl3acHZ2Nh577DFjz549Wb7/Ll26ZAwfPtyoXLmy4ejoaHh6ehqPPvqo8emnnxopKSk2ddl57wPIfxbD4Oc9AQAAAOQ/1nwAAAAAMAXhAwAAAIApCB8AAAAATEH4AAAAAGAKwgcAAAAAUxA+AAAAAJiCHxk0UXp6uk6dOiVXV1dZLBZ7twMAAADcMcMwdOnSJfn5+d32x0QJHyY6deqU/P397d0GAAAAkOdOnDihMmXK3LKG8GEiV1dXSddeGDc3Nzt3AwAAANy5hIQE+fv7Wz/r3grhw0QZX7Vyc3MjfAAAAKBAyc6yAhacAwAAADAF4QMAAACAKQgfAAAAAExB+AAAAABgCsIHAAAAAFMQPgAAAACYgvABAAAAwBSEDwAAAACmIHwAAAAAMAXhAwAAAIApCB8AAAAATFHY3g0AAAAAyLnyw5babB/7uL2dOsk+Zj4AAAAAmILwAQAAAMAUhA8AAAAApiB8AAAAADAF4QMAAACAKQgfAAAAAExB+AAAAABgCsIHAAAAAFMQPgAAAACYgvABAAAAwBSEDwAAAACmIHwAAAAAMAXhAwAAAIApCB8AAAAATEH4AAAAAGAKwgcAAAAAUxA+AAAAAJiC8AEAAADAFIQPAAAAAKYgfAAAAAAwBeEDAAAAgCkIHwAAAABMQfgAAAAAYArCBwAAAABTED4AAAAAmILwAQAAAMAUhA8AAAAApiB8AAAAADAF4QMAAACAKQgfAAAAAExB+AAAAABgCsIHAAAAAFMQPgAAAACYgvABAAAAwBSEDwAAAACmIHwAAAAAMAXhAwAAAIApCB8AAAAATEH4AAAAAGAKu4aPsWPHqlGjRnJ1dZW3t7c6duyoAwcO2NRcuXJF/fr1U6lSpVS8eHF17txZp0+ftqmJiYlR+/btVaxYMXl7e+vNN9/U1atXbWrWrFmjhx56SE5OTqpcubLmzJmTqZ/p06erfPnyKlq0qBo3bqzNmzfnuBcAAAAAWbNr+Fi7dq369eunjRs3KiIiQqmpqWrdurWSkpKsNYMHD9avv/6qBQsWaO3atTp16pQ6depk3Z+Wlqb27dsrJSVF69ev19y5czVnzhyNGDHCWnP06FG1b99eLVu2VHR0tAYNGqRXXnlFy5cvt9aEhYUpNDRUI0eO1Pbt21WvXj0FBQXpzJkz2e4FAAAAwM1ZDMMw7N1EhrNnz8rb21tr165V8+bNFR8fLy8vL82bN0/PPvusJGn//v2qUaOGNmzYoEceeUTLli3Tk08+qVOnTsnHx0eSNGvWLL399ts6e/asHB0d9fbbb2vp0qXas2eP9Vxdu3bVxYsXFR4eLklq3LixGjVqpGnTpkmS0tPT5e/vrzfeeEPDhg3LVi+3k5CQIHd3d8XHx8vNzS1PnzsAAADcX8oPW2qzfezj9nbpIyefce+qNR/x8fGSpJIlS0qStm3bptTUVAUGBlprqlevrrJly2rDhg2SpA0bNqhOnTrW4CFJQUFBSkhI0N69e6011x8joybjGCkpKdq2bZtNTaFChRQYGGityU4vN0pOTlZCQoLNDQAAALhf3TXhIz09XYMGDVKTJk1Uu3ZtSVJcXJwcHR3l4eFhU+vj46O4uDhrzfXBI2N/xr5b1SQkJOjff//VuXPnlJaWlmXN9ce4XS83Gjt2rNzd3a03f3//bD4bAAAAQMFz14SPfv36ac+ePfrhhx/s3UqeGT58uOLj4623EydO2LslAAAAwG4K27sBSerfv7+WLFmiqKgolSlTxjru6+urlJQUXbx40WbG4fTp0/L19bXW3HhVqowrUF1fc+NVqU6fPi03Nzc5OzvLwcFBDg4OWdZcf4zb9XIjJycnOTk55eCZAAAAAAouu858GIah/v37a+HChVq1apUqVKhgs79BgwYqUqSIIiMjrWMHDhxQTEyMAgICJEkBAQHavXu3zVWpIiIi5Obmppo1a1prrj9GRk3GMRwdHdWgQQObmvT0dEVGRlprstMLAAAAgJuz68xHv379NG/ePC1evFiurq7WtRPu7u5ydnaWu7u7QkJCFBoaqpIlS8rNzU1vvPGGAgICrFeXat26tWrWrKmXXnpJ48aNU1xcnN577z3169fPOuvw2muvadq0aXrrrbf08ssva9WqVZo/f76WLv3fFQJCQ0MVHByshg0b6uGHH9bkyZOVlJSkXr16WXu6XS8AAAAAbs6u4WPmzJmSpMcee8xmfPbs2erZs6ckadKkSSpUqJA6d+6s5ORkBQUFacaMGdZaBwcHLVmyRH379lVAQIBcXFwUHBys999/31pToUIFLV26VIMHD9aUKVNUpkwZ/d///Z+CgoKsNV26dNHZs2c1YsQIxcXFqX79+goPD7dZhH67XgAAAADc3F31Ox8FHb/zAQAAgLzC73wAAAAAwE0QPgAAAACYgvABAAAAwBSEDwAAAACmIHwAAAAAMAXhAwAAAIApCB8AAAAATEH4AAAAAGAKwgcAAAAAUxA+AAAAAJiC8AEAAADAFIQPAAAAAKYgfAAAAAAwBeEDAAAAgCkIHwAAAABMQfgAAAAAYArCBwAAAABTED4AAAAAmILwAQAAAMAUhA8AAAAApiB8AAAAADAF4QMAAACAKQgfAAAAAExB+AAAAABgCsIHAAAAAFMQPgAAAACYgvABAAAAwBSEDwAAAACmIHwAAAAAMAXhAwAAAIApCB8AAAAATEH4AAAAAGAKwgcAAAAAUxA+AAAAAJiC8AEAAADAFIQPAAAAAKYgfAAAAAAwBeEDAAAAgCkIHwAAAABMQfgAAAAAYArCBwAAAABTED4AAAAAmILwAQAAAMAUhA8AAAAApiB8AAAAADAF4QMAAACAKQgfAAAAAExB+AAAAABgCsIHAAAAAFMQPgAAAACYgvABAAAAwBSEDwAAAACmsGv4iIqK0lNPPSU/Pz9ZLBYtWrTIZn/Pnj1lsVhsbm3atLGpuXDhgrp37y43Nzd5eHgoJCREiYmJNjW7du1Ss2bNVLRoUfn7+2vcuHGZelmwYIGqV6+uokWLqk6dOvrtt99s9huGoREjRqh06dJydnZWYGCgDh48mDdPBAAAAHAfsGv4SEpKUr169TR9+vSb1rRp00axsbHW2/fff2+zv3v37tq7d68iIiK0ZMkSRUVF6dVXX7XuT0hIUOvWrVWuXDlt27ZN48eP16hRo/TFF19Ya9avX69u3bopJCREO3bsUMeOHdWxY0ft2bPHWjNu3DhNnTpVs2bN0qZNm+Ti4qKgoCBduXIlD58RAAAAoOCyGIZh2LsJSbJYLFq4cKE6duxoHevZs6cuXryYaUYkw759+1SzZk1t2bJFDRs2lCSFh4erXbt2OnnypPz8/DRz5ky9++67iouLk6OjoyRp2LBhWrRokfbv3y9J6tKli5KSkrRkyRLrsR955BHVr19fs2bNkmEY8vPz05AhQzR06FBJUnx8vHx8fDRnzhx17do1W48xISFB7u7uio+Pl5ubW06fIgAAAMCq/LClNtvHPm5vlz5y8hn3rl/zsWbNGnl7e6tatWrq27evzp8/b923YcMGeXh4WIOHJAUGBqpQoULatGmTtaZ58+bW4CFJQUFBOnDggP755x9rTWBgoM15g4KCtGHDBknS0aNHFRcXZ1Pj7u6uxo0bW2uykpycrISEBJsbAAAAcL/KVfg4cuRIXveRpTZt2ujrr79WZGSkPvnkE61du1Zt27ZVWlqaJCkuLk7e3t429ylcuLBKliypuLg4a42Pj49NTcb27Wqu33/9/bKqycrYsWPl7u5uvfn7++fo8QMAAAAFSa7CR+XKldWyZUt9++23+brmoWvXrnr66adVp04ddezYUUuWLNGWLVu0Zs2afDtnXho+fLji4+OttxMnTti7JQAAAMBuchU+tm/frrp16yo0NFS+vr7q06ePNm/enNe9ZVKxYkV5enrq0KFDkiRfX1+dOXPGpubq1au6cOGCfH19rTWnT5+2qcnYvl3N9fuvv19WNVlxcnKSm5ubzQ0AAAC4X+UqfNSvX19TpkzRqVOn9NVXXyk2NlZNmzZV7dq1NXHiRJ09ezav+5QknTx5UufPn1fp0qUlSQEBAbp48aK2bdtmrVm1apXS09PVuHFja01UVJRSU1OtNREREapWrZpKlChhrYmMjLQ5V0REhAICAiRJFSpUkK+vr01NQkKCNm3aZK0BAAAAcGt3tOC8cOHC6tSpkxYsWKBPPvlEhw4d0tChQ+Xv768ePXooNjb2lvdPTExUdHS0oqOjJV1b2B0dHa2YmBglJibqzTff1MaNG3Xs2DFFRkaqQ4cOqly5soKCgiRJNWrUUJs2bdS7d29t3rxZ69atU//+/dW1a1f5+flJkl544QU5OjoqJCREe/fuVVhYmKZMmaLQ0FBrHwMHDlR4eLgmTJig/fv3a9SoUdq6dav69+8v6dqVuAYNGqQxY8bol19+0e7du9WjRw/5+fnZXJ0LAAAAwC0Yd2DLli1G3759jRIlShhlypQx3n33XePIkSNGVFSU0apVK6NRo0a3vP/q1asNSZluwcHBxuXLl43WrVsbXl5eRpEiRYxy5coZvXv3NuLi4myOcf78eaNbt25G8eLFDTc3N6NXr17GpUuXbGp27txpNG3a1HBycjIeeOAB4+OPP87Uy/z5842qVasajo6ORq1atYylS5fa7E9PTzf+85//GD4+PoaTk5PRqlUr48CBAzl6vuLj4w1JRnx8fI7uBwAAANyo3NtLbG72kpPPuLn6nY+JEydq9uzZOnDggNq1a6dXXnlF7dq1U6FC/5tIOXnypMqXL6+rV6/mTUoqAPidDwAAAOSVe/F3Pgrn5gQzZ87Uyy+/rJ49e1rXX9zI29tbX375ZW4ODwAAAKAAylX4OHjw4G1rHB0dFRwcnJvDAwAAACiAcrXgfPbs2VqwYEGm8QULFmju3Ll33BQAAACAgidX4WPs2LHy9PTMNO7t7a2PPvrojpsCAAAAUPDkKnzExMSoQoUKmcbLlSunmJiYO24KAAAAQMGTq/Dh7e2tXbt2ZRrfuXOnSpUqdcdNAQAAACh4chU+unXrpgEDBmj16tVKS0tTWlqaVq1apYEDB6pr16553SMAAACAAiBXV7v64IMPdOzYMbVq1UqFC187RHp6unr06MGaDwAAAABZylX4cHR0VFhYmD744APt3LlTzs7OqlOnjsqVK5fX/QEAAAAoIHIVPjJUrVpVVatWzateAAAAABRguQofaWlpmjNnjiIjI3XmzBmlp6fb7F+1alWeNAcAAACg4MhV+Bg4cKDmzJmj9u3bq3bt2rJYLHndFwAAAIACJlfh44cfftD8+fPVrl27vO4HAAAAQAGVq0vtOjo6qnLlynndCwAAAIACLFfhY8iQIZoyZYoMw8jrfgAAAAAUULn62tUff/yh1atXa9myZapVq5aKFClis//nn3/Ok+YAAAAAFBy5Ch8eHh565pln8roXAAAAAAVYrsLH7Nmz87oPAAAAAAVcrtZ8SNLVq1e1cuVKff7557p06ZIk6dSpU0pMTMyz5gAAAAAUHLma+Th+/LjatGmjmJgYJScn64knnpCrq6s++eQTJScna9asWXndJwAAAIB7XK5mPgYOHKiGDRvqn3/+kbOzs3X8mWeeUWRkZJ41BwAAAKDgyNXMx++//67169fL0dHRZrx8+fL6+++/86QxAAAAAAVLrmY+0tPTlZaWlmn85MmTcnV1veOmAAAAABQ8uQofrVu31uTJk63bFotFiYmJGjlypNq1a5dXvQEAAAAoQHL1tasJEyYoKChINWvW1JUrV/TCCy/o4MGD8vT01Pfff5/XPQIAAAAoAHIVPsqUKaOdO3fqhx9+0K5du5SYmKiQkBB1797dZgE6AAAAAGTIVfiQpMKFC+vFF1/My14AAAAAFGC5Ch9ff/31Lff36NEjV80AAAAAKLhyFT4GDhxos52amqrLly/L0dFRxYoVI3wAAAAAyCRXV7v6559/bG6JiYk6cOCAmjZtyoJzAAAAAFnKVfjISpUqVfTxxx9nmhUBAAAAACkPw4d0bRH6qVOn8vKQAAAAAAqIXK35+OWXX2y2DcNQbGyspk2bpiZNmuRJYwAAAAAKllyFj44dO9psWywWeXl56fHHH9eECRPyoi8AAAAABUyuwkd6enpe9wEAAACggMvTNR8AAAAAcDO5mvkIDQ3Ndu3EiRNzcwoAAAAABUyuwseOHTu0Y8cOpaamqlq1apKkv/76Sw4ODnrooYesdRaLJW+6BAAAAHDPy1X4eOqpp+Tq6qq5c+eqRIkSkq798GCvXr3UrFkzDRkyJE+bBAAAAHDvy9WajwkTJmjs2LHW4CFJJUqU0JgxY7jaFQAAAIAs5Sp8JCQk6OzZs5nGz549q0uXLt1xUwAAAAAKnlyFj2eeeUa9evXSzz//rJMnT+rkyZP66aefFBISok6dOuV1jwAAAAAKgFyt+Zg1a5aGDh2qF154QampqdcOVLiwQkJCNH78+DxtEAAAAEDBkKvwUaxYMc2YMUPjx4/X4cOHJUmVKlWSi4tLnjYHAAAAoOC4ox8ZjI2NVWxsrKpUqSIXFxcZhpFXfQEAAAAoYHIVPs6fP69WrVqpatWqateunWJjYyVJISEhXGYXAAAAQJZyFT4GDx6sIkWKKCYmRsWKFbOOd+nSReHh4XnWHAAAAICCI1drPlasWKHly5erTJkyNuNVqlTR8ePH86QxAAAAAAVLrmY+kpKSbGY8Mly4cEFOTk533BQAAACAgidX4aNZs2b6+uuvrdsWi0Xp6ekaN26cWrZsmWfNAQAAACg4cvW1q3HjxqlVq1baunWrUlJS9NZbb2nv3r26cOGC1q1bl9c9AgAAACgAcjXzUbt2bf31119q2rSpOnTooKSkJHXq1Ek7duxQpUqVsn2cqKgoPfXUU/Lz85PFYtGiRYts9huGoREjRqh06dJydnZWYGCgDh48aFNz4cIFde/eXW5ubvLw8FBISIgSExNtanbt2qVmzZqpaNGi8vf317hx4zL1smDBAlWvXl1FixZVnTp19Ntvv+W4FwAAAAA3l+PwkZqaqlatWunMmTN69913NX/+fP32228aM2aMSpcunaNjJSUlqV69epo+fXqW+8eNG6epU6dq1qxZ2rRpk1xcXBQUFKQrV65Ya7p37669e/cqIiJCS5YsUVRUlF599VXr/oSEBLVu3VrlypXTtm3bNH78eI0aNUpffPGFtWb9+vXq1q2bQkJCtGPHDnXs2FEdO3bUnj17ctQLAAAAgJuzGLn4ZUAvLy+tX79eVapUybtGLBYtXLhQHTt2lHRtpsHPz09DhgzR0KFDJUnx8fHy8fHRnDlz1LVrV+3bt081a9bUli1b1LBhQ0lSeHi42rVrp5MnT8rPz08zZ87Uu+++q7i4ODk6OkqShg0bpkWLFmn//v2Srl0iOCkpSUuWLLH288gjj6h+/fqaNWtWtnrJjoSEBLm7uys+Pl5ubm558rwBAADg/lR+2FKb7WMft7dLHzn5jJurr129+OKL+vLLL3PVXHYdPXpUcXFxCgwMtI65u7urcePG2rBhgyRpw4YN8vDwsAYPSQoMDFShQoW0adMma03z5s2twUOSgoKCdODAAf3zzz/WmuvPk1GTcZ7s9JKV5ORkJSQk2NwAAACA+1WuFpxfvXpVX331lVauXKkGDRrIxcXFZv/EiRPvuLG4uDhJko+Pj824j4+PdV9cXJy8vb1t9hcuXFglS5a0qalQoUKmY2TsK1GihOLi4m57ntv1kpWxY8dq9OjRt3+wAAAAwH0gR+HjyJEjKl++vPbs2aOHHnpIkvTXX3/Z1Fgslrzr7h43fPhwhYaGWrcTEhLk7+9vx44AAAAA+8lR+KhSpYpiY2O1evVqSdfWSkydOjXTjEBe8PX1lSSdPn3aZiH76dOnVb9+fWvNmTNnbO539epVXbhwwXp/X19fnT592qYmY/t2Ndfvv10vWXFycuJHFwEAAID/L0drPm5cm75s2TIlJSXlaUMZKlSoIF9fX0VGRlrHEhIStGnTJgUEBEiSAgICdPHiRW3bts1as2rVKqWnp6tx48bWmqioKKWmplprIiIiVK1aNZUoUcJac/15MmoyzpOdXgAAAADcWq4WnGfIxYWybCQmJio6OlrR0dGSri3sjo6OVkxMjCwWiwYNGqQxY8bol19+0e7du9WjRw/5+flZr4hVo0YNtWnTRr1799bmzZu1bt069e/fX127dpWfn58k6YUXXpCjo6NCQkK0d+9ehYWFacqUKTZfhxo4cKDCw8M1YcIE7d+/X6NGjdLWrVvVv39/ScpWLwAAAABuLUdfu7JYLJnWdNzJGo+tW7eqZcuW1u2MQBAcHKw5c+borbfeUlJSkl599VVdvHhRTZs2VXh4uIoWLWq9z3fffaf+/furVatWKlSokDp37qypU6da97u7u2vFihXq16+fGjRoIE9PT40YMcLmt0AeffRRzZs3T++9957eeecdValSRYsWLVLt2rWtNdnpBQAAAMDN5eh3PgoVKqS2bdta1zH8+uuvevzxxzNd7ernn3/O2y4LCH7nAwAAAHnlXvydjxzNfAQHB9tsv/jiiznvDgAAAMB9KUfhY/bs2fnVBwAAAIAC7o4WnAMAAABAdhE+AAAAAJiC8AEAAADAFIQPAAAAAKYgfAAAAAAwBeEDAAAAgCkIHwAAAABMQfgAAAAAYArCBwAAAABT5OgXznHvKz9sqc32sY/b26kTAAAA3G+Y+QAAAABgCsIHAAAAAFMQPgAAAACYgvABAAAAwBSEDwAAAACmIHwAAAAAMAXhAwAAAIApCB8AAAAATEH4AAAAAGAKwgcAAAAAUxA+AAAAAJiC8AEAAADAFIQPAAAAAKYgfAAAAAAwBeEDAAAAgCkIHwAAAABMQfgAAAAAYArCBwAAAABTED4AAAAAmILwAQAAAMAUhA8AAAAApiB8AAAAADAF4QMAAACAKQgfAAAAAExB+AAAAABgCsIHAAAAAFMQPgAAAACYgvABAAAAwBSEDwAAAACmIHwAAAAAMAXhAwAAAIApCB8AAAAATEH4AAAAAGAKwgcAAAAAUxA+AAAAAJiC8AEAAADAFIQPAAAAAKYgfAAAAAAwBeEDAAAAgCnu6vAxatQoWSwWm1v16tWt+69cuaJ+/fqpVKlSKl68uDp37qzTp0/bHCMmJkbt27dXsWLF5O3trTfffFNXr161qVmzZo0eeughOTk5qXLlypozZ06mXqZPn67y5curaNGiaty4sTZv3pwvjxkAAAAoqO7q8CFJtWrVUmxsrPX2xx9/WPcNHjxYv/76qxYsWKC1a9fq1KlT6tSpk3V/Wlqa2rdvr5SUFK1fv15z587VnDlzNGLECGvN0aNH1b59e7Vs2VLR0dEaNGiQXnnlFS1fvtxaExYWptDQUI0cOVLbt29XvXr1FBQUpDNnzpjzJAAAAAAFwF0fPgoXLixfX1/rzdPTU5IUHx+vL7/8UhMnTtTjjz+uBg0aaPbs2Vq/fr02btwoSVqxYoX+/PNPffvtt6pfv77atm2rDz74QNOnT1dKSookadasWapQoYImTJigGjVqqH///nr22Wc1adIkaw8TJ05U79691atXL9WsWVOzZs1SsWLF9NVXX5n/hAAAAAD3qLs+fBw8eFB+fn6qWLGiunfvrpiYGEnStm3blJqaqsDAQGtt9erVVbZsWW3YsEGStGHDBtWpU0c+Pj7WmqCgICUkJGjv3r3WmuuPkVGTcYyUlBRt27bNpqZQoUIKDAy01txMcnKyEhISbG4AAADA/equDh+NGzfWnDlzFB4erpkzZ+ro0aNq1qyZLl26pLi4ODk6OsrDw8PmPj4+PoqLi5MkxcXF2QSPjP0Z+25Vk5CQoH///Vfnzp1TWlpaljUZx7iZsWPHyt3d3Xrz9/fP8XMAAAAAFBSF7d3ArbRt29b633Xr1lXjxo1Vrlw5zZ8/X87OznbsLHuGDx+u0NBQ63ZCQgIBBAAAAPetu3rm40YeHh6qWrWqDh06JF9fX6WkpOjixYs2NadPn5avr68kydfXN9PVrzK2b1fj5uYmZ2dneXp6ysHBIcuajGPcjJOTk9zc3GxuAAAAwP3qngofiYmJOnz4sEqXLq0GDRqoSJEiioyMtO4/cOCAYmJiFBAQIEkKCAjQ7t27ba5KFRERITc3N9WsWdNac/0xMmoyjuHo6KgGDRrY1KSnpysyMtJaAwAAAOD27urwMXToUK1du1bHjh3T+vXr9cwzz8jBwUHdunWTu7u7QkJCFBoaqtWrV2vbtm3q1auXAgIC9Mgjj0iSWrdurZo1a+qll17Szp07tXz5cr333nvq16+fnJycJEmvvfaajhw5orfeekv79+/XjBkzNH/+fA0ePNjaR2hoqP773/9q7ty52rdvn/r27aukpCT16tXLLs8LAAAAcC+6q9d8nDx5Ut26ddP58+fl5eWlpk2bauPGjfLy8pIkTZo0SYUKFVLnzp2VnJysoKAgzZgxw3p/BwcHLVmyRH379lVAQIBcXFwUHBys999/31pToUIFLV26VIMHD9aUKVNUpkwZ/d///Z+CgoKsNV26dNHZs2c1YsQIxcXFqX79+goPD8+0CB0AAADAzVkMwzDs3cT9IiEhQe7u7oqPj7fb+o/yw5babB/7uL1d+gAAAMCduVs+1+XkM+5dPfMBAAAA3CvuljBwN7ur13wAAAAAKDgIHwAAAABMwdeuAAAAgLvA/fC1LWY+AAAAAJiC8AEAAADAFIQPAAAAAKYgfAAAAAAwBQvOAQAAABPcuKD8fsTMBwAAAABTMPMBAAAA5ANmOjJj5gMAAACAKQgfAAAAAExB+AAAAABgCtZ8AAAAFCA3rjM49nF7O3Vivvv5sd8rCB8AAADAXagghim+dgUAAADAFIQPAAAAAKYgfAAAAAAwBWs+AAAAgCwUxDUX9sbMBwAAAABTED4AAAAAmIKvXQEAAADZwNew7hwzHwAAAABMQfgAAAAAYArCBwAAAABTsOYDAAAA9yXWcJiP8AEAAADkwo3hBbdH+AAAoADiX3QB3I0IHwAAAMA9oCDMtLDgHAAAAIApCB8AAAAATEH4AAAAAGAK1nwAAAAAKhhrKu52zHwAAAAAMAUzHwAAADDN9bML+X0JaGYy7j7MfAAAAAAwBeEDAAAAgCkIHwAAAABMwZoPAACAW7hx3UB+r1O4n91ujQbP/b2P8AEAAIBsI4zhThA+AAAAkGfyM5wQfO59hA/gPsBf1gAA4G7AgnMAAAAApmDmAwAAAPkmP3/ojx8RvPcQPgAAQIHCV02BuxfhAwAAAHbBzMX9h/ABAACQh+61mZfb9UtAQF4ifAAAACDXCCfICcIHABRg99q/wAKwP8IE8hPhAwAAmC6nX/XJz+Cc3+e606815Xc/gJkIHwAAu2FmBveiO33f5vTDv9nnA/IT4SOHpk+frvHjxysuLk716tXTZ599pocfftjebQEAskC4sZ+76QPv3dRLXuB9jXsZ4SMHwsLCFBoaqlmzZqlx48aaPHmygoKCdODAAXl7e9u7PQDAHbrVh7qcfuAraB8Qzf5qkD3Pf6czEwBujvCRAxMnTlTv3r3Vq1cvSdKsWbO0dOlSffXVVxo2bJiduwNwMwXtQ+C9JK+/LnI3vXZ3GkZuZPaah7z+wHynx7P3/e9l9/Njx73HYhiGYe8m7gUpKSkqVqyYfvzxR3Xs2NE6HhwcrIsXL2rx4sWZ7pOcnKzk5GTrdnx8vMqWLasTJ07Izc3NjLYzqT1yuc32ntFBdukD5rL3636785u9HwCAgshen+sSEhLk7++vixcvyt3d/Za1zHxk07lz55SWliYfHx+bcR8fH+3fvz/L+4wdO1ajR4/ONO7v758vPeaG+2R7dwB7sPfrfrvz5/d+AAAKInv//+/SpUuED3saPny4QkNDrdvp6em6cOGCSpUqJYvFYno/GanUnjMvMB+v+/2L1/7+xWt//+K1v3/Z87U3DEOXLl2Sn5/fbWsJH9nk6ekpBwcHnT592mb89OnT8vX1zfI+Tk5OcnJyshnz8PDIrxazzc3Njb+Q7kO87vcvXvv7F6/9/YvX/v5lr9f+djMeGQrlcx8FhqOjoxo0aKDIyEjrWHp6uiIjIxUQEGDHzgAAAIB7AzMfORAaGqrg4GA1bNhQDz/8sCZPnqykpCTr1a8AAAAA3BzhIwe6dOmis2fPasSIEYqLi1P9+vUVHh6eaRH63crJyUkjR47M9FUwFGy87vcvXvv7F6/9/YvX/v51r7z2XGoXAAAAgClY8wEAAADAFIQPAAAAAKYgfAAAAAAwBeEDAAAAgCkIH/eJ6dOnq3z58ipatKgaN26szZs327slmCAqKkpPPfWU/Pz8ZLFYtGjRInu3BBOMHTtWjRo1kqurq7y9vdWxY0cdOHDA3m3BBDNnzlTdunWtPzIWEBCgZcuW2bstmOzjjz+WxWLRoEGD7N0K8tmoUaNksVhsbtWrV7d3W7dE+LgPhIWFKTQ0VCNHjtT27dtVr149BQUF6cyZM/ZuDfksKSlJ9erV0/Tp0+3dCky0du1a9evXTxs3blRERIRSU1PVunVrJSUl2bs15LMyZcro448/1rZt27R161Y9/vjj6tChg/bu3Wvv1mCSLVu26PPPP1fdunXt3QpMUqtWLcXGxlpvf/zxh71buiUutXsfaNy4sRo1aqRp06ZJuvbL7P7+/nrjjTc0bNgwO3cHs1gsFi1cuFAdO3a0dysw2dmzZ+Xt7a21a9eqefPm9m4HJitZsqTGjx+vkJAQe7eCfJaYmKiHHnpIM2bM0JgxY1S/fn1NnjzZ3m0hH40aNUqLFi1SdHS0vVvJNmY+CriUlBRt27ZNgYGB1rFChQopMDBQGzZssGNnAMwSHx8v6dqHUNw/0tLS9MMPPygpKUkBAQH2bgcm6Nevn9q3b2/z/3wUfAcPHpSfn58qVqyo7t27KyYmxt4t3RK/cF7AnTt3TmlpaZl+hd3Hx0f79++3U1cAzJKenq5BgwapSZMmql27tr3bgQl2796tgIAAXblyRcWLF9fChQtVs2ZNe7eFfPbDDz9o+/bt2rJli71bgYkaN26sOXPmqFq1aoqNjdXo0aPVrFkz7dmzR66urvZuL0uEDwAowPr166c9e/bc9d8BRt6pVq2aoqOjFR8frx9//FHBwcFau3YtAaQAO3HihAYOHKiIiAgVLVrU3u3ARG3btrX+d926ddW4cWOVK1dO8+fPv2u/akn4KOA8PT3l4OCg06dP24yfPn1avr6+duoKgBn69++vJUuWKCoqSmXKlLF3OzCJo6OjKleuLElq0KCBtmzZoilTpujzzz+3c2fIL9u2bdOZM2f00EMPWcfS0tIUFRWladOmKTk5WQ4ODnbsEGbx8PBQ1apVdejQIXu3clOs+SjgHB0d1aBBA0VGRlrH0tPTFRkZyXeAgQLKMAz1799fCxcu1KpVq1ShQgV7twQ7Sk9PV3Jysr3bQD5q1aqVdu/erejoaOutYcOG6t69u6Kjowke95HExEQdPnxYpUuXtncrN8XMx30gNDRUwcHBatiwoR5++GFNnjxZSUlJ6tWrl71bQz5LTEy0+dePo0ePKjo6WiVLllTZsmXt2BnyU79+/TRv3jwtXrxYrq6uiouLkyS5u7vL2dnZzt0hPw0fPlxt27ZV2bJldenSJc2bN09r1qzR8uXL7d0a8pGrq2umNV0uLi4qVaoUa70KuKFDh+qpp55SuXLldOrUKY0cOVIODg7q1q2bvVu7KcLHfaBLly46e/asRowYobi4ONWvX1/h4eGZFqGj4Nm6datatmxp3Q4NDZUkBQcHa86cOXbqCvlt5syZkqTHHnvMZnz27Nnq2bOn+Q3BNGfOnFGPHj0UGxsrd3d31a1bV8uXL9cTTzxh79YA5IOTJ0+qW7duOn/+vLy8vNS0aVNt3LhRXl5e9m7tpvidDwAAAACmYM0HAAAAAFMQPgAAAACYgvABAAAAwBSEDwAAAACmIHwAAAAAMAXhAwAAAIApCB8AAAAATEH4AAAAAGAKwgcAoMD54osv5O/vr0KFCmny5Mm5Okb58uVve1+LxaJFixbl6vgAcD8qbO8GAAAF35w5czRo0CBdvHgx38+VkJCg/v37a+LEiercubPc3d1zdZwtW7bIxcUlj7sDgPsb4QMAkGspKSlydHS0dxs2YmJilJqaqvbt26t06dK5Po6Xl1cedgUAkPjaFQAgBx577DH1799fgwYNkqenp4KCgiRJEydOVJ06deTi4iJ/f3+9/vrrSkxMlCStWbNGvXr1Unx8vCwWiywWi0aNGiVJSk5O1tChQ/XAAw/IxcVFjRs31po1a27ZQ0xMjDp06KDixYvLzc1Nzz//vE6fPi3p2gxLnTp1JEkVK1aUxWLRsWPHMh3j0Ucf1dtvv20zdvbsWRUpUkRRUVGSMn/t6uDBg2revLmKFi2qmjVrKiIiItNxT5w4oeeff14eHh4qWbKkOnToYHP+9PR0vf/++ypTpoycnJxUv359hYeH3/LxAkBBQvgAAOTI3Llz5ejoqHXr1mnWrFmSpEKFCmnq1Knau3ev5s6dq1WrVumtt96SdO2D/uTJk+Xm5qbY2FjFxsZq6NChkqT+/ftrw4YN+uGHH7Rr1y4999xzatOmjQ4ePJjludPT09WhQwdduHBBa9euVUREhI4cOaIuXbpIkrp06aKVK1dKkjZv3qzY2Fj5+/tnOk737t31ww8/yDAM61hYWJj8/PzUrFmzLM/bqVMnOTo6atOmTZo1a1am8JKamqqgoCC5urrq999/17p161S8eHG1adNGKSkpkqQpU6ZowoQJ+vTTT7Vr1y4FBQXp6aefvunjBYACxwAAIJtatGhhPPjgg7etW7BggVGqVCnr9uzZsw13d3ebmuPHjxsODg7G33//bTPeqlUrY/jw4Vked8WKFYaDg4MRExNjHdu7d68hydi8ebNhGIaxY8cOQ5Jx9OjRm/Z35swZo3DhwkZUVJR1LCAgwHj77bet2+XKlTMmTZpkGIZhLF++3ChcuLBNr8uWLTMkGQsXLjQMwzC++eYbo1q1akZ6erq1Jjk52XB2djaWL19uGIZh+Pn5GR9++KFNL40aNTJef/31m/YKAAUJaz4AADnSoEGDTGMrV67U2LFjtX//fiUkJOjq1au6cuWKLl++rGLFimV5nN27dystLU1Vq1a1GU9OTlapUqWyvM++ffvk7+9vM5tRs2ZNeXh4aN++fWrUqFG2HoOXl5dat26t7777Ts2aNdPRo0e1YcMGff7557c8r5+fn3UsICDApmbnzp06dOiQXF1dbcavXLmiw4cPKyEhQadOnVKTJk1s9jdp0kQ7d+7MVt8AcK8jfAAAcuTGK0AdO3ZMTz75pPr27asPP/xQJUuW1B9//KGQkBClpKTcNHwkJibKwcFB27Ztk4ODg82+4sWL51v/Gbp3764BAwbos88+07x581SnTh3repHcSExMVIMGDfTdd99l2sfidQC4hvABALgj27ZtU3p6uiZMmKBCha4tJZw/f75NjaOjo9LS0mzGHnzwQaWlpenMmTNZrrPISo0aNXTixAmdOHHCOvvx559/6uLFi6pZs2aO+u7QoYNeffVVhYeHa968eerRo8dtzxsbG2u9gtbGjRttah566CGFhYXJ29tbbm5uWR7Hz89P69atU4sWLaxj69at08MPP5yj3gHgXsWCcwDAHalcubJSU1P12Wef6ciRI/rmm2+sC9EzlC9fXomJiYqMjNS5c+d0+fJlVa1aVd27d1ePHj30888/6+jRo9q8ebPGjh2rpUuXZnmuwMBA1alTR927d9f27du1efNm9ejRQy1atFDDhg1z1LeLi4s6duyo//znP9q3b5+6det209rAwEBVrVpVwcHB2rlzp37//Xe9++67NjXdu3eXp6enOnTooN9//11Hjx7VmjVrNGDAAJ08eVKS9Oabb+qTTz5RWFiYDhw4oGHDhik6OloDBw7MUe8AcK8ifAAA7ki9evU0ceJEffLJJ6pdu7a+++47jR071qbm0Ucf1WuvvaYuXbrIy8tL48aNkyTNnj1bPXr00JAhQ1StWjV17NhRW7ZsUdmyZbM8l8Vi0eLFi1WiRAk1b95cgYGBqlixosLCwnLVe/fu3bVz5041a9bspueUrl3Na+HChfr333/18MMP65VXXtGHH35oU1OsWDFFRUWpbNmy6tSpk2rUqKGQkBBduXLFOhMyYMAAhYaGasiQIapTp47Cw8P1yy+/qEqVKrnqHwDuNRbDuO46gwAAAACQT5j5AAAAAGAKwgcAAAAAUxA+AAAAAJiC8AEAAADAFIQPAAAAAKYgfAAAAAAwBeEDAAAAgCkIHwAAAABMQfgAAAAAYArCBwAAAABTED4AAAAAmOL/AfkXDqQzokLaAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 900x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distribution_Frequency(rate_values2,'rate of video')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ae6ff04-2406-464a-94d9-7844dcf88f3c",
   "metadata": {},
   "source": [
    "#### Distribution of `RATINGS counts` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "853bdfcb-0349-4746-ad97-5f9aa109f41a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/yq/sryk517930l66t3h_fdc8w040000gn/T/ipykernel_16784/107476399.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  rate_values2[i] = 0\n",
      "/var/folders/yq/sryk517930l66t3h_fdc8w040000gn/T/ipykernel_16784/107476399.py:7: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  ratings_values2[i] = 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "for i in range(len(rate_values2)):\n",
    "    if pd.isna(rate_values2[i]) or rate_values2[i] is None:\n",
    "        rate_values2[i] = 0\n",
    "        \n",
    "for i in range(len(ratings_values2)):\n",
    "    if pd.isna(ratings_values2[i]) or ratings_values2[i] is None:\n",
    "        ratings_values2[i] = 0\n",
    "\n",
    "fig, axs = plt.subplots(2, 1, figsize=(20, 10), sharex=True, sharey=True,\n",
    "                        tight_layout=True)\n",
    "\n",
    "# We can increase the number of bins on each axis\n",
    "#axs[0].hist2d(rate_values, ratings_values, bins=40)\n",
    "\n",
    "# As well as define normalization of the colors\n",
    "axs[0].hist2d(rate_values2, ratings_values2, bins=40, norm=colors.LogNorm())\n",
    "\n",
    "# We can also define custom numbers of bins for each axis\n",
    "axs[1].hist2d(rate_values2, ratings_values2, bins=(80, 20), norm=colors.LogNorm())\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc592121-7adf-4099-b8ad-6bb0c1eae65a",
   "metadata": {},
   "source": [
    "#### Distribution of `LENGTH` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "298da249-1c54-47e8-b1ff-a227321b3688",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/yq/sryk517930l66t3h_fdc8w040000gn/T/ipykernel_16784/3871701895.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  length_values2[i] = 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(len(length_values2)):\n",
    "    if pd.isna(length_values2[i]) or length_values2[i] is None:\n",
    "        length_values2[i] = 0\n",
    "\n",
    "#plot_video_length_barchart(length_values,'length of videos')\n",
    "#distribution_Frequency(length_values,'length of video')\n",
    "\n",
    "fig, axs = plt.subplots(2, 1, figsize=(20, 10), sharex=True, sharey=True,\n",
    "                        tight_layout=True)\n",
    "\n",
    "# We can increase the number of bins on each axis\n",
    "#axs[0].hist2d(length_values,rate_values, bins=40)\n",
    "\n",
    "# As well as define normalization of the colors\n",
    "axs[0].hist2d(length_values2,rate_values2, bins=40, norm=colors.LogNorm())\n",
    "\n",
    "# We can also define custom numbers of bins for each axis\n",
    "axs[1].hist2d(length_values2,rate_values2, bins=(80, 20), norm=colors.LogNorm())\n",
    "plt.ticklabel_format(useOffset=False, style='plain', axis='x')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8181747-c648-4e1f-a483-b2e7e04d3432",
   "metadata": {},
   "source": [
    "#### Distribution of `COMMENTS counts` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0de827f4-b9a2-4e63-8a13-8c59ee9e0a7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#distribution_Frequency(comments_values,'comments of video')\n",
    "for i in range(len(comments_values2)):\n",
    "    if pd.isna(comments_values2[i]) or comments_values2[i] is None:\n",
    "        comments_values2[i] = 0\n",
    "\n",
    "for i in range(len(comments_values2)):\n",
    "    if pd.isna(rate_values2[i]) or rate_values2[i] is None:\n",
    "        rate_values2[i] = 0\n",
    "\n",
    "fig, axs = plt.subplots(2, 1, figsize=(20, 10), sharex=True, sharey=True,\n",
    "                        tight_layout=True)\n",
    "\n",
    "# We can increase the number of bins on each axis\n",
    "#axs[0].hist2d(comments_values,rate_values, bins=40)\n",
    "\n",
    "# As well as define normalization of the colors\n",
    "axs[0].hist2d(comments_values2,rate_values2, bins=40, norm=colors.LogNorm())\n",
    "\n",
    "# We can also define custom numbers of bins for each axis\n",
    "axs[1].hist2d(comments_values2,rate_values2, bins=(80, 20), norm=colors.LogNorm())\n",
    "plt.ticklabel_format(useOffset=False, style='plain', axis='x')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "302fd20f-8f66-48f6-99be-c4f0b24077ad",
   "metadata": {},
   "source": [
    "#### Distribution of `UPLOADER` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a72f1ea0-0ad4-4323-b079-cc6b0ced2723",
   "metadata": {},
   "outputs": [],
   "source": [
    "plot_categorical_frequency(uploader_values2,'uploader of video')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7db23c41-08ee-4f56-b8e9-68383036fe10",
   "metadata": {},
   "source": [
    "#### Distribution of `VIEWS` of videos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "1f7314a4-2063-478b-ad20-f1a6617b706f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/yq/sryk517930l66t3h_fdc8w040000gn/T/ipykernel_16784/1774136897.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  views_values2[i] = 0\n",
      "/var/folders/yq/sryk517930l66t3h_fdc8w040000gn/T/ipykernel_16784/1774136897.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  comments_values2[i] = 0\n"
     ]
    },
    {
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      "text/plain": [
       "<Figure size 2000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#distribution_Frequency(views_values,'views of video')\n",
    "\n",
    "for i in range(len(views_values2)):\n",
    "    if pd.isna(views_values2[i]) or views_values2[i] is None:\n",
    "        views_values2[i] = 0\n",
    "\n",
    "for i in range(len(comments_values2)):\n",
    "    if pd.isna(comments_values2[i]) or comments_values2[i] is None:\n",
    "        comments_values2[i] = 0\n",
    "\n",
    "fig, axs = plt.subplots(2, 1, figsize=(20, 10), sharex=True, sharey=True,\n",
    "                        tight_layout=True)\n",
    "\n",
    "# We can increase the number of bins on each axis\n",
    "#axs[0].hist2d(comments_values,rate_values, bins=40)\n",
    "\n",
    "# As well as define normalization of the colors\n",
    "axs[0].hist2d(comments_values2,views_values2, bins=40, norm=colors.LogNorm())\n",
    "\n",
    "# We can also define custom numbers of bins for each axis\n",
    "axs[1].hist2d(comments_values2,views_values2, bins=(80, 20), norm=colors.LogNorm())\n",
    "plt.ticklabel_format(useOffset=False, style='plain', axis='y')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02b25cdc-0c54-46e0-970a-f186f736bbac",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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