Survey.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from collections import Counter\n",
    "from itertools import chain\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib.lines import Line2D\n",
    "\n",
    "typeLegend = [Line2D([0], [0], color=\"C0\", lw=8), Line2D([0], [0], color=\"C1\", lw=8)]\n",
    "wasteLegend = [Line2D([0], [0], color=f\"C{i}\", lw=4) for i in range(5)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": "    Id What is the main programming language you use in the chosen project?  \\\n0    0                                             Python                     \n1    1                                               Java                     \n2    2                                                PHP                     \n3    3                                               Java                     \n4    4                                               Java                     \n5    5                                         JavaScript                     \n6    6                                                 AL                     \n7    7                                         JavaScript                     \n8    8                                             Python                     \n9    9                                         JavaScript                     \n10  10                                             Python                     \n11  11                                         JavaScript                     \n12  12                                         JavaScript                     \n\n   What is your main role in the chosen project?  \\\n0                            Fullstack Developer   \n1                            Fullstack Developer   \n2                            Fullstack Developer   \n3                              Backend Developer   \n4                              Backend Developer   \n5                              Backend Developer   \n6                            Fullstack Developer   \n7                            Fullstack Developer   \n8                                Software Tester   \n9                             Frontend Developer   \n10                                 Data Engineer   \n11                            Frontend Developer   \n12                               Project Manager   \n\n    What is your level of work experience in a such or similar role?  \\\n0                                                   2                  \n1                                                   2                  \n2                                                   3                  \n3                                                   5                  \n4                                                   3                  \n5                                                   3                  \n6                                                   2                  \n7                                                   2                  \n8                                                   1                  \n9                                                   1                  \n10                                                  2                  \n11                                                  2                  \n12                                                  5                  \n\n    How long (in months) is your work experience in such or similar roles in general?  \\\n0                                                   7                                   \n1                                                  19                                   \n2                                                  18                                   \n3                                                  60                                   \n4                                                   2                                   \n5                                                  24                                   \n6                                                  16                                   \n7                                                   7                                   \n8                                                   4                                   \n9                                                   9                                   \n10                                                  6                                   \n11                                                 18                                   \n12                                                 72                                   \n\n    How long (in months) is your work experience in the chosen project?  \\\n0                                                   7                     \n1                                                  17                     \n2                                                  18                     \n3                                                  10                     \n4                                                   1                     \n5                                                   8                     \n6                                                   2                     \n7                                                   2                     \n8                                                   3                     \n9                                                   9                     \n10                                                  4                     \n11                                                 18                     \n12                                                 48                     \n\n    How common are those task-related \"wastes\" in the chosen project? [Unclearly defined tasks]  \\\n0                                                   3                                             \n1                                                   3                                             \n2                                                   4                                             \n3                                                   3                                             \n4                                                   4                                             \n5                                                   3                                             \n6                                                   2                                             \n7                                                   5                                             \n8                                                   2                                             \n9                                                   2                                             \n10                                                  3                                             \n11                                                  4                                             \n12                                                  2                                             \n\n    How common are those task-related \"wastes\" in the chosen project? [Focusing on unneeded tasks]  \\\n0                                                   2                                                \n1                                                   1                                                \n2                                                   3                                                \n3                                                   1                                                \n4                                                   3                                                \n5                                                   3                                                \n6                                                   1                                                \n7                                                   3                                                \n8                                                   1                                                \n9                                                   2                                                \n10                                                  4                                                \n11                                                  1                                                \n12                                                  2                                                \n\n    How common are those task-related \"wastes\" in the chosen project? [Leaving tasks uncompleted]  \\\n0                                                   2                                               \n1                                                   2                                               \n2                                                   4                                               \n3                                                   5                                               \n4                                                   3                                               \n5                                                   4                                               \n6                                                   3                                               \n7                                                   3                                               \n8                                                   2                                               \n9                                                   1                                               \n10                                                  2                                               \n11                                                  1                                               \n12                                                  3                                               \n\n    How common are those task-related \"wastes\" in the chosen project? [Poorly executed tasks]  \\\n0                                                   4                                           \n1                                                   2                                           \n2                                                   3                                           \n3                                                   4                                           \n4                                                   4                                           \n5                                                   2                                           \n6                                                   2                                           \n7                                                   2                                           \n8                                                   3                                           \n9                                                   3                                           \n10                                                  1                                           \n11                                                  1                                           \n12                                                  3                                           \n\n    ...  \\\n0   ...   \n1   ...   \n2   ...   \n3   ...   \n4   ...   \n5   ...   \n6   ...   \n7   ...   \n8   ...   \n9   ...   \n10  ...   \n11  ...   \n12  ...   \n\n    How common are those information-related \"wastes\" in the chosen project? [Too frequent meetings]  \\\n0                                                   2                                                  \n1                                                   1                                                  \n2                                                   1                                                  \n3                                                   1                                                  \n4                                                   4                                                  \n5                                                   2                                                  \n6                                                   1                                                  \n7                                                   1                                                  \n8                                                   3                                                  \n9                                                   2                                                  \n10                                                  1                                                  \n11                                                  1                                                  \n12                                                  2                                                  \n\n    How common are those information-related \"wastes\" in the chosen project? [Too long meetings]  \\\n0                                                   5                                              \n1                                                   3                                              \n2                                                   3                                              \n3                                                   1                                              \n4                                                   2                                              \n5                                                   3                                              \n6                                                   1                                              \n7                                                   1                                              \n8                                                   3                                              \n9                                                   2                                              \n10                                                  1                                              \n11                                                  2                                              \n12                                                  4                                              \n\n    How common are those information-related \"wastes\" in the chosen project? [Bad flow of information inside team]  \\\n0                                                   3                                                                \n1                                                   1                                                                \n2                                                   2                                                                \n3                                                   2                                                                \n4                                                   2                                                                \n5                                                   2                                                                \n6                                                   2                                                                \n7                                                   2                                                                \n8                                                   2                                                                \n9                                                   2                                                                \n10                                                  3                                                                \n11                                                  4                                                                \n12                                                  3                                                                \n\n    How common are those information-related \"wastes\" in the chosen project? [Language-specific communication issues]  \\\n0                                                   2                                                                   \n1                                                   1                                                                   \n2                                                   1                                                                   \n3                                                   1                                                                   \n4                                                   3                                                                   \n5                                                   1                                                                   \n6                                                   1                                                                   \n7                                                   1                                                                   \n8                                                   1                                                                   \n9                                                   2                                                                   \n10                                                  1                                                                   \n11                                                  2                                                                   \n12                                                  2                                                                   \n\n    How harmful are those information-related \"wastes\" in the chosen project? [Issues with documentation]  \\\n0                                                   2                                                       \n1                                                   3                                                       \n2                                                   4                                                       \n3                                                   5                                                       \n4                                                   3                                                       \n5                                                   4                                                       \n6                                                   5                                                       \n7                                                   2                                                       \n8                                                   5                                                       \n9                                                   2                                                       \n10                                                  1                                                       \n11                                                  5                                                       \n12                                                  3                                                       \n\n    How harmful are those information-related \"wastes\" in the chosen project? [Wrong introduction of new team members]  \\\n0                                                   4                                                                    \n1                                                   1                                                                    \n2                                                   3                                                                    \n3                                                   4                                                                    \n4                                                   4                                                                    \n5                                                   3                                                                    \n6                                                   3                                                                    \n7                                                   1                                                                    \n8                                                   4                                                                    \n9                                                   5                                                                    \n10                                                  2                                                                    \n11                                                  5                                                                    \n12                                                  2                                                                    \n\n    How harmful are those information-related \"wastes\" in the chosen project? [Too frequent meetings]  \\\n0                                                   5                                                   \n1                                                   1                                                   \n2                                                   4                                                   \n3                                                   3                                                   \n4                                                   2                                                   \n5                                                   2                                                   \n6                                                   2                                                   \n7                                                   1                                                   \n8                                                   4                                                   \n9                                                   3                                                   \n10                                                  1                                                   \n11                                                  2                                                   \n12                                                  2                                                   \n\n    How harmful are those information-related \"wastes\" in the chosen project? [Too long meetings]  \\\n0                                                   5                                               \n1                                                   2                                               \n2                                                   3                                               \n3                                                   3                                               \n4                                                   2                                               \n5                                                   4                                               \n6                                                   1                                               \n7                                                   1                                               \n8                                                   4                                               \n9                                                   3                                               \n10                                                  1                                               \n11                                                  2                                               \n12                                                  2                                               \n\n    How harmful are those information-related \"wastes\" in the chosen project? [Bad flow of information inside team]  \\\n0                                                   5                                                                 \n1                                                   1                                                                 \n2                                                   3                                                                 \n3                                                   5                                                                 \n4                                                   4                                                                 \n5                                                   4                                                                 \n6                                                   4                                                                 \n7                                                   2                                                                 \n8                                                   5                                                                 \n9                                                   5                                                                 \n10                                                  2                                                                 \n11                                                  4                                                                 \n12                                                  5                                                                 \n\n    How harmful are those information-related \"wastes\" in the chosen project? [Language-specific communication issues]  \n0                                                   2                                                                   \n1                                                   1                                                                   \n2                                                   1                                                                   \n3                                                   5                                                                   \n4                                                   3                                                                   \n5                                                   2                                                                   \n6                                                   3                                                                   \n7                                                   2                                                                   \n8                                                   3                                                                   \n9                                                   3                                                                   \n10                                                  1                                                                   \n11                                                  2                                                                   \n12                                                  3                                                                   \n\n[13 rows x 28 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Id</th>\n      <th>What is the main programming language you use in the chosen project?</th>\n      <th>What is your main role in the chosen project?</th>\n      <th>What is your level of work experience in a such or similar role?</th>\n      <th>How long (in months) is your work experience in such or similar roles in general?</th>\n      <th>How long (in months) is your work experience in the chosen project?</th>\n      <th>How common are those task-related \"wastes\" in the chosen project? [Unclearly defined tasks]</th>\n      <th>How common are those task-related \"wastes\" in the chosen project? [Focusing on unneeded tasks]</th>\n      <th>How common are those task-related \"wastes\" in the chosen project? [Leaving tasks uncompleted]</th>\n      <th>How common are those task-related \"wastes\" in the chosen project? [Poorly executed tasks]</th>\n      <th>...</th>\n      <th>How common are those information-related \"wastes\" in the chosen project? [Too frequent meetings]</th>\n      <th>How common are those information-related \"wastes\" in the chosen project? [Too long meetings]</th>\n      <th>How common are those information-related \"wastes\" in the chosen project? [Bad flow of information inside team]</th>\n      <th>How common are those information-related \"wastes\" in the chosen project? [Language-specific communication issues]</th>\n      <th>How harmful are those information-related \"wastes\" in the chosen project? [Issues with documentation]</th>\n      <th>How harmful are those information-related \"wastes\" in the chosen project? [Wrong introduction of new team members]</th>\n      <th>How harmful are those information-related \"wastes\" in the chosen project? [Too frequent meetings]</th>\n      <th>How harmful are those information-related \"wastes\" in the chosen project? [Too long meetings]</th>\n      <th>How harmful are those information-related \"wastes\" in the chosen project? [Bad flow of information inside team]</th>\n      <th>How harmful are those information-related \"wastes\" in the chosen project? [Language-specific communication issues]</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>Python</td>\n      <td>Fullstack Developer</td>\n      <td>2</td>\n      <td>7</td>\n      <td>7</td>\n      <td>3</td>\n      <td>2</td>\n      <td>2</td>\n      <td>4</td>\n      <td>...</td>\n      <td>2</td>\n      <td>5</td>\n      <td>3</td>\n      <td>2</td>\n      <td>2</td>\n      <td>4</td>\n      <td>5</td>\n      <td>5</td>\n      <td>5</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>Java</td>\n      <td>Fullstack Developer</td>\n      <td>2</td>\n      <td>19</td>\n      <td>17</td>\n      <td>3</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>...</td>\n      <td>1</td>\n      <td>3</td>\n      <td>1</td>\n      <td>1</td>\n      <td>3</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>PHP</td>\n      <td>Fullstack Developer</td>\n      <td>3</td>\n      <td>18</td>\n      <td>18</td>\n      <td>4</td>\n      <td>3</td>\n      <td>4</td>\n      <td>3</td>\n      <td>...</td>\n      <td>1</td>\n      <td>3</td>\n      <td>2</td>\n      <td>1</td>\n      <td>4</td>\n      <td>3</td>\n      <td>4</td>\n      <td>3</td>\n      <td>3</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>Java</td>\n      <td>Backend Developer</td>\n      <td>5</td>\n      <td>60</td>\n      <td>10</td>\n      <td>3</td>\n      <td>1</td>\n      <td>5</td>\n      <td>4</td>\n      <td>...</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>5</td>\n      <td>4</td>\n      <td>3</td>\n      <td>3</td>\n      <td>5</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4</td>\n      <td>Java</td>\n      <td>Backend Developer</td>\n      <td>3</td>\n      <td>2</td>\n      <td>1</td>\n      <td>4</td>\n      <td>3</td>\n      <td>3</td>\n      <td>4</td>\n      <td>...</td>\n      <td>4</td>\n      <td>2</td>\n      <td>2</td>\n      <td>3</td>\n      <td>3</td>\n      <td>4</td>\n      <td>2</td>\n      <td>2</td>\n      <td>4</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>5</td>\n      <td>JavaScript</td>\n      <td>Backend Developer</td>\n      <td>3</td>\n      <td>24</td>\n      <td>8</td>\n      <td>3</td>\n      <td>3</td>\n      <td>4</td>\n      <td>2</td>\n      <td>...</td>\n      <td>2</td>\n      <td>3</td>\n      <td>2</td>\n      <td>1</td>\n      <td>4</td>\n      <td>3</td>\n      <td>2</td>\n      <td>4</td>\n      <td>4</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>6</td>\n      <td>AL</td>\n      <td>Fullstack Developer</td>\n      <td>2</td>\n      <td>16</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>3</td>\n      <td>2</td>\n      <td>...</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>5</td>\n      <td>3</td>\n      <td>2</td>\n      <td>1</td>\n      <td>4</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>7</td>\n      <td>JavaScript</td>\n      <td>Fullstack Developer</td>\n      <td>2</td>\n      <td>7</td>\n      <td>2</td>\n      <td>5</td>\n      <td>3</td>\n      <td>3</td>\n      <td>2</td>\n      <td>...</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>8</td>\n      <td>Python</td>\n      <td>Software Tester</td>\n      <td>1</td>\n      <td>4</td>\n      <td>3</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>3</td>\n      <td>...</td>\n      <td>3</td>\n      <td>3</td>\n      <td>2</td>\n      <td>1</td>\n      <td>5</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>5</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>9</td>\n      <td>JavaScript</td>\n      <td>Frontend Developer</td>\n      <td>1</td>\n      <td>9</td>\n      <td>9</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>3</td>\n      <td>...</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>5</td>\n      <td>3</td>\n      <td>3</td>\n      <td>5</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>10</td>\n      <td>Python</td>\n      <td>Data Engineer</td>\n      <td>2</td>\n      <td>6</td>\n      <td>4</td>\n      <td>3</td>\n      <td>4</td>\n      <td>2</td>\n      <td>1</td>\n      <td>...</td>\n      <td>1</td>\n      <td>1</td>\n      <td>3</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>11</td>\n      <td>JavaScript</td>\n      <td>Frontend Developer</td>\n      <td>2</td>\n      <td>18</td>\n      <td>18</td>\n      <td>4</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>...</td>\n      <td>1</td>\n      <td>2</td>\n      <td>4</td>\n      <td>2</td>\n      <td>5</td>\n      <td>5</td>\n      <td>2</td>\n      <td>2</td>\n      <td>4</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>12</td>\n      <td>JavaScript</td>\n      <td>Project Manager</td>\n      <td>5</td>\n      <td>72</td>\n      <td>48</td>\n      <td>2</td>\n      <td>2</td>\n      <td>3</td>\n      <td>3</td>\n      <td>...</td>\n      <td>2</td>\n      <td>4</td>\n      <td>3</td>\n      <td>2</td>\n      <td>3</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>5</td>\n      <td>3</td>\n    </tr>\n  </tbody>\n</table>\n<p>13 rows × 28 columns</p>\n</div>"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"wastes.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "taskRelated = {col[col.index('[')+1:-1] for col in df.columns[6:11]}\n",
    "infoRelated = {col[col.index('[')+1:-1] for col in df.columns[16:22]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Q1: What is your name ?\n",
    "df.drop(columns=[\"What is your name ?\"], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAU8AAADnCAYAAACe9dTFAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAyn0lEQVR4nO3dd3xT5f4H8M85WZ2ku3SH0dICKSDIbCkUXBQVt8ioW6QyBP0ZF/Y6Lr16EcUF96LI0KsgKkIUUEYpe0OgLbusUrpTujPO748UZLTQpkmek/T7fr36gibnnOcTaL95zslznocTBAGEEEJahmcdgBBCnBEVT0IIsQIVT0IIsQIVT0IIsQIVT0IIsQIVT0IIsQIVT0IIsQIVT0IIsQIVT0IIsQIVT0IIsYKUdQBCSOvt2bMnSCqVzgfQHdQpsgUzgENGo/HZ3r17Fza2ARVPQlyAVCqd3759+7jAwMAynudpwopWMpvNXFFRUdeCgoL5AO5rbBt6hyLENXQPDAysoMJpGzzPC4GBgXpYevKNb+PAPIQQ++GpcNpWw79nkzWSiichhFiBrnkS4oJUGm1vWx4vLyNlT3O28/Dw6FVdXb3PVu2+9tpr7ZcvX+7P87zA8zy+/PLL08nJyVXN2TcvL082YcKEiNWrV59sapvi4mLJ/Pnz/TQaTVFLs1HPkxAiSn/99ZfnmjVrfHQ6XfbRo0ezN2zYcLRjx471zdnXYDBApVIZblY4AaCkpETy9ddfB1mTj4onIcSm9Ho9P2DAgJiuXbvGxcTEdF2yZIkPAEycODFs5syZgZe3mzZtWuiMGTOCm9r+/PnzMj8/P6O7u7sAACEhIUaVSmUAgMzMTI9evXrFdunSpatarY4rKyvj58yZ45+cnNy5f//+MQMHDuxy5MgReXR0dDcAmDNnjv+wYcM69e3bt0tUVFT36dOnhwDA9OnTw8+ePauIjY3t+sILL4S35HXSaTshxKY8PDzMWq32uJ+fn/nChQvSfv36xT7xxBPlY8aMKZ06dWrk66+/XgQAK1as8F2zZs3RprYfNWpUxcyZM0NVKlX3hISEitGjR5empKRU1tbWcmPGjOn03XffnUhKSqouLS3lvby8zABw+PBhj4MHDx4ODg42HTlyRH51roMHD3rqdLrDXl5e5l69enW9//779bNmzTo3cuRI99zc3OyWvk4qnoQQmzKbzdzUqVPDt2/f7sXzPAoLC+Xnzp2TDho0qKakpESal5cnu3DhglSpVJo6d+5sqKura3T7yMhI46FDh7JXr17tvW7dOu/U1NROM2bMONe/f//qoKAgQ1JSUjUA+Pn5mS+3nZiYWBEcHGxqLFdCQkJF+/btTQCQkpJStnHjRq/HHnus3NrXScWTEGJT8+bN8yspKZHqdLochUIhhIWFqWtqangAuO+++8qWLFniW1BQIHvwwQdLb7W9VCrFyJEjL40cOfJSfHx8zeLFi/379+9f3VTbHh4e5qae4zjupt+3FF3zJITYlF6vlwQEBBgUCoWwcuVK7/z8/Cunz2PHji1dvny536pVq3zHjRtXdrPtDxw4oNDpdIrL++7bt889PDy8Pj4+vrawsFCWmZnpAQBlZWW8wWC4Za7Nmze3u3jxoqSyspL7/ffffZKSkiqVSqWpqqrKqjpIPU9CXFBzhxbZksFggFwuF5599tnSe+65p3NMTEzX+Pj46g4dOtRe3qZPnz61VVVVfHBwcH1UVJQBAJravqKiQjJ58uTIiooKiUQiEVQqVd3ChQtPu7m5Cd99992JyZMnR9bW1vJubm7mTZs2Hb1Vvvj4+Kr77ruvU0FBgfzhhx8uGTx4cDUA9O7duzI6OrpbcnKyft68eeea+3o5WredEOd34MCBvB49ehSzzLBt2zb3559/XqXT6XJY5mjMnDlz/Hfv3u25aNGiMy3Z78CBAwE9evRQNfYc9TwJIa324YcfBs6bNy/oo48+Oss6i6NQz5MQFyCGnqcrulnPkz4wIoQQK9Bpu4ipNFoJgM4AIgEEN/LlD0AOy/+jpOHPy3+vA6AHUH7dnyUATgE4AeBEXkZKi+/pJYRQ8RQNlUYbDcvcgV0BdGv46gJAcbP9bNBuBYCTsBTTAwB2ANiZl5FSbs92CXF2VDwZaOhR9gaQBCARwEBYepEstAPQs+HroYbHBJVGewyWQroDwJa8jJT9LMIRIlZUPB1EpdEGARgFIAWWoqlkGujmOAAxDV/jAECl0Z4H8DsALYC/8jJSmjUtGGEkXWnTKemQrr/luFGJRNI7Ojq6xmQycZ07d65ZunRpnre3d6N3/Bw5ckS+YcMGrwkTJpQC1g8lYok+MLIjlUYbotJo01Qa7QYA+QDmwbIeipgLZ1PCADwH4FcAJSqNdnXDa7NqOi/iehQKhTk3Nzf72LFjh2UymTBr1qzAprY9duyY4scff/RzZD5bo56njak02nYAxgIYDcvpuCu+QSkA3NXw9YlKo10LYCGAFXkZKXVMkxFRSEhIqDx48KD71KlTQ/38/IwzZswoBIBJkyaFBQUFGX766Se/kydPusXGxnYdPXp0sa+vr6mgoECWmJgYfebMGcU999xTPnfu3HOA5d73WbNmtRcEgRs+fHj5V199dR6wTLz8zDPPFK5du1bp5uZmXrVq1fGIiAijo16jK/5iM6HSaLurNNqvAJwH8AWABLSNf18pgBEAfgRwXqXRzlZptF0ZZyIMGQwGrFmzpp1ara558cUXi3/44Qd/ADCZTPj11199n3vuuZIPPvjgfJ8+fSpzc3Oz33nnnUIAyM7O9vj1119P5uTkHP7tt998jx8/LsvLy5Olp6eHbdy48Wh2dvbhffv2eS5evNgHAGpqavgBAwZUHjlyJHvAgAGVn332WZM9XXugnmcrqDRaGSwfsqTBUizbOn8AUwFMbeiNZuRlpGxgG4k4Sl1dHR8bG9sVAPr163dpypQpxW5uboKPj49xy5Yt7hcuXJB169at+vK0cNdLSEio8Pf3NwFA586da0+cOKEoKiqS9u/f/1JoaKgRAB577LHSzMxMr3HjxpXLZDLh8ccf1wNA7969q/766692jnqtABVPq6g0WjmAZwG8DqBFs0+3IXcCuFOl0e4A8C8Av+ZlpNDtbC7s8jXP6x9/6qmniufPnx9QWFgoe+qpp0qa2l8ul1/5+ZBIJILBYLjpnHFSqVTgef7y32E0Gls3x1wLtYXTSptRabQylUb7AoDjsJyaU+G8tX4AfgaQrdJon2wYpkXakHHjxpVv2LBBeeDAAc+HHnpIDwBKpdJUWVl5y5+FxMTEqh07dnhfuHBBajQasWzZMr8hQ4ZU2j/1rVHPsxlUGq0UwJMA3gIQxTaN04oFsADAKyqNdnpeRsoa1oFcWjOGFjmKm5ubMHDgwAofHx+TVGopOX379q2RSCRCly5duj7xxBPFvr6+jZ7KR0VFGd55553zSUlJMZc/MBo7dmy5I/M3hSYGuQWVRpsMSy8zlnUWF7MawPS8jJQWrx1DbiTmiUFMJhO6devWddmyZSfUarVTjcagiUGsoNJoQ1Ua7f8ArAMVTnu4G8ABlUb7pUqjDWAdhtjHnj173KKiotSJiYkVzlY4b4V6ntdpOEWfDCAdgDfbNG1GKYBJeRkp37MO4qzE3PN0ZtTzbCaVRtsLwF4As0CF05H8AHyn0mh/UWm0wazDENIcVDwBqDRaTqXRvgJgOwA16zxt2CgAh1Ua7eOsgxByK22+eKo02lAAfwL4CJa5MQlb/gD+p9Jol6s0Wqe+95m4tjZdPFUa7SgABwEMYxyF3OhBAHtUGu1trIMQ0pg2Oc6zYaD2LABTWGchN6UCsEWl0U7My0hZwDqMM1EvVNt0Sjpdqq5Z40Y9PDx6VVdX77Nl22LV5nqeKo1WCcuclFQ4nYMbgG9UGu3chttiCRGFNlU8VRptZ1g+FLqLdRbSYi8AyGq4Rk1ETK/X8wMGDIjp2rVrXExMTNclS5b4AMDEiRPDZs6ceWXmo2nTpoXOmDEjuKntxa7NFE+VRjsUliUlaMC78+oLYKtKo41hHYQ0zcPDw6zVao9nZ2fnZGZmHn3jjTfCzWYzxowZU/rzzz9f+RBwxYoVvuPHjy9tanuxaxPXPFUa7XgA8wHIWGchrRYFYLNKox2Rl5Gym3UYciOz2cxNnTo1fPv27V48z6OwsFB+7tw56aBBg2pKSkqkeXl5sgsXLkiVSqWpc+fOhrq6uka3j4yMdNjExtZw+eKp0mifBzAXlnV5iGsIBLBBpdE+kJeR8hfrMORa8+bN8yspKZHqdLochUIhhIWFqWtqangAuO+++8qWLFniW1BQIHvwwQdLb7W9mIk+YGuoNNrJsKwbRIXT9XgB0Ko02kdZByHX0uv1koCAAINCoRBWrlzpnZ+ff+WDvrFjx5YuX77cb9WqVb7jxo0ru9X2YuayPU+VRvsqgA9Z5yB2JYdlQL2U7ou/VnOHFtmSwWCAXC4Xnn322dJ77rmnc0xMTNf4+PjqDh061F7epk+fPrVVVVV8cHBwfVRUlAEAbra9mLlk8VRptG8DeJd1DuIQPICFKo32Ul5GykrWYdqy3bt3u0dERNSFhIQY9+/fn9vUdkePHr1mGsJbbS9WLnfa3nCPOhXOtkUKYGnD3KuEgQ8//DBw7NixHf/xj3+cZ53FUVxqSrqGT9W/BV3jbKsqAQzPy0jZwTqIo9GUdPbRJqakK34n4o5QFH8AKpxtmReAP1QaLc2MRezONYpnujI+gKtYvkkxle/GnTrOOg5hyhfAKpVG69A1vEnb4/zFM10ZAmAVAG8pZw5dJX8zcBi/Zz/jVIStSADLGlYFIMQunLt4pivlAH4DEHH5IY6Dcr5sVtzTkj+2sgtGRCAJwCesQxDX5ezvzB8B6HP9gxwHxdvSxQM6cvmZbxmfSWKQi4hDmkqj3ZeXkfI16yCOlhMbZ9Mp6eJyc245blQikfSOjo6uMZlMXOfOnWuWLl2a5+3tbb5+mro5c+b4796923PRokVnpk2bFrpkyZIAPz8/o8lk4tLT08+NGTNGb8vs9uK8Pc905b2wLNTWKI4DN1a6Lul72fuZHJxglgE7UEh5/Jo2CH9MScTalwfj5eHRAICBnfyxalICfp+cgGUTBiDK3+OGfcN93ZH73t34fbJluw9GdQcAyCU8Fj51O9ZMHYyx/f9ewv6fD6jRLbSdY15Yy3yp0mgHsA7RFigUCnNubm72sWPHDstkMmHWrFnNuu48YcKEi7m5udk//vjjiZdeekllMjW6hLvoOGfxTFeGA2jW5LgDJdlJG+TTd8hhcKllT5ujzmjGE//djns+zcKIT7OQFBOIXhE+eH9Ud0z5YT9GzNmMFfvzMSm5c6P7ny6pxog5mzFizma8+eshAMDgmADsOl2Guz/dhAd7hQEA4kK8IeE5HM6vcNhrawE5LGNAfVkHaUsSEhIqjx8/rmjJPrfddlutRCJBQUGBU5wRO0XIa6QrJQC+h2Wtm2ZR8RcH7FRMPJBUNztKDy8fu2UToep6y7u4VMJBKuEhABAAeLtZ/uvbuUlxsaL57ytGkwB3mQQyngfXMChs2h1d8OYvOhsnt6lwWOY4oPvgHcBgMGDNmjXt7rzzzgoAqKur42NjY7tefl6v10vuuOOOG07N169f78nzvBASEiLq2ZQuc77iCbwDILGlO/lwVT12KNJO3FH/UdVZISjMDrlEieeAVZMSEOXvicXbTmP/2XJolh/EgidvR63RhMpaIx74svHP1iL83KGdnIDKWiP+vfYIduWVIet4MR64LQy/pA3EvMyTGB4XhMP5ehReEn3H/hGVRpual5GykHUQV3V1kezXr9+lKVOmFAN/n85f3u7yNc/L38+dOzd46dKl/p6enqZFixad5HnnOCF2ruKZrkwC8Ka1u7txhk4b5S9ffKj+H0f2C5272DCZaJkFYMSczWjnJsW8cX0QE+yFZxI64qlvd2H/2XI8P7gj3hoZB83ya3uOhRV1GJixHuXVBnQPa4f/jOuDO2dvQmWdEVN+2A8AkPIcFj3TF88t3I23UuIQ6uOOn/eew185hQxeabN8qtJo1+dlpJxlHcQVXV8km2vChAkX33333Yv2yGRPzlHiASBdqYBlQuNWZZZwQvAv8hmhI/gde20TzDlU1Bqx7WQxhnQJQlyIN/afLQcArDqQj96RN14OrDeZUV5tAAAcOl+BM6XV6BDgec024wZE4ee959Er0heXao146fu9eC6xo91fSysoYfkZIqTVnKnn+SqAxj/ZaCGOg/cXsk/VHxkf2/Kl6f5BtjimGPl5ymE0mVFRa4RCyiOhcyDmZp6At5sMHQI8caq4CgnRgTheVNnovuXV9TALltN3lb8nzpRWX3m+nbsUybFBGP/NTgyPC4ZZECAAUMgkDnyFVrlTpdE+5eqrcTZnaBFpHeeYGCRdqQKQDcDd1odebkrcON3w4hBbH1cMYtt7Y9ajPcBzHHiOg1aXjznrjuOubsF4+Y4YCAKgrzHg1Z8O4GxpDYbHBUEd7oPZfx7F3d3bY9odMTCazDALwOy/jmLdVafjb4+Mw5/ZF7H9ZCkUUh7/Hd8H7ZVu+G7HGSzcmsfuRTdPIYCYvIwUpxhP2Bw0MYh93GxiEGcpnisA3Gevw+8xR296pP6dQWbwou82EZuZnZeRMo11CFuh4mkfzj2rUrpyJOxYOAGgN39scJZiyh431NXYsx0iKi+pNFpaSZVYTdzFM13pBuBTRzQVxpX03amYeMIP+hJHtEeYk4HufSetIO7iafmQyGEf37bjarpvV0y61IHLP+OoNglTd6k0Wrue1RDXJd7ima5sB8Dh16TknFG1Tv6qe18up8Xj1YhT+pdKoxXv7wERLTH/0EwC4MOiYZ4TAn+Uvxf1AJ+1i0X7xKFiATzMOgRxPuIc55mu9AQwlWUEjoPnx7KveqlMBVmzjY+0+HZQ4lTeUmm0y/IyUpxg6EnzfDFhvU2npEubm9zscaOLFy/2GT9+fKe9e/ce7tWrV+2RI0fkI0eOjD527NhhW2ZiTaw9zxcBBLAOwXGQTpH+kvil7JNM1lmIXalh5xEdbckPP/zgd9ttt1UuWrTIj3UWexJf8bR8wv4K6xhXGyHZmbRK/kaWBCanmO2FWOUt1gFcgV6v53ft2uW1YMGCvF9++YWKp4M9ByCYdYjrdefzErcoJu/3QG0V6yzELvqoNNq7WYdwdt9//73PkCFD9PHx8XW+vr7GrKysG2fadhHiKp7pSimA/2MdoyntubI+uxQTzwShrIh1FmIXLnPHEStLly71Gz16dBkAPPTQQ6WLFy922d6nuIoncA8sE9eKlidXG7dFMbk2hjt7inUWYnPDVRptB9YhnNXFixcl27dv905LS4sKCwtTf/755+1Xrlzp6xS3gFtBbMXzKdYBmkPGmSJWyzXKBF4n6unTSYtxAJ5lHcJZLV682PeBBx4ozc/P150/f15XUFBwMDw8vP7UqVNy1tnsQTwTg6QrAwGch+W2OacgCKh5w/jMwf+ZhvVjnYXYzAUAkXkZKU714aAYJgbp169fzKuvvlrw8MMPX1nM6v333w9au3atcuvWrd7+/v5X/k1nzpx59umnny5jk7T5nGNWpXTlVACzWcdoKUGA+b+mEZv/aRw7mHUWYjMP5GWk/Mo6REuIoXi6ImeZVckpTtmvx3Hgn5f+Pvgb2YeZgFjeiUgrPcc6ABE/cRTPdGVvAPGsY7RGsmR/0hr5a1ulMBpYZyGtdpdKo23WmuOk7RJH8XTSXuf1uvDnBm1XvKTzQrUoFzAnzSYBMJJ1iBYym81mjnUIV9Lw72lu6nmxFM8HWAewlQCu4radiokXQlBSwDoLaZVRrAO00KGioiIlFVDbMJvNXFFRkRLAoaa2Yf+BUboyHsABtiFszyjw5++rf782W1B1Yp2FWKUGQEBeRkr1LbcUgT179gRJpdL5ALpDPJ0iZ2YGcMhoND7bu3fvRtfSFsOsSnexDmAPUs4ctkr+RvmzhlcOrDff1oN1HtJi7rD8bP7COkhzNPyC0+QmDiSGdyiXvZ+Y5+DztezfsamS1dtYZyFWuZ91ACJebIunZd7OBKYZ7IzjoEiXLur/rnQBTWvnfEawDkDEi3XPcwgAl7x162ocB2689M+k72Qf0FhQ5xJIK2ySprAuni57yt6YQZLDSevl07fLYahjnYU02yDWAYg4sS6ewxm373Ad+YIBOxRpOe1QqWedhTQLFU/SKHbF03K9M4ZZ+wz5cpU9dyrSisO5onzWWcgtUfEkjWLZ81Qzbp8pN87QKVM+le/BHT/KOgu5qRi6VZM0hmXxavNjHyWc0P5X+Yz2d/M79rLOQm5qAOsARHyoeDLGcWj3lexT9QuSlVtYZyFNUrMOQMSHZfHsybBtUeE4yDTS/w38SDqXxoKKUxfWAYj4sCme6UoO9G5+DY4D94h0U9JP8vRNHMxNzuRCmKDiSW7AqufZCYAXo7ZFrQ9/dPAm+dRdbqirYZ2FXEHFk9yAVfGkuzZuIoIv7rdTkXbcFxWlrLMQAIBSpdEGsw5BxIVV8WzPqF2n0Y6rVu9QvKRXcRfOss5CAFDvk1yHiqeIyTljh3XyV9xu53JzWGch6Mg6ABEXVsWTToGaScIJgUvl70bcz2/ZzTpLG+fPOgARF+p5OgGOg9cnsi96TpX+lMU6SxsWwDoAERfqeToJjoN0qvTnxM9ln25knaWNop4nuQb1PJ3MSMmOIb/J38ySwGRknaWNoZ4nuQb1PJ1QPH8qcYti8j4P1FaxztKGUM+TXMPxxdNyd1E7mx6zXRiQuhJI2wFM3A70m2B5fOibwItbgAlZwLhfAO8mOrxjlwOa08ATP177+IP/tew/bMbfjw1+BYhNsWl8a7Tnym7fqZh4OgDlRayztBFUPMk1WPQ8bb9ip9kIrH0L+KIfMH840Pc5ILALsHUO8NUgYG4icHQ1kPRa4/tvmQP8/MK1jwV3A4y1lv1DbwMU7QCvYCCsD5CrtflLsIYXV9t1m2JSTTR3Lo91ljbAjXUAIi4siqfE5kesvAhcaFj6vb4SKDoCeIcCdZf+3kbm2fTyQacyLftdzWQApG4AxwESKSCYLD3ZjTNtHr81ZJwpco38Ne9B/KFDrLO4ONv/3BKn5ho9z6v5RAIh8cD5hmGRyW8DLx8G4h8BNnzQ/OMUHwWqi4EXNgFHVgN+HQGO/7tIiwjPCf5LZP/s9Khkw07WWVwYFU9yDfsWMkeTewKPLgZWv/53r3P9e5avhGlA3+db1nNc/frffx/9A7BqKpD4CtC+O3BiA7B3oU3jtwoHt/LwFVVvbaj/rdYnJRq8lD6UsyEBoDWnyDVYFE+TXY7KSy2FU7cUyFl54/O6pcCYZdaddncZAVzYbynOfipg2ZPA2J8txzSwn/yoHqh7MDxkz2mZbOiZfutP/3v+eu8TnR44dC4sKQ4cT0tI2AAHlLPOQMSFxWm7fcYn3v85UHwE2PbF34/5XXU7cpcRQPGxlh+XlwL9XwS2fApI3YHLl015CSBhv+S8nuf0yZFhOadlsoEAcD6Ai1rVz3wo5vhPg5OypnsEF+zMhCBQr6n1DKwDEHHhhKY+RLEXy1Al2072G9kfeHoNcPEQIDQcet27QK/xQEBny2PlZ4FVLwOXLgChvYA+TwO/TbJs+9QfQECMpWdZUwqsmAScWGd5rv+LQK0e2P+95fuHvgaC4oBjfwJ/vWPTl9FS56WS/PvDQqrreL7z9c/N/cy4268SfQDAIPUoz44bv7/Er3tfcJyH45O6BF3a3OR41iGIeDi+eAJAurISgKfjG3YdOrn86NjQYG8zx4U09rxfhXDxqy9Mcg7wvfxYnVxZeKjbM7n6dh0HgONkjkvrEvamzU3uzToEEQ9WdxhdZNSuS/jLw33fE6HB7ZsqnABQ2o4L/nY4n3v1Y4p6fVDvfR8P7r/zHwWelee3QBBouY/mq2YdgIgLFU8ns0DpveXloIBu4Lhb3qX1x+38gHP+uGFVTo+aooh+u/856PY9Gafcaop32CepyznDOgARF1bFs4BRu07t7QC/jR/7+gwExzX7k6q3x0m6mzhcaOw578pznQbueKdfr32zs+X1FXtsl9QlnWYdgIgLq3Ge1PNsATNgfjIkaPM+N7chLd23yp1TzrmfPz71V3N7DuAa28ZXf7xrwtbXURQQvy87drzMJHXv3urQjfAJ9sBdz3a78n27AHfsWHkSB9efu/JYrzsiEdPXMkSV4zn4hnjim1eywPEc7pmghsJdih2/ncSpA8UAgBEvqrHx+yOo1tfbI/LVqHiSa7AqntTzbKZajqsdFRay/7xMOtjaY2yL43vfvducGXcOSTfbLrD4YK+kza8gv/2AnUejH/U1S+TR1rbZmPKL1fjxg10ALHe9PpkxCKf2F1+zzb4/z2Dfn5YzZJXaHz2GRaKu2oj4oeE4vOk8Tu4rwshJPXDqQDFUan8Una10ROEEqHiS69A1TxEr4/nS5IiwY+dl0v6tPdYHj0v6GiQ41ZxtQwu29U3Kmtap04lftnBmo12KRnisH/TFNbhUWtvkNtG3B+PYbsuPiskkQCqXQCLjIZgFcDyHHsMisG+Nw2oaFU9yDbrmKVKnpdKzwyLD9JckvNoWx6uXce7/fIyvFpp5kwIHgY86+9egpKyXwyLPrN0EwWzT/7PoPkE4tqvp91CpjEdkN3+c2FsIADi2swAdegTgvik9seeP01AnheHIjgIYDQ4bMEDFk1yDVfG04laftmOvQp5zb3iIm4HjOtjyuIej+G47unCbW7IPL5ilnU+uGJyU9bJPaP7mTAhCq9eS5yUcVD0CcHxPYZPbqOIDcOGEHnXVllpfX2uC9ouDWDZzN4rOXoIqPgAn9hZhyNhY3PV8dwR3sO0UsdcpSpubTEOVyDVYFc8jAOoYtS1qWk+P3akhwRECx9nlnvRPRvEJNTK0eCljidnoFnv0f0mDN78iDSzcuxGCcOnWezUuqrs/is5UouZS03c8Rt8e3GTPtM8IFXb/kYfo24Nx4Xg51n2bjb4jbfo+cz3qdZIbsCme6XojgMNM2haxr3zabdYE+vcEx3nZqw0zz0lnjJPIBaDpi403ITXVtlNnfz0kYaum3rc0NxOC0OLjRPdpujACgNxNgtBoH5w6cOMk+cogd3j5KpB/tBxSOW+ZolUApHK7zhhHxZPcgFXPEwDENzEmQ68G+m/80tcnARxn9xEQp4O5Tqt7c60aHC83VPr3OvhZ0oDtM8q8K/KyIAjNupYqlfOIiPPDyX1/n7J3SwxFt8TQK9937BWIs9mlMNbfeD2z//0dsX3FSQDAsV0X0X1wGB55vQ8OrD/bmpdzK1Q8yQ3Y3NsOAOnKKQA+YdO4eJgA05jQ4K2HFYpEhzYsCMJ/55j2K6vRyxaHq/Jon6fr9lx+tUfwAHBco+NJndjYtLnJ37EOQcSFep4MVXNc1V0RoXsdXjgBgOO4N1Ilwbaa5NezukDVf9d7A3vv/fdRRW2Zq81ov5V1ACI+LHuevgBa/cmtsyrh+eKUiNDCKp7vyjLHqK3mLU9kmgfZ+rglvnG67K5Pmgwyr562PraDFaTNTW5yAhbSdrHreabry9BGryWdlElPD48Mq2JdOAHg14H8oAIfbLf1cf3LctSJW17r2S37mz0SY22LP90XkW2sAxBxYnnaDgDrGbfvcDvdFIdHhYV4GjkuinWWy94aL4k2c2h60GUrBBfu6T148/S4mKM/bufNhhP2aMPO6JSdNIp18VzDuH2H+sXLc+cz7YM6CBwXwDrL1So8Of+vUni7nQVwAMLzN/VP2vSyqsOpVZs5s+ncLXcSj42sAxBxYl08/4Stl+QQqdm+yk0zAvx6i3UZjEw1f/vxEGTZsw0OgqTD6T8SkrJeDgo/t34TBPONAznFpRTAXtYhiDix+8DosnTldgD92Iawr8lBARs3eHoMYZ3jVtzqhcpvZptKpWZEOqI9Ey+vOhLz+O6C4L49wXFKR7TZQj+lzU1+hHUIIk6se56AC5+6GwDDQ6HtNztD4QSAWjnn9eHDfLngoLMBibnes2vuoqTELa/Cv/hgJgShyhHttsCfrAMQ8RJD8VzNOoA9VHLcpTsjwg4eVcgTWGdpif2d+Ph9nbhNjmxTZqxR9jg0L2nQtjeqleXHN0EQHDJBZzP8xToAES8xnLZLABThqlUend1FieTiveEhZTU8H8s6izWkJqF+wcemPIURMSzar3YPOHeo23OnKz3D+oPj7HrT+k3sS5ubfBujtokTYN/zTNebAKxiHcNWjshkJ++KCDU4a+EEAKOEk6ePkUAAmPQAPWqKw/vunjno9t0z89xrimw+BrWZFjBqlzgJ9sXT4lvWAWxhs7vbwUfC2vuaOC6cdZbWOhHKxWyI55iOcfSuOt9pwI70/r32zc6W1+kduUBdHQC6l53cFPvTdgBIV3IATgJQMU5itR+9vba/7+/bExznxjqLrXCCYP76E9Mhr1rEs84CAEX+6v05ceMlRqmHTWbXv4llaXOTH7VzG8TJiaPnma4XACxkHcNaM/18M9/39+3rSoUTAASO498cL/ERgErWWQAgsETXc/DmV9VxuYt38qb6o3Zsik7ZyS2Jo3hafAtABN3g5hMA4YXgwMzvld5J4Dgx/VvazAV/LvLngdy+xp6Td1Chwy8/X/mK2b0LvuPHX7ON39NP/73Nb78h9vAh8EolJL6+iPpuCTr89hu8hg27sn34F59DGnTzSfRDCrb3Tcp6Obrz8eVb7bBAXT6AtTY+JnFB4jhtvyxduR7AUNYxmqMeqH84LGT3KblsIOssjvDlF8adARXo2+QGPI/ozI049djjMObnN7qJ19Ah8EtNxZknn4LvuLEwletx6c8/EfGfeTgzPhVeQ4fArVs3FH/+RbNzmTneeEo1ctvpyOGdwUlsMftRRtrc5NdtcBzi4sTWW3KK06UKntMPiwzLbiuFEwDeSJV0MAMlTT3vOaA/6s+ebbJwAkC7lBRUaH8HAAgGI3h3N3ByOWAyARIJ/MaPR8n8r1uUixfM0k6nfktMyprmG3o+KxOCucmMzeQUP4OEPbEVz+UAylmHuJl8qeRCckRYYblE0pN1Fkcq9+ICv76Lb3LV03YjRqBCq21yf87NDV4JCahYazkjrli1Ct7JwxD5zdconvcf+D4xGvrffoNQa9XSSpYF6o79kDR48yvyoMI91i5QtzVtbrI9r6USFyKu4pmurwYwh3WMphyWy4/dEx6KOp6PZp2FhT9v4/ufDsSNSxfLZPBKTkbF6qbvtPUaOhTV+/bBrLdMXG+urMTZCROQ9/AjqM3OhteQoahYsxbt330XYZ9+AveePa3KKDXVeXfP/mZIwtbXDH6lOS1doO4bqxolbZK4iqfFJwCsXtbWXtZ5uO97PDQ4yMxxbXpW8XfGStQmDuevfswrMRG12dkwlTR9xqy8Sc80YOKLKJk3F8qUFNTs3YN8zesIeCmtVTnlhiq/ngc/Txq4/e2yds1boC4fwJJWNUraFPEVT8sM81+yjnG1b9t5b50aFNBNpDP/OFS1G6ec/QBfKFw1MsJyLbPpU3beywset/fBpXU3zn0ti4qCLDgY1Tt3gXNzg2AWAEEAr7DNqC+3urKQPns/Suy3673zHlUFW9H0J6QZaXOT62zSKGkTxFc8LWYBqGYdAgDeCfDbOMvPZwA4Ts46i1js7ML3OhxlmTyEc3eH56CBuLT27wmIfB57DD6PPXble+87hqNyy1YINTU3HCto6hQUfvIpAKBCq4Xv6MfRYdkylC5eZNPMntUXo/rvem9gn70fHVPUll6/QF0+gP/atEHi8sQ1VOlq6crZAKayat4MmJ9uH5S1x90tiVUGMZMZhdoFH5vOy03oxDqLNUp9Y3WH454yGeRePQFMSZubLNpr7UScxNrzBICPYLnH2OHqONSmhIfupMLZNIOUc3t/tKReAAyss1jDryxXnbj1tZ5xOQvXAvgP6zzE+Yi3eKbrmZxKlfN82dCI8KPnZNL+jm7b2eRGcHFbunJbWOdojZCLO39Im5ts3fgo0qaJt3hapOMmA7Nt7YxUem5YZFjZJQkviokwnMHn9/KJ1XIcZp3DSgfhxHMqELbEXTzT9SUAHHKr3H6FPPfe8BB5Pcd1dER7rsLMc5K3xks8BJF8wNdC/xeXm9MmFiAktifu4mkxH8AOezbwh6fHnnEhwWFmjguyZzuu6lwg10F7O7ebdY4WWhuXm+Oy62cR+xN/8bRMVzcRdlqUbJ5Pu83/F+jfAxznbY/jtxWLhvGJZZ5w5ITFrVEDYDLrEMS5ib94AkC6fi+AubY+7GuB/hs/9/VJAMdJbX3sNofjuDdSJaGCyOcmaKCJy805wjoEcW7OUTwt3oRlobhWMwGm0aHBWb97eQ6xxfGIRYmSC1mczGezznELfwH4jHUI4vzEO0i+MenK0QC+b80hajiu+t7wkEMXpdKm56Z0kGCPYPwz4Z/wd/eHAAE/Hf0J3+V8h5d6voShEUNhhhmltaV4a/NbKKq58X3jq+FfIT4wHvsu7sNL61+68nhGYgaifaKReS4Tc/ZZxn4/H/88jpcdx/qzN94iaWufzDNuDS2FGKfrKwegjsvNOcc6CHF+ztTzBNL1/0MrhpaU8Hzx0MiwU2IonABgEkz49+5/Y9SKURijHYPHuzyOjsqOWHB4AR5a+RAeWfkIMs9mYkKPCY3u/+2hb/FG1hvXPBbjG4NaYy0eWvkQugd0h5fMCwHuAVAHqB1SOAHgrXGSOBOHAoc01jKTqHASW3Gu4mmRBqDF16tOyqRnhkeGVVXxfDc7ZLJKcU0xckpzAADVxmqc0p9CsEcwqgxVV7Zxl7pDaGJ1kh0FO67ZFgAMZgPcpG7gwEHKS2ESTEjrmYYv9zturpVKD873i3t5sRWpn+Jyc2jWJGIzzlc80/VVAB5DC27d3OmmODwqLMTDyHFR9gvWOqGeoYj1i8XB4oMAgEm9JuHPh/9ESscUfLGv+ctSnNKfQmltKZbeuxQbz25EpHckeI6/UqQdZXM3vs+RMGxyaKNNKwDQePedECs51zXPq6Ur0wB8fqvNfvXy3Pl2gF93cJyHA1JZxV3qjm/v/hb/OfgfrDuz7prnnun+DBQSBb480HjPsU9wHzzZ7clrrnle7bPkz/DutncxqvModPHrgm3527D82HKbv4bGyA1C9bcfm4qkZrB+00qJy835nXEG4mKcr+d5Wbr+CwC/3GyTT32VWW8H+PUWc+GUclLMHjIb2pPaGwonAGhPaTE8arhVxx4aMRTZJdnwkHkgwjsCr2S+gjui7oCbxDErJNfLOI+Zj/KXBMDkkAYbN48KJ7EH5y2eFs8AaHTp2SlBARvn+ygTwXESB2dqkX8M+gdO6k9iUfbf81dGekde+XtyRDJO6U+1+LhSToqxcWOx4NACKCSKK9dNJZwEMl7W+uDNpOvAd98dzWU5rMFrZYEGwxM7cd7T9svSlWoAmwG0AwAjYHw8tP32Iwp5Attgt9YrqBcW3bMIR0uPwtxwA9WcvXPwQPQDULVTQRAE5Ffl473t76GwuhBd/bvi0ZhHkb4tHQDw7d3fooOyAzykHtDX6TFj6wxszd8KABgbNxaX6i9hxYkVAIB/Df4Xon2ikXUuC7P3znbo65SYBMOC2aYTbgbEOrDZEwD6xeXmOGxiGdK2OH/xBIB05Z0AtFUcVzsyPPRIsVTSm3Ukcq0OBcLxjAWmCA5QOKC5MgAD6C4iYk/Oftpuka5fW8rzE4ZGhp2lwilOp9pznf/sxW13QFMGAA9T4ST25hrFE4DfjLKva3h+GescpGnz7+IHV7hjvx2bMAMYF5eb45i7AUib5jLFEwB0qbp3AHzFOgdpAsdxb6ZKAgSgwk4tpMXl5vxop2MTcg2XKp4NXgJAv0AiddGXC1+ayB+0w6FnxOXm2HzmLUKa4nLFU5eqMwMYA1peQbSWJ/AJhUqbTnD9cVxuzns2PB4ht+RyxRMAdKk6E4CnQFOPidabqZJOZq7VUwwKsMzNOd0WmQhpCdcYqnQT6oXq9wC8xToHudHQA+adL/5utnaGq3oAT8fl5nxny0yENJdL9jyvpkvVvQ3gFdY5yI029OD7ngyGNXcfVQC4hwonYcnle56XqReqnwUwD23gDcOZuNcJl77+xKSXmhHezF3OAxgRl5tjjw+dCGm2NlNIdKm6+QDuh3OssdNm1Cg4738/yJcIzVvg7zAsdw5R4STMtZniCQC6VN0qAH0A0C+fiOyN5nsc7HDLyUMyASTE5eacdUQmQm6lTRVPANCl6k4AGACArpeJyL8e5vvXSXGsiaeXALgrLjen3IGRCLmpNnPNszHqheqXAHwMwHFztJEmRZ8Xjry/yNSBA+QND1XCctfQopvtRwgLba7neTVdqu5zAEMA5DOOQgAcC+O6bOrObW34dheAXlQ4iVi16eIJALpU3VYAagD0SyoCX6Xwgwp88CaAQXG5OcdZ5yGkKW36tP166oXqu2AZzsR6zZ226giAJ3WpOkdMXUdIq7T5nufVdKm6NQC6AZiD5g2dIbZhAjALQE8qnMRZUM+zCeqF6v4AvgbQlXUWF7cWwHRdqu4Q6yCEtAQVz5tQL1TLAUwCoAEQwDiOq8kG8IouVfcH6yCEWIOKZzOoF6q9AUwHMA2AN+M4zq4IwDsA/tMw+xUhTomKZwuoF6oDYOmFpgFwzOLnrqMawBcAPtCl6vSswxDSWlQ8raBeqA4DMAOWOUNpgP3NFcAyr+pcXaqulHUYQmyFimcrqBeqgwE8B+B5ABGM44iNDpa7t77XperqWYchxNaoeNqAeqFaAuBeABMBDAfAsU3E1FoAs3SpurWsgxBiT1Q8bUy9UB0N4EUA4wH4M47jKAcB/ADgB12q7hTrMIQ4AhVPO1EvVEsBDAYwCpZ5RCOZBrK9o/i7YOawDkOIo1HxdBD1QvVtsBTSUbDcS+9sjAD2AFgPYJkuVbePcR5CmKLiyYB6oboDLL3Sfg1f8QCkTEPdyADLzEYbYZmIeKsuVVfJNBEhIkLFUwTUC9XuAHrj72J6Oyyn+Y6ae6AUlkk5Ln/tArBNl6qrdlD7hDgdKp4ipV6oVgBQAegEoCOAcABhDV/tAbgDUMAyWP/yn1cXWwGWVSbLAegb/rz89wJYimQugCO6VF2xfV8NIa6HiqcLUS9Uy2AppDyASl2qjmaGIsROqHgSQogVaD5PQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixAhVPQgixwv8D3pOpn/6v9WAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q2: What is the main programming language you use in the chosen project?\n",
    "langData = df[\"What is the main programming language you use in the chosen project?\"].value_counts()\n",
    "_, ax = plt.subplots()\n",
    "languages, _, _ = ax.pie(langData.values, autopct=lambda pct: \"{:.1f}%\".format(pct), textprops={\"color\": \"w\"})\n",
    "ax.legend(languages, langData.index, bbox_to_anchor=(1, 0, 0.5, 1))\n",
    "#ax.set_title(\"Main languages used in project\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q3: What is your main role in the chosen project?\n",
    "rolesData = df[\"What is your main role in the chosen project?\"].value_counts()\n",
    "_, ax = plt.subplots()\n",
    "roles, _, _ = ax.pie(rolesData.values, autopct=lambda pct: \"{:.1f}%\".format(pct), textprops={\"color\": \"w\"})\n",
    "ax.legend(roles, rolesData.index, bbox_to_anchor=(1, 0, 0.5, 1))\n",
    "#ax.set_title(\"Main roles in project\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q4: What is your level of work experience in a such or similar role?\n",
    "levelData = df[\"What is your level of work experience in a such or similar role?\"].value_counts()\n",
    "fig, ax = plt.subplots()\n",
    "plt.bar(range(1, 6), [levelData.get(i, 0) for i in range(1, 6)])\n",
    "plt.xticks([1, 3, 5], [\"Junior\", \"Regular\", \"Senior\"])\n",
    "ax.yaxis.grid(color='gray', linestyle='dashed')\n",
    "plt.ylabel('Number of respondents')\n",
    "plt.xlabel('Work experience level')\n",
    "ax.set_axisbelow(True)\n",
    "plt.box(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q5: How long (in months) is your work experience in a such or similar role in general?\n",
    "fig, ax = plt.subplots()\n",
    "plt.hist(df[\"How long (in months) is your work experience in such or similar roles in general?\"], bins=20)\n",
    "plt.xlabel('Work experience (in months)')\n",
    "plt.ylabel('Number of respondents')\n",
    "ax.yaxis.grid(color='gray', linestyle='dashed')\n",
    "ax.set_axisbelow(True)\n",
    "plt.yticks(range(5))\n",
    "plt.box(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Q6: How long (in months) is your work experience in the chosen project?\n",
    "fig, ax = plt.subplots()\n",
    "plt.hist(df[\"How long (in months) is your work experience in the chosen project?\"], bins=20)\n",
    "plt.xlabel('Work experience (in months)')\n",
    "plt.ylabel('Number of respondents')\n",
    "ax.yaxis.grid(color='gray', linestyle='dashed')\n",
    "ax.set_axisbelow(True)\n",
    "plt.yticks(range(5))\n",
    "plt.box(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# RQ1: What kinds of \"waste\" in software development are the most common?\n",
    "frequenciesDict = {}\n",
    "for col in chain(df.columns[5:10], df.columns[15:21]):\n",
    "    name = col[col.index('[')+1:-1]\n",
    "    frequenciesDict[name] = df[col].mean()\n",
    "frequenciesList = sorted(frequenciesDict.items(), key=lambda x: x[1])\n",
    "names, means = zip(*frequenciesList)\n",
    "colors = [\"C0\" if name in taskRelated else \"C1\" for name in names]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots()\n",
    "ax.barh(names, means, color=colors)\n",
    "\n",
    "ax.legend(typeLegend, [\"Task-related\", \"Information-related\"])\n",
    "ax.set_title('Average frequency by waste and category')\n",
    "plt.xticks([0,5], [\"Doesn't happen\", \"Very common\"])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                        1  2  3  4  5\n",
      "Language-specific communication issues  8  4  1  0  0\n",
      "Too frequent meetings                   7  4  1  1  0\n",
      "Focusing on unneeded tasks              5  3  4  1  0\n",
      "Wrong introduction of new team members  5  4  2  1  1\n",
      "Bad flow of information inside team     1  8  3  1  0\n",
      "Too long meetings                       4  3  4  1  1\n",
      "Poorly executed tasks                   2  4  4  3  0\n",
      "Avoiding specific tasks                 3  4  1  5  0\n",
      "Leaving tasks uncompleted               2  4  4  2  1\n",
      "Issues with documentation               2  5  2  1  3\n",
      "Unclearly defined tasks                 0  4  5  3  1\n"
     ]
    }
   ],
   "source": [
    "dfStacked = pd.DataFrame(columns=range(1,6))\n",
    "for col in chain(df.columns[5:10], df.columns[15:21]):\n",
    "    counter = Counter({i: 0 for i in range(1, 6)})\n",
    "    counter.update(df[col])\n",
    "    _, values = zip(*sorted(counter.items()))\n",
    "    \n",
    "    wasteName = col[col.index('[')+1:-1]\n",
    "    dfStacked.loc[wasteName] = values\n",
    "\n",
    "dfStacked[\"sum\"] = dfStacked[1]+dfStacked[2]*2+dfStacked[3]*3+dfStacked[4]*4+dfStacked[5]*5\n",
    "dfStacked.sort_values(by=\"sum\", inplace=True)\n",
    "dfStacked.drop(columns=[\"sum\"], inplace=True)\n",
    "\n",
    "print(dfStacked)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjcAAAD+CAYAAADGUCT7AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAABXdUlEQVR4nO3deXxU1fnH8c83hB1ENlFwCbIIKDsqIiCoddeqoNQdtVKpy09b22prragtWBdcq+KGVouKu6IgIrsohH1HBdyQTfadJM/vj3uiQ0xIAgk3mTzv1yuvzJw5y3PvDMyTc87MlZnhnHPOOZcsUuIOwDnnnHOuKHly45xzzrmk4smNc84555KKJzfOOeecSyqe3DjnnHMuqaTGHYBzrnCmTp16QGpq6jPAUfgfKM6VVVnAnIyMjN+2b99+ZdzBlDSe3DhXyqSmpj5z4IEHNq9bt+7alJQU/y4H58qgrKwsrVq1qsXy5cufAc6JO56Sxv/qc670Oapu3bobPLFxruxKSUmxunXrrieawXU5eHLjXOmT4omNcy78P+Dv47nwk+Kcc865pOLJjXOu0C644IK0WrVqtW7SpMmRccdSlL788svyxx57bNNGjRod2bhx4yPvvvvuA+KOqahs2bJFLVu2bH7EEUe0aNy48ZE333xz/bhjKioZGRk0b968Rffu3RvHHUtRatCgQcumTZu2aNasWYujjjqqedzxlCae3DjnCu2qq65a/e67734RdxxFrXz58jzwwAPfffXVV3OnTJky/9lnnz1g6tSpleKOqyhUqlTJJkyYsHDhwoXz5s6dO2/UqFH7jRo1qmrccRWFe+65p17jxo23xh1HcRg7duyiBQsWzJszZ878uGMpTfzTUs6VUmm3DmtfnP0vHXDm1LweO/300zctXLiwQrEMfGeNYj0u7lyf53EddthhOw877LCdADVr1sxq1KjR1m+++aZC+/bttxXF0C1faFmsxzb7itl5HltKSgo1atTIAtixY4cyMjIkqUjGnd+sebEeV/MF8/M8rq+++qr8iBEjatx2220/DBw4sF5Rjvv4tZ8U63Fd9+SJeR6X2zs+c+Occ7lYuHBhhXnz5lU54YQTNsUdS1HJyMigWbNmLerVq9f6hBNO2HDiiSdujjumvXXdddcd8u9///u7lJTkfDs76aSTmhx55JHN77///jpxx1KaJOerwTnn9sL69etTzj///EYDBgz4tlatWllxx1NUUlNTWbBgwbxvvvlm1rRp06pOmTKlVC+5DRkypEadOnUyunTpsiXuWIrDhAkTFsybN2/+Rx999MXTTz99wIcfflgt7phKC09unHMuwfbt23XmmWc2uuCCC9ZcccUV6+KOpzjUqVMns0uXLhvfe++9GnHHsjcmTJhQbeTIkfs3aNCgZe/evQ//7LPPqv/6179uGHdcRaVhw4Y7ARo0aJBx5plnrps0aVJS7JHaF2TmX5fhXGkyc+bMpa1bt14ddxwLFy6scNZZZzX54osv5sYdS1HJysqiR48eaTVr1sx87rnnvo07nqK0bNmy1AoVKlidOnUyN23apBNOOKHpLbfcsvyiiy5aH3dsReH999+v/sADD9QbPXr0l3HHUhQ2bNiQkpmZSc2aNbM2bNiQcsIJJzT929/+tqxnz54bEuvNnDmzTuvWrdNiCrPE8pkb51yhnX322Q07d+7cbMmSJRXr1avXauDAgUmxH2DkyJHV3n777doTJkyo3qxZsxbNmjVr8eqrr5bq2Y1s3377bfkuXboc0bRp0xZt27Zt0b179w3Jktgko++++y61Y8eOzY444ogW7dq1a37KKaesy5nYuLz5zI1zpUxJmblxzsXPZ25y5zM3zjnnnEsqntw455xzLql4cuNc6ZOVlZVVNN++5pwrtcL/A0nzVQVFyZMb50qfOatWrarhCY5zZVdWVpZWrVpVA5gTdywlkV9+wblSJiMj47fLly9/Zvny5Ufhf6A4V1ZlAXMyMjJ+G3cgJZF/Wso555xzScX/6nPOOedcUvHkxjnnnHNJxZMb55xzziUVT26cc845l1Q8uXHOOedcUvHkxjnnnHNJxZMb55xzziUVT26cc845l1T8G4qdi9udNfybNEuAlg0PjTsEt4+81j8j7hBKhU+6PV6s/V/35InFdgkZT26cc3tPKdBnLGxcBv/rFXc0rgCG9xjOlp1byLRMMrMy+c2w38QdUpmjChU47KX/ogoVULlUNnw0gtWPPhZ3WIV24mXNOKxlHbZu3MErd0+OOxzAk5sSSVIa8L6ZHZVQdiewyczu34P+xgC3mFl6EcS2N3GkkeO48qh3H3AG8AHwFbDFzF4sfLS/6HdwGP/1HOW9gY/MbNke9Hkne3g+kkrHvrB6IVSsHnckrhCuGnEV67avizuMMst27ODr3ldiW7ZAaippL7/EpnHj2TZzZtyhFcr8ScuZNeY7Tu7dIu5QfuLJjSswSfvq9dIHqGVmmftovN5EV9YtdHLjgP3qQ5NTYfz9cNx1cUfjXKliW7YAoNRUlFoeSuH1Hn/4ch3Va1eKO4xd+IbiUkjSGEn3SposaZGkLqG8nKT7Jc2RNEvSDbm0PUXSJEnTJA2VVC2U3yFpSmg7SJISxnpIUjrwfwn9NJI0LeF+k8T7CeXtJc2UNBO4LqG8nKT7wpizJP0ulL8LVAOmSuol6U5JtxTguHPrS5Iek7RQ0sfAAbnE1xPoALwsaYakyrs5FzdKmhfGeCWXvq6R9GHoY7d1k8ppA2DkHWBZcUfiCsHMeOpXT/HqWa/Ss0nPuMMpu1JSaPjWmzSdOIFNn37Ktlmz4o4oKXhyU3qlmtkxwE3AP0JZHyANaGNmrYCXExtIqgPcDpxsZu2AdOAP4eHHzOzosGRUGTgroWkFM+tgZg9kF5jZV8B6SW1C0ZXA87nE+Txwg5m1zlF+NbDezI4GjgaukdTQzM4BtppZGzN7tYDHnWtfwHnAEUAL4HKgU87OwhJVOnBJGHPrbs7FrUDbcG6vTexH0vWh3rmhjzzrhvp9JKVLSh80dUcuh1lKND0VNq+CH2bEHYkrpCuGX0Gv93vR9+O+/KbZb2hfr33cIZVNWVksOe98vujWncqtWlKxSZO4I0oKntyUTHnNSyaWvxl+TyVKaABOBp4yswwAM1uTo31Hojf6iZJmAFcAh4XHukv6XNJs4ETgyIR2uSUZAM8AV0oqB/QC/pf4oKT9gf3NbFwo+m/Cw6cAl4c4PgdqAwX5V53bcefVV1dgiJllhv00nxSgf8j7XMwimuG5FEj8uMXlwOlATzPbnk9dAMxsUEgYO/RpX6GAYZVAh3SEI06Hm2ZBz+egYVc4f1DcUbkCWLllJQBrtq1h1DejOKrObrfCuWKWtXEjWz6fTNUuneMOJSl4clMy/QjUzFFWC1idcD/7TTSTgu+dEjAyzFC0MbMWZna1pErAf4jenFsCTwOJC6ib8+jvDaI39bOAqWb2YwHjyI7lhoRYGprZRwVol9tx72lfvwxq9+fiTOBxoB0wJWEP0myiROvghK7yqptcRvWDB1vAQ63g9atgyTh4s0/cUbl8VE6tTJXUKj/d7lS/E1+u/TLmqMqecjVrklI92oSvihWp2uk4dixeEnNUycGTmxLIzDYBP0g6EUBSLeA0YEI+TUcCv8t+Iw3tEn0GHC+pcXi8qqSm/PzmvTrswSnQAryZbQNGAE+Qy5KUma0D1knK/lPkkoSHRwB9JZUPsTSVVLUg4+Yir77GAb3CnpyDgO55tN8IZH/MJ9dzISkFOMTMRgN/AWoQ7Q0CmA78DnhXUv186joXu9qVavPi6S/y+tmv878z/8e478YxcdnEuMMqc1Lr1uWwFwbT8J23SRs6lM2fTmLTmDFxh1Vov7r6SHr8uT37H1iFK/p3onmng+IOyT8tVYJdDjwu6cFwv1/Y57I7zwBNgVmSdhLNOvz0pQlmtkrRx56HSKoYim83s0WSnib6xNByYEoh4nyZaG9LXjMlVwLPSbIcdZ4hmu2YFjbsrgLOLcS4ifLq6y2iZaV5wDfApDzaDwaelLQVOI7ovOU8F+WAlyTVIJopesTM1oW9xpjZhLDxeRjRMtkv6u7hsZUeSydEP67E+27Td/R8zzcRx237okUsOb9H3GHstZHPzo07hF+QlcKPnbmSI7yh1zCzv8cdi3POOQc+c+P2gqS3gEZEsyPOOedcieAzN84555xLKr6h2DnnnHNJxZMb55xzziUVT26cc845l1Q8uXHOOedcUvHkxjnnnHNJxZMb55xzziUVT26cc845l1T8S/yci1narcNK/ZdNLa10cdwhuH2kZcND4w5hr73WP6PYx/ik2+PFPkZpd92TJ6q4+vbkxrkkdVCNSjx4YRvqVKuAAUMmf8PzE5fGHVZyuGkWbN8ElglZmTCoW9wRlXr1qtTjX53/Re3KtTGM1xe9zsvzX441poP+eQ/VunUj48c1LDnnnFhj2VPlUlM475Z2lEsVKSniq2mrmPx+8l953JObYiBpk5mV+KtAS7oLGGdmH0u6CRhkZlvCY4U+BklLgQ5mtrrIgy1CkvYHLjaz/xSmnqT6RBfBLBVXHMzIMu4ZNo+5yzZQtUI53ruhM+O/WM2XKzfFHVpyeOEs2LIm7iiSRqZlcn/6/cxfM58qqVV49axXmbRsEovXL44tpnVvvc3al//HQQMGxBbD3srMyOKdgdPZuT2TlBRx/p/a8fXcH1mxZEPcoRUr33NThpnZHWb2cbh7E1AlxnD2pf2B3xe2npktKy2JDcCqjduZuyz6D2zzjky+WrWJA/erFHNUzuVu9dbVzF8zH4AtGVtYsn4J9arUizWmrenpZK5fF2sMRWHn9kwAUsqJlHIpUOoXwvPnyU0xknSQpHGSZkiaI6mLpHKSBof7syXdHOqOkdQh3K4TZkEI9e+TNEXSLEm/y6vvHGMfLenNcPvXkrZKqiCpkqTFoXywpJ6SbgTqA6MljU7o45+SZkr6TNIv/peRVFvSR5LmSnoGUMJjfwhxzQmzQtnll4fjmCnpv4lxJNTZFH53kzRW0juSFksaIOkSSZPDuWsU6tWV9EY4R1MkHR/K75T0XDi3i8NxAgwAGoVzd5+kapJGSZoW+v11HvXSJM0JfVeS9HyoP11S91DeW9KbkoZL+kLSvwv8gilGB9esTIv6NZjx7bq4Q0kOBlz2NvQZC+17xxxM8qlftT7NajVj1upZcYeSFCTo9bejueq+znw7fw0rlib3rA34slRxuxgYYWb/lFSOaGakDdDAzI6Cn5Y+dudqYL2ZHS2pIjBR0kfA+bn0nWh6GAugCzAHOJroOf88saKZPSLpD0D3hCWlqsBnZva38AZ9DXBPjjH+AUwws7sknRliRVJ74ErgWKKE53NJY4EdwO1AJzNbLalWPscO0BpoDqwBFgPPmNkxkv4PuIFoxulhYKCZTZB0KDAitAFoBnQHqgMLJT0B3AocZWZtQrypwHlmtkFSHeAzSe/mUi8tIa7rolNnLSU1Az6S1DQ81gZoC2wPYz5qZt8mHpSkPkAfgFqnXk/1NqcV4FTsmSoVyvHEJe256715bNpe/Bspy4TnToWNP0DVOlGSs3oRfP1p3FElhcqplRnYfSD3TrmXzTs3xx1OUjCDV/85hQqVUzn92pbUql+VNcuS+9x6clO8pgDPSSoPvG1mM8KsyeGSHgWGAR/l08cpQKuEmY0aQJPc+k5sZGYZkr6S1Bw4BngQ6AqUA8YXIPYdwPvh9lTgV7nU6UqUZGFmwyStDeWdgbfMbDNAmEHqQvT37tDsBMrMCrJhYYqZ/RD6+Yqfz9dsoqQF4GSghfTTxNF+krL3Cw0zs+3AdkkrgdzmuQX8S1JXIAtokEe9RJ2BR8NxLJD0NZCd3Iwys/Uh5nnAYcAuyY2ZDQIGQfF+Wio1RTx5aXvenvE9I+YuL65hyp6NP0S/N6+GBe9Dg/ae3BSBVKUysNtAhi0exqhvRsUdTtLZsTWD7xeu5dAjayV9cuPLUsXIzMYRJQDfA4MlXW5ma4lmI8YA1wLPhOoZ/Px8JG6MEHCDmbUJPw3N7KPc+s4lhHHA6cBO4GOiN+TOFCy52Wlm2W+6mRRvIvzTsUtKASokPLY94XZWwv2shJhSgI4J56iBmW3KpX1ex3EJUBdoH2ZpVrDrc1BYBRlzn7i3Zyu+XLmJZyck/6cj9pnyVaBCtZ9vNzoRVs6LN6Yk0e/4fixev5gX570YdyhJo1K18lSoHP0XVK58Coc0r8Xa5Vtijqr4eXJTjCQdBqwws6eJkph2YdkjxczeIFqiaReqLwXah9uJm1ZHAH3DDA2SmkqqmlvfuYQwnmjZZpKZrQJqA0cQLVHltJFo6aYwxhEtvSHpdKBmwrjnSqoiqSpwXij7BLhAUu3QJntZaik/H/s5QPlCxvER0RIVod82+dTPeaw1gJVmtjPsnTksj3qJxhMlRYTlqEOBhYWMu1h1OKwmPdodzHGNavPBjZ354MbOdDuibtxhlX7VDoCrhsO1E+CaT2DRR/ClzzLsrbYHtOWcRudw7IHHMvTsoQw9eyhdGnTJv2Exqv/A/aQNeYWKDdNoPGY0NXr0iDWePVG1RgXOvbktvW4/hgtu7cC389fw9ewf4w6r2PmyVPHqBvxJ0k5gE3A50ZLH82GGAuC28Pt+4LWwF2NYQh/PAGnANEXrLquAc/PoO6fPiZZXxoX7s4ADE2ZkEg0ChktaZmbdc3k8N/2AIZLmAp8C3wCY2TRJg4HJ2cdgZtMh2qQMjJWUSbQvqDfwNPCOpJnAcKCw86U3Ao9LmkX0mh5HNCuWKzP7UdLEsDn4Q+Be4D1Js4F0YEEe9RK/les/wBOhTQbQ28y2JyyNxS7967Wk3Tos/4qucNYuhSc7xx1F0pm+cjotX2gZdxi7WPbHW+IOYa/9+P1mXvvXlLjD2OeU+/ucc84551zp5MtSzjnnnEsqntw455xzLql4cuOcc865pOLJjXPOOeeSiic3zjnnnEsqntw455xzLql4cuOcc865pOLJjXPOOeeSiic3zjnnnEsqfvkF52JWnFcF31eWVro47hAc0LLhoXGH4ILX+mfEHcJe+6Tb4/lX2gvXPXlisV2vxpMb55LUQTUq8eCFbahTrQIGDJn8Dc9PXBp3WCWXUqDPWNi4DP7XK+5oyqwUpfDKma+wcstKrv/k+rjDKXFSDzyQ+vcOILV2bTBY+9prrP3vf2ON6cTLmnFYyzps3biDV+6enH+DfcCXpYqIpE3F2Pe1knK7MOae9HWTpCp72HawpJ751yxdJHWT9H4+ddpIOmMP+h4jqcOeR7fnMrKMe4bN41cDx3He4xO5rONhND6gWhyhlA4d+8LqEnVh9zLp0uaXsmT9krjDKLkyM1l5779ZfNbZLP1NL2pecjEVGjWKNaT5k5bz3qMzYo0hJ09uSgEze9LMXiyi7m4C9ii5KePaAIVObuK0auN25i7bAMDmHZl8tWoTB+5XKeaoSqj96kOTU2FaUf0zc3uiXpV6dDm4C2988UbcoZRYGatWsW3ePACyNm9hx1dfUb5evVhj+uHLdWzfUrKW4Ty5KUaSGkkaLmmqpPGSmoXysyV9Lmm6pI8l1ZOUImmppP0T2n8RHrtT0i2hbIykeyVNlrRIUpdQXkXSa5LmSXor9N8hRzw3AvWB0ZJGh7InJKVLmiupX0LdAaGvWZLuz+XY7g4zOeUKUPen+MP9OZLSws98SU+H8T+SVDnUaRzOzUxJ08K5lKT7QvvZknqFut0kjZX0jqTFIZ5LwjmaLalRqDdY0pPheBdJOiuXWKtKei60nS7p15IqAHcBvSTNkNQrt3qhfWVJr4TjeguoXLBXS/E6uGZlWtSvwYxv18UdSsl02gAYeQdYVtyRlGl/PvrPDEwfSJY/DwVSvkF9KjVvztaZM+MOpcTx5KZ4DQJuMLP2wC3Af0L5BKCjmbUFXgH+bGZZwDvAeQCSjgW+NrMVufSbambHEM3C/COU/R5Ya2YtgL8D7XM2MrNHgGVAdzPrHor/ZmYdgFbACZJaSaod4jjSzFoB9yT2I+k+oC5wJbD/7uoWQBPgcTM7ElgH9AjlL4fy1kAn4AfgfKIZlNbAycB9kg4K9VsD1wLNgcuApuEcPQPckDBeGnAMcCbwpKScUxl/Az4JbbsD9wHlgTuAV82sjZm9mls9SVWBvsAWM2tO9Nz84nkAkNQnJFnpG2cML8TpKrwqFcrxxCXtueu9eWzaXrL+uioRmp4Km1fBDzPijqRM63pwV9ZsW8O8NfPiDqVUUJUqNHjkEVb0H0DW5s1xh1Pi+IbiYiKpGtGb8lDppw3hFcPvg4FXwxtzBSB7gflVojfR54HfhPu5eTP8nkr0Zg3QGXgYwMzmSJpVwFAvlNSH6LVwENACmAdsA54Ne1ES96P8HfjczPqE41y/m7oFscTMZiQej6TqQAMzeyscz7YwVmdgiJllAiskjQWOBjYAU8zsh1DvK+Cj0OdsouQj22shkfxC0mKgWY54TgHOSZhpqgTk9hGUvOp1BR4Jcc/K63kws0FEyW+xfloqNUU8eWl73p7xPSPmLi+uYUq3QzrCEadDk19BaiWoWB3OHwRv9ok7sjKl7QFt6X5Id7oc3IWK5SpStXxV+nfuz20Tbos7tJInNZWDH3mYDe+9x8aRI+OOpkTy5Kb4pADrzKxNLo89CjxoZu9K6gbcGconAY0l1QXOJe9ZkO3hdyZ78RxKakg0o3S0ma2VNBioZGYZko4BTgJ6AtcDJ4ZmU4D2kmqZ2Zp86mbLYNdZwsTZku0JtzPZ82WcxH6yEu5nses5yplI5LwvoIeZ7bKzNMykFaReYWIudvf2bMWXKzfx7ATfoJmnUf2iH4C0ztDpBk9sYvDwtId5eNrDAHSo14HeR/b2xCYPB91zDzu+WsyawS/EHUqJ5ctSxcTMNgBLJF0AEPaLtA4P1wC+D7evSGhjwFvAg8B8M/uxEENOBC4MY7UAWuZRbyNQPdzeD9gMrJdUDzg9tK8G1DCzD4CbiZZ8sg0HBgDDJFXPp262pUC70Hc7oOHuDsTMNgLfSTo3tKmo6BNe44n2vZQLCWBXoLCfO7xA0f6mRsDhQM6Px4wAblDIUiS1DeWJ52139cYBF4eyo4iW+2LR4bCa9Gh3MMc1qs0HN3bmgxs70+2IunGF45wrApXbtWP/c39NlY7H0vCtN2n41ptU7do11ph+dfWR9Phze/Y/sApX9O9E804H5d+omPnMTdGpIum7hPsPApcAT0i6nWjfxivATKKZmqGS1gKfsOub/atEsyO9Czn+f4AXJM0DFgBzgfW51BsEDJe0zMy6S5oe6n9LlCBB9Cb+TtiPIuAPiR2Y2dCwdPQu0Rt5nnWDN4DLJc0FPgcWFeB4LgOeknQXsBO4gCjxO47oHBrRXqXlChu1C+gbooRoP+BaM9uWY7blbuAhYJakFKIlw7OA0cCtkmYA/XdT7wngeUnzgflES22xSP96LWm3Dotr+NJp6YTox8UqfUU66SvS4w6jRNo6bRrzmzWPO4xdjHx2btwh/IKiyQJX2kkqB5QPb9aNgI+BI8xsR8yhlRhh2e19M3s97licc84VH5+5SR5ViD7iXZ5oBuX3ntg455wri3zmxjnnnHNJxTcUO+eccy6peHLjnHPOuaTiyY1zzjnnkoonN84555xLKp7cOOeccy6peHLjnHPOuaTiyY1zzjnnkop/iZ9zMSvOq4IXVsXUFF793XFUTE2hXIr4cPYPDPz4i7jDAmBppYvjDmHvKAX6jIWNy+B/veKOZo+1bHhogerd1ekuuh7clTXb1nD+u+cXaozX+mfsSWilUqNRH5O1eTNkZmKZmSzteUHcIe0zzRfML7YrDfvMTSki6VxJVshrKeXs4wNJ++dSfqekW8LtuySdvBeh7hOSngkXCUXSBZLmSxotqYOkRwrRz03hwpx7EsNgST33pG1JtD0ji4uf/ozTHx7PGQ+P54SmdWl7yP5xh5UcOvaF1Tmv05q83vnqHfp+3DfuMEqFby6/giXnnV+mEpvi5slN6XIRMCH83iNmdoaZrcunzh1m9vGejrGvmNlvzWxeuHs1cI2ZdTezdDO7sRBd3UR0+QoHbNmRCUBqOZFaLoUSM61Umu1XH5qcCtNejDuSfWbqiqms357btXudK36e3JQSkqoBnYnexH8Tyk6TNDShTjdJ74fbF0maLWmOpHsT6iyVVCfc/pukRZImAEck1PlpNiLU7ydpWuivWSivK2mkpLlhBuXr7H4T+ikX+poT2t4cysdIeljSjPDYMaG8qqTnJE2WNF3SrxP6uT/UnSXphoR+Oki6I5ybZyXdl+M8VJP0fBh/lqQeOWK8EahPdF2u0aHsCUnp4dj6JdQdIGle6Of+XJ6ju8PxlsuvbkmWIvjgxs5Mvf1XTPhiNTO+XRd3SKXfaQNg5B1gWXFH4koaMw599lnS3nid/S/0mZui4ntuSo9fA8PNbJGkHyW1J7ry9yBJVc1sM9ALeEVSfeBeoD2wFvhI0rlm9nZ2Z6H9b4A2RK+DacDUPMZebWbtJP0euAX4LfAP4BMz6y/pNKKkK6c2QAMzOyqMuX/CY1XMrI2krsBzwFHA30KfV4W6kyV9DFwOpAFtzCxDUq3EQczsLkknAreYWbqkbgkP/x1Yb2YtQww1c7R9RNIfgO5mtjoU/83M1oQrrY+S1Ar4HjgPaGZmlnNpT9J9QHXgSqDW7uqWdFkGZzwygf0qpfLUZR1oWq8ai1Zsijus0qvpqbB5FfwwA9I6xx2NK2G+vvgSMlaupFytWhz63LNsX7yErenpcYdV6vnMTelxEfBKuP0KcJGZZQDDgbMlpQJnAu8ARwNjzGxVqPMy0DVHf12At8xsi5ltAN7dzdhvht9TiZIMiGZKXgEws+FESVROi4HDJT0aEqANCY8NCW3HAfuFBOAU4FZJM4AxQCXgUOBk4KlwLJjZmt3EmtPJwOPZd8wstzhzulDSNGA6cCTQAlgPbCOaHTof2JJQ/+9ADTO71qIr0e6uLgCS+oTZofSNM4YX4nD2nQ3bMpi0eDUnND0g7lBKt0M6whGnw02zoOdz0LArnD8o7qhcCZGxciUAmWvWsPHjj6ncqmXMESUHT25KgTBTcSLwjKSlwJ+I3oBFlGBcGB5PN7ONxRDC9vA7k0LM9oVEojVRonIt8EziwzmrAwJ6mFmb8HOomc3f46j3gKSGRLNTJ5lZK2AYUCkkVscArwNnESWV2aYA7bNnlPKpS6gzyMw6mFmH6m1OK85DKpRaVSuwX6XoKa6YmkLnxnX5apXP2uyVUf3gwRbwUCt4/SpYMg7e7BN3VK4EUOXKpFSt8tPtqscfz/ZFJePTiaWdJzelQ0/gv2Z2mJmlmdkhwBKi2ZexQDvgGn6e2ZkMnCCpTlhauSjUSzQOOFdSZUnVgbMLGdNEoqQKSacANXNWCHtwUszsDeD2EGe2XqFOZ6Jlo/XACOCGkLQhqW2oOxL4XZidyk72CmokcF1CTL+IE9hItKQEsB+wGVgvqR5wemhXjWh25gPgZqKkLdtwYAAwTFL1fOqWaAdUr8iQPh358P+68O71nZnw5So+WbAy7rBcKXRv13t56YyXSKuRxsc9P+a8xufFHVKJk1q7Noe9/DIN336Lhq+9xqYxY9k8YULcYSUF33NTOlxEtIcm0RtES1PjwubZ3sAVAGb2g6RbgdFEsyHDzOydxMZmNk3Sq8BMYCXR7ENh9AOGSLoMmAQsJ0oSEjUAnpeUnUTflvDYNknTgfLAVaHsbuAhYFZos4Ro5uMZoGko3wk8DTxWwDjvAR6XNIdo5qkfPy+zZRsEDJe0zMy6h7gWAN8SJXEQJT/vSKpEdE7/kNiBmQ0NSeK7wMW7q1uSLVi+kTMf8f9ci83SCdFPGfCXcX+JO4QSb+d337HkXE/6ioOiLQLOFY6kikBm2OB7HPCEmbUpYNsxhM2/xRiic865MspnbtyeOhR4Lcyw7CBaFnPOOedi5zM3zjnnnEsqvqHYOeecc0nFkxvnnHPOJRVPbpxzzjmXVDy5cc4551xS8eTGOeecc0nFkxvnnHPOJRVPbpxzzjmXVPxL/JyLWdqtw0r9l00trXRx3CE4oGXDQ+MOwQWv9c+IO4QSr/mC+Squvj25cS5JHVSjEg9e2IY61SpgwJDJ3/D8xKVxh1VyKQX6jIWNy+B/veKOpsxKUQqvnPkKK7es5PpPro87nFJPFSpw2Ev/RRUqoHKpbPhoBKsfLeil+UovX5YqpSRlSpohaY6koZKqFEGf3cJFOEs0STcV9njzOjZJbSSdsYdxpIULcpZIGVnGPcPm8auB4zjv8Ylc1vEwGh9QLe6wSq6OfWH1wrijKPMubX4pS9YviTuMpGE7dvB17ytZcu55LD7vPKp17kyl1q3jDqvYeXJTem01szZmdhTRtZ2u3ZvOJJWmWbybgL1O5oI2wB4lNyXdqo3bmbtsAwCbd2Ty1apNHLhfpZijKqH2qw9NToVpL8YdSZlWr0o9uhzchTe+eCPuUJKKbdkCgFJTUWp5KAOXXfLkJjmMBxpLqiXpbUmzJH0mqRXAbsrvlPRfSROB/2Z3JilF0heS6ibc/zL7fkK9qpKekzRZ0nRJvw7lD0u6I9w+VdK40Ed7SWMlTZU0QtJBoU5jSR9LmilpmqRGOWdaJD0mqbekG4H6wGhJo8Njp0iaFNoOlVQtlJ8maYGkacD5OU+apArAXUCvMAvWS9Ixoa/pkj6VdESoe2Q4zhnhPDbJ0dfhoc3R+dWNw8E1K9Oifg1mfLsu7lBKptMGwMg7wLLijqRM+/PRf2Zg+kCy/HkoWikpNHzrTZpOnMCmTz9l26xZcUdU7Dy5KeXCjMvpwGygHzDdzFoBfwWy/wzNqxygBXCymV2UXWBmWcBLwCWh6GRgppmtyjH834BPzOwYoDtwn6SqwG1ECUN34BHgSqAc8CjQ08zaA88B/wz9vAw8bmatgU7AD3kdr5k9AiwDuptZd0l1gNvDMbQD0oE/SKoEPA2cDbQHDsylrx3AHcCrYRbsVWAB0MXM2obH/hWqXws8bGZtgA7Ad9n9hAToDaC3mU3ZXd2ENn0kpUtK3zhjeF6HWySqVCjHE5e056735rFpu29y/IWmp8LmVfDDjLgjKdO6HtyVNdvWMG/NvLhDST5ZWSw573y+6Nadyq1aUrFJ7H9vFbvStBThdlVZ0oxwezzwLPA50APAzD6RVFvSfkDnPMoB3jWzrbn0/xzwDvAQcBXwfC51TgHOkXRLuF8JONTM5ku6BhgH3GxmX0k6CjgKGCkJomTnB0nVgQZm9laIbxtAqFMQHYkStImhTQVgEtAMWGJmX4T+XgL6FKC/GsALYbbFgPKhfBLwN0kHA2+a2RdhvLpE5+l8M5uXV92cg5jZIGAQFO+npVJTxJOXtuftGd8zYu7y4hqmdDukIxxxOjT5FaRWgorV4fxB8GZBXi6uqLQ9oC3dD+lOl4O7ULFcRaqWr0r/zv25bcJtcYeWNLI2bmTL55Op2qUz27/4xX9LScWTm9Jra5gZ+EkhEoJEm3MrNLNvJa2QdCJwDD/P4uwyJNDDzHLbhdkS+JFoCSm77lwzOy5HzNXziCuDXWcW89osImBk4sxT6LdNHvXzczcw2szOk5QGjAEws/9J+hw4E/hA0u+AxcB64BuiBHJeXnXN7JM9jGev3NuzFV+u3MSzE3yDZp5G9Yt+ANI6Q6cbPLGJwcPTHubhaQ8D0KFeB3of2dsTmyJQrmZNLCODrI0bUcWKVO10HD8+82zcYRU7X5ZKLuMJSYikbsBqM9uwm/L8PEO0PDXUzDJzeXwEcINCViWpbfh9GPBHoC1wuqRjgYVAXUnHhTrlJR1pZhuB7ySdG8orKvok1NdAi3B/f+CkhHE3AtlJ0WfA8ZIah/ZVJTUlWl5Kk9Qo1Nsl+cmjL4hmbr4Pt3tnF0o6HFgclsXeAVqFh3YA5wGXS7o4n7r7VIfDatKj3cEc16g2H9zYmQ9u7Ey3I+rm39A5lzRS69blsBcG0/Cdt0kbOpTNn05i05gxcYdV7HzmJrncCTwnaRawBbgin/L8vEu0HJXbkhREsxwPAbMkpQBLJJ1NtER2i5ktk3Q1MBg4GugJPCKpBtFr7yFgLnAZ8JSku4CdwAVmtljSa8AcYAkwPWHcQcBwScvCvpvewBBJFcPjt5vZIkl9gGGSthAleLnNEo0Gbg1LfP2BfxMtS90ODEuodyFwmaSdwHKivTj7AZjZZklnES25bSJaJstZd59L/3otabcOy7+i+9nSCdGPi1X6inTSV6THHUZS2L5oEUvO7xF3GPucrAx8JMztGUkdgIFm1iXuWJxzzrmC8pkblytJtwJ9yX2vjXPOOVdi+cyNc84555KKbyh2zjnnXFLx5MY555xzScWTG+ecc84lFU9unHPOOZdUPLlxzjnnXFLx5MY555xzScWTG+ecc84lFf8SP+diVpxXBXcFt7TSxXGHUCq0bHho3CE44LX+GcU+xifdHi/W/q978sQ9utpzQXhy45zbaymC927ozPL127j6Bb8m0F5LrQhXfgjlKkBKKsx7B8b0jzuqpJCiFF458xVWblnJ9Z9cH3c4xe6gf95DtW7dyPhxDUvOOadYxjjxsmYc1rIOWzfu4JW7JxfLGIXly1JlmKTakmaEn+WSvk+4X2EP+hssqWdxxFqcJO0v6fcJ9+tLej3OmEqbK49vyJcrN8UdRvLI2A4vnA1Pdo5+Gp8MB3eIO6qkcGnzS1myfkncYewz6956m2+v6VOsY8yftJz3Hp1RrGMUlic3ZZiZ/WhmbcysDfAk0UUy24SfHTGHty/tD/yU3JjZMjMrdUlaXA7crxInNjuAV6Z8G3coyWXH5uh3ufLRj18qZ6/Vq1KPLgd34Y0v3og7lH1ma3o6mevXFesYP3y5ju1bin+ZrDA8uXG7kHSSpOmSZkt6TlLF3ZXvQT9LJfWTNC081iyU15U0UtJcSc9I+lpSnVz63STpvlDvY0nHSBojabGkc0KdcqHOFEmzJP0uof2fEsr7heIBQKMwY3WfpDRJc0L93pLelDRc0heS/p3Q19WSFkmaLOlpSY+F8gskzZE0U9K4vXk+SoM7zm5B/w/n49epK2JKgWvHw5++hK9Gw/dT446o1Pvz0X9mYPpAsiwr7lBcMfPkxiWqBAwGeplZS6I9WX0l5VqeVycFqL/azNoBTwC3hLJ/AJ+Y2ZHA60BeuxarJtTbCNwD/Ao4D7gr1LkaWG9mRwNHA9dIaijpFKAJcAzQBmgvqStwK/BVmLH6Uy5jtgF6AS2BXpIOkVQf+DvQETgeaJZQ/w7gVDNrDeS6yC2pj6R0SekbZwzP41BLvhObHcCPm3Yw5/sNcYeSfCwLnuwCD7aABu3ggOZxR1SqdT24K2u2rWHemnlxh+L2AU9uXKJywBIzWxTuvwB0BY7Iozwv+dV/M/yeCqSF252BVwDMbDiwNo++dwDZ2cBsYKyZ7Qy3s/s6Bbhc0gzgc6A2UVJzSviZDkwjSkia7OY4so0ys/Vmtg2YBxxGlCCNNbM1YfyhCfUnAoMlXUN0Tn/BzAaZWQcz61C9zWkFCKFk6nBYTU5ucQAT/tKdRy9qS6dGdRjYq03cYSWXbeth6fho343bY20PaEv3Q7ozvMdw7jvhPo456Bj6d/ZN2snKPy3l4rA9/M6k8K/Bnfbz+kdWdl9mliUpuy8BN5jZiMSGkk4F+pvZUznK0woYb4FiNrNrJR0LnAlMldTezH7MZ4xS6d8jFvLvEQsB6Hh4La7pcjg3vzoj3qCSQZXakJURJTapleDw7jDxobijKtUenvYwD097GIAO9TrQ+8je3DbhtpijcsXFZ25cokwgTVLjcP8yYCywMI/yvBS2PkSzHRcChOWjmoUP/ycjiJbTyof+mkqqGsqvklQtlDeQdADR8lb1Qo4xBThBUs2QVPXIfkBSIzP73MzuAFYBh+zFsbiyqPqBcMX70Hci9BkNi0fDohH5t3Muh/oP3E/akFeo2DCNxmNGU6NHj/wbFdKvrj6SHn9uz/4HVuGK/p1o3umgIh+jsHzmxiXaBlwJDA1v2FOAJ81su6RflOfViZltK0z9oB8wRNJlwCRgOVHSsSeeIVqimiZJRAnGuWb2kaTmwKSomE3ApWb2laSJYRPxh0C+31xlZt9L+hcwGVgDLADWh4fvk9SEaAZpFDBzD4+jVPls8Ro+W7wm7jCSw4q58FSXuKNIWukr0klfUTa+j2nZH2/Jv9JeGvns3GIfo7Dkn3BwJUH4NFWmmWVIOg54InxEvcSSVM3MNoUE7i3gOTN7K+64nHOurPOZG1dSHAq8JimFaNPwNTHHUxB3SjqZ6FNmHwFvxxuOc8458Jkb55xzziUZ31DsnHPOuaTiyY1zzjnnkoonN84555xLKp7cOOeccy6peHLjnHPOuaTiyY1zzjnnkoonN84555xLKv4lfs7FLO3WYcX+ZVNLK11c3EM4V2q0bHho3CGUCq/1zyjW/psvmK/i6tuTG+dKkX/3bMWJzQ7gx007OPWhcXGH4wqq4++h3eWAwYp58M7vIWN7vs1ccquQUoHBpw+mQkoFyqWUY+TSkfxn5n/iDqvQDvrnPVTr1o2MH9ew5Jxz4g4HKCXLUpIyJc2QNFPSNEmdCtn+Tkm/uHqYpLqSPpc0XVIXSUsl1Sm6yPOMp4ukueGYKud47NO9aV9cJHVLPO+SrpV0eRH0W1/S63vY9q5w+YOc5d0kvV+IftIklYqpjdenfscVz02OOwxXGNUPgmOvhUHd4D/HQUo5OKror8zsSp8dWTu4esTV9HyvJxe8ewHHNzieVnVaxR1Woa17622+vaZP3GHsolQkN8BWM2tjZq2B24D+RdTvScBsM2trZuOLqM+CuAToH45pa+IDZlaQxC3P9rkJF3bcW92An2IzsyfN7MW97dTMlplZzz1se4eZfby3MRBdQbxUJDeTl6xh/dadcYfhCiulHJSv/PPvjcvjjsiVEFszov/CU1NSSU1JxSh9l0Tamp5O5vp1cYexi9KS3CTaD1gL0VWZJY0KszmzJf06u5Kkv0laJGkCcETOTiS1Af4N/DqPGZQ/SJoTfm4KZX+SdGO4PVDSJ+H2iZJezmWMk8Ks0GxJz0mqKOm3wIXA3Xm02RR+d5M0RtLrkhZIelmRXdqHsvtCnLMl9UpoP17Su8C8cH+spHckLZY0QNIlkiaHdo1Cu7MTZrM+llRPUhpwLXBzOFddEmfDJLWR9JmkWZLeklQzlI+RdG8YY5GkLrkcb5qkOeF2b0lvShou6QtJ/w7l5SQNTjjGm0P5YEk9w+3TwnmaBpyf0H/VcO4nh2P6dc4YgAFAl3BsN4fx7pM0JRzT70Jfub7ewjEsCPEsCs/LyZImhuM4JpcxXVmx8Qf49FG4eQ78cRFs2wBffRJ3VK6ESFEKQ88eytheY/ls2WfMXj077pCSQmlJbiqHN54FwDPA3aF8G3CembUDugMPhDf79sBvgDbAGcDROTs0sxnAHcCrOWdAQvsrgWOBjsA1ktoC44HsN+gOQDVJ5UPZLhsgJFUCBgO9zKwl0f6mvmb2DPAu8CczuySf424L3AS0AA4Hjs+l/fnhOFsDJwP3STootG8H/J+ZNQ33WxMlKc2By4CmZnZMOKc3hDoTgI5m1hZ4BfizmS0FngQGhnOVc5brReAvZtYKmA38I+Gx1DDGTTnK89IG6AW0BHpJOiSUNTCzo8K5fD6xQTjXTwNnA+2BAxMe/hvwSYihezg/VXOMeSswPhzbQOBqYL2ZHU302rlGUkPyeL2FPhoDDwDNws/FQGfgFuCvOQ9SUh9J6ZLSN84YXoDT4kqtSvtDszPhoVbwwBFQoQq0ujDuqFwJkWVZXPDeBZw89GSOqnMUjfdvHHdISaG0JDfZy1LNgNOAF8ObioB/SZoFfAw0AOoRJRtvmdkWM9tAlAwURufQfrOZbQLeDH1OBdpL2g/YDkwiSnK6ECU+iY4AlpjZonD/BaBrIeOYbGbfmVkWMINo+SS3WIeYWaaZrQDG8nMyN9nMliTUnWJmP5jZduAr4KNQPjuh74OBEZJmA38CjtxdgJJqAPub2dhQlPM43wy/p+YRf06jzGy9mW0D5gGHAYuBwyU9Kuk0YEOONs2IzvUXFl3m/qWEx04BbpU0AxgDVALy+6jEKcDloc3nQG2gCXm/3gjjzw7P1dxwHMau5/YnZjbIzDqYWYfqbU7L75y40uzwbrD2a9jyI2RlwPz34JBj447KlTAbd25kyvIpHN/g+LhDSQqlJbn5iZlNAuoAdYn2ntQF2ptZG2AF0ZtXcY29E1gC9AY+JUpouhP91T6/GIZM/DhFJoX/dNvm3fSXlXA/K6HvR4HHwgzJ79j785k9RkHj/8Uxm9laolmnMUQzT88UYnwBPUJy3MbMDjWz/J4rATcktGloZh+x+9dbQc6tK4vWfwsHd4j22gA0PAFWLYw3Jlci1KxYk+rlqwNQsVxFOtbvyJL1S/Jp5Qqi1CU3kpoB5YAfgRrASjPbKak70V/5EC0RnSupsqTqRMsVhTE+tK8SljDO4+eZmfFESw3jwu1rgenhr/REC4E0SdlzjJcRzaoUtfFEyzflJNUlmjXZm4/T1AC+D7evSCjfCFTPWdnM1gNrE/bTFPlxKvoEW4qZvQHcTrTclmgB0bluFO5flPDYCOCG7OWjsLyYU85jGwH0DUuOSGoaXgd5vd72mUd+04Y3+3bi8LpVmXTbiVzY4ZB9HYIrrO+nwrx34Hfj4PeTQCkwdXDcUbkSoG6Vujx76rO8cfYbDDlzCJ8t+4xx35W+r3io/8D9pA15hYoN02g8ZjQ1esT/acDS8hdl5bBEANFf1VeYWaaiDbnvhSWUdKI3OcxsmqRXgZnASmBKYQYL7Qfzc5LwjJlND7fHE+3jmGRmmyVt45dLUpjZNklXAkMVfVppCtG+laL2FnAc0bEa0R6Z5SEJ3BN3EsW8FvgEaBjK3wNeD5tob8jR5grgSUlViJaQrtzDsfPSAHheUnYyflvig+Fc9wGGSdpC9HxkJyt3Aw8Bs0L7JcBZOfqfBWRKmkm0T+phoqWkaSEpWgWcC+T6etuXbnxlxr4e0hWFMf2jH+cSLFq7iAvfL/37r5b98RfftBI7/XLCwTnnnHOu9Cp1y1LOOeecc7vjyY1zzjnnkoonN84555xLKp7cOOeccy6peHLjnHPOuaTiyY1zzjnnkoonN84555xLKp7cOOeccy6peHLjnHPOuaRSWi6/4FzSSrt1WJn6mvAJf+nOpu0ZZGUZGVnGOY9NjDukfWZppYvjDmHvKAX6jIWNy+B/veKOZo+1bHhosfRbr0o9/tX5X9SuXBvDeH3R67w8/+ViGeu1/hkFqnfQP++hWrduZPy4hiXnnFOoMT7p9niB6p14WTMOa1mHrRt38MrdBb+04XVPnqhCBVQIu525kTRQ0k0J90dIeibh/gOS/lBcweUSzweS9s+nTm9J9fdynN6SHtuLtvUT7j8jqcXexJPPeBUlfSxphqR9+r+NpL/uy/H2FUljJHWIO45kdtGgzzjjkQllKrFJCh37wmq/onleMi2T+9Pv59x3zuWSYZfwmyN+w+E1Do81pnVvvc231/Qp1jHmT1rOe4/OKNYxCiu/ZamJQCeAcNHBOsCRCY93Aj5NbBAuElkszOwMM1uXT7XeQK7JjaRyRR1TfuOb2W/NbF4xjtc2jNPGzF4txnFyk5TJzd4ozte/c7Harz40ORWmvRh3JCXW6q2rmb9mPgBbMrawZP0S6lWpF2tMW9PTyVy/rljH+OHLdWzfUrCZpH0lv+TmU6IrTkOU1MwBNkqqKaki0JzoysljJD0kKR34P0knSZouabak50JdJC2V1E/StPBYs1BeV9JISXPDTMfXkurkDCa0ryMpTdJ8SU+HNh9JqiypJ9ABeDnMZFQObe6VNA24QNJFYew5ku5N6PtKSYskTQaOTygfHPrNvr8p4fZfQl8zJQ3IY/yfZgF2M/YmSf8M/Xwm6Rf/GiTVkvS2pFmhTitJBwAvAUeH8RrlaDMmHPvkcGxdQnk5SfdJmhL6+10of1zSOeH2W5KeC7evkvTPHH0PIFytXdHV2ZF0aRhrhqSnspNJSU9ISg/PVb8cz2f/UD9dUjtFs4NfSbo2l3OQJmlBeE4WSXpZ0smSJkr6QtIxoV7V8LqbHF6Hvw7lvcM5HBnGvl7SH0KdzyTVShjushDXnAL2+66kT4BRkg6SNC6hfZecx1KWmcF/rz6W967vzEXHHBJ3OK6gThsAI+8Ay4o7klKhftX6NKvVjFmrZ8UdSpm02+TGzJYBGZIOJZqlmQR8TpTwdABmm9mOUL2CmXUAHgcGA73MrCXRvp6+Cd2uNrN2wBNA9nXS/wF8YmZHAq8DBVkQbQI8HtqsA3qY2etAOnBJmMnYGur+GMYcB9wLnAi0IUoKzpV0ENCPKKnpDOS7jCTpdODXwLFm1hr4927GR9FS1S/GDg9XBT4L/YwDrsllyH7AdDNrRTRj8qKZrQR+C4wP432VS7tUMzsGuInoPANcDaw3s6OBo4FrJDUExgPZb8QNEs5DlxDXT8zsVmBrGPcSSc2BXsDxZtYGyAQuCdX/Fl4brYATJLVK6OqbUH880eumJ9AxHG9uGgMPAM3Cz8VEz9kt/DyT9Dei19MxQHfgPklVw2NHAeeH4/4nsMXM2hK9ti9PGKdKiOv3wHMF6Lcd0NPMTggxjQjtWwMz8jiWMqnnk59y1qMT6P38ZC4/Lo1jGtbKv5GLV9NTYfMq+GFG3JGUCpVTKzOw+0DunXIvm3dujjucMqkgn5b6lCixyU5uJiXcT1wwz14SOQJYYmaLwv0XgK4J9d4Mv6cCaeF2Z+AVADMbDqwtQFxLzGxGLn3lJju2o4ExZrbKzDKAl0NsxyaU70iovzsnA8+b2ZYQ95p86uc1NsAO4P18jqUz8N8w1idAbUn7FSDO3M73KcDlkmYQJau1iZLF8UAXRXuE5gErQuJ3HDmWH3NxEtAemBL6PQnIXmy+UNHM2XSiGcDE5PHd8Hs28LmZbTSzVcB25b6/aomZzTazLGAuMMrMLLRPPL5bQxxjgEr8nDCPThhjPfBewvjZ7QGGAJjZOGC/EMvu+h2Z8BqYAlwp6U6gpZltzHkQkvqE2ar0jTOG53KYyWvFhu0A/Lh5ByPmLqf1wfvHG5DL3yEd4YjT4aZZ0PM5aNgVzh8Ud1QlUqpSGdhtIMMWD2PUN6PiDqfMKsj+gOx9Ny2JlqW+Bf4IbACeT6hX0PR0e/idWcDx8+snu6/Ku6m7N6lzBiEJVLTvqMJe9JWXneENGvb+vOSU2/kWcIOZjchZObyJn0Y0U1MLuBDYlNsbdM6mwAtmdluO/hoSzaocbWZrJQ0mSgpyxpfFrs9pFrmfh5x1EtsnHl8PM9tl56OkYwvYHiDnJ5gsn35/eo2Z2ThJXYEzgcGSHjSzXTYqmNkgYBCUrU9LVS5fjhTB5h2ZVC5fji5N6vLIqC/iDsvlZ1S/6AcgrTN0ugHeLN5NqqVVv+P7sXj9Yl6c53uT4lTQmZuzgDVmlhn+Ot2fvP+aXwikSWoc7l8GjM1njIlEb6JIOgWoWYC48rIRqJ7HY5OJlkXqhP0gF4XYPg/ltSWVBy5IaLOUaEYC4BygfLg9kuiv8yoh7uy59bzGz2vsghpPWOaR1I1oeW9DIdonGgH0DceKpKYJyyufES1hjQtj3hJ+52Zndh/AKKBn2AeUvUfoMGA/ojf+9Yr2Ep2+hzEXxgjgBkkKsbTdgz56hbadiZbw1he033DcK8zsaeAZoiUrB9SpXoHX+3biw//rwjvXH88nC1YydtGquMNyrki0PaAt5zQ6h2MPPJahZw9l6NlD6dIg3i139R+4n7Qhr1CxYRqNx4ymRo8eRT7Gr64+kh5/bs/+B1bhiv6daN7poCIfo7AKMkMwm+hTUv/LUVbNzFbnrGxm2yRdCQxV9MmRKcCT+YzRDxgi6TKiZa/lREnCnhgMPClpKz9vhs6O7QdJtwKjif4KH2Zm7wCEJYRJRPt3ZiQ0exp4R9JMYDjhL3QzGy6pDZAuaQfwAdGej1zH393YBXQn8JykWcAW4IpCtM3pGaIlmGnhjXoVcG54bDxwipl9KelrotmbvJKbQcAsSdPCvpvbgY/CDNdO4Doz+0zSdGAB0azfvvjs793AQyG2FGAJUYJeGNtC3OWBqwrZbzfgT5J2ApvYdS9Pmfbtmq2c/nBeLydXKiydEP24X5i+cjotX2gZdxi7WPbHW/KvtJdGPju32McoLP28GhJjENGnqTLNLEPSccATYTOmc0mvLC1LlXWl/kv8kkRxfYnfvlTQL/HbGwX9Er89VZxf4ldSkpsmwGtEy2Q7gN+b2ZR4o3LOOedcaVQikhvnnHPOuaLiF850zjnnXFLx5MY555xzScWTG+ecc84lFU9unHPOOZdUPLlxzjnnXFLx5MY555xzScWTG+ecc84llaK8QKNzbg/4NxSXHf4NxQWTDN8gnAyK+1uQmy+YX2zfUOzJjXNun5rwl+5s2p5BVpaRkWWc89i+uNyY20VqRbjyQyhXAVJSYd47MKZ/3FEljRSl8MqZr7Byy0qu/+T6uMMpdgf98x6qdetGxo9rWHLOOXGHA3hys0ckZRJdPDTbuWa2tBjHuxbYYmYvFtcYpY2k3kAHMyvw/xySloY2q3OU/9XM/rWHcYwBbjGz9D1pX1ZdNOgz1m7ZGXcYZVfGdnjhbNixOUpurhoBX46E7/xlXBQubX4pS9YvoWr5qnGHsk+se+tt1r78Pw4aMCDuUH7ie272zFYza5Pws7Q4BzOzJz2xKVZ/jTsA5/a5HZuj3+XKRz9+KZ4iUa9KPboc3IU3vngj7lD2ma3p6WSuXxd3GLvw5KaISGoj6TNJsyS9JalmKG8s6WNJMyVNk9RIUjdJ7ye0fSzMRCBpgKR5oZ/7Q9mdkm4Jt8dIulfSZEmLJHUJ5VUkvRbaviXpc0kdconzJEnTJc2W9Fy4IjuSlkrqF2KcLalZLm17S3os4f77krqF25sk/TMc52eS6oXywZIekfSppMWSeia0/5OkKeFY+yWUXxqOb4akpySVC+VXhmOeDByfUL+upDdCX1MkHR/Ka0v6SNJcSc8Av1jflTQAqBzGejmUvS1pamjXJ5SVC8cyJ5yfm3P0kxIevye/umWdGfz36mN57/rOXHTMIXGHU3YpBa4dD3/6Er4aDd9PjTuipPDno//MwPSBZFlW3KGUaZ7c7JnsN8MZkt4KZS8CfzGzVkRLVv8I5S8Dj5tZa6AT8ENenUqqDZwHHBn6uSePqqlmdgxwU8I4vwfWmlkL4O9A+1z6rwQMBnqZWUuiZcm+CVVWm1k74Anglt0cf26qAp+F4xwHXJPw2EFAZ+AsYECI5RSgCXAM0AZoL6mrpOZAL+B4M2sDZAKXSDoI6EeU1HQGWiT0/zAw0MyOBnoAz4TyfwATzOxI4C3gF7sUzexWfp6JuyQUX2Vm7YEOwI3heWkDNDCzo8K5ez6hm1Si5/kLM7s9n7qE4+8jKV1S+sYZw/M6p0mp55OfctajE+j9/GQuPy6NYxrWijukssmy4Mku8GALaNAODmged0SlXteDu7Jm2xrmrZkXdyhlnic3eyZxWeo8STWA/c1sbHj8BaCrpOpEb3JvAZjZNjPbspt+1wPbgGclnQ/kVffN8HsqkBZudwZeCePMAWbl0u4IYImZLUqMM59+C2oHkD0blbP922aWZWbzgHqh7JTwMx2YBjQjSnZOIkrMpkiaEe4fDhwLjDGzVWa2A3g1of+TgcdC/XeB/SRVC8f2EoCZDQPWFvBYbpQ0E/gMOCTEtRg4XNKjkk4DNiTUfwqYY2b/DPd3V5cQzyAz62BmHaq3Oa2AYSWHFRu2A/Dj5h2MmLuc1gfvH29AZd229bB0PDQ+Oe5ISr22B7Sl+yHdGd5jOPedcB/HHHQM/Tv7Ru04eHITjwx2PfeVAMwsg2gm43WiWY68/qTfHn5nUrSbwvPrN9e4g51mPy3a52y/PeG2En73T0gSG5vZs6H8hYTyI8zsznziTgE6JrRpYGab8mmTq7DMdjJwXJiFmg5UMrO1QGtgDHAtP88OAXwKdA8zY+RTt0yrXL4cVSuU++l2lyZ1WbRiY8xRlUFVakOlGtHt1EpweHdYvWj3bVy+Hp72MCe/fjKnvXEafxr7Jyb/MJnbJtwWd1hlkic3RcDM1gNrs/e/AJcBY81sI/CdpHMBJFWUVAX4GmgR7u9PNDtBmG2oYWYfADcTvUEW1ETgwtBPC6BlLnUWAmmSGifGWYgxlgJtwv6SQ4gSsT01ArgqHDOSGkg6ABgF9Ay3kVRL0mHA58AJYR9NeeCChL4+Am7IviOpTbg5Drg4lJ0O1Mwjlp2hT4AaRMt7W8K+o46hfR0gxczeAG4H2iW0fxb4AHhNUmo+dcu0OtUr8HrfTnz4f1145/rj+WTBSsYuWhV3WGVP9QPhiveh70ToMxoWj4ZFI+KOypVS9R+4n7Qhr1CxYRqNx4ymRo8ecYfkHwUvQlcAT4bkZTFwZSi/DHhK0l3ATuACM1ss6TVgDrCEaHYAoDrwTpgBEPCHQoz/H+AFSfOABcBcomWun5jZNklXAkMlpQJTgCcLMcbEEO88YD7RctIeMbOPwv6aSZIANgGXmtk8SbcDH0lKITpn15nZZ5LuBCYB64AZCd3dCDwuaRbRa3oc0YxJP2CIpLlEsyvf5BHOIGCWpGnAVcC1kuYTJYOfhToNgOdDTAC7/DlmZg+G5cn/Eu0ryrNuWfbtmq2c/vD4uMNwK+bCU13yr+f2WPqKdNJXlI2P1i/7Y2G3aBY/mX/8LymETxSVDwlMI+Bj4IiwP8U555wrM3zmJnlUAUaH5RUBv/fExjnnXFnkMzfOOeecSyq+odg555xzScWTG+ecc84lFU9unHPOOZdUPLlxzjnnXFLx5MY555xzScWTG+ecc84lFU9unHPOOZdU/Ev8nItZ2q3D/MumXKmxtNLFcYfggJYNDy32MV7rn1Gs/TdfMF/519ozntw455LK4XWq8tjFbX+6f0itKgwcuYjnJi6NLyhXcigF+oyFjcvgf73ijqbY3dXpLroe3JU129Zw/rvnF8sYB/3zHqp160bGj2tYcs45xTJGYfmyVCkRroY9I/wsl/R9wv0Ke9Bfs9B2ergWVYkh6aZwAdJ9OeZfc9z/dF+O74rO4tWbOeORCZzxyATOenQC23ZmMmLuirjDciVFx76wemHcUewz73z1Dn0/7lusY6x7622+vaZPsY5RWJ7clBJm9qOZtTGzNkRX8h6YfX8PryF1LvC6mbU1s6+yCxWJ+3VxE9G1svalXZIbM+u0j8d3xeD4xnX4+sctfL9ua9yhuJJgv/rQ5FSY9mLckewzU1dMZf329cU6xtb0dDLXryvWMQor7jcxtxcknRRmXmZLek5Sxd2VJ7Q7gyiB6CtptKQ0SQslvQjMAQ6R9CdJUyTNktQvoe3fJC2SNEHSEEm3hPIxkjqE23UkLQ23y0m6L6Gv34XybqHN65IWSHo5JFY3AvWJLgI6OpdjXiqpf5h1SpfUTtIISV9JujahXl7xXyppcmj/VIhvAFA5lL0c6m3aXZzZ5zGUTZX0iKT3Q/kJCbNq0yVV36sn2u2xs1vX592Zy+IOw5UUpw2AkXeAZcUdiStmntyUXpWAwUAvM2tJtH+qr6RcyxMbmtkH/Dz70z0UNwH+Y2ZHAkeE+8cAbYD2krpKag/8JpSdARxdgDivBtab2dGh/jWSGobH2hIlWS2Aw4HjzewRYBnQPSG2nL4JM1jjw7H2BDoC/QAknZJH/M2BXmGcNkAmcImZ3QpsDbNgl+Qy3i/iDOf5KeB0M2sP1E2ofwtwXRijC/CLaQNJfUJylr5xxvA8DtPtjfLlxMnN6/HB7B/iDsWVBE1Phc2r4IcZcUfi9gHfUFx6lQOWmNmicP8F4DpgdB7lD+XT39dm9lm4fUr4mR7uVyNKFqoDb5nZFgBJ7xYgzlOAVpJ6hvs1Ql87gMlm9l3oawaQBkwoQJ/Z484GqpnZRmCjpO2S9t9N/K2A9sCUMPlSGVhZgPFyi3MTsNjMloQ6Q4DsReeJwINhFujN7LaJzGwQMAj801LFpdsRBzDn+/Ws3rQnq7Yu6RzSEY44HZr8ClIrQcXqcP4geLNk7RVxRcOTG5dtc8JtAf3N7KnECpJu2k37DH6eCayUo68bzGxEjr66AdsTijIp+Osxu11Wjj6yQh95xX8D8IKZ3VbAcXKOV6A4zWyApGFEs1sTJZ1qZgsKOabbS+e0rs97viTlso3qF/0ApHWGTjd4YpPEfFmq9MoE0iQ1DvcvA8YCC/MoL4wRwFWSqgFIaiDpAGAccK6kymEfydkJbZYSzYpAtEyU2FdfSeVDX00lVc1n/I1Es0R7Kq/4RwE9w20k1ZJ0WGizMzvGAloIHC4pLdz/6TOlkhqZ2WwzuxeYAjTbi2Nxe6By+XJ0blyH4XOWxx2Kc7G6t+u9vHTGS6TVSOPjnh9zXuPzinyM+g/cT9qQV6jYMI3GY0ZTo0ePIh+jsHzmpvTaBlwJDJWUSvQm+qSZbZf0i/LCdGxmH4X9KZPC8s0m4FIzmybpVWAm0XLOlIRm9wOvSeoDDEsof4ZoGWda2Ii7iuiTWrszCBguadlu9t3sSfzzJN0OfKToE2E7iZbsvg5jzpI0LY99NznH2Crp9yHOzex6Lm6S1J1oJmku8GFhj8Htna07M2l798i4w3Al1dIJ0U8Z8Jdxfyn2MZb98ZZiH6OwZObL/W7PSLoT2GRm98cdSxwkVTOzTSFpexz4wswGxh2Xc86Vdb4s5dyeuyZsMJ5LtFH6qd1Xd845ty/4zI1zzjnnkorP3DjnnHMuqXhy45xzzrmk4smNc84555KKJzfOOeecSyqe3DjnnHMuqXhy45xzzrmk4smNc84555KKX37BuZj5VcGd29XSShfHHYIDWjY8tFj7n33FbBVX357cOOfKvKs7N6TX0YdgBguXb+BPr89ie0ZW3GG50kop0GcsbFwG/+uVf/1S7q5Od9H14K6s2baG8989P+5wgL1YlpK0qSgDSXaSPpC0f7h9o6T5kl6WdI6kW2MOr1jszbFJ+muO+58WUUx3STq5KPpyyaHefhXp3SmNsx+dwKkPjSMlRZzdun7cYbnSrGNfWL0w7ij2mXe+eoe+H/eNO4xd+J6bfcTMzjCzdeHu74FfmdklZvaumQ2IMbRis5fHtktyY2adiiAkzOwOM/u4KPpyyaNciqhUvhzlUkTl8uVYsWFb3CG50mq/+tDkVJj2YtyR7DNTV0xl/fb1cYexiyJNbiSdLelzSdMlfSypXii/U9JzksZIWizpxoQ2f5e0UNIESUMk3RLKx0jqEG7XkbQ03E6TNF7StPDTKZSnSPqPpAWSRoaZkp7hsfaSxkqaKmmEpINyib2qpGGSZkqaI6lXKF8q6d+SZkuaLKlxKK8r6Q1JU8LP8aG8mqTnQ/1Zknok9FNH0pPA4cCHkm6W1FvSY6FOPUlvhRhmZh9bjjhPC8c9U9KoUFZL0tthvM8ktUo47y+E8/W1pPMTjmW4pPIJsfWXNENSuqR24Tx9JenaUKebpPcT4nhMUu+E9v1CXLMlNQvl+R5biHuqpLmS+oSyAUDlEM/LoWxT+C1J94XnaHbC89QtvGZeD6+BlyX9Yj1X0uCE18UASfPCebs/lF0Q+p4paVzO4wj335fULdw+RdKkcOxDJVXLq29XMq3YsJ2nxy/m01tPZPJfT2LjtgzGf7E67rBcaXXaABh5B5gva8apqGduJgAdzawt8Arw54THmgGnAscA/5BUXtLRQA+gNXA60KEAY6wkmvVoB/QCHgnl5wNpQAvgMuA4gPAG/ijQ08zaA88B/8yl39OAZWbW2syOAoYnPLbezFoCjwEPhbKHgYFmln0Mz4Tyv2fXN7NWwCeJg5jZtcAyoLuZDcwRwyPAWDNrDbQjutr0TyTVBZ4GeoQ6F4SH+gHTw3h/BRL/ZGgEnAicA7wEjA7HshU4M6HeN2bWBhgPDAZ6Ah1D3wWxOjwnTwC35PJ4Xsd2VXheOgA3SqptZrcCW82sjZldkqOf84E2RK+Zk4H79HOy2ha4ieg1cDhwfF7BSqoNnAccGc7bPeGhO4BTQ5zn7O6AJdUBbgdODseeDvxhN30ntu0TEsn0jTOG53zY7UP7VU7lVy3q0eXfozn2X6OoUqEc57ZpEHdYrjRqeipsXgU/zIg7kjKvqDcUHwy8Gt5sKgBLEh4bZmbbge2SVgL1iN583jGzbcA2Se8VYIzywGOS2gCZQNNQ3hkYamZZwHJJo0P5EcBRwMjwh3w54Idc+p0NPCDpXuB9Mxuf8NiQhN/ZCcnJQIuEyYH9wl/tJwO/yS40s7UFOKZsJwKXh3aZQM55vo7AODNbEuqsCeWdiRIszOwTSbUl7Rce+9DMdkqaTXTs2e+ks4mSwWzvJpRXM7ONwEZJ2xX2CuXjzfB7KlECUtBju1HSeeH2IUAT4MfdjNMZGBL6WCFpLHA0sAGYbGbfAUiaEY5vQh79rAe2Ac+GGansWamJwGBJryUcU146EiVSE8ProAIwaTd9/8TMBgGDwD8tFbfOjevw7ZqtrNm8A4Dhc5fT/rCavD3j+5gjc6XOIR3hiNOhya8gtRJUrA7nD4I3+8QdWZlT1MnNo8CDZvZumLa/M+Gx7Qm3MwswdgY/zyxVSii/GVhB9Jd7CtGbyO4ImGtmx+1SKB0CZCdTT5rZk5LaAWcA90gaZWZ3hccT33yyb6cQzVLtMn4uKyFx2w5gZlmSdppZdvxZ7PocbE8oT3yususlPh+w63OS2L4gzy0QLSURJYPHmdkWSWNy6bcwCvwaM7MMSccAJxHNUl0PnGhm10o6lmhWa6qk9uR97AJGmtlFOfvPre89PipXrJat20bbQ/enUvkUtu3M4vhGdZj1fcnaP+BKiVH9oh+AtM7Q6QZPbGJS1MtSNYDsP3euKED9icDZkiqFWY+zEh5bCrQPt3vmGOOHMENzGdFsRHZfPRTtvakHdAvlC4G6kn5appJ0pJl9G5Y92oTEpj6wxcxeAu4jWjrJ1ivh96Rw+yPghuwKYSYJYCRwXUJ5zQKch2yjgL6hXTlJNXI8/hnQVVLDUKdWKB8PXBLKuhEtEW0oxLgF8TXRTFXFMJNzUiHb53ZsNYC1IbFpRjQTkm1nWFLMaTzQK/RRF+gKTC5kLITXWw0z+4AoYW4dyhuZ2edmdgewimg2aSnQJry2DiFaWoXo+TheP+/DqiqpaV59u5Jpxrfr+HD2Dwy7oQsjbuqKBEM+/ybusJwrNe7tei8vnfESaTXS+Ljnx5zX+Lz8GxWzvZm5qSLpu4T7DxLN1AyVtJZor0nD3XVgZlMkvQvMIpqNmc3PyxX3A6+FTabDEpr9B3hD0uVESyybQ/kbRG+484BvgWlEe192hA2kj4Q31FSifTO77GcBWhLt38gCdhLeiIOakmYRzQxk/5V+I/B4KE8FxgHXEu2veFzSHKLZg37kv7yR7f+AQZKuDm378nMyhZmtCufjTUkphP1HROf9uRDLFgqWWBaKmX0blmrmEC03Ti9kF7kd23DgWknziZLQzxLqDwJmSZqWY9/NW0T7qWYSzaL92cyWh+SoMKoD70iqRDQD84dQfp+kJqFsVBgHomOeB8wnem1lPx+9gSGSKoZ6twMb8+jblVADP/6CgR9/EXcYLpksnRD9lAF/GfeXuEP4Bf28ShFTAFI1M9skqQpRgtDHzKbtZV+1if6aP97Mlu9lfEuBDmbmH59wzjnnSoGS8A3FgyS1INrH8MKeJjbB+2HJpAJw994mNs4555wrfWKfuXHOOeecK0r+DcXOOeecSyqe3DjnnHMuqXhy45xzzrmk4smNc84555KKJzfOOeecSyqe3DjnnHMuqXhy45xzzrmk4smNc84555KKJzfOOeecSyr/D82rV+2J3iwkAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "dfStacked.plot(kind='barh', stacked=True, ax=ax, legend=False)\n",
    "plt.xticks([])\n",
    "plt.box(False)\n",
    "plt.legend(wasteLegend, range(1, 6), bbox_to_anchor=(.02, 1), ncol=len(df.columns))\n",
    "\n",
    "for n in dfStacked:\n",
    "    for i, (cumsum, x) in enumerate(zip(dfStacked.cumsum(1)[n], dfStacked[n])):\n",
    "        if x>0:\n",
    "            plt.text(cumsum-x/2, i, str(x), va='center', ha='center', color='white')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "harmfulnessDict = {}\n",
    "for col in chain(df.columns[10:15], df.columns[21:27]):\n",
    "    name = col[col.index('[')+1:-1]\n",
    "    harmfulnessDict[name] = df[col].mean()\n",
    "harmfulnessList = sorted(harmfulnessDict.items(), key=lambda x: x[1])\n",
    "names, means = zip(*harmfulnessList)\n",
    "colors = [\"C0\" if name in taskRelated else \"C1\" for name in names]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots()\n",
    "ax.barh(names, means, color=colors)\n",
    "\n",
    "ax.legend(typeLegend, [\"Task-related\", \"Information-related\"])\n",
    "ax.set_title('Average harmfulness by waste and category')\n",
    "plt.xticks([0,5], [\"Not harmful\", \"Very harmful\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                        1  2  3  4  5\n",
      "Language-specific communication issues  3  4  5  0  1\n",
      "Too frequent meetings                   3  5  2  2  1\n",
      "Too long meetings                       3  4  3  2  1\n",
      "Focusing on unneeded tasks              2  5  3  2  1\n",
      "Wrong introduction of new team members  2  2  3  4  2\n",
      "Avoiding specific tasks                 1  1  7  1  3\n",
      "Issues with documentation               1  3  3  2  4\n",
      "Poorly executed tasks                   0  1  4  7  1\n",
      "Leaving tasks uncompleted               0  1  4  6  2\n",
      "Bad flow of information inside team     1  2  1  4  5\n",
      "Unclearly defined tasks                 0  3  2  2  6\n"
     ]
    }
   ],
   "source": [
    "dfStacked = pd.DataFrame(columns=range(1,6))\n",
    "for col in chain(df.columns[10:15], df.columns[21:27]):\n",
    "    counter = Counter({i: 0 for i in range(1, 6)})\n",
    "    counter.update(df[col])\n",
    "    _, values = zip(*sorted(counter.items()))\n",
    "    \n",
    "    wasteName = col[col.index('[')+1:-1]\n",
    "    dfStacked.loc[wasteName] = values\n",
    "\n",
    "dfStacked[\"sum\"] = dfStacked[1]+dfStacked[2]*2+dfStacked[3]*3+dfStacked[4]*4+dfStacked[5]*5\n",
    "dfStacked.sort_values(by=\"sum\", inplace=True)\n",
    "dfStacked.drop(columns=[\"sum\"], inplace=True)\n",
    "\n",
    "print(dfStacked)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "dfStacked.plot(kind='barh', stacked=True, ax=ax, legend=False)\n",
    "plt.xticks([])\n",
    "plt.box(False)\n",
    "plt.legend(wasteLegend, range(1, 6), bbox_to_anchor=(.02, 1), ncol=len(df.columns))\n",
    "\n",
    "for n in dfStacked:\n",
    "    for i, (cumsum, x) in enumerate(zip(dfStacked.cumsum(1)[n], dfStacked[n])):\n",
    "        if x>0:\n",
    "            plt.text(cumsum-x/2, i, str(x), va='center', ha='center', color='white')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\pc\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\ipykernel_launcher.py:56: UserWarning: FixedFormatter should only be used together with FixedLocator\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "lang = \"Python\"\n",
    "df1 = df[df[\"What is the main programming language you use in the chosen project?\"]!=lang]\n",
    "df2 = df[df[\"What is the main programming language you use in the chosen project?\"]==lang]\n",
    "\n",
    "#role = \"Fullstack Developer\"\n",
    "#df1 = df[df[\"What is your main role in the chosen project?\"]!=role]\n",
    "#df2 = df[df[\"What is your main role in the chosen project?\"]==role]\n",
    "\n",
    "#print(df[\"What is your level of work experience in a such or similar role?\"].median())\n",
    "#df1 = df[df[\"What is your level of work experience in a such or similar role?\"]<3]\n",
    "#df2 = df[df[\"What is your level of work experience in a such or similar role?\"]>=3]\n",
    "\n",
    "#print(df[\"How long (in months) is your work experience in such or similar roles in general?\"].median())\n",
    "#df1 = df[df[\"How long (in months) is your work experience in such or similar roles in general?\"]<16]\n",
    "#df2 = df[df[\"How long (in months) is your work experience in such or similar roles in general?\"]>=16]\n",
    "\n",
    "#print(df[\"How long (in months) is your work experience in the chosen project?\"].median())\n",
    "#df1 = df[df[\"How long (in months) is your work experience in the chosen project?\"]<8]\n",
    "#df2 = df[df[\"How long (in months) is your work experience in the chosen project?\"]>=8]\n",
    "\n",
    "'''\n",
    "wFrequencies = []\n",
    "for col in chain(df.columns[6:11], df.columns[16:22]):\n",
    "    wasteName = col[col.index('[')+1:-1]\n",
    "    wFrequencies += [(wasteName, df1[col].mean(), df2[col].mean())]\n",
    "wFrequencies = sorted(wFrequencies, key=lambda x: x[1])\n",
    "fNames, frequencyMeans1, frequencyMeans2 = zip(*wFrequencies)\n",
    "diffs = [x-y for x, y in zip(frequencyMeans1, frequencyMeans2)]\n",
    "\n",
    "y = np.arange(len(fNames))  # the label locations\n",
    "width = 0.4  # the width of the bars\n",
    "\n",
    "_, ax = plt.subplots()\n",
    "ax.barh(y + width/2, frequencyMeans1, width, label=\"df1\")\n",
    "ax.barh(y - width/2, frequencyMeans2, width, label=\"df2\")\n",
    "#ax.barh(y - width, diffs, width, label=\"df3\")\n",
    "plt.xticks([0,5], [\"Doesn't happen\", \"Very common\"])\n",
    "ax.set_title('Frequency by waste and category')\n",
    "ax.set_yticklabels(fNames)\n",
    "ax.set_yticks(y)\n",
    "ax.legend()\n",
    "plt.show()\n",
    "'''\n",
    "\n",
    "dfDiff = pd.DataFrame(columns=[\"df1Mean\", \"df2Mean\", \"diff\", \"type\"])\n",
    "for col in chain(df.columns[10:15], df.columns[21:27]):\n",
    "    wasteName = col[col.index('[')+1:-1]\n",
    "    df1Mean, df2Mean = df1[col].mean(), df2[col].mean()\n",
    "    dfDiff.loc[wasteName] = [df1Mean, df2Mean, df1Mean-df2Mean, \"C0\" if wasteName in taskRelated else \"C1\"]\n",
    "dfDiff.sort_values(by=\"diff\", inplace=True)\n",
    "\n",
    "y = np.arange(len(dfDiff))\n",
    "_, ax = plt.subplots()\n",
    "ax.barh(y, dfDiff[\"diff\"], color=dfDiff[\"type\"])\n",
    "ax.set_title(lang)\n",
    "ax.set_yticklabels(dfDiff.index)\n",
    "ax.set_yticks(y)\n",
    "#ax.set_xticks(np.arange(-2, 2, .5))\n",
    "ax.legend(typeLegend, [\"Task-related\", \"Information-related\"])#, loc=\"lower right\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "freqToHarmCorr = {}\n",
    "for i in range(5, 10):\n",
    "    name = df.iloc[:,i].name\n",
    "    name = name[name.index('[')+1:-1]\n",
    "    freqToHarmCorr[name] = df.iloc[:,i].corr(df.iloc[:,i+5])\n",
    "for i in range(15, 21):\n",
    "    name = df.iloc[:,i].name\n",
    "    name = name[name.index('[')+1:-1]\n",
    "    freqToHarmCorr[name] = df.iloc[:,i].corr(df.iloc[:,i+6])\n",
    "freqToHarmCorr = sorted(freqToHarmCorr.items(), key=lambda x: x[1])\n",
    "names, corrs = zip(*freqToHarmCorr)\n",
    "colors = [\"C0\" if name in taskRelated else \"C1\" for name in names]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "wastes = frequenciesDict.keys()\n",
    "X, Y = zip(*[(frequenciesDict[waste], harmfulnessDict[waste]) for waste in wastes])\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.scatter(X, Y, color=colors)\n",
    "for i, txt in enumerate(wastes):\n",
    "    plt.annotate(txt, (X[i]+.05, Y[i]-.02))\n",
    "ax.legend(typeLegend, [\"Task-related\", \"Information-related\"])\n",
    "ax.yaxis.grid(color='lightgray', linestyle='dashed')\n",
    "ax.xaxis.grid(color='lightgray', linestyle='dashed')\n",
    "plt.ylabel('Average harmfulness')\n",
    "plt.xlabel('Average frequency')\n",
    "ax.set_axisbelow(True)\n",
    "plt.box(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ax = plt.subplots()\n",
    "ax.barh(names, corrs, color=colors)\n",
    "\n",
    "ax.legend(typeLegend, [\"Task-related\", \"Information-related\"], loc=\"lower right\")\n",
    "ax.set_title('Correlation between frequency and harmfulness by waste')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr = df.iloc[:,list(chain(range(5, 10), range(15, 21)))].corr()\n",
    "columns = [col[col.index('[')+1:-1] for col in corr.columns]\n",
    "sns.heatmap(corr, xticklabels=columns, yticklabels=columns).set_title(\"Correlations between waste frequencies\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr = df.iloc[:,list(chain(range(10, 15), range(21, 27)))].corr()\n",
    "columns = [col[col.index('[')+1:-1] for col in corr.columns]\n",
    "sns.heatmap(corr, xticklabels=columns, yticklabels=columns).set_title(\"Correlations between waste harmfulness\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}