2. Barplots Intro.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6e744e98",
   "metadata": {},
   "source": [
    "# Barplots Intro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "382b6bf2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ebc4fa6",
   "metadata": {},
   "source": [
    "## Table of contents\n",
    "\n",
    "[1. Simple Barplots](#simple)<br>\n",
    "\n",
    "[2. Multiple Barplots](#mult)<br>\n",
    "\n",
    "[3. Barplots on top of each other (Stacked barplots](#stacked)<br>\n",
    "\n",
    "[4. Horizontal Barplots](#horiz)\n",
    "- [Stacked horizontal barplots](#shoriz)<br>\n",
    "\n",
    "[5. Adding labels to our barplots](#labels)\n",
    "- [Adding labels to a stacked barplot](#slabels)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "698730c9",
   "metadata": {},
   "source": [
    "## <a id = 'simple'> Simple Barplots</a>\n",
    "Let's start for something very simple. A  normal barplot, with 2 bars, each one with a different color."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "099b400b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Made up data\n",
    "men_average_height = 1.80\n",
    "women_average_height = 1.70\n",
    "labels = ['Men', 'Women']\n",
    "colors = ['aqua', 'coral']\n",
    "\n",
    "plt.yticks(np.arange(1.70, 1.90, 0.05))\n",
    "plt.ylim(1.60, 1.90)\n",
    "plt.xlabel('Gender')\n",
    "plt.ylabel('Height')\n",
    "\n",
    "plt.title('Average Height')\n",
    "\n",
    "# Plotting bars for men and women separately\n",
    "plt.bar('Men', men_average_height, color=colors[0], label='Men')\n",
    "plt.bar('Women', women_average_height, color=colors[1], label='Women')\n",
    "\n",
    "plt.legend(title='gender')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a966b1b",
   "metadata": {},
   "source": [
    "## <a id = 'mult'>Multiple barplots</a>\n",
    "Imagine we have data of the average heights of men and women from 5 different countries: Spain, France, Portugal, Italy and Germany, and we want to plot them all in one graph."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d76207e",
   "metadata": {},
   "source": [
    "### Example 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "38669aef",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "men\n",
      "1\n",
      "women\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#made up data\n",
    "dict_average_heights = {'men': [176, 174, 179, 169, 185],\n",
    "                        'women': [168, 164, 169, 173, 179]}\n",
    "\n",
    "gender_labels = ['men', 'women']\n",
    "country_labels = ['Spain', 'France', 'Portugal', ' Italy', 'Germany']\n",
    "barWidth = 0.25 #necessary for plotting one graph next to each other\n",
    "x = np.arange(len(country_labels))\n",
    "\n",
    "# each loop is going to plot me all heights of each gender. \n",
    "# in other words, each loop is going to plot me the bars of a color\n",
    "for i, gender in enumerate(gender_labels):\n",
    "    print(i)\n",
    "    print(gender)\n",
    "    plt.bar(x + (barWidth * i), dict_average_heights[gender], width = barWidth, color = colors[i])\n",
    "\n",
    "#NOTE:\n",
    "# x + (barWidth * i) is placing the next color bar (the women's height) next to the men's height.\n",
    "# that's why we needed the barWidth variable, so gender's heights do not overlap.\n",
    "\n",
    "plt.xticks(x + (barWidth / 2) ,country_labels) # x + (barWidth / 2) is so that the xtick is in the middle\n",
    "plt.yticks(np.arange(155, 190, 3))\n",
    "plt.ylim(155, 190)\n",
    "plt.legend(title = 'gender', labels = gender_labels)\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b787e40",
   "metadata": {},
   "source": [
    ">**Note**: Notice that the for loop was looped *'gender-wise'* and not *'country-wise'*."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e82def2a",
   "metadata": {},
   "source": [
    "### Example 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d68727c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "barWidth = 0.25\n",
    "colors = ['r', 'k', 'DodgerBlue']\n",
    "# made up data\n",
    "views_per_year = {'Youtube':[43, 37, 48, 56, 76],\n",
    "                  'Tik Tok': [24, 38, 64, 446, 2034],\n",
    "                  'Facebook':[27, 24, 19, 21, 13]}\n",
    "x = np.arange(0, 5, 1)\n",
    "years_labels = np.arange(2015, 2020, 1)\n",
    "social_media_apps = list()\n",
    "for k in views_per_year:\n",
    "    social_media_apps.append(k)# I add the keys of the dictionary to a list, i.e names of the SM apps\n",
    "    \n",
    "for i, social_media in enumerate(social_media_apps):\n",
    "       plt.bar(x +( barWidth * i), views_per_year[social_media], width = barWidth, color = colors[i])\n",
    "        \n",
    "\n",
    "plt.xlabel('Years')\n",
    "plt.ylabel('Billion views')\n",
    "plt.title('Views in social media per year')\n",
    "plt.xticks(x + barWidth, years_labels) # + barWidth is important so that the year label is in the middle. \n",
    "                                       # We can see from the last example that denpending on how many bars we have\n",
    "                                       # we have to add a bit more distance to the x_axis to the right.  \n",
    "plt.yticks(np.arange(0, 2100, 500))\n",
    "\n",
    "plt.legend(title = 'Social Media Apps', labels = social_media_apps)\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a4d353e",
   "metadata": {},
   "source": [
    ">**Note**: Notice that the xticks in the graph are accomplished in two steps. First with a simple array [0, 1, 2,...], and then I change it to the one that I actual want. To see it clearer, the steps are:\n",
    "\n",
    "1. auxiliar xticks (np.arange(0, ... ))\n",
    "2. I move these ticks with `plt.xticks(x + barWidth)` so that the **xtick is in the middle**.\n",
    "3. Then I set the xticks that I want."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0180e97b",
   "metadata": {},
   "source": [
    "## <a id = 'stacked'>Barplots on top of each other (Stacked barplots)</a>\n",
    "Personally, I like the last layout better than the one we are about to see, but this one (stacked plot) appears a lot. \n",
    "\n",
    "We achieve this with the attribute **bottom** that we'll see in the next example:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1532a922",
   "metadata": {},
   "source": [
    "### Example 1:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fba54376",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "boys = (20, 35, 30, 35, 27)\n",
    "girls = (25, 32, 34, 20, 25)\n",
    "\n",
    "x = np.arange(0,5)   \n",
    "width = 0.35\n",
    "colors = ['DimGray', 'MediumOrchid']\n",
    " \n",
    "fig = plt.subplots(figsize =(10, 7))\n",
    "plt.bar(x, boys, width, color = colors[0])\n",
    "plt.bar(x, girls, width, color = colors[1],\n",
    "             bottom = boys)\n",
    " \n",
    "plt.ylabel('Contribution')\n",
    "plt.title('Contribution by the teams')\n",
    "plt.xticks(x, ('T1', 'T2', 'T3', 'T4', 'T5'))\n",
    "plt.yticks(list([30, 50, 60]))\n",
    "plt.legend(labels = ['boys', 'girls'])\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44006be6",
   "metadata": {},
   "source": [
    "### Example 2\n",
    "Let's see now an example with multiple barplots on top of each other."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "id": "bf8011c3",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create data\n",
    "x = ['A', 'B', 'C', 'D']\n",
    "y1 = np.array([10, 20, 10, 30])\n",
    "y2 = np.array([20, 25, 15, 25])\n",
    "y3 = np.array([12, 15, 19, 6])\n",
    "y4 = np.array([10, 29, 13, 19])\n",
    " \n",
    "# plot bars in stack manner\n",
    "plt.bar(x, y1, color='r')\n",
    "plt.bar(x, y2, bottom=y1, color='b')\n",
    "plt.bar(x, y3, bottom=y1+y2, color='y')\n",
    "plt.bar(x, y4, bottom=y1+y2+y3, color='g')\n",
    "plt.xlabel(\"Teams\")\n",
    "plt.ylabel(\"Score\")\n",
    "plt.legend([\"Round 1\", \"Rond 2\", \"Round 3\", \"Round 4\"])\n",
    "plt.title(\"Scores by Teams in 4 Rounds\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "926899b2",
   "metadata": {},
   "source": [
    "## <a id = 'horiz'>Horizontal Barplots</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "id": "47b4f720",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "player_goals = {'Ronaldo': 567,\n",
    "                'Messi': 601,\n",
    "                'Pele': 439,\n",
    "                'Maradona': 401,\n",
    "                'Zidane': 254,\n",
    "                'Raul': 385,\n",
    "                'Mbappe': 202}\n",
    "\n",
    "#order the dictionary so the barplot is nicer\n",
    "player_goals = dict(sorted(player_goals.items(), key = lambda x: x[1]))\n",
    "players_list = list()\n",
    "goals_list = list()\n",
    "\n",
    "for k,v in player_goals.items():\n",
    "    players_list.append(k),\n",
    "    goals_list.append(v)\n",
    "\n",
    "x = np.arange(0, 650, 50)\n",
    "colors = np.random.rand(len(players_list),3) #the 3 needs to be added because of RGB\n",
    "plt.barh(players_list, goals_list, color = colors)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f41dd65",
   "metadata": {},
   "source": [
    "### <a id = 'shoriz'>Stacked horizontal barplots</a>\n",
    "They work the same way with a tiny change. With vertical plots, we use the attribute `bottom`. \n",
    "\n",
    "Here, with horizontal barplots, since they are horizontal, this attributes changes to  `left`.\n",
    "\n",
    "Let's see the example we did before"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "364d1a5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiwAAAHFCAYAAADR1KI+AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA+eElEQVR4nO3deVyVZf7/8fdhEQTkkLgAiRsyipaQSw0uqWXK5JZRqS2KNlbmmlZoU6FligWOWi7fccPMTMtsUmcwc3csM/2iTjaKuTZi5gYqiQLX749+nG8ncAGRc6Ov5+NxHo/OdW+f+1wHz7vr3mzGGCMAAAALc3N1AQAAAFdDYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYMFNY8uWLerevbtq1qwpLy8vVa9eXdHR0RoxYoSrS7shateurc6dO9+w9cfFxclms131FRcXd8NqKEu1a9e+ofsya9Ys2Ww2+fn5XdP8o0ePdvqcPT09VbNmTfXv31/Hjh27YXWWlri4ONWuXdvVZeAm4uHqAoDSsGLFCnXt2lVt27bV22+/reDgYGVkZOjbb7/VRx99pOTkZFeXWO689tpreu655xzvt2/froEDB2rcuHFq166do71q1aquKK/ULV26VP7+/jdk3f/973/14osvKiQkRJmZmcVaNjU1VXa7XefOndMXX3yh5ORkbd68WWlpafL09Lwh9QJWRGDBTeHtt99WnTp1tHLlSnl4/N/XumfPnnr77bfLtJbs7Gz5+PiU6TZvhLCwMIWFhTneX7hwQZIUHh6uP/7xj64q64a56667bti6n3vuOd17772qXLmyPvnkk2It27RpU1WpUkWS1L59e504cUJz587Vpk2bnIIjcLPjkBBuCidPnlSVKlWcwkoBN7fCX/MPP/xQ0dHR8vPzk5+fn6KiojR79myneebMmaPIyEh5e3urcuXK6t69u77//nuneeLi4uTn56ddu3apQ4cOqlSpku6//35J0sWLFzV27Fg1aNBAXl5eqlq1qvr27auff/7ZaR1r1qxR27ZtFRgYqIoVK6pmzZqKjY1Vdnb2Ne370qVL1bhxY3l7e6tu3bqaMmWKY9q5c+cUEBCgZ599ttByBw8elLu7u955551r2s7lfPnll7r//vvl7+8vHx8ftWzZUqtXr3aaZ9++ferbt6/Cw8Pl4+Oj22+/XV26dNGuXbuc5lu3bp1sNps+/PBDxcfHKzg4WH5+furSpYt++uknnT17Vs8884yqVKmiKlWqqG/fvjp37pzTOj7++GPdc889stvt8vHxUd26ddWvX7+r7sfvDwkV1LJw4UL95S9/UUhIiPz9/dW+fXvt2bPnmj+fDz74QOvXr9e0adOueZkradasmSTpp59+cmq/lu9r27Zt1bZt20Lr/P3hm4MHD8pmsykpKUkTJ05UnTp15Ofnp+joaH399deFlk9JSVH9+vXl5eWliIgIvf/++0XWPn36dEVGRsrPz0+VKlVSgwYN9MorrxTzE8CtisCCm0J0dLS2bNmiIUOGaMuWLbp06dJl53399df1xBNPKCQkRCkpKVq6dKn69OmjQ4cOOeYZP368nn76aTVq1EiffvqpJk+erJ07dyo6Olrp6elO67t48aK6du2q++67T3//+981ZswY5efnq1u3bkpMTNTjjz+uFStWKDExUatWrVLbtm31yy+/SPr1h6FTp06qUKGC5syZo9TUVCUmJsrX11cXL1686n6npaVp2LBheuGFF7R06VK1aNFCQ4cOVVJSkiTJz89P/fr104IFCwodipg2bZoqVKhwTT/ml/PBBx+oQ4cO8vf317x587R48WJVrlxZHTt2dAotR48eVWBgoBITE5WamqqpU6fKw8ND99xzT5E//q+88oqOHz+ulJQUJScna926derVq5diY2Nlt9u1cOFCvfzyy5o/f77TD95XX32lHj16qG7duvroo4+0YsUKvf7668rNzS3xPr7yyis6dOiQZs2apb/97W9KT09Xly5dlJeXd9Vljx8/rmHDhikxMVE1atQocQ2/deDAAUnSH/7wB0dbcb6vxTF16lStWrVKkyZN0oIFC3T+/Hk9+OCDTt+llJQU9e3bVxEREVqyZIleffVVvfnmm1qzZo3Tuj766CM9//zzatOmjZYuXarPPvtML7zwgs6fP1/i+nCLMcBN4MSJE6ZVq1ZGkpFkPD09TYsWLcz48ePN2bNnHfPt37/fuLu7myeeeOKy6zp9+rSpWLGiefDBB53aDx8+bLy8vMzjjz/uaOvTp4+RZObMmeM078KFC40ks2TJEqf2rVu3Gklm2rRpxhhjPvnkEyPJpKWlFXufa9WqZWw2W6FlH3jgAePv72/Onz9vjDHmhx9+MG5ubuavf/2rY55ffvnFBAYGmr59+17z9tauXWskmY8//tgYY8z58+dN5cqVTZcuXZzmy8vLM5GRkebuu+++7Lpyc3PNxYsXTXh4uHnhhRcKbeP36xw2bJiRZIYMGeLU/tBDD5nKlSs73iclJRlJ5syZM9e8XwVq1apl+vTpU6iW338PFi9ebCSZr7766qrrjI2NNS1atDD5+fnGmF+/L76+vtdUT0JCgpFkjh07Zi5dumROnz5tFi9ebHx9fU2vXr0c8xXn+9qmTRvTpk2bQtvq06ePqVWrluP9gQMHjCRz5513mtzcXEf7N998YySZhQsXGmN+7euQkBDTpEkTxz4aY8zBgweNp6en0zoHDRpkAgICrmnfgaIwwoKbQmBgoDZu3KitW7cqMTFR3bp10969ezVq1CjdeeedOnHihCRp1apVysvL08CBAy+7rq+++kq//PJLoStGQkNDdd999xU63CFJsbGxTu+XL1+ugIAAdenSRbm5uY5XVFSUgoKCtG7dOklSVFSUKlSooGeeeUbz5s3T/v37i7XfjRo1UmRkpFPb448/rqysLG3fvl2SVLduXXXu3FnTpk2TMUbSr4fETp48qUGDBhVre7+1efNmnTp1Sn369HHax/z8fMXExGjr1q2O/3vOzc3VuHHj1LBhQ1WoUEEeHh6qUKGC0tPTCx22kFTo6qeIiAhJUqdOnQq1nzp1ynFYqHnz5pKkxx57TIsXL9Z///vfEu9fga5duzq9b9y4sSQ5jcgVZcmSJVq2bJlmzpwpm81W4u0HBQXJ09NTt912mx577DE1bdpU8+bNc0wvyff1WnXq1Enu7u6O97/f9z179ujo0aN6/PHHnfaxVq1aatGihdO67r77bp05c0a9evXS3//+d8ffJHCtCCy4qTRr1kzx8fH6+OOPdfToUb3wwgs6ePCg48TbgvNHrjQ8f/LkSUlScHBwoWkhISGO6QV8fHwKXV3y008/6cyZM6pQoYI8PT2dXseOHXP8Yx0WFqYvv/xS1apV08CBAx0nuk6ePPma9jcoKOiybb+tc+jQoUpPT9eqVask/TrUHx0drSZNmlzTdopScA7FI488UmgfJ0yYIGOMTp06JUkaPny4XnvtNT300ENatmyZtmzZoq1btyoyMtJxeOy3Kleu7PS+QoUKV2wvOCH43nvv1Weffabc3Fz17t1bNWrU0B133KGFCxeWeD8DAwOd3nt5eUlSkXUXOHfunAYOHKjBgwcrJCREZ86c0ZkzZxyH+c6cOXPNh0K+/PJLbd26VStXrlRsbKw2bNigwYMHO6YX9/taHFfb94J1X+l7WOCpp57SnDlzdOjQIcXGxqpatWq65557HN9J4Gq4Sgg3LU9PTyUkJOivf/2r/v3vf0v6v0twf/zxR4WGhha5XME/0hkZGYWmHT161HHFRoGi/u+5SpUqCgwMVGpqapHbqFSpkuO/W7durdatWysvL0/ffvut3n33XQ0bNkzVq1dXz549r7iPRd2Po6Dttz829913n+644w6999578vPz0/bt2/XBBx9ccd1XU/A5vPvuu5e9aqh69eqSfj3XpXfv3ho3bpzT9BMnTiggIOC66vi9bt26qVu3bsrJydHXX3+t8ePH6/HHH1ft2rUVHR1dqtu6nBMnTuinn35ScnJykZfU33bbberWrZs+++yzq64rMjLS8Vk/8MAD6tixo/72t7/p6aefVvPmzYv1ffX29i7ysuqSjnYUbPtK38Pf6tu3r/r27avz589rw4YNSkhIUOfOnbV3717VqlWrRDXg1sEIC24KRf1jLclxuCEkJESS1KFDB7m7u2v69OmXXVd0dLQqVqxY6Af9xx9/1Jo1axxXAV1J586ddfLkSeXl5alZs2aFXvXr1y+0jLu7u+655x5NnTpVkhyHdK7ku+++044dO5zaPvzwQ1WqVKnQ6MmQIUO0YsUKjRo1StWrV9ejjz561fVfScuWLRUQEKDdu3cXuY/NmjVzjIDYbDbH/50XWLFiRakcsrkcLy8vtWnTRhMmTJAk/e///u8N29bvBQUFae3atYVeHTt2lLe3t9auXauxY8cWe702m01Tp06Vu7u7Xn31VUnF+77Wrl1be/fuVU5OjqPt5MmT2rx5c4n2s379+goODtbChQsdhxulXw8ZXWmdvr6++tOf/qS//OUvunjxor777rsSbR+3FkZYcFPo2LGjatSooS5duqhBgwbKz89XWlqakpOT5efnp6FDh0r69R/sV155RW+++aZ++eUX9erVS3a7Xbt379aJEyc0ZswYBQQE6LXXXtMrr7yi3r17q1evXjp58qTGjBkjb29vJSQkXLWenj17asGCBXrwwQc1dOhQ3X333fL09NSPP/6otWvXqlu3burevbtmzJihNWvWqFOnTqpZs6YuXLigOXPmSPr1nhtXExISoq5du2r06NEKDg7WBx98oFWrVmnChAmF7gXz5JNPatSoUdqwYYNeffVVR5goKT8/P7377rvq06ePTp06pUceeUTVqlXTzz//rB07dujnn392BMPOnTsrJSVFDRo0UOPGjbVt2za98847pXblTIHXX39dP/74o+6//37VqFFDZ86c0eTJk+Xp6ak2bdqU6rauxNvbu8jLh1NSUuTu7l7ktGsVHh6uZ555RtOmTdOmTZvUqlWra/6+PvXUU/qf//kfPfnkk+rfv79Onjypt99+u8Q3zHNzc9Obb76pP//5z+revbv69++vM2fOaPTo0YUOCfXv318VK1ZUy5YtFRwcrGPHjmn8+PGy2+2Oc4+AK3LxSb9AqVi0aJF5/PHHTXh4uPHz8zOenp6mZs2a5qmnnjK7d+8uNP/7779vmjdvbry9vY2fn5+56667zNy5c53mmTVrlmncuLGpUKGCsdvtplu3bua7775zmudKV31cunTJJCUlmcjISMd2GjRoYJ599lmTnp5ujDHmq6++Mt27dze1atUyXl5eJjAw0LRp08Z8/vnnV93nWrVqmU6dOplPPvnENGrUyFSoUMHUrl3bTJw48bLLxMXFGQ8PD/Pjjz9edf2/9/urhAqsX7/edOrUyVSuXNl4enqa22+/3XTq1MlpvtOnT5unn37aVKtWzfj4+JhWrVqZjRs3Frpq5XLbmDt3rpFktm7d6tRecCXNzz//bIwxZvny5eZPf/qTuf32202FChVMtWrVzIMPPmg2btx41f273FVCv6+l4Aqa339frkVJrhIq2Lff+umnn4yfn59p166do+1avq/GGDNv3jwTERFhvL29TcOGDc2iRYsue5XQO++8U2h5SSYhIcGpbdasWSY8PNxUqFDB/OEPfzBz5swptM558+aZdu3amerVq5sKFSqYkJAQ89hjj5mdO3de0+cB2Iz5zTgegJvWxYsXVbt2bbVq1UqLFy92dTkAUCwcEgJucj///LP27NmjuXPn6qefftLIkSNdXRIAFBuBBbjJrVixQn379lVwcLCmTZt2XZcyA4CrcEgIAABYHpc1AwAAyyOwAAAAyyOwAAAAy7spTrrNz8/X0aNHValSpet6yBgAACg7xhidPXtWISEhcnO78hjKTRFYjh49etnnwgAAAGs7cuTIVe98fVMEloIHyR05cqTEt5gGAABlKysrS6GhoU4PhL2cmyKwFBwG8vf3J7AAAFDOXMvpHJx0CwAALI/AAgAALI/AAgAALI/AAgAALI/AAgAALI/AAgAALI/AAgAALI/AAgAALI/AAgAALI/AAgAALI/AAgAALI/AAgAALI/AAgAALI/AAgAALM/D1QWUKrvd1RXgFmSTcXUJsJi1a20u3X679S7dPIpgEvh34noxwgIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACyPwAIAACzPpYElLi5ONptNNptNnp6eql69uh544AHNmTNH+fn5riwNAABYiMtHWGJiYpSRkaGDBw/qn//8p9q1a6ehQ4eqc+fOys3NdXV5AADAAjxcXYCXl5eCgoIkSbfffruaNGmiP/7xj7r//vuVkpKiP//5zy6uEAAAuJrLR1iKct999ykyMlKffvppkdNzcnKUlZXl9AIAADcvSwYWSWrQoIEOHjxY5LTx48fLbrc7XqGhoWVbHAAAKFOWDSzGGNlstiKnjRo1SpmZmY7XkSNHyrg6AABQllx+DsvlfP/996pTp06R07y8vOTl5VXGFQEAAFex5AjLmjVrtGvXLsXGxrq6FAAAYAEuH2HJycnRsWPHlJeXp59++kmpqakaP368OnfurN69e7u6PAAAYAEuDyypqakKDg6Wh4eHbrvtNkVGRmrKlCnq06eP3NwsOQAEAADKmEsDS0pKilJSUlxZAgAAKAcYwgAAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJZHYAEAAJbn4eoCSlVmpuTv7+oqcIsxri4AFuTab4Vp69LNAzcEIywAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyCCwAAMDyPFxdQKmy211dQamyybi6hHJt7Vqbq0vA77Rb7+oKrMck8HcOXAtGWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOVZIrAcO3ZMgwcPVt26deXl5aXQ0FB16dJFq1evdnVpAADAAjxcXcDBgwfVsmVLBQQE6O2331bjxo116dIlrVy5UgMHDtR//vMfV5cIAABczOWB5fnnn5fNZtM333wjX19fR3ujRo3Ur18/F1YGAACswqWHhE6dOqXU1FQNHDjQKawUCAgIKPuiAACA5bh0hGXfvn0yxqhBgwbFWi4nJ0c5OTmO91lZWaVdGgAAsBCXjrAYYyRJNputWMuNHz9edrvd8QoNDb0R5QEAAItwaWAJDw+XzWbT999/X6zlRo0apczMTMfryJEjN6hCAABgBS4NLJUrV1bHjh01depUnT9/vtD0M2fOFLmcl5eX/P39nV4AAODm5fL7sEybNk15eXm6++67tWTJEqWnp+v777/XlClTFB0d7eryAACABbj8suY6depo+/bteuuttzRixAhlZGSoatWqatq0qaZPn+7q8gAAgAXYTMGZr+VYVlaW7Ha7MiXdTAeHbCr3XeNSa9cW72Ru3Hjt1ru6AusxCfyd49bl+P3OzLzq6R0uPyQEAABwNQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgeQQWAABgedcVWC5evKg9e/YoNze3tOoBAAAopESBJTs7W08//bR8fHzUqFEjHT58WJI0ZMgQJSYmlmqBAAAAJQoso0aN0o4dO7Ru3Tp5e3s72tu3b69FixaVWnEAAACS5FGShT777DMtWrRIf/zjH2Wz2RztDRs21A8//FBqxQEAAEglHGH5+eefVa1atULt58+fdwowAAAApaFEgaV58+ZasWKF431BSJk5c6aio6NLpzIAAID/r0SHhMaPH6+YmBjt3r1bubm5mjx5sr777jt99dVXWr9+fWnXCAAAbnElGmFp0aKFNm/erOzsbIWFhemLL75Q9erV9dVXX6lp06alXSMAALjFFXuE5dKlS3rmmWf02muvad68eTeippLLzJT8/V1dRakxri6g3OMTtBrT1tUVACivij3C4unpqaVLl96IWgAAAIpUokNC3bt312effVbKpQAAABStRCfd1qtXT2+++aY2b96spk2bytfX12n6kCFDSqU4AAAASbIZY4p9oL9OnTqXX6HNpv37919XUcWVlZUlu92uzMxM+d9E57AAAHAzK87vd4lGWA4cOFCiwgAAAEriup7WLEnGGJVgkAYAAOCalTiwvP/++7rzzjtVsWJFVaxYUY0bN9b8+fNLszYAAABJJTwkNHHiRL322msaNGiQWrZsKWOM/vWvf+m5557TiRMn9MILL5R2nQAA4BZW4pNux4wZo969ezu1z5s3T6NHjy7zc1w46RYAgPKnOL/fJToklJGRoRYtWhRqb9GihTIyMkqySgAAgMsqUWCpV6+eFi9eXKh90aJFCg8Pv+6iAAAAfqtE57CMGTNGPXr00IYNG9SyZUvZbDZt2rRJq1evLjLIAAAAXI8SjbDExsZqy5YtqlKlij777DN9+umnqlKlir755ht17969tGsEAAC3uBKddGs1nHQLAED5c8NPuv3HP/6hlStXFmpfuXKl/vnPf5ZklQAAAJdVosAycuRI5eXlFWo3xmjkyJHXXRQAAMBvlSiwpKenq2HDhoXaGzRooH379l13UQAAAL9VoquE7Ha79u/fr9q1azu179u3T76+vqVRV8nY7a7bNq6JTeX+lCmUsrVrba4uodxqt97VFeBWYBKs8e92iUZYunbtqmHDhumHH35wtO3bt08jRoxQ165dS604AAAAqYSB5Z133pGvr68aNGigOnXqqE6dOmrQoIECAwOVlJRU2jUCAIBbXIkPCW3evFmrVq3Sjh07VLFiRUVGRqp169alXR8AAEDxRli2bNniuGzZZrOpQ4cOqlatmpKSkhQbG6tnnnlGOTk5N6RQAABw6ypWYBk9erR27tzpeL9r1y71799fDzzwgEaOHKlly5Zp/PjxpV4kAAC4tRUrsKSlpen+++93vP/oo4909913a+bMmRo+fLimTJnCs4QAAECpK1ZgOX36tKpXr+54v379esXExDjeN2/eXEeOHCm96gAAAFTMwFK9enUdOHBAknTx4kVt375d0dHRjulnz56Vp6dn6VYIAABuecUKLDExMRo5cqQ2btyoUaNGycfHx+nKoJ07dyosLKzUiwQAALe2Yl3WPHbsWD388MNq06aN/Pz8NG/ePFWoUMExfc6cOerQoUOpFwkAAG5txQosVatW1caNG5WZmSk/Pz+5u7s7Tf/444/l5+dXqgUCAACU+MZxRalcufJ1FQMAAFCUEt2aHwAAoCwRWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOW5PLDExcXJZrM5XoGBgYqJidHOnTtdXRoAALAIlwcWSYqJiVFGRoYyMjK0evVqeXh4qHPnzq4uCwAAWIQlAouXl5eCgoIUFBSkqKgoxcfH68iRI/r5559dXRoAALAAD1cX8Hvnzp3TggULVK9ePQUGBhY5T05OjnJychzvs7Kyyqo8AADgApYILMuXL5efn58k6fz58woODtby5cvl5lb0AND48eM1ZsyYsiwRAAC4kCUOCbVr105paWlKS0vTli1b1KFDB/3pT3/SoUOHipx/1KhRyszMdLyOHDlSxhUDAICyZIkRFl9fX9WrV8/xvmnTprLb7Zo5c6bGjh1baH4vLy95eXmVZYkAAMCFLDHC8ns2m01ubm765ZdfXF0KAACwAEuMsOTk5OjYsWOSpNOnT+u9997TuXPn1KVLFxdXBgAArMASgSU1NVXBwcGSpEqVKqlBgwb6+OOP1bZtW9cWBgAALMHlgSUlJUUpKSmuLgMAAFiYJc9hAQAA+C0CCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwCCwAAsDwPVxdQqjIzJX9/V1eBKzCuLgAWxLeipExbV1cAlB1GWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOURWAAAgOXdXDeOAwDccvLy8nTp0iVXl4EieHp6yt3dvVTWRWABAJRLxhgdO3ZMZ86ccXUpuIKAgAAFBQXJZrNd13oILACAcqkgrFSrVk0+Pj7X/YOI0mWMUXZ2to4fPy5JCg4Ovq71EVgAAOVOXl6eI6wEBga6uhxcRsWKFSVJx48fV7Vq1a7r8BAn3QIAyp2Cc1Z8fHxcXAmupqCPrvc8IwILAKDc4jCQ9ZVWHxFYAACA5RFYAACAJCkuLk4PPfSQq8so0s110q3d7uoKSpVNxtUl4BqsXXtrD0m3W+/qCkqfSeBvr9wq60NEpnjflbi4OM2bN0+S5O7urpCQEHXq1Enjxo3TbbfddiMqLFUXLlzQc889p23btun7779X586d9dlnn5XJthlhAQCgDMXExCgjI0MHDx7UrFmztGzZMj3//POuLuua5OXlqWLFihoyZIjat29fptsmsAAAUIa8vLwUFBSkGjVqqEOHDurRo4e++OILx/T8/Hy98cYbqlGjhry8vBQVFaXU1FTH9HXr1slmszndMC8tLU02m00HDx6UJKWkpCggIEArV65URESE/Pz8HEGpQF5enoYPH66AgAAFBgbq5ZdflrnKiJGvr6+mT5+u/v37KygoqHQ+kGtEYAEAwEX279+v1NRUeXp6OtomT56s5ORkJSUlaefOnerYsaO6du2q9PT0Yq07OztbSUlJmj9/vjZs2KDDhw/rxRdfdExPTk7WnDlzNHv2bG3atEmnTp3S0qVLS23fShuBBQCAMrR8+XL5+fmpYsWKCgsL0+7duxUfH++YnpSUpPj4ePXs2VP169fXhAkTFBUVpUmTJhVrO5cuXdKMGTPUrFkzNWnSRIMGDdLq1asd0ydNmqRRo0YpNjZWERERmjFjhuwWPhf05jrpFgAAi2vXrp2mT5+u7OxszZo1S3v37tXgwYMlSVlZWTp69KhatmzptEzLli21Y8eOYm3Hx8dHYWFhjvfBwcGO2+RnZmYqIyND0dHRjukeHh5q1qzZVQ8LuQojLAAAlCFfX1/Vq1dPjRs31pQpU5STk6MxY8Y4zfP7m60ZYxxtbm5ujrYCRd1F9reHmQrWadUwci0ILAAAuFBCQoKSkpJ09OhR+fv7KyQkRJs2bXKaZ/PmzYqIiJAkVa1aVZKcTqBNS0sr1jbtdruCg4P19ddfO9pyc3O1bdu2Eu7FjcchIQAAXKht27Zq1KiRxo0bp/fee08vvfSSEhISFBYWpqioKM2dO1dpaWlasGCBJKlevXoKDQ3V6NGjNXbsWKWnpys5ObnY2x06dKgSExMVHh6uiIgITZw40enKo8vZvXu3Ll68qFOnTuns2bOOsBQVFVXsGoqDwAIAuHmU00Mew4cPV9++fRUfH68hQ4YoKytLI0aM0PHjx9WwYUN9/vnnCg8Pl/TroZ6FCxdqwIABioyMVPPmzTV27Fg9+uijxdrmiBEjlJGRobi4OLm5ualfv37q3r27MjMzr7jcgw8+qEOHDjne33XXXZJ0ww832Ux5PqD1/2VlZclutytTkr+riylF3Om2fOBOt66uoPRxp1vru3Dhgg4cOKA6derI29vb1eXgCq7UV47f78xM+ftf+Recc1gAAIDlEVgAAIDlEVgAAIDlEVgAAIDlEVgAAIDlEVgAAIDlEVgAAIDlEVgAAIDlEVgAAIDlEVgAAIAkKS4uTg899JCryygSgQUAcNOw2cr2VVxxcXGy2Wyy2Wzy8PBQzZo1NWDAAJ0+fbr0P4wbYN26derWrZuCg4Pl6+urqKgox0MZbzQCCwAAZSgmJkYZGRk6ePCgZs2apWXLlun55593dVnXZPPmzWrcuLGWLFminTt3ql+/furdu7eWLVt2w7dNYAEAoAx5eXkpKChINWrUUIcOHdSjRw998cUXjun5+fl64403VKNGDXl5eSkqKkqpqamO6evWrZPNZtOZM2ccbWlpabLZbDp48KAkKSUlRQEBAVq5cqUiIiLk5+fnCEoF8vLyNHz4cAUEBCgwMFAvv/zyVZ+4/Morr+jNN99UixYtFBYWpiFDhigmJkZLly4tnQ/nCggsAAC4yP79+5WamipPT09H2+TJk5WcnKykpCTt3LlTHTt2VNeuXZWenl6sdWdnZyspKUnz58/Xhg0bdPjwYb344ouO6cnJyZozZ45mz56tTZs26dSpUyUKHpmZmapcuXKxlysuAgsAAGVo+fLl8vPzU8WKFRUWFqbdu3crPj7eMT0pKUnx8fHq2bOn6tevrwkTJigqKkqTJk0q1nYuXbqkGTNmqFmzZmrSpIkGDRqk1atXO6ZPmjRJo0aNUmxsrCIiIjRjxgzZ7fZibeOTTz7R1q1b1bdv32ItVxIeN3wLAADAoV27dpo+fbqys7M1a9Ys7d27V4MHD5YkZWVl6ejRo2rZsqXTMi1bttSOHTuKtR0fHx+FhYU53gcHB+v48eOSfh0VycjIUHR0tGO6h4eHmjVrdtXDQgXWrVunuLg4zZw5U40aNSpWbSXBCAsAAGXI19dX9erVU+PGjTVlyhTl5ORozJgxTvPYfncJkjHG0ebm5uZoK3Dp0qVC2/ntYaaCdV5rGLma9evXq0uXLpo4caJ69+5dKuu8GgILAAAulJCQoKSkJB09elT+/v4KCQnRpk2bnObZvHmzIiIiJElVq1aVJKcTaNPS0oq1TbvdruDgYH399deOttzcXG3btu2qy65bt06dOnVSYmKinnnmmWJt93oQWAAAcKG2bduqUaNGGjdunCTppZde0oQJE7Ro0SLt2bNHI0eOVFpamoYOHSpJqlevnkJDQzV69Gjt3btXK1asUHJycrG3O3ToUCUmJmrp0qX6z3/+o+eff97pyqOiFISVIUOGKDY2VseOHdOxY8d06tSpYm+/uAgsAICbhjFl+yotw4cP18yZM3XkyBENGTJEI0aM0IgRI3TnnXcqNTVVn3/+ucLDwyX9eqhn4cKF+s9//qPIyEhNmDBBY8eOLfY2R4wYod69eysuLk7R0dGqVKmSunfvfsVlUlJSlJ2drfHjxys4ONjxevjhh0u038VhM6V1QOs6bd68Wa1bt9YDDzzgdL35tcjKypLdblemJP8bU55L2GSJrsFVrF1bgttd3kTarXd1BaXPJPC3Z3UXLlzQgQMHVKdOHXl7e7u6HFzBlfrK8fudmSl//yv/gltmhGXOnDkaPHiwNm3apMOHD7u6HAAAYCGWCCznz5/X4sWLNWDAAHXu3FkpKSmuLgkAAFiIJQLLokWLVL9+fdWvX19PPvmk5s6dW2qXXgEAgPLPEoFl9uzZevLJJyX9+lCoc+fOOd2N7/dycnKUlZXl9AIAADcvlweWPXv26JtvvlHPnj0l/XqnvR49emjOnDmXXWb8+PGy2+2OV2hoaFmVCwAAXMDlt+afPXu2cnNzdfvttzvajDHy9PTU6dOnddtttxVaZtSoURo+fLjjfVZWFqEFAICbmEsDS25urt5//30lJyerQ4cOTtNiY2O1YMECDRo0qNByXl5e8vLyKqsyAQCAi7k0sCxfvlynT5/W008/XegJkY888ohmz55dZGABAAC3FpeewzJ79my1b9++yMdZx8bGKi0tTdu3b3dBZQAA3Hri4uL00EMPubqMIrk0sCxbtkwrVqwoclqTJk1kjFGTJk3KuCoAAG6MuLg42Ww22Ww2eXh4qGbNmhowYIBOnz7t6tKuyZ49e9SuXTtVr15d3t7eqlu3rl599dUinxZd2lx+0i0AAKVl3bqyfVRG27bFv2dYTEyM5s6dq9zcXO3evVv9+vXTmTNntHDhwhtQYeny9PRU79691aRJEwUEBGjHjh3q37+/8vPzHQ9vvFFcflkzAAC3Ei8vLwUFBalGjRrq0KGDevTooS+++MIxPT8/X2+88YZq1KghLy8vRUVFOT1jb926dbLZbE5PVk5LS5PNZtPBgwcl/fqQwoCAAK1cuVIRERHy8/NTTEyMMjIyHMvk5eVp+PDhCggIUGBgoF5++eWr3rS1bt266tu3ryIjI1WrVi117dpVTzzxhDZu3Fg6H84VEFgAAHCR/fv3KzU1VZ6eno62yZMnKzk5WUlJSdq5c6c6duyorl27Kj09vVjrzs7OVlJSkubPn68NGzbo8OHDevHFFx3Tk5OTNWfOHM2ePVubNm3SqVOntHTp0mJtY9++fUpNTVWbNm2KtVxJEFgAAChDy5cvl5+fnypWrKiwsDDt3r1b8fHxjulJSUmKj49Xz549Vb9+fU2YMEFRUVGaNGlSsbZz6dIlzZgxQ82aNVOTJk00aNAgp7vIT5o0SaNGjVJsbKwiIiI0Y8aMIi+CKUqLFi3k7e2t8PBwtW7dWm+88UaxaisJAgsAAGWoXbt2SktL05YtWzR48GB17NhRgwcPlvTrjVCPHj2qli1bOi3TsmVLff/998Xajo+Pj8LCwhzvg4ODdfz4cUlSZmamMjIyFB0d7Zju4eGhZs2aXdO6Fy1apO3bt+vDDz/UihUrlJSUVKzaSoLAAgBAGfL19VW9evXUuHFjTZkyRTk5ORozZozTPDab88nDxhhHm5ubm6OtQFFX6fz2MFPBOkvrwcKhoaFq2LChevXqpcTERI0ePVp5eXmlsu7LIbAAAOBCCQkJSkpK0tGjR+Xv76+QkBBt2rTJaZ7NmzcrIiJCklS1alVJcjqBNi0trVjbtNvtCg4O1tdff+1oy83N1bZt24pdvzFGly5dKrUwdDlc1gwAgAu1bdtWjRo10rhx4/Tee+/ppZdeUkJCgsLCwhQVFaW5c+cqLS1NCxYskCTVq1dPoaGhGj16tMaOHav09HQlJycXe7tDhw5VYmKiwsPDFRERoYkTJzpdeVSUBQsWyNPTU3feeae8vLy0bds2jRo1Sj169JCHx42NFAQWAABcbPjw4erbt6/i4+M1ZMgQZWVlacSIETp+/LgaNmyozz//XOHh4ZJ+PdSzcOFCDRgwQJGRkWrevLnGjh2rRx99tFjbHDFihDIyMhQXFyc3Nzf169dP3bt3V2Zm5mWX8fDw0IQJE7R3714ZY1SrVi0NHDhQL7zwwnXt/7WwmRs9hlMGsrKyZLfblSnJ39XFlCKbyn3X3BLWri3bG1VZTbv1rq6g9JkE/vas7sKFCzpw4IDq1Kkjb29vV5eDK7hSXzl+vzMz5e9/5V9wzmEBAACWR2ABAACWR2ABAACWR2ABAACWR2ABAACWR2ABAACWR2ABAACWR2ABAACWR2ABAACWR2ABAACSpLi4OD300EOuLqNIBBYAAMpIXFycbDabbDabPDw8VLNmTQ0YMECnT592dWnFtm/fPlWqVEkBAQFlsj0efggAuGnYxpTts71K8typmJgYzZ07V7m5udq9e7f69eunM2fOaOHChTegwhvj0qVL6tWrl1q3bq3NmzeXyTYZYQEAoAx5eXkpKChINWrUUIcOHdSjRw998cUXjun5+fl64403VKNGDXl5eSkqKkqpqamO6evWrZPNZtOZM2ccbWlpabLZbDp48KAkKSUlRQEBAVq5cqUiIiLk5+enmJgYZWRkOJbJy8vT8OHDFRAQoMDAQL388su61uchv/rqq2rQoIEee+yx6/swioHAAgCAi+zfv1+pqany9PR0tE2ePFnJyclKSkrSzp071bFjR3Xt2lXp6enFWnd2draSkpI0f/58bdiwQYcPH9aLL77omJ6cnKw5c+Zo9uzZ2rRpk06dOqWlS5dedb1r1qzRxx9/rKlTpxarnutFYAEAoAwtX75cfn5+qlixosLCwrR7927Fx8c7piclJSk+Pl49e/ZU/fr1NWHCBEVFRWnSpEnF2s6lS5c0Y8YMNWvWTE2aNNGgQYO0evVqx/RJkyZp1KhRio2NVUREhGbMmCG73X7FdZ48eVJxcXFKSUmRv79/seq5XpzDAgBAGWrXrp2mT5+u7OxszZo1S3v37tXgwYMlSVlZWTp69KhatmzptEzLli21Y8eOYm3Hx8dHYWFhjvfBwcE6fvy4JCkzM1MZGRmKjo52TPfw8FCzZs2ueFiof//+evzxx3XvvfcWq5bSwAgLAABlyNfXV/Xq1VPjxo01ZcoU5eTkaMyYMU7z2GzOJw8bYxxtbm5ujrYCly5dKrSd3x5mKljntZ6jcjlr1qxRUlKSPDw85OHhoaefflqZmZny8PDQnDlzrmvdV0NgAQDAhRISEpSUlKSjR4/K399fISEh2rRpk9M8mzdvVkREhCSpatWqkuR0Am1aWlqxtmm32xUcHKyvv/7a0Zabm6tt27ZdcbmvvvpKaWlpjtcbb7yhSpUqKS0tTd27dy9WDcXFISEAAFyobdu2atSokcaNG6f33ntPL730khISEhQWFqaoqCjNnTtXaWlpWrBggSSpXr16Cg0N1ejRozV27Filp6crOTm52NsdOnSoEhMTFR4eroiICE2cONHpyqOiFISmAt9++63c3Nx0xx13FHv7xXVzBZbMTKmMTwK6ka5v4A5l59buKdPW1RUA5d/w4cPVt29fxcfHa8iQIcrKytKIESN0/PhxNWzYUJ9//rnCw8Ml/XqoZ+HChRowYIAiIyPVvHlzjR07Vo8++mixtjlixAhlZGQoLi5Obm5u6tevn7p3767MzMwbsYvXzWau94CWBWRlZclutyszM7PMz1oGAJS9Cxcu6MCBA6pTp468vb1dXQ6u4Ep9VZzfb85hAQAAlkdgAQAAlkdgAQAAlkdgAQAAlkdgAQAAlkdgAQCUWzfBha43vdLqIwILAKDcKbjtfHZ2tosrwdUU9NHvHxVQXDfXjeMAALcEd3d3BQQEOB7m5+PjU+j5O3AtY4yys7N1/PhxBQQEyN3d/brWR2ABAJRLQUFBkuQILbCmgIAAR19dDwILAKBcstlsCg4OVrVq1Yp8WjFcz9PT87pHVgoQWAAA5Zq7u3up/SjCujjpFgAAWB6BBQAAWB6BBQAAWN5NcQ5LwU1psrKyXFwJAAC4VgW/29dyc7mbIrCcPHlSkhQaGuriSgAAQHGdPXtWdrv9ivPcFIGlcuXKkqTDhw9fdYfhOllZWQoNDdWRI0fk7+/v6nJwGfRT+UA/lR/01eUZY3T27FmFhIRcdd6bIrC4uf16Ko7dbufLUA74+/vTT+UA/VQ+0E/lB31VtGsdaOCkWwAAYHkEFgAAYHk3RWDx8vJSQkKCvLy8XF0KroB+Kh/op/KBfio/6KvSYTPXci0RAACAC90UIywAAODmRmABAACWR2ABAACWR2ABAACWV+4Dy7Rp01SnTh15e3uradOm2rhxo6tLuqWNHz9ezZs3V6VKlVStWjU99NBD2rNnj9M8xhiNHj1aISEhqlixotq2bavvvvvORRVD+rXfbDabhg0b5mijn6zjv//9r5588kkFBgbKx8dHUVFR2rZtm2M6feV6ubm5evXVV1WnTh1VrFhRdevW1RtvvKH8/HzHPPTTdTLl2EcffWQ8PT3NzJkzze7du83QoUONr6+vOXTokKtLu2V17NjRzJ071/z73/82aWlpplOnTqZmzZrm3LlzjnkSExNNpUqVzJIlS8yuXbtMjx49THBwsMnKynJh5beub775xtSuXds0btzYDB061NFOP1nDqVOnTK1atUxcXJzZsmWLOXDggPnyyy/Nvn37HPPQV643duxYExgYaJYvX24OHDhgPv74Y+Pn52cmTZrkmId+uj7lOrDcfffd5rnnnnNqa9CggRk5cqSLKsLvHT9+3Egy69evN8YYk5+fb4KCgkxiYqJjngsXLhi73W5mzJjhqjJvWWfPnjXh4eFm1apVpk2bNo7AQj9ZR3x8vGnVqtVlp9NX1tCpUyfTr18/p7aHH37YPPnkk8YY+qk0lNtDQhcvXtS2bdvUoUMHp/YOHTpo8+bNLqoKv5eZmSnp/x5QeeDAAR07dsyp37y8vNSmTRv6zQUGDhyoTp06qX379k7t9JN1fP7552rWrJkeffRRVatWTXfddZdmzpzpmE5fWUOrVq20evVq7d27V5K0Y8cObdq0SQ8++KAk+qk0lNuHH544cUJ5eXmqXr26U3v16tV17NgxF1WF3zLGaPjw4WrVqpXuuOMOSXL0TVH9dujQoTKv8Vb20Ucfadu2bfr2228LTaOfrGP//v2aPn26hg8frldeeUXffPONhgwZIi8vL/Xu3Zu+soj4+HhlZmaqQYMGcnd3V15ent566y316tVLEn9TpaHcBpYCNpvN6b0xplAbXGPQoEHauXOnNm3aVGga/eZaR44c0dChQ/XFF1/I29v7svPRT66Xn5+vZs2aady4cZKku+66S999952mT5+u3r17O+ajr1xr0aJF+uCDD/Thhx+qUaNGSktL07BhwxQSEqI+ffo45qOfSq7cHhKqUqWK3N3dC42mHD9+vFCCRdkbPHiwPv/8c61du1Y1atRwtAcFBUkS/eZi27Zt0/Hjx9W0aVN5eHjIw8ND69ev15QpU+Th4eHoC/rJ9YKDg9WwYUOntoiICB0+fFgSf1NW8dJLL2nkyJHq2bOn7rzzTj311FN64YUXNH78eEn0U2kot4GlQoUKatq0qVatWuXUvmrVKrVo0cJFVcEYo0GDBunTTz/VmjVrVKdOHafpderUUVBQkFO/Xbx4UevXr6ffytD999+vXbt2KS0tzfFq1qyZnnjiCaWlpalu3br0k0W0bNmy0K0B9u7dq1q1aknib8oqsrOz5ebm/JPq7u7uuKyZfioFLjzh97oVXNY8e/Zss3v3bjNs2DDj6+trDh486OrSblkDBgwwdrvdrFu3zmRkZDhe2dnZjnkSExON3W43n376qdm1a5fp1asXl/ZZwG+vEjKGfrKKb775xnh4eJi33nrLpKenmwULFhgfHx/zwQcfOOahr1yvT58+5vbbb3dc1vzpp5+aKlWqmJdfftkxD/10fcp1YDHGmKlTp5patWqZChUqmCZNmjgun4VrSCryNXfuXMc8+fn5JiEhwQQFBRkvLy9z7733ml27drmuaBhjCgcW+sk6li1bZu644w7j5eVlGjRoYP72t785TaevXC8rK8sMHTrU1KxZ03h7e5u6deuav/zlLyYnJ8cxD/10fWzGGOPKER4AAICrKbfnsAAAgFsHgQUAAFgegQUAAFgegQUAAFgegQUAAFgegQUAAFgegQUAAFgegQUAAFgegQVAqbHZbFd8xcXFubpEAOWUh6sLAHDzyMjIcPz3okWL9Prrrzs9uK9ixYquKAvATYARFgClJigoyPGy2+2y2WxObRs2bFDTpk3l7e2tunXrasyYMcrNzXUsP3HiRN15553y9fVVaGionn/+eZ07d84xPSUlRQEBAVq+fLnq168vHx8fPfLIIzp//rzmzZun2rVr67bbbtPgwYOVl5fnWG7atGkKDw+Xt7e3qlevrkceeaRMPxcA148RFgBlYuXKlXryySc1ZcoUtW7dWj/88IOeeeYZSVJCQoIkyc3NTVOmTFHt2rV14MABPf/883r55Zc1bdo0x3qys7M1ZcoUffTRRzp79qwefvhhPfzwwwoICNA//vEP7d+/X7GxsWrVqpV69Oihb7/9VkOGDNH8+fPVokULnTp1Shs3bnTJZwDgOrj66YsAbk5z5841drvd8b5169Zm3LhxTvPMnz/fBAcHX3YdixcvNoGBgU7rlGT27dvnaHv22WeNj4+POXv2rKOtY8eO5tlnnzXGGLNkyRLj7+9vsrKyrneXALgQIywAysS2bdu0detWvfXWW462vLw8XbhwQdnZ2fLx8dHatWs1btw47d69W1lZWcrNzdWFCxd0/vx5+fr6SpJ8fHwUFhbmWEf16tVVu3Zt+fn5ObUdP35ckvTAAw+oVq1aqlu3rmJiYhQTE6Pu3bvLx8enjPYcQGngHBYAZSI/P19jxoxRWlqa47Vr1y6lp6fL29tbhw4d0oMPPqg77rhDS5Ys0bZt2zR16lRJ0qVLlxzr8fT0dFqvzWYrsi0/P1+SVKlSJW3fvl0LFy5UcHCwXn/9dUVGRurMmTM3docBlCpGWACUiSZNmmjPnj2qV69ekdO//fZb5ebmKjk5WW5uv/6/1OLFi0tl2x4eHmrfvr3at2+vhIQEBQQEaM2aNXr44YdLZf0AbjwCC4Ay8frrr6tz584KDQ3Vo48+Kjc3N+3cuVO7du3S2LFjFRYWptzcXL377rvq0qWL/vWvf2nGjBnXvd3ly5dr//79uvfee3XbbbfpH//4h/Lz81W/fv1S2CsAZYVDQgDKRMeOHbV8+XKtWrVKzZs31x//+EdNnDhRtWrVkiRFRUVp4sSJmjBhgu644w4tWLBA48ePv+7tBgQE6NNPP9V9992niIgIzZgxQwsXLlSjRo2ue90Ayo7NGGNcXQQAAMCVMMICAAAsj8ACAAAsj8ACAAAsj8ACAAAsj8ACAAAsj8ACAAAsj8ACAAAsj8ACAAAsj8ACAAAsj8ACAAAsj8ACAAAsj8ACAAAs7/8BN5SXH4lFz5EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create data\n",
    "x = ['A', 'B', 'C', 'D']\n",
    "y1 = np.array([10, 20, 10, 30])\n",
    "y2 = np.array([20, 25, 15, 25])\n",
    "y3 = np.array([12, 15, 19, 6])\n",
    "y4 = np.array([10, 29, 13, 19])\n",
    " \n",
    "# plot bars in stack manner\n",
    "plt.barh(x, y1, color='r')\n",
    "plt.barh(x, y2, left=y1, color='b') # left instead of bottom\n",
    "plt.barh(x, y3, left=y1+y2, color='y') # left instead of bottom\n",
    "plt.barh(x, y4, left=y1+y2+y3, color='g') # left instead of bottom\n",
    "plt.xlabel(\"Teams\")\n",
    "plt.ylabel(\"Score\")\n",
    "plt.legend([\"Round 1\", \"Round 2\", \"Round 3\", \"Round 4\"])\n",
    "plt.title(\"Scores by Teams in 4 Rounds\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41d7aa82",
   "metadata": {},
   "source": [
    "## <a id = 'labels'>Adding labels to our barplots</a>\n",
    "In order to do this, we are going to use `plt.bar_label()` that receives by parameter the `plt.bar()` (or the `ax.bar()` if we are using the OO-style). It works exactly the same with both styles.\n",
    "\n",
    "Let's reuse some of our plots to see how to add labels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "id": "3e2e6f60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#made up data\n",
    "dict_average_heights = {'men': [176, 174, 179, 169, 185],\n",
    "                        'women': [168, 164, 169, 173, 179]}\n",
    "\n",
    "gender_labels = ['men', 'women']\n",
    "country_labels = ['Spain', 'France', 'Portugal', ' Italy', 'Germany']\n",
    "barWidth = 0.25 #necessary for plotting one graph next to each other\n",
    "x = np.arange(len(country_labels))\n",
    "\n",
    "\n",
    "for i, gender in enumerate(gender_labels):\n",
    "    barplot = plt.bar(x + (barWidth * i), dict_average_heights[gender], width = barWidth, color = colors[i]) # <---------\n",
    "    plt.bar_label(barplot, labels =dict_average_heights[gender], label_type = 'edge', rotation = 0) # <-----------------\n",
    "\n",
    "plt.xticks(x + (barWidth / 2) ,country_labels)\n",
    "plt.yticks(np.arange(155, 190, 3))\n",
    "plt.ylim(155, 190)\n",
    "plt.legend(title = 'gender', labels = gender_labels)\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6047871d",
   "metadata": {},
   "source": [
    "This `plt.bar_label()` function has the attribute:\n",
    "- **labels** that receives the data we  want to insert in our barplot\n",
    "- **label_type**: locate where you want these labels. Possible values (edge, center)\n",
    "- **padding**: normally used with `label_type = 'edge'`. Sets a distance between the barplot and the label\n",
    "- **rotation**: Rotate the label the degrees you want.\n",
    "- **color**: set the color of the label\n",
    "- **fontsize**: set the fontsize of the label\n",
    "- **style**: label style. Possible value are: normal (default), italic, oblique\n",
    "\n",
    "Let's see the same example with other attribute's values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "77427f2a",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i, gender in enumerate(gender_labels):\n",
    "    # here I pass the attribute height, which is always going to be the same as labels in the next line\n",
    "    barplot = plt.bar(x + (barWidth * i), height = dict_average_heights[gender], width = barWidth, color = colors[i])\n",
    "    # you can declare the labels here, in the previous line or in both. \n",
    "    plt.bar_label(barplot, labels =dict_average_heights[gender], label_type = 'edge', rotation = 90,\n",
    "                 color = 'c', fontsize = 15, padding = 20) # <-----------------\n",
    "\n",
    "plt.xticks(x + (barWidth / 2) ,country_labels)\n",
    "plt.yticks(np.arange(155, 195, 6))\n",
    "plt.ylim(155, 195)\n",
    "plt.legend(ncol = len(gender_labels), labels = gender_labels,\n",
    "          loc = 'upper left')\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e288368a",
   "metadata": {},
   "source": [
    "<br><br>\n",
    "\n",
    ">**Note**: The ***labels*** attribute passed to `plt.bar_label()` could  be ommitted since it is already passed to `plt.bar()` with the attribute **height**.\n",
    "\n",
    "<br><br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "id": "2b908956",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "player_goals = {'Ronaldo': 567,\n",
    "                'Messi': 601,\n",
    "                'Pele': 439,\n",
    "                'Maradona': 401,\n",
    "                'Zidane': 254,\n",
    "                'Raul': 385,\n",
    "                'Mbappe': 202}\n",
    "\n",
    "#order the dictionary so the barplot is nicer\n",
    "player_goals = dict(sorted(player_goals.items(), key = lambda x: x[1]))\n",
    "players_list = list()\n",
    "goals_list = list()\n",
    "\n",
    "for k,v in player_goals.items():\n",
    "    players_list.append(k),\n",
    "    goals_list.append(v)\n",
    "\n",
    "x = np.arange(0, 650, 50)\n",
    "colors = np.random.rand(len(players_list),3) #the 3 needs to be added because of RGB\n",
    "barplot = plt.barh(players_list, goals_list, color = colors)\n",
    "plt.bar_label(barplot, labels = goals_list, label_type = 'center',style = 'oblique', fontsize = 15)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ebbec8d",
   "metadata": {},
   "source": [
    "### <a id = 'slabels'>Adding labels to a stacked barplot</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "id": "affd2193",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create data\n",
    "x = ['A', 'B', 'C', 'D']\n",
    "y1 = np.array([10, 20, 10, 30])\n",
    "y2 = np.array([20, 25, 15, 25])\n",
    "y3 = np.array([12, 15, 19, 6])\n",
    "y4 = np.array([10, 29, 13, 19])\n",
    "\n",
    "list_y = [y1, y2, y3, y4]\n",
    "colors = ['r', 'b', 'y', 'g']\n",
    "sum_of_y = 0 #variable needed for the stack. I am going to use to sum  y1 + y2... in the bottom attribute\n",
    "\n",
    "for i, y in enumerate(list_y):\n",
    "    if i !=  0: #sum y if you  are not the first stack\n",
    "        sum_of_y += list_y[i-1]\n",
    "    barplot = plt.bar(x, height = y, bottom = sum_of_y, color = colors[i])\n",
    "    plt.bar_label(barplot, label_type = 'center', color = 'white', style = 'italic',\n",
    "                 fontsize = 10, rotation = 0)\n",
    "    # in this example, I decided not to pass the labels attribute because\n",
    "    # as I said, it is already been passed in plt.bar with the heigth attribute\n",
    "\n",
    "\n",
    "# plot bars in stack manner\n",
    "\n",
    "plt.xlabel(\"Teams\")\n",
    "plt.ylabel(\"Score\")\n",
    "plt.legend([\"Round 1\", \"Round 2\", \"Round 3\", \"Round 4\"])\n",
    "plt.title(\"Scores by Teams in 4 Rounds\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f0aa7cc",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "<p style=\"text-align:center\"><b>This notebook has been done by:</b></p>\n",
    "<p style=\"text-align:center\"><i>Javier Coque</i></p>\n",
    "<p style=\"text-align:center\"><i>University of U-tad: Double Degree in software engineering and computational mathematics </i></p>\n",
    "\n",
    "LinkedIn: <a href=\"https://www.linkedin.com/in/javier-coque-92b934278/\">Javier Coque</a>"
   ]
  }
 ],
 "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": "3.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}