Exploratory Data Analyse (EDA).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a0e013ae",
   "metadata": {},
   "source": [
    "### EXPLORATORY DATA ANALYSIS (EDA)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c82f9a16",
   "metadata": {},
   "source": [
    "In the EDA we are going to do some assumptions, do a comprehension of the dataset and check missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d766e308",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "    }\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>Gender</th>\n",
       "      <th>age</th>\n",
       "      <th>education</th>\n",
       "      <th>currentSmoker</th>\n",
       "      <th>cigsPerDay</th>\n",
       "      <th>BPMeds</th>\n",
       "      <th>prevalentStroke</th>\n",
       "      <th>prevalentHyp</th>\n",
       "      <th>diabetes</th>\n",
       "      <th>totChol</th>\n",
       "      <th>sysBP</th>\n",
       "      <th>diaBP</th>\n",
       "      <th>BMI</th>\n",
       "      <th>heartRate</th>\n",
       "      <th>glucose</th>\n",
       "      <th>Heart_ stroke</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Male</td>\n",
       "      <td>39</td>\n",
       "      <td>postgraduate</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>26.97</td>\n",
       "      <td>80.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Female</td>\n",
       "      <td>46</td>\n",
       "      <td>primaryschool</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>28.73</td>\n",
       "      <td>95.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Male</td>\n",
       "      <td>48</td>\n",
       "      <td>uneducated</td>\n",
       "      <td>1</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>245.0</td>\n",
       "      <td>127.5</td>\n",
       "      <td>80.0</td>\n",
       "      <td>25.34</td>\n",
       "      <td>75.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Female</td>\n",
       "      <td>61</td>\n",
       "      <td>graduate</td>\n",
       "      <td>1</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>28.58</td>\n",
       "      <td>65.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Female</td>\n",
       "      <td>46</td>\n",
       "      <td>graduate</td>\n",
       "      <td>1</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>285.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>23.10</td>\n",
       "      <td>85.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  age      education  currentSmoker  cigsPerDay  BPMeds  \\\n",
       "0    Male   39   postgraduate              0         0.0     0.0   \n",
       "1  Female   46  primaryschool              0         0.0     0.0   \n",
       "2    Male   48     uneducated              1        20.0     0.0   \n",
       "3  Female   61       graduate              1        30.0     0.0   \n",
       "4  Female   46       graduate              1        23.0     0.0   \n",
       "\n",
       "  prevalentStroke  prevalentHyp  diabetes  totChol  sysBP  diaBP    BMI  \\\n",
       "0              no             0         0    195.0  106.0   70.0  26.97   \n",
       "1              no             0         0    250.0  121.0   81.0  28.73   \n",
       "2              no             0         0    245.0  127.5   80.0  25.34   \n",
       "3              no             1         0    225.0  150.0   95.0  28.58   \n",
       "4              no             0         0    285.0  130.0   84.0  23.10   \n",
       "\n",
       "   heartRate  glucose Heart_ stroke  \n",
       "0       80.0     77.0            No  \n",
       "1       95.0     76.0            No  \n",
       "2       75.0     70.0            No  \n",
       "3       65.0    103.0           yes  \n",
       "4       85.0     85.0            No  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Display the first few rows\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "629b6f11",
   "metadata": {},
   "source": [
    "Lets check some information in this dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7e1f9761",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4238 entries, 0 to 4237\n",
      "Data columns (total 16 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   Gender           4238 non-null   object \n",
      " 1   age              4238 non-null   int64  \n",
      " 2   education        4133 non-null   object \n",
      " 3   currentSmoker    4238 non-null   int64  \n",
      " 4   cigsPerDay       4209 non-null   float64\n",
      " 5   BPMeds           4185 non-null   float64\n",
      " 6   prevalentStroke  4238 non-null   object \n",
      " 7   prevalentHyp     4238 non-null   int64  \n",
      " 8   diabetes         4238 non-null   int64  \n",
      " 9   totChol          4188 non-null   float64\n",
      " 10  sysBP            4238 non-null   float64\n",
      " 11  diaBP            4238 non-null   float64\n",
      " 12  BMI              4219 non-null   float64\n",
      " 13  heartRate        4237 non-null   float64\n",
      " 14  glucose          3850 non-null   float64\n",
      " 15  Heart_ stroke    4238 non-null   object \n",
      "dtypes: float64(8), int64(4), object(4)\n",
      "memory usage: 529.9+ KB\n"
     ]
    }
   ],
   "source": [
    "#Display the summary information\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2e2a4dfc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Gender              object\n",
       "age                  int64\n",
       "education           object\n",
       "currentSmoker        int64\n",
       "cigsPerDay         float64\n",
       "BPMeds             float64\n",
       "prevalentStroke     object\n",
       "prevalentHyp         int64\n",
       "diabetes             int64\n",
       "totChol            float64\n",
       "sysBP              float64\n",
       "diaBP              float64\n",
       "BMI                float64\n",
       "heartRate          float64\n",
       "glucose            float64\n",
       "Heart_ stroke       object\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Display the data type of the data\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1b31d19b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gender               0\n",
      "age                  0\n",
      "education          105\n",
      "currentSmoker        0\n",
      "cigsPerDay          29\n",
      "BPMeds              53\n",
      "prevalentStroke      0\n",
      "prevalentHyp         0\n",
      "diabetes             0\n",
      "totChol             50\n",
      "sysBP                0\n",
      "diaBP                0\n",
      "BMI                 19\n",
      "heartRate            1\n",
      "glucose            388\n",
      "Heart_ stroke        0\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "#Show the number of missing (NaN values) per column\n",
    "print(df.isnull().sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1cb1edc9",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Gender                2\n",
       "age                  39\n",
       "education             4\n",
       "currentSmoker         2\n",
       "cigsPerDay           33\n",
       "BPMeds                2\n",
       "prevalentStroke       2\n",
       "prevalentHyp          2\n",
       "diabetes              2\n",
       "totChol             248\n",
       "sysBP               234\n",
       "diaBP               146\n",
       "BMI                1363\n",
       "heartRate            73\n",
       "glucose             143\n",
       "Heart_ stroke         2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Show number of unique values per column\n",
    "df.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1560ed5c",
   "metadata": {},
   "source": [
    "##### In a previous analyse is possible to notice:\n",
    "\n",
    "In data.info we can see in this dataset is distributed in 4238 entries and 16 columns. And there are data with different type, being float64(8), int64(4), object(4).\n",
    "\n",
    "In df.type we observed there are float (cigsPerDay,BPMeds, totChol, sysBP, diaBP, BMI, heartRate, glucose), int64 (age, currentSmoker, prevalentHyp, diabetes), object (Gender, education, prevalentStroke, Heart_ stroke).\n",
    "\n",
    "isnull().sum() shows the columns education, cigsPerDay, BPMeds, totChol, BMI, heartRate, glucose presents considerable number of missing values in this dataset.\n",
    "\n",
    "It is also possible to see in df.nunuque() this dataset is not in balance, considering the columns do not have the same number of information.\n",
    "\n",
    "For this project the column education is not relevant, we are goint to deleate it.\n",
    "___"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e6b4899",
   "metadata": {},
   "source": [
    "We are going to separate our categorical, binomial and continuous columns. \n",
    "We do this proccess to prepare it type of data before perform the models and also to normalise them."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0d9dc5c",
   "metadata": {},
   "source": [
    "#### Now we are going to investigate the dataset to get some insigts\n",
    "* Make some plots\n",
    "* Check Correlation\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6751d277",
   "metadata": {},
   "source": [
    "Let us check the number of Heart stroke vs. non-Heart stroke cases in the data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9bb6adb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set white background\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "# Define colors\n",
    "colors = ['#7FB3D5', '#FF5555']\n",
    "sns.set_palette(colors)\n",
    "\n",
    "# Figure with two plots\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(7, 4))\n",
    "fig.patch.set_facecolor('white')  # Set background color for the figure\n",
    "\n",
    "# Plot for Heart Stroke Cases\n",
    "ax1 = sns.countplot(x=\"Heart_ stroke\", data=df, order=df['Heart_ stroke'].value_counts().index, ax=axes[0])\n",
    "#, width=0.7)\n",
    "ax1.set_title('HEARTH STROKE CASES (UNITS)', fontsize=12, fontweight='bold')\n",
    "ax1.set_xlabel('Heart Stroke', fontsize=10)\n",
    "ax1.set_ylabel('Count', fontsize=10)\n",
    "ax1.grid(False)\n",
    "\n",
    "# Remove border around the bar plot\n",
    "for spine in ax1.spines.values():\n",
    "    spine.set_visible(False)\n",
    "\n",
    "# Display the count values on the bars\n",
    "for p in ax1.patches:\n",
    "    ax1.annotate('{:.0f}'.format(p.get_height()), (p.get_x() + 0.30, p.get_height() + 8), fontsize=10)\n",
    "\n",
    "# Plot Pie chart with percentual for Heart Stroke\n",
    "ax2 = plt.subplot(1, 2, 2)\n",
    "df['Heart_ stroke'].value_counts().plot(kind='pie', autopct='%1.1f%%', ax=ax2, startangle=90, explode=(0.1, 0))\n",
    "ax2.set_title('HEARTH STROKE (%)', fontsize=12, fontweight='bold')\n",
    "ax2.set_ylabel('')\n",
    "\n",
    "# Set background color for the subplot\n",
    "ax2.set_facecolor('white')\n",
    "\n",
    "# Show plot\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6b990a3",
   "metadata": {},
   "source": [
    "In the graphic above the number of patients that did not have a heart stroke is 84.8% it is way greater comparated with patients that had a hearth stroke 15.2%. \n",
    "\n",
    "In this plot is also possible to observe our column is imbalance, considering there is a relevant difference between the number of cases and it might bring some inconsistence when apply the models. \n",
    "\n",
    "We are going to add some synthetic data in our training to balance our target variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "94e89821",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set white background\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "# Define colors\n",
    "colors = ['#7FB3D5', '#FF5555']\n",
    "sns.set_palette(colors)\n",
    "\n",
    "# Bar chart for Gender vs Heart Stroke\n",
    "plt.figure(figsize=(8, 4))\n",
    "ax = sns.countplot(x='Gender', hue='Heart_ stroke', data=df)\n",
    "#, width=0.7)  \n",
    "ax.set_title('GENDER X HEART STROKE', fontsize=12, fontweight='bold')\n",
    "ax.set_xlabel('Gender', fontsize=12)\n",
    "ax.set_ylabel('Count', fontsize=12)\n",
    "\n",
    "# Add a line from y-axis to x-axis\n",
    "plt.axhline(0, color='black', linewidth=1)\n",
    "\n",
    "# Remove borders and grid\n",
    "ax.grid(False)\n",
    "for spine in ax.spines.values():\n",
    "    spine.set_visible(False)\n",
    "\n",
    "# Display the count values on the bars\n",
    "for p in ax.patches:\n",
    "    ax.annotate('{:.0f}'.format(p.get_height()), (p.get_x() + p.get_width() / 2, p.get_height() + 8),\n",
    "                ha='center', fontsize=10)\n",
    "\n",
    "# Create a legend \n",
    "legend_handles = [plt.Rectangle((0, 0), 1, 1, color=color, ec=\"k\", lw=0.5, label=label) for color, label in zip(colors, ['No = did not have heart stroke', 'Yes = had heart stroke'])]\n",
    "legend = plt.legend(handles=legend_handles, loc='upper right', bbox_to_anchor=(1.25, 1), title='Heart Stroke', fontsize=10, frameon=True, facecolor='white')\n",
    "legend.set_title('Heart Stroke', prop={'size': 10, 'weight': 'bold'})\n",
    "\n",
    "# Adjust layout \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b98191d",
   "metadata": {},
   "source": [
    "The plot above demonstrate there are more Male cases of hearth stroke being 343 case versus 301 cases for women"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "02a30af3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define colors\n",
    "colors = ['#F5F5F5', '#4F4F4F']\n",
    "sns.set_palette(colors)\n",
    "\n",
    "# Bar chart for Smoking vs Heart Stroke\n",
    "plt.figure(figsize=(8, 4))\n",
    "ax = sns.countplot(x='currentSmoker', hue='Heart_ stroke', data=df)\n",
    "#, width=0.7)  \n",
    "ax.set_title('CURRENT SMOKER X HEART STROKE', fontsize=12, fontweight='bold')\n",
    "ax.set_xlabel('Current Smoker', fontsize=10)\n",
    "ax.set_ylabel('Count', fontsize=10)\n",
    "\n",
    "# Add a line from y-axis to x-axis\n",
    "plt.axhline(0, color='black', linewidth=1)\n",
    "\n",
    "# Remove borders and grid\n",
    "ax.grid(False)\n",
    "for spine in ax.spines.values():\n",
    "    spine.set_visible(False)\n",
    "\n",
    "# Display the count values on the bars\n",
    "for p in ax.patches:\n",
    "    ax.annotate('{:.0f}'.format(p.get_height()), (p.get_x() + p.get_width() / 2, p.get_height() + 8),\n",
    "                ha='center', fontsize=10)\n",
    "\n",
    "# Create a legend \n",
    "legend_handles = [plt.Rectangle((0, 0), 1, 1, color=color, ec=\"k\", lw=0.5, label=label) for color, \n",
    "                  label in zip(colors, ['No = did not have heart stroke', 'Yes = had heart stroke'])]\n",
    "legend = plt.legend(handles=legend_handles, loc='upper right', bbox_to_anchor=(1.25, 1), \n",
    "                    title='Heart Stroke', fontsize=10, frameon=True, facecolor='white')\n",
    "legend.set_title('Heart Stroke', prop={'size': 10, 'weight': 'bold'})\n",
    "\n",
    "# Replace labels\n",
    "ax.set_xticklabels(['No Smoker', 'Smoker'], fontsize=10)\n",
    "ax.set_yticklabels(ax.get_yticks(), fontsize=10)  # Set font size for y-axis labels\n",
    "\n",
    "# Adjust layout \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8e79748",
   "metadata": {},
   "source": [
    "In this plot show the number of heart stroke for No smoker and Smoker, there is slightly different between them which people that had the habit of smoke were more susceptible to have hearth stroke being 333 cases of heart stroke versos 311 case for no smokers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "585d5ff4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+FkVEcoPu7ItYgKSkJKKiooiOjjYtC9m7d2+WLFlyx08GDQ8PN03PadSoUbZ1bs0ZT0xM5McffzQru3LlClFRUURFRREXF4eTkxMVKlTgiy++MD0kebu4uDhT/X9+Pey0iNTU1Du2mZiYCNy88/v999/TvHlzihQpQnJyMra2tpQtW5aBAwfy5Zdf3rH9cePGce3aNaytrQkKCjJd3Nz6FFV7e3uSk5MZNmxYlgc8/627na/U1FTTUpP169fP9kHfV199lfz58wP3fmfmmWeeMV3MXbhw4a7n5H6NHj2aUaNGUb58eezt7UlMTOSZZ56hUaNGfP/993h7e//rPm6xtrZm/PjxODg4kJGRwejRo02vR/v27fn+++9p2rQpRYoUIT4+HgcHB6pUqUJQUBDz58+/rwsbJycnBg0aBEBycjIjR440K7+fn0URkdxgZTzq/6FEREREROSJoDv7IiIiIiIWSmFfRERERMRCKeyLiIiIiFgohX0REREREQulsC8iIiIiYqEU9kVERERELJTCvoiIiIiIhVLYFxERERGxUAr7IiIiIiIWSmFfRERERMRCKeyLiIiIiFgohX0REREREQtlm9sDkP+OvXv3Mm3aNE6dOoWTkxONGjVi4MCBODo6Mnr0aFatWoWdnZ2p/pAhQ2jbti2GYTBr1ixWrVpFXFwcxYsXp1evXjRq1AiAmJgYatasibOzs2lfV1dXtm7dmuPHKCIiIvIkUdiXHHHlyhW6devGmDFjaNGiBTExMbz//vvMnTuXPn36cPToUYKCgmjZsmWWfb/55htWr17NV199RenSpdm2bRsffvghxYoVo0KFChw9epTixYsr3IuIPAKZmZmkpqbm9jBE5C7s7e2xtr6/CToK+5Ij3Nzc2LNnDy4uLhiGQVxcHDdu3MDNzY3U1FROnDhBuXLlst33+vXr9OrVixdffBGAunXr8uKLL3Lo0CFT2L/TviIicv9SU1M5ffo0mZmZuT0UEbkLa2trSpUqhb29/T3rKuxLjnFxcQGgdu3aREVF4e3tjZ+fH+Hh4aSnp/PFF19w8OBB8ubNS6tWrejcuTPW1tb06dPHrJ1Tp05x8uRJypYtC8DRo0e5du0aTZs2JSYmhvLlyzN48GDc3d1z/BhFRJ5WhmHw999/Y2NjQ4kSJe77rqGI5KzMzEwuXrzI33//TcmSJbGysrprfYV9yXFbtmzh2rVrDBgwgD59+vDee+/h4+NDYGAg06ZN488//6RXr15YW1vTuXNns31Pnz5Nly5daN68OVWrVgUgX758uLu706VLF+zt7Zk+fTrvvfceGzduJG/evLlxiCIiT5309HSSkpIoVqyY2TNQIvLkKVy4MBcvXiQ9Pd3secfsWBmGYeTQuETMHDlyhNatW7N//37y589vVjZv3jw2btzI6tWrTdu2bt3KkCFD8PPzY/DgwXe8ks3MzMTb25upU6dSp06dx3oMIiKWIiUlhdOnT/PCCy/g5OSU28MRkbtITk7mzJkzlCpVCkdHx7vW1Xt0kiMOHTpEo0aNzB76Sk1Nxc7Ojt27d7Ns2TKz+qmpqWY/vDNnzqR///6MHDmSIUOGmIJ+QkICkydP5sKFC6a6GRkZpKen3/OHX0REsrrXlAARyX0P8nuaK2F/7969tG7dmsqVK1OzZk2CgoJISUkBYPTo0ZQrVw4vLy/T1/Lly037rlmzhvr161OpUiX8/PwICwszlWVkZDB58mRq1KiBl5cXPXr0IDo6+o7jOH36NB06dMDLy4tatWoxe/bsx3fQ/3Genp6kpKQwdepUUlNTuXDhApMnT8bf3x87OzsmTpzI3r17MQyDsLAwFi1aRNu2bQFYsGABCxYsYOnSpTRr1sysXRcXF/bs2cPkyZOJj48nMTGRoKAgnnvuOby9vXPjUEVERHJURETEI2nn1KlTj6QdecIYOSw2NtYoX768sWrVKiMjI8OIiooymjZtakyfPt0wDMNo2bKlsXr16mz33bdvn+Hl5WUcOHDASE1NNRYsWGD4+voaSUlJhmEYxowZM4xmzZoZFy9eNOLj440PP/zQ6NKlS7ZtpaamGg0aNDA+/fRT48aNG8axY8eMWrVqGRs3bnw8By7GyZMnjffee8/w9vY26tSpY0ybNs24ceOGYRiG8d133xkNGjQwKlasaLzxxhvGkiVLDMMwjMzMTKNKlSrGK6+8YlSqVMnsKzg42DAMwzh//rzRq1cvw8fHx/Dy8jK6d+9unD9/PteOU0TkaZScnGz88ccfRnJycm4P5anj4eFhVKpU6b63P0r9+/c3vLy87lpn0aJFRtOmTY3y5csbVatWNVq3bm2Wd/7++2+jbdu2RteuXf/1eOrUqWN4eHgYsbGx/7otubMH+X3N8Qd0/80SjCtWrKBJkyZUqVIFgI4dO7J8+XI2btxIq1atWLFiBQMGDKBo0aIADB8+nFq1ahEZGUmJEiXM2goNDSU6Opo+ffpgb2/PK6+8QmBgIEuXLuXNN998vCfhMTEM44l++9Xd3Z358+dnW/b222/z9ttvZ9luZWXFgQMH7tpu8eLF+fLLLx/JGHPSk/56iYjIk2/9+vV3faB66dKlfPzxx5QpU4aOHTuSnJzM2rVr+fDDD3F2dqZ27dqcPXuWsLAwXn/99ZwbuOSYXFmN52GXYIyIiKBVq1Zmbbm7uxMeHk58fDyXLl3Cw8PDVFaoUCHy58/P8ePHs4T9kydPZlmf1N3dnblz5z7GI3+8rKysuHHjhtZHfgpYW1vj4OCQ28MQEZFHxDAMzp49e9c6Z8+eZcKECRw8eBA7OzuaNm3KwIEDTVlk7ty5LFu2jOjoaJydnalWrRrjxo2jQIECDBkyhDVr1tCxY0fWrl2Lm5sbiYmJACQlJeHp6cmiRYvw9fU16/Pw4cMA9OrVy3Qzs2bNmnz33XdcvHiR8+fP8+677wKwfft2PD09OX78OIGBgezfv5/OnTvz/fffU65cORYsWMCxY8eYNm0aYWFhODo6UrlyZQYOHMjzzz+f5Xj/+OMP2rdvj2EYzJ8/Hy8vr3ueA3n0cnXpzQddgjExMTHLCgGOjo4kJSWZfuD/eXXr6OhoKrtddm05OTmRlJT0iI8yZ2VmZmJogaUnni7IREQsS3JyMg0aNLhr+Xvvvcfly5dp3bo1V69eZdGiRaSmpjJ27Fg2b97M1KlTKVu2LM2aNSMkJITNmzfj4eHBBx98YGpn1apVtGrViqJFi2Jra0tQUBB2dnb07NmT5557Lku/DRo0YO3atXz00Ud88803+Pr6UrVqVWbOnImtrS3x8fG0atWKVatWUapUKZo3b262/7p16/D398fDw4O//vqL9u3bk5aWhp+fHxkZGfzwww+EhISwZs0as/4jIyPp2bMnGRkZzJkzBy8vr3ueA3k8cjXsOzo64ujoyMCBA2ndujVTp05l0aJFpvIKFSrQoUMHNm7cSOfOnXFycjI9yHtLSkoKrq6upuCenJycpTxPnjxZ+nZ2ds5SNzk5Odu6IiIiInfj4ODAJ598Yratb9++pn9v376dCxcu0Lx5czp06ADcnGWwevVqhgwZwhtvvMGPP/6Iq6srMTExpKamEhYWxt9//23W5rvvvmv2YZO3h/3s1KtXj5kzZ/LNN99w6NAhwsLCmD17NkWLFuWLL76gQoUKvPXWW6xatYrnn38+SzsffvihaVbFmDFjSEpKYvDgwXTq1AmAokWLMmPGDJYsWcKQIUNM+/Xq1YuYmBjGjBlDtWrV7uscaMnXxyPHw/6hQ4cYNmwY69atM71lc/sSjNevXzebu337EoxlypTh5MmTZu1FRETw2muvkT9/fooUKUJERIRpKs/ly5eJi4szm9pzS5kyZThz5gzp6enY2tqa2ipTpsxjOW4RERGxXDY2NjRq1OiO5efPnwdu3ilft26dWdlff/1F8eLFmTlzJtu3b6dgwYI8++yzwM2VBm+X3XSZu0lLS6NSpUrUq1ePxMREDh8+zA8//MDatWsZN24cK1euvOv+t/cXGRkJ3LwZe0v58uUBzJbABrhy5QoAP/74I++88w5w73NQtmzZBzo2uT85HvZvX4Kxf//+XL58OcsSjM8//zzVqlXjt99+Y9GiRQwdOhQAf39/05yzKlWqsHTpUmJjY6lfvz4Afn5+BAcHU758eVxdXZkwYQI+Pj6ULFkyyzh8fX1xdXVl6tSpfPjhh5w+fZrFixfTr1+/HD0fIiIiYvmeeeYZAOrWrctbb70F3LyrXbRoUYoWLcqECRPYuHEj06ZNo0mTJmzatInQ0NAs7WT3vNfdpu/WrVuX6Oho1q1bh6enJzVq1MDd3Z21a9ea3jW4tVhEdu3c3t+taTq///67aXnr33//HSDLs5ETJkxg27Zt/PTTT2zYsIGmTZve8xzI45HjYT9PnjzMmzePCRMmULNmTfLmzUuzZs3o1asX9vb2DB06lDFjxhAVFUWhQoXo3bu36QeievXqjB492lTu7u7OV199RYECBYCbbxmlp6cTEBBAYmIivr6+fP7556a+O3fuTLFixRg3bhy2trbMnz+fcePGUbNmTZydnQkMDMTPzy+nT4mIiIhYuDfeeIOCBQuyb98+ihcvTnJyMqtWreKFF16gZcuWpme5Fi5cyLFjx1izZg2A2YdRZidPnjwkJSUxYcIE/Pz8eOmll8zKAwMDmTp1Kh07dqRZs2bY29vz888/A9CwYUNTG3DzgdqJEycyYMCAbPtq164da9asYcqUKfz1119kZmayZs0aChQoQGBgoFnd1157japVq7J9+3Y++eQT6tate89zII+HlaGnOS1KcnKyHtB9ClhZWWluoog8UVJSUjh9+jSlSpXSJ5A/IE9PT5ydnc0+6DO77eHh4UyaNInffvsNGxsbqlatysiRIylevDgXLlxgyJAhHDlyhHz58tG0aVOWLl3KM888wy+//GJajWf69Olm04Xmzp3LV199hWEYTJ06ldq1a2cZ33fffcf333/PuXPnSE1NpXjx4jRp0oTu3btjZ2dHZmYmffv2ZefOneTNm9e0NOf+/ftZuXKlaaoOwJEjR5g+fTphYWE4ODhQtWpVBg4caLqzX7duXS5cuMDevXtxc3Nj+vTpzJo1iy5dujBgwIC7ngO5fw/y+6qwb2EU9p8OCvsi8qRR2Bd5ejzI76t1Do1JRERERERymMK+iIiIiIiFUtgXEREREbFQCvsiIiIiIhZKYV9ERERExEIp7IuIiIiIWCiFfRERERERC6WwLyIiIiJioRT2RUREREQslG1uD0BERESeXB988AHXr1/Psf7y5cvHl19+mWP9WbozZ87wwgsv5PYwnjgPe15u3LjB1atXefbZZx/9oB4ThX0RERG5o+vXrzN79uwc66979+4PVN/T05PatWszZ84crKysTNtXr17Nl19+ydatWx/1EO9L3bp1+eCDD/Dz86Nz5854e3vf8dg8PT1ZtGgRvr6+j3QMf/zxB23atOH333/PtjwwMBAfHx969+79SPt9UEOGDAFg0qRJOdLf0qVL+emnn1i8ePED79uuXTsCAgLw8/N7qL5v/7nIKQr7IiIi8lTbsWMH8+bNo0uXLrk9lGzNmzcvV/qNj48nLS0tV/p+kl25cuWh97169eojHEnO0Jx9EREReaoFBgYyffp0Dh06dMc6x48fp0uXLvj4+PDaa68xZswY4uPjs607atQovLy8sv3KjmEYzJ49m1q1auHt7c3kyZPJyMgwG9+MGTMASEtLY+LEifj6+lKtWrV7Xgh4enqyePFiGjZsiJeXF2+//TbHjx83lR84cICAgAC8vb2pW7cun3/+OampqURGRpoufry8vAgLC8u2/bNnz9KpUyeqVq3KG2+8wU8//WQqO3ToEO+++y61atWifPny+Pn58dtvvwEQEBDAtGnTzNpq3bq16XiOHTtGYGAgVatWpUGDBixcuBDDMO54nLGxsfTp0wdfX19q1arFkiVLTGUJCQmMGzeO2rVrU716dfr160dMTIypfOvWrbz99ttUr16dihUr0r59e86cOQPcfIfHz8+PTp064e3tzZo1a5gzZw4HDhzA29s727F8++231KtXD29vb5o1a8aKFSsA6NSpExcvXmT06NGMGzeOkJAQateuTf/+/fH29mbu3LlkZmYyd+5c6tWrR5UqVfD392fXrl3Z9rNr1y6qVKnCpk2bAIiJiWHAgAHUrFmTWrVqMWrUKBISEu54zu6Xwr6IiIg81erXr0/btm356KOPiIuLy1J+9epV3n33Xdzd3dm5cyerVq3i9OnTDBo0KNv2xo0bR1hYWLZf2Vm1ahXffPMNc+bMYc+ePdjZ2XHp0qVs686aNYvt27ezcuVKtm7dyokTJ+55fD/++CNLlixh586dODk58cknnwDw119/8d5779GgQQP27NnDggUL2Lp1K5988gklSpTgq6++AiAsLOyOFyq7d++mf//+hISE4Ofnx9ChQ0lLSyMlJYUePXrQsGFDdu7cSUhICCVLljT13bp1a9atW0dmZiYAp06d4s8//6RFixZERUXRoUMHGjVqxJ49e5g1axbffvsty5cvv+Mx7tu3j7fffpt9+/bRv39/Pv74Y6KiogAYNmwYZ8+eZfXq1fzyyy+4uLjwwQcfYBgGly5dom/fvnTt2pW9e/eyfft2DMNg5syZpraPHTtGs2bN2LNnD2+++SbdunXD29ubAwcOZBlHZGQkEydOZO7cuRw4cIBBgwYRFBREdHQ08+fPp1ixYowdO5ZRo0YBcOnSJUqXLs3evXtp164dM2fOZOnSpUyfPp2QkBA6depEz549OXLkiFk/O3bs4KOPPmLatGm8+eabZGZm0rNnT6ytrdm8eTPr168nOjra1M+/obAvIiIiT73Bgwfj5ubGkCFDstxB/t///oednR0DBgzA0dGRwoULM3LkSLZu3crly5f/dd9r166lTZs2lC1bFnt7e/r27Yurq+sd677//vuUKFECZ2dnRowYYfasQXYCAwMpXLgwefPm5c033zTdtV6/fj2enp506NABe3t7nn/+efr378+KFStMIfxeGjduTNmyZbG2tqZx48YkJSURGxuLnZ0dy5cvp127dqSmpnLhwgUKFChgCuCNGjUiMTGRkJAQ4OYd9Nq1a1OoUCHWrVvHiy++SEBAAHZ2dri7u/P++++zdOnSO46jZs2a1KhRAysrK5o0aYJhGERGRhIbG8vmzZsZPnw4BQsWJE+ePAwbNoyjR49y7Ngx3Nzc+PHHH6lbty4JCQlcunQJV1dX0zgB7OzseOutt7C3t8fR0fGu58PGxgbDMFi2bBkHDx6kevXq/PbbbzzzzDN33Mff3x87OztcXFxYtWoVXbt2pWzZstja2tK4cWPq1q3LypUrTfV37NhBr169GDt2LLVr1wbg999/59ixY4wePRoXFxdcXV0ZPHgwP/7447+eOqQ5+yIiIvLUs7e35/PPP6dly5bMnz/fLGzHxsZSrFgxbGxsTNuee+45AC5cuEDhwoXN2hozZgwbNmzItp/s7gZHR0dTtGhR0/c2NjYUK1Ys2/3/WTdfvnzkz5//rsdWqFAh079tbW1NFzOxsbGUKFHCrO5zzz1HSkoKsbGxd23zlgIFCpj+bWdnB0B6ejo2NjaEhITQpUsXkpKScHd3N+vb0dGRZs2a8cMPP+Dj48O6desICgoCbp7TY8eOmU2TyczMNDv/dxuHvb09ABkZGVy4cAGANm3amNW3sbHh/PnzlC1blg0bNrBs2TKsrKzw8PAgISEBW9v/j7iFCxfG2vr+7m8XK1aMxYsXM2/ePLp3705GRgZ+fn4MHDgQBweHbPe5/UIgJiYm29ckPDzc9P3evXspW7Ysa9asoXHjxgCcP3+ejIwMU/i//VxERkbe8eLxfijsi4iIiEUoWbIkQUFBDBo0yGy1k+LFi3Px4kUyMjJMgfPcuXMAWYI+3Az7Y8aMue9+n332WSIjI03fG4ZBdHT0fdVNSkq647MD91K8eHG2bNlitu3cuXPY29vf8wLiXg4fPkxQUBDLli2jXLlyAMyfP5/Tp0+b6rRp04Z33nmH+vXrY2VlxauvvgrcPEZfX1++/vprU92rV6+SmJj4wOMoUqQIAJs2bTJ7rSIiIihRogSbNm1iyZIlfPfddzz//PMABAUFmU2Putc7J7eLjY0lIyODmTNnkpmZyaFDh+jTpw+lSpUiICAg231ub7948eJmry/cnBp0+wVB//79ef3112nSpAnLli3j7bff5tlnn8XR0ZGQkBDTz+itZy9uHdfD0jQeERERsRiNGzemVatWZvPDb90tnTJlCikpKVy+fJnx48dTrVo1ihcv/q/7bN26Nd9//z1hYWGkpaURHBx8x+lBtx5iPXXqFDdu3GDSpElmD/M+iCZNmnDq1Cm++eYbUlNTOXfuHNOmTaNZs2bY29ub7kQ/zMVEfHw81tbWpmkvv/32G4sWLSI1NdVU56WXXqJ06dJMmDCBli1bmkJqs2bN+O2331i3bh3p6elER0fTvXv3h1pas0iRIrz++uuMHz+eq1evms6vv78/169fNxunYRjs3LmTH3744a6rEDk4OJCQkJDtA8MXL16kU6dO7N27F2tra9PFxq076/b29nc9n61bt2bu3LkcO3aMjIwMNm3axNatW2nZsqWpjp2dHUWKFGHo0KFMnjyZc+fOUaFCBZ5//nkmTZpEYmIiKSkpTJgwgY4dOz70z8ctCvsiIiJiUYYNG8bLL79s+j5v3rwsWLCAEydOULt2bZo2bUrx4sWZPn36I+mvadOm9OnTh379+uHj40NkZCSenp7Z1u3SpQvNmzenffv21KpVi7x585pNYXkQzz33HPPmzWPz5s3UqFGDdu3aUbNmTdNDnR4eHlSpUoVXX32VHTt2PFDbNWvWNK0pX7VqVcaOHUtgYCBXrlwxWwmnTZs2XLx4EX9/f9O24sWLM2/ePJYvX06NGjV46623KF269EOvo//JJ5+QL18+WrRoQbVq1UxLrRYuXJiWLVtSo0YNmjRpQrVq1QgODqZDhw6cPn3a7MLkdnXq1CEuLo4qVapk+cC48uXLM2rUKMaMGYOXlxcBAQG0a9eON998E7g5P/+zzz5jwIAB2bb93nvvERAQQL9+/fD29mbOnDlMmzYNHx+fLHVbtWpF1apVGTx4MNbW1syZM4eYmBgaNGhArVq1OHfuHAsWLLjj9KH7ZWXcbR0keeokJyffdWkreTJYWVnh5OSU28MQETFJSUnh9OnTlCpVyuwhRn2CrsiT506/r9nRnH0RERG5IwVvkaebpvGIiIiIiFgohX0REREREQulsC8iIiIiYqEU9kVERERELJTCvoiIiIiIhVLYFxERERGxUAr7IiIiIiIWSuvsi4iIyB317hFA/NW/c6y/vK5FmRG8NMf6k4dz5swZXnjhhQfeLyMjg4sXL1KiRIlHPyjJVq6E/b179zJt2jROnTqFk5MTjRo1YuDAgTg6OnL48GE+/vhjIiIicHV1pUePHrRu3dq075o1a5g1axaXL1+mdOnSjBw5Ei8vL+DmD9CUKVNYu3YtycnJVKtWjbFjx/LMM89kO47Tp08zZswYjhw5Qp48eWjfvj3du3fPkXMgIiLyNIi/+jcLByfnWH8dJ9//hcWYMWP4+eefWbduHQULFjRtT09Pp127dri6ujJ79mysrKwex1DvasiQIQBMmjTpkbQ3Y8YM9u/fz+LFix+o7HHYunUr48eP53//+98D79uvXz/KlClD7969H6rvwMBAfHx8Hnr//6Icn8Zz5coVunXrxjvvvMOBAwdYs2YN+/fvZ+7cuVy7do2uXbvSokULQkNDGT9+PBMnTuTIkSMAhISEEBQUxKRJkwgNDaV58+b06NGD5OSbf4SCg4PZvXs3q1atYteuXTg6OjJixIhsx5GWlkb37t0pX748ISEhzJ07l6VLl7Jp06YcOxciIiLy8IYOHUqhQoUYOnSo2fYZM2YQExPD5MmTcyXoW7q4uDgMw3iofa9evfqIRyP3kuNh383NjT179uDn54eVlRVxcXHcuHEDNzc3tmzZQoECBQgICMDW1pbq1avTrFkzli69+XbeihUraNKkCVWqVMHOzo6OHTvi6urKxo0bTeVdunShaNGiuLi4MHz4cHbu3ElkZGSWcYSGhhIdHU2fPn2wt7fnlVdeITAw0NSXiIiIPNkcHBz47LPPCA0NNd3V3r9/PwsXLuTzzz+nQIECnDt3ju7du+Pr60udOnX47LPPSE1NBSAhIYF+/frh6+tLzZo1ef/99zl16lS2fXXu3BkvL68sX02aNLnj+GJjY+nTpw++vr7UqlWLJUuWmMpOnTpFt27deP3116lQoQKNGzdm27ZtpvJDhw7RqlUrKlWqxNtvv8358+fvei4SExMZMWIEtWrVwtfXl88++8xUlpqayvTp03njjTfw8fGhS5cunD171qyvd999l1q1alG+fHn8/Pz47bffgJs3WmvXrk3//v3x9vZm7ty5jB49mosXL+Ll5UVUVFSWsWzevNmU1958801mzZoFwPDhwzlw4ABz5syhe/funD9/Hk9PTyZNmkTVqlUZO3Ys8P95r3LlyjRr1ox169Zle8x//PEH1apVY+HChcDN13PcuHHUrl2b6tWr069fP2JiYu563v4LcuUBXRcXFwBq165Ns2bNKFy4MH5+fpw8eRIPDw+zuu7u7oSHhwMQERFxx/L4+HguXbpkVl6oUCHy58/P8ePHs4zh5MmTlCpVCnt7+2z7EhERkSdf6dKlGTVqFFOnTuXPP/9kyJAhDBo0iAoVKpCUlETHjh0pU6YMO3fu5Ntvv2XPnj3MmDEDgPnz55OQkMCOHTvYtm0bhQsXZsqUKdn2M2/ePMLCwrJ8/fjjj3cc2759+3j77bfZt28f/fv35+OPPzaF4969e+Ph4cHPP//MgQMHqFWrFmPGjAFu3v3u1q0bDRs2JDQ0lIEDB/LLL7/c9Tz88ccfVK1alV27djF9+nTmzJlDWFgYAJ999hnbt29n4cKF7Nq1i4oVK9KpUydu3LhBSkoKPXr0oGHDhuzcuZOQkBBKlizJJ598Ymr70qVLlC5dmr1799KuXTvGjh1LsWLFCAsLo0iRImbjSElJYeDAgYwaNYqDBw8ydepUvvrqK44cOcL48ePx9vamW7duzJ4927RPYmIiu3fvpl+/fqxevZpJkyYxYsQIQkNDGTZsGGPHjuXnn3826+f333+nU6dO9O/fn44dOwIwbNgwzp49y+rVq/nll19wcXHhgw8+eOh3ISxFrq7Gs2XLFnbu3Im1tTV9+vQhMTERJycnszqOjo4kJSUB3LU8MTERAGdn5yzlt8pul11bTk5Opr5ERETk6dCyZUsaNGjA22+/jZeXFwEBAQBs376d1NRUPvroIxwcHChatCh9+/Y1vYvv6OhIeHg4P/zwA1FRUUyYMIHg4OBHNq6aNWtSo0YNrKysaNKkCYZhmGYbzJkzh969e2MYBhcuXCBfvnymC4Ht27fj5OREly5dsLOzo0qVKrRq1equfZUpU4a33noLKysrqlWrRqFChTh37hyGYbBs2TI++ugjSpQogYODA7169SItLY3t27djZ2fH8uXLadeuHampqVy4cIECBQpkuWPv7++PnZ2d6Ybt3Tg6OrJy5Ur27t3Liy++yMGDB6lQocId67do0QJ7e3vy5cvHqlWraNu2LdWrV8fGxobq1avTtm1bli1bZqp/7Ngx3nvvPd5//33Tc52xsbFs3ryZ4cOHU7BgQfLkycOwYcM4evQox44du+eYLVmursbj6OiIo6MjAwcOpHXr1gQGBhIfH29WJyUlhTx58gA3w3hKSkqWcldXV1NwvzV/P7v9b+fs7JylbnJycrZ1RURE5Mn2wQcfsHbtWvr27WvaduHCBa5cuULVqlVN2wzDIC0tjdjYWLp06YK9vT0rV65k3LhxlChRgv79+9OgQYMs7Xfr1o2DBw9m2V60aFHWr1+f7ZgKFChg+vetmQQZGRkAhIeH07NnTy5fvsyLL76Im5ub6Q50VFQURYsWNXveoGTJkvz55593PP7b+7rVX0ZGBleuXCEpKYm+fftibf3/93jT0tK4cOECNjY2hISE0KVLF5KSknB3d8fW1jbL3fA7LXbyT46Ojnz33XfMmjWL/v37k5CQQMOGDRkxYgT58+fPdp/b246JicmyUs9zzz3H1q1bTd/v2bMHLy8vNmzYQIcOHbC3t+fChQsAtGnTxmxfGxsbzp8/T7ly5e5r/JYox8P+oUOHGDZsGOvWrTP94KempmJnZ4e7uzu7d+82qx8REUGZMmWAm1etJ0+ezFL+2muvkT9/fooUKWI21efy5cvExcVlmfpzq60zZ86Qnp6Ora1tlr5ERETk6XEryN4eaJ999llKlizJTz/9ZNqWkJBAbGwsbm5uHD9+nLp169KxY0fi4+P59ttv6devH/v27SNv3rxm7c+ZM+eRjTUqKoq+ffvy5ZdfUrduXeDmPPctW7aYxn3hwgUyMzNNx3Pp0qWH6svV1RUHBwfmz59PpUqVTNv/+usvihQpwuHDhwkKCmLZsmWmQDx//nxOnz5t1s79PuickJBAdHQ0U6dOBeDPP//ko48+Yvbs2QwePDjbfW5v+7nnnuPcuXNm5ZGRkRQuXNj0fceOHenWrRvNmjVjxowZ9O/f3zSdaNOmTWZ1IyIi/vPLfOb4NB5PT09SUlKYOnWq6e2iyZMn4+/vT8OGDYmJiWHhwoWkpaWxb98+1q9fb3rryt/fn/Xr17Nv3z7S0tJYuHAhsbGx1K9fHwA/Pz+Cg4OJjIwkISGBCRMm4OPjQ8mSJbOMw9fXF1dXV6ZOncqNGzcIDw9n8eLF+Pv75+j5EBERkcejTp06JCYmMm/ePFJTU7l+/TqDBw+mX79+WFlZsWLFCgYNGkRsbCwuLi64uLjg7Oxs9jzf45CYmEhGRoZpVkJERAQzZ84Ebt4ArVu3LoZhMGPGDFJTU/n9999ZsWLFQ/VlbW2Nv78/U6dO5dKlS2RmZrJmzRqaNm3K2bNniY+Px9raGkdHRwB+++03Fi1aZHqIOTsODg4kJyeTnp6e7bF16dKF9evXYxgGzzzzDNbW1ri6ugI333H45yyO2/n7+7N8+XL27t1LRkYG+/btY/ny5WbTmOzs7MiTJw/jx49n/vz5HDp0iCJFivD6668zfvx4rl69SlpaGsHBwfj7+3P9+vWHOneWIsfDfp48eZg3bx4nT56kZs2aBAYGUqNGDYYNG4arqyvz58/np59+wtfXlxEjRjBixAiqVasGQPXq1Rk9ejRjxozBx8eHH3/8ka+++sr01lWvXr2oXbs2AQEB1K5dmxs3bvD555+b+u7cuTOjRo0CwNbWlvnz53PixAlq1qxJ165dCQwMxM/PL6dPiYiIiDwGLi4uLFy4kJCQEF577TXq1auHtbW1aV7+Rx99xPPPP29a+WX16tXMmjULBweHxzqu0qVLM2jQIAYOHEiVKlXo27cvrVq1ws7OjhMnTpAvXz6+/vpr9u7di4+PD8OHD6dhw4YP3d/gwYOpWLEi7dq1w9vbm4ULF/LFF1/wyiuvULNmTdq1a0dAQIBpRZzAwECuXLlyx5VsqlatSsGCBalatWqWRVCKFCnCF198wVdffUXlypVp2rQp1apVMz1E26JFC1atWkW7du2ybfvNN99k6NChfPzxx3h7ezNmzBgGDRpEixYtstStXr06rVu3ZvDgwSQlJfHJJ5+QL18+WrRoQbVq1dixYwfz5s0zu9P/X2Rl/NcfUbYwycnJ//mnzp8GVlZWWR4QFxHJTSkpKZw+fZpSpUqZ7vKCPkFX5El0p9/X7OTqA7oiIiLyZFPwFnm65erSmyIiIiIi8vgo7IuIiIiIWCiFfRERERERC6WwLyIiIiJioRT2RURExEQruok8+R7k91RhX0RERLCxsQG464cpiciT4dbv6a3f27vR0psiIiKCra0tzs7OXL58GTs7O6ytdT9Q5EmUmZnJ5cuXcXZ2xtb23lFeH6plYfShWk8HfaiWiDyJUlNTOX36NJmZmbk9FBG5C2tra0qVKoW9vf096yrsWxiF/aeDwr6IPKkyMzM1lUfkCWdvb3/f775pGo+IiIiYWFtb4+jomNvDEJFHRBPyREREREQslMK+iIiIiIiFUtgXEREREbFQCvsiIiIiIhZKYV9ERERExEIp7IuIiIiIWCiFfRERERERC6WwLyIiIiJioRT2RUREREQslMK+iIiIiIiFUtgXEREREbFQCvsiIiIiIhZKYV9ERERExEIp7IuIiIiIWCiFfRERERERC6WwLyIiIiJioRT2RUREREQslMK+iIiIiIiFUtgXEREREbFQuRL2w8PDee+99/Dx8aFmzZoMGjSIK1euADB69GjKlSuHl5eX6Wv58uWmfdesWUP9+vWpVKkSfn5+hIWFmcoyMjKYPHkyNWrUwMvLix49ehAdHX3HcZw+fZoOHTrg5eVFrVq1mD179uM7aBERERGRHJbjYT8lJYXOnTvj5eXFr7/+yoYNG4iLi2PYsGEAHD16lKCgIMLCwkxfbdu2BSAkJISgoCAmTZpEaGgozZs3p0ePHiQnJwMQHBzM7t27WbVqFbt27cLR0ZERI0ZkO460tDS6d+9O+fLlCQkJYe7cuSxdupRNmzblzIkQEREREXnMcjzsX7x4kZdeeolevXphb2+Pq6srbdu2JTQ0lNTUVE6cOEG5cuWy3XfFihU0adKEKlWqYGdnR8eOHXF1dWXjxo2m8i5dulC0aFFcXFwYPnw4O3fuJDIyMktboaGhREdH06dPH+zt7XnllVcIDAxk6dKlj/X4RURERERySo6H/dKlSzNv3jxsbGxM2zZv3kzZsmUJDw8nPT2dL774gho1atCwYUPmzp1LZmYmABEREXh4eJi15+7uTnh4OPHx8Vy6dMmsvFChQuTPn5/jx49nGcfJkycpVaoU9vb2WdoSEREREbEEtrnZuWEYfP7552zbto0lS5YQExODj48PgYGBTJs2jT///JNevXphbW1N586dSUxMxMnJyawNR0dHkpKSSExMBMDZ2TlL+a2y22XXlpOTE0lJSY/4KEVEREREckeuhf2EhASGDh3KsWPHWLJkCZ6ennh6elKzZk1TnQoVKtChQwc2btxI586dcXJyIiUlxaydlJQUXF1dTcH91vz928vz5MmTpX9nZ+csdZOTk7OtKyIiIiLyNMqV1XjOnTtHq1atSEhIYOXKlXh6egLwyy+/sGzZMrO6qampODo6AlCmTBlOnjxpVh4REUGZMmXInz8/RYoUISIiwlR2+fJl4uLiskz9udXWmTNnSE9Pz9KWiIiIiIglyPGwf+3aNTp06EDlypX5+uuvcXNzM5UZhsHEiRPZu3cvhmEQFhbGokWLTKvx+Pv7s379evbt20daWhoLFy4kNjaW+vXrA+Dn50dwcDCRkZEkJCQwYcIEfHx8KFmyZJZx+Pr64urqytSpU7lx4wbh4eEsXrwYf3//nDkRIiIiIiKPmZVhGEZOdrhgwQImTZqEk5MTVlZWZmVhYWEsW7aMBQsWEBUVRaFChXjvvfcICAgw1Vm7di3BwcFERUXh7u7OiBEjqFixInBzOc3p06ezbt06EhMT8fX1JSgoiIIFCwLQuXNnihUrxrhx4wA4e/Ys48aN4/Dhwzg7O9O+fXu6du2aQ2fi8UhOTiaHX1J5CFZWVlmeGRERERF51HI87MvjpbD/dFDYFxERkZyQK3P2RURERETk8VPYFxERERGxUAr7IiIiIiIWSmFfRERERMRCKeyLiIiIiFgohX0REREREQulsC8iIiIiYqEU9kVERERELJTCvoiIiIiIhVLYFxERERGxUAr7IiIiIiIWSmFfRERERMRCKeyLiIiIiFgohX0REREREQulsC8iIiIiYqEU9kVERERELJTCvoiIiIiIhVLYFxERERGxUAr7IiIiIiIWSmFfRERERMRCKeyLiIiIiFgohX0REREREQulsC8iIiIiYqEU9kVERERELJTCvoiIiIiIhVLYFxERERGxUAr7IiIiIiIWSmFfRERERMRCKeyLiIiIiFioRxb2ExISHlVTIiIiIiLyCDxw2Pfx8cl2++uvv37fbYSHh/Pee+/h4+NDzZo1GTRoEFeuXAHg8OHDtG7dGi8vL+rWrcuKFSvM9l2zZg3169enUqVK+Pn5ERYWZirLyMhg8uTJ1KhRAy8vL3r06EF0dPQdx3H69Gk6dOiAl5cXtWrVYvbs2fd9DCIiIiIiT7r7Cvtnz56lQ4cOvPvuuyQkJPDuu++affn5+ZEvX7776jAlJYXOnTvj5eXFr7/+yoYNG4iLi2PYsGFcu3aNrl270qJFC0JDQxk/fjwTJ07kyJEjAISEhBAUFMSkSZMIDQ2lefPm9OjRg+TkZACCg4PZvXs3q1atYteuXTg6OjJixIhsx5GWlkb37t0pX748ISEhzJ07l6VLl7Jp06b7Og4RERERkSfdfYX9559/ngYNGuDj44O1tTU+Pj5mX40aNWLu3Ln31eHFixd56aWX6NWrF/b29ri6utK2bVtCQ0PZsmULBQoUICAgAFtbW6pXr06zZs1YunQpACtWrKBJkyZUqVIFOzs7OnbsiKurKxs3bjSVd+nShaJFi+Li4sLw4cPZuXMnkZGRWcYRGhpKdHQ0ffr0wd7enldeeYXAwEBTXyIiIiIiTzvb+60YEBAAwHPPPUeLFi0eusPSpUszb948s22bN2+mbNmynDx5Eg8PD7Myd3d3Vq5cCUBERAStWrXKUh4eHk58fDyXLl0y279QoULkz5+f48ePU6JECbP9Tp48SalSpbC3tzdr634vWkREREREnnT3HfZvadGiBUeOHOH06dMYhpGl7EEYhsHnn3/Otm3bWLJkCYsWLcLJycmsjqOjI0lJSQAkJibesTwxMREAZ2fnLOW3ym6XXVtOTk6mvkREREREnnYPHPanTZvGV199ReHChbG1/f/draysHijsJyQkMHToUI4dO8aSJUvw9PTEycmJ+Ph4s3opKSnkyZMHuBnGU1JSspS7urqagvut+fvZ7X87Z2fnLHWTk5OzrSsiIiIi8jR64LC/du1aZs+eTe3atR+603PnztGlSxeKFSvGypUrcXNzA8DDw4Pdu3eb1Y2IiKBMmTIAlClThpMnT2Ypf+2118ifPz9FihQhIiLCNJXn8uXLxMXFZZkadKutM2fOkJ6ebrpoub0vEREREZGn3QMvvZmUlMRrr7320B1eu3aNDh06ULlyZb7++mtT0AeoX78+MTExLFy4kLS0NPbt28f69etN8/T9/f1Zv349+/btIy0tjYULFxIbG0v9+vUB8PPzIzg4mMjISBISEpgwYQI+Pj6ULFkyyzh8fX1xdXVl6tSp3Lhxg/DwcBYvXoy/v/9DH5uIiIiIyJPEyvjnxPt7GDhwIK+++irNmzd/qA4XLFjApEmTcHJywsrKyqwsLCyMo0ePMn78eE6cOIGbmxs9e/bEz8/PVGft2rUEBwcTFRWFu7s7I0aMoGLFisDN5TSnT5/OunXrSExMxNfXl6CgIAoWLAhA586dKVasGOPGjQNuLik6btw4Dh8+jLOzM+3bt6dr164PdVxPiuTk5CzPUsiTx8rKKsszIyIiIiKP2gOH/T59+vDLL7/wwgsvUKhQIbOyRYsWPdLByYNT2H86KOyLiIhITnjgOfseHh7ZzoEXEREREZEnywPf2Zcnm+7sPx10Z19ERERywgPf2R86dOgdyyZOnPivBiMiIiIiIo/OA6/G809Xr15l06ZNWT7MSkREREREctcD39nP7u79nj17+Pbbbx/JgERERERE5NH413f2AWrUqMG+ffseRVMiIiIiIvKIPPCd/X9KT09nw4YNZh+OJSIiIiIiue+Bw/5LL72U5cOwbGxsGD58+CMblIiIiIiI/HsPvPTm/v37zb63trbm+eefp3Dhwo90YPJwtPTm00FLb4qIiEhOeOA5+z4+Pnh7e+Po6EhMTAwABQsWfOQDExERERGRf+eBp/FcvnyZ7t27Ex4eToECBbh69SovvPAC8+fP59lnn30cYxQRERERkYfwwHf2J0+ezAsvvMD+/fvZvXs3ISEhvPzyy/pALRERERGRJ8wDz9mvVasWP/30Ey4uLqZt8fHxvPHGG1nm80vO05z9p4Pm7IuIiEhOeOA7+5mZmVlW47GyssLOzu6RDUpERERERP69Bw77vr6+jBkzhqSkJAASExMZM2YMPj4+j3xwIiIiIiLy8B54Gs/Fixd57733uHDhAgUKFCAuLo4XX3yRuXPnUqRIkcc1TrlPmsbzdNA0HhEREckJDxT2DcMgMjKSYsWKceDAAWJjY7lw4QLvv/8+NjY2j3Occp8U9p8OCvsiIiKSE+477CclJdGpUycKFSrEl19+CUBsbCx16tShXLlyzJs3D2dn58c6WLk3hf2ng8K+iIiI5IT7nrMfHByMnZ0dY8eONW0rWLAg27ZtIz09nTlz5jyWAYqIiIiIyMO577C/efNmPv744yyflluwYEHGjh3LTz/99MgHJyIiIiIiD+++w35sbCzPP/98tmUvv/wyly9ffmSDEhERERGRf+++w76LiwtXr17NtiwuLk7zj0VEREREnjD3HfarV6/O0qVLsy379ttvqVSp0qMak4iIiIiIPAK291uxW7du+Pn5cfXqVRo3bkzhwoWJjo5m06ZNrFq1iiVLljzOcYqIiIiIyAN6oHX2Dx06xOjRozl58iRWVlYYhoGHhwcjR46katWqj3Occp+09ObTQUtvioiISE544E/QBYiMjOTKlSsULlyYYsWKPY5xyUNS2H86KOyLiIhITniosC9PLoX9p4PCvoiIiOSE+35AV0REREREni4K+yIiIiIiFkphX0RERETEQuVq2L9y5Qr169cnJCTEtG306NGUK1cOLy8v09fy5ctN5WvWrKF+/fpUqlQJPz8/wsLCTGUZGRlMnjyZGjVq4OXlRY8ePYiOjr5j/6dPn6ZDhw54eXlRq1YtZs+e/XgOVEREREQkF+Ra2D948CBt27bl3LlzZtuPHj1KUFAQYWFhpq+2bdsCEBISQlBQEJMmTSI0NJTmzZvTo0cPkpOTAQgODmb37t2sWrWKXbt24ejoyIgRI7LtPy0tje7du1O+fHlCQkKYO3cuS5cuZdOmTY/3wEVEREREckiuhP01a9YwYMAA+vXrZ7Y9NTWVEydOUK5cuWz3W7FiBU2aNKFKlSrY2dnRsWNHXF1d2bhxo6m8S5cuFC1aFBcXF4YPH87OnTuJjIzM0lZoaCjR0dH06dMHe3t7XnnlFQIDA+/4KcEiIiIiIk+bXAn7tWrV4ueff6Zx48Zm28PDw0lPT+eLL76gRo0aNGzYkLlz55KZmQlAREQEHh4eZvu4u7sTHh5OfHw8ly5dMisvVKgQ+fPn5/jx41nGcPLkSUqVKoW9vX2WtkRERERELIFtbnRauHDhbLfHx8fj4+NDYGAg06ZN488//6RXr15YW1vTuXNnEhMTs6xN7ujoSFJSEomJiQA4OztnKb9Vdrvs2nJyciIpKenfHJqIiIiIyBPjiVqNp2bNmixatAgfHx/s7OyoUKECHTp0ME3TcXJyIiUlxWyflJQU8uTJYwrut+bv/7P8n5ydnbPUTU5OzrauiIiIiMjT6IkK+7/88gvLli0z25aamoqjoyMAZcqU4eTJk2blERERlClThvz581OkSBEiIiJMZZcvXyYuLi7L1J9bbZ05c4b09PQsbYmIiIiIWIInKuwbhsHEiRPZu3cvhmEQFhbGokWLTKvx+Pv7s379evbt20daWhoLFy4kNjaW+vXrA+Dn50dwcDCRkZEkJCQwYcIEfHx8KFmyZJa+fH19cXV1ZerUqdy4cYPw8HAWL16Mv79/jh6ziIiIiMjjYmUYhpGbA/D09GTRokX4+voCsGzZMhYsWEBUVBSFChXivffeIyAgwFR/7dq1BAcHExUVhbu7OyNGjKBixYrAzeU0p0+fzrp160hMTMTX15egoCAKFiwIQOfOnSlWrBjjxo0D4OzZs4wbN47Dhw/j7OxM+/bt6dq1aw6fgUcrOTmZXH5J5T5YWVlleWZERERE5FHL9bAvj5bC/tNBYV9ERERywhM1jUdERERERB4dhX0REREREQulsC8iIiIiYqEU9kVERERELJTCvoiIiIiIhVLYFxERERGxUAr7IiIiIiIWSmFfRERERMRCKeyLiIiIiFgohX0REREREQulsC8iIiIiYqEU9kVERERELJTCvoiIiIiIhVLYFxERERGxUAr7IiIiIiIWSmFfRERERMRCKeyLiIiIiFgohX0REREREQulsC8iIiIiYqEU9kVERERELJTCvoiIiIiIhVLYFxERERGxUAr7IiIiIiIWSmFfRERERMRCKeyLiIiIiFgohX0REREREQulsC8iIiIiYqEU9kVERERELJTCvoiIiIiIhVLYFxERERGxULka9q9cuUL9+vUJCQkxbTt8+DCtW7fGy8uLunXrsmLFCrN91qxZQ/369alUqRJ+fn6EhYWZyjIyMpg8eTI1atTAy8uLHj16EB0dfcf+T58+TYcOHfDy8qJWrVrMnj370R+kiIiIiEguybWwf/DgQdq2bcu5c+dM265du0bXrl1p0aIFoaGhjB8/nokTJ3LkyBEAQkJCCAoKYtKkSYSGhtK8eXN69OhBcnIyAMHBwezevZtVq1axa9cuHB0dGTFiRLb9p6Wl0b17d8qXL09ISAhz585l6dKlbNq06fEfvIiIiIhIDsiVsL9mzRoGDBhAv379zLZv2bKFAgUKEBAQgK2tLdWrV6dZs2YsXboUgBUrVtCkSROqVKmCnZ0dHTt2xNXVlY0bN5rKu3TpQtGiRXFxcWH48OHs3LmTyMjILGMIDQ0lOjqaPn36YG9vzyuvvEJgYKCpLxERERGRp12uhP1atWrx888/07hxY7PtJ0+exMPDw2ybu7s74eHhAERERNyxPD4+nkuXLpmVFypUiPz583P8+PEsYzh58iSlSpXC3t4+275ERERERJ52trnRaeHChbPdnpiYiJOTk9k2R0dHkpKS7lmemJgIgLOzc5byW2X36svJycnUl4iIiIjI0+6JWo3HycmJlJQUs20pKSnkyZPnnuW3gvut+fvZ7X87Z2fnLHWTk5OzrSsiIiIi8jR6osK+h4cHJ0+eNNsWERFBmTJlAChTpswdy/Pnz0+RIkWIiIgwlV2+fJm4uLgsU39utXXmzBnS09Oz7UtERERE5Gn3RIX9+vXrExMTw8KFC0lLS2Pfvn2sX7+eVq1aAeDv78/69evZt28faWlpLFy4kNjYWOrXrw+An58fwcHBREZGkpCQwIQJE/Dx8aFkyZJZ+vL19cXV1ZWpU6dy48YNwsPDWbx4Mf7+/jl6zCIiIiIij4uVYRhGbg7A09OTRYsW4evrC8DRo0cZP348J06cwM3NjZ49e+Ln52eqv3btWoKDg4mKisLd3Z0RI0ZQsWJF4OZymtOnT2fdunUkJibi6+tLUFAQBQsWBKBz584UK1aMcePGAXD27FnGjRvH4cOHcXZ2pn379nTt2jWHz8CjlZycTC6/pHIfrKyssjwzIiIiIvKo5XrYl0dLYf/poLAvIiIiOeGJmsYjIiIiIiKPjsK+iIiIiIiFUtgXEREREbFQCvsiIiIiIhZKYV9ERERExEIp7IuIiIiIWCiFfRERERERC6WwLyIiIiJioRT2RUREREQslMK+iIiIiIiFUtgXEREREbFQCvsiIiIiIhZKYV9ERERExEIp7IuIiIiIWCiFfRERERERC6WwLyIiIiJioRT2ReSe4uLiGDRoEL6+vlStWpWePXsSHR0NwOHDh2ndujVeXl7UrVuXFStWZNvG7t27efnllzl//nxODl1EROQ/TWFfRO6pd+/eJCUl8fPPP7Nt2zZsbGwYOXIk165do2vXrrRo0YLQ0FDGjx/PxIkTOXLkiNn+ly9fZvDgwWRmZubSEYiIiPw32eb2AETkyfb7779z+PBh9uzZg4uLCwBBQUFcvnyZLVu2UKBAAQICAgCoXr06zZo1Y+nSpVSoUAGAzMxMBgwYQOvWrZk1a1auHYeIiMh/ke7si8hdHTlyBHd3d77//nvq169PrVq1mDx5MoULF+bkyZN4eHiY1Xd3dyc8PNz0/axZsyhYsCCtWrXK6aGLiIj85ynsi8hdXbt2jePHj3PmzBnWrFnDDz/8QFRUFIMHDyYxMREnJyez+o6OjiQlJQGwf/9+1q1bx7hx43Jj6CIiIv95Cvsiclf29vYADB8+HBcXFwoVKsSHH37Ijh07MAyDlJQUs/opKSnkyZOHK1euMGTIED799FPT9B8RERHJWQr7InJX7u7uZGZmkpaWZtp260Hbl19+mZMnT5rVj4iIoEyZMuzatYvY2Fjef/99vL29ad68OQDNmzdn7ty5OXcAIiIi/2FWhmEYuT0IeXSSk5PRS/rks7KyyjL95UmVlpZGkyZNeOmll5g4cSI3btygX79+5M2bl6CgIBo0aECvXr0ICAjg4MGD9OzZk1mzZlGtWjWzds6fP88bb7zB//73P5577rlcOhoREZH/Ft3ZF5G7srOzY/HixdjY2NCwYUMaNmzIs88+y4QJE3B1dWX+/Pn89NNP+Pr6MmLECEaMGJEl6IuIiEju0J19C6M7+0+Hp+nOvoiIiDy9dGdfJBdYWVlhGPqAqaeFXisREXla6UO1RHKJlZU1V8M/Jz3pfG4PRe7C1vk5XF/6MLeHISIi8lAU9kVyUXrSedIT/srtYYiIiIiF0jQeEREREREL9USG/Y0bN/LKK6/g5eVl+ho4cCAAhw8fpnXr1nh5eVG3bl1WrFhhtu+aNWuoX78+lSpVws/Pj7CwsDv2k5SUxNChQ/H19aVKlSoMGjSIxMTEx3psIiIiIiI55YkM+0ePHuWtt94iLCzM9PXpp59y7do1unbtSosWLQgNDWX8+PFMnDiRI0eOABASEkJQUBCTJk0iNDSU5s2b06NHD5KTk7PtJygoiL///pvNmzezZcsW/v77b6ZMmZKThyoiIiIi8tg8sWG/XLlyWbZv2bKFAgUKEBAQgK2tLdWrV6dZs2YsXboUgBUrVtCkSROqVKmCnZ0dHTt2xNXVlY0bN2ZpKzk5mfXr19OnTx8KFChAwYIFGTBgAKtXr77jxYGIiIiIyNPkiQv7mZmZHDt2jO3bt1OnTh1ee+01Ro4cybVr1zh58iQeHh5m9d3d3QkPDwcgIiLiruW3O3v2LGlpaWb1X3zxRVJSUjhz5syjPzARERERkRz2xIX9K1eu8Morr9CwYUM2btzIsmXLOHPmDAMHDiQxMTHLBxE5OjqSlJQEcM/y2yUkJADg7Oxs2nZrX83bFxERERFL8MSF/UKFCrF06VL8/f1xcnKiWLFiDBw4kJ07d2IYBikpKWb1U1JSyJMnD3AzrN+t/Ha3Qv7tU3Zu/dvFxeWRHpOIiIiISG544sJ+eHg4U6ZMwTAM07bU1FSsra2pUKECJ0+eNKsfERFBmTJlAChTpsxdy29XqlQp7OzsiIiIMG07deoUdnZ2vPDCC4/wiEREREREcscTF/YLFCjA0qVLmTdvHunp6Vy8eJFPP/2Uli1b0rBhQ2JiYli4cCFpaWns27eP9evX06pVKwD8/f1Zv349+/btIy0tjYULFxIbG0v9+vWz9OPk5MSbb77JlClTuHLlCleuXGHKlCk0bdoUR0fHnD5sEREREZFHzsq4/Rb6E2L//v1MmzaNEydO4ODgQJMmTRg4cCAODg4cPXqU8ePHc+LECdzc3OjZsyd+fn6mfdeuXUtwcDBRUVG4u7szYsQIKlasCMDs2bNZv349P/74I3Bz3v7kyZPZunUraWlpvPHGG4wcOdJsHv/TJjk5mSfwJZV/sLa2xtHRkcuHBugTdJ9wti6lKVxZS/KKiMjT6YkM+/LwFPafDgr7Tw+FfREReZo9cdN4RERERETk0VDYFxERERGxUAr7IiIiIiIWSmFfRERERMRCKeyLiIiIiFgohX0REREREQulsC8iIiIiYqEU9kVERERELJTCvoiIiIiIhVLYFxERERGxUAr7IiIiIiIWSmFfRERERMRCKeyLiIiIiFgohX0REREREQulsC8iIiIiYqEU9kVERERELJTCvoiIiIiIhVLYFxERERGxUAr7IiIiIiIWSmFfRESeOnFxcQwaNAhfX1+qVq1Kz549iY6OBmDHjh20aNECLy8vmjdvzs8//5zLoxURyT0K+yIi8tTp3bs3SUlJ/Pzzz2zbtg0bGxtGjhzJsWPH6NWrFwEBAYSGhjJq1CgGDx5MSEhIbg9ZRCRX2Ob2AERERB7E77//zuHDh9mzZw8uLi4ABAUFcfnyZdauXUvlypVp3bo1AN7e3jRr1ozvvvsOX1/f3By2iEiu0J19ERF5qhw5cgR3d3e+//576tevT61atZg8eTKFCxcmIyMDZ2dns/rW1tb89ddfuTRauV1GRgaBgYEMGTLEtO3w4cO0bt0aLy8v6taty4oVK3JxhCKWR2FfRESeKteuXeP48eOcOXOGNWvW8MMPPxAVFcXgwYOpX78+v/76K5s3byY9PZ2DBw+yceNGbty4kdvDFuDLL7/kwIEDpu+vXbtG165dadGiBaGhoYwfP56JEydy5MiRXByliGVR2BcRkaeKvb09AMOHD8fFxYVChQrx4YcfsmPHDjw9Pfnkk0/48ssvqVmzJl9//TV+fn7ky5cvl0cte/fuZcuWLTRo0MC0bcuWLRQoUICAgABsbW2pXr06zZo1Y+nSpbk4UhHLorAvIiJPFXd3dzIzM0lLSzNty8zMBG6u0lOmTBnWr19PSEgIs2bN4u+//6ZcuXK5NVwBYmNjGT58OFOnTsXJycm0/eTJk3h4eJjVdXd3Jzw8PKeHKGKxFPZFROSpUqNGDUqUKMGwYcNITEzkypUrfPbZZ9SrV4+YmBjatGlDeHg46enpbNy4kW3bttGuXbvcHvZ/VmZmJgMHDuS9997jpZdeMitLTEw0C/8Ajo6OJCUl5eQQRSyaVuMREZGnip2dHYsXL2bSpEk0bNiQGzduULduXYYPH06+fPkYNGgQPXv25OrVq5QuXZrZs2dTpkyZ3B72f9acOXOwt7cnMDAwS5mTkxPx8fFm21JSUsiTJ09ODU/E4insi4jIU6dIkSJ89tln2Za98847vPPOOzk8IrmTtWvXEh0djbe3N3AzzAP88ssvDBo0iN27d5vVj4iI0MWZyCOkaTwiIv9RhmHk9hDkATytr9dPP/3EoUOHOHDgAAcOHKBp06Y0bdqUAwcOUL9+fWJiYli4cCFpaWns27eP9evX06pVq9wetojFsLg7+7GxsYwcOZL9+/djY2ND8+bNGTx4MLa2WQ91x44dTJkyhcjISIoWLcqgQYOoU6dOLoxaRCTnWVlZcePGDdPDrfLksra2xsHBIbeH8ci5uroyf/58xo8fzxdffIGbmxsjRoygWrVquT00EYthZTyttwruIDAwkCJFihAUFERMTAw9evSgRYsWdO7c2azemTNnaN68OdOmTeP1119ny5YtDB06lC1btlCkSJFcGv2/l5yc/NTe/fkvsba2xtHRkcuHBpCeoA/7eZLZupSmcOUpuT2Mx0Z/M54ON8O+PVZWekP+aWAYmXqt5IlhUXf2z549y/79+9m5cydOTk6UKFGCnj178umnn2YJ+2vWrMHb25t69eoB0LhxY1avXs3y5cvp06dPbgxfRETkjqysrLka/jnpSedzeyhyF7bOz+H60oe5PQwRE4sK+ydPnqRAgQJmd+ZffPFFLl68yPXr180+VCUiIiJH1vb966+/iIuLe6Rt3k1qaqrekn8K2NjYYGdnx/XTBhkpWnXiSWbjaJCPQ7k9jMdGfzOeDv//NyOSjJTo3B6O3IWNo0G+pJz7m1G5cuUc60ueThYV9rNbr/fW90lJSWZhP6fW9i1duvQjbU8sjP5Ii8iD0N8MEXlAFjWhzNnZmeTkZLNtt77/55q9Tk5OpuW/btHaviIiIiJiSSwq7JcpU4a4uDhiYmJM206dOsWzzz5L3rx5zep6eHhw8uRJs21a21dERERELIlFhf0XXniBKlWqMGHCBBISEoiMjGTWrFn4+/tnqdu8eXP279/Pxo0bTR+pvn//ft56661cGLmIiIiIyKNncUtvxsTEMG7cOEJCQrC2tqZFixYMGDAAGxsbvLy8GDt2LM2bNwdg165dTJkyhXPnzlG8eHEGDhxI7dq1c/kIREREREQeDYsL+yIiIiIicpNFTeMREREREZH/p7AvIiIiImKhFPZFRERERCyUwr6IiIiIiIVS2BcRERERsVAK+yIiIiIiFkphX0RERETEQinsi4iIiIhYKIV9ERERERELpbAvIiIiImKhFPZFRERERCyUwr6IhcjIyCAyMjK3hyEiuejMmTO5PQQRecIo7IvF8/T0pGvXrhiGYbZ99erV1K1b96HaDAkJwdPTEy8vL7y8vKhYsSI+Pj50796dkydPmuqtW7eOJk2a3FebM2bMIDAw8KHGA9CvXz9++OGHh95fRB5c3bp1KV++vOlvQaVKlXjrrbdYsWKFqY6XlxcHDhy4Z1vnz5/H09OT8+fPP9RYtm7dyvvvv/9Q+4qI5bLN7QGI5IQdO3Ywb948unTp8kjbDQsLM/07NjaWmTNn8s477/D9999TunRpmjdvTvPmzR9pn3dy9erVHOlHRMyNHTsWPz8/AFJTU9m+fTtDhw7l6tWrdO3a1ezvxOMUFxeX5aaGiIju7Mt/QmBgINOnT+fQoUN3rHP8+HG6dOmCj48Pr732GmPGjCE+Pv6++yhYsCCjRo3C3d2dmTNnAlnfPVi5ciV+fn74+vri5eVFt27duHLliqk8KSmJIUOG4Ovry5tvvml2pz41NZXp06fzxhtv4OPjQ5cuXTh79iwAw4cP58CBA8yZM4fu3bsDcO7cObp3746vry916tThs88+IzU1FYCEhAT69euHr68vNWvW5P333+fUqVP3fawikj17e3saNGjA4MGD+fLLL0lISMDT05OQkBAATp06Rbdu3Xj99depUKECjRs3Ztu2bWZt/PDDD9SrV48aNWowYsQIEhISTGV79uzB398fb29vmjRpwrp164Cb7zaOHj2aixcv4uXlRVRU1F3/ZgB8++231KtXD29vb5o1a2b2boSIWA6FfflPqF+/Pm3btuWjjz4iLi4uS/nVq1d59913cXd3Z+fOnaxatYrTp08zaNCgB+6rTp067Nu3L8v2I0eO8PHHHzNmzBhCQkLYtGkTZ86cYdGiRaY6v//+O+XKlePXX39lxIgRjBgxwvT2/2effcb27dtZuHAhu3btomLFinTq1IkbN24wfvx4vL296datG7NnzyYpKYmOHTtSpkwZdu7cybfffsuePXuYMWMGAPPnzychIYEdO3awbds2ChcuzJQpUx74WEUke6+//jo3btzIcoOhd+/eeHh48PPPP3PgwAFq1arFmDFjzOocOHCA77//nnXr1nHixAkmTJgAQHh4OD169KBr166EhIQQFBTEhAkT2LVrF76+vowdO5ZixYoRFhZGkSJF7vo3IzIykokTJzJ37lwOHDjAoEGDCAoKIjo6OqdOkYjkEIV9+c8YPHgwbm5uDBkyJMtb3f/73/+ws7NjwIABODo6UrhwYUaOHMnWrVu5fPnyA/Xj6uqa7QWFh4cHGzZsoEKFCly7do3o6Gjc3NyIiooy1Xn55Zdp3749dnZ21KxZk4YNG7J27VoMw2DZsmV89NFHlChRAgcHB3r16kVaWhrbt2/P0tf27dtJTU3lo48+wsHBgaJFi9K3b1+WLl0KgKOjI+Hh4fzwww9ERUUxYcIEgoODH+g4ReTOXF1dAbL8LZgzZw69e/fGMAwuXLhAvnz5zP4GAAwZMgQ3NzcKFSpEnz59WL9+PZmZmSxbtow33niDBg0aYGNjQ+XKlWnTpo3p9/p29/qbYWNjY6pz8OBBqlevzm+//cYzzzzz2M6JiOQOzdmX/wx7e3s+//xzWrZsyfz5803/GcPN+fbFihXDxsbGtO25554D4MKFCxQuXPi++4mNjcXNzS3LdmtraxYtWsT69etxdnbG09OThIQEswuPW33eUrRoUU6cOMGVK1dISkqib9++WFv//zV6WloaFy5cyNLXhQsXuHLlClWrVjVtMwyDtLQ0YmNj6dKlC/b29qxcuZJx48ZRokQJ+vfvT4MGDe77OEXkzm5NzytYsKDZ9vDwcHr27Mnly5d58cUXcXNzy3Lz4fa/A0WLFiU1NZW4uDguXLjAvn378Pb2NpVnZGRQsmTJbPu/29+Mhg0bsnjxYubNm0f37t3JyMjAz8+PgQMH4uDg8EjOgYg8GRT25T+lZMmSBAUFMWjQINMDdQDFixfn4sWLZGRkmAL/uXPnAB4o6ANs27aNGjVqZNm+cOFCdu/ezfr16ylUqBCAaX79Lf98Cz0yMpLixYvj6uqKg4MD8+fPp1KlSqbyv/76iyJFimTp69lnn6VkyZL89NNPpm0JCQmmC5Hjx49Tt25dOnbsSHx8PN9++y39+vVj37595M2b94GOV0Sy2rp1K87OzlSsWNG0LSoqir59+/Lll1+anuXZvHkzW7ZsMds3KioKFxcX4OYKPc7Ozri5ufHss8/SsmVLxo0bZ6obHR2d7UO59/qbERsbS0ZGBjNnziQzM5NDhw7Rp08fSpUqRUBAwKM8FSKSyzSNR/5zGjduTKtWrVi+fLlpW+3atQGYMmUKKSkpXL58mfHjx1OtWjWKFy9+X+1evnyZMWPGcO7cOT744IMs5QkJCdja2mJnZ0d6ejpr165l165dpKWlmeocOXKEVatWkZaWxrZt29i6dSutW7fG2toaf39/pk6dyqVLl8jMzGTNmjU0bdrU9MCdvb296YHiOnXqkJiYyLx580hNTeX69esMHjyYfv36YWVlxYoVKxg0aBCxsbG4uLjg4uKCs7Mz9vb2D31eReTmg/QbN25k2rRp9OvXzxTaARITE8nIyMDJyQmAiIgI08P8tx6eB/j000+5du0aly5dYvr06bRt2xYAf39/NmzYwK+//kpmZiZnzpyhffv2zJ8/HwAHBweSk5NJT0+/59+Mixcv0qlTJ/bu3Yu1tbXppsHt73iKiGXQnX35Txo2bBiHDx/m+vXrAOTNm5cFCxYwadIkU/B/44037vmArpeXFwBWVlbkzZsXHx8fli9fTokSJbLU7dSpEydOnKBOnTo4ODjwyiuv0K5dO7OHeWvUqMH//vc/Pv74Y5577jmmT5/OK6+8Atx85mDGjBm0a9eOuLg4SpQowRdffGEqb9GiBWPGjOH333/n22+/ZeHChUyaNIl58+aRmZmJr6+vaV7+Rx99xLhx42jSpAk3btygdOnSzJo1S2/fizyE0aNHExQUBNwM3KVLl2bs2LE0btzYrF7p0qUZNGgQAwcOJDk5mWeffZY2bdrw6aefcuLECQoUKADc/LvSqFEjrK2tadq0Kf369QOgYsWKTJs2jWnTptG3b1+cnJxo2rQpH330EQBVq1alYMGCVK1alWXLlt3zb8aoUaMYM2YM0dHR5M2bl3bt2vHmm2/m0FkTkZxiZWhRXhERERERi6RpPCIiIiIiFkphX0RERETEQinsi4iIiIhYKIV9ERERERELpbAvIiIiImKhFPZFRERERCyUwr6IiIiIiIVS2BcRySVnzpzJ7SGIiIiFU9gXEYtz+vRpBg8ezGuvvYaXlxf16tVjypQpJCYm5vbQTP744w+aNm161zqrVq2iZcuWeHl5UaVKFdq1a8f27dsfy3hCQkLw9PR8LG2LiEjuUdgXEYty6NAhWrZsSfHixfnhhx8ICwvjq6++4vDhw3Tq1ImMjIzcHiIA8fHxpKWl3bF8/fr1TJs2jdGjR3Pw4EH27t1LmzZt+OCDDwgNDc3BkYqIyNNMYV9ELMqoUaNo0aIFffr0wc3NDYBSpUrx2WefUbBgQSIjIwHw9PQkJCTEtN/q1aupW7cucPMud+3atenfvz/e3t7MnTuXIUOG0KdPH958802qVavGuXPniImJYcCAAdSsWZNatWoxatQoEhISTG3UrVuX4OBgXn31VXx8fOjduzcJCQlERkbSpUsXALy8vAgLC8tyHAcPHuSll16iUqVKWFtbY29vT4sWLejRowfXrl0DYMaMGfTt25fBgwdTuXJlXnvtNTZt2sTMmTOpUaMGPj4+zJo1y9TmhQsX+PDDD6levTo1a9akf//+REdHZ+nbMAyGDx9OkyZNiIqKAmDPnj34+/vj7e1NkyZNWLdunal+dudGRESeDAr7ImIxzp07x8mTJ7OdHlOoUCFmzZrFCy+8cF9tXbp0idKlS7N3717atWsHwK5du5g+fTpbtmzhueeeo2fPnlhbW7N582bWr19PdHQ0o0aNMrVx4cIFoqKi+Pnnn1mxYgVhYWF8++23lChRgq+++gqAsLAwvLy8svTfsGFD9u3bx/vvv8+SJUs4evQoaWlp9OrVi3r16pnqbd68mTp16nDw4EGaN29O//79SUhIYMeOHUyYMIHp06dz4cIF0tLS6NSpEzY2NmzZsoVNmzYB0L17d9LT003tZWZmMmzYMP78808WL15MkSJFCA8Pp0ePHnTt2pWQkBCCgoKYMGECu3btMu13+7kpWbLkfZ1jERF5/BT2RcRiXLlyBbgZ7B8Ff39/7OzscHFxAaBSpUp4eHiQL18+fv/9d44dO8bo0aNxcXHB1dWVwYMH8+OPP3L16lVTG7169cLR0ZHnn38eX19fTp8+fV99V69enVWrVlG8eHG++eYb/P398fHxYfTo0WbPHri7u9OoUSOsrKyoWbMmGRkZdO/eHTs7O9M7FRcvXuTAgQNERkYyduxY8ubNS758+Rg7dizh4eH8/vvvpvYGDx7Mrl27WLRokemdkWXLlvHGG2/QoEEDbGxsqFy5Mm3atGHp0qWm/W4/NyIi8uSwze0BiIg8KoULFwbg8uXL2d7Bj4mJeaALgWeeeeaO358/f56MjAxq165tVsfe3t40Vej2MQHY2dlhGMZ99//SSy8xbtw44OaFzJ49e/j0009JSkri008/BaBAgQKm+tbWN+/f5M+f3+z7zMxMYmNjcXV1NV24ALi4uFCgQAEuXLhgOi+XLl0iMTGRnTt30rhxY+DmOxT79u3D29vbtG9GRobZHfx/nisREXkyKOyLiMUoXrw4Hh4ebNy4kapVq5qVxcbGUqdOHSZOnEjTpk2xtrY2e0D29rvxt1hZWd3x+2effRZHR0dCQkKwsbEBIDU1lcjISJ5//nkOHjz4r47l9ddfp0uXLgQEBADg5uZG06ZNuXr1KsuXL7/jGO+kePHiXL16lYSEBFPgj4+P5+rVqxQuXNh0EfL111/z/fffM3bsWLy9vXnmmWd49tlnadmypenCAyA6OtrswuV+xyEiIjlL03hExKKMHDmSVatW8eWXX3L16lUMw+DPP/+ke/fulC1bloYNGwLw4osvsnnzZtLT0zl37hwrV658oH4qVKjA888/z6RJk0hMTCQlJYUJEybQsWPH+1rxx8HBAbgZuLPTvHlzgoOD2bZtG/Hx8aSnpxMeHs7KlStp0KDBA40VoHz58ri7uzN69Gji4+OJj49nzJgxlCxZksqVK5vq2dvbExAQgIeHB8OHDwduTmfasGEDv/76K5mZmZw5c4b27dszf/78Bx6HiIjkLIV9EbEoPj4+LFmyhD/++IMmTZpQuXJl+vTpQ7Vq1Zg3bx52dnYAjB49mmPHjuHj48OHH36Iv7//A/Vja2vLnDlziImJoUGDBtSqVYtz586xYMECU5C/Gw8PD6pUqcKrr77Kjh07spT369eP7t27M2PGDF577TW8vb0ZMGAALVu2pHfv3g801tvHm56eTsOGDalTpw5paWksWLAAW1vzN3mtrKyYMGECBw4cYNmyZVSsWJFp06Yxbdo0qlatSvv27albty79+/d/4HGIiEjOsjIeZAKpiIiIiIg8NXRnX0RERETEQinsi4iIiIhYKIV9ERERERELpbAvIiIiImKhFPZFRERERCyUwr6IiIiIiIVS2BcRERERsVAK+yIiIiIiFkphX0RERETEQinsi4iIiIhYKIV9ERERERELpbAvIiIiImKh/g9/wLe0y3zmmAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define colors\n",
    "colors = ['#F5F5F5', '#FFCE38']\n",
    "sns.set_palette(colors)\n",
    "\n",
    "# Bar chart for Smoking vs Heart Stroke\n",
    "plt.figure(figsize=(8, 4))\n",
    "ax = sns.countplot(x='diabetes', hue='Heart_ stroke', data=df)\n",
    "#, width=0.7)  \n",
    "ax.set_title('DIABETES X HEART STROKE', fontsize=12, fontweight='bold')\n",
    "ax.set_xlabel('Current Smoker', fontsize=10)\n",
    "ax.set_ylabel('Count', fontsize=10)\n",
    "\n",
    "# Add a line from y-axis to x-axis\n",
    "plt.axhline(0, color='black', linewidth=1)\n",
    "\n",
    "# Remove borders and grid\n",
    "ax.grid(False)\n",
    "for spine in ax.spines.values():\n",
    "    spine.set_visible(False)\n",
    "\n",
    "# Display the count values on the bars\n",
    "for p in ax.patches:\n",
    "    ax.annotate('{:.0f}'.format(p.get_height()), (p.get_x() + p.get_width() / 2, p.get_height() + 8),\n",
    "                ha='center', fontsize=10)\n",
    "\n",
    "# Create a legend \n",
    "legend_handles = [plt.Rectangle((0, 0), 1, 1, color=color, ec=\"k\", lw=0.5, label=label) for color, \n",
    "                  label in zip(colors, ['No = did not have heart stroke', 'Yes = had heart stroke'])]\n",
    "legend = plt.legend(handles=legend_handles, loc='upper right', bbox_to_anchor=(1.25, 1), \n",
    "                    title='Heart Stroke', fontsize=10, frameon=True, facecolor='white')\n",
    "legend.set_title('Heart Stroke', prop={'size': 10, 'weight': 'bold'})\n",
    "\n",
    "# Replace labels\n",
    "ax.set_xticklabels(['No Diabetes', 'Diabetes'], fontsize=10)\n",
    "ax.set_yticklabels(ax.get_yticks(), fontsize=10)  # Set font size for y-axis labels\n",
    "\n",
    "# Adjust layout \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcda85c6",
   "metadata": {},
   "source": [
    "Patients which did not have diabetes had a hight level of heart stroke, and almost all of the patients that have diabetes are more likeable to get a heart strokePatients which did not have diabetes had a hight level of heart stroke, and almost all of the patients that have diabetes are more likeable to get a heart stroke"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "dd29250c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define colors\n",
    "colors = ['#F5F5F5', '#FF0000']\n",
    "sns.set_palette(colors)\n",
    "\n",
    "# Bar chart for Smoking vs Heart Stroke\n",
    "plt.figure(figsize=(8, 4))\n",
    "ax = sns.countplot(x='prevalentHyp', hue='Heart_ stroke', data=df)\n",
    "                   #, width=0.7)  \n",
    "ax.set_title('HYPERTENSION X HEART STROKE', fontsize=12, fontweight='bold')\n",
    "ax.set_xlabel('Current Smoker', fontsize=10)\n",
    "ax.set_ylabel('Count', fontsize=10)\n",
    "\n",
    "# Add a line from y-axis to x-axis\n",
    "plt.axhline(0, color='black', linewidth=1)\n",
    "\n",
    "# Remove borders and grid\n",
    "ax.grid(False)\n",
    "for spine in ax.spines.values():\n",
    "    spine.set_visible(False)\n",
    "\n",
    "# Display the count values on the bars\n",
    "for p in ax.patches:\n",
    "    ax.annotate('{:.0f}'.format(p.get_height()), (p.get_x() + p.get_width() / 2, p.get_height() + 8),\n",
    "                ha='center', fontsize=10)\n",
    "\n",
    "# Create a legend \n",
    "legend_handles = [plt.Rectangle((0, 0), 1, 1, color=color, ec=\"k\", lw=0.5, label=label) for color, \n",
    "                  label in zip(colors, ['No = did not have heart stroke', 'Yes = had heart stroke'])]\n",
    "legend = plt.legend(handles=legend_handles, loc='upper right', bbox_to_anchor=(1.25, 1), \n",
    "                    title='Heart Stroke', fontsize=10, frameon=True, facecolor='white')\n",
    "legend.set_title('Heart Stroke', prop={'size': 10, 'weight': 'bold'})\n",
    "\n",
    "# Replace labels\n",
    "ax.set_xticklabels(['No Hypertension', 'Hypertension'], fontsize=10)\n",
    "ax.set_yticklabels(ax.get_yticks(), fontsize=10)  # Set font size for y-axis labels\n",
    "\n",
    "# Adjust layout \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58910f86",
   "metadata": {},
   "source": [
    "The number of patients without hypertension are greater, but it seems that having hypertension might contribute for heart stroke. Is similar to diabetes vs heart stroke.\n",
    "\n",
    "#### ______________________________________________________________________________________________________________"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "633c0ed2",
   "metadata": {},
   "source": [
    "##### * Correlation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa906233",
   "metadata": {},
   "source": [
    "We are going to check the Person Correlation for the continuous data to understand the strength and direction of the linear relationship between pairs of continuous variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "e70a534a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Correlation between continuous data\n",
    "data = ['cigsPerDay', 'totChol', 'sysBP', 'diaBP', 'BMI', 'heartRate', 'glucose']\n",
    "df_continuos = pd.DataFrame(data)\n",
    "continuous_columns = ['cigsPerDay', 'totChol', 'sysBP', 'diaBP', 'BMI', 'heartRate', 'glucose']\n",
    "\n",
    "#Correlation Matrix\n",
    "correlation_matrix = df[continuous_columns].corr()\n",
    "\n",
    "# Plot Heatmap\n",
    "plt.figure(figsize=(9, 4))\n",
    "cmap = sns.color_palette(\"YlOrRd\", as_cmap=True)\n",
    "annot_font_size = 10\n",
    "sns.heatmap(correlation_matrix, annot=True, cmap=cmap, linewidths=0.5, annot_kws={\"size\": annot_font_size})\n",
    "plt.title('CORRELATION MATRIX FOR CONTINUOUS DATA', fontsize=12, fontweight='bold')\n",
    "plt.show()"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
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  "toc": {
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