training_6.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python for Data Analysis II\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "**Agenda:**\n",
    "\n",
    "    * matplotlib\n",
    "    * seaborn\n",
    "    * numpy\n",
    "    * scipy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basic plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "UsageError: unrecognized arguments: # needed for inline plotting in jupyter\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline  # needed for inline plotting in jupyter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('Churn-Modelling.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RowNumber</th>\n",
       "      <th>CustomerId</th>\n",
       "      <th>Surname</th>\n",
       "      <th>CreditScore</th>\n",
       "      <th>Geography</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
       "      <th>Balance</th>\n",
       "      <th>NumOfProducts</th>\n",
       "      <th>HasCrCard</th>\n",
       "      <th>IsActiveMember</th>\n",
       "      <th>EstimatedSalary</th>\n",
       "      <th>Exited</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>15634602</td>\n",
       "      <td>Hargrave</td>\n",
       "      <td>619</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>42</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>101348.88</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>15647311</td>\n",
       "      <td>Hill</td>\n",
       "      <td>608</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>83807.86</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>112542.58</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>15619304</td>\n",
       "      <td>Onio</td>\n",
       "      <td>502</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>42</td>\n",
       "      <td>8</td>\n",
       "      <td>159660.80</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>15701354</td>\n",
       "      <td>Boni</td>\n",
       "      <td>699</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93826.63</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>15737888</td>\n",
       "      <td>Mitchell</td>\n",
       "      <td>850</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>125510.82</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>79084.10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   RowNumber  CustomerId   Surname  CreditScore Geography  Gender  Age  \\\n",
       "0          1    15634602  Hargrave          619    France  Female   42   \n",
       "1          2    15647311      Hill          608     Spain  Female   41   \n",
       "2          3    15619304      Onio          502    France  Female   42   \n",
       "3          4    15701354      Boni          699    France  Female   39   \n",
       "4          5    15737888  Mitchell          850     Spain  Female   43   \n",
       "\n",
       "   Tenure    Balance  NumOfProducts  HasCrCard  IsActiveMember  \\\n",
       "0       2       0.00              1          1               1   \n",
       "1       1   83807.86              1          0               1   \n",
       "2       8  159660.80              3          1               0   \n",
       "3       1       0.00              2          0               0   \n",
       "4       2  125510.82              1          1               1   \n",
       "\n",
       "   EstimatedSalary  Exited  \n",
       "0        101348.88       1  \n",
       "1        112542.58       0  \n",
       "2              NaN       1  \n",
       "3         93826.63       0  \n",
       "4         79084.10       0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 10000 entries, 0 to 9999\n",
      "Data columns (total 14 columns):\n",
      "RowNumber          10000 non-null int64\n",
      "CustomerId         10000 non-null int64\n",
      "Surname            10000 non-null object\n",
      "CreditScore        10000 non-null int64\n",
      "Geography          10000 non-null object\n",
      "Gender             10000 non-null object\n",
      "Age                10000 non-null int64\n",
      "Tenure             10000 non-null int64\n",
      "Balance            9992 non-null float64\n",
      "NumOfProducts      10000 non-null int64\n",
      "HasCrCard          10000 non-null int64\n",
      "IsActiveMember     10000 non-null int64\n",
      "EstimatedSalary    9985 non-null float64\n",
      "Exited             10000 non-null int64\n",
      "dtypes: float64(2), int64(9), object(3)\n",
      "memory usage: 1.1+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dropna(inplace=True)  # dropping the null values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Boxplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'boxes': [<matplotlib.lines.Line2D at 0x7f9ddf13d4a8>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x7f9ddf13deb8>,\n",
       "  <matplotlib.lines.Line2D at 0x7f9ddf0ce320>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x7f9ddf0ceb70>],\n",
       " 'means': [],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x7f9ddf0ce748>],\n",
       " 'whiskers': [<matplotlib.lines.Line2D at 0x7f9ddf13d5f8>,\n",
       "  <matplotlib.lines.Line2D at 0x7f9ddf13da90>]}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qELAhyY1JrgLuBPYN3JMkXbGW9JlGVb2e5B7gALAC2F1VRwZuS5KuWEs6NACqaj+wf+g+JElL//KUJGkJMTQkSd0MDUlSN0NDktTN0JAkdcty+1JTkpPAS0P3IZ3DdcDvhm5COo9/qqqJ+QYtu9CQlqokU1U1GroPaTG8PCVJ6mZoSJK6GRrSm2fX0A1Ii+U9DUlSN880JEndDA3pEkuyO8mJJM8N3Yu0WIaGdOk9BEwO3YR0MRga0iVWVT8FTg3dh3QxGBqSpG6GhiSpm6EhSepmaEiSuhka0iWW5HvA/wL/kuRokm1D9yQtlN8IlyR180xDktTN0JAkdTM0JEndDA1JUjdDQ5LUzdCQJHUzNCRJ3QwNSVK3/wcYH3rYvW5L4wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9de13d58d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot(df.Balance)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9ddf10fb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df.Age, df.CreditScore, '*')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('CreditScore')\n",
    "plt.title('Age/CreditScore plot')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.hist?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([8.26141836e-03, 2.94160667e-02, 4.90674078e-02, 2.52718142e-02,\n",
       "        1.11732298e-02, 7.08315050e-03, 2.81700823e-03, 1.72000022e-03,\n",
       "        2.70866176e-04, 5.41732352e-05]),\n",
       " array([18. , 25.4, 32.8, 40.2, 47.6, 55. , 62.4, 69.8, 77.2, 84.6, 92. ]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9ddf08feb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df.Age.values, normed=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  18.,  165.,  447.,  956., 1442., 1861., 1948., 1523.,  964.,\n",
       "         654.]),\n",
       " array([350., 400., 450., 500., 550., 600., 650., 700., 750., 800., 850.]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2bewlNJKsTbI5yeZdu3ZNoouSpHmMHQJJfga4Cfh8Vb0EXAO8F1gD7AC+fKDbrKr1VTVbVbMzMzPjdlGStBdjhUCSn2IQAF+vqm8BVNVzVfVaVf0Y+Aqvn/LZDhw79PYVrSZJmpJx7g4K8FXgkar6/aH6sqFmnwAebPMbgfOTHJbkOGA18INR9y9JGt84dwd9CPgU8ECS+1rtt4ELkqwBCtgKfAagqh5KciPwMIM7iy7xziBJmq6RQ6Cq/geQeVbdvo/3XAFcMeo+JUmT5TeGJaljhoAkdcwQkKSOjXNhWHuxat1t0+6CJC2IRwKS1DFDQJI6ZghIUscMAUnqmCEgSR0zBCSpY4aAJHXMEJCkjhkCktQxQ0CSOmYISFLHDAFJ6pghIEkdW/QQSHJWkseSzCVZt9j7lyS9blFDIMkhwB8BZwMnMnge8YmL2QdJ0usW+3kCpwJzVfUkQJIbgHMZPHx+4vxdf0nat8U+HbQceGZoeVurSZKm4G35ZLEka4G1bfH/JXlsmv0ZwdHA30y7E4vMMffBMS+S/N5Yb/9nC2242CGwHTh2aHlFq71BVa0H1i9WpyYtyeaqmp12PxaTY+6DY156Fvt00D3A6iTHJXkHcD6wcZH7IElqFvVIoKpeTXIpcAdwCLChqh5azD5Ikl636NcEqup24PbF3u8iO2hPZY3BMffBMS8xqapp90GSNCX+bIQkdcwQGFGSQ5L8MMmtbfm4JHe3n8P4RrvwTZLD2vJcW79qmv0eVZKtSR5Icl+Sza12VJJNSR5vr0e2epJc3cZ8f5KTp9v70SQ5Isk3kzya5JEkH1zKY07yvvb33T29lOTzS3nMAEn+Q5KHkjyY5PokP73UP8/DDIHRfQ54ZGj594CrquqfAz8CLm71i4EftfpVrd3B6heras3Q7XLrgDurajVwZ1uGwc+CrG7TWuCaRe/pZPwB8BdV9S+An2Pw916yY66qx9rfdw1wCvAycDNLeMxJlgP/HpitqvczuGHlfPr4PA9UldMBTgy+33An8K+AW4Ew+DLJoW39B4E72vwdwAfb/KGtXaY9hhHGvBU4eo/aY8CyNr8MeKzN/wlwwXztDpYJeBfw1J5/q6U85j3GeQbwP5f6mHn9VwyOap/PW4Ezl/rneXjySGA0/wX4LeDHbfndwP+tqlfb8vDPYfzkpzLa+hdb+4NNAd9JsqV9oxvgmKra0eafBY5p80vh50GOA3YB/7Wd9vvTJIeztMc87Hzg+ja/ZMdcVduBLwF/Dexg8PncwtL/PP+EIXCAkvwKsLOqtky7L4vsF6rqZAanAC5J8pHhlTX412gp3Wp2KHAycE1VfQD4O14/DQIsyTED0M5/fxz4sz3XLbUxt+sb5zII/fcAhwNnTbVTi8wQOHAfAj6eZCtwA4NTQn8AHJFk9/cuhn8O4yc/ldHWvwt4fjE7PAntPyaqaieD88SnAs8lWQbQXne25gv6eZC3uW3Atqq6uy1/k0EoLOUx73Y2cG9VPdeWl/KYfwl4qqp2VdU/AN9i8Blf0p/nYYbAAaqqy6pqRVWtYnDI/JdV9avA94B/05pdBNzS5je2Zdr6v2z/TR00khye5J275xmcL36QN45tzzFf2O4eOQ14ceh0wkGhqp4Fnknyvlb6KIOfPF+yYx5yAa+fCoKlPea/Bk5L8k+ShNf/zkv28/wm074ocTBPwOnArW3+eOAHwByDw+jDWv2n2/JcW3/8tPs9wjiPB/53mx4CfqfV383gAvnjwHeBo1o9DB4e9ATwAIM7L6Y+jhHGvQbYDNwPfBs4soMxH87gP9t3DdWW+pj/I/Aog39s/htw2FL+PO85+Y1hSeqYp4MkqWOGgCR1zBCQpI4ZApLUMUNAkjpmCEhSxwwBSeqYISBJHfv/TAZPJb+gwvUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9ddf0bdd30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df.CreditScore.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  18.,  165.,  447.,  956., 1442., 1861., 1948., 1523.,  964.,\n",
       "         654.]),\n",
       " array([350., 400., 450., 500., 550., 600., 650., 700., 750., 800., 850.]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kirill/.local/lib/python3.5/site-packages/matplotlib/figure.py:2022: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
      "  warnings.warn(\"This figure includes Axes that are not compatible \"\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9ddf0b8a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, axs = plt.subplots(1, 2, sharey=True, tight_layout=True)\n",
    "\n",
    "# We can set the number of bins with the `bins` kwarg\n",
    "axs[0].hist(df.Age.values, bins=10)  # <-- first subplot (Age histogram)\n",
    "axs[1].hist(df.CreditScore.values, bins=10)  # <-- second subplot (CreditScore)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bar plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 2 artists>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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r6pvzcEzqRFXtafetLuNHHwE/BdiWZBVQwEnTbGId8Kokf9D6zwDOBO5fkAl3xAA4cQV4S1Xt/KFicj7wxEDpewP97/GDP/O/At5XVTvaOu+YZh9PY+os4TvzN211agfwF8D5wHMH6lcBt1bVr7eQ+Ow06wZ4dVX5u2DzzEtAJ66dwG8nOQkgyfPneFp8Cj+4GbdxhjGf4QeXjEjijWgdra3AO6vq7iPqg5/DN82w7k7gLWmnoknOWZAZdsgAOHF9CLgP+EKSe4C/ZW5ndO8A/inJHcz8C4y/C6xpN5nvY+q+gjRnVbW3qq6bZtGfA3+W5E5m/vxexdSloT1J7m19zQO/CSxJnfIMQJI6ZQBIUqcMAEnqlAEgSZ0yACSpUwaAJHXKAJCkThkAktSp/wP4e72P8pJ3fAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9ddef984e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# See the difference in frequency\n",
    "plt.bar(df.Gender.value_counts().keys(), df.Gender.value_counts().values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Horizontal bar plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9ddef134e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# How many people are using how many products?\n",
    "df.NumOfProducts.value_counts().plot(kind='barh',title=\"Number of products\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pie chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9ddefab390>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9ddee858d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Geography.value_counts().plot(kind='pie')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can plot more interesting plots, with matplotlib already embedded into pandas functions. For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9ddee695c0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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8MMmWeYb6Ys6cOXnkkUdy3XXX5dxzz+33tXdE5xAAAAAwfPRx6fnBVErJihUrsmjRolxxxRWZPHly9txzz3zyk5/MOeeck66ursycOTNN02Ty5MlZsWJFv6916aWXZsGCBfmrv/qrnH766X0eN3/+/KxduzZ77713v6+9I6VpmkE/6a6aNWtWs3r16naXAbRZx+KVPdtdS/v+Q3K4GGj9I/31AwBAf9x///2ZPn16u8sY9s4444wsWrQoc+fO3e7z23sfSylrmqaZtbNzu60MAAAAYJh6+umnc9hhh+VVr3rVDoOhgXJbGQAAAMAw9ZrXvCYPPvjgkF5D5xAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDETUgODxlLsAADAQLWWtwb1fJ0LOvt03GWXXZbrrrsuY8eOzZgxY/K5z30uc+bM2aVr3XLLLbnvvvuyePHi/pTaNsIhAAAAoGrf/e53c+utt+buu+/OhAkT8uSTT+aXv/zlLp9n3rx5mTdv3hBUOLTcVgYAAABU7bHHHst+++2XCRMmJEn222+//OZv/mY6Ojpy6aWXptVqZfbs2Vm/fn2S5Ktf/WrmzJmTo48+Om95y1vy+OOPJ0mWLVuWCy+8MEmycOHC/Omf/mne9KY35dBDD82Xv/zl9ry4PhAOAQAAAFU75ZRT8sgjj+Swww7LBz/4wfzzP/9zz3OTJk1KZ2dnLrzwwlx88cVJkt/5nd/J9773vXz/+9/PO9/5zlxxxRXbPe9jjz2WVatW5dZbbx3Wt5q5rQwAAACo2l577ZU1a9bk29/+dr71rW/lHe94R5YuXZokOffcc3u+L1q0KEmyYcOGvOMd78hjjz2WX/7yl5k6dep2z3vWWWdlzJgxmTFjRk930XAkHAIgiQnFAQCo29ixY3PiiSfmxBNPTKvVyvLly5MkpZSeY7ZuX3TRRfmzP/uzzJs3L7fffnuWLFmy3XNuvU0tSZqmGbriB8htZQAAAEDVfvjDH2bdunU9j9euXZtDDjkkSXLDDTf0fD/uuOOSJJs2bcqBBx6YJD0h0kimcwgAAAAYNvq69Pxg2rx5cy666KI8/fTTGTduXH7rt34rV111VW699db85Cc/yZFHHpkJEybki1/8YpJkyZIlOeecc7L33nvn5JNPzo9//OPdXvNgEg4BAAAAVTvmmGPyL//yL9t97pJLLsknP/nJbfadeeaZOfPMM3/t2IULF2bhwoVJtqxc1tvmzZsHpdahIBwC6GbOHQAAoEbCIQAAAIDt6OrqancJu4VwCBg1dP4AAMDI1DTNNquCsWsGuhKa1coAAACAtpk4cWKeeuqpYb3U+3DWNE2eeuqpTJw4sd/n0DkEAAAAtM1BBx2UDRs2ZOPGje0uZcSaOHFiDjrooH6PFw4BAAAAbTN+/PhMnTq13WVUzW1lAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFRMOAQAAABQMeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRvX7gKA4aNj8cqe7a6lp7exEgAAAHYXnUMAAAAAFRMOAQAAAFRMOAQAAABQMXMOwShiziAAAAB2lc4hAAAAgIoJhwAAAAAqJhwCAAAAqJhwCAAAAKBiwiEAAACAigmHAAAAAComHAIAAAComHAIAAAAoGLCIQAAAICKCYcAAAAAKiYcAgAAAKiYcAgAAACgYsIhAAAAgIoJhwAAAAAqJhwCAAAAqJhwCAAAAKBiwiEAAACAigmHAAAAAComHAIAAAComHAIAAAAoGLCIQAAAICKCYcAAAAAKiYcAgAAAKiYcAgAAACgYsIhAAAAgIoJhwAAAAAqJhwCAAAAqJhwCAAAAKBiwiEAAACAigmHAAAAAComHAIAAAComHAIAAAAoGLjdnZAKeXgJH+bZP8kTZKrmqb5dCllnyQ3JOlI0pVkftM0PymllCSfTvK2JM8mWdg0zd1DUz4AW3UsXtmz3bX09DZWAgAAjCR96Rx6IcmHmqaZkeSNSS4opcxIsjjJN5qmmZbkG92Pk+T3kkzr/jovyZWDXjUAAAAAg2Kn4VDTNI9t7fxpmuaZJPcnOTDJmUmWdx+2PMlZ3dtnJvnbZovvJXlNKeV1g145AAAAAAO2S3MOlVI6khyd5F+T7N80zWPdT/1Httx2lmwJjh7pNWxD9z4AAAAAhpk+h0OllL2S3JTk4qZpftr7uaZpmmyZj6jPSinnlVJWl1JWb9y4cVeGAgAAADBI+hQOlVLGZ0sw9IWmaf6he/fjW28X6/7+RPf+R5Mc3Gv4Qd37ttE0zVVN08xqmmbW5MmT+1s/AAAAAAOw03Coe/Wxa5Lc3zTN/+j11C1JFnRvL0jylV77/5+yxRuTbOp1+xkAAAAAw8hOl7JPcnySP07SWUpZ273vI0mWJvlSKeVPkjycZH73c1/LlmXs12fLUvbvGdSKAQAAABg0Ow2HmqZZlaTs4Om52zm+SXLBAOsCAAAAYDfYpdXKAAAAABhdhEMAAAAAFRMOAQAAAFRMOAQAAABQMeEQDLKOxSvTsXhlu8sAAACAPhEOAQAAAFRMOAQAAABQMeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFRMOAQAAABQMeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFRMOAQAAABQMeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFRMOAQAAABQMeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOwTDTsXhlOhavbHcZAAAAVEI4BAAAAFAx4RAAAABAxca1uwAARofet0N2LT29jZUAAAC7QucQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFRMOAQAAABQMeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFRMOAQAAABQMeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFRMOAQAAABQMeEQAMNCx+KV6Vi8st1lAABAdYRDAAAAABXbaThUSrm2lPJEKeUHvfYtKaU8WkpZ2/31tl7PfbiUsr6U8sNSyqlDVTgAAAAAA9eXzqFlSU7bzv7/2TTNG7q/vpYkpZQZSd6Z5IjuMf+rlDJ2sIoFAAAAYHDtNBxqmuaOJP/Zx/OdmeT6pml+0TTNj5OsTzJ7APUBAAAAMIQGMufQhaWUe7pvO9u7e9+BSR7pdcyG7n0AAAAADEP9DYeuTPJfk7whyWNJ/vuunqCUcl4pZXUpZfXGjRv7WQYAAAAAA9GvcKhpmsebpnmxaZqXklydX9069miSg3sdelD3vu2d46qmaWY1TTNr8uTJ/SkDAAAAgAHqVzhUSnldr4dnJ9m6ktktSd5ZSplQSpmaZFqSOwdWIgAAAABDZdzODiilfDHJiUn2K6VsSPLxJCeWUt6QpEnSleQDSdI0zb2llC8luS/JC0kuaJrmxaEpHQAAAICB2mk41DTNudvZfc0rHH9ZkssGUhQAAAAAu8dAVisDAAAAYIQTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFRMOAQAAABQMeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFRMOAQAAABQMeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BMCo0LF4ZToWr2x3GQAAMOIIhwAAAAAqJhwCAAAAqJhwCAAAAKBiwiEAAACAigmHAAAAAComHIKXseIRAAAANREOAQAAAFRMOAQAAABQMeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAw6rWWt9Ja3mp3GQAAAMOScAgAAACgYuPaXQAAO9a746lzQWcbKwEAAEYrnUMAAAAAFRMOAQAAAFRMOAQAAABQMXMOAbwCc/4AAACjnc4hAAAAgIoJhwCGwpJJW74AAACGOeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAkKRj8cp0LF7Z7jIAAGC3Ew4BAAAAVGxcuwsAYOi0lrd6tjsXdLaxEgAAYLjSOQQAAABQMeEQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEOMOh2LV6Zj8cp2lwEAAAAjgnAIAAAAoGLCIQAAAICKCYcAAAAAKiYcAgAAAKiYcAgAAACgYsIhAAAAgIoJhwAAAAAqNq7dBcDLdSxemSTpWnp6mythRFsy6VfbU6e0rw4AAIBhTucQAAAAQMWEQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEDHut5a20lrfaXQYAAMCoJBwCAAAAqJhwCAAAAKBiwiEAAACAigmHAAAAACo2rt0FAIxmvSfS7lzQ2cZKdtGSSd3fN7W3DgAAYMjpHAIAAAComHAIAAAAoGLCIQAAAICKCYeAIdda3tpm7h0AAACGD+EQAAAAQMWsVgYMja2rXSXJ1CntqwMAAIBXpHMIAAAAoGI7DYdKKdeWUp4opfyg1759Sin/WEpZ1/197+79pZTy/5VS1pdS7imlzBzK4gEYppZM2rZ7DAAAGLb60jm0LMlpL9u3OMk3mqaZluQb3Y+T5PeSTOv+Oi/JlYNTJgAAAABDYafhUNM0dyT5z5ftPjPJ8u7t5UnO6rX/b5stvpfkNaWU1w1WsQAwWnUsXpmOxSvbXQYAABXq75xD+zdN81j39n8k2b97+8Akj/Q6bkP3PgAAAACGoQFPSN00TZOk2dVxpZTzSimrSymrN27cONAyAKCtdP4AADBS9Tccenzr7WLd35/o3v9okoN7HXdQ975f0zTNVU3TzGqaZtbkyZP7WQYAAAAAAzGun+NuSbIgydLu71/ptf/CUsr1SeYk2dTr9jNgJOm90tSSTe2rg/7Z+t9v6pT21gEAAAx7Ow2HSilfTHJikv1KKRuSfDxbQqEvlVL+JMnDSeZ3H/61JG9Lsj7Js0neMwQ1AwAAADBIdhoONU1z7g6emrudY5skFwy0KGBwtZa3kiSdCzrbXAl9pvMHAADYTQY8ITUAAAAAI5dwCNip1vJWT/cRAAAAo4twCAAAAKBi/V2tDGB0M+cPAABQCZ1DAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFTMUvYA7FBreatnu3NB524fDwAADD2dQwAAAAAVEw4BAAAAVEw4BAAAAFAxcw4Bw9OSSb/anjqlfXUAAACMcjqHAAAAAComHAIAAAComHAIAAAAoGLCIQAAAICKCYcAAAAAKma1MgCGl94r1S3Z1L46AACgEjqHAAAAAComHAIAAAComHAIAAAAoGLmHILRqve8LVOntK8OYLfoWLwySdK19PQ2VwIAwEijcwgAAACgYjqHABhdrHYGAAC7ROcQAAAAQMWEQwAAAAAVEw4BAAAU+au7AAAaGklEQVQAVEw4BAAAAFAx4RAAAABAxYRDAAAAABUTDgEAAABUTDgEAAAAULFx7S4A2IElk3ptb2pfHQAAAIxqOocAAAAAKiYcAgAAAKiYcAgAAACgYuYcgt2gtbzVs925oLONlcDI4s8OAAAMPZ1DAAAAABUTDgEAAABUTDgEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFRMOAQAAABQsXHtLgAAhkpreatnu3NBZxsrAQCA4UvnEAAAAEDFhEMwArSWt7bpgAAAAIDBIhwCAAAAqJg5h/g1HYtX9mx3LT29jZUAjEBLJvXa3tS+OgAAoI90DgEAAABUTOcQDJXe3QNTp7SvDgAAAHgFOocAAAAAKqZzCAB6M2cQAACV0TkEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFTMhNQMuo7FK5MkXUtPb3MlA9RrUtpWr6XoOxd0tqMagGFr68/9ZBT87AcAqJDOIQAAAICKCYcAAAAAKiYcAgAAAKiYOYcAYJhqLW/1bA/lfGfmDAIAqJvOIQAAAICKCYcAAAAAKiYcAgAAAKiYcAgAAACgYsIhAAAAgIoJhwAAAAAqJhwCAAAAqJhwCAAAAKBiwiEAAACAio1rdwEAMFy1lrd6tjsXdLaxEgAAGDo6hwAAAAAqJhwCAAAAqJhwCAAAAKBiwiEAAACAigmHAAAAAComHAIAAAComHAIAAAAoGLj2l0AADCMLJnUa3vTbrlkx+KVPdtdS0/fLdcEAOBXdA4BAAAAVEw4BAAAAFAxt5UBwHDS+7auqVPaVwcAANXQOQQAAABQMZ1DADBEWstbPdudCzrbWMnoZkJrAICB0TkEAAAAUDHhEAAAAEDFhEMAAAAAFRMOAQAAAFRMOAQAAABQMeEQAAAAQMWEQwAAAAAVGzeQwaWUriTPJHkxyQtN08wqpeyT5IYkHUm6ksxvmuYnAysTAAAAgKEwGJ1DJzVN84amaWZ1P16c5BtN00xL8o3uxwAAAAAMQ0NxW9mZSZZ3by9PctYQXAMAAACAQTDQcKhJclspZU0p5bzuffs3TfNY9/Z/JNl/gNcAAAAAYIgMaM6hJL/TNM2jpZTXJvnHUsoDvZ9smqYppTTbG9gdJp2XJFOmTBlgGQBAkmTJpF7bm9pXBwAAI8aAOoeapnm0+/sTSW5OMjvJ46WU1yVJ9/cndjD2qqZpZjVNM2vy5MkDKQMAAACAfup351ApZc8kY5qmeaZ7+5Qkf5nkliQLkizt/v6VwSgUBqK1vNWz3bmgs42VAIxyI7BzqWPxyp7trqWnt7ESAID2GMhtZfsnubmUsvU81zVN879LKXcl+VIp5U+SPJxk/sDLBAAAAGAo9DscaprmoSRHbWf/U0nmDqQoAAAAAHaPoVjKHgAAAIARYqCrlcGOjcB5JwAAAKA2OocAAAAAKiYcAgAAAKiYcAgAAACgYuYcGoY6Fq/s2e5aevpuHw8AAADUQ+cQAAAAQMWEQwAAAAAVc1sZI0Jreatnu3NBZ98GLZn0q+2pUwa5IgCGRO+f3Us2ta8OAICK6BwCAAAAqJjOIYYvnT8AwBDbupCHRTwAqJnOIQAAAICKCYcAgO1qLW9tM+cbAACjk3AIAAAAoGLCIQAAAICKCYcAAAAAKiYcAgAAAKiYcAgAAACgYuPaXQAAwKBZMqnX9qb21bEbdSxe2bPdtfT0NlYCAIxUOocAAAAAKqZziN2itbzVs925oLONlQDUw89eAAD6QucQAAAAQMWEQwAAAAAVEw4BAAAAVMycQwAAbWS1MQCg3XQOAQAAAFRMOAQAAABQMeEQAAAAQMXMOQQAMADmDAIARjqdQwAAAAAVEw4BAAAAVEw4BAAAAFAx4RAAAABAxUxITZ+0lrd6tjsXdLaxEgBqsfV3j987AABDS+cQAAAAQMV0Dg0BS9oCwAi1ZFKv7U3tqwMAYDfSOQQAAABQMeEQAAAAQMWEQwAAAAAVM+cQADAkrDZWB3MtAsDIp3MIAAAAoGI6h0aIrf/6mvgXWAAYtbaullbRSmk6jwCg/XQOAQAAAFRM59Bo1/0vkK2pU3p27VLn0dZ/wew1HgAAABg9dA4BAAAAVEznEABAxbY3589ImuvQnEUAMHA6hwAAAAAqJhwCAGB0WDLpV/Ml7iYdi1du070EACORcAgAAACgYuYcAgAYLbZ2zSzZ1NYy+j1n0TCpf3fa2nVkviQA2knnEAAAAEDFhEMAAAAAFRMOAQAAAFTMnEMAwKi0dd6bXZrzZhDHV2nrnEFTp7S3DgBgl+gcAgAAAKiYzqHt2LpqRGLlCABgF2ztnEmqWnGLkctqaQAkOocAAAAAqqZzCABgmNk631FiziNemc4fAAaDziEAAACAigmHAAAAACrmtjIAgEHWmjol6b41rB23hbktjZHAIjAAw4fOIQAAAICK6RwCAGCLJZO2fJ86pb11AAC7lc4hAAAAgIrpHAIAAEYccxYBDB6dQwAAAAAVEw4BAAAAVEw4BAAAAFAxcw4BADCstJa3erY7F3S2sZJdsHWltyRZsql9ddDz+Rkxn51+MucSMJh0DgEAAABUTOcQAAC0W6/Oo9bUKT3b/el+GZGdVwC0lc4hAAAAgIrpHOoj/wIDAEBf+HsjACONziEAAACAigmHAAAAAComHAIAAACo2Kicc6hj8cqe7a6lp7exkvSsPNHvVSe2rlzRazwAADtmzh/YuWH1/0xA2+kcAgAAAKjYsOwckmIDALBbbe3WTpIlm9pXByNG7f/PUvvrh9FG5xAAAABAxYZl5xAAALSLOYvaa+v7P9Tvvc6XYWRr556uPWgbnUMAAAAAFRv9nUMDXS0MAABGu15zLu3K35u3dt+M+M6bNsw5pXMJGE50DgEAAABUbPR3DgEAAMNb786dXp1LI9HumjPpla7drusDI5fOIQAAAICKCYcAAAAAKjb8bytrw+Rw273+CG9vBQBgFGv3bVnt/jv7SFfh+7fNhNwT21gIkETnEAAAAEDVhn/nUC/tnNwNAAAYpoZT51Q7r9/fa3ePb/UaP9r/n2ubzqWlp/d7fH/GwnCkcwgAAACgYsIhAABg0LSWt7ZZUp1d4/0D2kE4BAAAAFCxETXnEAAAAKNT746pnc15tO1qZ+/aMr6/cyYNZM6lNq001+45j9p9fQafziEAAACAig1Z51Ap5bQkn04yNsn/3zTN0qG6FgAAwGCwQnL/7Urnz2jUn86n3p03u/P90/kzcg10pb0dGZLOoVLK2CSfTfJ7SWYkObeUMmMorgUAAABA/w1V59DsJOubpnkoSUop1yc5M8l9Q3Q9AAAA2mHrvDu95uyhj3rPWTTA92+gnUf9Gt/POZcGrXOpH9ff3nxV/R4/iJ077e5aHKo5hw5M8kivxxu69wEAAAAwjJSmaQb/pKX8YZLTmqZ5X/fjP04yp2maC3sdc16S87ofvj7JD1/hlPsleXIAJRlv/EgdP5JrN95440fu+JFcu/HGG+9nh/HGG1/X+JFc++4Yf0jTNJN3epamaQb9K8lxSf5Pr8cfTvLhAZxv9QDrMd74ETl+JNduvPHGj9zxI7l244033s8O4403vq7xI7n24TB+69dQ3VZ2V5JppZSppZQ9krwzyS1DdC0AAAAA+mlIJqRumuaFUsqFSf5Ptixlf23TNPcOxbUAAAAA6L+hWq0sTdN8LcnXBul0VxlvfKXjR3Ltxhtv/MgdP5JrN95449s3fiTXbrzxxo/c8SO59uEwPskQTUgNAAAAwMgwVHMOAQAAADACCIcAAAAAKiYcAgAAAKiYcIidKqW8to3X3rdd1waAdmjn793u6/vdWymfPdrJ5w/aSzj0MqWUSaWUpaWUB0op/1lKeaqUcn/3vtcM8Nxf78Mxv1FK+X9LKX9XSnnXy577X30Yf0Ap5cpSymdLKfuWUpaUUjpLKV8qpbyuD+P3ednXvknuLKXsXUrZpw/jT+u1PamUck0p5Z5SynWllP13MnZpKWW/7u1ZpZSHkvxrKeXhUsrv9uHad5dSPlpK+a87O3YH42eVUr5VSvn7UsrBpZR/LKVsKqXcVUo5ug/j9yql/GUp5d7ucRtLKd8rpSzs4/XHlVI+UEr5393v2T2llK+XUs4vpYzvz2vqde6dzmBfShnbff1PlFKOf9lzH+3D+P9SSrm0lHJJKWViKWVhKeWWUsoVpZS9+ln3g7tw7JG9tsd3fxZuKaVcXkr5L30Yf2Gvz99vlVLuKKU8XUr511JKqw/j/6GU8kcDeK2HllKuLaX8Vfdn6epSyg9KKTeWUjr6MH5MKeW9pZSVpZR/6/7zcH0p5cQ+jPXZ+/Vz+uzths9e93i/d9v0e7d7TO2/e4fk8+ez57PXh/F+9vn89evzNwifPX/v+/Vz7s6/9w30710D+rP7SoZdONTuH9RJvpTkJ0lObJpmn6Zp9k1yUve+L/Xh+jN38HVMkjf04fqfT1KS3JTknaWUm0op/7e9c4+2Y7rj+Od387hLhBuPNCgaFY96lEUqSCyPoEQbobGULiWLaktF0dV2oU2xKFos2qXVFiHxqigqjVe945UQJEhCI4QSbxGPksevf+x95TjOvWefM+ecuSf3+1lr1pkzcz5n75n5zeyZPXv2tMZ5Oyb444FngZeBe4CPgRHAA8CfE/y3gMcLhseALwMz4ng5zioYPw94Dfg2MB24pIy7n7u/Fcd/Bxzs7oOAveJ/lWMNoB9wj5lNM7MTzGy9BK+di4FzgX8BDwGXuHsb8Ms4rxxXAS8A3wROAy4CDgN2N7OzOhMjEwgx8hvCNhsR/2cbYGI5uUQhW1jYjkhI/xJgV+Bt4CIzO79g3oEJ/nhgALARYR0OJmxHA/6UkP/FZvZ+HBab2WJg4/bpiem3czYwiBA3q5AW+z8uiL8LgQvcvR/wi0R/CDAKWBBPjA4ws94JXjvjCfvJB8AjwBxgX+A24LIE/1JgQ+C3hH1/cpx2qpkdV8ZV7Cn28oo9ULmbZ7kLKnurjj/FnmKPnGIPFH907/jTNUdzn/eNJ9t5V9Z9t2PcvUsNwLS4cg4hHGxGx+nDgYcT/JuBI4D1gROBXwGbAFcAZyX4c6uZV/CbZcDdhINk8fBxgv9k0fdTgAeBtYAZCf4TBeMLOvvvDvyTCIG5dcG0+RVsvxkdpVcufWA20DOOP1I0b1aFae9COLAujOv+6Izr7okE/6mi79PjZwswJ8F/rpp5RbH3AjC/YGj//mmCP7NgvCfwF+AfQGvi8j8ZPy2udyv4PjPBvwi4EhhQZewVbr8ngV4Vpj+3YHx6R+umXPrA6oQCegrwJuEAvncD4m9m0fdH4mcrMFuxp9jrirFXvPyVzCuKP5W7pZclJf3uXvZWHX+KPcVeXrGn+Ove8VeD2NN5X77nfVmPPZn23c6GnnQ9ern7rQBmdo67TwJw97vM7PcJ/kB3Hx/Hzzez6e5+hpmNIdRun1zGf8nMfg5c4e6vx3wMIFQ4vZyQ/mzgh+7+fPEMM0vxW82sxd2XA7j7mWb2X+B+IKWZXGFrsCuL5vUoJ7v7eWZ2HXBBzO84wBPSbedLZnYiYedY3czMY9RSvqXaxcAUMzsbuM3MLiQcKPYg7HjJuPsDwAPxrvVewMGEA09n/M/M9gbaADezUe5+k4WmpcsSkv3QzIa5+1QzGwm8E/Oy3MwswX/HzA4Cbmjf/mbWAhxEuItUjheA4e6+oHhGYux91tLA3ZcCR5vZOMKJR3ITTXd3M5vSvt3j97Ix5O5j492ua8zsJuCPVBZ7bWZ2ICH2Wt19SSXpA5PMbDxwOnCjmf0UuJEQf19Yp6UWIab3PuGOzIR4B+Ugwl2gO8r4y81sU8JdqD5mNtjdHzOzQSTsu8ASM9vY3eeZ2XbApzE/nyQsv2Ive+wdQDjGNXPstdH42IOVu9wt20I753IXVPZmiT/FXr6x99n27YaxB4q/7hx/uuYg9/O+LNccHZ3zb0LaeVfWfbdjstQs1WMAHgb2JgTnS8CoOH1X4LEE/yFgWBwfCdxeMC+lFn4N4BxC8653CTvb7DhtzQR/NLBZB/NGJfjnAnuWmL4P8HyCfzrQt8T0QcCkCrfFSEJTt4UVOOOKhv5x+jrAlQn+bsB1wBPALMId8KOJNbJl3Gszxt42wO3ArcDmhMc73gOeAXZO9KfFuJnaHgdAf2Bsgj8wLvsbwHNxeCNO2yjBPxbYpoN5xyX4E4F9Skw/CliS4P+tg9jbGJhawXZoAcYSmiW/WoF3edEwoCD27kr8jyOARwlNnRcTKpTPAtoS3Pszxt9wYG483gwjNBV9PsbA/gl+e0XC84Q7N0MK4u/cxNh7M8Zde7qKvTRvfA1ib0wXjb2Ucqs99v4TY2/H1NiLv1O5u8JpeLkbf7sb+ZW92/LFsvddQtk7NMEvLns3LYi/lLK36vhT7DV97JU676sk9r6eV+wp/moWf7t3sfhLuu4oiL33qoy9geiaA7Jdc1xGled9ZD/nz7TvdvrfWeR6DFl2lOhnOlDH324O7FkcdKWCuBN/eB38fRudPuHZya0atfx1XHep/tdq4GeJnSHADoRmgUOBnwEjUtzo7wB8I45vQXi0Mm9/P2Jzzwr9XYBfV5j+kBrmf0tCk+dGrr8hRelXuv13ypJ+9NaKw8RKvBL/k3RiVm8/NfaK3HWBt3PO/4Sc058MtFTwewPWrkX6cd8/iYRH4jrwh8XYb1Z/F+DUnNPPc/03NP143G2L430IF7yTCRfonVbORnf1OL5KdG9JcUukXa1fmP5pGfw+hAuOf1eZ/z4Z81/Ruq/j+q80/cLlr3T9jwU2qCbOV0afgmuOZsx/I/0apN0bOJzQymkt4HuEllTHklYx1gp8n1hBARxKaH1TC793A9LvXeQfRmgNdUwF+T88Y/qFfkXrPzpfJVwnXAicD/yo/XiYZWh/Pq8pMLMx7n55PX0zG0vYMLMJd7OOd/eb47wZ7r5dnf3jgJ/k6OeW/y6w7sYSDgpzcvLHEfrb6gncSahouJdw4L7d3c+s0B9CeO65Wf2sy5+33zTLb2b/LDF5D0LzXtx9ZJm0i30j3I1rVh+yLX/efrMt/zR33yGOH0UoB24itCK+xd3PrsD/QfRvbGL/mAzLfxShHKw2/a6w/hu9/M8Q7oAvtfCWnQ8Jd3GHx+kddo5awv0ImJTidlE/edmVfk3SXxTTnAdcDVzvKzpILkuRf03032xi/+85Ln9Trf8SeZ9UYdpXEc4XVwEWAasSjpvDCTfVDk/0+xAacfQlPJJXCx93P6LBfi2Xv5L0q13/Y4FvER4jG0Fo+fYecABwjLvf25nfKVlrlxo5UNRhUz18QpPCvnF8IKG3/OPj95QOouRX6Tdz3mvo9yAcaN7n83fDUjo3ky+/Kp/wZpCJhOb9u8bP1+L4rglpP9Hkft7Ln3f6ufsF49NZ8WjAqqR1CipffhZ/dsH4jKJ5ZV+kUa0rXz7h2NlCqMi8lPBo922EFgWryZdfx7Rnxs+ewOtAj/g9tUNl+fn6swqcPsC9cXxDEq45Oxu64qvsZ3YwzCK8sq6uPqEZ/QcA7v4i4SR3Xwuv2Evp4Et+9X4z570W/lJ3X+buHwHzPHQui7t/DCyXL7+O/mDCa2RPARZ5uOPwsbvf5+73JaS9fZP7eS9/3unn7beY2RoWOtE2j3c/3f1DYKl8+XX2n7bw0hKAp8xsMICFzkKX1NGVL9/dfbm73+HuRwLrER4t2YfwiIt8+fVKu8XMegOrESoX2uL0VqCX/C7vA5+9WKyV2Am1hw7CU/3SeIaapXoMhNqzbYGvFA0DSegoqgb+3cC2RdN6EnrhXya/fn4z571G/qNAnzjeUjC9jbRXisqXX7Uff7s+cD3huemKW2rKl1+ND7zIilfgvgCsG6f3Je3uu3z5Wfw2Qqfy8wjH0SXxf+6jgw5Xa+HKl08nd/iJ5bl8+XVK+4QYqy8R+i+6C/groUXKOPld3j8emBmdOcCYOL0/GV9S0uX6HDKzS4HL3X1qiXlXu/uhdfbXJ9yBX1hi3lB3f1B+ffxmznuN/FZ3/6TE9LUJJ7uz5Muvl1/k7Ed4U8vJqY58+bXyC/6nD+ENIPPly6+3b2arAxsRbuq84vHV4vV25Xdf38w2dffnKklLvvxapB3/Yz0Ad3/VzPoRXqizwN2nyW8Kf0vCi5Cedvc5KU7S/3a1yiEhhBBCCCGEEEII0Ti6XJ9DQgghhBBCCCGEEKJxqHJICCGEEEIIIYQQohujyiEhhBBCiCLMbJSZuZltnndehBBCCCHqjSqHhBBCCCG+yCHA1PgphBBCCLFSo8ohIYQQQogCzKwvMAw4EvhunNZiZheb2Rwzu9PMppjZ6DhvezO7z8weN7PbzWzdHLMvhBBCCFExqhwSQgghhPg8+wO3xVcFv21m2wMHAgOBLYDDgJ0AzKwX8AdgtLtvD1wGnJlHpoUQQgghqqVn3hkQQgghhOhiHAJcGMevjd97Ate7+3JgoZndE+dvBmwF3GlmAD2A1xqbXSGEEEKIbKhySAghhBAiYmZrAnsAW5uZEyp7HLixIwV4xt13alAWhRBCCCFqjh4rE0IIIYRYwWhggrt/xd0HuvsGwHzgHeA7se+hAcBu8fdzgf5m9tljZma2ZR4ZF0IIIYSoFlUOCSGEEEKs4BC+2EroBmAd4BXgWWAiMANY5O6fEiqUzjGzp4AngZ0bl10hhBBCiOyYu+edByGEEEKILo+Z9XX3D8xsLWAaMNTdF+adLyGEEEKIrKjPISGEEEKINCabWT+gN3CGKoaEEEIIsbKglkNCCCGEEEIIIYQQ3Rj1OSSEEEIIIYQQQgjRjVHlkBBCCCGEEEIIIUQ3RpVDQgghhBBCCCGEEN0YVQ4JIYQQQgghhBBCdGNUOSSEEEIIIYQQQgjRjVHlkBBCCCGEEEIIIUQ35v+bmBvgYav1SQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9ddef1c048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(['Age', 'Geography']).size().unstack('Geography').plot(kind='bar', figsize=(20,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Seaborn basic plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting seaborn\n",
      "Installing collected packages: seaborn\n",
      "Successfully installed seaborn-0.8.1\n",
      "\u001b[33mYou are using pip version 8.1.1, however version 10.0.1 is available.\n",
      "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip3 install seaborn  # for installation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9dd6bea9e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, axes = plt.subplots(nrows=1, ncols=4, figsize=(25, 7))\n",
    "# enumerate returns index of element in list and element itself\n",
    "for (index, col) in enumerate(['CreditScore', 'Age', 'Balance', 'EstimatedSalary']):\n",
    "    sns.boxplot(data=df, y=col, ax=axes[index])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9dded38278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, axes = plt.subplots(nrows=1, ncols=4, figsize=(25, 7))\n",
    "for (index, col) in enumerate(['CreditScore', 'Age', 'Balance', 'EstimatedSalary']):\n",
    "    sns.distplot(df[col], bins=20, ax=axes[index])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RowNumber</th>\n",
       "      <th>CustomerId</th>\n",
       "      <th>CreditScore</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
       "      <th>Balance</th>\n",
       "      <th>NumOfProducts</th>\n",
       "      <th>HasCrCard</th>\n",
       "      <th>IsActiveMember</th>\n",
       "      <th>EstimatedSalary</th>\n",
       "      <th>Exited</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RowNumber</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.004085</td>\n",
       "      <td>0.005191</td>\n",
       "      <td>0.000908</td>\n",
       "      <td>-0.006368</td>\n",
       "      <td>-0.008643</td>\n",
       "      <td>0.008563</td>\n",
       "      <td>0.000625</td>\n",
       "      <td>0.011716</td>\n",
       "      <td>-0.005427</td>\n",
       "      <td>-0.015581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CustomerId</th>\n",
       "      <td>0.004085</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.004191</td>\n",
       "      <td>0.009683</td>\n",
       "      <td>-0.014249</td>\n",
       "      <td>-0.012308</td>\n",
       "      <td>0.017736</td>\n",
       "      <td>-0.013575</td>\n",
       "      <td>0.001613</td>\n",
       "      <td>0.015328</td>\n",
       "      <td>-0.006045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CreditScore</th>\n",
       "      <td>0.005191</td>\n",
       "      <td>0.004191</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.004225</td>\n",
       "      <td>0.001057</td>\n",
       "      <td>0.006442</td>\n",
       "      <td>0.013760</td>\n",
       "      <td>-0.005090</td>\n",
       "      <td>0.026115</td>\n",
       "      <td>-0.001240</td>\n",
       "      <td>-0.026406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>0.000908</td>\n",
       "      <td>0.009683</td>\n",
       "      <td>-0.004225</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.009847</td>\n",
       "      <td>0.028510</td>\n",
       "      <td>-0.030547</td>\n",
       "      <td>-0.011896</td>\n",
       "      <td>0.085518</td>\n",
       "      <td>-0.008016</td>\n",
       "      <td>0.285222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tenure</th>\n",
       "      <td>-0.006368</td>\n",
       "      <td>-0.014249</td>\n",
       "      <td>0.001057</td>\n",
       "      <td>-0.009847</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.012253</td>\n",
       "      <td>0.013068</td>\n",
       "      <td>0.022737</td>\n",
       "      <td>-0.027932</td>\n",
       "      <td>0.008038</td>\n",
       "      <td>-0.013821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Balance</th>\n",
       "      <td>-0.008643</td>\n",
       "      <td>-0.012308</td>\n",
       "      <td>0.006442</td>\n",
       "      <td>0.028510</td>\n",
       "      <td>-0.012253</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.305079</td>\n",
       "      <td>-0.014318</td>\n",
       "      <td>-0.009995</td>\n",
       "      <td>0.012967</td>\n",
       "      <td>0.118469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NumOfProducts</th>\n",
       "      <td>0.008563</td>\n",
       "      <td>0.017736</td>\n",
       "      <td>0.013760</td>\n",
       "      <td>-0.030547</td>\n",
       "      <td>0.013068</td>\n",
       "      <td>-0.305079</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.002597</td>\n",
       "      <td>0.010825</td>\n",
       "      <td>0.013374</td>\n",
       "      <td>-0.049465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HasCrCard</th>\n",
       "      <td>0.000625</td>\n",
       "      <td>-0.013575</td>\n",
       "      <td>-0.005090</td>\n",
       "      <td>-0.011896</td>\n",
       "      <td>0.022737</td>\n",
       "      <td>-0.014318</td>\n",
       "      <td>0.002597</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.012313</td>\n",
       "      <td>-0.010285</td>\n",
       "      <td>-0.007694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IsActiveMember</th>\n",
       "      <td>0.011716</td>\n",
       "      <td>0.001613</td>\n",
       "      <td>0.026115</td>\n",
       "      <td>0.085518</td>\n",
       "      <td>-0.027932</td>\n",
       "      <td>-0.009995</td>\n",
       "      <td>0.010825</td>\n",
       "      <td>-0.012313</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.011161</td>\n",
       "      <td>-0.155444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EstimatedSalary</th>\n",
       "      <td>-0.005427</td>\n",
       "      <td>0.015328</td>\n",
       "      <td>-0.001240</td>\n",
       "      <td>-0.008016</td>\n",
       "      <td>0.008038</td>\n",
       "      <td>0.012967</td>\n",
       "      <td>0.013374</td>\n",
       "      <td>-0.010285</td>\n",
       "      <td>-0.011161</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.011460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Exited</th>\n",
       "      <td>-0.015581</td>\n",
       "      <td>-0.006045</td>\n",
       "      <td>-0.026406</td>\n",
       "      <td>0.285222</td>\n",
       "      <td>-0.013821</td>\n",
       "      <td>0.118469</td>\n",
       "      <td>-0.049465</td>\n",
       "      <td>-0.007694</td>\n",
       "      <td>-0.155444</td>\n",
       "      <td>0.011460</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 RowNumber  CustomerId  CreditScore       Age    Tenure  \\\n",
       "RowNumber         1.000000    0.004085     0.005191  0.000908 -0.006368   \n",
       "CustomerId        0.004085    1.000000     0.004191  0.009683 -0.014249   \n",
       "CreditScore       0.005191    0.004191     1.000000 -0.004225  0.001057   \n",
       "Age               0.000908    0.009683    -0.004225  1.000000 -0.009847   \n",
       "Tenure           -0.006368   -0.014249     0.001057 -0.009847  1.000000   \n",
       "Balance          -0.008643   -0.012308     0.006442  0.028510 -0.012253   \n",
       "NumOfProducts     0.008563    0.017736     0.013760 -0.030547  0.013068   \n",
       "HasCrCard         0.000625   -0.013575    -0.005090 -0.011896  0.022737   \n",
       "IsActiveMember    0.011716    0.001613     0.026115  0.085518 -0.027932   \n",
       "EstimatedSalary  -0.005427    0.015328    -0.001240 -0.008016  0.008038   \n",
       "Exited           -0.015581   -0.006045    -0.026406  0.285222 -0.013821   \n",
       "\n",
       "                  Balance  NumOfProducts  HasCrCard  IsActiveMember  \\\n",
       "RowNumber       -0.008643       0.008563   0.000625        0.011716   \n",
       "CustomerId      -0.012308       0.017736  -0.013575        0.001613   \n",
       "CreditScore      0.006442       0.013760  -0.005090        0.026115   \n",
       "Age              0.028510      -0.030547  -0.011896        0.085518   \n",
       "Tenure          -0.012253       0.013068   0.022737       -0.027932   \n",
       "Balance          1.000000      -0.305079  -0.014318       -0.009995   \n",
       "NumOfProducts   -0.305079       1.000000   0.002597        0.010825   \n",
       "HasCrCard       -0.014318       0.002597   1.000000       -0.012313   \n",
       "IsActiveMember  -0.009995       0.010825  -0.012313        1.000000   \n",
       "EstimatedSalary  0.012967       0.013374  -0.010285       -0.011161   \n",
       "Exited           0.118469      -0.049465  -0.007694       -0.155444   \n",
       "\n",
       "                 EstimatedSalary    Exited  \n",
       "RowNumber              -0.005427 -0.015581  \n",
       "CustomerId              0.015328 -0.006045  \n",
       "CreditScore            -0.001240 -0.026406  \n",
       "Age                    -0.008016  0.285222  \n",
       "Tenure                  0.008038 -0.013821  \n",
       "Balance                 0.012967  0.118469  \n",
       "NumOfProducts           0.013374 -0.049465  \n",
       "HasCrCard              -0.010285 -0.007694  \n",
       "IsActiveMember         -0.011161 -0.155444  \n",
       "EstimatedSalary         1.000000  0.011460  \n",
       "Exited                  0.011460  1.000000  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9dd870c780>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9dda2e5c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.pairplot?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7f9dd6c23080>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9dd6c23c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot pairwise relationships in a dataset.\n",
    "sns.pairplot(data=df, vars=['CreditScore', 'Age', 'Balance', 'EstimatedSalary'], kind='scatter')  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Extra"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://github.com/luminousmen/python_for_ds\n",
    "    \n",
    "Filename: PoliceKillingsUS.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "kill = pd.read_csv('PoliceKillingsUS.csv', encoding='windows-1252')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>date</th>\n",
       "      <th>manner_of_death</th>\n",
       "      <th>armed</th>\n",
       "      <th>age</th>\n",
       "      <th>gender</th>\n",
       "      <th>race</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>signs_of_mental_illness</th>\n",
       "      <th>threat_level</th>\n",
       "      <th>flee</th>\n",
       "      <th>body_camera</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
       "      <td>Tim Elliot</td>\n",
       "      <td>02/01/15</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>53.0</td>\n",
       "      <td>M</td>\n",
       "      <td>A</td>\n",
       "      <td>Shelton</td>\n",
       "      <td>WA</td>\n",
       "      <td>True</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>Lewis Lee Lembke</td>\n",
       "      <td>02/01/15</td>\n",
       "      <td>shot</td>\n",
       "      <td>gun</td>\n",
       "      <td>47.0</td>\n",
       "      <td>M</td>\n",
       "      <td>W</td>\n",
       "      <td>Aloha</td>\n",
       "      <td>OR</td>\n",
       "      <td>False</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>John Paul Quintero</td>\n",
       "      <td>03/01/15</td>\n",
       "      <td>shot and Tasered</td>\n",
       "      <td>unarmed</td>\n",
       "      <td>23.0</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>Wichita</td>\n",
       "      <td>KS</td>\n",
       "      <td>False</td>\n",
       "      <td>other</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>Matthew Hoffman</td>\n",
       "      <td>04/01/15</td>\n",
       "      <td>shot</td>\n",
       "      <td>toy weapon</td>\n",
       "      <td>32.0</td>\n",
       "      <td>M</td>\n",
       "      <td>W</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>CA</td>\n",
       "      <td>True</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9</td>\n",
       "      <td>Michael Rodriguez</td>\n",
       "      <td>04/01/15</td>\n",
       "      <td>shot</td>\n",
       "      <td>nail gun</td>\n",
       "      <td>39.0</td>\n",
       "      <td>M</td>\n",
       "      <td>H</td>\n",
       "      <td>Evans</td>\n",
       "      <td>CO</td>\n",
       "      <td>False</td>\n",
       "      <td>attack</td>\n",
       "      <td>Not fleeing</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id                name      date   manner_of_death       armed   age  \\\n",
       "0   3          Tim Elliot  02/01/15              shot         gun  53.0   \n",
       "1   4    Lewis Lee Lembke  02/01/15              shot         gun  47.0   \n",
       "2   5  John Paul Quintero  03/01/15  shot and Tasered     unarmed  23.0   \n",
       "3   8     Matthew Hoffman  04/01/15              shot  toy weapon  32.0   \n",
       "4   9   Michael Rodriguez  04/01/15              shot    nail gun  39.0   \n",
       "\n",
       "  gender race           city state  signs_of_mental_illness threat_level  \\\n",
       "0      M    A        Shelton    WA                     True       attack   \n",
       "1      M    W          Aloha    OR                    False       attack   \n",
       "2      M    H        Wichita    KS                    False        other   \n",
       "3      M    W  San Francisco    CA                     True       attack   \n",
       "4      M    H          Evans    CO                    False       attack   \n",
       "\n",
       "          flee  body_camera  \n",
       "0  Not fleeing        False  \n",
       "1  Not fleeing        False  \n",
       "2  Not fleeing        False  \n",
       "3  Not fleeing        False  \n",
       "4  Not fleeing        False  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kill.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2535 entries, 0 to 2534\n",
      "Data columns (total 14 columns):\n",
      "id                         2535 non-null int64\n",
      "name                       2535 non-null object\n",
      "date                       2535 non-null object\n",
      "manner_of_death            2535 non-null object\n",
      "armed                      2526 non-null object\n",
      "age                        2458 non-null float64\n",
      "gender                     2535 non-null object\n",
      "race                       2340 non-null object\n",
      "city                       2535 non-null object\n",
      "state                      2535 non-null object\n",
      "signs_of_mental_illness    2535 non-null bool\n",
      "threat_level               2535 non-null object\n",
      "flee                       2470 non-null object\n",
      "body_camera                2535 non-null bool\n",
      "dtypes: bool(2), float64(1), int64(1), object(10)\n",
      "memory usage: 242.7+ KB\n"
     ]
    }
   ],
   "source": [
    "kill.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "kill.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Manner of death')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9dd4379cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, axes = plt.subplots(nrows=1, ncols=2, figsize=(20, 7))\n",
    "\n",
    "sns.countplot(kill.gender, ax=axes[0])\n",
    "axes[0].set_title('Genders killed', color='blue', fontsize=15)\n",
    "sns.countplot(kill.manner_of_death, ax=axes[1])\n",
    "axes[1].set_title('Manner of death', color='blue', fontsize=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Kill weapon')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9dd4383198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# kill weapon\n",
    "armed = kill.armed.value_counts()\n",
    "plt.figure(figsize=(20,7))\n",
    "sns.barplot(x=armed[:7].index,y=armed[:7].values)\n",
    "plt.ylabel('Number of Weapon')\n",
    "plt.xlabel('Weapon Types')\n",
    "plt.title('Kill weapon',color = 'blue',fontsize=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Threat types')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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OAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQKxacqur0qrqyqi6aG9u/qs6pqk9Mz/tN41VVL6yqLVV1YVUdPvea46b5n6iq41ZqvQAAAACMsZJnOJ2R5Ojtxp6W5NzuPjTJudN+khyT5NDpsSnJS5JZoEpycpL7JDkiycnbIhUAAAAAu6YVC07d/Y4kV203vDHJmdP2mUkePjd+Vs+cl2TfqjowyYOTnNPdV3X31UnOyXdHLAAAAAB2Iat9D6c7dffl0/YVSe40bR+U5JK5eZdOYzsa/y5VtamqNlfV5q1bt45dNQAAAADLtrCbhnd3J+mB73dqd2/o7g1r164d9bYAAAAA7KTVDk6fny6Vy/R85TR+WZKD5+atm8Z2NA4AAADALmq1g9PZSbZ909xxSd4wN/646dvqjkxyzXTp3VuSPKiq9ptuFv6gaQwAAACAXdSalXrjqnpFkvsnOaCqLs3s2+aen+RVVXVCks8medQ0/c1JHpJkS5KvJzk+Sbr7qqp6TpL3TvOe3d3b34gcAAAAgF3IigWn7n7MDg4dtcTcTnLiDt7n9CSnD1waAAAAACtoYTcNBwAAAGDPJDgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMNRCglNV/c+q+nBVXVRVr6iq21bVIVV1flVtqaq/qaq9p7m3mfa3TMfXL2LNAAAAACzPqgenqjooya8l2dDd90iyV5JHJ/n9JKd09w8nuTrJCdNLTkhy9TR+yjQPAAAAgF3Uoi6pW5Nkn6pak+R2SS5P8oAkr5mOn5nk4dP2xmk/0/GjqqpWca0AAAAA7IRlBaeqOnc5Y8vR3Zcl+cMkn8ssNF2T5IIkX+ru66ZplyY5aNo+KMkl02uvm+Z//xLr2VRVm6tq89atW2/K0gAAAAAY4AaD03Rvpf2THFBV+1XV/tNjfb4ThHZKVe2X2VlLhyS5c5LvSXL0TXmved19andv6O4Na9euvblvBwAAAMBNtOZGjv9SkidnFoYuSLLtUrYvJ/mzm/iZD0zy6e7emiRV9dok90uyb1Wtmc5iWpfksmn+ZUkOTnLpdAneHZJ88SZ+NgAAAAAr7AbPcOruP+3uQ5L8Rnf/UHcfMj1+rLtvanD6XJIjq+p2072YjkpycZK3JXnkNOe4JG+Yts+e9jMdf2t39038bAAAAABW2I2d4ZQk6e4XVdV9k6yff013n7WzH9jd51fVa5K8L8l1Sd6f5NQkb0ryyqp67jR22vSS05K8rKq2JLkqs2+0AwAAAGAXtazgVFUvS3LXJB9I8u/TcCfZ6eCUJN19cpKTtxv+VJIjlpj7jSTH3pTPAQAAAGD1LSs4JdmQ5DCXsgEAAABwY27wHk5zLkryAyu5EAAAAAD2DMs9w+mAJBdX1XuSfHPbYHf/zIqsCgAAAIDd1nKD07NWchEAAAAA7DmW+y11/7zSCwEAAABgz7Dcb6n7SmbfSpckeye5dZKvdff3rdTCAAAAANg9LfcMp+/dtl1VlWRjkiNXalEAAAAA7L6W+y1139Yzr0/y4BVYDwAAAAC7ueVeUvezc7u3SrIhyTdWZEUAAAAA7NaW+y11Pz23fV2Sz2R2WR0AAAAAXM9y7+F0/EovBAAAAIA9w7Lu4VRV66rqdVV15fT426pat9KLAwAAAGD3s9ybhr80ydlJ7jw9/m4aAwAAAIDrWW5wWtvdL+3u66bHGUnWruC6AAAAANhNLTc4fbGqHltVe02Pxyb54kouDAAAAIDd03KD0xOSPCrJFUkuT/LIJI9foTUBAAAAsBtb1rfUJXl2kuO6++okqar9k/xhZiEKAAAAAL5tuWc4/ei22JQk3X1VknutzJIAAAAA2J0tNzjdqqr227YzneG03LOjAAAAALgFWW40+qMk766qV0/7xyZ53sosCQAAAIDd2bKCU3efVVWbkzxgGvrZ7r545ZYFAAAAwO5q2ZfFTYFJZAIAAADgBi33Hk4AAAAAsCyCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADLVm0QsAgN3N5579nxa9BIAdusvvfGjRSwAAZzgBAAAAMJbgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMtJDhV1b5V9Zqq+mhVfaSqfryq9q+qc6rqE9PzftPcqqoXVtWWqrqwqg5fxJoBAAAAWJ5FneH0p0n+obv/Q5IfS/KRJE9Lcm53H5rk3Gk/SY5Jcuj02JTkJau/XAAAAACWa9WDU1XdIclPJjktSbr72u7+UpKNSc6cpp2Z5OHT9sYkZ/XMeUn2raoDV3nZAAAAACzTIs5wOiTJ1iQvrar3V9VfVtX3JLlTd18+zbkiyZ2m7YOSXDL3+kunseupqk1VtbmqNm/dunUFlw8AAADADVlEcFqT5PAkL+nueyX5Wr5z+VySpLs7Se/Mm3b3qd29obs3rF27dthiAQAAANg5iwhOlya5tLvPn/Zfk1mA+vy2S+Wm5yun45clOXju9eumMQAAAAB2QasenLr7iiSXVNWPTENHJbk4ydlJjpvGjkvyhmn77CSPm76t7sgk18xdegcAAADALmbNgj73V5O8vKr2TvKpJMdnFr9eVVUnJPlskkdNc9+c5CFJtiT5+jQXAAAAgF3UQoJTd38gyYYlDh21xNxOcuKKLwoAAACAIRZxDycAAAAA9mCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDLSw4VdVeVfX+qnrjtH9IVZ1fVVuq6m+qau9p/DbT/pbp+PpFrRkAAACAG7fIM5xOSvKRuf3fT3JKd/9wkquTnDCNn5Dk6mn8lGkeAAAAALuohQSnqlqX5KFJ/nLaryQPSPKaacqZSR4+bW+c9jMdP2qaDwAAAMAuaFFnOP1Jkt9M8q1p//uTfKm7r5v2L01y0LR9UJJLkmQ6fs00/3qqalNVba6qzVu3bl3JtQMAAABwA1Y9OFXVw5Jc2d0XjHzf7j61uzd094a1a9eOfGsAAAAAdsKaBXzm/ZL8TFU9JMltk3xfkj9Nsm9VrZnOYlqX5LJp/mVJDk5yaVWtSXKHJF9c/WUDAAAAsByrfoZTdz+9u9d19/okj07y1u7++SRvS/LIadpxSd4wbZ897Wc6/tbu7lVcMgAAAAA7YZHfUre9pyZ5SlVtyeweTadN46cl+f5p/ClJnrag9QEAAACwDIu4pO7buvvtSd4+bX8qyRFLzPlGkmNXdWEAAAAA3GS70hlOAAAAAOwBBCcAAAAAhhKcAAAAABhKcAIAAABgKMEJAAAAgKEEJwAAAACGEpwAAAAAGEpwAgAAAGAowQkAAACAoQQnAAAAAIYSnAAAAAAYSnACAAAAYCjBCQAAAIChBCcAAAAAhhKcAAAAABhKcAIAAABgKMEJAAAAgKEEJwAAAACGEpwAAAAAGEpwAgAAAGAowQkAAACAoQQnAAAAAIYSnAAAAAAYSnACAAAAYCjBCQAAAIChBCcAAAAAhhKcAAAAABhKcAIAAABgKMEJAAAAgKEEJwAAAACGEpwAAAAAGEpwAgAAAGAowQkAAACAoQQnAAAAAIYSnAAAAAAYSnACAAAAYCjBCQAAAIChBCcAAAAAhhKcAAAAABhKcAIAAABgKMEJAAAAgKEEJwAAAACGEpwAAAAAGEpwAgAAAGAowQkAAACAoQQnAAAAAIYSnAAAAAAYSnACAAAAYCjBCQAAAIChBCcAAAAAhhKcAAAAABhKcAIAAABgKMEJAAAAgKEEJwAAAACGEpwAAAAAGEpwAgAAAGAowQkAAACAoQQnAAAAAIYSnAAAAAAYSnACAAAAYCjBCQAAAIChBCcAAAAAhlr14FRVB1fV26rq4qr6cFWdNI3vX1XnVNUnpuf9pvGqqhdW1ZaqurCqDl/tNQMAAACwfIs4w+m6JL/e3YclOTLJiVV1WJKnJTm3uw9Ncu60nyTHJDl0emxK8pLVXzIAAAAAy7Xqwam7L+/u903bX0nykSQHJdmY5Mxp2plJHj5tb0xyVs+cl2TfqjpwlZcNAAAAwDIt9B5OVbU+yb2SnJ/kTt19+XToiiR3mrYPSnLJ3Msunca2f69NVbW5qjZv3bp1xdYMAAAAwA1bWHCqqtsn+dskT+7uL88f6+5O0jvzft19andv6O4Na9euHbhSAAAAAHbGQoJTVd06s9j08u5+7TT8+W2Xyk3PV07jlyU5eO7l66YxAAAAAHZBi/iWukpyWpKPdPcfzx06O8lx0/ZxSd4wN/646dvqjkxyzdyldwAAAADsYtYs4DPvl+QXknyoqj4wjT0jyfOTvKqqTkjy2SSPmo69OclDkmxJ8vUkx6/ucgEAAADYGasenLr7nUlqB4ePWmJ+JzlxRRcFAAAAwDAL/ZY6AAAAAPY8ghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4AQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMJTgBAAAAMBQghMAAAAAQwlOAAAAAAwlOAEAAAAwlOAEAAAAwFCCEwAAAABDCU4AAAAADCU4AQAAADCU4ATetybZAAAK7klEQVQAAADAUIITAAAAAEMJTgAAAAAMJTgBAAAAMNSaRS8AAABgEe73ovstegkAO/SuX33XopdwszjDCQAAAIChBCcAAAAAhhKcAAAAABhKcAIAAABgKMEJAAAAgKEEJwAAAACGEpwAAAAAGEpwAgAAAGAowQkAAACAoQQnAAAAAIYSnAAAAAAYSnACAAAAYCjBCQAAAIChBCcAAAAAhhKcAAAAABhKcAIAAABgKMEJAAAAgKEEJwAAAACGEpwAAAAAGEpwAgAAAGAowQkAAACAoQQnAAAAAIYSnAAAAAAYSnACAAAAYCjBCQAAAIChBCcAAAAAhhKcAAAAABhKcAIAAABgKMEJAAAAgKEEJwAAAACGEpwAAAAAGEpwAgAAAGAowQkAAACAoQQnAAAAAIYSnAAAAAAYSnACAAAAYCjBCQAAAIChdpvgVFVHV9XHqmpLVT1t0esBAAAAYGm7RXCqqr2SvDjJMUkOS/KYqjpssasCAAAAYCm7RXBKckSSLd39qe6+Nskrk2xc8JoAAAAAWEJ196LXcKOq6pFJju7uX5z2fyHJfbr7SXNzNiXZNO3+SJKPrfpCYXUdkOQLi14EADeb3+cAewa/z7kl+MHuXruciWtWeiWrpbtPTXLqotcBq6WqNnf3hkWvA4Cbx+9zgD2D3+dwfbvLJXWXJTl4bn/dNAYAAADALmZ3CU7vTXJoVR1SVXsneXSSsxe8JgAAAACWsFtcUtfd11XVk5K8JcleSU7v7g8veFmwaC4hBdgz+H0OsGfw+xzm7BY3DQcAAABg97G7XFIHAAAAwG5CcAIAAABgKMEJdkFV9Yy57X2r6ok3473OqKpHjlkZADfF9r/Lq+r+VfXGRa4JgJmqentVbbiROU+uqtut4Br+ddD7rK+qi0a8F9xcghPsmp4xt71vkpscnADYJQz9XV5Vu8UXvwDsQZ6cZKeCU1Xttdy53X3fnV4R7OIEJ1iwqnp9VV1QVR+uqk1V9fwk+1TVB6rq5Umen+Su0/4Lqur2VXVuVb2vqj5UVRvn3utxVXVhVX2wql62xGc9Zzrjadl/+AGw86rqKVV10fR4crb7XT5Nu31VvaaqPlpVL6+qml5776r65+nPhrdU1YHT+Nur6k+qanOSkxbzkwHserY/q6eqfqOqnjX93vz9qnpPVX28qv7LdHyfqnplVX2kql6XZJ+51z6oqt49/V371dPfvX8tyZ2TvK2q3rajedP4Z6bPfF+SY6c1nFJVm6fP+89V9dqq+kRVPXfuc786Pd9/es3O/Plw7+nv/x9McuIK/+eGZfN/x2DxntDdV1XVPknem+Snkjypu++ZzP4ATXKPuf01SR7R3V+uqgOSnFdVZyc5LMkzk9y3u79QVfvPf8j0D5zvTXJ8+3pKgBVTVfdOcnyS+ySpJOcneWyu/7v8/knuleTuSf5vkncluV9VnZ/kRUk2dvfWqvofSZ6X5AnT2+/d3Td42QcA17Omu4+oqockOTnJA5P8SpKvd/d/rKofTfK+JJn+bv3MJA/s7q9V1VOTPKW7n11VT0nyX6e/Zy85L8mzp8/8YncfPr3nLye5trs3VNVJSd6Q5N5Jrkryyao6pbu/uN2ad/bPh5dm9u+Hd8z9Tw1YOMEJFu/XquoR0/bBSQ69kfmV5Peq6ieTfCvJQUnulOQBSV7d3V9Iku7/3969xdhV1XEc//6kLWKBEmuNUcE+cC1Via1KkZqYNDE1xkAgIUBCCkbjg5cXHgiJl5gGwSsxGBMuUYJoiooGpFQaban23tKxpYIxUR5EghitgSLYlr8Pe9Wcmcyt03OcgXw/yeTsvfZae/9zHtbe899rrVP/6GnzeWB7VX2yr5FLkkZzMfCzqjoIkOR+YPko9XZU1V9anSFgIXAAWAysby+0TwCe6WmzZnBhS9Jr0v3tczddPwvwQeDbAFW1N8neVn4h3Uvcza0PngNsHeWcE9Ub2Vc/0D73Afur6hmAJH+ie/4fmXCa9P0hyWnAaVW1qbW9B1g56jch/Z+ZcJKmUXvDvQJYVlUvJtkIvH6CZlcDC4AlVXUoyVOTaLMTWJLkjSMSUZKk6fNyz/YRuuey0P0zsmyMNgcHHpUkvfocZvhyMb3Pxkf72qP97HgCrK+qK4+z3si++mgMrzC8739ljJgmfX9oCSdpRnINJ2l6zQP+2ZJN59K9LQE4lGR2236ebipcb5u/tWTTh4B3tPJf080Tnw8wYkrdOrr1Qx5K0nsuSVL//Qa4JMkbkswFLqWbEjGZ/vcPwIIkywCSzE5y/uBClaTXhGeBNyeZn+RE4KMT1N8EXAWQZDHwrla+jW762pnt2NwkZ7djvc/k49UblFHvD1V1ADiQ5OJW7+oBxyFNmgknaXqtA2YleYIuIbStld8O7E1yb5vTvTndwrNfA+4FlibZB1wDPAlQVfvp5nE/2hYM/Gbvharqx8AdwANtvShJ0gBU1WPA94EddOs33VlVuxnel4/V9j/A5cAtrS8fAvzlIkkaR1Udols/aQewnvZ8PI7v0v1wwxOt3e52nueAVcCP2jS7rcC5rc3twLokGyaoNxAT3B+uBb7Tpt9lkHFIxyKuHSxJkiRJkqR+coSTJEmSJEmS+sqEkyRJkiRJkvrKhJMkSZIkSZL6yoSTJEmSJEmS+sqEkyRJkiRJkvpq1nQHIEmSNJ2SzAd+1XbfAhwBngMWAn+tqkUDuOYFwFurau2I8g8Dt7TdM4GngX8De6vqmn7HIUmSNCipqumOQZIkaUZI8iXghar6epKFwC+qavEEbWZV1eFjvM4qYGlVfXqcOhuB66tq17GcW5IkaSZwSp0kSdLYTkhyR5L9SR5JchJ0yaAktybZBXwuyYIkP02ys/19oNV7X5KtSfYk2ZLknCRzgC8DVyQZSnLFZAJp7Rf37G9Lcn6S1Unubvt/THJdT50bkuxIsjfJF1rZKUkeTvK7JI8nubyP35ckSRLglDpJkqTxnAVcWVWfSHIfcBnwg3ZsTlUtBUjyQ+BbVfXbJGcAvwTOA54EllfV4SQrgJuq6rKW/Bl3hNMo7gJWAdcnWUQ3Un1/EoB3AhcBpwKPJXkIWAKcAbwfCLA2yUXA6cBTVbWyxT5val+NJEnS2Ew4SZIkje3PVTXUtnfTret01Jqe7RXAopb8ATg1ycnAPODuJGcBBcw+jljWAHuS3ABcB3yv59jPq+ol4KUkm4D3tphWAntanZOBs4HtwM1JbgYerKrNxxGTJEnSqEw4SZIkje3lnu0jwEk9+wd7tl8HXNiSPv+T5DZgQ1Vd2taE2jjVQKrqhbau08foRlpd0Ht4ZHW6UU2rq+qukedKshT4CF3i6eGqummqcUmSJI3GNZwkSZKO3yPAZ47utF+hg26E09Nte1VP/eeBU6ZwnTuB24AtVfWvnvJLkpyYZAGwHNhFN63v40nmtpjenuRNSd5GtzD6PcA3gPdMIQ5JkqRxmXCSJEk6fp8FlrbFuX8PfKqVfxX4SpI9DB9ZvoFuCt6kFw0HqKrtwIsMn04H8DjwKLAF+GJVPVtVa4GfANuS7APuo5tW925gZ5Ih4EbA0U2SJKnvUjVyBLYkSZJmoiSnA+uB86o9xCVZDfy9qm6d1uAkSZJ6OMJJkiTpVSDJtXQjmG4s3xhKkqQZzhFOkiRJkiRJ6itHOEmSJEmSJKmvTDhJkiRJkiSpr0w4SZIkSZIkqa9MOEmSJEmSJKmvTDhJkiRJkiSpr/4LmDYOygVtIAgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9dd43249b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Threat types\n",
    "plt.figure(figsize=(20,10))\n",
    "sns.countplot(kill.threat_level)  \n",
    "plt.xlabel('Threat Types')\n",
    "plt.title('Threat types',color = 'blue', fontsize = 15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Most dangerous cities')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AYAB7jUBVdaWq+vuq+qeq+nhVnTwvv0FVfaiq/qWqXl1Vh2z8uAAAAADsj9XsCXRRktt3908lOTrJXarqZ5L8QZJTuvuHk3wpyYM2bkwAAAAA1mKvEagnX50vHjy/dZLbJ3ndvPy0JPfakAkBAAAAWLNVnROoqg6qqtOTnJvknUn+NckF3f3teZUzk1xnD597QlXtrKqdu3btWo+ZAQAAANhHq4pA3X1xdx+d5LpJjk3yY6u9g+4+tbt3dPeO7du37+eYAAAAAKzFPr06WHdfkOQ9SW6e5OpVtW2+6rpJzlrn2QAAAABYJ6t5dbDtVXX1+eMrJ7ljkk9mikHHz6s9IMkbN2pIAAAAANZm295XyRFJTquqgzJFo9d091uq6hNJXlVV/zPJPyZ5yQbOCQAAAMAa7DUCdfdHkxyzwvLPZDo/EAAAAACXc/t0TiAAAAAADkwiEAAAAMAARCAAAACAAYhAAAAAAAMQgQAAAAAGIAIBAAAADEAEAgAAABiACAQAAAAwABEIAAAAYAAiEAAAAMAARCAAAACAAYhAAAAAAAMQgQAAAAAGIAIBAAAADEAEAgAAABiACAQAAAAwABEIAAAAYAAiEAAAAMAARCAAAACAAYhAAAAAAAMQgQAAAAAGIAIBAAAADEAEAgAAABiACAQAAAAwgG2LHoDF+8L/On7RIxwwjnzk6xY9AgAAAOwXewIBAAAADEAEAgAAABiACAQAAAAwABEIAAAAYAAiEAAAAMAARCAAAACAAYhAAAAAAAMQgQAAAAAGIAIBAAAADEAEAgAAABiACAQAAAAwABEIAAAAYAAiEAAAAMAARCAAAACAAYhAAAAAAAMQgQAAAAAGIAIBAAAADEAEAgAAABiACAQAAAAwABEIAAAAYAAiEAAAAMAARCAAAACAAYhAAAAAAAMQgQAAAAAGIAIBAAAADEAEAgAAABiACAQAAAAwABEIAAAAYAAiEAAAAMAARCAAAACAAYhAAAAAAAMQgQAAAAAGIAIBAAAADEAEAgAAABiACAQAAAAwABEIAAAAYAAiEAAAAMAARCAAAACAAYhAAAAAAAMQgQAAAAAGsNcIVFXXq6r3VNUnqurjVXXSvPzJVXVWVZ0+v91t48cFAAAAYH9sW8U6307y6O7+h6q6apKPVNU75+tO6e5nbdx4AAAAAKyHvUag7j47ydnzx1+pqk8muc5GDwYAAADA+tmncwJV1VFJjknyoXnRiVX10ap6aVVdYw+fc0JV7ayqnbt27VrTsAAAAADsn1VHoKo6NMlfJHlUd1+Y5PlJbpjk6Ex7Cj17pc/r7lO7e0d379i+ffs6jAwAAADAvlpVBKqqgzMFoFd09+uTpLu/2N0Xd/d3krwoybEbNyYAAAAAa7GaVwerJC9J8snu/sMly49YstpxSc5Y//EAAAAAWA+reXWwWya5f5KPVdXp87LHJ7lvVR2dpJN8LslDN2RCAAAAANZsNa8O9oEktcJVb13/cQAAAADYCPv06mAAAAAAHJhEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwAC2LXoAGNE7XnK3RY9wwLjzg9666BEAAAC2BHsCAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAALYtegCAzfDC/33nRY9wwHjo/d+x6BEAAIANYE8gAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAHsNQJV1fWq6j1V9Ymq+nhVnTQvv2ZVvbOqPj2/v8bGjwsAAADA/ljNnkDfTvLo7r5xkp9J8oiqunGSxyV5V3ffKMm75ssAAAAAXA7tNQJ199nd/Q/zx19J8skk10lyzySnzaudluReGzUkAAAAAGuzT+cEqqqjkhyT5ENJDu/us+erzkly+B4+54Sq2llVO3ft2rWGUQEAAADYX6uOQFV1aJK/SPKo7r5w6XXd3Ul6pc/r7lO7e0d379i+ffuahgUAAABg/6wqAlXVwZkC0Cu6+/Xz4i9W1RHz9UckOXdjRgQAAABgrVbz6mCV5CVJPtndf7jkqjclecD88QOSvHH9xwMAAABgPWxbxTq3THL/JB+rqtPnZY9P8vQkr6mqByX5fJJ7b8yIAAAAAKzVXiNQd38gSe3h6jus7zgAAAAAbIR9enUwAAAAAA5MIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMIBtix4AgK3p199wl0WPcMB42XFvX/QIAAAMwJ5AAAAAAAMQgQAAAAAGIAIBAAAADEAEAgAAABiACAQAAAAwABEIAAAAYAAiEAAAAMAARCAAAACAAYhAAAAAAAMQgQAAAAAGIAIBAAAADEAEAgAAABiACAQAAAAwABEIAAAAYADbFj0AALA+7v6GZy56hAPGXx33mEWPAACw6ewJBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAA9i26AEAAA5U93jdKxY9wgHjLcf/6qJHAIDh2RMIAAAAYAAiEAAAAMAARCAAAACAAYhAAAAAAAMQgQAAAAAGIAIBAAAADEAEAgAAABiACAQAAAAwABEIAAAAYAAiEAAAAMAARCAAAACAAew1AlXVS6vq3Ko6Y8myJ1fVWVV1+vx2t40dEwAAAIC1WM2eQC9PcpcVlp/S3UfPb29d37EAAAAAWE97jUDd/b4k52/CLAAAAABskG1r+NwTq+rXkuxM8uju/tJKK1XVCUlOSJIjjzxyDXcHAMDo7vW6dy16hAPGXx5/h3W5nUe+4d/W5XZG8L+Ou96iRwC4TPt7YujnJ7lhkqOTnJ3k2XtasbtP7e4d3b1j+/bt+3l3AAAAAKzFfkWg7v5id1/c3d9J8qIkx67vWAAAAACsp/2KQFV1xJKLxyU5Y0/rAgAAALB4ez0nUFX9eZLbJjmsqs5M8qQkt62qo5N0ks8leegGzggAAADAGu01AnX3fVdY/JINmAUAAACADbK/J4YGAAAA4AAiAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAawbdEDAAAAcKm3vfq8RY9wwLjrLx+2Lrfzueecsy63M4KjHnXtRY/AGtgTCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxg26IHAAAAAMbyxed+cNEjHDAOP+nm63Zb9gQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMYK8RqKpeWlXnVtUZS5Zds6reWVWfnt9fY2PHBAAAAGAtVrMn0MuT3GXZsscleVd33yjJu+bLAAAAAFxO7TUCdff7kpy/bPE9k5w2f3xaknut81wAAAAArKP9PSfQ4d199vzxOUkO39OKVXVCVe2sqp27du3az7sDAAAAYC3WfGLo7u4kfRnXn9rdO7p7x/bt29d6dwAAAADsh/2NQF+sqiOSZH5/7vqNBAAAAMB6298I9KYkD5g/fkCSN67POAAAAABshNW8RPyfJ/lgkh+tqjOr6kFJnp7kjlX16SQ/N18GAAAA4HJq295W6O777uGqO6zzLAAAAABskDWfGBoAAACAyz8RCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMAARCAAAAGAAIhAAAADAAEQgAAAAgAGIQAAAAAADEIEAAAAABiACAQAAAAxABAIAAAAYgAgEAAAAMIBta/nkqvpckq8kuTjJt7t7x3oMBQAAAMD6WlMEmt2uu89bh9sBAAAAYIM4HAwAAABgAGuNQJ3kr6vqI1V1wkorVNUJVbWzqnbu2rVrjXcHAAAAwP5YawS6VXf/dJK7JnlEVd16+QrdfWp37+juHdu3b1/j3QEAAACwP9YUgbr7rPn9uUnekOTY9RgKAAAAgPW13xGoqq5SVVfd/XGSOyU5Y70GAwAAAGD9rOXVwQ5P8oaq2n07r+zut6/LVAAAAACsq/2OQN39mSQ/tY6zAAAAALBBvEQ8AAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIC7MA2dAAAgAElEQVQIBAAAADAAEQgAAABgACIQAAAAwABEIAAAAIABiEAAAAAAAxCBAAAAAAYgAgEAAAAMQAQCAAAAGIAIBAAAADAAEQgAAABgACIQAAAAwADWFIGq6i5V9amq+peqetx6DQUAAADA+trvCFRVByV5XpK7JrlxkvtW1Y3XazAAAAAA1s9a9gQ6Nsm/dPdnuvtbSV6V5J7rMxYAAAAA66m6e/8+ser4JHfp7gfPl++f5GbdfeKy9U5IcsJ88UeTfGr/x12Yw5Kct+ghBmObbz7bfPPZ5pvPNt98tvnms803n22++WzzzWebbz7bfPMdyNv8+t29fW8rbdvoKbr71CSnbvT9bKSq2tndOxY9x0hs881nm28+23zz2eabzzbffLb55rPNN59tvvls881nm2++Ebb5Wg4HOyvJ9ZZcvu68DAAAAIDLmbVEoA8nuVFV3aCqDklynyRvWp+xAAAAAFhP+304WHd/u6pOTPKOJAcleWl3f3zdJrt8OaAPZztA2eabzzbffLb55rPNN59tvvls881nm28+23zz2eabzzbffFt+m+/3iaEBAAAAOHCs5XAwAAAAAA4QIhAAAADAAEQgAAAAgAGIQJugqmp+f6VFzwIceHb/DIFRLP2e9/3PVud7fH1V1RFVdfCi54DNtPzniJ8ri1FVP11Vt6yqy3VnuVwPtxVUVXV3V9XPJ/nzqjp00TNtNVX14Kq6+6LnGIFfKJtryfa23TfISr+kfZ8v1pLfm7erqqPbK1hsON/zi7P7+33++Oiquk5VHbHouQ5ENblWkpOTHOL7+vLNv8/6WfZzZEdVHex358LcIcnTk9ysqg5a9DB7IgJtsPmB7F2SPCXJc7v7q1W1bdFzHchW+KPtWkm+fw/XsU6W/YK5cVUdUlWHLHqurWrJH8K3TfLMqnpEVf3soufaarr7O8klz9wcWVVXmre7B6cLsuSJkz9Kcu1Fz7PVLfvZ/it+zmyuJdv+UUn+JMkfJ3m6J7f2XU/OTXJSkmOS/FpVXXHBY7HEkqMjbpHkeI/b18eynyNPTPKDu6/zeGZz7P5e7u5nJvmnJL+b5OYLHeoy+I+3OY5J8ntJPl9V907ylvmB1lX9x9x3S/5o+69VtT3JwUmOXnod62vZHwmPSPLmJC9L8t+r6poLHW6LWhKAXp7k00l+Isl9q+rXFjnXVrHscKNHJHljpmePX1BVVxWCFqeqDs/04Om/dffbq+omVXX7Rc+1VS352f6YJI9Icv5iJxpDVV1tycc3SfJrSe6S5Lcy/Tx6SFUds6DxDjhLf1539zeSHJHkYUnuJQRdfsy/W++R6THkOR63r01Vff+Sj38hyX2S3K+7P19V11vyxJa/+TfIkp89u3+XPjzTE1jfl+TF86Fhl7vHk74hNsAK/9BfTPKQJH+W5HpJPpTkHkkOsave6s3P1P/+/PGNkvx2kjckuXGS+1TVb85/LOxY5Jxb0ZI/Eu6VKUbcJslfJblhhKCNdHSSp3b3C5L8jyTvSXLTpX88sO+q6pAl39N3SHL9JD+b5MmZ/gB+sRC0UIck+XKS21TVizI9ifLKqvrVxY61dc2/U+/e3bdM8tmqun1V3XfRc21VVfXjSR60JE50kgu6+8Lu/myS9yX590w/m9iLZU9U3ayqrtHdr03y+CQPT/KLQtDiVNW1dj9OrKprJ3lsknt29/ur6qbzns5XX+yUB56qunGSX1/yvb09ySeS3KSqnpLkVUk+VlXfJ7ZtqB9MLgmcP5UpPj+su2+X5KVJfj/JLRc434pKg1hfSw7huHumXcAOyfSHxQ0z/YL/t6r6oUz/MX+1uz+9uGkPLHPtvnKSI7r79HnZDyW5WpLXJfnbTHsF/VSS23T3lxY161Y0Pzv/gSQf6+5fnJcdl+QWSb6S5I9s87VZ8vPj0PnQ0Uck+ZVMD5bOm/d8e02SB3f3vy522gNTVR2d6efxmzL97Ph4ko9kCvNXSHJ4pmfib5zkl7r7qwsadRhLvu+vn+Ss7v52Vd0/08+WN3f3W6vqfkluluRR3X3xQgfeYubfrYck+WCS12b6P3DFJD+f5JHdfdoCx9uSquoqSa6UaW+VQ7v776rqLZl+v/7OvM4pSc7u7mcscNQDSlU9LMljknwyyduTvDjTY/EnZHoi9pXd/a3FTTie+YmUP0jyot1/81TVC5JcJ8m/Jblmpv8LX07y62LF6s1PCB6c6efIQUk+k+ln+MWZ9iL/yyQvSvLH3f3hBY25pVXVNTL9/fm87n7hHDtfnOSJ3X3GvM7Lk/xckuMuT/8O9gRaZ/MD2TtmCj+vSvILmY7vPmMOQPfKtJvvUwWgfdPdF2Z6lv5ZVfUX87LPZPqh9y9JHtPd909yMzFi7ZbvOtrdX0zy0CQ/XVW/MS97Q5Kdmf5gsMfEGiz5Q/hmSU6dn014RZL3Jnns/IvlapkeLLH/rpzk/Zn2yjw/yZ2S3CDTg89vd/dZSZ6T5PRM25sNtuSJk1dnOhfKEzPFn4fPAeg2SX5nXiYAraOq+plMj1f+M8lvZPpZ/ifdfb9Mf0z/oL3h1k/NuvtrSS5M8v8kecAcpx+f5HpV9VdVdVKSOyd5/QLHvdxbdljvtZL8ZJJjM51P7AaZzg30wSTPSHJ8/P7cVPPjlmt292OTfKOqnlPTSc+fmekw91cmuV+mf5+vx+PIVZt/jnw5yX8kOTHJgzI9SX7n7r5bd78myd2T3DTJWQscdUub/958dJIHV9WDuvv8TI8tb1mXnuD/7UnOSHLmgsZckT2B1sG8h8QNuvvv5stPzXSY0uGZfqnft7u/MF/3i0m+1N3vWbr7KitbtovvFbr7O3P5fnGS/+zuX5mve2WSV3X3m3avt8Cxt5SazmP145lC27uTXDfTyStf2t3Pn9c51B4Ta1fTSeRPyHTI3Zcz/VK/UpJfTnLrTH+oPau7/2JhQx6gquqK3X3R/PG1k7wwybu7+7nzIaSvTvL73f2SeZ2DBIfNUVU3T/KCTE+aPCrJbZN8OMlTk3wj056ez+jutyxqxq1i+eOOObDdI8lFSV7Q3WfOyx+a5JGZzsv0zwsZdotZ9njmat395ZpeMfYJmfbEem2mPxROTPK1JO/q7k8sbODLuWXb88RM5+D42e6+zbzsrknumGlP5acluUJ3f31R846mphcOeVam2PmSTH8YvzrTEyxPmwNG5ifO/yDJyd39xgWNe0Cqqltl2uvno5li/rZMTx7+/+2ddbSc1fWGnzd40OJaoBSH8kOKO8UhwQJBQouFFvfgXlyKO7RIsSJBm5IWh0qAhuLuFggECIEAeX9/7DMwvQ2Q3Ds3X2buftZicUey1l4z35zvnHfv/e7HCQHoBGINf6KqGFuV0dxL1wBOI76HQcCZhEDXjbB26DW+VfCnCNRBFJO++gIrAueV/tZDiVaCGYBdbD9feuuntX1OheE2LWVD+mPgA9unSZoS+AMwwvbWknYHbqptYJPGIKkvcRA4j9hMPUUcyCYGrgaOrR2ak44haR6idHcb24NLK8BcwBG2H5c0OyF8vpsC8thRvAaWAv4DbExMbfgRIa790/Y5kpYEBgJ72r68smC7IJLWJrzzZiJ65w8GdgQ+JTJs3Uo7ZF73DULSKrbvLX8vD6xHZOEvIzLy1xGeBnl4aACjESy2BAYQQxaeInyvJgausP1oZYE2IaUt/WBiCu/pwCDbW5TXehDtYKfY/qC6KLsmpaJ5N+A1oitiFCEIvQqcSqw5RxFVnv1zjf9+6irGuwFTEEmTmQnfmaeI38CXRCHCS8Cktl+vKt5Wpc16/mPgc9vvKYa5nEEMtvgr4QO0MHD7+Nj9kyJQA5A0H7GBWhA4h/gB3g8caPviUm59KdFbP7C6SJuTUj11BJEVPpG4WexRhKD+wGDbe1cZY6si6VLgwuJXMC/QB/jU9knl4PBOaclLOoik6YALgX62XyjP9Scqrza1/UpukNpH8d/YlxAyZwR+Udpz1yau6Qdtn1c2rMNrn3/SuZQ1ZSbbD5S2jnMI34jHJJ1HbHJPTCGi49QdHkRMLLkLeNr2DuX1VYgM5pOEIPGJY8JS0kBKdcp2RBJrRaI99Xoic3wqUbVylO3PKwuyiShVhP2A28p+W8CjwDO2tyzvmby03yXjiDaH5EWBvQnh52zgK6IS912iUuUThwdi7m/GEMVwi5GSfgpsRLS3X0kIQacD7wFHO/2vGk6ba/sAYh3vTgzLuZDwLjyZqKy9qLJAx4D0BOoAtV5k288RquuLRNXESKKsfXdJVxA/yH4pAI09kn5BfJb9Sn/rEsAGkk63/Ul57bQqY2wVJM1SbtZI6lF6uYcCW5dN1PPAncA6kqay/VAKQO2ntn5ImqBkdYaV/5bRt9PWziXM/s6Db6e0JWNG3Ro9nLh2ZyBaGieQNKHtAcRhbF1JO9oenAJQ51J33a8AHAvsI2m5cm3PAvRV+GItDZycAlBjqFs7Ji2/h82BaRUGrZSqoOeIA5pTAGo8kpYALicEi9sJw9bXgF5Etco+wOkpAH03tfWj/ingI2A1SYuV63wJYFmFGWtt/U/GEXWC84KK4S1vEJVacxJVQRMQ05PmBKauWQnk/mbMkLQS8JBiAt4LxPlzCOEvNj9RHXRWCkCdQ50AtB6whu0exN7958Bntv9GXO99JE0zmjVrvCErgdpJ3SK3JCGmvVf+2x2Yj6haGUKog1PYfilV7h9mND2W2xDtdvcQzuvvlgPyS8AFtvtVE2nrIWku4C+EF8csRLn6vMSEmFdKpcSGxPexpdMDqN3UrR/rA72JjNhVRKn08UTb0nBC5OxLjFPdx/ZbFYXcdLTJ1mwCfE74bexB9NBfZ/uRUiW0LFEVkZ/vOEDSWkTVwyVEFe0ThBj3GvE7MHCZ7T9VFmSLIGkBYGTZg/yGmLj2KnAD8D5hoPs1IZLuSPgWZPtAAxjdnk/ShcDqwHK2h5RWgm2BKYEjU3z7btqs6csR68UwQtzfnRCDbrL9n/KeuW2/XFW8XZlyQD6WmNI2I1EB9ABR+fMekbz9yOm794OM5lwkYt1ekFivh5YE7uXEHv6IFJIbj6TFgfVtH1seb0Rc29MSPoY9SnXW/LafldTd47kHWYpAHUBh4noaYVJ8ImH8NALoSWQiLrJ9X3URNhejucG/D7wFLEkchG8ljFyHKDw+ps+sfcdp87kfAhxGtDL+TmFa2QNYh/BkmpTwifh3ZQG3CHWbpN2I63tlYGtiY7sOYQ59KTANsYFazelpMNZI2p9Yk3e2/aTCyP8gQhSanKg4+UWpLEw6kbJ5nYgQgP5u+6qSKf4VITgf7vDQ6277s0ycdAxFy3Q/YpP6JLAV0VrdG/iQqIq7m5iGB5Fo+U8FobYcbe6rqwDTA/8kPve9iTV+U9vvSJqDaEMdWlnATYTCA3IboqVxbqLVd3KiuuRrwlfpyeoi7NpImoEQlXcnTKCXIkxydycSXocCx+T+/Ydps46sCEwH/IM4a+4HrEJMEVwV2B7YzTHJN2kgkn5OVLSNAmaz/ajC6uVkwruwZxGA9gJWA7ZoBiFuwqoDaEZK68bMxPjUHsRN6HlgiMMY6jrC4C9v6GNB3UK3K3EYvoswbv0ZUTa6DjCppNttv09kfZIO0OYGMx/hS9Ab+IOkYbYvA/4o6Q7imh5VPvukA0iaAFiMuM5/CsxD3EyuIES22oSq1Yne+U1SABp7JC1CZGdWlDSZwrTvR8QhbHviO9gpBaBxQ1lrRkp6E1ivrOUvKaY7XkeMyj7b9jt170/aie1PJN0CrEUIoZfYHijpUeCXwEa27wR+LWki219WGW8rUXdf3YcQLF4mRLj7iDawCYGBklbPyqvvR9KstSpNSRsQ7XOrEEnY+Ygqwu2IysI+hNCQjGPq9pNfEQncx8pB+H6Fv+Qqtn8rabe8544ZdevIvsT68Saxb7yXMCCeivCgnYgYKpLXfoMp7Xe3E4mqYcBVkp61vaukfxDJ8T6SJiH2lVs2gwAEKQK1C8f48bck3UVsrrYlVMD3JPUismun5YZq7CleEBsRn+uewBulr/UKSaOIaombKgyxpWhzg1kb2M72m6V95kZJHxLK95rE1KRR1UXb3NS1gC1i+wlJZxPtovsBuzomgPUiBLjFbb9HZO/X8Xg2VrIZkDQZ8A7QXWEyDNFysSYwg+0LJXXLa7pzadM6PTeRGX6QMH3uLekiYpjCe8TB7hFyje8Q9de17X9K+ozYwP5K0gO2n5N0AfBXSfPZfi73K42j7pqfgdjLrGr74yJgrAHMZ/uIKIyje5Wxju9Img3YQd/6QL5BtKpvS/ifbEB45l1H+FwdmdfyuKVO/JlB0hDbH0oaClxD7OcBvgDmKtWg6dE0FkialVg3VrY9vLQhrQrMY3tPhTn00Kwk7DRmJJK0axAVndsBl0g6zvZ+krYnJoBNAvS2/VR1oY4daQw9lkhaSFKfspAtTXj/rFxK2JcEDgRmz5vQmFE+x3qGEYrrb4gDwQblfT1tXwXsa/vjcRtlayNpS2AzYLMiAP3Y9l+BXxCtA/sSE8LysNxO6g4F6wDXSVqybGi/JAzlv5K0MiH6rFUE5W62300BaOwpFT/7EwaUuxLmoRfa3oa4nqeAbwT9pBMp1/2GxOjxJYis/SyED9DPCJ+IW4CdCfFnjopCbRlq17WkNcpv4SXi9/AQsH/Zq6xEbFrz4NAgJM0I31zz/0d8tpMTwjO2byPW/N7l8RG2X6km2vEfxQCKNykVP5J+Zfvf5bmFgQNK5cMLhI/ehLn3HveU6319YCBwmaQziGrbDyXdJ2lnIql7vYO8744dnxIVzKsB2L6Z2NNsUx6/kAJQp/IssCnh1/lQqdzcDlha0vG2L7W9L7B3MwlAkJVAY0TdAW4F4otfgMhGbE2Y6J5ZKibWJQy5BlcXbfPQphVpMoch4rtEX/ektucqr/UBtpF0fy50nYKJ/u2NJM0J9JD0DHETXwv40na23rWD2jVe1o95ic3sTrYfAXAY+o0kxOPViYqgJ8truVEaQ+rXkkI3YC6iNeD3tn9d3rcz4cG0xTgPsgshaRZgTduXS5qeuFeuRvi7bUisN58SPm/zElVACxBr/4aVBN0CtLmn7kx4b/yNMBFdgfDlOIb43AcB2zrbexvJypJ2JD7f9Yn2jSuARUqFxH2E+LmEYjrhVxXGOl4jaW3gOEn9Sgvj4sTn+5XtK4GpiUmCTxMZ+g1sv11lzF2V8t1sSEy3GwLsAPyeODjvUt62l+27KgmwiVB45E1i++nyuFupIryCWDeG2n6IqKhdONeRzqHNnvIj4FHCW28eSe/YfkPSL4mOidNs70O0QTYVaQw9hihGlZ8PHAesSBwy/khkMbcgMs7P2H5gNAeS5HuQtBNR8fMG0dv6ELFxvaa8ZR2iTSkNKxtIWcDuIvpZ9wQWIQxb3ycObZc5DaDbjWLqy6rAVba/VkxvOMz25uX1SWx/Uf6eBpjO9ou5frQfSSvZvr/8vTLRNvASMQlpFOHFsbdz7HinUao7twFWst1X0Sd/NFF9tQSwle2XyyHvaduvFfH5LOAgp6Fru2gjAE1LiBB/tf2WpDOJJNVSxHq/AyGO5jS8BiPp74TX2ELlOl+CSKZsQPgCLUN4vOUa9D0ozJ9PJvaEp9geIGlrQvC5gfBEOYQ4mJ2byddxj8IfdWrgdaJCYi2F32E3ovLzmlL9lowBkqYGDidMn6+0/Uzda4sRa/r6hAftCoSnW94vG0ybe+mWwBe2b5S0GjFB817gFoep/yzARLZfqzDkdpMi0BhQFroDCePniyTNTGyoNgfOsP3nSgNsYsoP7ACi6mQaolXjGqIt4JdEH/Http+tLMgWReFJswmwqO0PatVYknoCRwIbZ6l6+ykZndoGaQRhrD2A8Au7prxnXWB524dVFmgTI2mm0g5Qm4R0MdEb/5vy3GrA6cAdhIg/xDmCudMpVW+3AofYvkExoW1Lop337lJVeymwte1B5d9M6TQLbReq8wCStCchwnUDznaY+1NaNLYhfJk+y+xxY2gr2kvqSySu5gRWLPfUicrjuYFnm/XAMC4pFYSHEPfPlYBLbd9aKsNXBQbYvi6TJtVT9jE3AX1sX1+eOw14zvb5lQbXZChMiNcnfJP+ZPvpNqLEfMQ68oztVysMteVRDCnqS4j2L5bnViGEoH8B17rJjbjTE2gMKJur4YT79/SOySV3Eoe6jRRmxkn76A6cZfue0ue6M7EAjrJ9vO3TUgBqLJKmA7C9G3Al8G/F9I0RkrYgBKA+KQC1n3LTfgl4mjCs3J8oFT0VWFPSMZLWJHqM/15dpM2LpAWAtyWdLmnHIiD8lpg+dVb5Du4mxjJPD3ySAtC4wfbzwFHAFkWcu5MYa7ujwqT7YkIQGlSSLKQA1H7qBKDVCZ+lfYC/Ej4q65b37ElMT5oxBaDG0OZwtqakdW1faHsTwt/tH+Wt6wCL274rBaDvRtLPJP2sPBwKjAQWIoyf+0paz/YVwMPASgrPoBSAxiGl0hNJP5e0maR5HRMGNyImyR5dki/rEX6HyVhQKpn7E1O/NpO0cN0asxfQy/aAFIAaT+3aLn/PSNi/bAC8ImlTxQCdF4gE1sJEkUJTk5VAo6F2Y1eYJ85PmFZOSFSpTEIcNGYmyteHAnfa/kNV8TYDtR9X2xt2yZrtSWyQRpYDwdXA4Sn+NB6FSeh6wNW2HyvPnUqMXF2yvG1ih/Fi0g5qPdp168giwElEFdCtwAyEKPQmMLBkNzObOZZImp2oGryVMDF/vfz9ITHpbpHyeFtidOor1UTa+pR2rg2AJ23fU577KXACcIztwaUybhZgNuClIgDldd8B2ogQCxPmuEfaPrp83lsSh4mHbPevMNSWpuxjdgM+I9ahA0tr79WE11U3YmxwU5mGjktKcmoIcV/cG3gVeIwYg30LYYy7FXCJ7f5FAMohIRVQhOXfEX5XOwP72L5eYZtxO2EQ/ZvS6psTONuBpOWISv2PCS+39YmzZ69a9WzSONrcS3chLEn6EBOpnyUM/ocCH9k+RNIUtj+tLOAGkZVAo6Ec3NYgPH9+RaiyCwF/IT6ze4DriZv+fcCCKlQScHMwe90PbHtJR0pa0faFwG3A/aXMcSvC0LXpf1zjA6O5Jl8leug3VvQYQwgSXxIbrQ9SAGofkmYsG56vJK0FnCOpB5ER3oO4iW8EDLK9me09UwBqP7bfIKp8liDacwcSXla/BW4mqjcXAn6dAlCnMzPhN7O/pMslzW37BeL7Oa9WGWf7QdvX1Taxed13jLp76iwOb4gDiO9gnlKJeAVRgbikpMkrDLVlKYmVjYlE1rLAO8DBkn5ie0ti0um6KQB9P7Y/IMT82YhqtnWAywlhbQZHC/VNwFaSJk8BqBoUrb6HE/fch4kpVbtK6mN7IOHZtAxxX4YYPJKMJbYfBm4kuiWuIYaK9EwBqHOou5duTJxDvyDMza8Bji1r+b+BGcq5anhFoTaUrAQaDaXN4BQim/OEpCOJHszzbT+sMHwdTpj/nU/8MJ+uLODxmPJj+REhnJ1JmLSeQJRJT078qC4G+gHzEQLFvk7TxA7TRtnekDgMDAUGEzeUoYQANydxWP697ZcrCrepkTQVMXVHRCXb74h2jCUIceJCoiXpcsKf5kTbX1cTbfNTV2U1MfGZ7kVk3C8jzM6nIg5jxzqnH3Uqbb6LKYgK2S+IhMlphMh8se17KwyzZVEYDx8PHGf7XoX/0gHAyg4/idmBEeWQnTSQUr2yK7ATsIPtv0iakLjuZyIGATxXZYzNRknAXkrcOzcjDmSvA9sTlfhKAahaJC1I3GPPAZYjPFJOBrZ3+DT1JO4DixBt2HnQbCeSlif8Zy9MIblzKWf/64GbbR8maYLaPl3SDsSku1+20vk0RaA2SOpOGBLvD5xs+7zy/GHAz4nD24OSZgOOIIyh0539O5A0ke0vFZN6jiYOBr0dE0s2IUrtXgAuKO/7ZmJS0jHqDme7EDfpO4ny0ssIkeIIQtxcihQy203JjB1EXMeLAHMQ68RtJUvcu7x2ESEETWf7nxWF2zIUgXki4DDgJ0Q744G2b5Y0P/Ce7Q+rjLErof82J16I2LhuBsxDtJ9uX2V8rcB3VQ1KOpxYe86yfb+kfYhE1gIpQjQOxUS7WQhT4rfLcz8hDLdnJiZBPliEoOOJIQA5tnwskbQecCKwnO1PS2VhJqgqoG4fOTcwtcvEWEm9gQ1tby1paSK5u0/d65PbbolqiUZTLy6M4fsntj2yM2PqirS9n0qagqja3xboa/u+ss+cF/g1MTG5paZUd3kRqBwWehJl0+/aHqUY+bYxkYm4tdZLL+koQiGseal0t/1ZRaGP9yiMb7cnKk8eA94lsvRn2T66vGcjwkvi38C5RFVe174oO0jx4hhie5ikmYBrif7spyX9CHiE8I24XNJkwBS2h1QZc7NSDrtXEJU+Nb+fE4i1dZ3ynpWITPHTwElZAdRYyhp+L3CO7WOqjqer0KbSsHZQaLupWowi9DvMQ5MOIGlG2++Vv1cHZrb9x/L4QGB5vk1U7Qb8JUWgxiBpEiKBshbwB2IwyB7lup+FsA6YA7jeYUifdIAiBJ0KrGB7aHkuW6crQNL6RHXbSOBh231L1cSpwAfEWWk32/fUkgH5XY0exRj4XrYvlrQTMJntM7/jvfkZdhJt9i8bA9MBjxKeZD0IXeAE2w8ovGonasUChS7tCVS+2M0oCjZwmaRpS+bmCuKCWE/S5gC2j7D9mL6dZpIC0HcgaR3Cm+Mhou2rNzCKyA5vKunXAI6JYDcTG6dRueB1jCLy7Ep4EkztGF/4PnHzplRG7EW0f2F7RApA7aO0gJ1NiA8X2H7L9mCiFeMNSWeUG839xFSeW1MAajwOA/kDgQlKJWfSydSJPmtIWqq2bteLQuXxYNtn2b6z9lzSPiTNANxdMvAQlTOnO20AAA7+SURBVD9rS9oUwPYJRIvv7yUtZ/vsFIAaRzkA3E4ceq8EZgUukXQQsbe5gDhArC9psrzeO4btO4h1faCkbnkgroaSZNmJOBgvAcyjGP/+FnAoYUa/l8tAgFo1aH5X/4ukyWwPA2aX9DbxuV49mvdNAfkZdiZ1e5VdiM6fSYjhLYsRXkz9geMlLV/Opi0nAEEXF4HKYnUP8DLh3zEEuLS0fs1BZPefAFaXNFPdxjad7r8HSdMSvifH2D6LaIPpDsxTMmR7ANsrxh1i+7YiViTtpG7D+RFhYD4S2Ls8/zxwbSlRh/AAmkPSBOM+0pZiBOFVcANE62N5/gkiQ1abIIjte91CfcTjIX/nWyPKpJMpAtD6RPXmtKN7fUyeS8acItYfDhwgaZ2SPX6AEII2L2+7DXiG2NMkDaJu73cVcD+wpO1NiermfYgBIb2Jz/3YklzJ672DlCr8lTNBWA2SpieSij8GJrD9JWEpsChRJfGY7ZNtD0zR8/sp98sTFT5iVwGvERXjQ8rrKv9fHti9bj+ZNJC6z1kKW5cVCUP64cDjxMTeD4A/EZWfr1cV67hgwh9+S2tTyqYvB1a3vZ+k7YnKoB2A8whh6NgUKcYc20MVRsQnSbrXMSbyK2DG8vq9kg4GDpP0e2BY3uA7zASE8bNK1n0qoiJluO2DJE1JTGAbTExu2DqrUjrM5ITwsCJwu8PTagLbX0t6h2iBXEjSQk5Dv07F9jOSemd15rihHA4OB7ay/YikxYn1/RGnEXdDqa+AsH2DJAMnl7aLiySNAnYsQtBPiFaDd6qMudVo0+o4EFhA0jJEZXMPYFJiKtINtj+qMNSWwy0whrmZaLPevC/pSmBKYENJI22/IKkX0F/Swi6eqLmH/24kbUB0Rhxh+wNJw2wvI+l0SQ8DPWwPUdgL/AN4tQhuSYOoXdd112l3YnjI08RwkSmBNR2tjLsSe/pLKwp3nNGlPYHqStpXBnoRWftriSlW9xFO4JfkAa59SFqX+CwHEKXTW9seUff6ZPWPk/ZRDmSDgKVtvydpVsLhfjDwKfCh7eMVU2SmIm4wmSluAJL6AssCZ9r+d50ItDbQB+hn+81qo0ySxlKymacDTwK1STHzEL+DS6qMrZWoP5ApvCRG2f6kJFl+Sxih3yFpUWBtoL/t5ysMueUpLdcPAvMD69keUJ7PoRZJU1N3JvoFsDRRrXIzMXlzW6Iqor/t5zSW5sZdFUkzEy1fB9j+l6RJiYEWE9r+UNJxwEqEp+TOxD4+Jzk2GP23n97mwGpEG1g/QsDfzvazkrYgho1s2BXOSV1aBKpH0p3EJmqvUmaNpEltf15tZM1NuZn8hTCwfC+Fn86hHAqOJ0rSzwButH2OYjpVT6I97LfO0aoNpfh07EWYyl0H3E2Ys14M7G37zxWGlyQNoe5w8BNigMJwxRjgZYB7HKOx+xCbqR2BrzMz3Dgk7UdUHM5FTE26m6hCPJaYYvo/vhJJ49G3prerAX2JSbJfkQMtkhahVK0cSSRwexPdEHsRNgK7EC2PZwCfpzXGD1NE42uBfQlrhgOJtXwy4HHbv1F4pM5BTBfMooMGU/bp9wBH275WMbTo/2yfXFrCTgBEVPfPCWzbVewbumw7WN3NvDbWdldic3Vz3espAHWQ0iu8PmFouVpNiU0ai+1bJX1J9LQebPuc8tL9hOHZSuX/SQMpJbxnEm0B5xBm8vMAB6UAlLQKRQBaj6g+ubNsbA/1t5MzVyLaT/ez/VWFobYEkpYkWnyfI8SezQnfgnWB1YGpbF9Q2n53l3Qb8GkKER2nTfXVhET11ag2lQ8vArMDK9r+W1WxJklHUUy2m98x2Ws6YFNiYM7ixLTTlwlrjJ2B8wnxJ9uux5yPiG6IU4CFiXbSawhD7d0V/m7nS5ow752dQ9mnHw4cImkEMIziiWz7TUk7APMBUxOdEm9UF+24pctUArVp/Xq7bcl02UxdBtxl+/xKgmxhStb4CGApMmvWaRSF+yxgGccUgtrz3fPG3blImomYEjOJ7TfqDxNJ0sxIWpqobtsY2JrIEL8E/Ab4jJh+d7Ht2yoLskVQTNY8hljH/wasAGxgu095fU1CcN6wlK9Pkb4pjaGNALQ3MSnmM8LLY0j9Qa0cHO53TmBLmhhJmxBm8q/Z/rRURkxD+KT0IrxSrgOeIvzGUqgYSxTTvhYlqn3619pGJV0C3Gv78irja1Xa7sEVo+CPAt4APiQGKXQDJgYedUz37VJ0melgRQDakFCy5649L30z9eFjYsTni9VE2No4pzyME2zfBewN/FMxpa32fApAnYztd20PqWUR8jpPmpnavbEwMSH8zE20l24JfExM0ITop7+tzb9JxhJJqxDizy62Ly9rybPAqGJEXFvj7wemL49TAGoQdQLQqkRFxNXAF0T124y2v5I0cXnvJSkAJc2KpNkkLW37RmLK3dmSNi0eht2AQbZfIvze/kwIoSkAtQPbn9p+2PZ1dQJQL0JkfrDa6FqTNoL+lMWK5CbgUMLPbRmi2nY5YC1iP9Pl6DLtYMUs9yhgE8ckmfmJkup/lde72f5L+Tsz+J1AblbHDY7pYBMDAyVl5VWSJGOMpKltDyuJk1q79MOAiamZh9geLOllYirSXLYfgRQ+G8CSwNkOA9Fa1cnLwJvAxqXt7n1gVcK3I2kwJVm4I1HZNgAYIOkk4FZJPZ2T15ImR9IERFvpzopJvQ8RrexrSRpJ+KcsL+liYEPgV7YfryreVqK0320B7ARsYTsLDzqBOgFoP6IDZVZJ+9q+RdIXwHHAW7Z3qzLOqukylUBEJvNdYElJ5xL9mbdI2gig3uAsN7JJs5OVV0mSjC2SJgEeLa0w+FvfvK8J48RpgDUUkx/XBg6rCUBJ+6mroJqb8OEA+Lp89sOAk4lM5YKEv1sP26+P+0hbj9FUr71MGIQuK2kaANsHAI8A10jqlhVvSTNT1vMriTavgwivmpqn4SbEOrMCcAXRinpnRaG2Ih8RBtE93UXMh6tCMep9XaKFHeBPktYq4v7JwDGSppbUlbSQ/6JlPYHqPIDmJkygPgS2IzZQNxU1cGfgp8Tovtb8IJIkSZJkDJG0HNAfOLzmj1erSpE0IzE15kvgFtvXVxhqyyFpdeBgoJ/tR8rmtFv57HcjJm2+YntkpYG2CG1aBpYF3rH9iqQ5iVbHvwEX2P6ovOebMcNJ0ozUnY3WBbYiBll8QlQW/oOo9lyDmFR1a2WBJslYUozNR9n+sDzeC7iBGKywDFHhdizQx/bt6afXwiIQfGOweCIwGJgX2Lr0uCJpBeImv6ftgdVFmSRJkiTjD6WN9C5iyt35tclIihHxKwHX2/4sW6cbi6TJgf2B7sC1tSorSb2J6Ws9swKo8Ujal/C6egV4i/BlmhA4FxgEnOa6QQtJ0syUdXwgYfwMsDSwAeGX8gTRDvlgtoAlzYJieumRxBr+gu2DSxJlTmJwRY9ifP4w8Gl5PKKqeMcXWtYTqGRyTgR2Ax4A9gAeKj31I8tr/VIASpIkSZJvsT2oTKG6q7QknVvMcm8ANq8ZzacA1FhsD5d0EZGNP03SIGAEMbJ5sxSAGkMxCR1R/u4JrG17ZUmXElUQkxF7xD2Ak2jhvXLSdagT7ScGnq0Tmd8GlgXOBva2fV6FYSbJWFEKPg4Gfgu8CuxbW+MlvUF46m1aRKGngKNTAApaqhKoTWnvdITvzw7wjbfB8cAnto+T9GPbr2UmM0mSJEn+l1IRdAdwE7AKcHCZJpN0IpImI0yifwG8Ddydk6gaQ8kYrwWcavv1Im6+TFRC9CQ8Uk4B3iEOFq/nVKSkmalrAZvc9vDy3D3AfbYPL4/3IcaYn1sbmJMk4ztlCvL7wKa2b5K0NNHOfiMh3u9BeAItT0wC29z2k1XFO77REiJQbZpJ+bu22E1DlLNfa/uU8touwKy2D03xJ0mSJEm+H0k/J7xRtrd9fc0UN++fSbMhaQMiW3wE0L8uaVhr/TrJ9gtleMgXwPHpAZS0AsUDaA/gn8DlxOj3/YFRwLVExVsf24MqCzJJ2oGk9Qmvn18RAv5DwMVE5fLjtncs75vW9tCq4hwfaXoRqEwzeYoYq3p6ea5mYjkvYQR1LfAiMZLvAJdR8EmSJEmSfD81A8VMniTNiqSZgauJPeC/JE0MTERMvHubOASvCZwP9AU2sv1qVfEmSUepOwstTRySLwPWA14nkuRPET5AnwMPlKmySdJ0lJawO4hq5RPKc1MAtwBb2B5SZXzjK03f52z7C0nbAP0ljbB9fln0JrH9vKTFgF2JkZ/9UgBKkiRJkrFieNUBJEkH+YKYave5pEmBA4EVgUmAJ4mqiE+AJYBtUwBKmpUyFXmo7WHl71OBAbavlnQ3URG0LjDc9u51/y5F/qQpsf1nSWsDZ0s6v0x07AVMSoicyWjoVnUAjcD2w4S6fbykX5enaz3c0wHP2T7J9oBaKXuSJEmSJD9M7WCQB4SkifkIGEC0C7wAzAVcA+xHJAlXsH0UsKvt/1QVZJI0gHmAV4stxmvAo8A2khaz/Q5wOlEEsGXxVAFyfU+aG9t3AXsBDxT7l+2AvrY/qTay8Zembwerp26s7SF100z+BPTOKWBJkiRJkiRdk9IesCgwB+EJ9EV5/hLCJPcPVcaXJI2itMecBSxVKoIOAZYCjrD9uKQZgGltP1tpoEnSYIr3243A4mkC/f20lAgEOc0kSZIkSZIk+WEk9QL6Eb4RL1YdT5I0ijIJ70xi0uDHxHW+OrC/7cFVxpYknYmk7rY/qzqO8Z2m9wRqi+1BxSm8Ns3kxuxzTZIkSZIkSQAkzQJsQQwMSQEoaTls31EcMAYRVUAnEmboLXf2S5J6UgAaM1quEqhGTjNJkiRJkiRJ2iJpMqIq4lnbL1QdT5J0FqU17DJgAdvDqo4nSZLxg1YWgWTbKQIlSZIkSZIkSdIVKR0Sw23fU3UsSZKMH7SsCJQkSZIkSZIkSZLkGPgkSb4lRaAkSZIkSZIkSZIkSZIuQLeqA0iSJEmSJEmSJEmSJEk6nxSBkiRJkiRJkiRJkiRJugApAiVJkiRJkiRJkiRJknQBUgRKkiRJkiRJkiRJkiTpAqQIlCRJkiRJkiRJkiRJ0gX4f8Pm+s5jDxICAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9dd44bacc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Most dangerous cities\n",
    "city = kill.city.value_counts()\n",
    "plt.figure(figsize=(20,10))\n",
    "sns.barplot(x=city[:12].index,y=city[:12].values)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Most dangerous cities',color='red',fontsize=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Kill Numbers from States')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9dda25fb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Kill numbers from states in kill data\n",
    "sta = kill.state.value_counts().index[:10]\n",
    "plt.figure(figsize=(20,10))\n",
    "sns.barplot(x=sta, y=kill.state.value_counts().values[:10])\n",
    "plt.title('Kill Numbers from States',color = 'blue',fontsize=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Numpy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Install numpy https://www.scipy.org/install.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.14.1'"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Arrays\n",
    "\n",
    "The central feature of NumPy is the array object class. Arrays are similar to lists in Python,\n",
    "except that every element of an array must be of the same type, typically a numeric type like\n",
    "float or int. Arrays make operations with large amounts of numeric data very fast and are\n",
    "generally much more efficient than lists."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.array([1, 4, 5, 8], float) # <-- constructor of array in numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 4., 5., 8.])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 4., 5., 8.])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, the function array takes two arguments: the list to be converted into the array and the\n",
    "type of each member of the list. Array elements are accessed, sliced, and manipulated just like\n",
    "lists:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 4.])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 4., 5., 8.])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.0"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.array([[1, 2, 3], [4, 5, 6]], float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 2., 3.],\n",
       "       [4., 5., 6.]])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.0"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[1][0]  # <-- accesing elemtns of matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0, 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 2., 3.],\n",
       "       [4., 5., 6.]])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([[1, 2, 3], [4, 5, 6]], float)\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([4., 5.])"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[1,:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3., 6.])"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:,2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 3)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.shape "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 1., 2., 3., 4., 5.])"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array(range(6), float)\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0., 1., 2.],\n",
       "       [3., 4., 5.]])"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.reshape((2, 3))  # <-- tuple of dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 1., 2., 3., 4., 5.])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 1., 2., 3., 4., 5.])"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 2., 3., 4., 5., 6., 7., 8., 9.])"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([1,2], float)\n",
    "b = np.array([3,4,5,6], float)\n",
    "c = np.array([7,8,9], float)\n",
    "np.concatenate((a, b, c))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Other ways to create arrays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 1., 2., 3., 4.])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(5, dtype=float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 1., 1.],\n",
       "       [1., 1., 1.]])"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.ones((2,3), dtype=float) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 0])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.zeros(7, dtype=int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Array mathematics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([6., 4., 9.])"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([1,2,3], float)\n",
    "b = np.array([5,2,6], float)\n",
    "a + b  # <-- [6, 4, 9]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-4.,  0., -3.])"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a - b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 5.,  4., 18.])"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a * b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5., 1., 2.])"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b / a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 0., 3.])"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a % b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  5.,   4., 216.])"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b ** a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "operands could not be broadcast together with shapes (3,) (2,) ",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-67-20b621636e6f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0ma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mb\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0ma\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mb\u001b[0m  \u001b[0;31m# <-- Error\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m: operands could not be broadcast together with shapes (3,) (2,) "
     ]
    }
   ],
   "source": [
    "a = np.array([1,2,3], float)\n",
    "b = np.array([4,5], float)\n",
    "a + b  # <-- Error"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition to the standard operators, NumPy offers a large library of common mathematical\n",
    "functions that can be applied elementwise to arrays. Among these are the functions: abs,\n",
    "sign, sqrt, log, log10, exp, sin, cos, tan, arcsin, arccos,\n",
    "arctan, sinh, cosh, tanh, arcsinh, arccosh, and arctanh"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic array operations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.0"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([2, 4, 3], float)\n",
    "a.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.0"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.816496580927726"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.0"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6666666666666666"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.var()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "DataFrame <- Series <- numpy.array "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Array item selection and manipulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = np.array([[6, 4], [5, 9]], float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[6., 4.],\n",
       "       [5., 9.]])"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([6., 9.])"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[a >= 6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2., 2., 4., 8., 6., 4.])"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([2, 4, 6, 8], float)\n",
    "b = np.array([0, 0, 1, 3, 2, 1], int)  # <-- index array that contain indexes from `a`\n",
    "a.take(b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More: http://docs.scipy.org/doc/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Scipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting scipy\n",
      "  Downloading https://files.pythonhosted.org/packages/cd/32/5196b64476bd41d596a8aba43506e2403e019c90e1a3dfc21d51b83db5a6/scipy-1.1.0-cp35-cp35m-manylinux1_x86_64.whl (33.1MB)\n",
      "\u001b[K    100% |████████████████████████████████| 33.1MB 42kB/s eta 0:00:011   40% |████████████▉                   | 13.3MB 1.3MB/s eta 0:00:16    56% |██████████████████▏             | 18.7MB 1.3MB/s eta 0:00:12    99% |███████████████████████████████▉| 32.9MB 1.6MB/s eta 0:00:01\n",
      "\u001b[?25hCollecting numpy>=1.8.2 (from scipy)\n",
      "  Downloading https://files.pythonhosted.org/packages/7b/61/11b05cc37ccdaabad89f04dbdc2a02905cf6de6f9b05816dba843beed328/numpy-1.14.3-cp35-cp35m-manylinux1_x86_64.whl (12.1MB)\n",
      "\u001b[K    100% |████████████████████████████████| 12.1MB 124kB/s ta 0:00:01\n",
      "\u001b[?25hInstalling collected packages: numpy, scipy\n",
      "Successfully installed numpy-1.14.1 scipy-1.1.0\n",
      "\u001b[33mYou are using pip version 8.1.1, however version 10.0.1 is available.\n",
      "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip3 install scipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "SciPy is a collection of mathematical algorithms and convenience functions built on the Numpy extension of Python. It adds significant power to the interactive Python session by providing the user with high-level commands and classes for manipulating and visualizing data. With SciPy an interactive Python session becomes a data-processing and system-prototyping environment rivaling systems such as MATLAB, IDL, Octave, R-Lab, and SciLab."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "All of the statistics functions are located in the sub-package scipy.stats and a fairly complete listing of these functions can be obtained using info(stats) function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RowNumber</th>\n",
       "      <th>CustomerId</th>\n",
       "      <th>Surname</th>\n",
       "      <th>CreditScore</th>\n",
       "      <th>Geography</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
       "      <th>Balance</th>\n",
       "      <th>NumOfProducts</th>\n",
       "      <th>HasCrCard</th>\n",
       "      <th>IsActiveMember</th>\n",
       "      <th>EstimatedSalary</th>\n",
       "      <th>Exited</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>15634602</td>\n",
       "      <td>Hargrave</td>\n",
       "      <td>619</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>42</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>101348.88</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>15647311</td>\n",
       "      <td>Hill</td>\n",
       "      <td>608</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "      <td>83807.86</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>112542.58</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>15619304</td>\n",
       "      <td>Onio</td>\n",
       "      <td>502</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>42</td>\n",
       "      <td>8</td>\n",
       "      <td>159660.80</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>15701354</td>\n",
       "      <td>Boni</td>\n",
       "      <td>699</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>93826.63</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>15737888</td>\n",
       "      <td>Mitchell</td>\n",
       "      <td>850</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>43</td>\n",
       "      <td>2</td>\n",
       "      <td>125510.82</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>79084.10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>15574012</td>\n",
       "      <td>Chu</td>\n",
       "      <td>645</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Male</td>\n",
       "      <td>44</td>\n",
       "      <td>8</td>\n",
       "      <td>113755.78</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>15592531</td>\n",
       "      <td>Bartlett</td>\n",
       "      <td>822</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>50</td>\n",
       "      <td>7</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10062.80</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>15656148</td>\n",
       "      <td>Obinna</td>\n",
       "      <td>376</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Female</td>\n",
       "      <td>29</td>\n",
       "      <td>4</td>\n",
       "      <td>115046.74</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>15792365</td>\n",
       "      <td>He</td>\n",
       "      <td>501</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>44</td>\n",
       "      <td>4</td>\n",
       "      <td>142051.07</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>74940.50</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>15592389</td>\n",
       "      <td>H?</td>\n",
       "      <td>684</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>134603.88</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>71725.73</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>15767821</td>\n",
       "      <td>Bearce</td>\n",
       "      <td>528</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>31</td>\n",
       "      <td>6</td>\n",
       "      <td>102016.72</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>80181.12</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>15737173</td>\n",
       "      <td>Andrews</td>\n",
       "      <td>497</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Male</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>76390.01</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>15632264</td>\n",
       "      <td>Kay</td>\n",
       "      <td>476</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>34</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>26260.98</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>15691483</td>\n",
       "      <td>Chin</td>\n",
       "      <td>549</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>25</td>\n",
       "      <td>5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>190857.79</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>15600882</td>\n",
       "      <td>Scott</td>\n",
       "      <td>635</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>65951.65</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>15643966</td>\n",
       "      <td>Goforth</td>\n",
       "      <td>616</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Male</td>\n",
       "      <td>45</td>\n",
       "      <td>3</td>\n",
       "      <td>143129.41</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>64327.26</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>15737452</td>\n",
       "      <td>Romeo</td>\n",
       "      <td>653</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Male</td>\n",
       "      <td>58</td>\n",
       "      <td>1</td>\n",
       "      <td>132602.88</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5097.67</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>15788218</td>\n",
       "      <td>Henderson</td>\n",
       "      <td>549</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>24</td>\n",
       "      <td>9</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>14406.41</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>15661507</td>\n",
       "      <td>Muldrow</td>\n",
       "      <td>587</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Male</td>\n",
       "      <td>45</td>\n",
       "      <td>6</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>158684.81</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>15568982</td>\n",
       "      <td>Hao</td>\n",
       "      <td>726</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>54724.03</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>15577657</td>\n",
       "      <td>McDonald</td>\n",
       "      <td>732</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>41</td>\n",
       "      <td>8</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>170886.17</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>15597945</td>\n",
       "      <td>Dellucci</td>\n",
       "      <td>636</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>32</td>\n",
       "      <td>8</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>138555.46</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>15699309</td>\n",
       "      <td>Gerasimov</td>\n",
       "      <td>510</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Female</td>\n",
       "      <td>38</td>\n",
       "      <td>4</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>118913.53</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>15725737</td>\n",
       "      <td>Mosman</td>\n",
       "      <td>669</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>46</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8487.75</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>15625047</td>\n",
       "      <td>Yen</td>\n",
       "      <td>846</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>38</td>\n",
       "      <td>5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>187616.16</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>15738191</td>\n",
       "      <td>Maclean</td>\n",
       "      <td>577</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>25</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>124508.29</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>15736816</td>\n",
       "      <td>Young</td>\n",
       "      <td>756</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Male</td>\n",
       "      <td>36</td>\n",
       "      <td>2</td>\n",
       "      <td>136815.64</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>170041.95</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>15700772</td>\n",
       "      <td>Nebechi</td>\n",
       "      <td>571</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>44</td>\n",
       "      <td>9</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>38433.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>15728693</td>\n",
       "      <td>McWilliams</td>\n",
       "      <td>574</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Female</td>\n",
       "      <td>43</td>\n",
       "      <td>3</td>\n",
       "      <td>141349.43</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100187.43</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>15656300</td>\n",
       "      <td>Lucciano</td>\n",
       "      <td>411</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>59697.17</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>53483.21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9970</th>\n",
       "      <td>9971</td>\n",
       "      <td>15587133</td>\n",
       "      <td>Thompson</td>\n",
       "      <td>518</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>42</td>\n",
       "      <td>7</td>\n",
       "      <td>151027.05</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>119377.36</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9971</th>\n",
       "      <td>9972</td>\n",
       "      <td>15721377</td>\n",
       "      <td>Chou</td>\n",
       "      <td>833</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>34</td>\n",
       "      <td>3</td>\n",
       "      <td>144751.81</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>166472.81</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9972</th>\n",
       "      <td>9973</td>\n",
       "      <td>15747927</td>\n",
       "      <td>Ch'in</td>\n",
       "      <td>758</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>26</td>\n",
       "      <td>4</td>\n",
       "      <td>155739.76</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>171552.02</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9973</th>\n",
       "      <td>9974</td>\n",
       "      <td>15806455</td>\n",
       "      <td>Miller</td>\n",
       "      <td>611</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>27</td>\n",
       "      <td>7</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>157474.10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9974</th>\n",
       "      <td>9975</td>\n",
       "      <td>15695474</td>\n",
       "      <td>Barker</td>\n",
       "      <td>583</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>33</td>\n",
       "      <td>7</td>\n",
       "      <td>122531.86</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>13549.24</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9975</th>\n",
       "      <td>9976</td>\n",
       "      <td>15666295</td>\n",
       "      <td>Smith</td>\n",
       "      <td>610</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Male</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>113957.01</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>196526.55</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9976</th>\n",
       "      <td>9977</td>\n",
       "      <td>15656062</td>\n",
       "      <td>Azikiwe</td>\n",
       "      <td>637</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>33</td>\n",
       "      <td>7</td>\n",
       "      <td>103377.81</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>84419.78</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9977</th>\n",
       "      <td>9978</td>\n",
       "      <td>15579969</td>\n",
       "      <td>Mancini</td>\n",
       "      <td>683</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>32</td>\n",
       "      <td>9</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>24991.92</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9978</th>\n",
       "      <td>9979</td>\n",
       "      <td>15703563</td>\n",
       "      <td>P'eng</td>\n",
       "      <td>774</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>40</td>\n",
       "      <td>9</td>\n",
       "      <td>93017.47</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>191608.97</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9979</th>\n",
       "      <td>9980</td>\n",
       "      <td>15692664</td>\n",
       "      <td>Diribe</td>\n",
       "      <td>677</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>58</td>\n",
       "      <td>1</td>\n",
       "      <td>90022.85</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2988.28</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9980</th>\n",
       "      <td>9981</td>\n",
       "      <td>15719276</td>\n",
       "      <td>T'ao</td>\n",
       "      <td>741</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Male</td>\n",
       "      <td>35</td>\n",
       "      <td>6</td>\n",
       "      <td>74371.49</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>99595.67</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9981</th>\n",
       "      <td>9982</td>\n",
       "      <td>15672754</td>\n",
       "      <td>Burbidge</td>\n",
       "      <td>498</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Male</td>\n",
       "      <td>42</td>\n",
       "      <td>3</td>\n",
       "      <td>152039.70</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>53445.17</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9982</th>\n",
       "      <td>9983</td>\n",
       "      <td>15768163</td>\n",
       "      <td>Griffin</td>\n",
       "      <td>655</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Female</td>\n",
       "      <td>46</td>\n",
       "      <td>7</td>\n",
       "      <td>137145.12</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>115146.40</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9983</th>\n",
       "      <td>9984</td>\n",
       "      <td>15656710</td>\n",
       "      <td>Cocci</td>\n",
       "      <td>613</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>151325.24</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9984</th>\n",
       "      <td>9985</td>\n",
       "      <td>15696175</td>\n",
       "      <td>Echezonachukwu</td>\n",
       "      <td>602</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Male</td>\n",
       "      <td>35</td>\n",
       "      <td>7</td>\n",
       "      <td>90602.42</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>51695.41</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9985</th>\n",
       "      <td>9986</td>\n",
       "      <td>15586914</td>\n",
       "      <td>Nepean</td>\n",
       "      <td>659</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>36</td>\n",
       "      <td>6</td>\n",
       "      <td>123841.49</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>96833.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9986</th>\n",
       "      <td>9987</td>\n",
       "      <td>15581736</td>\n",
       "      <td>Bartlett</td>\n",
       "      <td>673</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Male</td>\n",
       "      <td>47</td>\n",
       "      <td>1</td>\n",
       "      <td>183579.54</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>34047.54</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9987</th>\n",
       "      <td>9988</td>\n",
       "      <td>15588839</td>\n",
       "      <td>Mancini</td>\n",
       "      <td>606</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Male</td>\n",
       "      <td>30</td>\n",
       "      <td>8</td>\n",
       "      <td>180307.73</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1914.41</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9988</th>\n",
       "      <td>9989</td>\n",
       "      <td>15589329</td>\n",
       "      <td>Pirozzi</td>\n",
       "      <td>775</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>30</td>\n",
       "      <td>4</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>49337.84</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9989</th>\n",
       "      <td>9990</td>\n",
       "      <td>15605622</td>\n",
       "      <td>McMillan</td>\n",
       "      <td>841</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Male</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>179436.60</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9990</th>\n",
       "      <td>9991</td>\n",
       "      <td>15798964</td>\n",
       "      <td>Nkemakonam</td>\n",
       "      <td>714</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Male</td>\n",
       "      <td>33</td>\n",
       "      <td>3</td>\n",
       "      <td>35016.60</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53667.08</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9991</th>\n",
       "      <td>9992</td>\n",
       "      <td>15769959</td>\n",
       "      <td>Ajuluchukwu</td>\n",
       "      <td>597</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>53</td>\n",
       "      <td>4</td>\n",
       "      <td>88381.21</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>69384.71</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9992</th>\n",
       "      <td>9993</td>\n",
       "      <td>15657105</td>\n",
       "      <td>Chukwualuka</td>\n",
       "      <td>726</td>\n",
       "      <td>Spain</td>\n",
       "      <td>Male</td>\n",
       "      <td>36</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>195192.40</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9993</th>\n",
       "      <td>9994</td>\n",
       "      <td>15569266</td>\n",
       "      <td>Rahman</td>\n",
       "      <td>644</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>28</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>29179.52</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9994</th>\n",
       "      <td>9995</td>\n",
       "      <td>15719294</td>\n",
       "      <td>Wood</td>\n",
       "      <td>800</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>167773.55</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>9996</td>\n",
       "      <td>15606229</td>\n",
       "      <td>Obijiaku</td>\n",
       "      <td>771</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>39</td>\n",
       "      <td>5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>96270.64</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>9997</td>\n",
       "      <td>15569892</td>\n",
       "      <td>Johnstone</td>\n",
       "      <td>516</td>\n",
       "      <td>France</td>\n",
       "      <td>Male</td>\n",
       "      <td>35</td>\n",
       "      <td>10</td>\n",
       "      <td>57369.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>101699.77</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>9998</td>\n",
       "      <td>15584532</td>\n",
       "      <td>Liu</td>\n",
       "      <td>709</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>36</td>\n",
       "      <td>7</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>42085.58</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>9999</td>\n",
       "      <td>15682355</td>\n",
       "      <td>Sabbatini</td>\n",
       "      <td>772</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Male</td>\n",
       "      <td>42</td>\n",
       "      <td>3</td>\n",
       "      <td>75075.31</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>92888.52</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>10000</td>\n",
       "      <td>15628319</td>\n",
       "      <td>Walker</td>\n",
       "      <td>792</td>\n",
       "      <td>France</td>\n",
       "      <td>Female</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>130142.79</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>38190.78</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10000 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      RowNumber  CustomerId         Surname  CreditScore Geography  Gender  \\\n",
       "0             1    15634602        Hargrave          619    France  Female   \n",
       "1             2    15647311            Hill          608     Spain  Female   \n",
       "2             3    15619304            Onio          502    France  Female   \n",
       "3             4    15701354            Boni          699    France  Female   \n",
       "4             5    15737888        Mitchell          850     Spain  Female   \n",
       "5             6    15574012             Chu          645     Spain    Male   \n",
       "6             7    15592531        Bartlett          822    France    Male   \n",
       "7             8    15656148          Obinna          376   Germany  Female   \n",
       "8             9    15792365              He          501    France    Male   \n",
       "9            10    15592389              H?          684    France    Male   \n",
       "10           11    15767821          Bearce          528    France    Male   \n",
       "11           12    15737173         Andrews          497     Spain    Male   \n",
       "12           13    15632264             Kay          476    France  Female   \n",
       "13           14    15691483            Chin          549    France  Female   \n",
       "14           15    15600882           Scott          635     Spain  Female   \n",
       "15           16    15643966         Goforth          616   Germany    Male   \n",
       "16           17    15737452           Romeo          653   Germany    Male   \n",
       "17           18    15788218       Henderson          549     Spain  Female   \n",
       "18           19    15661507         Muldrow          587     Spain    Male   \n",
       "19           20    15568982             Hao          726    France  Female   \n",
       "20           21    15577657        McDonald          732    France    Male   \n",
       "21           22    15597945        Dellucci          636     Spain  Female   \n",
       "22           23    15699309       Gerasimov          510     Spain  Female   \n",
       "23           24    15725737          Mosman          669    France    Male   \n",
       "24           25    15625047             Yen          846    France  Female   \n",
       "25           26    15738191         Maclean          577    France    Male   \n",
       "26           27    15736816           Young          756   Germany    Male   \n",
       "27           28    15700772         Nebechi          571    France    Male   \n",
       "28           29    15728693      McWilliams          574   Germany  Female   \n",
       "29           30    15656300        Lucciano          411    France    Male   \n",
       "...         ...         ...             ...          ...       ...     ...   \n",
       "9970       9971    15587133        Thompson          518    France    Male   \n",
       "9971       9972    15721377            Chou          833    France  Female   \n",
       "9972       9973    15747927           Ch'in          758    France    Male   \n",
       "9973       9974    15806455          Miller          611    France    Male   \n",
       "9974       9975    15695474          Barker          583    France    Male   \n",
       "9975       9976    15666295           Smith          610   Germany    Male   \n",
       "9976       9977    15656062         Azikiwe          637    France  Female   \n",
       "9977       9978    15579969         Mancini          683    France  Female   \n",
       "9978       9979    15703563           P'eng          774    France    Male   \n",
       "9979       9980    15692664          Diribe          677    France  Female   \n",
       "9980       9981    15719276            T'ao          741     Spain    Male   \n",
       "9981       9982    15672754        Burbidge          498   Germany    Male   \n",
       "9982       9983    15768163         Griffin          655   Germany  Female   \n",
       "9983       9984    15656710           Cocci          613    France    Male   \n",
       "9984       9985    15696175  Echezonachukwu          602   Germany    Male   \n",
       "9985       9986    15586914          Nepean          659    France    Male   \n",
       "9986       9987    15581736        Bartlett          673   Germany    Male   \n",
       "9987       9988    15588839         Mancini          606     Spain    Male   \n",
       "9988       9989    15589329         Pirozzi          775    France    Male   \n",
       "9989       9990    15605622        McMillan          841     Spain    Male   \n",
       "9990       9991    15798964      Nkemakonam          714   Germany    Male   \n",
       "9991       9992    15769959     Ajuluchukwu          597    France  Female   \n",
       "9992       9993    15657105     Chukwualuka          726     Spain    Male   \n",
       "9993       9994    15569266          Rahman          644    France    Male   \n",
       "9994       9995    15719294            Wood          800    France  Female   \n",
       "9995       9996    15606229        Obijiaku          771    France    Male   \n",
       "9996       9997    15569892       Johnstone          516    France    Male   \n",
       "9997       9998    15584532             Liu          709    France  Female   \n",
       "9998       9999    15682355       Sabbatini          772   Germany    Male   \n",
       "9999      10000    15628319          Walker          792    France  Female   \n",
       "\n",
       "      Age  Tenure    Balance  NumOfProducts  HasCrCard  IsActiveMember  \\\n",
       "0      42       2       0.00              1          1               1   \n",
       "1      41       1   83807.86              1          0               1   \n",
       "2      42       8  159660.80              3          1               0   \n",
       "3      39       1       0.00              2          0               0   \n",
       "4      43       2  125510.82              1          1               1   \n",
       "5      44       8  113755.78              2          1               0   \n",
       "6      50       7       0.00              2          1               1   \n",
       "7      29       4  115046.74              4          1               0   \n",
       "8      44       4  142051.07              2          0               1   \n",
       "9      27       2  134603.88              1          1               1   \n",
       "10     31       6  102016.72              2          0               0   \n",
       "11     24       3       0.00              2          1               0   \n",
       "12     34      10       0.00              2          1               0   \n",
       "13     25       5       0.00              2          0               0   \n",
       "14     35       7       0.00              2          1               1   \n",
       "15     45       3  143129.41              2          0               1   \n",
       "16     58       1  132602.88              1          1               0   \n",
       "17     24       9       0.00              2          1               1   \n",
       "18     45       6       0.00              1          0               0   \n",
       "19     24       6       0.00              2          1               1   \n",
       "20     41       8       0.00              2          1               1   \n",
       "21     32       8       0.00              2          1               0   \n",
       "22     38       4       0.00              1          1               0   \n",
       "23     46       3       0.00              2          0               1   \n",
       "24     38       5       0.00              1          1               1   \n",
       "25     25       3       0.00              2          0               1   \n",
       "26     36       2  136815.64              1          1               1   \n",
       "27     44       9       0.00              2          0               0   \n",
       "28     43       3  141349.43              1          1               1   \n",
       "29     29       0   59697.17              2          1               1   \n",
       "...   ...     ...        ...            ...        ...             ...   \n",
       "9970   42       7  151027.05              2          1               0   \n",
       "9971   34       3  144751.81              1          0               0   \n",
       "9972   26       4  155739.76              1          1               0   \n",
       "9973   27       7       0.00              2          1               1   \n",
       "9974   33       7  122531.86              1          1               0   \n",
       "9975   50       1  113957.01              2          1               0   \n",
       "9976   33       7  103377.81              1          1               0   \n",
       "9977   32       9       0.00              2          1               1   \n",
       "9978   40       9   93017.47              2          1               0   \n",
       "9979   58       1   90022.85              1          0               1   \n",
       "9980   35       6   74371.49              1          0               0   \n",
       "9981   42       3  152039.70              1          1               1   \n",
       "9982   46       7  137145.12              1          1               0   \n",
       "9983   40       4       0.00              1          0               0   \n",
       "9984   35       7   90602.42              2          1               1   \n",
       "9985   36       6  123841.49              2          1               0   \n",
       "9986   47       1  183579.54              2          0               1   \n",
       "9987   30       8  180307.73              2          1               1   \n",
       "9988   30       4       0.00              2          1               0   \n",
       "9989   28       4       0.00              2          1               1   \n",
       "9990   33       3   35016.60              1          1               0   \n",
       "9991   53       4   88381.21              1          1               0   \n",
       "9992   36       2       0.00              1          1               0   \n",
       "9993   28       7        NaN              1          1               0   \n",
       "9994   29       2       0.00              2          0               0   \n",
       "9995   39       5       0.00              2          1               0   \n",
       "9996   35      10   57369.61              1          1               1   \n",
       "9997   36       7       0.00              1          0               1   \n",
       "9998   42       3   75075.31              2          1               0   \n",
       "9999   28       4  130142.79              1          1               0   \n",
       "\n",
       "      EstimatedSalary  Exited  \n",
       "0           101348.88       1  \n",
       "1           112542.58       0  \n",
       "2                 NaN       1  \n",
       "3            93826.63       0  \n",
       "4            79084.10       0  \n",
       "5                 NaN       1  \n",
       "6            10062.80       0  \n",
       "7                 NaN       1  \n",
       "8            74940.50       0  \n",
       "9            71725.73       0  \n",
       "10           80181.12       0  \n",
       "11           76390.01       0  \n",
       "12           26260.98       0  \n",
       "13          190857.79       0  \n",
       "14           65951.65       0  \n",
       "15           64327.26       0  \n",
       "16            5097.67       1  \n",
       "17           14406.41       0  \n",
       "18          158684.81       0  \n",
       "19           54724.03       0  \n",
       "20          170886.17       0  \n",
       "21          138555.46       0  \n",
       "22          118913.53       1  \n",
       "23            8487.75       0  \n",
       "24          187616.16       0  \n",
       "25          124508.29       0  \n",
       "26          170041.95       0  \n",
       "27           38433.35       0  \n",
       "28          100187.43       0  \n",
       "29           53483.21       0  \n",
       "...               ...     ...  \n",
       "9970        119377.36       0  \n",
       "9971        166472.81       0  \n",
       "9972        171552.02       0  \n",
       "9973        157474.10       0  \n",
       "9974         13549.24       0  \n",
       "9975        196526.55       1  \n",
       "9976         84419.78       0  \n",
       "9977         24991.92       0  \n",
       "9978        191608.97       0  \n",
       "9979          2988.28       0  \n",
       "9980         99595.67       0  \n",
       "9981         53445.17       1  \n",
       "9982        115146.40       1  \n",
       "9983        151325.24       0  \n",
       "9984         51695.41       0  \n",
       "9985         96833.00       0  \n",
       "9986         34047.54       0  \n",
       "9987          1914.41       0  \n",
       "9988         49337.84       0  \n",
       "9989        179436.60       0  \n",
       "9990         53667.08       0  \n",
       "9991         69384.71       1  \n",
       "9992        195192.40       0  \n",
       "9993         29179.52       0  \n",
       "9994        167773.55       0  \n",
       "9995         96270.64       0  \n",
       "9996        101699.77       0  \n",
       "9997         42085.58       1  \n",
       "9998         92888.52       1  \n",
       "9999         38190.78       0  \n",
       "\n",
       "[10000 rows x 14 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'np' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-5-bb9c837dd8f8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Percentile:\\n25%={}\\n50%={}\\n75%={}'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpercentile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'CreditScore'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m25\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpercentile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'CreditScore'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m50\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpercentile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'CreditScore'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m75\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'np' is not defined"
     ]
    }
   ],
   "source": [
    "print('Percentile:\\n25%={}\\n50%={}\\n75%={}'.format(np.percentile(df['CreditScore'], 25), np.percentile(df['CreditScore'], 50), np.percentile(df['CreditScore'], 75)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](https://www.managedfuturesinvesting.com/images/default-source/default-album/measure-of-skewness.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stats.skew(df['CreditScore'])  # skewness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "stats.kurtosis(df['CreditScore'])  # kurtosis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# H0 - sample came from a normally distributed population\n",
    "# H1 - it is not\n",
    "stats.shapiro(df['CreditScore'])  # Shapiro-wilk"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Student’s t-test: the simplest statistical test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1-sample t-test: testing the value of a population mean\n",
    "`scipy.stats.ttest_1samp()` tests if the population mean of data is likely to be equal to a given value (technically if observations are drawn from a Gaussian distributions of given population mean). It returns the T statistic, and the p-value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats\n",
    "# is the mean is == 620?\n",
    "# H0 - mean == 620\n",
    "# H1 - mean != 620\n",
    "stats.ttest_1samp(df['CreditScore'], 620) # p < 0.05 -> H1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2-sample t-test: testing for difference across populations\n",
    "\n",
    "To test if this difference in genders significant in credit scores, we do a 2-sample t-test with `scipy.stats.ttest_ind()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# H0 - there is some difference\n",
    "# H1 - there is no difference\n",
    "female_scores = df[df['Gender'] == 'Female']['CreditScore']\n",
    "male_scores = df[df['Gender'] == 'Male']['CreditScore']\n",
    "stats.ttest_ind(female_scores, male_scores) # p >= 0.05 -> H0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "More in docs:\n",
    "\n",
    "https://docs.scipy.org/doc/scipy/reference/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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