diff --git a/Model_Deployment_Python.ipynb b/Model_Deployment_Python.ipynb
new file mode 100644
index 0000000..dcd5ce4
--- /dev/null
+++ b/Model_Deployment_Python.ipynb
@@ -0,0 +1,1056 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "name": "Model Deployment Python",
+      "provenance": [],
+      "authorship_tag": "ABX9TyPmVs/Eoi8slS/G+y5HiEaF",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/rfim/clean-code-python/blob/master/Model_Deployment_Python.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "9awX_GjpwkIg"
+      },
+      "source": [
+        "import pandas as pd\n",
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import seaborn as sns\n",
+        "import pandas_profiling\n",
+        "import pickle\n",
+        "\n",
+        "%matplotlib inline"
+      ],
+      "execution_count": 11,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 241
+        },
+        "id": "bPVWfEJ-xCKj",
+        "outputId": "d8f7021a-5dba-4b94-a6e7-0f1bbe57fa26"
+      },
+      "source": [
+        "data = pd.read_csv('Placement_Data_Full_Class.csv')\n",
+        "\n",
+        "#Removing Serial Number from data set\n",
+        "data.drop(\"sl_no\",axis=1,inplace=True)\n",
+        "data.head()"
+      ],
+      "execution_count": 6,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "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>gender</th>\n",
+              "      <th>ssc_p</th>\n",
+              "      <th>ssc_b</th>\n",
+              "      <th>hsc_p</th>\n",
+              "      <th>hsc_b</th>\n",
+              "      <th>hsc_s</th>\n",
+              "      <th>degree_p</th>\n",
+              "      <th>degree_t</th>\n",
+              "      <th>workex</th>\n",
+              "      <th>etest_p</th>\n",
+              "      <th>specialisation</th>\n",
+              "      <th>mba_p</th>\n",
+              "      <th>status</th>\n",
+              "      <th>salary</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>M</td>\n",
+              "      <td>67.00</td>\n",
+              "      <td>Others</td>\n",
+              "      <td>91.00</td>\n",
+              "      <td>Others</td>\n",
+              "      <td>Commerce</td>\n",
+              "      <td>58.00</td>\n",
+              "      <td>Sci&amp;Tech</td>\n",
+              "      <td>No</td>\n",
+              "      <td>55.0</td>\n",
+              "      <td>Mkt&amp;HR</td>\n",
+              "      <td>58.80</td>\n",
+              "      <td>Placed</td>\n",
+              "      <td>270000.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>M</td>\n",
+              "      <td>79.33</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>78.33</td>\n",
+              "      <td>Others</td>\n",
+              "      <td>Science</td>\n",
+              "      <td>77.48</td>\n",
+              "      <td>Sci&amp;Tech</td>\n",
+              "      <td>Yes</td>\n",
+              "      <td>86.5</td>\n",
+              "      <td>Mkt&amp;Fin</td>\n",
+              "      <td>66.28</td>\n",
+              "      <td>Placed</td>\n",
+              "      <td>200000.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>M</td>\n",
+              "      <td>65.00</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>68.00</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>Arts</td>\n",
+              "      <td>64.00</td>\n",
+              "      <td>Comm&amp;Mgmt</td>\n",
+              "      <td>No</td>\n",
+              "      <td>75.0</td>\n",
+              "      <td>Mkt&amp;Fin</td>\n",
+              "      <td>57.80</td>\n",
+              "      <td>Placed</td>\n",
+              "      <td>250000.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>M</td>\n",
+              "      <td>56.00</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>52.00</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>Science</td>\n",
+              "      <td>52.00</td>\n",
+              "      <td>Sci&amp;Tech</td>\n",
+              "      <td>No</td>\n",
+              "      <td>66.0</td>\n",
+              "      <td>Mkt&amp;HR</td>\n",
+              "      <td>59.43</td>\n",
+              "      <td>Not Placed</td>\n",
+              "      <td>NaN</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>M</td>\n",
+              "      <td>85.80</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>73.60</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>Commerce</td>\n",
+              "      <td>73.30</td>\n",
+              "      <td>Comm&amp;Mgmt</td>\n",
+              "      <td>No</td>\n",
+              "      <td>96.8</td>\n",
+              "      <td>Mkt&amp;Fin</td>\n",
+              "      <td>55.50</td>\n",
+              "      <td>Placed</td>\n",
+              "      <td>425000.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "  gender  ssc_p    ssc_b  hsc_p  ... specialisation  mba_p      status    salary\n",
+              "0      M  67.00   Others  91.00  ...         Mkt&HR  58.80      Placed  270000.0\n",
+              "1      M  79.33  Central  78.33  ...        Mkt&Fin  66.28      Placed  200000.0\n",
+              "2      M  65.00  Central  68.00  ...        Mkt&Fin  57.80      Placed  250000.0\n",
+              "3      M  56.00  Central  52.00  ...         Mkt&HR  59.43  Not Placed       NaN\n",
+              "4      M  85.80  Central  73.60  ...        Mkt&Fin  55.50      Placed  425000.0\n",
+              "\n",
+              "[5 rows x 14 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 6
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "KWsGqdm5yKxl",
+        "outputId": "2ab95d08-c434-4d02-9512-780a2867f40a"
+      },
+      "source": [
+        "print(\"The shape of the data is (row,column):\" + str(data.shape))\n",
+        "print(data.info())"
+      ],
+      "execution_count": 12,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "The shape of the data is (row,column):(215, 14)\n",
+            "<class 'pandas.core.frame.DataFrame'>\n",
+            "RangeIndex: 215 entries, 0 to 214\n",
+            "Data columns (total 14 columns):\n",
+            " #   Column          Non-Null Count  Dtype  \n",
+            "---  ------          --------------  -----  \n",
+            " 0   gender          215 non-null    object \n",
+            " 1   ssc_p           215 non-null    float64\n",
+            " 2   ssc_b           215 non-null    object \n",
+            " 3   hsc_p           215 non-null    float64\n",
+            " 4   hsc_b           215 non-null    object \n",
+            " 5   hsc_s           215 non-null    object \n",
+            " 6   degree_p        215 non-null    float64\n",
+            " 7   degree_t        215 non-null    object \n",
+            " 8   workex          215 non-null    object \n",
+            " 9   etest_p         215 non-null    float64\n",
+            " 10  specialisation  215 non-null    object \n",
+            " 11  mba_p           215 non-null    float64\n",
+            " 12  status          215 non-null    object \n",
+            " 13  salary          148 non-null    float64\n",
+            "dtypes: float64(6), object(8)\n",
+            "memory usage: 23.6+ KB\n",
+            "None\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 436
+        },
+        "id": "RfSr_UTSybfo",
+        "outputId": "13740fe3-d1c3-44a0-91bd-858afb93a21f"
+      },
+      "source": [
+        "#Lewati cell ini jika tidak menggunakan profiling\n",
+        "\n",
+        "report = data.profile_report(title='Campus Placement Data - Report', progress_bar=False)\n",
+        "\n",
+        "report\n",
+        "\n",
+        "report.to_file(output_file='output.html')"
+      ],
+      "execution_count": 13,
+      "outputs": [
+        {
+          "output_type": "error",
+          "ename": "AttributeError",
+          "evalue": "ignored",
+          "traceback": [
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+            "\u001b[0;32m<ipython-input-13-22f76f445aac>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m#Lewati cell ini jika tidak menggunakan profiling\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mreport\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprofile_report\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Campus Placement Data - Report'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprogress_bar\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mreport\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m   5139\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_info_axis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_can_hold_identifiers_and_holds_name\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\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[1;32m   5140\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5141\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5142\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5143\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;31mAttributeError\u001b[0m: 'DataFrame' object has no attribute 'profile_report'"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 367
+        },
+        "id": "f6Rl6RUCy_xJ",
+        "outputId": "1f79b0db-2469-4b39-a906-1fe92527bbc6"
+      },
+      "source": [
+        "data['salary'].fillna(value=0,inplace=True)\n",
+        "print('Salary column with null values:',\n",
+        "      data['salary'].isnull().sum(), sep = '\\n')\n",
+        "\n",
+        "data.gender.value_counts()\n",
+        "\n",
+        "sns.countplot(\"gender\", hue=\"status\", data=data)\n",
+        "plt.show()"
+      ],
+      "execution_count": 16,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Salary column with null values:\n",
+            "0\n"
+          ],
+          "name": "stdout"
+        },
+        {
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
+            "  FutureWarning\n"
+          ],
+          "name": "stderr"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": "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\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 290
+        },
+        "id": "WuhWg-3AzrlM",
+        "outputId": "71e01827-3e1d-4533-e62d-f33cfcd3e147"
+      },
+      "source": [
+        "sns.kdeplot(data.salary[data.gender==\"M\"])\n",
+        "sns.kdeplot(data.salary[data.gender==\"F\"])\n",
+        "plt.legend([\"Male\",\"Female\"])\n",
+        "plt.xlabel(\"Salary (100k)\")\n",
+        "plt.show()"
+      ],
+      "execution_count": 19,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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mqKFkpVSc++dw4HLg6KjTngZudf/8YeDvWoqHzB/VJZBeyPGWwal1C3nELYaYLKgcf1GPpSnRDDhcVLX0+KChQixsZj4RpAOvKqUOALsxcgTPKqW+o5S61n3O/UCiUqoc+BfgKya2R/iTYwBq96KzNlLR1E3OdAKBUrB4C5zeOW6eIN89Q1nyBELMnmm1hrTWB4AiL/u/OeznPmD8wjJi7qo/CM5+2hIL6R10smQ6gQBg8blw8M/QchIS88Yc9gxFLW/o4vJVqb5osRALlswsFuao2g3AiVBjubzcpCnMIRhu8XnG9rT37qGYMDupMaGUNUjCWIjZkkAgzFFTAtHpHO+NBSAnaYojhjySlkFEIlS9M+4p+SlRnJCuISFmTQKBMEftPshYz6mmLkJsFjJiw6d3vVKQuQFq3hv3lKUp0ZQ1dMniJELMkgQC4Xv9ndBcDunrON3cQ3ZCBBbLDCaMZ26AhiPG/bzIT4miZ8BJbfvEq5oJISYmgUD4Xt0hQENGIVWtvWRPdSLZaJkbjPuc2e/18PCEsRBi5iQQCN9zf3DrtLVUt/SwKH6a3UIeGeuNbXWJ18NL3YFAZhgLMTsSCITvndkHUam0WRPp7HdMvbTEaJGJEJ8LNXu8Hk6MCiU+ws6JRnkiEGI2JBAI3ztzANLXUdVqzPqdcSCAqSWM6yUQCDEbEgiEbzkHoek4pK6mqqUXgEXxswwEHdXQWef1cF5KlIwcEmKWJBAI32ouB9cgpKymssXzRDDDHAG4E8aM2z20NCWK9t5BmroGZv4eQixwEgiEb9WXGtuUlVS19hAfYSc6zD7z+6WvBYtt/ECQKgljIWZLAoHwrYYjxgd30jKqWnpmlx8AsIdD6upxA4FnCOmJJlm/WIiZkkAgfKvhMCTmgy3ECASzyQ94ZG6Amr1eK5GmxYQREWKVUhNCzIIEAuFbDYchZSVOl6amrXf2TwQAaWuhvx1aK8YcUkqRlxwlQ0iFmAUJBMJ3+ruMD+uU1dR39DHo1LNLFHukrzW2dQe9Hs5LjuRko3QNCTFTEgiE7zQeM7YpK8+OGPJF11DKKlBWqDvg9XBechQ1bb30DDhm/15CLEASCITvNLhHDKWuGlpCcsZ1hoazhxtlqcd7InAnjOWpQIiZkUAgfKfhCNgjIC6HqtZelIKMOB90DYHRPXRm/CcCQPIEQsyQBALhO/WlkLwCLBaqWnpIjwkjxOaj/8TS1kJnLXQ3jTm0ODECi4IT8kQgxIxIIBC+03DE6M8H38whGC5tjbH1kicIs1tZlBAhTwRCzJBpgUAptUgp9apS6rBSqlQp9c9eztmqlGpXSu1zv77p7V5iDuhugu4GSHUHglaTAsEE3UMyl0CImbGZeG8H8EWt9XtKqWhgj1LqZa314VHnvam1vtrEdgh/aDxqbJOX0zfopL6j3zcjhjwiEiB20YRDSN8ub8Lp0lhnshqaEAuYaU8EWuszWuv33D93AkeATLPeTwRY03Fjm7SM6laj6mh2oo8SxR5payccQtrvcFHb1uvb9xRiAfBLjkAplQMUAe96ObxFKbVfKfWCUmr1ONffoZQqUUqVNDY2mthSMWNN5WALh5iss+sQ+PKJAIyRQ01lMDA2KewZQloueQIhps30QKCUigKeAL6gte4Ydfg9YLHWeh3wM+Cv3u6htb5Pa12stS5OTk42t8FiZprLjBpD7hFDMMsFabxJWwPosxVOhxkaQip5AiGmzdRAoJSyYwSBP2it/zL6uNa6Q2vd5f75ecCulEoys01Br/RJ+NMn4Mk7oaM20K2ZuqbjkJQPGCOGQm0WkqNCffseQyOHxuYJEiJD3MtWyhBSIabLzFFDCrgfOKK1/vE456S5z0Mptcndnmaz2hT0dvwc/nybMTLm8FPwf+cbXS7BztEPbZWQuBSAqpZesuLDsfg6aRu7CMJiof6Q18NSfE6ImTHzieA84GbgkmHDQ69SSt2plLrTfc6HgUNKqf3AvcANeqGuOVhfCi9/E1ZeA5/bA3e8Di4nPP05cLkC3bqJtZwE7TLKQACVvp5D4KEUpBZA3fiB4KQEAiGmzbTho1rrt4AJvxJqrX8O/NysNswZWsMLX4awGLjmXrCFQPIyuPI/4am74MCfoPDjgW7l+JrKjK2na6i1h+KceHPeK7UA9v7eCI6Wkd9j8lIiebRkgLaeAeIiQsx5fyHmIZlZHAyqS6DiTbjoK8Z4eY/Cj0PqGqPLKJgflDxDRxPzae8ZpLPP4fsRQx5pBTDYDa2nxhw6W3NI8gRCTIcEgmCw50EIiYKiT4zcrxScc6dR1fPUG4Fp21Q0l0N0BoRG+2bB+omkFhhbL3kCKT4nxMxIIAi03lY49ASs+QiERo89XvBhiEiEkgf837apaiob0S0EJgwd9UhZCcriNU+QFR9OiNUigUCIaZJAEGhHnwdHH6y/2ftxexis+gCUveR1IlXAae2eQ+AZMWRyILCHG+/l5YnAZrWQkxTBiYYg/DsJEcQkEATa0ecgJgsy1o9/zuoPwGCPEQyCTXcj9LVDkhEIKlt6iA23ExNmN+8909bIyCEhfEgCQSANdMOJ7bDi/UY+YDyLz4PIZCj1OvE6sIZGDLmfCFp7fbMq2UTSCqC9EnrbxhzKS47idEsPA44gH3IrRBCRQBBIJ/5udAuteP/E51mssPwqKN8OzkH/tG2qmt2BwN01VN3SY16i2CPVPcPYW8I4JRKnS1PZIt1DQkyVBIJAOvF3Y7TQ4nMnPzf/UhjoNIaaBpOmMrCFQewiXC5NdWuveUNHPdLcI4e8dA95Rg6VS55AiCmTQBBIp94wgoB1Cv3puRcZo2VObDe/XdPRVAYJeWCxUN/Zx4DTZV6i2CMqFSKSoH5szSEZQirE9EkgCJT2GmP8fe5FUzs/PA4yi43uoWDSXHY2P9BirAVgeiBQyngq8PJEEBlqIz02TAKBENMggSBQPBPEci+c+jV5l0DtXq9J0oBw9EPr6REjhgAWxZucIwBjYlnDEXA6xhwyis9J15AQUyWBIFAq3oTwhLMzZaci5zxAQ5W39X0CoOUUaOeIOQRKQaY/AkHaGnD2G09Vo+QlR3KioYuFWr9QiOmaUiBQSv1FKfV+pZQEDl+peheyzxlTOG1CmcVgscPpHea1azqaxxabS4sJI9RmNf+9Jyo1kRJFV7+Dhs5+89shxDww1U+hXwAfB8qUUj9QSi03sU3zX3ez8U02a+P0rguJgIwiqNxpTrumq2nk0NGqlh7zRwx5JC0zgqKXRWpktTIhpmdKgUBr/YrW+hPAeqACeEUptUMp9Un3KmRiOqp3GdtFm6d/7eJzoeY9GAyCRdqbyyEqzSifjZEsNj1R7GELgeQVUnxOCB+Ycr+EUioRuA34NLAX+ClGYHjZlJbNZ1W7wGIzvt1PV/YWcA0awSDQmo4PJYr7Bp3Ud/aZP5lsuHFGDqXGhBIZYpWEsRBTNNUcwZPAm0AEcI3W+lqt9aNa688BUWY2cF6q2mUkO0Nm8O05c4OxrQ1wINDa6BpKNPIDNW29aI3/uobAyBN01UF304jdSinyUmTZSiGmaqpPBL/WWq/SWn9fa30GQCkVCqC1LjatdfORywVn9hmJ35mISobY7MA/EfQ0Q1/b0PKUnqqj2Yl+DARDM4y95wkkRyDE1Ew1EHzXy74gyVjOMc3lMNA1s24hj8wiqNnjuzbNhGdVsmHF5sDfTwQT1BxKjqS2vY/u/rHzDIQQI00YCJRSaUqpDUC4UqpIKbXe/dqK0U000bWLlFKvKqUOK6VKlVL/7OUcpZS6VylVrpQ6oJSaoBbzPFG719jOKhBsgLbTxuijQBkaMeQeOtrSQ4jNQkp0qP/aEJkI0ekT1hw61SR5AiEmM9ni9VdiJIizgB8P298JfG2Sax3AF7XW7ymlooE9SqmXtdaHh53zPmCp+7UZ+KV7O3/V7gV7xFCXyox41i6ofQ+WXu6bdk1XcxlYQyEuGzACQVZ8OBbLBOW0zZBaMO5cAoDyhi4KMmP92yYh5pgJA4HW+mHgYaXU9VrrJ6ZzY3cu4Yz7506l1BEgExgeCK4DfquNKaDvKKXilFLpnjzEvFS7F9LWgnWyGDyBjEJAGXmCQAWCpnJIzDNKZGNMJvNrt5BHWgGcfA0cA8aQUrfFiRFYLYpyyRMIMakJP42UUjdprX8P5Cil/mX0ca31j71c5u0+OUARMLo2QiZQNez3ave+EYFAKXUHcAdAdnb2VN4yOLmcUHcA1t8yu/uERkPy8sDmCZqOQ+rqoV8rm3soXBTn/3akFhjDaZuOGSOx3EJtVnKTIjlW3+n/Ngkxx0yWLI50b6OAaC+vSSmlooAngC9orTtm0kit9X1a62KtdXFycvJMbhEcWiuMJSenU19oPBnrja6hQNTTcQwY/xZ3ori9d5COPof5K5N54/nw95InWJ4azXEJBEJMarKuoV+5t9+eyc3ds46fAP6gtf6Ll1NqgEXDfs9y75ufGo4Y29RVs79X5nrY/0dorxrqp/eb1ooxxebAzyOGPBLyjIVxvOQJlqVG8/yhM/QMOIgImUVXnBDz3FQnlP0/pVSMUsqulNqulGpUSt00yTUKuB84MkEX0tPALe7RQ+cA7fM6P+AJBMkrZn+vTHfCOBDzCYaKzY2cQ+C38hLDWW2QstLrXILlaVFojeQJhJjEVOcRXOHu1rkao9ZQPvCvk1xzHnAzcIlSap/7dZVS6k6l1J3uc54HTgLlwK+Bu6b7D5hTGg5DfA6ERE566qRSC8AaEpg8wdAcgrNVRyFAgQDOjhwa1U22LNXovTxWJ91DQkxkqs/LnvPeD/xZa91ufOEfn9b6LWDCk9yjhT47xTbMfQ2HIcUH3UIAtlDjXmf2++Z+09FUDpEpEGYMy6xq6SUmzEZseIDqD6atgb2/g846iEkf2r04MZIQm0XyBEJMYqpPBM8qpY4CG4DtSqlkoM+8Zs1DDvciKikrxz2ld8DJt58p5dzvb+cj/7eDlw/XT3zP9HVGIPB3wnjY8pRgrEwWsKcBGHdtAqtFsTQlimP10jUkxESmWob6K8C5QLHWehDoxpgDIKaquRxcjnGfCLr7HXzwF2/z4NsVrMqIoblrgDt/v4dn9teOf8/0dUa9n7ZKkxo9jqaRgaCqtScwI4Y8PMNYveUJUqM5Ll1DQkxoOkMpVmDMJxh+zW993J75y5MoHicQ/L+/HeVYfSe/uaWYy1al0tXv4PYHd/OFR/exPC16qL97hPRCY3tmP8QvNqnho3Q3Q2/L0Ighl0tT3drLZStT/fP+3oTHGYX4vI0cSovmL3traO8ZJDZCls4Qwpupjhr6HfAj4Hxgo/slVUeno+GwsQaBuzbPcLsrWnh452lu3ZLDZauMD9SoUBv/d/MGIkKs/OfzR7zfM3UVKKt/8wSjis01dPYz4HD5Z8H6iYyzNsHyNCOAHm+QpwIhxjPVJ4JiYJWW1cBnruGI8S16WBkEjx+/dJy0mDD+9cqRK4AmRIbw+UuW8r3nj/DG8UYuXDZqMp093BiK6tdAcMzYeoaOukcMZQWyawiMPMHxvxkrt9nPBqXlw0YObcxJCFTrhAhqU00WHwLSzGzIvFdf6jVRfLi2g50nm7ntvBwiQ8fG5VvOXUxmXDi/fO2E9/umrzPWN/BXjG4qMyZwuSexVbire+Yk+mBI7GykFYB2ne2Cc0uPDSM61CYjh4SYwFQDQRJwWCn1olLqac/LzIbNK/1dRtloL/mBB98+Rbjdyo0bvc8ODrVZ+fjmbHaebOaktxW30tdBd6MxdNIfGo8ZTzbuYnOVLT1YFGTGBbhraJyRQ0oplqVFc1QSxkKMa6qB4N+BDwD/Cfz3sJeYikZ3d8qo0hJtPQM8ta+W6zdkTpjI/EhxFjaL4tHdVWMPpq8ztv7qHmo6BslnS2ifbu4hMz6cENuUl782R3wuhER5HTm0zF1zSHo2hfBuqsNHX8eYUWx3/7wbCILV0+eIBnfl7VFdQy+V1jPgdPHR4kVeLjorJTqMy1am8uc91fQ7nCMPphUAyj+BYKAH2qpGrKVwurmbxQkB7hYCsFiMJy6vxeeiaOsZpLGzPwANEyL4TXXU0D8AjwO/cu/KBP5qVqPmnYYjYAuHuK1aH2cAACAASURBVJwRu589eIZFCeGsmcLCKR/dmEVL9wA7ToxalSw02hiJ5I9A0FwO6JGBoKXHv+sUTyStwMjFjC414R45JCWphfBuqs/zn8WoHdQBoLUuA1LMatS801AKKSuMb61urd0DvF3exPvXZDBZuQ6A8/KTiAq18eIhL7kAzwxjs3mGjiYbo5vaewZp6xkkJ1gCQWoB9LePmWC3XGoOCTGhqQaCfq31gOcX96Qy6XCdqoYjYxLFL5bW4XRprl6bPs5FI4XarGxdnszLh+txukb96dPXQUe1+WsYNx4DZTFKPwOnW4wRQ9nB0DUEZ9cmGJUwTowKJSU6lMO1M1oOQ4h5b6qB4HWl1NcwFrG/HPgz8Ix5zZpHupuhq35MfuDlw/VkxYezOiNmyrfaVpBGc/cAJRUtIw94EsZ1Jj8VNB2HuMVgDwOMRDFATlKQPBGkrAKU1zxBQWYsh2rb/d8mIeaAqQaCrwCNwEHgMxjlo79hVqPmlcaxpSX6HU52nGjm4uUpU+oW8ti6PIUQm4UXS0cVo0tfa2zN7h5qOj7ULQRGohgIbJ2h4UKjICEX6seOHCrIiKG8oYveAaeXC4VY2KY0s1hr7VJK/RX4q9a60eQ2zS9eagztqWild9DJRaNnCk8iKtTGOUsSef14AzCsqyk83vimbmYgcDqMZHH+ZUO7Tjf3kBwdGlyrf6UWeB1CWpAZi0vDkboO1mfHB6BhQgSvCZ8I3CuH/btSqgk4Bhxzr072Tf80bx5oOAxhcRB9dmL268cbsVsVW/ISp327C5cmcaKxm9q23pEH0teaGwjaToNzYOQTQUtP8CSKPdLWQOsp6B+ZGC5wj8wqrZHuISFGm6xr6G6M0UIbtdYJWusEYDNwnlLqbtNbNx/UuxejGdYF9PrxRooXJ3gtKTGZC5YaTxFvlTWNPJC+DlpOQp9JH3RDxeZGziEImkSxx9AM48MjdqfHhpEQGcKhGkkYCzHaZIHgZuBGrfUpzw6t9UngJuAWMxs2L2jtHjF0NlHc0NHH0brOsQXkpmhZahQp0aG8UTaqh85TktpLt4hPNI4sNtc36KS+oz8Inwg8gWDk30EpxeqMGA7KE4EQY0wWCOxa66bRO915AinuPpmOWmNc+7BA8M4pY8TPefnT7xYC4wPtgqXJvFXeNHIYqdmlJhqOQFSaUfsfo8YQEDyTyTxiFxlLaI4zcuh4fefY2dlCLHCTBYKBGR4TcDZR7FlBC3jnZDPRoTZWpU992OhoFyxNoq1nkCNnhnVzRKVAdLqJgaD07LdtzlYdXRzoqqOjKXV2MftRCjJicbg0x+tk6UohhpssEKxTSnV4eXUCaya6UCn1gFKqQSk19v9I4/hWpVS7Umqf+zX/EtCeGkPJK4Z2vXuymeKceGzWmRdp27zEqKv/7ikv8wnMCATOQaNraNjIJ88TQdB1DYHxd6g7ZLR7mIJMI/jKfAIhRprw00hrbdVax3h5RWutJ+saegjYNsk5b2qtC92v70yn4XNCw2HjW3qE8cHd0NnHicZuNi+ZWbeQR3psOIsSwtntLRA0HYeB7lndf4zmcmPEUOqwJ4LmbmLCbMRFjF1oJ+Ay1oOjd8zaBNkJEUSH2TgkeQIhRjCtdrDW+g2gZdIT57OGwyPyA7vcH9ybc2e/UtbGnAR2V7SMLK2cvs5YnKW+dNb3H8Fzv2FdXKebe8hJCrJuIY/M9ca2dmSBXKUUBRmxHJJSE0KMEOAi8mxRSu1XSr2glFo93klKqTuUUiVKqZLGxjkyn83lHNOd8s7JZiJDrENj2mdjU04Czd0DnGgc9u3frIRxfamx3vKwoaOVLT3BM6N4tIQlxtyNmrGV0gsyYzhypoNBpysADRMiOAUyELwHLNZarwN+xgRlrbXW92mti7XWxcnJMxt26XetFeDoG/FE8N7pNgqz47DPIj/gscn9VLF7eN2hmEyISDSWrvSl+lIjCLjXWx50uqhu7WVxMOYHwEgYZxSNeSIAY+TQgMPFCW+rvQmxQAUsEGitO7TWXe6fnwfsSqmkQLXH54YWozGeCHoGHByt66BokW/KG+QmRZIUFTLU3QQYH4BmJIwbDo/oFqpt68Xp0sE3Ymi4zPXGpLLBkTOwV2cYT2MysUyIswIWCJRSacpdcU0ptcndFpPrKPtRwxFADZVkOFjdjktDUXacT26vlGJjTsLIQABGIGg4Ag4frcbV2wbtVSMCQYW76ujiYO0aAsjcANo5ZoJdblIkkSFWDlS3BahhQgQf0wKBUuoRYCewXClVrZT6lFLqTqXUne5TPgwcUkrtB+4FbtDzaVHZ+lKIz4EQ41vz3irjg6dwkW8CARjdQzVtvdQMrzuUvg5cjrNPJLM19GRzNhCcdHerLEmO8s17mCHDnTCu2TNit9WiWJsVx95KCQRCeJhWNlJrfeMkx38O/Nys9w+4UYvR7K1sZXFiBIlRoT57i4057jzBqRYyizKNncMTxhlFs38TLyOGTjZ2Ex1mIykqCIeOesSkG0N3vSSMi7LjuO+Nk/QOOAkPsQagcUIEl0CPGpqfHP3G2Ht3olhrzd7KNop8+DQAsDI9huhQG7uGJ4zjcyE01nd5gvpSYwROTMbQrpNNXSxJjprWWgoBkbHea8J4fXY8DpeWiWVCuEkgMENTmdE/7Q4EZ9r7aOjs92m3EBjdHBty4kdOLFPKtyWp60uNp4FhH/onGrrJSw7iRLFHZpERkHtHdgMVuvM0751uDUSrhAg6EgjMMKrGkKc/usiEBVE25iRQ1tBFS/ew0k/jlFiYNpdzzIih7n4HdR195AVzfsAjc4OxHfVUkBQVSnZChOQJhHCTQGCGhsNgsQ8t8r63spUQm4WVsyg0Nx7PfIIR6xinrwNn/9k1BGaquRwGukbkGk65i80tCdZZxcNlFgMKqnaNOVSUHcd7la3Mp/EJQsyUBAIzNByGpKVDE7D2VrWxJjOWEJvv/9xrMmMJsVrYM7ybw1czjGv3GtthgcAzESsvZQ48EYTFGE8zVe+OObQ+O56Gzn6qW3u9XCjEwiKBwAzDagwNOFwcqmn3eaLYI8xupSAzZuQM48R8sEfMPhDUvAf2yBGlJU40dmNRBO+s4tEWbYLqEqOba5ihEVcVC7sclhAggcD3+juhrXIoEByt66Df4RpKUJphY04Ch2o66Bt0f9hZrJC21uvQyWmp3Ws8XVjODrE82dhFVnwEobY5Muxy0TnQ3wGNR0fsXp4WTUyYbeyEPCEWIAkEvuZZ0tE9h8DMRLHHhsXxDDhdI5dhXLTJ+CAfnGHXh9MBdQfGzEU40djNkrkwYshj0SZjO6p7yGpxz8yWJwIhJBD43KgaQ3srW0mJDiUjNsy0t9yw2AgyJRXD8gTZW8A1eLaff7rqDxlF8zwlnQGH0yjWtiw1ejbN9a/4HIhMgcqxeYKNuQmcbOymsdNH5TiEmKMkEPha/WGjfz5uMQD7qtooyo4zdfJVYlQoS5Ii2XN62LfbRZuNbeU7M7upZ6SN5z7A6ZYeBhyuuRUIlDKeCrwkjL2OuBJiAZJA4GsNh42lKS0WWroHqGjuMbVbyGPD4nj2nG7F5VnQPjLRSPJ6+QCckqp3IDoDYrOGdpXVdwKwLHUOjBgaLvscaD0FXQ0jdhdkxBJut45d8lOIBUYCga8NqzG0r8roqvH1jGJvNuYk0NozyMmmYXX2s8+Byp1jRsxMSeW7kL15xIzi4/XGvfPnwtDR4TxPNaPmE4TYLBTnxLPjRFMAGiVE8JBA4EvdTdDdMDRiaG9lGxYFa7NmvyLZZDbkeMkT5F4Efe3TH0baXg0d1caIm2GO1XeSnRBBRIhptQrNkb4OrCHGU84o5+Uncby+i4aOvgA0TIjgIIHAlzylJdyBYF9VGyvSYvzywbkkKZKEyBBKhk8sy7nA2J56fXo3O73D2GaPDARl9Z1zr1sIwBZqzDKueHvMofPzjbWQdpyYP0thCDFdEgh8aVjJZpdLs6+yzWcL0UxGKcX67PiRM4yjUyF5JZycZiA4+RqEx0PamqFdAw4XJxu751aieLic840lPPtGVhxdlR5DXISdt8qle0gsXBIIfKn+IEQkQVQqJxq76Ox3+CVR7FGcE8+ppm6auoYNh1xykZEnGJxi14fWRiDIvXDERLKK5m4cLj13A0HuBaBdY0ZRWSyKc/MS2VHeJHWHxIIlgcCX6kshrQCUGppI5o9EscdGb3mCvEuN+QAVb03tJk1l0FEDSy4esftYnTFiaOlc7BoCyNpo5AlOvTHm0Hn5SdS293GisTsADRMi8CQQ+IrTYeQIUgsAo9BcTJjNr1U6C9yF7UbMJ8i90KgXdOy5qd3k5KvGdsnWEbtLazuwWxVLU+boE4E9HLI2eQ2IFy1LBuC1Yw1jjgmxEEgg8JWWE8Y3b08gqGylMDsei8V/q3iF2qyszYwdmTC2h0H+JXDsBaPbZzJHnzXmHyTkjthdWtvO0pRoUyqo+k3O+UbZjFEL1WTFR7AsNYpXJRCIBcrMxesfUEo1KKUOjXNcKaXuVUqVK6UOKKXWeztvzqh3/zNTV9PV7+B4fadpFUcnsiEnnkM17WcL0AEsvwo6z3hdtnGE7iZjZM3Ka0fs1lpzuLaDgkzfr6fgV0N5gp1jDl28PIVdp1ro6ncEoGFCBJaZX+8eArZNcPx9wFL36w7glya2xXx1h8Big+TlHKhuw6Xx24ih4YoXJzDo1ByoHjY6Ztk2o3/8wGMTX3z0OWOJzVXXjdhd19FHc/cAqzPMnw9hqsxisIbCqTfHHLp4RQqDTs1bZTJ6SCw8pgUCrfUbwERz968DfqsN7wBxSql0s9pjuvpDkLQcbKHsq/J/othjqADd8DxBRILxVHDgMXAMjHMlcOhxo0jbsGGjAKU1HQCszpjjTwT2MKPuUMXYQLBhcTzRYTb+frQ+AA0TIrAC2eGbCVQN+73avW9u8izyjjGjeElSJHERIX5vRkJkCHnJkSNHDgEU3QS9LXD8Be8XNh4zRtSsv2VEWQkwEsVKYcpSm36XeyHUHTS6wYaxWy1cvDyFV4404HTJMFKxsMyJzJ9S6g6lVIlSqqSxsTHQzRmrp8UYcplWgNaavZVtpi5EM5lNuQnsrmgZ+YG25GKIy4a3fuI9abzr10b30fpbxxwqrW0nNzGSyNA5VlrCm/xLAQ0nXh1zaFtBGi3dA7JqmVhwAhkIaoBFw37Pcu8bQ2t9n9a6WGtdnJyc7JfGTcvQjOICqlt7aerq9+tEstG25CXR2eegtHZYnsBqgwu+ZCSMy14eeUHradj7eyj4MEQmjblfaW0Hq+Z6t5BHehFEJEL5K2MOXbQsmRCbhb8dqgtAw4QInEAGgqeBW9yjh84B2rXWZwLYnpkbGjFUMJQfCMSIIY9zlhh19sfUzyn8uJEDeOHfzg6h1Br+9lWjO+iSr4+5V117HzVtvQENbD5lsUDeJXBiO7hcIw5Fhtq4cGkyL5bWySxjsaCYOXz0EWAnsFwpVa2U+pRS6k6l1J3uU54HTgLlwK+Bu8xqi+nqDkFkMkSnsreyjTC7hRVpgZt4lRIdxtKUqLGBwGqHD94H7VXw6E1GWeZn7zYmm239yoi1BzzeqzRyDesD2NXlc/mXQXejMadglG0FaZxp72NvVZuXC4WYn0zr9NVa3zjJcQ181qz396u6/UMjbfZWtbI2Mw6bNbDply15ify5pJoBh2vkJLDszXDNvfD8l+D+y419530Bzv281/u8d7qVEJtl7g8dHS7vEmNb/gpkFI44dMXqVEKetPD0vlrWz5enICEmMSeSxUFtsNdYnjJjPf0OJ6U1HQGZPzDauXmJ9A462V/t5Ztt0Sfgc3vg+vvhzrfh8m+PGSnk8V5lK2vcpSvmjagUY42C8u1jDsWE2bl0RQrPHqjF4XR5uViI+Wce/d8dIHWHjElYGUUcru1gwOkKikCwZUkSFgVvHB9nlFVMBqz5sFEkbxz9DieHajrmV7eQR/5lxjKeo8pSA1xXmElT1wBvyxoFYoGQQDBbtXuNbUbR0Nj9YOhSiI2wU5Qdz2vHZj7cttQd2DyT1OaV/MuMAO5lGOnW5clEh9n4616vg9iEmHckEMxW7XsQmQIxGeyqaGFxYgQpMWGBbhUAW5clc7CmncbO/slP9mK3e1H3YAhsPpe1yVh859jzYw6F2a1csy6DFw6dob13MACNE8K/JBDMVu1eyFyPS0NJRQsbcxIC3aIhF69IASboHprEW+VNLEuNCprA5lNWm1F249jfvJbduGHjIvoGXTy9vzYAjRPCvyQQzEZ/l1GaIaOIE41dtPYMsimIAsGq9BiSokJ5bQaBoG/Qya5TLZyfH4QT+HxlxdXQ3+619tCazFhWpsfw2O4qLxcKMb9IIJiNugOAhowidrnLEmzMDZ5AYLEoLl6ezGvHGuh3OCe/YJjdFS30O1xcsHTsTON5I+9iY9Geo8+OOaSU4oaNizhY087B6rEJZSHmEwkEs1Hjru/vThQnRYWSkxgR2DaN8r41aXT2OXh7mouzv1XWhN2q2LwkeAKbz9nDjdpDR58fM8sY4ANFmUSEWHl4Z4XfmyaEP0kgmI3avRCTBVHGoiabcuNR44zHD5Tz840RMM8dmF79nDfLmlifHU9EyDwoNDeRlddCVx3UlIw5FBtu5/r1WTy9r5amrpkl3IWYCyQQzEbtXsgopLatl5q23qBKFHuE2CxcsSqNlw7XTbl76HRzN4fPdHCJO9k8ry27Aix2OPK018O3npvDgNPFH9+t9HPDhPAfCQQz1dtqrFOcUTRUtjgYAwHA1WvT6exz8ObxqXUPPXvAqP139boMM5sVHMJiYclFUPqU1+6h/JQoLlqWzG93Voxc/lOIeUQCwUxV7TK2izaz61QLUaG2oF245bz8JJKiQvnT7ql9q31mfy0bFseTGRducsuCxJqPQnulMdPYizsvyqOpa4A/l8gIIjE/SSCYqdM7jC6FrGJ2V7SwfnE8Vktw5Qc8QmwWbty0iO1HG6hq6Znw3OP1nRyt6+SatXN31dBpW/F+sEfAgUe9Hj5nSQJF2XH86o2TUn9IzEsSCGbq9A7IKKJ1wMrx+i425QT37NsbN2WjgD/umvip4E+7qrBaFFctpEAQGmUEg9InvU4uU0rx2a35VLf28qSUnRDzkASCmRjsNRLFi7cEfX7AIyMunMtWpvLIrkrae7yXTWju6ueRXZVcV5hBSvQ8nE08kbUfg742KH/Z6+FLV6awJjOWn24vY8AhTwVifpFAMBPVJeAahOxz2XGimTC7JaBrFE/VFy5bRnvvID/7e5nX4w/tqKDP4eSurXl+blkQWHIxRCSN2z2klOJLVy6nurWXR6eYaxFirpBAMBOVOwEF2Zt5s6yRTbmJhNqsgW7VpFZlxPCx4kU8tKOC8oauEccqmrp58O0KrliVSn5K4FZXCxirDQquN2oP9XpfnezCpUlsyk3gp9vL6OiTYnRi/pBAMBOnd0DKKs4MhHGisZsL8udOGYYvXrGcyFAbtz+0m/qOPgB6B5zc+fs92KyKb7x/VYBbGECFHwdn/4RPBd+8ehXN3QP85GXvT1VCzEUSCKbL6YDq3bB4C2+VGePyz5tDgSA5OpSHPrmR5q5+rvv523ztyYNc9uPXOVbfyU8+VsiihOAqkeFXGYWQsR5KHoBxFq8vyIzlxk3ZPLyzgmN1nf5tnxAmkUAwXXUHYKALsrfwdnkTSVEhAV2ofiaKsuP53ac3sywtmsdLqkmLDeN3t29m6/IFMJN4MsW3Q+NRd/efd/96xXKiw2x86+lD6HEChhBziamBQCm1TSl1TClVrpT6ipfjtymlGpVS+9yvT5vZHp84vQMA16ItvFXexHn5SViCdP7ARNZnx/Pb2zdx9D+28cQ/nsv587nK6HQUfAhCY42ngnHER4bwpSuW887JlqFZ2ELMZaYFAqWUFfhf4H3AKuBGpZS3DuhHtdaF7tdvzGqPz5x8FRKXsr8jgqaugTlfj2cuBjFThUTCuhvg8FPQPX5Jjhs3ZVOQGcN/PHuY1u6xcw+EmEvMfCLYBJRrrU9qrQeAPwHXmfh+5hvsg4q3If9S/n60AYuCi5bN44VbFqriT4JzAN777binWC2K/7p+La09A3z9rweli0jMaWYGgkxgeHGWave+0a5XSh1QSj2ulFrk7UZKqTuUUiVKqZLGxpkvxj5rlTvB0Qt5l7D9SAPFixOIiwgJXHuEOVJWQu5F8O6vwDF++enVGbH8y+XLef5gHX95T2Yci7kr0MniZ4AcrfVa4GXgYW8naa3v01oXa62Lk5MD+A38xHaw2KlL2GCUaV45t7uFxATO/4KxTsH+P0142h0XLmFTTgLferp00jpOQgQrMwNBDTD8G36We98QrXWz1trzles3wAYT2zN7x1+ExefycpkxGevSOZ4fEBNYcjGkrYUd94Jr/PLTVovivz+6DoC7H93HoBSlE3OQmYFgN7BUKZWrlAoBbgBGrP6hlBpe2exa4IiJ7ZmdpnJoOg4r3s9zB8+QnxJFfkpUoFslzKKU8VTQXA5Hn5vw1EUJEXzvgwWUnG7lP5497KcGCuE7pgUCrbUD+CfgRYwP+Me01qVKqe8opa51n/Z5pVSpUmo/8HngNrPaM2vHXwCgKesS3j3VwlVr0oNuWUrhYyuvg/gceOt/xp1g5nFdYSZ3XLiE3+48zSOTVHgVItiYuiCt1vp54PlR+7457OevAl81sw0+c/R5SF3DC5V2tDZW/RLznNUG5/8LPPN546lg5dUTnv7lbSs4cqaDbz51iKUpURQHeUVaITwCnSyeGzrOGCOGVl7NsweMbqFlqXNrNrGYocJPQOJS2P6dCXMFYOQLfn7jejLjwrnz93s41dTtp0YKMTsSCKbi8F8BzZlFV/HuqRauWbsA1vIVBqsNLr0Hmo7B/kcmPT02ws79t23E6dLcfP+7Q4X9hAhmEgim4tATkLaGP50MQym4foO36RBi3lp5LWRugFe/b0wqnERechQPfXITrd0D3HL/rnEXAhIiWEggmEzzCajejWv19Ty+p5rz85PIil/AFToXIqXgsm9DR7UxnHQK1i2K475bijnV1M0nH9pFp6xfIIKYBILJ7P0dKCu7Y6+kpq2XjxR7nfws5rvcC2D1h+CNHxlfDqbgvPwk7r2xiAPV7dwkTwYiiEkgmIhzEPb9EZZdya/39pAQGcIVq1ID3SoRKNu+D7ZQeO6Lkw4nHbqkII1ffGI9R2o7+Phv3pECdSIoSSCYyNHnoKueuryPsP1oPTdtzibMHvxLUgqTRKfBpd80KtAefHzKl12xOo37btlAeUMXN9z3DnXtkkAWwUUCwUR2/i/E5/KLmjzsFgs3bVkc6BaJQCu+3UgcP/9FaKua/Hy3rctTePC2jdS09fLBX7zN0boOExspxPRIIBhP1S6o3kVn4T/w2Hu1XFeYQUp0WKBbJQLNYoUP/dqYU/CXO4ylS6fo3PwkHvvMFrSGj/xy59BSp0IEmgSC8bz+XxCewE+bN+Jwaj57cX6gWySCRWIevP/HULkD3vzRtC5dlRHDk589l8z4cG57cBcPvn1K1jIQASeBwJvKd6D8FdrW38XDe5r46MZF5CRFBrpVIpis+xisvQFe+8GkRelGS48N5893bmHr8hS+/cxhvvDoPnoHJp61LISZJBCM5nLBS9+AyBTuqT0Hi1J8/pKlgW6VCEZX/w9kFMHjn4KaPdO6NDrMzn03b+BLVyzj6f21fPAXb1NW32lSQ4WYmASC0fb/Eap3c3DV3TxzpIN/vmwpabGSGxBehETAxx+FqBT448eg5eS0LrdYFP90yVIevG0jDZ39XP2zt3hIuopEAEggGK7jDLz0DRwZG7lj31JWpEXzDxcsCXSrRDCLSoFPPA4uBzx4FTQcnfYtti5P4W9fuIAteYn8+zOHueWBXbLamfArCQQeLhc8dRd6sI+v63+kucfBDz+8DrtV/kRiEsnL4LbnQbvgwfdB7d5p3yIlOowHb9vIdz9QQElFK5f/z+v8/O9l9DskdyDMJ59yHtu/DSf+zouL/plHT4XxzWtWsSYrNtCtEnNF6ir45AsQEgUPvA/2/mHat1BKcdM5i9n+xYu4eHkKP3rpONt+8ibPHqjF5ZLuImEeCQQAO38Bb/+E0owPc+eRNdy4KZtPbM4OdKvEXJOYB59+BbKK4am74K93QW/btG+TERfOL2/awMO3b8JqUfzTH/ey7adv8Mz+WhyyJrIwgZpriani4mJdUlLim5tpDW/8EF79HkfjL+bqM5/kfeuy+cnHCrFaZBlKMUMupzGs9I0fQkSisZ5B0c3GZLRpcro0zx08w73byyhv6CIlOpTrN2Tx0eJF5I43pNnlhNYKaDgM9YeNbWcd9HdAXwcMdIHVDrYwo3ZSaAzEZEBsFsRkQtIySCswfpblWOcNpdQerXWx12MLNhB0N8Ez/wxHn+XNiEv5ZMutfHxLHt+8ehU2yQsIXzizH174srG6XUIebP4MFH4cQqe/up3Tpdl+pJ5Hd1fx6rEGXBqWp0TxvhzFJYnN5OtKItqOGR/6DUfB0eu+UhnrLsctMj7wQ2MgJNJIbjv6wdlvPLV01EB7DQwMG8IaFgepBUZQSF8H6YVGkLCausKtMIkEguF622Dv73C98SNc/d38t/MGfsv7uefq1dywSbqDhI9pDYefgh0/g5oSsIXDkq2wfBtkbYKkpca388nu0XkGmsuhqYyemkO0VRwguuM40a6zNYuaiKMuNIfmyKV0xCylL34F3bH5aHsEVoti0KnpG3QOvXoHnfQNuhhwuBh0Gi/bYAfpfafIGDjJ4sFT5DpPsWjwFGHaKJQ3aAmlKWoFXQmrGUhZizVzPbHZq0iKiQy6gRUul6apu5/69n7qOvqo7+ijsbOf7n4H3QNOegYc9Aw4cThd2KwWbBaF1aIIsVqIDrMRQAY0kQAADDhJREFUHxlCfEQIcRF2kqJCyYgLJz02bM4WngxYIFBKbQN+CliB32itfzDqeCjwW2AD0Ax8TGtdMdE9ZxwImsoYfOte1ME/Y3P28pZrDd8evJllazbylW0rWJQgi80Ik1WXwIHH4NgL0F5p7LOGQvxiiEyBiHiw2AAF/Z3Q0wy9LdDVAIPDhpPaIyFlJaSuYiBxJUddWezvz+BAq52yhi4aO/tp7RmgZ4LZyuF2K2F2C2F2K2F2K3arwmaxYLdZCLEq7FYLWkO/w8nAwCDJA1XkDhwnZ6CMFZxktaogUvUD0KtDKNU5lFvzqQvPpy86G1d8LmEJWaTGhpMSHUZqTCipMWEkRob45Im7q99BXXsfDR191Hf2Ud/RT1278WFf19FHfXsfDZ39OLwk2SNDrISH2IgMtRIRYsNmUThcGqfLhcOpGXC66OgdpKPPex2pxMgQ0uPCyIgNJyMunIy4MNJjjW1KdBgpMaGE2oIvWAQkECilrMBx4HKgGtgN3Ki1PjzsnLuAtVrrO5VSNwAf1Fp/bKL7zjgQHH+R/kdu5snBLTxp28bSwvO56ZzFrEiLmf69hJgNraGpzOg6qtsPbZXQ1Wh86GuX8QqJMvILEQkQmWwkohPzjS6mmEywTP5h2jfopN/hwunSOF0au1URZrcSarOgZtH33zPgoLmjl+4zR3FUvYet/gDRrYdI6jpGqKt36Lx+badKJ1OrE2kilmYdQwsx9IcmYA+PISQixpiUZ4uE0AiwR6Etdga0xXi5rPRrC539Ljr6BunoddDRN0hr9wDdXoJcVKiN1JhQ0mLDSI0JIy0mbMzP0wlEDqeLtl7j/Rq7+jnT1kdtWy+17cb2THsvtW19dPWPDRhxEXZS3UEhOSqU2Ag7MWF2YsLtxITZiAm3Ex1mI8xuJcRqIdRmIcT9CrVZCbFZsFsVVqWwKIXFBznLQAWCLcC/a62vdP/+VQCt9feHnfOi+5ydSikbUAck6wkaNeNA4HLy7tEKXKFxFOfEB91jrBBznstpBLXWU9ByClfLSQYaT+Jqr4WeJux9zdidvZPfZ5S7on5KU9RyYsJtxITZiY2wkxZjfMCnxISSFhNGSkwYUaGByV109A0agaGtj4bOPho6+qkf2vbT1NlPR+8gnV4CxnRYFNx5UR7/tm3FjK6fKBCY+ZfLBIYXbK8GNo93jtbaoZRqBxKBEfV5lVJ3AHe4f+1SSh2bYhuSRt9rDpG2B8ZcbftcbTdM2vZP+q0hM+DXv/uXfwBfnvnl4y6oMifS/1rr+4D7pnudUqpkvAgY7KTtgTFX2z5X2w3S9mBgZv9IDTB8pfcs9z6v57i7hmIxksZCCCH8xMxAsBtYqpTKVUqFADcAT48652ngVvfPHwb+PlF+QAghhO+Z1jXk7vP/J+BFjOGjD2itS5VS3wFKtNZPA/cDv1NKlQMtGMHCl6bdnRREpO2BMVfbPlfbDdL2gJtzE8qEEEL4loyhFEKIBU4CgRBCLHDzKhAopRKUUi8rpcrc23gv5xQqpXYqpUr/f3vnH2tlXcfx19tbqA2MylJqNjLBBCxCJJdbarIkbFKpDRb5I6bT0uVcORyb/fxHt1qLZAUNEVdIOkUaUQ0Go7FQM1F+OBDE2p0o0dRWKwV798f3e+Xp9BzOcy73nnPuuZ/X9mzf83w/9zzv+915zud8fzzvr6SnJR31SebBRNIMSbsk7ZE0v6T+eEkrc/2jksa2XmU5FbTfKmlnbuP1kuquYW41jbQX4i6XZEkdszywinZJX8htv0PSL1qtsR4VPjPvl7RB0pP5czOzHTprkbRU0gFJ2+vUS9KP8v/1tKQprdZ4zNjumgO4C5ify/OBO0tixgPjcvm9wH5gdBu09gB7gdOBEcBTwISamK8AP8nl2cDKdrdxE9ovAt6WyzcOJe05bhSwCdgCTG237ibafRzwJPCO/Po97dbdhPbFwI25PAF4vt26s5ZPAFOA7XXqZwJrAQHnAY+2W3OzR1f1CIBZwL25fC/w2doA27ttP5vLLwAHgHe3TOERpgF7bD9n+3XgfpL+IsX/50HgYh2LSczA0VC77Q22+5zStpCeI+kEqrQ7wHeBO4F/t1JcA6povw642/bLALYPtFhjPapoN9Bn/vV24IUW6quL7U2kVY31mAUsd2ILMFrSmNaoGxi6LRGcYnt/Lr8InHK0YEnTSL9O9g62sBLKLDjeVy/G9mGgz4Kj3VTRXmQe6RdTJ9BQe+7an2Z7TSuFVaBKu48HxkvaLGlLdgDuBKpo/xYwV1Iv8Gvg5tZIO2aavR86jiFhMVFE0jrg1JKqBcUXti2p7trYnLHvA662Hfv/DRKS5gJTgQvaraUKko4DfgBc02Yp/eUtpOGhC0m9sE2Szrbd/J6ZrWcOsMz297Np5X2SJsX9OfgMuURge3q9OkkvSRpje3/+oi/tFks6CVgDLMhduXbQjAVHb4dZcFTRjqTppAR9ge3XWqStEY20jwImARvzKNypwGpJl9keoD1S+02Vdu8ljVEfAvZJ2k1KDI+3RmJdqmifB8wAcHIkPoFk6tYpw1v1qHQ/dDLdNjRUtKy4GnikNiDbXTxMGtN7sIXaahnKFhwNtUv6KPBT4LIOGqeGBtptv2r7ZNtjbY8lzW90QhKAap+ZVaTeAJJOJg0VPddKkXWoov0vwMUAks4CTgD+2lKV/WM1cFVePXQe8GphiHpo0O7Z6oE8SOPn64FngXXAO/P5qaQd0gDmAoeArYVjcpv0ziRt3rOX1DsB+A7piwfSjfAAsAd4DDi93W3chPZ1wEuFNl7dbs1VtdfEbqRDVg1VbHeRhrZ2AtuA2e3W3IT2CcBm0oqircCn2q0561pBWl14iNTjmgfcANxQaPO78/+1rZM+L1WPsJgIgiAY5nTb0FAQBEHQJJEIgiAIhjmRCIIgCIY5kQiCIAiGOZEIgiAIOphGpncl8U2bDkYiCLoGSQsKrrJbJX2sQfwySVcMkpZbJF2Vy1dmXf+pdTKVdHt2rdwl6ZLC+VKnTknP5+cDiu8xQtKm/NBh0H0sIz9o1whJ44DbgfNtTwRuqfJ3kQiCriBbEnwGmGL7w8B0/tf/ZSCuUemLNsd9Gej7NbYd+DzJzbQYN4H0YNVE0o2+SFKPpB7SuvRPk9bWz8mxpTiZuK0H2mapHgweLjG9k/RBSb+R9ISk30v6UK7ql+lgJIKgWxgDHHS2srB90MldFkl3SHpc0nZJi8scXOvFSNoo6YeS/ggskLRP0ltz3UnF1wU+CfzJySgQ28/Y3lWieRZwv+3XbO8jPTg4jQpOnZJOlLRW0nX51Crgi803WzBEWQzcbPsc4OvAony+X6aDkQiCbuF3wGmSdktaJKlocvdj2+fangScSOo51HK0mBG2p9r+NulJ40vz+dnAQ06+PkXOB56ooLmea2UjN8uRwK+AFbaX5HPbgXMrXDMY4kgaCXwceEDSVpKVS5/tddF0cA6wRNLoRu8ZiSDoCmz/AzgHuJ7kT7NS0jW5+iKlHd62kX6tTyx5i6PFrCyUfwZcm8vXAveUvNcYBtcj5xHgHtvL+07YfgN4XdKoQbxu0BkcB7xie3LhOCvX9ZLsXA7lXmaf6WDDNwyCrsD2G7Y32v4mcBNweXawXARcYftsYAnJw+lNKsT8s3CNzcBYSRcCPbbLVnL8q/YadajnWtnIzXIzMKNkiOt4OmsjnWAQsP13krPslfDmVpkfydX9Mh2MRBB0BZLOzCsm+pgM/JkjX8gHc5e6bJVQlZgiy0kTwWW9AYBngDMqyF4NzFbam/oDpF9uj9HYqfMO4GXShDIAkt5FmiOpHaYKhjiSVgB/AM6U1CtpHmk+aJ6kp4AdHJlD+i3wN0k7gQ3AN2w3tK6P5WZBtzASWJjHQw+TJl6vt/2KpCWkMfQXKfHlrxJTw8+B75FcKctYS9r0CABJnwMWkrZEXSNpq+1LbO+Q9EuSU+hh4Kt5iAdJN5Fu6h5gqe0dNdf4GrBU0l22byPtEd1pO6oFA4DtOXWq/m8i2MlF9NZ8VCbcR4OgSfKzB7Nsf+koMQ8Dtznvj90CTQ8B823vbsX1gu4iegRB0ASSFpLW989sEDqfNGk86IkgDx+tiiQQ9JfoEQRBEAxzYrI4CIJgmBOJIAiCYJgTiSAIgmCYE4kgCIJgmBOJIAiCYJjzX7o8FIkq2esIAAAAAElFTkSuQmCC\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Fjrqs4WWzrL4"
+      },
+      "source": [
+        ""
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 293
+        },
+        "id": "yEsL9vJp0cE3",
+        "outputId": "f79dc0c2-f96a-4005-db56-fcea56a4b559"
+      },
+      "source": [
+        "plt.figure(figsize=(18,6))\n",
+        "sns.boxplot(\"salary\",\"gender\",data=data)\n",
+        "plt.show()"
+      ],
+      "execution_count": 20,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
+            "  FutureWarning\n"
+          ],
+          "name": "stderr"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": "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\n",
+            "text/plain": [
+              "<Figure size 1296x432 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 279
+        },
+        "id": "t2xxrz2H0nGA",
+        "outputId": "d4c8d854-b28e-4449-bcb3-ef02a8c0ae89"
+      },
+      "source": [
+        "sns.kdeplot(data.ssc_p[data.status==\"Placed\"])\n",
+        "sns.kdeplot(data.ssc_p[data.status==\"Not Placed\"])\n",
+        "plt.legend([\"Placed\",\"Not Placed\"])\n",
+        "plt.xlabel(\"Secondary Education Percentage\")\n",
+        "plt.show()\n"
+      ],
+      "execution_count": 23,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 334
+        },
+        "id": "lzwg0q5Z1jiY",
+        "outputId": "a3e690fe-a165-4a23-d7d0-c229180c6525"
+      },
+      "source": [
+        "sns.countplot(\"ssc_b\",hue=\"status\",data=data)\n",
+        "plt.show()"
+      ],
+      "execution_count": 24,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
+            "  FutureWarning\n"
+          ],
+          "name": "stderr"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": "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\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 287
+        },
+        "id": "Kl0X5lGS1rO1",
+        "outputId": "0a97eb85-5a67-4780-a34c-cfec152bc110"
+      },
+      "source": [
+        "plt.figure(figsize=(18,6))\n",
+        "sns.boxplot(\"salary\",\"ssc_b\",data=data)\n",
+        "plt.show()"
+      ],
+      "execution_count": 25,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
+            "  FutureWarning\n"
+          ],
+          "name": "stderr"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 1296x432 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 333
+        },
+        "id": "3CjhTuk52HYR",
+        "outputId": "46416d30-b78f-406b-c8e7-b567c8ae4c17"
+      },
+      "source": [
+        "sns.lineplot(\"ssc_p\",\"salary\",hue=\"ssc_b\",data=data)\n",
+        "plt.show()"
+      ],
+      "execution_count": 26,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
+            "  FutureWarning\n"
+          ],
+          "name": "stderr"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": [],
+            "needs_background": "light"
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 454
+        },
+        "id": "s09DZxBQ2WDu",
+        "outputId": "ebe262f0-c082-4919-a2cd-328bd9c096a7"
+      },
+      "source": [
+        "sns.set(rc={'figure.figsize':(12,8)})\n",
+        "sns.set(style=\"white\", color_codes=True)\n",
+        "sns.jointplot(x=data[\"etest_p\"],y=data[\"salary\"],kind='kde', color=\"skyblue\")\n",
+        "\n",
+        "plt.show()"
+      ],
+      "execution_count": 27,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<seaborn.axisgrid.JointGrid at 0x7fb69a05c510>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 27
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 432x432 with 3 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 828
+        },
+        "id": "q8StdEcI3M0D",
+        "outputId": "68ef4e5d-4eed-4ed3-e49d-450635c60381"
+      },
+      "source": [
+        "plt.figure(figsize = (15,7))\n",
+        "plt.style.use('seaborn-white')\n",
+        "\n",
+        "plt.subplot(231)\n",
+        "sns.distplot(data['ssc_p'])\n",
+        "fig=plt.gcf()\n",
+        "fig.set_size_inches(10,10)\n",
+        "\n",
+        "plt.subplot(232)\n",
+        "sns.distplot(data['hsc_p'])\n",
+        "fig = plt.gcf()\n",
+        "fig.set_size_inches(10,10)\n",
+        "\n",
+        "plt.subplot(233)\n",
+        "sns.distplot(data['degree_p'])\n",
+        "fig = plt.gcf()\n",
+        "fig.set_size_inches(10,10)\n",
+        "\n",
+        "plt.subplot(234)\n",
+        "sns.distplot(data['etest_p'])\n",
+        "fig = plt.gcf()\n",
+        "fig.set_size_inches(10,10)\n",
+        "\n",
+        "plt.subplot(235)\n",
+        "sns.distplot(data['mba_p'])\n",
+        "fig = plt.gcf()\n",
+        "fig.set_size_inches(10,10)\n",
+        "\n",
+        "plt.subplot(236)\n",
+        "sns.distplot(data['salary'])\n",
+        "fig = plt.gcf()\n",
+        "fig.set_size_inches(10,10)\n"
+      ],
+      "execution_count": 29,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+            "  warnings.warn(msg, FutureWarning)\n",
+            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+            "  warnings.warn(msg, FutureWarning)\n",
+            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+            "  warnings.warn(msg, FutureWarning)\n",
+            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+            "  warnings.warn(msg, FutureWarning)\n",
+            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+            "  warnings.warn(msg, FutureWarning)\n",
+            "/usr/local/lib/python3.7/dist-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n",
+            "  warnings.warn(msg, FutureWarning)\n"
+          ],
+          "name": "stderr"
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 720x720 with 6 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 319
+        },
+        "id": "pKx1ZR254l2L",
+        "outputId": "37086eba-c875-482e-8c58-7dcc1458ac07"
+      },
+      "source": [
+        "plt.style.use('seaborn-white')\n",
+        "f,ax=plt.subplots(1,2,figsize=(18,8))\n",
+        "data['workex'].value_counts().plot.pie(explode=[0,0.05], \n",
+        "autopct='%1.1f%%',ax=ax[0],shadow=True)\n",
+        "\n",
+        "ax[0].set_title('Work experience')\n",
+        "sns.countplot(x='workex',hue='status', data = data)\n",
+        "ax[1].set_title('influence of experience on placement')\n",
+        "\n",
+        "plt.show()\n"
+      ],
+      "execution_count": 34,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<Figure size 1296x576 with 2 Axes>"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          }
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 224
+        },
+        "id": "fK4CXU_G6N-N",
+        "outputId": "173b0f25-a848-4f5d-e13c-22f0696e6d77"
+      },
+      "source": [
+        "from sklearn.preprocessing import LabelEncoder\n",
+        "object_cols = ['gender','workex','specialisation','status']\n",
+        "\n",
+        "label_encoder = LabelEncoder()\n",
+        "for col in object_cols:\n",
+        "  data[col] = label_encoder.fit_transform(data[col])\n",
+        "data.head()"
+      ],
+      "execution_count": 35,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "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>gender</th>\n",
+              "      <th>ssc_p</th>\n",
+              "      <th>ssc_b</th>\n",
+              "      <th>hsc_p</th>\n",
+              "      <th>hsc_b</th>\n",
+              "      <th>hsc_s</th>\n",
+              "      <th>degree_p</th>\n",
+              "      <th>degree_t</th>\n",
+              "      <th>workex</th>\n",
+              "      <th>etest_p</th>\n",
+              "      <th>specialisation</th>\n",
+              "      <th>mba_p</th>\n",
+              "      <th>status</th>\n",
+              "      <th>salary</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>1</td>\n",
+              "      <td>67.00</td>\n",
+              "      <td>Others</td>\n",
+              "      <td>91.00</td>\n",
+              "      <td>Others</td>\n",
+              "      <td>Commerce</td>\n",
+              "      <td>58.00</td>\n",
+              "      <td>Sci&amp;Tech</td>\n",
+              "      <td>0</td>\n",
+              "      <td>55.0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>58.80</td>\n",
+              "      <td>1</td>\n",
+              "      <td>270000.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>1</td>\n",
+              "      <td>79.33</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>78.33</td>\n",
+              "      <td>Others</td>\n",
+              "      <td>Science</td>\n",
+              "      <td>77.48</td>\n",
+              "      <td>Sci&amp;Tech</td>\n",
+              "      <td>1</td>\n",
+              "      <td>86.5</td>\n",
+              "      <td>0</td>\n",
+              "      <td>66.28</td>\n",
+              "      <td>1</td>\n",
+              "      <td>200000.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>1</td>\n",
+              "      <td>65.00</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>68.00</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>Arts</td>\n",
+              "      <td>64.00</td>\n",
+              "      <td>Comm&amp;Mgmt</td>\n",
+              "      <td>0</td>\n",
+              "      <td>75.0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>57.80</td>\n",
+              "      <td>1</td>\n",
+              "      <td>250000.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>1</td>\n",
+              "      <td>56.00</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>52.00</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>Science</td>\n",
+              "      <td>52.00</td>\n",
+              "      <td>Sci&amp;Tech</td>\n",
+              "      <td>0</td>\n",
+              "      <td>66.0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>59.43</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>1</td>\n",
+              "      <td>85.80</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>73.60</td>\n",
+              "      <td>Central</td>\n",
+              "      <td>Commerce</td>\n",
+              "      <td>73.30</td>\n",
+              "      <td>Comm&amp;Mgmt</td>\n",
+              "      <td>0</td>\n",
+              "      <td>96.8</td>\n",
+              "      <td>0</td>\n",
+              "      <td>55.50</td>\n",
+              "      <td>1</td>\n",
+              "      <td>425000.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>"
+            ],
+            "text/plain": [
+              "   gender  ssc_p    ssc_b  hsc_p  ... specialisation  mba_p  status    salary\n",
+              "0       1  67.00   Others  91.00  ...              1  58.80       1  270000.0\n",
+              "1       1  79.33  Central  78.33  ...              0  66.28       1  200000.0\n",
+              "2       1  65.00  Central  68.00  ...              0  57.80       1  250000.0\n",
+              "3       1  56.00  Central  52.00  ...              1  59.43       0       0.0\n",
+              "4       1  85.80  Central  73.60  ...              0  55.50       1  425000.0\n",
+              "\n",
+              "[5 rows x 14 columns]"
+            ]
+          },
+          "metadata": {
+            "tags": []
+          },
+          "execution_count": 35
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "f2QkQXVp6rhb",
+        "outputId": "671c4d4c-a692-4a13-a809-a5081fd8c3c9"
+      },
+      "source": [
+        "from sklearn.tree import DecisionTreeClassifier\n",
+        "from sklearn.ensemble import RandomForestClassifier\n",
+        "from sklearn.linear_model import LogisticRegression\n",
+        "\n",
+        "from sklearn.model_selection import train_test_split\n",
+        "from sklearn.metrics import accuracy_score, classification_report\n",
+        "\n",
+        "X=data[['ssc_p','hsc_p','degree_p','etest_p']]\n",
+        "y=data['status']\n",
+        "\n",
+        "X_train, X_test, y_train,y_test = train_test_split(X,y,test_size=0.3,random_state=4)\n",
+        "\n",
+        "dtree = DecisionTreeClassifier(criterion='entropy')\n",
+        "dtree.fit(X_train,y_train)\n",
+        "\n",
+        "y_pred = dtree.predict(X_test)\n",
+        "\n",
+        "print(\"Accuracy Score:\",accuracy_score(y_test,y_pred))\n",
+        "print(classification_report(y_test,y_pred))"
+      ],
+      "execution_count": 65,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Accuracy Score: 0.8461538461538461\n",
+            "              precision    recall  f1-score   support\n",
+            "\n",
+            "           0       0.78      0.70      0.74        20\n",
+            "           1       0.87      0.91      0.89        45\n",
+            "\n",
+            "    accuracy                           0.85        65\n",
+            "   macro avg       0.83      0.81      0.81        65\n",
+            "weighted avg       0.84      0.85      0.84        65\n",
+            "\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "q8GzNYHJ8JDk",
+        "outputId": "a027f655-9911-4816-dcac-a30968a63e4d"
+      },
+      "source": [
+        "#Using Random Forest\n",
+        "\n",
+        "random_forest = RandomForestClassifier(n_estimators=100)\n",
+        "random_forest.fit(X_train,y_train)\n",
+        "\n",
+        "y_pred = random_forest.predict(X_test)\n",
+        "\n",
+        "print(\"Accuracy Score:\",accuracy_score(y_test,y_pred))\n",
+        "print(classification_report(y_test,y_pred))"
+      ],
+      "execution_count": 73,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Accuracy Score: 0.8615384615384616\n",
+            "              precision    recall  f1-score   support\n",
+            "\n",
+            "           0       0.79      0.75      0.77        20\n",
+            "           1       0.89      0.91      0.90        45\n",
+            "\n",
+            "    accuracy                           0.86        65\n",
+            "   macro avg       0.84      0.83      0.84        65\n",
+            "weighted avg       0.86      0.86      0.86        65\n",
+            "\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Btn2T-nc8uEV",
+        "outputId": "e7aa76f5-2bbe-45ec-f72f-fe2f5a5b2f4a"
+      },
+      "source": [
+        "#Using Logistic Regression\n",
+        "\n",
+        "LogR = LogisticRegression(solver='lbfgs')\n",
+        "LogR.fit(X_train,y_train)\n",
+        "\n",
+        "y_pred = random_forest.predict(X_test)\n",
+        "\n",
+        "print(\"Accuracy Score:\",accuracy_score(y_test,y_pred))\n",
+        "print(classification_report(y_test,y_pred))"
+      ],
+      "execution_count": 76,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "text": [
+            "Accuracy Score: 0.8615384615384616\n",
+            "              precision    recall  f1-score   support\n",
+            "\n",
+            "           0       0.79      0.75      0.77        20\n",
+            "           1       0.89      0.91      0.90        45\n",
+            "\n",
+            "    accuracy                           0.86        65\n",
+            "   macro avg       0.84      0.83      0.84        65\n",
+            "weighted avg       0.86      0.86      0.86        65\n",
+            "\n"
+          ],
+          "name": "stdout"
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "8x5ppQmv8_7T"
+      },
+      "source": [
+        "# Final Deployment Pickle File\n",
+        "\n",
+        "pickle.dump(random_forest,open('deployed_ML_RF_model_classifier.pkl','wb'))\n",
+        "pickle.dump(dtree,open('deployed_ML_DT_model_classifier.pkl','wb'))\n",
+        "pickle.dump(LogR,open('deployed_ML_LR_model_classifier.pkl','wb'))"
+      ],
+      "execution_count": 79,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file