Dropout_code+visualization.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "S_Wtv181X9bf",
        "outputId": "465e6eec-aa02-4a18-ec27-b402246a74dc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy: 99.90%\n",
            "\n",
            "Enter Student details to calculate dropout probability:\n",
            "School Type: Private\n",
            "Location: Rural\n",
            "Gender: Female\n",
            "Caste: General\n",
            "Age: 13\n",
            "Standard: 6\n",
            "Socioeconomic Status: Low\n",
            "Estimated dropout probability: 61.00%\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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ZpWaRtMLa2ppcuXJx+/ZtDhw4YDyeJ08eBg8eTLNmzfjiiy+YMWOGGasUSXsMBgObN2+mQ4cOlCtXDh8fH65cuYKHhwdHjhyhUqVKTJ8+nTx58lCmTBnu3r2rJXwiwC+//EKbNm0ACAwM5L333uPSpUsUKFAAJycn6tevT7169fj888+N18zKlSs5evRoqvYLIvJqPT9D6ssvv2Ty5MkUL16cevXqYWtry6hRowgLCzOGVg8ePKBy5cqMHTsWT09Pc5Utr4AhWR1kRV6JSZMmsW/fPq5cucKHH35ImzZtKFWqFO7u7hw5coR8+fLh5ubG8ePHiYyM5MiRI1hbW2v9s2R4ly5dYurUqRw/fhx3d3f69u1rvO3WrVssW7aMLl26UKhQITNWKWJe8fHxWFtbG2fmPn78mA4dOtC4cWM8PDyIjo6mcOHCdOrUCV9fX+N5Bw4cYOrUqfj5+fHWW2+Zq3yRNOPw4cM0bdoUV1dXjh07xldffcVHH30EwJ07d2jfvj13795l+vTpxMTE8NNPP+Hv709QUBBlypQxc/Ui6d+2bdu4cOECdnZ29OnTB4CbN29So0YN8uXLR9euXSlYsCC+vr44OjqyZs0aY5sHjaneTAqlRP6h51/4ZsyYwezZsxk+fDhPnjxhw4YN/Oc//2HMmDHUqFGDNWvWsHHjRrJkyULBggUZN24cVlZWJCQkYGWl/QYkY0hZLnH8+HEuX75MXFwcderUIW/evFy+fJkpU6Zw7tw5unfvniqYUpNmyej8/f25evUqI0aMwMHBAXjWY6Nu3bosXrwYJycnatSoQfPmzfn888+BZx/qixYtyltvvcXTp0+xtbU151MQSVO8vb0ZM2YMJUuW5OTJk8Bv7zXXr19nwIABXLp0CYPBgKurK97e3gqkREzg1q1b5M+fH4AJEyYwYcIE4+fH+/fv0717d65fv050dDQuLi7s3LnT+IWN+vS+uRRKifxL58+fx9/fn5o1a9KiRQsAQkND8fb2JiIigmXLluHi4vLCeRpoS0a0du1a+vfvj7OzM7GxsYSHh7Ns2TLat29vnDF1+fJl2rZty+DBg81drkia0K1bN06cOMGHH35Iv379cHBw4MGDBzRo0IAPP/yQpUuXGgMqS0tLwsLC8PDwoH379rRt29bc5YukCc8PWjdt2sTRo0f58ssvKVSoELt27cLCwiLVZ7OUXmy2trbGMFhEXr/Dhw/ToUMHChYsyLfffkuuXLmMkwESExN59OgRkZGRFChQAAsLC33Jnw5ofpvI/+j59c579+6lRIkSzJs3j5iYGOPxihUr4unpyZEjRwgODn7p4yiQkozm559/pm/fvsycOZPg4GAOHz5Mt27d6Nq1K4GBgbi5uTFq1Chy5crF1q1befTokblLFkkTli9fbtyRcv78+URGRpI9e3Z69+6Np6cnBQsWZOnSpcb3lcWLF3Py5EkqVapk5spF0oaUQOrHH3/E39+fqlWr4uXlxerVq407JcNvn82CgoJwcnIiR44cCqREXpM/2lW5cuXKBAQEcOLECQYNGkRERAQWFhYkJydjaWlJ9uzZcXV1xcLCwtj0XN5sCqVE/kcpS/ZiYmKoX78+kydPJjY2lhMnThAXF2fs91GxYkVKlSrFoUOHzFmuiFl899133LlzJ9WxsLAwXFxcaNmyJc7OzuTIkQM/Pz969uxJnz59uHPnDsWLF8fb25sVK1aQNWtW8xQvkobEx8cbdxlycXFhzZo1LF68mCdPntC7d28GDRrE3r17GTduHBMnTqRv377Mnz+f1atXqymzCL8FUilNza9fv05ERAQA1apVIyAggEuXLlG/fn0uXrzIp59+Sq9evXj48KGZKxdJv55vg7Jq1SqmTp3KsGHDuH37NgBVq1Zly5Yt7Ny5kz59+hAZGfnS5XnqIZU+6G9R5B/w9/encuXKJCYm8umnnzJ+/Hi8vb1ZuXKlccZUVFQU9+7dI2fOnGauVsR0kpKSOH/+PH369CEuLi7VbeHh4Zw7dw5bW1sMBgOxsbEAjBgxAjs7O44ePQrAW2+9RZ48eUxeu0haZG1tTUBAAN27d+fhw4eEhYUxY8YMFi1aRFJSEt7e3vj5+bFt2zb27t1LbGwsBw4coFy5cuYuXSRNMBgM7N+/n48//hg/Pz8mTJhAkSJFgGe92apVq8amTZu4du0ajRs35ssvv2T16tV6HxJ5jVLCJE9PT0aNGsWhQ4c4ePAg1apVY+vWrTx9+pTq1auzbds29uzZQ9u2bYmOjjZz1fK6aK6byD+QN29eMmXKRGhoKFWqVMHLy4vExETc3d3ZunUrRYsW5ezZs1hZWeHh4WHuckVMxsLCgmLFihEWFoaDgwOnTp3C2dmZvHnz0qJFC0qUKEH//v357LPPjEsirKyssLW1xdra2szVi6Q9x44dw93dHV9fX5o0aYKzszO9evXiq6++AqB///4MHDiQLl264OTkRFxcHDY2NmauWiRtOXDgANWqVaN79+7ExMQQFBTEF198QVJSEs2bN6dr166cPXuWAwcOUKxYMQVSIq9RyuzFRYsWsXr1arZs2UK5cuXYu3cvDRs2pHfv3ixYsICmTZtSrVo11q5dy/Tp07VhRzqmmVIif2HTpk1s3rw51bGqVasSGxuLv7+/8djkyZOZNGkSGzdu5MSJE3Tu3Jljx45hbW1NQkKCqcsWMbnk5GSSkpJISkrCwcGBhw8fUqZMGUaNGsWvv/6Kk5MTvXv35uLFi7i7u3P//n2uX7/O0qVLiYuLo3jx4uZ+CiJpzrVr18iaNStNmzYlb9682Nra4u/vT4kSJfD29mbx4sVERETg5OQEoHBX5DkpLRUSEhK4c+cOy5cvp1OnTsybN4/79+/j4OBg3PnVxsaGunXrKpASeQ3GjRvHqlWrgGezFx8/fsyDBw+YOHEi5cqVY8OGDbRp0wZ/f3+qV6/OgAED2LFjB9HR0dSpU4ft27cbe0hJ+qNQSuRPLFq0iFatWuHq6kp8fLzxeNasWfH29mbr1q2EhIQYj3/66adMmjTJuITC0tKSxMRENeCTdC3lA0JsbCwWFhZYWFhw9uxZsmXLxrZt21i7di1jx44lMjKSjz/+2PiNdO7cuWnWrBlffPEF69evN24BLCK/DaZTQqYnT54AGGdCLVq0CIPBwMKFC1m+fLnx/toSW+Q3KdfDBx98QI4cOZgzZw7ZsmVj6NCh7Nq1i65du+Lo6Iijo6OZKxVJvy5dusSBAwdYtmwZgYGBADg5OdGgQQOaNm3K+fPnGT16NJMmTaJbt24MHjyY27dv065dO0JDQ1M9lnpIpU8aKYv8geXLlzNkyBDWr1/PgQMHGDx4ME2bNmX48OFYWFhQqVIlcuXKxbFjx6hevbpxG+GxY8fy9OlT+vbtS0xMDH369DH3UxF5rSwsLLh58ybdunVjxYoV/Pzzz3Tu3Jnvv/+eJk2asGnTJt59910AfHx86Nu3Lz169GD79u1kz56dggULKpASIfWW9Sm/1q5dm/j4eMaOHUtAQIBxad6DBw+oXLky+fPnp23btgqjRPjtGgoNDeXYsWMYDAaqVatGyZIlWbNmDVFRUeTNm9d4/127dmEwGMiUKZMZqxZJ39zc3JgxYwYzZszgs88+IyEhgQ4dOlC9enUANm7cSJYsWWjRogUAiYmJjB49GisrK+N9JH1TKCXyEqtXr6Z3797MnDmT999/n+DgYAoVKsSqVatYtmwZH3/8MT169KBLly5MmjSJ9u3bp2poPmXKFJ48ecLYsWP54IMP9A2cpHuXLl0iU6ZMNGzYkCtXrvDVV19Rrlw5EhISaNSoEdu2bePdd9/FYDAwadIk8uTJQ8uWLc1dtkiakTKY3r9/P7t37yZPnjxUqVKFChUqEBAQQIsWLWjfvj1jx47F0dGRlStXYmFhwezZs/UeI0LqXfY++eQT8uTJg729PZ6enqxfv55atWoZr5Vdu3axY8cOli1bxr59+8iePbuZqxdJnxISErCysqJSpUp8+OGHrFixgjlz5mBvb0/z5s2BZ7sznz9/nvDwcCwtLZk9ezZubm7MnTs31WNI+mVITpnvLSIALFmyhH79+lGuXDkePHjAmjVrqFKlCk+fPiUuLg5vb2+OHTtGSEgIHTp0YN26dUyfPp0+ffoYZ0ul0O57kpHMnTuXYcOG4erqyo4dOyhSpAgJCQkYDAYsLS3ZtWsXLVu2pHXr1vj6+pIrVy5zlyySpmzcuJFOnTpRtmxZwsPDyZw5M9OnT6dp06aEhITQqVMnkpKSSE5OJiEhgc2bN1OxYkVzly2SZvzwww+0a9eOadOm0bt3b44cOUKVKlWwtbUlMDCQpk2bEh4ejoeHB9euXWPu3LmULl3a3GWLpHtjx47lzJkzXL9+nRMnTlCmTBnGjBlDmzZtAKhVqxaHDx8mT548ZM2alcOHD6tHYgaiUErkOXPnzmX06NF8++23lCtXjqFDhxIcHMyWLVtSffCPiIhg586dLFu2jJ9++onSpUvz448/AqmXX4hkBCnfYK1fv57z589z5MgRrl27xpIlS6hQoQLx8fFYWFhgaWnJ9u3b6dKlCydOnFAzWZHn3L17l/nz51OoUCF69uxJSEgIS5cuZffu3SxevJhmzZoRGRnJsWPHSEhIoGjRolr2KhnevXv3uHbtGgCVKlXCy8uL5ORkJk6cyM2bN6lRowYNGjQgMTGRb7/9lu3bt1O3bl3Cw8NJTk7WDCkRE1i6dCnDhw9n69atFCtWjJMnTzJjxgyio6MZMmQIbdu2BeDbb7/F3t6ed999F0tLS82QykAUSonwLEiKjY2lbNmyeHl50alTJwBOnTqFl5cXwcHBbN26lfLly5OUlITBYDDuHHHy5Ek++OADpk2bRteuXc38TERM548C2B07drBgwQJu3brFsmXLKFeuHAA//vgj77zzDjExMdjZ2Zm4WpG06+eff6Zr165YW1uzePFiKlWqBMDJkyfx9fVl9+7dLFiwwNhvQ0TgzJkz9OnThyxZsmBnZ0dgYCChoaHExcVRqlQpGjVqRNmyZVmyZAnBwcHUrl0bgG3bttGkSRMzVy+ScQwYMICwsDA2btxoPBYcHMygQYNISkrCy8uL999/P9U5v199IumbokeR/2dra8vJkyexsbEhKSkJCwsLSpUqhZeXF15eXjRr1swYTCUkJGBpaYmTkxPly5enXLlyXLlyxdxPQcRkUgKpgwcPsnfvXiwtLSlevDjvv/++8cP+woUL6dWrFzNmzCA4OJgFCxZw4sQJcufObebqRdKW+/fvkz9/fn744QciIyONx0uXLs2wYcOwsrKiU6dOrF+/nkaNGpmxUpG04fTp09SqVYv+/fvTt29f8uXLB2Cc1X7o0CESExMZOnQo8GzX5Pbt21OwYEEKFChgtrpFMpKUz4o5c+bk9OnTREREGPu61axZE3d3dwYPHszo0aOxt7enYcOGxnMVSGUsCqVE+G2Xo5RdjSwsLIwvpM8HU82bN2fLli2pZkzZ29tjYWHB6dOnU82iEkmvnm8m26dPH6pUqUJiYiJffPEFFy5cYMSIETRp0gQrKysWL15Mp06dcHZ2ZsuWLQqkRF6iQYMG2NnZERsbS//+/fH396datWoAlCpViv79+5MpUyZcXV3NW6hIGhAeHo67uztdu3Zl6tSpxuMpXyjCs90pQ0NDSUhIACAgIICoqCi8vLzInDmzWeoWSe+evwbht/FVqVKlmDlzJhs2bKBz587G+zg5OVGrVi3q169P/fr1zVKzpA1avifyN506dYpJkyaxdu1azp07R9GiRQH46aef6NWrF6tWrTIuUxJJ70JCQmjXrh3jxo3D3d2d0NBQGjZsSFRUFCNHjjQOFMLDw/n111/Jli2bekiJkHrL+rCwMG7cuEGnTp3Inj07R44cYcqUKVy/fp3FixdTpUoV43lxcXHGL05EMrIzZ87QsmVLvvjiC2rVqpVqEAwYNwLo2LEjGzZsoFKlSpw9e5agoCDKli1rpqpF0rfnWzp8/fXXPHz4EDs7O3r27AnAiBEj8PPzw9fXlxo1apAvXz569OhBhQoVmDhxIgaDQUv2MjCFUpJh/T7N/zuOHz/O2rVrmThxovFFMzIykqdPn2qXPckQkpOTSU5OxtfXl6tXrzJ//nyuX79OnTp1eOeddyhcuDBTpkxh2rRpjBgxwtzliqRJ69ato1+/fpQvX55Lly7h5OREr169GDBgAPv27cPPz4+bN2/i4+NDzZo1zV2uSJry9ddf061bN+Li4jAYDC/9PBcdHc33339PfHw8V65c4b333qNIkSJmqlgkfXs+kPLw8GDFihXkyZOHyMhI3Nzc2L17NwDjxo1jxYoVxMXF4eDggK2tLcePH8fa2lobRWVwCqUkw9m4caOxmd4/CaZSpPSV0guoZAQpHxZSZms8evSIM2fOULFiRRo3boybmxvLly/n3Llz1KpVi/DwcCZOnMi4cePMXbpImnL06FGaNWuGt7c33bt359q1axQqVIgZM2YYg9ygoCDGjx9PUlIS27dvJ1OmTHqvEfl/Bw4coEGDBqxatcq4a9fvLVy4kA0bNrBz504TVyeScT148IBevXoxZcoU8ubNy9GjR+nbty85c+bk4MGDAISGhhIZGUlERATNmzfXLnsCwD8bjYu8oZYuXcqwYcOYPXs28Kx3VFJS0j96LCsrKw0SJENICaR++OEHZs+ezZUrV8iaNSs1atTg0qVLPH78mE8++QQABwcHGjRowIIFC/jggw/MXLmI+fzRe8vly5d5++236d69O+fPn6devXr06tXLGEjdvXuXWrVqMWnSJFatWoWtra3ea0SeU7BgQRwdHfnyyy+5du2a8fjz37NfvnyZChUqoO/eRUxjwYIF1KlTh+TkZFxcXHB2dqZ+/fqsWLGCe/fuGfskVqxYkbp169KyZUssLS1JTExUICUKpSRjadq0Kc2aNSMwMJBZs2YBfy+Y0ocaychSmpq/9957xMbGEh4enuq2CxcucODAAQAWLVrEvXv3+OCDD7RUQjKslFm4YWFhrF69mqVLl3L9+nUAbt68SZYsWUhMTKRRo0Y0atSIJUuWALBp0yaWLFlCbGwstWrVIn/+/OZ8GiJpUr58+Vi0aBE7duxg3LhxnDlzBnj2fhQdHc2YMWNYt24dPXv2VKArYgIJCQk4OjqSlJTEyZMncXJyAp6NsWrWrMnKlSsJDw9/6edC9ZAS0PI9yUBSZnvcunWLadOmceTIEdq2bWv8dvqPlvI9v8b59u3batYsGc7Jkydp0qQJEyZMoG/fvqlui4qKYsqUKcyfP58CBQpw584d9u7dq6b/kmGlvJecPn2ajz76iNKlS5M3b15mzJgBwIULF3jnnXe4d+8eAwcOZN68ecZzBw8ezPXr11m5cqVx22wReVFSUhJLly5l4MCBuLm5Ub16dWxtbbl58yYHDx5k+/btlC9f3txliqRLL+v/FBkZyfbt2xkwYAC1atUiMDDQeFtSUhLff/89S5Ys4ZtvvlEQJS9QKCUZSspg4ebNm0ybNo3Q0NA/Daaef9GdN28e8+bN49ChQ+TIkcMs9YuYQ0BAALNmzWLPnj1kzZoVSH2tPH78mNDQUK5evUq9evUoVKiQGasVMZ+U94zTp09Tu3ZtBgwYwIgRI4wB08aNG4mLi+PWrVvMnTuXvn374unpyZUrV1i6dClLlixh//79vP3222Z+JiJvhkOHDjFr1iwuXbpElixZqFGjBr169dJMXZHX5PnPf2FhYdjZ2WFlZYWTkxNRUVFs3boVDw8PqlWrxnfffWc87/kxlXbZk99TKCXp3h/NgLpx4wbe3t4cOXKEdu3avRBMPf/iuWTJEsaMGcNnn31Gp06dTFq/iLmkXAOff/45s2fP5qeffiJbtmypro0ffviBwoUL4+LiYuZqRdKG8PBwWrduTZkyZZg/f77x+IwZMxg9ejTvvvsujRo1Iioqijlz5mBnZ0eOHDmIi4vjm2++0ewOkf+RBrgipvH8mGratGmsX7+emJgYsmbNyrJlyyhevLgxmBo5ciTVqlUjICDAzFXLm0A9pSRde/7FMyAggGnTpjFx4kSOHTuGi4sL48aNo3LlyqxduzZV8/OEhIRUgdTIkSP5/PPPFUhJhpJyDbi5uXHp0iU2b96c6jg829o+MDCQxMRE9V4TAe7cucPNmzdp06aNsV/h4sWLGTduHH5+fsTHxxMUFETRokU5efIks2bN4rPPPmPv3r0KpET+gd/PcBeR1yPlWhs7dizz5s3Dw8MDPz8/EhMTqVu3LocPH8bBwYFmzZoxa9Ys1q9fr12Y5W/RTCnJEDw8PFi9ejVFihQhJiaG0NBQ/Pz8GDhwoLHH1LFjx2jYsCETJ040nvf5558zcuRIli9f/ofbDoukFykzoC5cuMC9e/ewsrKifPny2NjYMGLECObPn8/ChQtp3LgxlpaWzJs3j2XLlhESEqKlEiL/b9WqVXTv3p34+HhjgBsWFsaVK1eoXbs2J0+eZOjQoTx69Ii1a9fi6upq3oJFRET+pn379jFy5EjmzJlD7dq1+e9//0vXrl3Jly8f169fZ8+ePVSuXJnIyEgOHz5MnTp1NJNR/pL2X5R0b/PmzXz55Zfs2LGD0qVLY2Vlhbe3N0OGDMHR0ZGuXbsyatQoRo8eze3bt40D8zVr1uDu7s7atWtp06aNuZ+GyGuV8u9+3bp1DB8+3Lgcws7Ojo0bN+Lt7Y29vT39+vUjd+7cODo6EhkZya5duxRIiTzH1dUVKysr1q9fT5s2bUhOTiZ//vzkz5+fpKQkSpcuTceOHVm6dCm2trbmLldERORvSU5OJkeOHLRo0YLatWuzY8cOPv74Y6ZOncp7771HgwYNaNWqFd999x01a9akfv36gJbYyl/TTClJ91asWMHChQsJCgrC0tLS+KL46aefsmTJEuNSvvv37+Ps7Gycmnrx4kWuXbtGw4YNzVm+iMmEhITQuHFjfH19qVWrFg8fPmTChAmcPn2aH3/8kbfeeotDhw5x584dLCwsKFeuHPny5TN32SJpSlhYGBUrVqRatWr4+flRsGDBF+7j4eHB9evXWb58OVmyZDFDlSIiIn8uODiYypUrY2Njw/Tp0ylevDitW7fm/v37ZM+enffff5/ixYszc+ZM4uPjadWqFT/99BNly5Zlz5495i5f3iCaKSXpXlJSEqdOneLJkydky5aNuLg4bGxs6NChAytXruTWrVu4uLgYd9RL6UNVpEgRzQCRDOXEiRNUrVqVHj16GMPbdevW0bp1a9q2bcvhw4epUqWKmasUSdvy58/PwoUL+fDDDxk3bhyenp7G3fQiIiKYMmUKX3zxBfv371cgJSIiadIvv/zCgAEDcHNzI0+ePCxatIiff/4ZgBw5cnDv3j1Onz5Nx44dAXj69CmZM2fmv//9L9WqVTNn6fIGUigl6cYf7bLXokULlixZQv/+/Zk3bx7/+c9/AMicOTN2dnYvNMV82WOIZAR37tzh1KlTxkAqISGBLFmyMHLkSNzd3bl48aK2qhf5G1q1amXsW3j48GFq1KiBtbU1N2/e5MiRI+zZs4eSJUuau0wREZGXyp8/P56engwaNIgnT54QHBxMyZIliY+Px9rampw5c1KmTBk8PT159OgRAQEBxMfHU6VKFQwGwx+Oy0ReRv9SJF14/oXvu+++Y+bMmfj6+nL48GFy5szJkCFDuHHjBl26dOHgwYP8+OOPDB06lJw5c2rmh2QYKTuBPX369KW3t2zZEmdnZ2bNmkV8fDxWVs++t8iePTtJSUkkJCSYrFaRN5mlpSV9+/YlKCiIt99+m9DQUE6fPk2pUqXYv3+/dtkTEZE06cSJE5w7dw4bGxv+85//YGdnh6urK76+vkRFRWFtbU18fDwAkydPpnr16vj7+5MjRw7279+PpaWlAin5n6mnlKQrI0aMwN/fn0qVKnH8+HFy585N27ZtGTduHJs2bWL+/Pl8//33lChRghw5crBz506sra3VgE8yjJs3bzJ06FD69etHvXr1gN+anEdGRjJy5EjOnz9P48aN8fT0JCoqCm9vbwIDA9m3b59xpqGI/D16fxERkTfBN998w+zZsylSpAifffYZycnJJCQksG/fPnx9fSlQoAArV67E3t7eeE5CQgLR0dFkyZIFg8FAQkKC8UtNkb9LoZSkG5s3b6Zv374EBgZStWpVHj9+zNy5c9m0aROdOnXCw8MDgFOnTuHo6Ej+/PmxsLDQi6dkKL/88gudO3fG2dmZ0aNHU7NmTeC3gfPdu3fx8vLi+++/JywsjFKlSnHhwgV2796t2R0i/0BK6Pv734uIiKQV/v7+DB48GB8fH6pVq0apUqWMt8XGxrJ69WoWLVpE4cKFWbFiBXZ2dvTv35/33nuPZs2aAXqPk39OoZSkGwsWLGDJkiUcOnTIuM32vXv3mDx5MseOHWPbtm04ODikesHU9FLJiC5evMigQYNITk5m3LhxxmAqpU9AVFQUMTExzJs3j1q1alGsWDEKFSpk5qpFRERE5FULCQmhffv2+Pj40KFDh1S3RUdHkzlzZhISEggICGDu3LnExMSQN29ezpw5w7Vr1/TlvvxrGo3LGy+lT07WrFlJTEzk9u3bwLO0PmfOnPTs2ZPg4GBOnjwJkCrBVyAlGVGRIkXw8/PDYDAwefJkgoODAYxLWW1sbPDx8eHixYvUqVNHgZSIiIhIOnX+/HlKlixJ69atjcd27tzJqFGjqFy5MkOHDuX8+fN89NFHzJgxg8aNG1OsWDFjIJWYmGjG6iU90Ihc3ihJSUnGECpFSrBUvnx5wsLC8PPz48mTJ8bwycbGhtKlS+Pg4GDyekXSqj8KphITExk+fDgzZ85k9OjR2NnZmblSEREREXnVTp8+TXh4OFFRUZw+fZobN24AMGzYMKZMmcLevXupX78+/v7+TJ48GYPBQIMGDfD19eWzzz7DysqKhIQE9U2Uf03L9+SNERERgaOjo/HnJUuWcOHCBRwcHOjVqxcFChQgMDCQDh060LNnT5o1a0bBggUZPXo0jx494sCBA5oZJfI7zy/l8/T0ZNu2bcyfP5/g4GD1kBIRERFJZ5KTkwkLC6NVq1bGBuZdu3bl6tWr2NjYkJCQgKenJ++++y4FCxZk48aNtG7dmuPHj1OmTBlzly/pkEIpeSOMHTuWxYsXc/bsWXLmzMnIkSNZsWIFZcuW5e7du4SHh7N7926KFSvGtm3bGDlyJA8fPiRLlizkypWLXbt2YW1trR5SIi9x8eJFhg0bRnBwME+ePCEkJIQKFSqYuywREREReU0GDBjAwYMH+emnnwgNDeXIkSM8ePCATz75hKxZs2IwGEhOTmbbtm1MnDiRdevWkT9/fnOXLemQQil5I+zbt48JEybw4MEDNm3ahI+PD7169aJ8+fKcPn2akSNHcuDAAUJCQihevDi//vor0dHRREdH8/bbb2uXPZG/cP78eUaOHMm0adMoWbKkucsRERERkdcg5Uv6Bw8e0LNnT1q3bk337t1fet/Y2Fg6dOiAtbU1a9as0e568loolJI3RkhICCNHjuTatWvkyZOHtWvX4uLiAsClS5cYPHgwISEhhISEUKxYsVTnaoaUyF9L2X1PRERERNK3xMRExo8fz+nTp9mwYQOA8Uv8J0+ecPz4caZOncqNGzc4duwYVlZWGlPJa6F/UZKmPd/UvHr16syaNYvSpUtz8uRJUvLU5ORk3Nzc8PPzo1atWpQoUYKwsLBUj6MXT5G/pkBKREREJP15ftyU8qulpSWenp4cPXqUadOmAWBlZUVMTAzTp0/Hy8sLa2trjh49amxqrjGVvA6aKSVp1vNJ/L59+8ibNy9Fixbl4MGDDB48mIcPHxIcHEzOnDlJTk7GYDBw/vx5li1bxvTp07VUT0REREREMrTnx1SPHj3CxsYGW1tb47FvvvmGr7/+mpkzZ1KiRAkA9u/fT2xsLPXr11cbFHntFHVKmpScnGx8ofT09KRfv34cOHCAqKgoqlatyty5c8mVKxd169bl7t27xkZ8xYoVY9asWcY0X0REREREJCN6PpCaNWsWbdu2pX79+jRr1oybN28CUKFCBSIjIwkJCTGeV7t2bRo2bIiFhQVJSUkKpOS10kwpSdNmzZrF7NmzWbNmDRUrVsTe3t5424EDB/D09OTRo0fs3LmT3Llzm7FSERERERGRtOfTTz9l6dKlzJw5E1dXVzp37kyOHDnYu3cvzs7OLF++nFGjRnHw4EHc3NzMXa5kMJopJWlKbGys8feRkZFs3bqVMWPG8M477xgDqcTERABq1KjB7NmziY2NxcPDwyz1ioiIiIiIpFXXrl1jx44drFq1iu7duxMVFUVUVBR9+/bF2dkZgF69etGyZUtWrlyZajwmYgoKpSTN2LlzJ35+fhw6dAh4tvvDL7/8Qs6cOYHfwihLS0uePn3KpUuXqFKlCuvXr2flypVmq1tERERERCQtCg8PJywsjMaNG7N161Y6derEjBkz6NevH1FRUSxYsICkpCSqVavGvn37iIiIMHfJksEolJI0wd/fn549e3LlyhXjuuds2bKRPXt24xallpaWxt34zp8/z6pVq7h37x5vv/02lpaWxtBKREREREQko3lZZ55ixYpRtmxZPDw86NixIz4+PvTt2xd4Notqw4YNHD16lD59+lC3bl2uXbtm6rIlg1NPKTG7gIAAevXqhb+/P02bNsXR0dG4m963337Lp59+SvPmzZk3bx7JycnExsbSunVrrKys2LRpEwaDwdxPQURERERExGyeb2ru7e1NyZIladGiBVFRUfTr1481a9bQp08f/Pz8AIiJiaFdu3YYDAYCAwOxsbExjsFETEmhlJjVvXv36NChA+3atWPAgAHG41FRUVy+fJkbN25w4cIF/P39sbKyokCBAty5c4fo6GhCQ0OxtrbWi6eIiIiIiGRYzwdSFy9epH///vz4449s27aN+vXrc+PGDTp27EhSUhJlypTB1dWVHTt28PDhQ+OYKjExEUtLSwCNr8SktHxPzO7u3bvky5fP+POiRYvo0aMH5cuXZ9iwYaxevZoVK1ZQr149XFxcaN68OUePHsXa2pqEhAS9YIqIiIiISIaVEkiNHj2abt26YWtri729Pc2aNWPLli24uLjw9ddf06hRI86ePcvhw4cpX758qjFVSiAFaHwlJmVl7gJEIiIi2LJlC46OjixcuJALFy5Qq1Yttm/fzuPHjxk9ejT79+/Hx8cn1XmJiYlYWemfsIiIiIiIZGxfffUVfn5+7Nmzh5IlS3L16lXmzJlD69atWb9+Pc2bN2fixIkYDIZUoZPGVGJu+tcnZpUzZ05WrFhB27Zt2bt3L1myZGHu3LmULVuW7Nmz8/DhQ6ZNm8aDBw9eOPf5NF9ERERERCSjunLlCrVr16ZatWoAlC5dGm9vb548eUK7du3Ytm0bdevWJSkpKVUopTGVmJuW74nZNWjQgIsXL7J7926OHz9O/fr1yZ49u/F2R0dHXFxczFihiIiIiIhI2pCyI3nKrwD29vaEhoby+PFj4FlfqNy5c9OxY0diY2Np2rQpP/zwAxYWFi/dpU/EXBRKSZqQM2dOChUqlOrYvXv36NKlC7GxsfTq1ctMlYmIiIiIiKQNAQEBfPzxx1y4cIGYmBjj8Xr16uHq6srkyZO5c+eOcTZU/vz56dOnD927d6dnz56EhYWpZ5SkKdp9T9Kc+/fvs2zZMoKCgrh79y7BwcEv7AghIiIiIiKSkURERFChQgUiIiLInTs3VapUoVatWnTv3h0AX19fAgICKFWqFIMHDyZTpkwMHz6cXLly0bVrVzp27Mjq1atp0KCBeZ+IyHPUU0rSnLCwMIKDg3Fzc2PDhg1YWVmRkJCgBnwiIiIiIpJh2dvb06FDBwoWLEjlypXZu3cvQ4cOZfv27dSoUYNBgwaRnJzM999/T7ly5Xjrrbews7Nj8+bN3LlzB0dHR6ytrc39NERS0UwpSZMePXqEk5MTBoNBM6RERERERESAbdu20bFjR4KCgihTpgxPnz5l2rRpTJkyhRo1avD+++9Tu3ZtrKyssLKyokyZMlhYWODh4cGOHTvYtWsXuXPnNvfTEDFSKCVpWnJystY8i4iIiIiI/L8BAwYAsGDBAgBKlixJ0aJFKVSoEKdPn2bXrl34+/vTrVs3fvzxRwICAggICGDv3r2UK1fOjJWLvEjroSRNUyAlIiIiIiLymwoVKuDv78/Dhw9p0KAB2bJlY+XKlTg6OnLz5k32799Pu3btALC1tcXS0pLg4GBKlChh5spFXqSZUiIiIiIiIiJvkCpVqnDkyBHeeecdAgMDcXZ2fuE+KX154+LisLGxMUOVIn/NwtwFiIiIiIiIiMhfS5lTMmjQIEqWLMmcOXNwdnbmZXNNUjaKUiAlaZlCKREREREREZE3QEp7k3r16vHgwQN27dqV6rjIm0ahlIiIiIiIiMgbJF++fIwePZrZs2dz5swZc5cj8o+p0bmIiIiIiIjIG6ZZs2YcOXKE4sWLm7sUkX9Mjc5FRERERERE3kDJyckYDAYSExOxtLQ0dzki/zOFUiIiIiIiIiIiYnLqKSUiIiIiIiIiIianUEpERERERERERExOoZSIiIiIiIiIiJicQikRERERERERETE5hVIiIiIiIiIiImJyCqVERERERERERMTkFEqJiIiIZAD79u3DYDDw6NEjc5ciIiIiAiiUEhEREXnBr7/+yieffELhwoXJlCkTLi4utGjRgj179vyt81esWEHWrFlfb5H/oxo1anD79m2cnJzMXYqIiIgIAFbmLkBEREQkLbl69So1a9Yka9aszJo1i9KlSxMfH8+OHTsYMGAA586dM3eJ/7P4+HhsbGzInTu3uUsRERERMdJMKREREZHn9O/fH4PBwKFDh2jbti1FixalZMmSDBs2jIMHDwLg4+ND6dKlsbe3x8XFhf79+xMVFQU8WybXo0cPHj9+jMFgwGAw4OXlBUBsbCweHh7ky5cPe3t7qlatyr59+1L9/5cuXYqLiwuZM2emdevW+Pj4vDDratGiRbz11lvY2NhQrFgxvvrqq1S3GwwGFi1aRMuWLbG3t2fq1KkvXb4XFBRE7dq1sbOzw8XFhUGDBvHkyRPj7QsXLqRIkSLY2tqSK1cu2rVr92r+kEVERERQKCUiIiJiFB4ezvbt2xkwYAD29vYv3J4SDllYWODn58fp06dZuXIle/fuZeTIkcCzZXJz587F0dGR27dvc/v2bTw8PAAYOHAgISEhBAQEcOLECdq3b0/Tpk25ePEiAMHBwbi7uzN48GCOHz9Oo0aNmDp1aqoa1q9fz+DBgxk+fDinTp2ib9++9OjRg++//z7V/by8vGjdujUnT56kZ8+eLzyXy5cv07RpU9q2bcuJEyf49ttvCQoKYuDAgQAcOXKEQYMGMWnSJM6fP8/27dt55513/t0fsIiIiMhzDMnJycnmLkJEREQkLTh06BBVq1YlMDCQ1q1b/+3z1q5di7u7O/fv3wee9ZQaMmRIqllJ169fp3Dhwly/fp28efMajzds2JAqVaowbdo0PvjgA6Kioti8ebPx9s6dO7N582bjY9WsWZOSJUvy+eefG+/ToUMHnjx5wpYtW4BnM6WGDBmCr6+v8T779u2jXr16PHz4kKxZs/Lxxx9jaWnJkiVLjPcJCgqiTp06PHnyhK1bt9KjRw/CwsLIkiXL3/6zEBEREfm7NFNKRERE5P/93e/qdu/eTYMGDciXLx9ZsmShS5cuPHjwgOjo6D885+TJkyQmJlK0aFEcHByM//3www9cvnwZgPPnz1OlSpVU5/3+57Nnz1KzZs1Ux2rWrMnZs2dTHatUqdKfPoeff/6ZFStWpKqlSZMmJCUlceXKFRo1akTBggUpXLgwXbp0YfXq1X/6/ERERET+V2p0LiIiIvL/ihQpgsFg+NNm5levXuW9996jX79+TJ06FWdnZ4KCgujVqxdxcXFkzpz5pedFRUVhaWlJaGgolpaWqW5zcHB4pc8DeOnyw9/X07dvXwYNGvTCbQUKFMDGxoajR4+yb98+du7cyfjx4/Hy8uLw4cNpbmdBEREReTNpppSIiIjI/3N2dqZJkyYsWLAgVcPvFI8ePSI0NJSkpCTmzJlDtWrVKFq0KLdu3Up1PxsbGxITE1MdK1++PImJidy9exc3N7dU/6XsilesWDEOHz6c6rzf/1yiRAmCg4NTHQsODubtt9/+n55rhQoVOHPmzAu1uLm5YWNjA4CVlRUNGzZk5syZnDhxgqtXr7J3797/6f8jIiIi8kcUSomIiIg8Z8GCBSQmJlKlShXWrVvHxYsXOXv2LH5+flSvXh03Nzfi4+OZP38+v/zyC1999RWLFy9O9Riurq5ERUWxZ88e7t+/T3R0NEWLFuWjjz6ia9euBAYGcuXKFQ4dOsT06dONvaA++eQTtm7dio+PDxcvXmTJkiVs27YNg8FgfOwRI0awYsUKFi1axMWLF/Hx8SEwMNDYTP3vGjVqFAcOHGDgwIEcP36cixcvsnHjRmOj882bN+Pn58fx48e5du0aX375JUlJSRQrVuxf/gmLiIiIPKNQSkREROQ5hQsX5ujRo9SrV4/hw4dTqlQpGjVqxJ49e1i0aBFly5bFx8eHGTNmUKpUKVavXs306dNTPUaNGjVwd3enY8eO5MyZk5kzZwLg7+9P165dGT58OMWKFaNVq1YcPnyYAgUKAM96Qy1evBgfHx/Kli3L9u3bGTp0KLa2tsbHbtWqFfPmzWP27NmULFmSJUuW4O/vT926df+n51mmTBl++OEHLly4QO3atSlfvjzjx483NmHPmjUrgYGB1K9fnxIlSrB48WK++eYbSpYs+S/+dEVERER+o933RERERNKw3r17c+7cOfbv32/uUkREREReKTU6FxEREUlDZs+eTaNGjbC3t2fbtm2sXLmShQsXmrssERERkVdOM6VERERE0pAOHTqwb98+IiMjKVy4MJ988gnu7u7mLktERETklVMoJSIiIiIiIiIiJqdG5yIiIiIiIiIiYnIKpURERERERERExOQUSomIiIiIiIiIiMkplBIREREREREREZNTKCUiIiIiIiIiIianUEpERERERERERExOoZSIiIiIiIiIiJicQikRERERERERETE5hVIiIiIiIiIiImJy/weJMK6g95DL/AAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import pandas as pd\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.metrics import accuracy_score\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "data = pd.read_csv('SIH-Dataset.csv')\n",
        "\n",
        "data = data.drop(columns=[\"Dropout_Reason\"], axis=1)\n",
        "data.head()\n",
        "\n",
        "# Encode the target variable 'Dropout_Status' to 0 or 1\n",
        "le = LabelEncoder()\n",
        "data['Dropout_Status'] = le.fit_transform(data['Dropout_Status'])\n",
        "\n",
        "# Select categorical columns (all columns except 'Dropout_Status')\n",
        "categorical_cols = data.columns.drop('Dropout_Status')\n",
        "categorical_cols\n",
        "\n",
        "# Apply one-hot encoding to categorical columns\n",
        "data = pd.get_dummies(data, columns=categorical_cols, drop_first=True)\n",
        "\n",
        "X = data.drop('Dropout_Status', axis=1)\n",
        "y = data['Dropout_Status']\n",
        "\n",
        "# Split the data into training and testing sets (80% training, 20% testing)\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
        "\n",
        "# Build and train a Random Forest Classifier\n",
        "model = RandomForestClassifier(random_state=42)\n",
        "model.fit(X_train, y_train)\n",
        "\n",
        "# Make predictions on the testing data\n",
        "y_pred = model.predict(X_test)\n",
        "\n",
        "# Calculate accuracy\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "print(f'Accuracy: {accuracy * 100:.2f}%')\n",
        "# Input student details to calculate dropout probability\n",
        "print(\"\\nEnter Student details to calculate dropout probability:\")\n",
        "school_type= input(\"School Type: \")\n",
        "location = input(\"Location: \")\n",
        "gender = input(\"Gender: \")\n",
        "caste = input(\"Caste: \")\n",
        "age = int(input(\"Age: \"))\n",
        "standard = input(\"Standard: \")\n",
        "socioeconomic_status = input(\"Socioeconomic Status: \")\n",
        "\n",
        "# Create a DataFrame for the input data with all categorical columns\n",
        "input_data = pd.DataFrame({'School_Type':[school_type],'Location': [location], 'Gender': [gender],\n",
        "                           'Caste': [caste], 'Age': [age], 'Standard': [standard],\n",
        "                           'Socioeconomic_Status': [socioeconomic_status]})\n",
        "\n",
        "# Apply one-hot encoding to the input data\n",
        "input_data = pd.get_dummies(input_data, columns=['School_Type','Location', 'Gender', 'Caste', 'Age','Standard', 'Socioeconomic_Status'], drop_first=True)\n",
        "\n",
        "# Ensure that input data columns match the model's columns in the correct order\n",
        "missing_columns = list(set(X.columns) - set(input_data.columns))\n",
        "input_data = input_data.reindex(columns=X.columns, fill_value=0)\n",
        "\n",
        "# Predict dropout probability\n",
        "dropout_probability = model.predict_proba(input_data)[0][1] * 100\n",
        "\n",
        "print(f\"Estimated dropout probability: {dropout_probability:.2f}%\")\n",
        "\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "# Load the dataset\n",
        "dataset_path = \"SIH-Dataset.csv\"\n",
        "data = pd.read_csv(dataset_path)\n",
        "\n",
        "# Filter the dataset to consider only \"Dropout\" in the \"Dropout_Status\" column\n",
        "dropout_data = data[data['Dropout_Status'] == 'Dropout']\n",
        "\n",
        "# Calculate dropout percentages based on Dropout_Status\n",
        "dropout_percentage = (len(dropout_data) / len(data)) * 100\n",
        "\n",
        "# School-wise dropout analysis\n",
        "school_dropout = dropout_data.groupby('School_Type')['Dropout_Status'].count() / data.groupby('School_Type')['Dropout_Status'].count() * 100\n",
        "school_dropout.plot(kind='bar', figsize=(10, 5))\n",
        "plt.title('School-wise Dropout Rates')\n",
        "plt.xlabel('School Type')\n",
        "plt.ylabel('Percentage of Dropout')\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()\n",
        "\n",
        "# Location-wise dropout analysis\n",
        "location_dropout = dropout_data.groupby('Location')['Dropout_Status'].count() / data.groupby('Location')['Dropout_Status'].count() * 100\n",
        "location_dropout.plot(kind='bar', figsize=(10, 5))\n",
        "plt.title('Location-wise Dropout Rates')\n",
        "plt.xlabel('Location')\n",
        "plt.ylabel('Percentage of Dropout')\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()\n",
        "\n",
        "# Gender-wise dropout analysis\n",
        "gender_dropout = dropout_data.groupby('Gender')['Dropout_Status'].count() / data.groupby('Gender')['Dropout_Status'].count() * 100\n",
        "gender_dropout.plot(kind='bar', figsize=(10, 5))\n",
        "plt.title('Gender-wise Dropout Rates')\n",
        "plt.xlabel('Gender')\n",
        "plt.ylabel('Percentage of Dropout')\n",
        "plt.xticks(rotation=0)\n",
        "plt.show()\n",
        "\n",
        "# Caste-wise dropout analysis\n",
        "caste_dropout = dropout_data.groupby('Caste')['Dropout_Status'].count() / data.groupby('Caste')['Dropout_Status'].count() * 100\n",
        "caste_dropout.plot(kind='bar', figsize=(10, 5))\n",
        "plt.title('Caste-wise Dropout Rates')\n",
        "plt.xlabel('Caste')\n",
        "plt.ylabel('Percentage of Dropout')\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()\n",
        "\n",
        "# Standard-wise dropout analysis\n",
        "standard_dropout = dropout_data.groupby('Standard')['Dropout_Status'].count() / data.groupby('Standard')['Dropout_Status'].count() * 100\n",
        "standard_dropout.plot(kind='bar', figsize=(12, 6))\n",
        "plt.title('Standard-wise Dropout Rates')\n",
        "plt.xlabel('Standard')\n",
        "plt.ylabel('Percentage of Dropout')\n",
        "plt.xticks(rotation=90)\n",
        "plt.show()\n",
        "\n",
        "# Age-wise dropout analysis (Histogram)\n",
        "plt.figure(figsize=(10, 5))\n",
        "sns.histplot(data=dropout_data, x='Age', bins=20)\n",
        "plt.title('Age-wise Dropout Rates')\n",
        "plt.xlabel('Age')\n",
        "plt.ylabel('Count')\n",
        "plt.show()\n",
        "\n",
        "\n",
        "# Load the dataset\n",
        "dataset_path = \"SIH-Dataset.csv\"\n",
        "data = pd.read_csv(dataset_path)\n",
        "\n",
        "# Filter the dataset to consider only \"Dropout\" in the \"Dropout_Status\" column\n",
        "dropout_data = data[data['Dropout_Status'] == 'Dropout']\n",
        "\n",
        "# Calculate dropout percentages based on Dropout_Status\n",
        "dropout_percentage = (len(dropout_data) / len(data)) * 100\n",
        "\n",
        "# Calculate dropout rates for all categories\n",
        "dropout_rates = []\n",
        "\n",
        "# School-wise dropout rate\n",
        "school_dropout_rate = dropout_data.groupby('School_Type')['Dropout_Status'].count() / data.groupby('School_Type')['Dropout_Status'].count() * 100\n",
        "dropout_rates.append(school_dropout_rate)\n",
        "\n",
        "# Location-wise dropout rate\n",
        "location_dropout_rate = dropout_data.groupby('Location')['Dropout_Status'].count() / data.groupby('Location')['Dropout_Status'].count() * 100\n",
        "dropout_rates.append(location_dropout_rate)\n",
        "\n",
        "# Gender-wise dropout rate\n",
        "gender_dropout_rate = dropout_data.groupby('Gender')['Dropout_Status'].count() / data.groupby('Gender')['Dropout_Status'].count() * 100\n",
        "dropout_rates.append(gender_dropout_rate)\n",
        "\n",
        "# Caste-wise dropout rate\n",
        "caste_dropout_rate = dropout_data.groupby('Caste')['Dropout_Status'].count() / data.groupby('Caste')['Dropout_Status'].count() * 100\n",
        "dropout_rates.append(caste_dropout_rate)\n",
        "\n",
        "# Age/standard-wise dropout rate\n",
        "age_standard_dropout_rate = dropout_data.groupby(['Age', 'Standard'])['Dropout_Status'].count() / data.groupby(['Age', 'Standard'])['Dropout_Status'].count() * 100\n",
        "dropout_rates.append(age_standard_dropout_rate.unstack())\n",
        "\n",
        "# Create a bar graph for all columns\n",
        "plt.figure(figsize=(12, 6))\n",
        "for i, category in enumerate(['School_Type', 'Location', 'Gender', 'Caste', 'Age/Standard']):\n",
        "    plt.bar(category, dropout_rates[i].mean(), label=f'{category} Dropout Rate')\n",
        "\n",
        "plt.xlabel('Categories')\n",
        "plt.ylabel('Percentage of Dropout')\n",
        "plt.title('Overall Dropout Rates for Different Categories')\n",
        "plt.legend()\n",
        "plt.xticks(rotation=45)\n",
        "plt.tight_layout()\n",
        "plt.show()\n",
        "\n",
        "# Pie chart for overall dropout percentage\n",
        "plt.figure(figsize=(6, 6))\n",
        "labels = ['Dropout', 'Enrolled']\n",
        "sizes = [dropout_percentage, 100 - dropout_percentage]\n",
        "plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=140)\n",
        "plt.title('Overall Dropout Percentage')\n",
        "plt.show()\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Get feature importances\n",
        "feature_importances = model.feature_importances_\n",
        "\n",
        "# Create a DataFrame to associate feature names with their importance scores\n",
        "feature_importance_df = pd.DataFrame({'Feature': X.columns, 'Importance': feature_importances})\n",
        "\n",
        "# Sort features by importance\n",
        "feature_importance_df = feature_importance_df.sort_values(by='Importance', ascending=False)\n",
        "\n",
        "# Select the top N most important features\n",
        "top_features = feature_importance_df.head()['Feature'].tolist()\n",
        "\n",
        "# Use only the top features for training and testing\n",
        "X_train_selected = X_train[top_features]\n",
        "X_test_selected = X_test[top_features]\n",
        "top_features\n",
        "X_train_selected\n"
      ],
      "metadata": {
        "id": "oHidiiuFpaze",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "outputId": "11b90896-f039-43e2-cac6-2c1d546cf1f0"
      },
      "execution_count": null,
      "outputs": [
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              "      const quickchartButtonEl =\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "pSiUd6hVAnD3"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}