02c_regression_summary.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import ast\n",
    "\n",
    "from collections import Counter\n",
    "import itertools\n",
    "\n",
    "plt.style.use('ggplot')\n",
    "cycle_colors = plt.rcParams['axes.prop_cycle'].by_key()['color']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('regression_models_summary.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ***Best pipelines*** ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['pipeline_name','score_rmsle']].groupby('pipeline_name').agg('mean').sort_values('score_rmsle', ascending= False).plot(kind='barh');\n",
    "plt.title('Mean RMSLE across pipelines');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['pipeline_name','score_mae']].groupby('pipeline_name').agg('mean').sort_values('score_mae', ascending= False).plot(kind='barh');\n",
    "plt.title('Mean MAE across pipelines');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['pipeline_name','score_mse']].groupby('pipeline_name').agg('mean').sort_values('score_mse', ascending= False).plot(kind='barh');\n",
    "plt.title('Mean MSE across pipelines');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['pipeline_name','score_rmse']].groupby('pipeline_name').agg('mean').sort_values('score_rmse', ascending= False).plot(kind='barh');\n",
    "plt.title('Mean RMSE across pipelines');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['pipeline_name','score_r2']].groupby('pipeline_name').agg('mean').sort_values('score_r2', ascending= True).plot(kind='barh');\n",
    "plt.title('Mean R2 error across pipelines');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ***Best models*** ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['model','score_rmsle']].groupby('model').agg('mean').sort_values('score_rmsle', ascending= False).plot(kind='barh', color = cycle_colors[1]);\n",
    "plt.title('Mean RMSLE across models');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['model','score_mae']].groupby('model').agg('mean').sort_values('score_mae', ascending= False).plot(kind='barh', color = cycle_colors[1]);\n",
    "plt.title('Mean MAE across models');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['model','score_mse']].groupby('model').agg('mean').sort_values('score_mse', ascending= False).plot(kind='barh', color = cycle_colors[1]);\n",
    "plt.title('Mean MSE across models');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['model','score_rmse']].groupby('model').agg('mean').sort_values('score_rmse', ascending= False).plot(kind='barh', color = cycle_colors[1]);\n",
    "plt.title('Mean RMSE across models');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['model','score_r2']].groupby('model').agg('mean').sort_values('score_r2', ascending= True).plot(kind='barh', color = cycle_colors[1]);\n",
    "plt.title('Mean R2 across models');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ***Best features*** ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['n_feats','score_rmsle']].groupby('n_feats').agg('mean').sort_values('score_rmsle', ascending= False).plot(kind='barh', color = cycle_colors[2]);\n",
    "plt.title('Mean RMSLE in relation to number of features');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['n_feats','score_mae']].groupby('n_feats').agg('mean').sort_values('score_mae', ascending= False).plot(kind='barh', color = cycle_colors[2]);\n",
    "plt.title('Mean MAE in relation to number of features');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['n_feats','score_mse']].groupby('n_feats').agg('mean').sort_values('score_mse', ascending= False).plot(kind='barh', color = cycle_colors[2]);\n",
    "plt.title('Mean MSE in relation to number of features');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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zE5mZmZg6dSr8/PwQGhoKAPj444+xZ88ezJ8/Hzk5Obh69SoOHDiA6dOno6qqSqe+9LletI21qe8xb29veHp6IjY2FhcvXsSJEycwb968ejdGn9TYZ+HKlSuIjo7GiRMncPPmTZw6dQrHjx9XO2SpC7NMEHZ2dnBycqr39e7du+PPP/9EeXk5hg8fDl9fX7zzzjuoqqqCg4MDAGDNmjXw9PTE0KFDERoaCjc3N4wbN05vMVtbW2P27NmIi4vDgwcPNLZxcnJq8GqFl19+GT/88ANGjhyJrl27Ytq0afDx8cHJkyfVjuXeuHED7dq1q/OTk5PT3MPSypQpU7Bjxw7s27cP/fv3R79+/RAbGws3N7d659myZQuUSiX69++PMWPGYMSIEejXr59am+XLl0MqlaJr165wcXGpcz8IANja2uLQoUOwtrbG4MGDERwcDJFIhAMHDjzzNenTp09Hv379EBAQABcXF/z444/gOA67d+9Gt27d8Morr6Bfv34oLCzEH3/8obaOmqJr1674+uuv8eOPP6Jnz5749ttv69xX8yzatWuHGTNmYNy4cRg0aBDs7Oywa9cu1Rff0KFDkZqaivPnzyMoKAi9evXCvHnz8Nxzz+l8r4M+14u2sTb1PSYUCrF9+3YUFxfjhRdewKxZs7Bq1SrVoaeGNPZZEIlEuHz5MiZMmIAuXbrgjTfeQEBAANavX9+k/wPHdDmISAghxGyY5R4EIYSQxlGCIIQQohElCEIIIRpRgiCEEKIRJQhCCCEamdSNcvq8D4EPrVu3brRAmzEyxXHRmIyDKY4JeLZx1ZaF0YT2IAghhGhECYIQQohGvB9i2rBhA7KzsyEWi5GQkKD22t69e5GcnIzNmzejVatWjS5r73apnqLki5TvAPREqlPrUeMd9BIFIaRhvCeIIUOGYMSIEXVqwpSUlOD8+fPPXF6AEGKYGGOQyWRQKpVa1SFqDkVFRaiurm6RvlpSY+NijMHCwgI2NjY6/a95TxC+vr4aK4l+9913ePPNNxEfH89DVIQQfZPJZLC0tIRQ2HJfQ0KhUK2UuanQZlxyuRwymQy2trbaL/dZA9OHjIwMODk5oWPHjg22O3z4MA4fPgwA+Oyzz1ogMsIHY9iLFAqFRhGnLvQ9pqKiIrUHHLWUlkxILamxcQmFQnAcp9M6Nbj/VHV1NVJSUrB06dJG24aFhSEsLKwFoiJ8MobLEk3x8kl9j6m6urrFt+aFQiFvZev1SdtxVVdX11mnRnWZa1FREYqLi/HBBx9g1qxZuH//PqKjoyGVSvkOjRBCzIrB7UF4eHhg8+bNqr9nzZqFTz/9VKurmEztahdT3CoFTHdc5Nk091WIpvZ9wAfeE0RiYiLy8vJQVlaGyMhIhIeHIyQkhO+wCCFEJ3K5vMnnN55lXn3iPaK5c+c2+HpzPhKREEKeVFlZiXfffRd3796FUqnE+++/D09PTyxbtgyVlZWwtrbG9u3bIRQKsXjxYpw/fx4CgQAxMTEIDAzE9u3bsX//flRUVECpVCI5ORlLly5Ffn4+Hj16hAULFmD48OEa+3563vDwcBw8eBCVlZW4fv06IiMjUVNTg507d8LKygrJyclwdHTEN998g+TkZAiFQvj4+ODLL79ERUUFFi9erFW/uuA9QRBCCF/S0tLQtm1bJCcnAwAePnyI4cOH48svv4Sfnx/KyspgY2ODzZs3g+M4HDlyBFeuXMHEiRNx/PhxAMCFCxdw+PBhODo64tNPP0VgYCA+//xzlJaW4pVXXkFQUFC9jwJ+ct7t27cjPz8fBw8eRHV1NQIDA7FkyRIcOnQIMTEx+OWXX/DOO+8gKSkJp06dgrW1NUpLSwE8PhKjS7/aMriT1IQQ0lK6deuG9PR0rFq1CmfOnMGdO3fQpk0b+Pn5AQCee+45CIVCZGRk4PXXXwcAeHt7o0OHDrh27RoAYPDgwXB0dAQApKenIykpCcOGDcO4ceNQXV2NO3fu1Nv/k/MCQEBAAOzt7eHs7IznnnsOw4YNAwB0794dt2/fVv3+3nvvYefOnarDUseOHdOpX23RHgQhxGx5eXnhwIEDSE1NRVxcHAIDA3VexpNb6YwxfPXVV/D29tZ5XgCwsrJS/W5hYaG6T4TjOCgUCgDAtm3bcPr0afzxxx9Yu3Ytjhw5onO/2uI1QZSUlCApKQlSqRQcxyEsLAwjR45EeXk51qxZg3v37sHFxQXz5s2Dvb19o8ujWkzGQtqkueiqFNLcCgsL4eDggDfeeAOtWrXCtm3bUFxcjJycHPj5+aG8vBw2Njbo378/UlJSMGjQIFy9ehV37tyBl5cXLly4oLa84OBgbNmyBStXrgTHcfj777/Rs2fPZotXqVSioKAAgYGB6N+/P3799VdUVFRgyJAheumX1wQhEAgwZcoUdO7cGVVVVVi0aBF69eqFo0eP4vnnn8eYMWOwe/du7N69G5MnT+YzVEKInvGxAXDx4kXVl6qlpSU+/fRTMMawdOlSyGQy2NjYYPv27Zg6dSoWL16M0NBQCAQCrFmzRuNd4HPnzkVMTAzCwsKgVCrh7u6Obdu2NVu8CoUCs2fPRllZGRhj+O///m+IxWLMnz8fH374YbP3yzHGWDPE3Szi4uIwYsQIfPPNN4iNjYWjoyMePHiA2NhYfPHFF43Ov2lNXgtESfhiyHsQpnhvh77HVFlZ+cwnUXVl7ndSa/qfG8Wd1MXFxbh+/Tq8vb1RWlqqOnHj4OCgOlNPCCGk5RjESWqZTIaEhARERETUyW4cx9VbnpaK9ZkXQy6GR8X6dFdUVMTLzWEt3WdaWhpWrFihNs3DwwNbt25t1n60GZe1tbVxFeuTy+VISEhAUFAQBgwYAAAQi8V48OCB6hBTfWU2qFifeTHkQzh0iEl35lKsLygoCIcOHaozvTnjMMlifYwxbNy4EW5ubnj11VdV0/39/XHs2DEAj6/v7devH18hEkL0xIBOf5oNXf/nvJ6kvnjxIpYtWwYPDw/VYaSJEyfCx8cHa9asQUlJiU6XuRYUFOg75BZlilulgGmOi8aku6qqKl4eGGSuJ6nlcjkePXpU54FBDe1BGNRVTM+KEoRxMMVx0Zh0x8cjR62trU3ykaONjauhR442lCB4PwdBCDFPHMfp9PjL5mCKiRzQ37gM5jJXQgghhoUSBCGEEI0oQRBCCNGI13MQGzZsQHZ2NsRiMRISEgAAycnJyMrKglAohKurK6KioiASibRaHhXrMxbSZ5rbkEtuEGJKeN2DGDJkCJYsWaI2rVevXkhISMDq1avRrl07pKSk8BQdIYSYN14ThK+vb537G3r37q26u7JLly6QSCR8hEYIIWbPoC9zTU1NRUBAQL2vUy0m82SINY+oFpNxMMUxAfobl8EmiF27dkEgECAoKKjeNlSLyTwZ4nXspnh9PY3JeDzLuAy2FlN9jh49iqysLMyZM6fF7rAkhBCizuASRE5ODvbs2YPo6GiNT2wihBDSMnitxZSYmIi8vDyUlZVBLBYjPDwcKSkpkMvlqpPXPj4+mDFjhlbLo1pMxsEUx0VjMg6mOCZAf4eYeD0HMXfu3DrTQkJCWj4QQgghdRjcISZCCCGGgRIEIYQQjShBEEII0YgSBCGEEI0MrljfmjVrVFcjVVZWws7ODvHx8Votj4r1GQtpsy2JCvcRoj+8JoghQ4ZgxIgRSEpKUk2bN2+e6vdt27bBzs6Oj9AIIcTsGVyxvlqMMZw6dQqBgYEtHBUhhBDAgGsx/fPPPxCLxWjXrl29bahYHzGUwmumWASOxmQ8zK5Y38mTJxvde6BifcRQ7oo1xTt0aUzGw6yK9SkUCpw9e7bBUt+EEEL0yyD3IC5cuID27dvD2dlZp/lM7YoW2tohhPCJ1wTxZLG+yMhIhIeHIyQkRKvDS4QQQvTL4Ir1AcCsWbNaNhBCCCF1GOQ5CEIIIfyjBEEIIUQjShCEEEI0ogRBCCFEI4Mr1rdjxw4cOXIErVq1AgBMnDgRffr00Wp5VKzPWEj1slRTu8yZEL4ZXLE+AHjllVcwevRonqIihBACGHCxPkIIIfwyyDupDx48iPT0dHTu3BlvvfVWvUmEivWRJ/FZhM0Ui8DRmIyH2RTre+mllzBu3DgAwPbt27Ft2zZERUVpbEvF+siT+CzfYYrlQ2hMxsNsivU5ODjAwsICFhYWCA0NxdWrV/kOiRBCzJLB7UE8ePAAjo6OAICzZ8/C3d1d63lN7SoW2tohhPDJ4Ir15ebm4saNG+A4Di4uLpgxYwafIRJCiNkyuGJ9ISEhLR8IIYSQOgzuHAQhhBDDQAmCEEKIRpQgCCGEaEQJghBCiEa8X+aqqWDfTz/9hMzMTHAcB7FYjKioKDg5OTW6LCrWZyykfAfQbEzt0mpCnsT7HsSQIUOwZMkStWmjR4/G6tWrER8fjz59+uCXX37hKTpCCDFfvCcITQX77OzsVL9XV1eD47iWDosQQswe74eY6vPjjz8iPT0ddnZ2iImJ0diGivURvtUWSDPFInA0JuNhNsX6ak2cOBETJ05ESkoKDhw4gPDw8DptqFgf4VttyRBTLB9CYzIeZlOs72lBQUE4c+YM32EQQojZMcg9iLt376Jdu3YAgIyMjAYz3JNM7YoS2tohhPCJ9wShqWBfdnY27t69C47j0Lp1ayrYRwghPOA9QVDBPkIIMUwGfw6CEEIIPyhBEEII0YgSBCGEEI14PQehqQ7TqVOn8PPPP+POnTv45JNP4OXlpfXyqBaTsZDyHYAeSFW/mdrVdMR88boHoakOk7u7OxYuXIju3bvzFBUhhBCA5z0IX19fFBcXq03r0KEDT9EQQgh5Eu+XuT4LqsVEDJGp1PoxxbpFpjgmwAxrMWmDajERQ2Qqd4mb4h3vpjgmwIxrMRFCCOEHJQhCCCEacYwxxlfnT9ZhEovFCA8Ph729Pb799ls8fPgQIpEIHTt2xIcffqjV8goKCvQcccui3WHjQWMyDqY4JkB/h5h4PQehqQ4TAPTv379lAyGEEFIHHWIihBCiESUIQgghGj1TgigqKqpzoxshhBDToFOCSExMRH5+PgAgLS0N8+fPx4IFC5CamqqX4AghhPBHp5PUf//9N9577z0AwL59+/DRRx9BJBIhPj6+SQ/5KSkpQVJSEqRSKTiOQ1hYGEaOHInk5GRkZWVBKBTC1dUVUVFREIlEjS6PivUZCynfAeiBtNEWVMSPGBudEoRcLodQKIREIkF5eTm6desGACgtLW1S5wKBAFOmTEHnzp1RVVWFRYsWoVevXujVqxcmTZoEgUCA77//HikpKZg8eXKT+iCEENI0OiWIjh07IiUlBffu3UOfPn0AABKJBLa2tk3q3NHREY6OjgAAW1tbuLm5QSKRoHfv3qo2Xbp0wenTp5u0fEIIIU2nU4KIjIzE9u3bVVv+AHDp0iUMGjTomQMpLi7G9evX4e3trTY9NTUVAQEBGuehYn3EmBhbkThTLGxnimMCDKRYX1lZGd5//321aQMHDnzmwGQyGRISEhAREQE7OzvV9F27dkEgECAoKEjjfFSsjxgTY7uD1xTvOjbFMQEGUqxv5cqVGqevWrVKt4ieIJfLkZCQgKCgIAwYMEA1/ejRo8jKysKcOXPAcVyTl08IIaRptNqDUCqVAADGmOqnVlFREQQCQZM6Z4xh48aNcHNzw6uvvqqanpOTgz179mD58uWwtrbWenmmdpUIbe0YD1McEyFaJYiJEyeqfp8wYYLaaxYWFhg7dmyTOs/Pz0d6ejo8PDzwwQcfqPrasmUL5HI5VqxYAQDw8fHBjBkzmtQHIYSQptEqQaxfvx6MMcTGxmL58uWq6RzHoVWrVrCysmpS5926dcOOHTvqTK+9QooQQgh/tEoQLi4uAIANGzboNRhCCCGGQ+dy35mZmcjLy8PDhw/VptfeYU0IIcQ06HQV088//4yvvvoKSqUSp0+fhr29Pf766y+1S1MJIYSYBp32INLS0rB06VJ4eHjg6NGjiIiIwKBBg7Bz5059xUcIIYQnOiWIiooKeHh4PJ5RKIRcLoe3tzfy8vKa1HlNTQ1iYmIgl8uhUCgwcOBAhIeHq17/9ttvkZaWhuTkZK2WR8X6jIWU7wD0QKpTa1O7JJuYJp0SRNu2bXH79m24u7vD3d0dhw4dgr29Pezt7ZvUuaWlJWJiYmBjYwO5XI5ly5bBz88PXbp0wdWrV1FRUdGk5RJCCHl2Op2DGD9+PMrKygAAkyZNwv79+5GcnIy33nqrSZ1zHAcbGxsAgEKhgEKhAMdxUCqV+P7776mCKyGE8EinPYgn70/w8fHBunXrnjkApVKJ6OhoFBYWYvjw4fDx8cHvv/+Ovn37qiq91oeK9RFjZQwF40yxsJ0pjgkwkGJ9AHDnzh2cOnUKpaWlmD59OgoKCvDo0SN4eno2KQALCwvEx8ejoqICq1evRl5eHk6dOoXY2NhG56VifcRYGUNZDlMsH2KKYwIMpFjfqVOnEBMTA4lEgvT0dABAVVUVtm3b1qTAniQSidCjRw/k5uaisLAQc+bMwaxZs1BTU4PZs2c/8/IJIYToRqc9iB07dmDp0qXo2LEjTp06BQDw9PTEjRs3mtT5w4cPIRAIIBKJUFNTg/Pnz+O1117D119/rWozZcoUrQ9lmdqVIbS1YzxMcUyE6JQgSktL6xxK4jiuyeW4Hzx4gKSkJCiVSjDG8OKLL6Jv375NWhYhhJDmpVOC6Ny5M9LT0xEcHKyadvLkyTpPgdOWp6cn4uLiGmyj7T0QhBBCmpdOCWLatGlYuXIlUlNTUV1djVWrVqGgoABLly7VV3yEEEJ40miCKC8vV90I5+bmhsTERGRlZaFv375wdnZG3759VfcyEEIIMR2NXsU0a9Ys1e8rVqyAtbU1AgICMHr0aAQGBlJyIIQQE9VogrCyssKtW7egVCpx5coVMMagVCrr/BBCCDEtjR5i+q//+i8sWbIEjx49AlD3kaO1tm/frnPnGzZsQHZ2NsRiMRISEgAAN27cwNdffw2ZTAYXFxfMmTNH63LiVKzPWEj5DkAPpDq1NrVLsolpajRBvPTSSwgNDYVUKsXcuXPx+eefN1vnQ4YMwYgRI5CUlKSatmnTJkyZMgW+vr5ITU3Fr7/+Wm9SIoQQoj9a3UktEAjg7OyMuLg4uLi4aPyp9emnn2rdua+vb51KsAUFBejevTsAoFevXjhz5ozWyyOEENJ8dLrMtV27do22uXjxYpODAQB3d3dkZGSgf//+OH36NO7fv19vWyrWR4yVMRSMM8XCdqY4JsCAivXp28yZM7Flyxbs3LkT/v7+EArrD5GK9RFjZQxlOUyxfIgpjgnQX7E+g0sQbm5uqhvvCgoKkJ2dzXNEhBBingwuQZSWlkIsFkOpVGLXrl0YNmyY1vOa2pUhtLVjPExxTIQ0e4JgjGndNjExEXl5eSgrK0NkZCTCw8Mhk8lw8OBBAED//v0xdOjQ5g6REEKIFnRKEHK5HEePHsWNGzcgk8nUXnvvvfcAAGPHjtV6eXPnztU4feTIkbqERQghRA90ShDr16/HzZs30bdvX4jFYo1tdEkQhBBCDJdOCeKvv/7C+vXrIRKJ9BUPIYQQA6HTI0dbt26tKrlBCCHEtOm0BzF48GDEx8fj5ZdfhoODg9prPXv2bM64moRqMRkLKd8B6IFUp9amdsUdMU06JYgDBw4AAH788Ue16RzHYf369Tp3XlNTg5iYGMjlcigUCgwcOBDh4eEoLi5GYmIiysrK0LlzZ8yePbvBG+YIIYQ0P52+dZ8sqtccLC0tERMTAxsbG8jlcixbtgx+fn7Yt28fXnnlFQQGBuKrr75CamoqXnrppWbtmxBCSMN0OgfR3DiOUz1wSKFQQKFQgOM45ObmYuDAgQAeV3zNyMjgM0xCCDFLvB+3USqViI6ORmFhIYYPHw5XV1fY2dlBIBAAAJycnCCRSDTOS8X6iLEyhoJxpljYzhTHBJhwsT4LCwvEx8ejoqICq1evRkFBgdbzUrE+YqyMoSyHKZYPMcUxAfor1sfrIaYniUQi9OjRA5cuXUJlZSUUCgUAQCKRwMnJiefoCCHE/PC6B/Hw4UMIBAKIRCLU1NTg/PnzeO2119CjRw+cPn0agYGBOHr0KPz9/bVanqldOkhbO8bDFMdECK8J4sGDB0hKSoJSqQRjDC+++CL69u2LDh06IDExET/99BM6deqEkJAQPsMkhBCzxGuC8PT0RFxcXJ3prq6uOj26lBBCSPMzmHMQhBBCDAslCEIIIRpRgiCEEKJRi56DUCqVWLRoEZycnLBo0SIcOHAAv/32G4qKirB582a0atUKAFBZWYm1a9fi/v37UCgUGDVqlFZPlqNifcZCyncAeiDVeQ5Tu+qOmJ4W3YP4/fff4ebmpvq7a9eu+Oijj+Di4qLW7sCBA+jQoQPi4+MRGxuLbdu2QS6Xt2SohBBi9losQdy/fx/Z2dkIDQ1VTevUqRPatGlTpy3HcZDJZGCMQSaTwd7eHhYWdDSMEEJaUosdYtq6dSsmT56MqqqqRtuOGDECcXFxePfdd1FVVYV58+ZpTBBUi4kYM0OvCWSKdYtMcUyAkddiysrKglgsRufOnZGbm9to+7/++guenp5YtmwZioqKsGLFCnTr1g12dnZq7agWEzFmhn7ntSneHW6KYwL0V4upRRJEfn4+MjMzce7cOdTU1KCqqgpr167FnDlzNLZPS0vDmDFjwHEc2rZtizZt2qCgoADe3t4tES4hhBC0UIKYNGkSJk2aBADIzc3F3r17600OwONseOHCBXTv3h1SqRQFBQUaz1UQQgjRH15Lbfz+++/49ddfIZVK8cEHH+CFF15AZGQk3njjDWzYsAELFiwAALz55puqS2AbYmqXDdLusPEwxTERwjHGGN9BNBddniVhDEz1S8cUx0VjMg6mOCbADJ4HQQghxLBQgiCEEKIRJQhCCCEaUYIghBCiEa9XMTXk999/x5EjR8AYQ2hoKF555ZVG56FifcZCyncAeiDlOwA9kPIdgB5ITe5qR30yyD2IW7du4ciRI/jkk08QHx+P7OxsFBYW8h0WIYSYFYNMEHfu3IG3tzesra0hEAjQvXt3nDlzhu+wCCHErBjkISZ3d3f89NNPKCsrg5WVFc6dOwcvL6867ahYHyFEV1SsT3sGe6NcamoqDh48CBsbG3To0AGWlpaIiIhocJ5Na/JaJjhCiNEyxXMQRl2srylCQkIQEhICAPjf//1fODs78xwRIYSYF4NNEKWlpRCLxSgpKcHZs2exatWqRucxtS0DKgtgPGhMxsEUx6RPBpsgEhISUFZWBqFQiOnTp0MkEvEdEiGEmBWDTRAff/wx3yEQQohZM8jLXAkhhPCPEgQhhBCNKEEQQgjRiBIEIYQQjQz2JHVBQQHWrFmj+ru4uBjh4eENFu2jYn3GQsp3AHog5TsAPZDyHYAeSAGY3iXx+mKwCaJ9+/aIj48HACiVSrz77rvo378/z1ERQoj5MIpDTBcuXEDbtm3h4uLCdyiEEGI2DHYP4kknT55EYGBgnelUrI8Q0hSmVrBPX8X6DD5ByOVyZGVlYdKkSXVeCwsLQ1hYGA9REUKMmamV29BXsT6DP8R07tw5dOrUCQ4ODnyHQgghZsXg9yDqO7ykialdmWCqhcVMcVw0JuNgimPSJ4Peg5DJZDh//jwGDBjAdyiEEGJ2DHoPwsbGBt9++y3fYRBCiFky6D0IQggh/KEEQQghRCNKEIQQQjSiBEEIIUQjgz5JPWvWLNjY2MDCwgICgaDRu6WpWJ+xkPIdgB5I+Q5AD6R8B6AHUo1TTe0S+eZi0AkCAGJiYtCqVSu+wyCEELNDh5gIIYRoZPB7EKtWrQIADBs2rE7dJSrWRwhpDsZevE9fxfo4xhhr9qU2E4lEAicnJ5SWlmLlypWYNm0afH19622/aU1eC0ZHCDEVxn4OwiyL9Tk5OQEAxGIx+vXrhytXrvAcESGEmA+DPcQkk8nAGIOtra2qJtO4ceManMfYtwKeZqqFxUxxXDQm42CKY9Ing00QpaWlWL16NQBAoVBg0KBB8PPz4zcoQggxIwabIFxdXVXPpCaEENLyDPocBCGEEP5QgiCEEKIRJQhCCCEaGew5iJqaGsTExEAul0OhUGDgwIEIDw9vcB6qxWQspHwHoAdSvgPQAynfAeiBlO8AdMbn1ZkGmyAsLS0RExMDGxsbyOVyLFu2DH5+fujSpQvfoRFCiFkw2ENMHMfBxsYGwOPLXBUKBTiO4zkqQggxHwa7BwEASqUS0dHRKCwsxPDhw+Hj48N3SIQQYjYMOkFYWFggPj4eFRUVWL16NW7dugUPDw/V61SsjxBi6rQpwqevYn0GnSBqiUQi9OjRAzk5OWoJIiwsrE6FV0IIMSXalAYxu2J9Dx8+REVFBYDHVzSdP38ebm5uPEdFCCHmw2D3IB48eICkpCQolUowxvDiiy+ib9++Dc5DxfqMgymOi8ZkHExxTPpksAnC09MTcXFxfIdBCCFmy2APMRFCCOEXJQhCCCEaUYIghBCiESUIQgghGhnsSep9+/YhNTUVHMfB3d0dUVFRsLKyanAeKtZnLKR8B6AHUr4D0AMp3wHogZTvAJqdPq/eNMg9CIlEgv379+Ozzz5DQkIClEol/vzzT77DIoQQs2KQCQJ4XIeppqYGCoUCNTU1cHR05DskQggxKwZ5iMnJyQmjRo3CzJkzYWVlhd69e6N379512lEtJkKIuWvdurV51WIqLy9HRkYGkpKSYGdnh88//xzp6ekYPHiwWjuqxUQIMXclJSXmVYvpwoULaNOmDVq1agWhUIgBAwbg0qVLfIdFCCFmxSATROvWrXH58mVUV1eDMYYLFy5QoT5CCGlhBnmIycfHBwMHDkR0dDQEAgE6duyo1aEkKtZnHExxXDQm42CKY9Ing0wQABAeHo7w8HC+wyCEELNlkIeYCCGE8I9jjDG+gyCEEGJ4TGYPYtGiRXyH0OxMcUyAaY6LxmQcTHFMgP7GZTIJghBCSPOiBEEIIUQjk0kQpnhHtSmOCTDNcdGYjIMpjgnQ37joJDUhhBCNTGYPghBCSPOiBEEIIUQjg72TWhc5OTnYsmULlEolQkNDMWbMGL5D0llJSQmSkpIglUrBcRzCwsIwcuRIlJeXY82aNbh37x5cXFwwb9482Nvb8x2uTpRKJRYtWgQnJycsWrQIxcXFSExMRFlZGTp37ozZs2dDKDSet2JFRQU2btyI27dvg+M4zJw5E+3btzf69aTpKY5SqdSo1tWGDRuQnZ0NsViMhIQEAKj3M8QYw5YtW3Du3DlYW1sjKioKnTt35nkEdWkaU3JyMrKysiAUCuHq6oqoqCiIRCIAQEpKClJTU2FhYYFp06bBz8+v6Z0zI6dQKNh7773HCgsL2aNHj9jChQvZ7du3+Q5LZxKJhF29epUxxlhlZSWbM2cOu337NktOTmYpKSmMMcZSUlJYcnIyj1E2zd69e1liYiL79NNPGWOMJSQksBMnTjDGGNu0aRM7ePAgn+HpbN26dezw4cOMMcYePXrEysvLjX493b9/n0VFRbHq6mrG2ON1lJaWZnTrKjc3l129epXNnz9fNa2+dZOVlcVWrVrFlEoly8/PZ4sXL+Yj5EZpGlNOTg6Ty+WMscfjqx3T7du32cKFC1lNTQ0rKipi7733HlMoFE3u2+gPMV25cgVt27aFq6srhEIhAgICkJGRwXdYOnN0dFRtvdja2sLNzQ0SiQQZGRkIDg4GAAQHBxvd2O7fv4/s7GyEhoYCABhjyM3NxcCBAwEAQ4YMMaoxVVZW4p9//kFISAgAQCgUQiQSGf16Auo+xdHBwcHo1pWvr2+dPbf61k1mZiYGDx4MjuPQpUsXVFRU4MGDBy0ec2M0jal3794QCAQAgC5dukAikQB4PNaAgABYWlqiTZs2aNu2La5cudLkvg13X1FLEokEzs7Oqr+dnZ1x+fJlHiN6dsXFxbh+/Tq8vb1RWlqqetyqg4MDSktLeY5ON1u3bsXkyZNRVVUFACgrK4OdnZ3qze3k5KR6cxuD4uJitGrVChs2bMDNmzfRuXNnREREGP160vQUx86dOxv1uqpV37qRSCRqT2FzdnaGRCIxuscbp6amIiAgAMDjMfn4+Khee9Z1ZvR7EKZGJpMhISEBERERsLOzU3uN4zhwHMdTZLrLysqCWCw2yOO6TaVQKHD9+nW89NJLiIuLg7W1NXbv3q3WxtjWE6D+FMdNmzZBJpMhJyeH77CanTGum4bs2rULAoEAQUFBelm+0e9BODk54f79+6q/79+/DycnJx4jajq5XI6EhAQEBQVhwIABAACxWIwHDx7A0dERDx48QKtWrXiOUnv5+fnIzMzEuXPnUFNTg6qqKmzduhWVlZVQKBQQCASQSCRGtb6cnZ3h7Oys2kobOHAgdu/ebdTrCVB/iiMADBgwAPn5+Ua9rmrVt26cnJzUng1hbN8dR48eRVZWFpYtW6ZKek9/Hz7rOjP6PQgvLy/cvXsXxcXFkMvl+PPPP+Hv7893WDpjjGHjxo1wc3PDq6++qpru7++PY8eOAQCOHTuGfv368RWiziZNmoSNGzciKSkJc+fORc+ePTFnzhz06NEDp0+fBvD4TW5M68vBwQHOzs4oKCgA8PiLtUOHDka9ngDNT3Hs0KGDUa+rWvWtG39/f6Snp4MxhkuXLsHOzs5oDi/l5ORgz549iI6OhrW1tWq6v78//vzzTzx69AjFxcW4e/cuvL29m9yPSdxJnZ2dje+++w5KpRJDhw7F66+/zndIOrt48SKWLVsGDw8P1dbAxIkT4ePjgzVr1qCkpMRoL58EgNzcXOzduxeLFi1CUVEREhMTUV5ejk6dOmH27NmwtLTkO0St3bhxAxs3boRcLkebNm0QFRUFxpjRr6cdO3bgzz//VD3FMTIyEhKJxKjWVWJiIvLy8lBWVgaxWIzw8HD069dP47phjOGbb77BX3/9BSsrK0RFRcHLy4vvIdShaUwpKSmQy+Wq95iPjw9mzJgB4PFhp7S0NFhYWCAiIgIvvPBCk/s2iQRBCCGk+Rn9ISZCCCH6QQmCEEKIRpQgCCGEaEQJghBCiEaUIAghhGhECYIQQohGlCAIIYRo9P8Ay5lpYQ6xGz0AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['n_feats','score_rmse']].groupby('n_feats').agg('mean').sort_values('score_rmse', ascending= False).plot(kind='barh', color = cycle_colors[2]);\n",
    "plt.title('Mean RMSE in relation to number of features');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['n_feats','score_r2']].groupby('n_feats').agg('mean').sort_values('score_r2', ascending= True).plot(kind='barh', color = cycle_colors[2]);\n",
    "plt.title('Mean R2 in relation to number of features');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Top 5 feature sets \n",
    "top_n_feats = [17, 12, 20, 14, 15]\n",
    "top_feats_dict = dict()\n",
    "for nfeats in top_n_feats:\n",
    "    top_feats_dict[nfeats] = ast.literal_eval(df[df['n_feats'] == nfeats]['feats'].tolist()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{17: ['workingday',\n",
       "  'atemp',\n",
       "  'count',\n",
       "  'year',\n",
       "  'month',\n",
       "  'day',\n",
       "  'hour',\n",
       "  'dayofweek',\n",
       "  'weekend',\n",
       "  'mean',\n",
       "  'median',\n",
       "  'season_1',\n",
       "  'season_2',\n",
       "  'season_3',\n",
       "  'season_4',\n",
       "  'weather_1',\n",
       "  'weather_2'],\n",
       " 12: ['workingday',\n",
       "  'weather',\n",
       "  'count',\n",
       "  'year',\n",
       "  'month',\n",
       "  'day',\n",
       "  'hour',\n",
       "  'dayofweek',\n",
       "  'mean',\n",
       "  'median',\n",
       "  'Clear',\n",
       "  'Partlycloudy'],\n",
       " 20: ['workingday',\n",
       "  'weather',\n",
       "  'count',\n",
       "  'year',\n",
       "  'month',\n",
       "  'day',\n",
       "  'hour',\n",
       "  'dayofweek',\n",
       "  'weekend',\n",
       "  'mean',\n",
       "  'median',\n",
       "  'season_1',\n",
       "  'season_2',\n",
       "  'season_3',\n",
       "  'season_4',\n",
       "  'Clear',\n",
       "  'Partlycloudy',\n",
       "  'Cloudy',\n",
       "  'Brokenclouds',\n",
       "  'Mist'],\n",
       " 14: ['workingday',\n",
       "  'temp',\n",
       "  'atemp',\n",
       "  'humidity',\n",
       "  'windspeed',\n",
       "  'count',\n",
       "  'year',\n",
       "  'month',\n",
       "  'day',\n",
       "  'hour',\n",
       "  'dayofweek',\n",
       "  'mean',\n",
       "  'median',\n",
       "  'weather_1'],\n",
       " 15: ['workingday',\n",
       "  'atemp',\n",
       "  'year',\n",
       "  'month',\n",
       "  'hour',\n",
       "  'dayofweek',\n",
       "  'mean',\n",
       "  'median',\n",
       "  'season_1',\n",
       "  'season_2',\n",
       "  'season_3',\n",
       "  'season_4',\n",
       "  'weather_1',\n",
       "  'weather_2',\n",
       "  'count']}"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_feats_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Cloudy', 1),\n",
       " ('Brokenclouds', 1),\n",
       " ('Mist', 1),\n",
       " ('temp', 1),\n",
       " ('humidity', 1),\n",
       " ('windspeed', 1),\n",
       " ('weekend', 2),\n",
       " ('weather_2', 2),\n",
       " ('weather', 2),\n",
       " ('Clear', 2),\n",
       " ('Partlycloudy', 2),\n",
       " ('atemp', 3),\n",
       " ('season_1', 3),\n",
       " ('season_2', 3),\n",
       " ('season_3', 3),\n",
       " ('season_4', 3),\n",
       " ('weather_1', 3),\n",
       " ('day', 4),\n",
       " ('workingday', 5),\n",
       " ('count', 5),\n",
       " ('year', 5),\n",
       " ('month', 5),\n",
       " ('hour', 5),\n",
       " ('dayofweek', 5),\n",
       " ('mean', 5),\n",
       " ('median', 5)]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Frequency of features in top 5 feature sets\n",
    "merged = list(itertools.chain.from_iterable([v for v in top_feats_dict.values()]))\n",
    "cnt = Counter()\n",
    "cnt.update(merged)\n",
    "\n",
    "sorted(cnt.items(), key = lambda i: i[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ***Best feature selection method*** ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['fs_method','score_rmsle']].groupby('fs_method').agg('mean').sort_values('score_rmsle', ascending= False).plot(kind='barh', color = cycle_colors[3]);\n",
    "plt.title('Mean RMSLE in relation to feature selection method');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>score_rmsle</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fs_method</th>\n",
       "      <th>pipeline_name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">selectVarianceThreshold</th>\n",
       "      <th>main_preprocess</th>\n",
       "      <td>0.347504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>no_nlp</th>\n",
       "      <td>0.347977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>more_dummies_different_scaler_no_nlp_keep_3variables</th>\n",
       "      <td>0.348486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>no_nlp_no_cos_sim</th>\n",
       "      <td>0.349548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>more_dummies_different_scaler_no_nlp</th>\n",
       "      <td>0.351155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">anova_feats</th>\n",
       "      <th>more_dummies_different_scaler_no_nlp</th>\n",
       "      <td>0.556379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>main_preprocess</th>\n",
       "      <td>0.556669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>no_nlp_no_cos_sim</th>\n",
       "      <td>0.556996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>no_nlp</th>\n",
       "      <td>0.558720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>more_dummies_different_scaler_no_nlp_keep_3variables</th>\n",
       "      <td>0.614963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">no_selection</th>\n",
       "      <th>no_nlp</th>\n",
       "      <td>0.622962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>more_dummies_different_scaler_no_nlp</th>\n",
       "      <td>0.625958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>no_nlp_no_cos_sim</th>\n",
       "      <td>0.626489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>main_preprocess</th>\n",
       "      <td>0.631671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>more_dummies_different_scaler_no_nlp_keep_3variables</th>\n",
       "      <td>0.640512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>basic_pipeline</th>\n",
       "      <td>1.309705</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                            score_rmsle\n",
       "fs_method               pipeline_name                                                  \n",
       "selectVarianceThreshold main_preprocess                                        0.347504\n",
       "                        no_nlp                                                 0.347977\n",
       "                        more_dummies_different_scaler_no_nlp_keep_3vari...     0.348486\n",
       "                        no_nlp_no_cos_sim                                      0.349548\n",
       "                        more_dummies_different_scaler_no_nlp                   0.351155\n",
       "anova_feats             more_dummies_different_scaler_no_nlp                   0.556379\n",
       "                        main_preprocess                                        0.556669\n",
       "                        no_nlp_no_cos_sim                                      0.556996\n",
       "                        no_nlp                                                 0.558720\n",
       "                        more_dummies_different_scaler_no_nlp_keep_3vari...     0.614963\n",
       "no_selection            no_nlp                                                 0.622962\n",
       "                        more_dummies_different_scaler_no_nlp                   0.625958\n",
       "                        no_nlp_no_cos_sim                                      0.626489\n",
       "                        main_preprocess                                        0.631671\n",
       "                        more_dummies_different_scaler_no_nlp_keep_3vari...     0.640512\n",
       "                        basic_pipeline                                         1.309705"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['score_rmsle', 'fs_method', 'pipeline_name']].groupby(['fs_method', 'pipeline_name']).agg('mean').sort_values(by='score_rmsle')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>score_rmsle</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fs_param_value</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.1</th>\n",
       "      <td>0.341355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.2</th>\n",
       "      <td>0.342074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.3</th>\n",
       "      <td>0.362125</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                score_rmsle\n",
       "fs_param_value             \n",
       "0.1                0.341355\n",
       "0.2                0.342074\n",
       "0.3                0.362125"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['fs_method'] == 'selectVarianceThreshold'][['fs_param_value', 'score_rmsle']].groupby('fs_param_value').agg('median')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['fs_method','score_mae']].groupby('fs_method').agg('mean').sort_values('score_mae', ascending= False).plot(kind='barh', color = cycle_colors[3]);\n",
    "plt.title('Mean MAE in relation to feature selection method');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['fs_method','score_mse']].groupby('fs_method').agg('mean').sort_values('score_mse', ascending= False).plot(kind='barh', color = cycle_colors[3]);\n",
    "plt.title('Mean MSE in relation to feature selection method');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['fs_method','score_rmse']].groupby('fs_method').agg('mean').sort_values('score_rmse', ascending= False).plot(kind='barh', color = cycle_colors[3]);\n",
    "plt.title('Mean RMSE in relation to feature selection method');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[['fs_method','score_r2']].groupby('fs_method').agg('mean').sort_values('score_r2', ascending= True).plot(kind='barh', color = cycle_colors[3]);\n",
    "plt.title('Mean R2 in relation to feature selection method');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "423b8b96d4e1ec477b5c8920e05a523372dc7245eb6302a2ca5de114e24c04c2"
  },
  "kernelspec": {
   "display_name": "Python 3.7.5 64-bit",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}