diff --git a/Nguyen & Cao_Final Project Upds.pptx b/Nguyen & Cao_Final Project Upds.pptx new file mode 100644 index 0000000..9dc0d90 Binary files /dev/null and b/Nguyen & Cao_Final Project Upds.pptx differ diff --git a/Nguyen + Cao Final Project/Data400_FinalProject.ipynb b/Nguyen + Cao Final Project/Data400_FinalProject.ipynb new file mode 100644 index 0000000..091c7d6 --- /dev/null +++ b/Nguyen + Cao Final Project/Data400_FinalProject.ipynb @@ -0,0 +1,9339 @@ +{ + "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": 254, + "metadata": { + "id": "kr13v_LgvIpi" + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "g = pd.read_excel(\"Giant.xlsm\", engine=\"openpyxl\")\n", + "w = pd.read_excel(\"Walmart.xlsx\", engine=\"openpyxl\")\n", + "t = pd.read_excel(\"Target.xlsm\", engine=\"openpyxl\")" + ] + }, + { + "cell_type": "code", + "source": [ + "g.head()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 400 + }, + "id": "gD84Op8TvOCk", + "outputId": "e1eae6f4-19c5-4948-b14c-9e99777a0f89" + }, + "execution_count": 255, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " Giant_product_url \\\n", + "0 https://giantfoodstores.com/product/barilla-al... \n", + "1 https://giantfoodstores.com/product/barilla-al... \n", + "2 https://giantfoodstores.com/product/barilla-al... \n", + "3 https://giantfoodstores.com/product/barilla-al... \n", + "4 https://giantfoodstores.com/product/barilla-al... \n", + "\n", + " Giant_product_image_url \\\n", + "0 https://i5.peapod.com/c/NQ/NQDKE.png \n", + "1 https://i5.peapod.com/c/VI/VIDJJ.png \n", + "2 https://i5.peapod.com/c/RT/RTN08.png \n", + "3 https://i5.peapod.com/c/6O/6O6EP.png \n", + "4 https://i5.peapod.com/c/F5/F5DXA.png \n", + "\n", + " Giant_product_name Giant_product_brand \\\n", + "0 Barilla Al Bronzo Bronze Cut Penne Rigate Pasta Barilla \n", + "1 Barilla Al Bronzo Bronze Cut Bucatini Pasta Barilla \n", + "2 Barilla Al Bronzo Bronze Cut Fusilli Pasta Barilla \n", + "3 Barilla Al Bronzo Bronze Cut Spaghetti Pasta Barilla \n", + "4 Barilla Al Bronzo Linguine Pasta Barilla \n", + "\n", + " Giant_product_type Giant_food_group Giant_product_price \\\n", + "0 Pasta Grain 2.59 \n", + "1 Pasta Grain 2.59 \n", + "2 Pasta Grain 2.59 \n", + "3 Pasta Grain 2.59 \n", + "4 Pasta Grain 2.59 \n", + "\n", + " Giant_product_quantity Giant_product_price_per_unit Unnamed: 9 Unnamed: 10 \\\n", + "0 14.1 OZ BOX $0.18 /OZ NaN NaN \n", + "1 12 OZ BOX $0.22 /OZ NaN NaN \n", + "2 14.1 OZ BOX $0.18 /OZ NaN NaN \n", + "3 14.1 OZ BOX $0.18 /OZ NaN NaN \n", + "4 14.1 OZ BOX $0.18 /OZ NaN NaN \n", + "\n", + " Unnamed: 11 Unnamed: 12 \n", + "0 NaN NaN \n", + "1 NaN NaN \n", + "2 NaN NaN \n", + "3 NaN NaN \n", + "4 NaN NaN " + ], + "text/html": [ + "\n", + "
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1https://www.walmart.com/ip/12-Cans-Arizona-Arn...(12 Cans) Arizona Arnold Palmer Lite Half & Ha...12.0ArizonaBeveragesBeveragescurrent price $5.4811.50.476522NaNNaNNaN47.6521740.47652247.6521745.48NaNNaNNaN138.0
2https://www.walmart.com/ip/12-Cans-Bush-s-Orig...(12 Cans) Bush's Original Baked Beans, Canned ...12.0Bush'sProteinProteincurrent price $23.9816.01.498750NaNNaNNaN149.8750001.498750149.87500023.98NaNNaNNaN192.0
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4https://www.walmart.com/ip/12-pack-Barilla-Cla...(12 pack) Barilla Classic Non-GMO, Kosher Cert...12.0BarillaPastaGraincurrent price $22.0816.01.380000NaNNaNNaN138.0000001.380000138.00000022.08NaNNaNNaN192.0
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Giant_product_namegiant_unit_price_ozGiant_product_typegiant_quantity_ozGiant_food_group
0Barilla Al Bronzo Bronze Cut Penne Rigate Pasta0.18Pasta14.1Grain
1Barilla Al Bronzo Bronze Cut Bucatini Pasta0.22Pasta12.0Grain
2Barilla Al Bronzo Bronze Cut Fusilli Pasta0.18Pasta14.1Grain
3Barilla Al Bronzo Bronze Cut Spaghetti Pasta0.18Pasta14.1Grain
4Barilla Al Bronzo Linguine Pasta0.18Pasta14.1Grain
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Walmart_product_namewalmart_priceWalmart_product_typewalmart_quantity_ozWalmart_food_group
0(2 Pack ) Dole Canned Crushed Pineapple in 100...1.372500Canned Fruit16.0Fruit & Vegetables
1(12 Cans) Arizona Arnold Palmer Lite Half & Ha...0.476522Beverages138.0Beverages
2(12 Cans) Bush's Original Baked Beans, Canned ...1.498750Protein192.0Protein
3(12 pack) Annie's Yummy Bunnies and Cheddar, M...0.197000Pasta72.0Grain
4(12 pack) Barilla Classic Non-GMO, Kosher Cert...1.380000Pasta192.0Grain
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target_product_name_adjtarget_priceTarget_product_typetarget_quantity_ozTarget_food_group
0Annie's 2 Pack/6 oz Each Organic Super Mac She...0.473333Pasta12.0Grain
1Annie's 2 Pack/6 oz Each Organic Super Mac She...0.473333Pasta12.0Grain
2Annie's 3 Pack/6 oz Each Organic Super Mac She...0.473333Pasta18.0Grain
3Annie's 3 Pack/6 oz Each Organic Super Mac She...0.473333Pasta18.0Grain
4Annie's Cheddar Squares Baked Snack Crackers -...0.638667Pasta7.5Grain
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productpricestoreproduct_typefood_group
0Barilla Al Bronzo Bronze Cut Penne Rigate Pasta0.18GiantPastaGrain
1Barilla Al Bronzo Bronze Cut Bucatini Pasta0.22GiantPastaGrain
2Barilla Al Bronzo Bronze Cut Fusilli Pasta0.18GiantPastaGrain
3Barilla Al Bronzo Bronze Cut Spaghetti Pasta0.18GiantPastaGrain
4Barilla Al Bronzo Linguine Pasta0.18GiantPastaGrain
..................
3993NaNLundbergTargetNaNNaN
3994NaNAnnie'sTargetNaNNaN
3995NaNRao's HomemadeTargetNaNNaN
3996NaNOikosTargetNaNNaN
3997NaNLight + FitTargetNaNNaN
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3998 rows × 5 columns

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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "variable_name": "stacked_all", + "summary": "{\n \"name\": \"stacked_all\",\n \"rows\": 3998,\n \"fields\": [\n {\n \"column\": \"product\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 3714,\n \"samples\": [\n \"Bush's Vegetarian Baked Beans - 28 oz\",\n \"Birds Eye Steamfresh Long Grain White Rice Frozen\",\n \"Jif No Added Sugar Creamy Peanut Butter Spread\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"price\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 1344,\n \"samples\": [\n 4.315,\n 0.8620437956204381,\n 0.404954954954955\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"store\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 3,\n \"samples\": [\n \"Giant\",\n \"Walmart\",\n \"Target\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"product_type\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 12,\n \"samples\": [\n \"Beverages\",\n \"Bread\",\n \"Pasta\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"food_group\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"Grain\",\n \"Dairy\",\n \"Beverages\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" + } + }, + "metadata": {}, + "execution_count": 266 + } + ] + }, + { + "cell_type": "code", + "source": [ + "print(stacked_all['food_group'].unique())\n", + "\n", + "#stacked_all1 = stacked_all[stacked_all['food_group'].notna()]\n", + "\n", + "stacked_all1 = stacked_all[\n", + " (stacked_all['food_group'].notna()) &\n", + " (stacked_all['food_group'] != 'Other')\n", + "]\n", + "\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "O3BpohhWL16r", + "outputId": "dea66dec-6539-46ab-9fbc-e8f770993959" + }, + "execution_count": 267, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "['Grain' 'Dairy' 'Protein' 'Fruit & Vegetables' 'Prepared Food'\n", + " 'Beverages' nan 'Other']\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import matplotlib.pyplot as plt\n", + "grouped = stacked_all1.groupby(['food_group', 'store']).size().unstack(fill_value=0)\n", + "\n", + "# Step 2: Plot stacked bar chart\n", + "grouped.plot(kind='bar', stacked=True)\n", + "\n", + "# Step 3: Customize\n", + "plt.title('Number of Products by Food Group and Store')\n", + "plt.xlabel('Food Group')\n", + "plt.ylabel('Count of Products')\n", + "plt.legend(title='Store')\n", + "plt.xticks(rotation=45)\n", + "plt.tight_layout()\n", + "\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 487 + }, + "id": "_uWUAZyvMCmy", + "outputId": "3663fbc3-5c2b-4e9b-8395-a2b9787c7211" + }, + "execution_count": 268, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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+E3nz5sXatWvx+vVr3LhxAxMnToSenh46d+6MI0eOfHP+5J5XPj8HfM85jzSLfexIY3Lnzo3WrVtj6dKlGDJkSKLpX2uV+bxzckK6urpJKgPwn/3dviY+KZg2bRpcXV2/WOfzk3jCX7+akjNnTtSoUeOb9VIj1u95X7+HsbExTp06hePHj2Pfvn04cOAANm/ejGrVquHQoUNfPS6Sq23btujduzf+/fdfREZG4sKFC5g/f36KLDstsbS0hJ2dHW7evJloWnyfu68lToaGht99Z2VKHC9JaeGNjY2Fh4cH3r59i8GDByN//vwwNTXFs2fP0K5du0Q/CFLq+EkqXV1dFClSBEWKFIGbmxuqVq2K9evXJ+lznRyfnwO+55xHmsXEjjRqxIgRWLduHaZMmZJoWqZMmQAg0R1kP/JL/lvif53GExE8ePAARYsWBfDplz8AWFhYpPgJ1cHBAXfv3k1UfufOHWV6aotf5927dxN13r57964yPf7fz/dffL2Ekvq+xl9+/FIikdB/fWnr6OigevXqqF69OmbOnImJEydi+PDhOH78+Dffvy9ty71792BiYqLWUtOyZUv069cPGzduxMePH6Gvr49ffvnlP5edFNbW1jAxMfnqMaGjo6PcfZrUY8fBwQE3b96EiKjtty/N+yX16tXD8uXL4evr+8Md5uNvDHj//r1aq93nMX/PeeD+/ftqLU8PHjxAXFzcf44P6Ofnh3v37mHNmjVqNyUdPnw4ydv0ufhhYcLCwtSSn6Tu768pVaoUAKh1Y/na5+BHzys/85xHPwcvxZJGOTs7o3Xr1liyZAlevnypNs3CwgJZs2ZVG2IC+DQQ58/y559/4v3798rrbdu24cWLF8pYbyVLloSzszOmT5/+xUtS8ZfovkfdunXh6+urNkTGhw8fsHTpUjg6On53X7UfUapUKWTLlg2LFy9WGxJj//79uH37NurVqwfgU78vV1dXrFmzRu2yzOHDhxP14XFwcICuru4331dra2tUqlQJK1euxJMnT9SmJWxtjR8P7fMv/rdv3ybanvgWh6QM73H+/HlcuXJFef306VPs2rULNWvWVGutyZo1K+rUqYN169Zh/fr1qF27dqJL/99DV1cXNWvWxK5du9RawgIDA7FhwwZUqFABFhYWAJJ+7NStWxfPnz9X6xMYHh6OpUuXJimmQYMGwcTEBB06dEBgYGCi6clpBa9bty5iY2MTtW7OmjULKpVK+cx9z3ng8z5+8YOh/9dg3PHvacJtEBHMmTMnCVvzZXXr1kVMTAwWLVqklMXGxiZ5cPbTp08jOjo6UXl8X8GEl1hNTU2/OIzKj55XfuY5j34OttiRxg0fPhxr167F3bt3UahQIbVpv//+OyZPnozff/8dpUqVwqlTp3Dv3r2fFkvmzJlRoUIFtG/fHoGBgZg9ezZcXFzQqVMnAJ9agJYvX446deqgUKFCaN++PXLkyIFnz57h+PHjsLCwwJ49e75r3UOGDMHGjRtRp04d9OrVC5kzZ8aaNWvg7++P7du3a2SQUH19fUyZMgXt27dH5cqV8euvvyrDnTg6OqJv375K3UmTJqFevXqoUKECOnTogLdv32LevHkoVKiQ2heCpaUlmjdvjnnz5kGlUsHZ2Rl79+794oCrc+fORYUKFVCiRAl07twZTk5OCAgIwL59+3Dt2jUAUG5wGD58OFq2bAl9fX14enpi7NixOHXqFOrVqwcHBwcEBQVh4cKFyJkz5zfHEwQ+9e2rVauW2nAnANRG+4/Xtm1b5YaEcePGJX0Hf8P48eOVsfi6desGPT09LFmyBJGRkZg6dapSL6nHTqdOnTB//ny0bdsWly9fhp2dHdauXQsTE5MkxZMnTx5s2LABv/76K/Lly6c8eUL+/4kmGzZsgI6OTpKGuPH09ETVqlUxfPhwBAQEoFixYjh06BB27dqFPn36KC1FQPLPA/7+/mjQoAFq166N8+fPY926dfjtt99QrFixr86TP39+ODs7Y8CAAXj27BksLCywffv2L/bFTSpPT0+4u7tjyJAhCAgIQMGCBbFjx44k90mbMmUKLl++jCZNmihXDa5cuYI///wTmTNnVrv5qWTJkli0aBHGjx8PFxcXZMuWDdWqVfvh88rPPOfRT6Khu3EpA0o43Mnn4ocPSDjcicinW+o7duwolpaWYm5uLi1atJCgoKCvDnPw+dAWXl5eYmpqmmh9nw+tEn+r/8aNG2Xo0KGSLVs2MTY2lnr16iUaakNE5OrVq9KkSRPJkiWLGBoaioODg7Ro0UKOHj36zZj+y8OHD6VZs2ZiZWUlRkZGUqZMGdm7d2+iekjmcCffqhu//Vu3bv3i9M2bN0vx4sXF0NBQMmfOLK1atZJ///03Ub3t27dLgQIFxNDQUAoWLCg7duwQLy8vteFORERevXolTZs2FRMTE8mUKZP88ccfcvPmzS8OAXHz5k1p3Lixsk/y5csnI0eOVKszbtw4yZEjh+jo6CjDhRw9elQaNmwo2bNnFwMDA8mePbv8+uuvcu/evSTvs3Xr1kmePHnE0NBQihcv/tXhQCIjIyVTpkxiaWmpNizMf/nWPo935coVqVWrlpiZmYmJiYlUrVpVzp07l6heUo+dx48fS4MGDcTExESyZs0qvXv3lgMHDnxzuJOEHjx4IF27dhUXFxcxMjISY2NjyZ8/v3Tp0kWuXbumVvdrn0GRT8Nu9O3bV7Jnzy76+vqSJ08emTZtmtqwGiLJPw/cunVLmjVrJubm5pIpUybp0aNHkt6XW7duSY0aNcTMzEyyZs0qnTp1kuvXryc6Lr+2TfHrT+jNmzfSpk0bsbCwEEtLS2nTpo1cvXo1ScOdnD17Vrp37y6FCxcWS0tL0dfXl1y5ckm7du3UhsAREXn58qXUq1dPzM3NBYDa0CdJOTa+dTwm5ZxHaYNK5Dt6kBMRkSImJgbZs2eHp6cnVqxYoelwMixvb2+MGTMGr169SpHL4UTpEfvYERH9IB8fH7x69eq7nwRCRJRS2MeOiOg7Xbx4ETdu3MC4ceNQvHhxZcwzIiJNYYsdEdF3WrRoEbp27Yps2bJ98zmkRESpgX3siIiIiLQEW+yIiIiItAQTOyIiIiItwZsn8OlZeM+fP4e5uXmSnilIRERElFpEBO/fv0f27Nm/Oag0EzsAz58/V565SERERJQWPX369JtPdmFiBygPoH769Kny7EUiIiKitCA0NBT29vZKvvJfmNgByuVXCwsLJnZERESUJiWluxhvniAiIiLSEkzsiIiIiLQEEzsiIiIiLcE+dkRERFosNjYW0dHRmg6D/oO+vj50dXVTZFlM7IiIiLSQiODly5cICQnRdCiUBFZWVrC1tf3h8XSZ2BEREWmh+KQuW7ZsMDEx4QD8aZSIIDw8HEFBQQAAOzu7H1oeEzsiIiItExsbqyR1WbJk0XQ49A3GxsYAgKCgIGTLlu2HLsvy5gkiIiItE9+nzsTERMORUFLFv1c/2h+SiR0REZGW4uXX9COl3ismdkRERERagokdERERkZZgYkdERESp5tWrV+jatSty5coFQ0ND2NraolatWjh79iyAT5ckfXx8NBtkOsa7YomI0pkia4poOoTv4uflp+kQvkt63N92BnYY7DIYTnDSdCiJNG3aFFFRUVizZg1y586NwMBAHD16FG/evEnR9URHR0NfXz9Fl5kesMWOiIiIUkVISAhOnz6NKVOmoGrVqnBwcECZMmUwdOhQNGjQAI6OjgCAxo0bQ6VSKa8BYNGiRXB2doaBgQHy5cuHtWvXqi1bpVJh0aJFaNCgAUxNTTFhwgQAwK5du1CiRAkYGRkhd+7cGDNmDGJiYlJrk1MdEzsiIiJKFWZmZjAzM4OPjw8iIyMTTb906RIAYNWqVXjx4oXyeufOnejduzf69++Pmzdv4o8//kD79u1x/Phxtfm9vb3RuHFj+Pn5oUOHDjh9+jTatm2L3r1749atW1iyZAlWr16tJH3aiIkdERERpQo9PT2sXr0aa9asgZWVFdzd3TFs2DDcuHEDAGBtbQ3gf4/Xin89ffp0tGvXDt26dUPevHnRr18/NGnSBNOnT1db/m+//Yb27dsjd+7cyJUrF8aMGYMhQ4bAy8sLuXPnhoeHB8aNG4clS5ak7oanIiZ2RERElGqaNm2K58+fY/fu3ahduzZOnDiBEiVKYPXq1V+d5/bt23B3d1crc3d3x+3bt9XKSpUqpfb6+vXrGDt2rNJSaGZmhk6dOuHFixcIDw9PsW1KS3jzBBEREaUqIyMjeHh4wMPDAyNHjsTvv/+O0aNHo127dj+0XFNTU7XXYWFhGDNmDJo0afLFGLQRW+yIiIhIowoWLIgPHz4AAPT19REbG6s2vUCBAspwKPHOnj2LggUL/udyS5Qogbt378LFxSXRn46OdqZAbLEjIiKiVPHmzRs0b94cHTp0QNGiRWFubo6///4bU6dORcOGDQEAjo6OOHr0KNzd3WFoaIhMmTJh4MCBaNGiBYoXL44aNWpgz5492LFjB44cOfKf6xs1ahTq16+PXLlyoVmzZtDR0cH169dx8+ZNjB8/PjU2OdVpZ7pKREREaY6ZmRnKli2LWbNmoVKlSihcuDBGjhyJTp06Yf78+QCAGTNm4PDhw7C3t0fx4sUBAI0aNcKcOXMwffp0FCpUCEuWLMGqVatQpUqV/1xfrVq1sHfvXhw6dAilS5dGuXLlMGvWLDg4OPzsTdUYlYiIpoPQtNDQUFhaWuLdu3ewsLDQdDj0g9LjYKJA+h28lVIfj/HUlR73d/wAxe5F3LW2L5m2iYiIgL+/P5ycnBK9Z8nJU9hiR0RERKQlmNgRERERaQkmdkRERERagokdERERkZZgYkdERESkJZjYEREREWkJjSZ2sbGxGDlyJJycnGBsbAxnZ2eMGzcOCUdgERGMGjUKdnZ2MDY2Ro0aNXD//n215bx9+xatWrWChYUFrKys0LFjR4SFhaX25hARERFplEYTuylTpmDRokWYP38+bt++jSlTpmDq1KmYN2+eUmfq1KmYO3cuFi9ejIsXL8LU1BS1atVCRESEUqdVq1b4559/cPjwYezduxenTp1C586dNbFJRERERBqj0UeKnTt3Dg0bNkS9evUAfHqMyMaNG+Hr6wvgU2vd7NmzMWLECOVRI3/++SdsbGzg4+ODli1b4vbt2zhw4AAuXbqEUqVKAQDmzZuHunXrYvr06ciePbtmNo6IiIgolWm0xa58+fI4evQo7t27BwC4fv06zpw5gzp16gAA/P398fLlS9SoUUOZx9LSEmXLlsX58+cBAOfPn4eVlZWS1AFAjRo1oKOjg4sXL35xvZGRkQgNDVX7IyIiovRDpVLBx8dH02GkORptsRsyZAhCQ0ORP39+6OrqIjY2FhMmTECrVq0AAC9fvgQA2NjYqM1nY2OjTHv58iWyZcumNl1PTw+ZM2dW6nxu0qRJGDNmTEpvDhERUZrnOGRfqq4vYHK9ZM/z8uVLTJo0Cfv27cO///4LS0tLuLi4oHXr1vDy8oKJiQlevHiBTJkypWisVapUgaurK2bPnp2iy01NGk3stmzZgvXr12PDhg0oVKgQrl27hj59+iB79uzw8vL6aesdOnQo+vXrp7wODQ2Fvb39T1sfERERJc2jR4/g7u4OKysrTJw4EUWKFIGhoSH8/PywdOlS5MiRAw0aNICtra2mQ02TNHopduDAgRgyZAhatmyJIkWKoE2bNujbty8mTZoEAMqbFhgYqDZfYGCgMs3W1hZBQUFq02NiYvD27duvvumGhoawsLBQ+yMiIiLN69atG/T09PD333+jRYsWKFCgAHLnzo2GDRti37598PT0BJD4UuzgwYORN29emJiYIHfu3Bg5ciSio6OV6d7e3nB1dcXatWvh6OgIS0tLtGzZEu/fvwcAtGvXDidPnsScOXOgUqmgUqkQEBCQmpueIjSa2IWHh0NHRz0EXV1dxMXFAQCcnJxga2uLo0ePKtNDQ0Nx8eJFuLm5AQDc3NwQEhKCy5cvK3WOHTuGuLg4lC1bNhW2goiIiFLCmzdvcOjQIXTv3h2mpqZfrKNSqb5Ybm5ujtWrV+PWrVuYM2cOli1bhlmzZqnVefjwIXx8fLB3717s3bsXJ0+exOTJkwEAc+bMgZubGzp16oQXL17gxYsX6fJqnkYTO09PT0yYMAH79u1DQEAAdu7ciZkzZ6Jx48YAPr15ffr0wfjx47F79274+fmhbdu2yJ49Oxo1agQAKFCgAGrXro1OnTrB19cXZ8+eRY8ePdCyZUveEUtERJSOPHjwACKCfPnyqZVnzZoVZmZmMDMzw+DBg78474gRI1C+fHk4OjrC09MTAwYMwJYtW9TqxMXFYfXq1ShcuDAqVqyINm3aKI1HlpaWMDAwgImJCWxtbWFrawtdXd2fs6E/kUb72M2bNw8jR45Et27dEBQUhOzZs+OPP/7AqFGjlDqDBg3Chw8f0LlzZ4SEhKBChQo4cOAAjIyMlDrr169Hjx49UL16dejo6KBp06aYO3euJjaJiIiIUpivry/i4uLQqlUrREZGfrHO5s2bMXfuXDx8+BBhYWGIiYlJ1NXK0dER5ubmyms7O7tE3bnSO40mdubm5pg9e/Z/3n2iUqkwduxYjB079qt1MmfOjA0bNvyECImIiCi1uLi4QKVS4e7du2rluXPnBgAYGxt/cb7z58+jVatWGDNmDGrVqgVLS0ts2rQJM2bMUKunr6+v9lqlUindv7QFnxVLREREaUKWLFng4eGB+fPn48OHD0me79y5c3BwcMDw4cNRqlQp5MmTB48fP072+g0MDBAbG5vs+dISJnZERESUZixcuBAxMTEoVaoUNm/ejNu3b+Pu3btYt24d7ty588V+b3ny5MGTJ0+wadMmPHz4EHPnzsXOnTuTvW5HR0dcvHgRAQEBeP36dbpszWNiR0RERGmGs7Mzrl69iho1amDo0KEoVqwYSpUqhXnz5mHAgAEYN25conkaNGiAvn37okePHnB1dcW5c+cwcuTIZK97wIAB0NXVRcGCBWFtbY0nT56kxCalKpWIiKaD0LTQ0FBYWlri3bt3HNNOCxRZU0TTIXwXPy8/TYdA6QSP8dSVHve3nYEdBrsMhnsRd7WbDSntioiIgL+/P5ycnBK9Z8nJU9hiR0RERKQlmNgRERERaQkmdkRERERagokdERERkZZgYkdERESkJZjYEREREWkJJnZEREREWoKJHREREZGWYGJHREREpCWY2BERERFpCT1NB0BERESpyNsyldf3LslVVSrVf04fPXo0vL29fzCg76NSqbBz5040atRII+tPKiZ2RERElCa8ePFC+f/mzZsxatQo3L17VykzMzNL1vKioqJgYGCQYvGlB7wUS0RERGmCra2t8mdpaQmVSqW8/vDhA1q1agUbGxuYmZmhdOnSOHLkiNr8jo6OGDduHNq2bQsLCwt07twZALBs2TLY29vDxMQEjRs3xsyZM2FlZaU2765du1CiRAkYGRkhd+7cGDNmDGJiYpTlAkDjxo2hUqmU12kREzsiIiJK88LCwlC3bl0cPXoUV69eRe3ateHp6YknT56o1Zs+fTqKFSuGq1evYuTIkTh79iy6dOmC3r1749q1a/Dw8MCECRPU5jl9+jTatm2L3r1749atW1iyZAlWr16t1Lt06RIAYNWqVXjx4oXyOi3ipVgiIiJK84oVK4ZixYopr8eNG4edO3di9+7d6NGjh1JerVo19O/fX3k9fPhw1KlTBwMGDAAA5M2bF+fOncPevXuVOmPGjMGQIUPg5eUFAMidOzfGjRuHQYMGYfTo0bC2tgYAWFlZwdbW9qdu549iix0RERGleWFhYRgwYAAKFCgAKysrmJmZ4fbt24la7EqVKqX2+u7duyhTpoxa2eevr1+/jrFjx8LMzEz569SpE168eIHw8PCfs0E/CVvsiIiIKM0bMGAADh8+jOnTp8PFxQXGxsZo1qwZoqKi1OqZmpome9lhYWEYM2YMmjRpkmiakZHRd8esCUzsiIiIKM07e/Ys2rVrh8aNGwP4lIwFBAR8c758+fIl6hP3+esSJUrg7t27cHFx+epy9PX1ERsbm/zAUxkTOyIiIkrz8uTJgx07dsDT0xMqlQojR45EXFzcN+fr2bMnKlWqhJkzZ8LT0xPHjh3D/v371cbMGzVqFOrXr49cuXKhWbNm0NHRwfXr13Hz5k2MHz8ewKc7Y48ePQp3d3cYGhoiU6ZMP21bfwT72BEREVGaN3PmTGTKlAnly5eHp6cnatWqhRIlSnxzPnd3dyxevBgzZ85EsWLFcODAAfTt21ftEmutWrWwd+9eHDp0CKVLl0a5cuUwa9YsODg4KHVmzJiBw4cPw97eHsWLF/8p25gSVCIimg5C00JDQ2FpaYl3797BwsJC0+HQDyqypoimQ/gufl5+mg6B0gke46krPe5vOwM7DHYZDPci7umuj1hq6NSpE+7cuYPTp09rOhRFREQE/P394eTklOg9S06ewkuxREREpNWmT58ODw8PmJqaYv/+/VizZg0WLlyo6bB+CiZ2REREpNV8fX0xdepUvH//Hrlz58bcuXPx+++/azqsn4KJHREREWm1LVu2aDqEVMObJ4iIiIi0BBM7IiIiIi3BxI6IiIhISzCxIyIiItISTOyIiIiItAQTOyIiIiItwcSOiIiItNaJEyegUqkQEhKi6VBSBcexIyIiykBS+xFpyXmU3OLFizFw4EAEBwdDT+9TihIWFoZMmTLB3d0dJ06cUOqeOHECVatWxYMHD+Ds7JzSYacYb29v+Pj44Nq1a6myPrbYERERUZpQtWpVhIWF4e+//1bKTp8+DVtbW1y8eBERERFK+fHjx5ErV640m9SJCGJiYlJ9vUzsiIiIKE3Ily8f7OzsErXMNWzYEE5OTrhw4YJaedWqVbF27VqUKlUK5ubmsLW1xW+//YagoKCvrmP16tWwsrLC3r17kS9fPpiYmKBZs2YIDw/HmjVr4OjoiEyZMqFXr16IjY1V5vvWeuIv+e7fvx8lS5aEoaEh1q1bhzFjxuD69etQqVRQqVRYvXp1iu6zzzGxIyIiojSjatWqOH78uPL6+PHjqFKlCipXrqyUf/z4ERcvXkTVqlURHR2NcePG4fr16/Dx8UFAQADatWv3n+sIDw/H3LlzsWnTJhw4cAAnTpxA48aN8ddff+Gvv/7C2rVrsWTJEmzbtk2ZJ6nrGTJkCCZPnozbt2/Dw8MD/fv3R6FChfDixQu8ePECv/zyS4rsp69hHzsiIiJKM6pWrYo+ffogJiYGHz9+xNWrV1G5cmVER0dj8eLFAIDz588jMjISVatWRa5cuZR5c+fOjblz56J06dIICwuDmZnZF9cRHR2NRYsWKZdxmzVrhrVr1yIwMBBmZmYoWLCgkmDGJ2IdOnRI0nrGjh0LDw8P5bWZmRn09PRga2ubcjvpP7DFjoiIiNKMKlWq4MOHD7h06RJOnz6NvHnzwtraGpUrV1b62Z04cQK5c+dGrly5cPnyZXh6eiJXrlwwNzdH5cqVAQBPnjz56jpMTEzU+ubZ2NjA0dFRLUGzsbFRu9Sa1PWUKlUqRfbD92JiR0RERGmGi4sLcubMiePHj+P48eNKApU9e3bY29vj3LlzOH78OKpVq4YPHz6gVq1asLCwwPr163Hp0iXs3LkTABAVFfXVdejr66u9VqlUXyyLi4sDgGStx9TU9Md2wA/ipVgiIiJKU6pWrYoTJ04gODgYAwcOVMorVaqE/fv3w9fXF127dsWdO3fw5s0bTJ48Gfb29gCgdkdtSvmR9RgYGKjdhPGzscWOiIiI0pSqVavizJkzuHbtmtJiBwCVK1fGkiVLEBUVpfSvMzAwwLx58/Do0SPs3r0b48aNS/F4fmQ9jo6O8Pf3x7Vr1/D69WtERkameHwJMbEjIiKiNKVq1ar4+PEjXFxcYGNjo5RXrlwZ79+/V4ZFsba2xurVq7F161YULFgQkydPxvTp01M8nh9ZT9OmTVG7dm1UrVoV1tbW2LhxY4rHl5BKROSnriEdCA0NhaWlJd69ewcLCwtNh0M/KLVHVU8pyRmdnTI2HuOpKz3ubzsDOwx2GQz3Iu4wMjLSdDiUBBEREfD394eTk1Oi9yw5eQpb7IiIiIi0RLITuwMHDuDMmTPK6wULFsDV1RW//fYbgoODUzQ4IiIiIkq6ZCd2AwcORGhoKADAz88P/fv3R926deHv749+/fqleIBERERElDTJHu7E398fBQsWBABs374d9evXx8SJE3HlyhXUrVs3xQMkIiIioqRJdoudgYEBwsPDAQBHjhxBzZo1AQCZM2dWWvKIiIhIc+IQB4GA90emHyn1XiW7xa5ChQro168f3N3d4evri82bNwMA7t27h5w5c6ZIUERERPT93sW8Q0xcDMLDw2FsbKzpcCgJ4hvNPn8CRnIlO7GbP38+unXrhm3btmHRokXIkSMHAGD//v2oXbv2DwVDREREPy4iLgKn3pyCg4UDgE/PRlWpVBqOir5ERBAeHo6goCBYWVlBV1f3h5aX7MQuV65c2Lt3b6LyWbNm/VAgRERElHL2vtqLnsV7qj3IntIuKysr2Nra/vBykp3Y6erq4sWLF8iWLZta+Zs3b5AtW7ZkPw/t2bNnGDx4MPbv34/w8HC4uLhg1apVKFWqFIBPmezo0aOxbNkyhISEwN3dHYsWLUKePHmUZbx9+xY9e/bEnj17oKOjg6ZNm2LOnDkwMzNL7uYRERFpBYHAzs4O2bJlQ3R0tKbDof+gr6//wy118ZKd2H2tc19kZCQMDAyStazg4GC4u7ujatWq2L9/P6ytrXH//n1kypRJqTN16lTMnTsXa9asgZOTE0aOHIlatWrh1q1bysjMrVq1wosXL3D48GFER0ejffv26Ny5MzZs2JDczSMiItIqurq6KZY0UNqX5MRu7ty5AACVSoXly5ertYbFxsbi1KlTyJ8/f7JWPmXKFNjb22PVqlVKmZOTk/J/EcHs2bMxYsQINGzYEADw559/wsbGBj4+PmjZsiVu376NAwcO4NKlS0or37x581C3bl1Mnz4d2bNnT1ZMREREROlVkhO7+D50IoLFixerZf8GBgZwdHTE4sWLk7Xy3bt3o1atWmjevDlOnjyJHDlyoFu3bujUqROAT2PmvXz5EjVq1FDmsbS0RNmyZXH+/Hm0bNkS58+fh5WVlZLUAUCNGjWgo6ODixcvonHjxsmKiYiIiCi9SnJi5+/vDwCoWrUqduzYoXa59Hs9evQIixYtQr9+/TBs2DBcunQJvXr1goGBAby8vPDy5UsAgI2Njdp8NjY2yrSXL18m6u+np6eHzJkzK3U+FxkZicjISOU1x98jIiIibZDsPnbHjx9PsZXHxcWhVKlSmDhxIgCgePHiuHnzJhYvXgwvL68UW8/nJk2ahDFjxvy05RMRERFpQrITu6ZNm6JMmTIYPHiwWvnUqVNx6dIlbN26NcnLsrOzUx5PFq9AgQLYvn07ACi3/QYGBsLOzk6pExgYCFdXV6XO57dyx8TE4O3bt1+9bXjo0KFqz7UNDQ2Fvb19kuOmtM3P/4mmQyAiItKIZD9S7NSpU198JmydOnVw6tSpZC3L3d0dd+/eVSu7d+8eHBw+Dajo5OQEW1tbHD16VJkeGhqKixcvws3NDQDg5uaGkJAQXL58Walz7NgxxMXFoWzZsl9cr6GhISwsLNT+iIiIiNK7ZLfYhYWFfXFYE319/WT3Vevbty/Kly+PiRMnokWLFvD19cXSpUuxdOlSAJ/uwO3Tpw/Gjx+PPHnyKMOdZM+eHY0aNQLwqYWvdu3a6NSpExYvXozo6Gj06NEDLVu25B2xRERElKEku8WuSJEiyvNhE9q0aVOiy6rfUrp0aezcuRMbN25E4cKFMW7cOMyePRutWrVS6gwaNAg9e/ZE586dUbp0aYSFheHAgQPKGHYAsH79euTPnx/Vq1dH3bp1UaFCBSU5JCIiIsookt1iN3LkSDRp0gQPHz5EtWrVAABHjx7Fxo0bk9W/Ll79+vVRv379r05XqVQYO3Ysxo4d+9U6mTNn5mDERERElOElO7Hz9PSEj48PJk6ciG3btsHY2BhFixbFkSNHULly5Z8RIxERERElQbITOwCoV68e6tWrl9KxEBEREdEPSHYfOyIiIiJKm5LdYqejowOVSvXV6bGxsT8UEBERERF9n2Qndjt37lR7HR0djatXr2LNmjV8mgMRERGRBiU7sWvYsGGismbNmqFQoULYvHkzOnbsmCKBEREREVHypFgfu3Llyqk9IYKIiIiIUleKJHYfP37E3LlzkSNHjpRYHBERERF9h2Rfis2UKZPazRMigvfv38PExATr1q1L0eCIiIiIKOmSndjNmjVLLbHT0dGBtbU1ypYti0yZMqVocERERESUdMlO7Nq1a/cTwiAiIkqb/PyfaDoEoiRLUmJ348aNJC+waNGi3x0MEREREX2/JCV2rq6uUKlUEBEA4ADFRERERGlQku6K9ff3x6NHj+Dv748dO3bAyckJCxcuxNWrV3H16lUsXLgQzs7O2L59+8+Ol4iIiIi+Ikktdg4ODsr/mzdvjrlz56Ju3bpKWdGiRWFvb4+RI0eiUaNGKR4kEREREX1bssex8/Pzg5OTU6JyJycn3Lp1K0WCIiIiIqLkS3ZiV6BAAUyaNAlRUVFKWVRUFCZNmoQCBQqkaHBERERElHTJHu5k8eLF8PT0RM6cOZU7YG/cuAGVSoU9e/akeIBERERElDTJTuzKlCmDR48eYf369bhz5w4A4JdffsFvv/0GU1PTFA+QiIiIiJIm2YkdAJiamqJz584pHQsRERER/YDvSuwePnyI2bNn4/bt2wCAQoUKoVevXnB2dk7R4IiIiIgo6ZJ988TBgwdRsGBB+Pr6omjRoihatCguXLiAQoUK4fDhwz8jRiIiIiJKgmS32A0ZMgR9+/bF5MmTE5UPHjwYHh4eKRYcERERESVdslvsbt++jY4dOyYq79ChA8exIyIiItKgZCd21tbWuHbtWqLya9euIVu2bCkRExERERF9h2Rfiu3UqRM6d+6MR48eoXz58gCAs2fPYsqUKejXr1+KB0hERERESZPsxG7kyJEwNzfHjBkzMHToUABA9uzZ4e3tjV69eqV4gERERESUNMlK7GJiYrBhwwb89ttv6Nu3L96/fw8AMDc3/ynBEREREVHSJauPnZ6eHrp06YKIiAgAnxI6JnVEREREaUOyb54oU6YMrl69+jNiISIiIqIfkOw+dt26dUP//v3x77//omTJkomeD1u0aNEUC46IiIiIki7ZiV3Lli0BQO1GCZVKBRGBSqVCbGxsykVHREREREmW7MTO39//Z8RBRERJ5Of/RNMhEFEalazELjQ0FPfu3UNUVBTKlCkDa2vrnxUXERERESVTkhO7a9euoW7duggMDISIwNzcHFu2bEGtWrV+ZnxERERElERJvit28ODBcHJywpkzZ3D58mVUr14dPXr0+JmxEREREVEyJLnF7vLlyzh06BBKlCgBAFi5ciUyZ86M0NBQWFhY/LQAiYiIiChpktxi9/btW+TMmVN5bWVlBVNTU7x58+anBEZEREREyZOsmydu3bqFly9fKq9FBLdv31YeLQZwHDsiIiIiTUlWYle9enWIiFpZ/fr1OY7dNxRZU0TTIXwXPy8/TYdAREREyZDkxI7j1xERERGlbUlO7BwcHH5mHERERET0g5J88wQRERERpW1M7IiIiIi0BBM7IiIiIi2RpMRu9+7diI6O/tmxEBEREdEPSFJi17hxY4SEhAAAdHV1ERQU9DNjIiIiIqLvkKTEztraGhcuXAAAZbw6IiIiIkpbkjTcSZcuXdCwYUOoVCqoVCrY2tp+tS4HKCYiIiLSjCQldt7e3mjZsiUePHiABg0aYNWqVbCysvrJoRERERFRciR5gOL8+fMjf/78GD16NJo3bw4TE5OfGRcRpSN8bB4RUdqQrGfFAsDo0aMBAK9evcLdu3cBAPny5YO1tXXKRkZEREREyZLscezCw8PRoUMHZM+eHZUqVUKlSpWQPXt2dOzYEeHh4T8jRiIiIiJKgmQndn379sXJkyexe/duhISEICQkBLt27cLJkyfRv3//nxEjERERESVBsi/Fbt++Hdu2bUOVKlWUsrp168LY2BgtWrTAokWLUjI+IiIiIkqi77oUa2Njk6g8W7ZsP3QpdvLkyVCpVOjTp49SFhERge7duyNLliwwMzND06ZNERgYqDbfkydPUK9ePZiYmCBbtmwYOHAgYmJivjsOIiIiovQq2Ymdm5sbRo8ejYiICKXs48ePGDNmDNzc3L4riEuXLmHJkiUoWrSoWnnfvn2xZ88ebN26FSdPnsTz58/RpEkTZXpsbCzq1auHqKgonDt3DmvWrMHq1asxatSo74qDiIiIKD1L9qXYOXPmoFatWsiZMyeKFSsGALh+/TqMjIxw8ODBZAcQFhaGVq1aYdmyZRg/frxS/u7dO6xYsQIbNmxAtWrVAACrVq1CgQIFcOHCBZQrVw6HDh3CrVu3cOTIEdjY2MDV1RXjxo3D4MGD4e3tDQMDg2THQ0RERJReJbvFrnDhwrh//z4mTZoEV1dXuLq6YvLkybh//z4KFSqU7AC6d++OevXqoUaNGmrlly9fRnR0tFp5/vz5kStXLpw/fx4AcP78eRQpUkTt0nCtWrUQGhqKf/75J9mxEBEREaVnyW6xAwATExN06tTph1e+adMmXLlyBZcuXUo07eXLlzAwMEj0hAsbGxu8fPlSqfN5f7/41/F1viQyMhKRkZHK69DQ0O/dBCIiIqI0I9ktdinl6dOn6N27N9avXw8jI6NUXfekSZNgaWmp/Nnb26fq+omIiIh+Bo0ldpcvX0ZQUBBKlCgBPT096Onp4eTJk5g7dy709PRgY2ODqKgohISEqM0XGBgIW1tbAICtrW2iu2TjX8fX+ZKhQ4fi3bt3yt/Tp09TduOIiIiINEBjiV316tXh5+eHa9euKX+lSpVCq1atlP/r6+vj6NGjyjx3797FkydPlLtv3dzc4Ofnh6CgIKXO4cOHYWFhgYIFC3513YaGhrCwsFD7IyIiIkrvvquPXUowNzdH4cKF1cpMTU2RJUsWpbxjx47o168fMmfODAsLC/Ts2RNubm4oV64cAKBmzZooWLAg2rRpg6lTp+Lly5cYMWIEunfvDkNDw1TfJkobHCM2aDqE7xKg6QCIiCjdS3aLXe7cufHmzZtE5SEhIcidO3eKBBVv1qxZqF+/Ppo2bYpKlSrB1tYWO3bsUKbr6upi79690NXVhZubG1q3bo22bdti7NixKRoHERERUXqQ7Ba7gIAAxMbGJiqPjIzEs2fPfiiYEydOqL02MjLCggULsGDBgq/O4+DggL/++uuH1ktERESkDZKc2O3evVv5/8GDB2Fpaam8jo2NxdGjR+Ho6JiiwRERERFR0iU5sWvUqBEAQKVSwcvLS22avr4+HB0dMWPGjBQNjoiIiIiSLsmJXVxcHADAyckJly5dQtasWX9aUERERESUfMnuY+fv7/8z4iAiIiICABRZU0TTIXwXPy8/TYfwfcOdHD16FEePHkVQUJDSkhdv5cqVKRIYERERESVPshO7MWPGYOzYsShVqhTs7OygUql+RlxERERElEzJTuwWL16M1atXo02bNj8jHiIiIiL6TskeoDgqKgrly5f/GbEQERER0Q9IdmL3+++/Y8OG9PnIJiIiIiJtluxLsREREVi6dCmOHDmCokWLQl9fX236zJkzUyw4IiIiIkq6ZCd2N27cgKurKwDg5s2batN4IwURERGR5iQ7sTt+/PjPiIOIiIiIflCy+9gRERERUdqU7Ba7qlWr/ucl12PHjv1QQERERET0fZKd2MX3r4sXHR2Na9eu4ebNm/Dy8kqpuIiIiIgomZKd2M2aNeuL5d7e3ggLC/vhgIiIiIjo+6RYH7vWrVvzObFEREREGpRiid358+dhZGSUUosjIiIiomRK9qXYJk2aqL0WEbx48QJ///03Ro4cmWKBEREREVHyJDuxs7S0VHuto6ODfPnyYezYsahZs2aKBUZEREREyZPsxG7VqlU/Iw4iIiIi+kHJTuziXb58Gbdv3wYAFCpUCMWLF0+xoIiIiIgo+ZKd2AUFBaFly5Y4ceIErKysAAAhISGoWrUqNm3aBGtr65SOkYiIiIiSINl3xfbs2RPv37/HP//8g7dv3+Lt27e4efMmQkND0atXr58RIxERERElQbJb7A4cOIAjR46gQIECSlnBggWxYMEC3jxBREREpEHJTuzi4uKgr6+fqFxfXx9xcXEpEhQREVFa4RixQdMhfLcATQdAqS7Zl2KrVauG3r174/nz50rZs2fP0LdvX1SvXj1FgyMiIiKipEt2Yjd//nyEhobC0dERzs7OcHZ2hpOTE0JDQzFv3ryfESMRERERJUGyL8Xa29vjypUrOHLkCO7cuQMAKFCgAGrUqJHiwWkLP/8nmg6BiIiIMoDvGsdOpVLBw8MDHh4eKR0PEREREX2nJF+KPXbsGAoWLIjQ0NBE0969e4dChQrh9OnTKRocERERESVdkhO72bNno1OnTrCwsEg0zdLSEn/88QdmzpyZosERERERUdIlObG7fv06ateu/dXpNWvWxOXLl1MkKCIiIiJKviQndoGBgV8cvy6enp4eXr16lSJBEREREVHyJTmxy5EjB27evPnV6Tdu3ICdnV2KBEVEREREyZfkxK5u3boYOXIkIiIiEk37+PEjRo8ejfr166docERERESUdEke7mTEiBHYsWMH8ubNix49eiBfvnwAgDt37mDBggWIjY3F8OHDf1qgRERERPTfkpzY2djY4Ny5c+jatSuGDh0KEQHwaUy7WrVqYcGCBbCxsflpgRIRERHRf0vWAMUODg7466+/EBwcjAcPHkBEkCdPHmTKlOlnxUdERERESfRdT57IlCkTSpcundKxEBFREjhGbNB0CN8lQNMBEGUASb55goiIiIjSNiZ2RERERFqCiR0RERGRlmBiR0RERKQlvuvmCSKihPz8n2g6BCIiAlvsiIiIiLQGEzsiIiIiLcHEjoiIiEhLMLEjIiIi0hJM7IiIiIi0BBM7IiIiIi3BxI6IiIhISzCxIyIiItISTOyIiIiItAQTOyIiIiItodHEbtKkSShdujTMzc2RLVs2NGrUCHfv3lWrExERge7duyNLliwwMzND06ZNERgYqFbnyZMnqFevHkxMTJAtWzYMHDgQMTExqbkpRERERBqn0cTu5MmT6N69Oy5cuIDDhw8jOjoaNWvWxIcPH5Q6ffv2xZ49e7B161acPHkSz58/R5MmTZTpsbGxqFevHqKionDu3DmsWbMGq1evxqhRozSxSUREREQao6fJlR84cEDt9erVq5EtWzZcvnwZlSpVwrt377BixQps2LAB1apVAwCsWrUKBQoUwIULF1CuXDkcOnQIt27dwpEjR2BjYwNXV1eMGzcOgwcPhre3NwwMDDSxaURERESpLk31sXv37h0AIHPmzACAy5cvIzo6GjVq1FDq5M+fH7ly5cL58+cBAOfPn0eRIkVgY2Oj1KlVqxZCQ0Pxzz//pGL0RERERJql0Ra7hOLi4tCnTx+4u7ujcOHCAICXL1/CwMAAVlZWanVtbGzw8uVLpU7CpC5+evy0L4mMjERkZKTyOjQ0NKU2g4iIiH6Qn/8TTYeQbqWZFrvu3bvj5s2b2LRp009f16RJk2Bpaan82dvb//R1EhEREf1saSKx69GjB/bu3Yvjx48jZ86cSrmtrS2ioqIQEhKiVj8wMBC2trZKnc/vko1/HV/nc0OHDsW7d++Uv6dPn6bg1hARERFphkYTOxFBjx49sHPnThw7dgxOTk5q00uWLAl9fX0cPXpUKbt79y6ePHkCNzc3AICbmxv8/PwQFBSk1Dl8+DAsLCxQsGDBL67X0NAQFhYWan9ERERE6Z1G+9h1794dGzZswK5du2Bubq70ibO0tISxsTEsLS3RsWNH9OvXD5kzZ4aFhQV69uwJNzc3lCtXDgBQs2ZNFCxYEG3atMHUqVPx8uVLjBgxAt27d4ehoaEmN4+IiIgoVWk0sVu0aBEAoEqVKmrlq1atQrt27QAAs2bNgo6ODpo2bYrIyEjUqlULCxcuVOrq6upi79696Nq1K9zc3GBqagovLy+MHTs2tTaDiIiIKE3QaGInIt+sY2RkhAULFmDBggVfrePg4IC//vorJUMjIiIiSnfSxM0TRERERPTjmNgRERERaQkmdkRERERagokdERERkZZgYkdERESkJdLMs2K1mWPEBk2H8F0CNB0AERERJQtb7IiIiIi0BBM7IiIiIi3BxI6IiIhISzCxIyIiItISTOyIiIiItAQTOyIiIiItwcSOiIiISEtwHDsi+mEcq5GIKG1gix0RERGRlmBiR0RERKQlmNgRERERaQkmdkRERERagokdERERkZZgYkdERESkJZjYEREREWkJJnZEREREWoKJHREREZGWYGJHREREpCX4SDEiIiJKU/iYwu/HFjsiIiIiLcHEjoiIiEhLMLEjIiIi0hJM7IiIiIi0BBM7IiIiIi3BxI6IiIhISzCxIyIiItISTOyIiIiItAQTOyIiIiItwcSOiIiISEswsSMiIiLSEkzsiIiIiLQEEzsiIiIiLcHEjoiIiEhLMLEjIiIi0hJM7IiIiIi0BBM7IiIiIi3BxI6IiIhISzCxIyIiItISTOyIiIiItAQTOyIiIiItwcSOiIiISEswsSMiIiLSEkzsiIiIiLQEEzsiIiIiLcHEjoiIiEhLMLEjIiIi0hJM7IiIiIi0BBM7IiIiIi3BxI6IiIhIS2hNYrdgwQI4OjrCyMgIZcuWha+vr6ZDIiIiIkpVWpHYbd68Gf369cPo0aNx5coVFCtWDLVq1UJQUJCmQyMiIiJKNVqR2M2cOROdOnVC+/btUbBgQSxevBgmJiZYuXKlpkMjIiIiSjXpPrGLiorC5cuXUaNGDaVMR0cHNWrUwPnz5zUYGREREVHq0tN0AD/q9evXiI2NhY2NjVq5jY0N7ty588V5IiMjERkZqbx+9+4dACA0NPSnxBgXGf5Tlvuz/az98bNxf6c+7vPUxf2dutLr/ga4z1Pbz9rf8csVkW/WTfeJ3feYNGkSxowZk6jc3t5eA9GkXZazNR1BxsL9nfq4z1MX93fq4z5PXT97f79//x6Wlpb/WSfdJ3ZZs2aFrq4uAgMD1coDAwNha2v7xXmGDh2Kfv36Ka/j4uLw9u1bZMmSBSqV6qfGm5JCQ0Nhb2+Pp0+fwsLCQtPhaD3u79THfZ66uL9TF/d36kuv+1xE8P79e2TPnv2bddN9YmdgYICSJUvi6NGjaNSoEYBPidrRo0fRo0ePL85jaGgIQ0NDtTIrK6ufHOnPY2Fhka4O0PSO+zv1cZ+nLu7v1MX9nfrS4z7/VktdvHSf2AFAv3794OXlhVKlSqFMmTKYPXs2Pnz4gPbt22s6NCIiIqJUoxWJ3S+//IJXr15h1KhRePnyJVxdXXHgwIFEN1QQERERaTOtSOwAoEePHl+99KqtDA0NMXr06ESXlenn4P5OfdznqYv7O3Vxf6e+jLDPVZKUe2eJiIiIKM1L9wMUExEREdEnTOyIiIiItAQTOyIiIiItwcSOiIgoA9m4caOmQ6CfiIkdEdF3iIuLU3vN+9AoPdi7dy9atWqFUaNGaToU+kmY2BGlEH6xZxxxcXHQ0fl0+jxz5gxiY2PT1eMIKeMqW7YsZs2ahQULFmD48OGaDod+AiZ2pPg8MWGiknQionyxR0REaDga+plEREnqRo4cibZt22LLli2JWvC0Dc8H6V9sbCysra3xxx9/YMKECViwYAGmTZum6bAohWnNAMX0YxK2QNy6dQt58+aFnh4Pj6SKT+pWr16N27dvY/LkyWrlpD3i39MRI0Zg2bJl2LJlCwoUKKB8frRR/A+XS5cuwdfXFy4uLihatCjs7Ow0HRolkYhAV1cXALBq1Sr8888/AIDBgwcjIiICI0eO1GR4aVLCH+zpCb+5SS2pGz16NC5evIguXbqgYcOG6fKg1qQzZ87g6tWryn5LrycG+m8BAQHYv38/Vq5cicqVK+Pt27f4559/4OPjgypVqqBo0aIwNzfXdJgpRqVSwcfHB7/99hvy5s2LBw8eoGnTpujUqRMqVKig6fAoCeLPQyNHjsTixYsxb948lClTBidOnMC0adMQHR2NsWPHajjKtCP+3H3u3DmcOHECuXLlgpubG5ydnTUd2rcJ0f8bMmSIZM2aVfbv3y+BgYFq0+Li4jQUVdqVcJ/ExsaKiEhQUJBkz55d5s6dq6mwKBXcvn1bzM3N5ciRI3Lx4kXp3LmzFC1aVOzs7MTBwUEOHDggIun7cxMTE6PE//TpU/n1119l6dKlIiKyfft2qVKlijRs2FBOnTqlyTApGd68eSPu7u6yZMkSpezFixcyefJkMTY2lokTJ2owurRn9+7dYmBgIBUqVBATExNp1KiR7Nq1S9NhfZP2XjugZDl79iy2bduG/fv3o3bt2jAzM8OTJ0+wceNGvH79GiqVSuv7ECVXwpa4+BZPMzMzNGzYEBcuXICIsF+SFvjScZ8/f340bNgQDRs2RLVq1WBsbIwJEybg+fPnsLCwwPnz5wGkz0vxp06dAgDo6upCpVLB19cXY8aMQXBwMOrUqQMAaNKkCQYOHIjQ0FDMmDEDZ86c0WTIlER6enoICAjA8+fPlTJbW1t4eXmhVKlSGD58OAYMGKDBCDUrNjZWOWc/e/YMu3btwvz583H69GkcPnwYkZGRWLBgAXx8fDQb6DcwsSMAnz7wUVFRMDIywu3btzFq1ChUrVoVAwYMQOHChfH27Vut7kOUHAm/6BcuXIj27dvj1q1biIqKgrGxMZo0aYItW7bgyJEj6fKLnf4nYTeFnTt3YunSpZg4cSJCQkKwZs0a7NmzB8ePH8fs2bNRv359AECWLFmQNWtWTYb93bZs2QJvb2+8fv1aKbt69SoOHDiAixcv4t9//1XK69atiwEDBiA8PByjRo1SkllKG770g8TMzAyNGzfG1atXlT52wKfkztXVFRUqVMC9e/cy3A/S/fv3K30Q43/MDBo0CA8ePEClSpUAAOXLl4e3tzf09PSwcOFC7N69W8NRfx2/qTOgL33gM2XKBCcnJ7Rs2RJubm4IDQ2Ft7c3Lly4AH19/TT/CyU1xX/RL1q0CGZmZjh79iw6duyIhg0b4tq1a3B3d0e/fv2wcuVKhIaGajha+hHx7/WgQYPQt29fbN++HXv27IGLiwuOHDmCqlWronTp0vjw4QNu374NT09PvH37Fl26dNFw5N/Hzc0Na9asQdasWREQEAAA+OOPPzB9+nTY2tpi3rx58PPzU+rXrVsX3bp1g7m5Oezt7TUUNX0u4Q+SZ8+ewd/fH8Cn47lhw4a4e/culixZguvXrwMAwsLC8PTpU7Rr1w67d++GSqXKMMndnj17MHXqVAQGBiplL168wOXLl/H333/j7t27SnmZMmXg7e2ttNDv27dPEyF/myavA1Pqi+8LJiJy/vx52bVrl5w7d04iIyPl4cOHsnz5cjl48KCEhYWJiEhISIiULFlSdu/eramQ04yE+27KlCmiUqkkICBAoqKiZPv27dK4cWOxt7eXJk2aSJUqVcTNzU2ePn2aaF5KX/7880+xsbGRa9euiYjIwYMHRaVSKZ+JuLg42b59u1SqVEmqVKkiUVFRIvKpj1p6krA/oJ+fn5QuXVomTZqklK1YsUJKlCghHTt2FD8/P7V5488XpHkJ38eRI0dKwYIFxcbGRvLkySPLli0TEREfHx8pWrSoFCtWTKpXry4lSpSQokWLSnR0dKJlaLuQkBB59uyZiIjcvXtX2fajR49KyZIlxdPTU06fPq02z9mzZ6VFixby+PHjVI83KZjYZVCDBg2SfPnyibOzs1SuXFlKlSolL168UKZHRkbKkydPpH79+lKmTJl09yWV0hJu//nz52XEiBFy8ODBRPX27NkjEyZMEGtra1GpVNKxY8fUDJN+0JduBJgwYYL06dNHREQ2btwoFhYWsmjRIhERCQ0Nlbi4OHn79q3s2bNHOU7ivyDTq4CAAGnTpo1UqFBBZsyYoZQvX75cSpQoIZ07d1YSXUqbJk2aJFmyZJHNmzfL6dOnpXPnzpI/f34ZM2aMiIhcvnxZVqxYIR07dpRRo0Ypx2xGOtcnTGDv3LkjpUqVkn79+inle/fulbJly0rz5s3lzJkzavN+/PgxVWNNDiZ2GdD8+fPF2tpazp07JyIiY8aMEZVKJXv37hURkaioKFmwYIHUqlVLypUrl25bIFJC/Bd6vIMHD4qtra3Y2trK33//LSKf9svnLXJPnjyRgQMHSuXKldUSZkq71q5dKyqVStavX69W3r59e2nbtq0cP35czM3NZeHChcq0iRMnyqhRo9Tqa8vn5NGjR9K5c2cpV66cWnK3cuVKcXJykl69eklkZKQGI6QviYuLk9DQUKlYsaLMnDlTbZq3t7fY29vLoUOHvjhvev9B8iPevn0rPXr0kPLly8uwYcOU5G7Pnj1StmxZ+fXXX+X48eOaDTKJmNhlMDExMdKxY0eZNm2aiHy6ndvMzExpov/w4YPExMTI+fPnZenSpVrTAvE9zpw5Iw0aNFDb9r///lu6du0qhoaGMmvWLKX8S0OfPHnyRMzNzeXPP/9MtZjpxwwdOlQMDQ3VkrvDhw+Lq6ur6OnpKS11IiLv378XT09P6du3ryZCTTHxx+6jR4/k/PnzcufOHQkNDRURkQcPHnwxuVu7dq08evRII/HSt4WFhYmrq6tyjoqIiFCm1ahRQ+rVqyciGeuS6+e+dM5++/atDB48WEqXLq2W3O3bt0/y5csn7du3l/DwcI3EmxwcoFjLJexEC3wawuD9+/ewsLDAvn378Ntvv2HatGn4/fffERsbi3Xr1sHY2Bht2rRBuXLlAHy6BTwjPoWibNmy8PHxgUqlwvr169GqVSuULFkSJiYmiIuLw8yZM2FhYYEOHToonY1VKhV0dHQQFxcHe3t7uLm5qd1hSGnbxIkTISJo164dRAStWrVC0aJF4erqipiYGMTExCAsLAwPHjzA8OHD8fLlS+zYsQNA+hyMOj7mnTt3YujQofjw4QNsbW1RsGBBTJo0Cc7Ozhg8eDCmTJmCnTt3Ijw8HCNGjEDr1q01HTr9vy8dd6ampsiZMyfWr1+PPn36wNDQENHR0dDX10eRIkXw7NkzAOlzOJ6UEL/PTpw4gaNHj+LRo0eoW7cumjVrpjyB4+jRowCA8ePHo27dutDV1UW+fPlgbGysydCTRoNJJaWihw8fisinXya9e/eWAgUKiKWlpdplpcDAQKlVq5ZMnz5dU2GmSffv3xdra2upXLmyUubn5yfdu3eX/Pnzy8qVK5XyhL8CN2/eLCqVSu7cuZOa4VIKGDx4sOjr6yutrf7+/uLl5SXOzs5iZmYmxYsXl6pVq2pFN4WDBw+KpaWlzJ07V8LDw2XGjBlibm4uNWvWlCdPnojIp/PHb7/9Jh4eHvLmzRsNR0zxEnYBCQgIkH///VdevnwpIiL37t2THDlySP369SUuLk6ioqIkLi5OKlSoIF27dtVUyGnG9u3bxcrKSn799Vfp27ev6OrqipeXl4SHh0twcLAMHDhQypcvL7179053LZtM7LRUwg/8kSNHJEeOHEr/gJCQEClcuLA4OjrK3bt3JTg4WJ49eyZ16tSRsmXLZsjLrv8lMjJSdu/eLYUKFZLq1asr5Tdu3JAePXpIwYIFZf78+Ynm+/Dhg9y/fz81Q6Vk+q9jfcCAAaKnp6ckd+/evZN///1X9uzZIzdv3lQ+Y+n58xIaGir16tWTCRMmiMinJ6fY29uLh4eHlCxZUjw8POT58+ci8im5ZX/RtOPzu19LlCghmTNnlgoVKsjUqVNF5FM3Ant7e8mdO7dUr15dypQpIwUKFEjXx2xKePjwoeTNm1ftCRwmJiYyZMgQ5XMdEhIi3bp1kxo1akhQUJCmQv0uTOy0UMKkbsuWLdKtWzcxMDCQwoULK51m7927Jw4ODpIvXz7JkSOHlC9fXkqXLq0VLRA/4mvDkoSHh8uePXskX758asmdn5+ftG7dWn799Ve1E21G3X/pxecn6uXLl8ugQYNk5MiRah2k45O7tWvXfnE56XEYm/jj9NatWxIRESF79+6VCxcuyOvXr6VQoULSpUsXEREZNWqUqFQqKV26tNJyR5r3eevRuHHjJHPmzOLj4yPr16+XUaNGiaGhoXJTz9u3b2XkyJEydOhQGT9+vJLUZaTk7vN9dufOHSlbtqyI/K9ls1OnTsr069evi4hIcHBwosdrpgdM7LTYgAEDxMHBQaZNmyZ9+vSRYsWKSaFChZTnWH748EG2bNkiS5Yskf3792foGyVE1L+kN27cKN7e3jJ27Fi5ceOGiHy6vT0+uatRo4ZS9+HDh8q86a3JPiNq2bKlVK9eXRmDasSIEWJqaipNmjQRBwcHcXV1lZ49eyrv5aBBg8TIyEi5wUgb7Nq1SxwdHZU740U+JbceHh7KF9mmTZuUuwEDAgI0FSp9JmGiERoaKh4eHmo39Xz48EFWrlwpZmZmsmbNmi8uIyP88PxSi/rLly8lOjpafH19JWfOnHLmzBlxdnaWTp06Kfvk4sWL0rhxY7l165ZG4k4JTOy0lJ+fnzg5OSlJnIjI8ePHpWnTplKoUCE5cuTIF+fLCB/4bxk0aJDkypVLPDw8pEGDBmJpaamMbxaf3BUsWFCKFSumNl96bL3JiC5cuCBmZmbSvHlzuXjxolStWlXOnj0rIp/e30mTJkmZMmVkyJAhyjxdu3aVSpUqaSrkFBGfqL59+1ZatGghc+bMUZs+fvx4yZUrlwQHB4vIp8/BwIED5d27d6kdKn3FnDlzxMTERN6+fSsin7oH2NnZKWPTxQsNDZWmTZtK9+7dRSTjnpseP34svXr1EhGRHTt2SP78+eXZs2cSFxcnLVq0EF1dXWnRooXaPEOHDpXy5csrfRXTIyZ2WurmzZtiZmaWaBDdgwcPirW1tRQoUECOHTumlLOl6ZNFixZJzpw55dKlSyIisn79elGpVGJoaCj79u0TkU9f/lu3bpVff/01w54w06v4Hy5XrlwRY2NjqVatmlSpUkWtFSQ4OFgGDx4sZcuWldevXyvl6e0z8qVj88SJE+Lu7i5Vq1ZVG4dRRGT//v3i5uYmZcuWlWbNmomJiUm6brXQNosXLxYjIyPZvHmzWnmXLl2kQYMGcvv2bbXyzp07i6enZ2qGmOYsWLBAihcvLjVr1hR9fX21LhU+Pj7KZ+HixYty5MgR6d+/v1hYWCiXYtMrJnZaJv7L5+nTp+Lm5iaTJ09O9Lif+E605cuX5+jxCbx790769esnK1asEJFPA1Oam5vLjBkzpE2bNmJiYqL0v0o4MCtbOdOX+Pfr6tWrkilTJlGpVHLixAm1Ovfv3xeVSiX79+9XK08vyV18Uvf06VNZt26dLFu2TAIDA+Xly5diY2MjKpVKtmzZojZPdHS0rFmzRjp27Ci//vproseGkeYsX75c9PX1ZdeuXWrlERERcuDAASlQoID0799f/vnnHxH51GJXpUqVRAOsZ0RdunQRlUolVapUSTSg9oYNG8TT01P09fWlcOHC4u7urhXfiUzs0rn/ajHq27ev2NnZyaZNm5TkLjg4WJo1aybz5s2TkiVLyty5c1Mr1DTnxYsXcuPGDVm7dq34+fnJx48f5fHjx3L//n25deuWuLi4yLx580REZOfOnaJSqUSlUimX7Sj9+NrnxM/PT8zMzKRevXpy9+5dpTwgIEDy5s2bKOFLD+K39ebNm1KsWDFp3bq1DBo0SCkPDg4WFxcXKV68+FeTt/ibqEjzDh06JCqVKtHl1nbt2imDRi9fvlyKFi0qhQsXlmrVqkmZMmWkcOHCGfLZr/EiIyMlJiZGRo8eLe3atZNKlSpJhw4dvngzxK1bt+T169dKN4T0TiUioumx9Oj7JBx8eOXKlTh//jyMjIxQokQJtG/fHgDQtm1bnDhxApUrV4azszOOHj0KEcGZM2dQvXp1ZMmSBVu2bNHkZmjEjh07sGLFCly5cgXh4eGIiopCzZo1MXr0aJQoUQJbt27FrFmzsG/fPmTKlAknT57Exo0bUbRoUXTu3DlDDticXiX8nDx9+hQfP35E3rx5lUFKr1y5gooVK6JUqVL47bff4OjoiPnz5yMgIADXrl2Drq6uhrcg6eK36Z9//kHFihXRvXt3DBw4EBYWFgA+Hff29vbImzcvXF1dkSNHDixduhQFCxYE8L99JelwsGVtdfToUfTt2xfFihVDz549UaZMGTRv3hzXr1/H4cOH4eDgAAA4d+4cbt++jb///htOTk7o168f9PT0EBMTk6HOV187dmfMmIFt27ahYMGCmDx5MqytrQEADx8+hL29PQwMDFI71J9Hg0klpZBBgwaJnZ2ddO7cWX7//XfJmTOnjB49Wpk+ffp0adWqlZQtW1Zat26tPLy4fv36avUyiqVLl0qmTJlk+vTpcuTIEQkODpaxY8dK/vz5JV++fOLr6yt//fWXqFQquXnzprx+/Vo8PT3VbofPqHcOpzcJW+pGjx4tBQsWlGzZsknJkiVl7969EhISIiKfHohuZWUlKpVK2rZtK3/88Ue6HfrnzZs3UqlSJenRo4da+eTJk0WlUknFihXl0qVLEhISIo6OjlKpUqV036dI2x06dEjKlSsnv/76q1SsWFFcXV2VIWj+66pNejt2f1R8y+Tp06dl5MiRMmzYMLV+dbNnz5by5ctL+/bt5fHjxzJ69GgpXLiw8gg9bcHELp1buXKlODs7y4ULF0TkU58BQ0NDMTIyUutfER0drfQvCAsLkxEjRkjWrFkz3FMRli5dKgYGBrJ9+/ZE07Zs2SJFixaVihUrypUrV6Rp06aiUqkkT548UrhwYeWLPiNe1kjvvL29xc7OTrZu3SohISFSqlQpKVq0qKxYsUJJ7v755x9RqVQyceJEZb70mMDfunVLnJ2d5dixY8qX/qJFi0RfX18WLFggHh4e4uHhIb6+vvLu3TsxNTWVunXrJup/RJqX8Fxz4MABKVWqlGTOnFmtfyTPR+q2b98upqamUrNmTalUqZLo6OhI69atlc/53LlzpUyZMpIjRw7JkSOH8t2pTZjYpTOf/zqbNm2aMmr87t27xcrKSqZPny4TJkz4Yr+MZ8+eSYsWLcTBwUGuXr2aWmGnCcePH1fbJ3FxcRIXF6f25T1v3jwxNTWV7du3S2RkpGzfvl22bNmS4cf4S28SftldvHhRSpcurdwhfvToUTE3NxdXV1exs7OTVatWKX1r7ty5k+77Ja1du1Z0dXXV4n/69KkyZI+fn59Ur15dihcvLm/fvpXAwEC5d++epsKlb0j4Ph47dkzKli0rv/zyi/J+fl4nI/P39xdHR0dZsGCBUnb69GmxsrKStm3bKmXXr1+Xffv2ae34jEzs0qmpU6fKvn37JCIiQh48eCDPnj2TwoULy7Rp00RExNfXVywsLESlUsns2bPV5r1y5Yr4+/trIGrNunfvnlSsWFEaNmyodlIUUU+YCxcunOgylkjGu6yRXn3+4+fly5eycuVKiY2NlWPHjom1tbUsX75cRESKFSsmRYsWlblz58r79++VedJzAn/69GkxNDRUWqUTfunH75ulS5fyiRJpTLdu3b56R+bnLXflypWT5s2by+nTp1MrvDQr4b65d++eODk5KV0L4o/3EydOiJ6e3hev1GgjHU338aOkiYuLU/6/cuVKzJ49G1myZIGhoSGcnZ1x+/ZtxMbGolWrVgAAQ0NDeHp6Yvfu3ejRo4fasooXLw5HR8fUDD9NyJMnD1asWIHIyEhMmDABZ86cUabFd7YNDQ1FREQEsmXLlmj+9NSJPqM6deoUQkNDAQDDhw/HxIkTYWNjA09PT6hUKixcuBCtW7dGu3btAABOTk548eIFLl26BFNTU2U56bmzuaOjIywtLbFmzRo8fvxYrSN5/E0kd+/ehaOjI6ysrDQUJSUUHh6OY8eOoXnz5rh161ai6SqVCvL/9znWqlULY8aMwfPnz+Ht7Y3r16+ndrhpikqlwpYtW7BixQqYm5vj33//xYMHD5TpcXFxKFOmDIoUKYKAgADNBZqKmNilE/EnZF9fX9y4cQPjxo1D2bJllQ+7paUl/v33X2zevBnPnj3DkCFDICKoV68edHV1ERsbq8nw04w8efJg7ty5UKlUGD9+PM6ePas2/dGjR8iZMyfKlSsHAMr+pbQvODgYjRo1QsuWLdGlSxfMnz8fDRo0AABkzZoVMTExeP36NczNzZUk3dzcHAcOHMDq1avVvjzTs5w5c2LhwoU4cOAARo4cqZYohIaGYtCgQVi5ciVGjx4Nc3NzDUZK8UxMTHDx4kXY2dnB09Pzm8ldzZo1MWjQIDg7O6NIkSKpHa7GJfyc3rx5E507d0ZYWBhsbGzg5eWFKVOm4NSpU9DR0YGOjg6MjY1hbGysfI9qOw53ko5cvnwZ7u7uAICpU6eiV69eyrSQkBBMmzYNc+fORdasWZEpUyZcvHgR+vr6HLrgC+7fv49evXpBRDB8+HBUrFgRMTExaNiwIXR0dLBr164McxLQJkFBQXBycoKOjg727t2LypUrq01v2rQpbt26hVq1auHy5csIDg7G9evXoaurqzYsSnoXGxuL5cuXo0ePHnBxcUH58uWhr6+PZ8+e4e+//8Zff/2F4sWLazpMwqf3Kv6HxpMnT1C7dm1YWlpi+fLlKFSoUKL6Xzqfa9Ox+zVf2sabN29i69atiIiIwJQpUwB8arWfPXs2AgIC0L9/f+TMmRP79u3DihUr4OvrC2dnZ02En6qY2KVh8R/ghB/klStXon///qhcuTKmTZuGPHnyKPVDQkLw7NkzPH/+HNWqVYOurm6GG8MoOeKTOx0dHQwbNgwzZ87EnTt3cO3aNejr62eIk6U2iYmJwZ07d1CiRAmYm5vD3d0dK1asgLW1tdpn6ddff0VYWBhMTU2xbt06rX6vL168iKlTp+Lhw4cwNzdHhQoV0LFjR7i4uGg6NPrMkCFDcPv2bTx79gxXr15Fvnz5lHHXMrr4z+ezZ89w5swZxMbGwtzcHJs2bcLBgwfRtGlTLFmyRKl/5swZbNq0CStWrICTkxP09PSwZs2aDPNjholdGpXwi+bDhw9QqVQwMTEBACxZsgTe3t5o27YtunbtqvSX+/yXXMJfgvRl9+/fR9++fXHo0CHkzp0bfn5+0NfXZ0KcTnwpIRMRPH78GOXKlUOJEiXw559/ImvWrF9dhra/1zwPpH2LFi3CkCFDcPDgQWTLlg2vX79Gr1698ObNG/j4+Hyx5S6jiP+M37hxA40bN4aRkRHu37+PokWLIkeOHIiOjsbNmzexe/duuLq6qs37/PlzAICxsTEyZcqkgeg1g4ldGpTwy2rmzJk4fPgwwsPDkS1bNqxatQpmZmZYvHgxxo8fj9atW6Nr167K6OOUfHfu3MHChQsxc+bMDDlSe3qV8HOyf/9+PHjwAJkyZUKBAgVQsmRJ+Pn5oVatWihZsiSWLVsGa2trtGnTBmXKlEGfPn0AfH2Uem2ScBszwvamRwMHDsTjx4/VngL08uVL1K1bF3FxcVi/fn2GTO4SJnVubm7o0aMHevfujb///hsLFy7E+/fv0ahRI+zevRuZM2fGuHHjULRoUYgI4uLiMu4PmtS5+Za+x9ChQyVbtmyyYMEC5YH0FSpUUIZlWLRokeTKlUu6dOkiL1680HC02iE9D3ORUQ0cOFAcHBykcuXKUq9ePbG2tpZ9+/aJyKfnpWbPnl3y5MkjxYsXl3z58vE5qJRmxA/V8fvvv0vhwoWV8vjz0OLFi0WlUomNjY08evRIIzFq2pMnTyRr1qzSvHlztfJFixaJlZWVPH78WHbu3CnVq1eXhg0byo0bNzQUadqhfZ1KtMS9e/ewb98+bNiwAd26dYOOjg5UKhVatWoFMzMzAECXLl3QrVs3vHjxAjY2NhqOWDuwpS59Wb9+PdatW4dNmzbhxIkTqFu3Ll6/fo2QkBAAQKFChXDjxg00bdoULVq0wM2bN5VL7USpLeGwVcD/hlnq3Lkz3r9/j3HjxgH433nIzs4Of/zxB1q0aIFcuXKlbrBpRGxsLJycnBAZGak2RJWzszNUKhU+fPiARo0aoVOnTvj48SN69+6Nf/75R4MRpwGazizpk/iBFON/wZ05c0Zy5colIiJ79uwRMzMzWbx4sYiIhIaGyrJly5R54+fh6OOU0QwbNky6du0qIiI7duwQMzMzWbp0qYiIvH///otPVGCrLGlCwoGzt23bJuPHj5eZM2fK0aNHRURk+PDhUqZMGRk8eLCEhYWJv7+/1KtXTwYMGKDMl1EHSb93757Url1batasKbdu3ZL379+LtbW1DBo0SK3emjVrpEGDBvL06VMNRZo2sI9dGuPn54ciRYrg7du3aNasGcqXL485c+ZgxowZ6Ny5MwDg6tWrGDZsGLy9vdXGsmPfGdJmX7pRYtSoURARlC5dGq1atcK0adPQpUsXiAg2bdqEx48fo0ePHkorN5GmDRo0CBs3bkTZsmWhUqlw6NAhLF68GLVr18bChQuxfPlyvH79GlmzZoWlpSUuXboEfX19TYetcffv30fv3r0RHh6OGzduwMvLC7NmzQIAREdHK/vo/fv3GX58Rl6KTUMOHTqEVq1a4cGDB1CpVMiUKROmT5+Ozp07K0ldREQERowYAUNDQ5QuXRrAp4SOSR1pMxFRkrqEg0rb2NhgwYIF+PXXX5WkDvg0EO/q1asRGhrKpI7SjB07dmDjxo3YsmULtm3bhrp16+Ljx4+IiIhApkyZMHDgQPj5+WHVqlVYunQpLl++zK4D/y9PnjyYM2cOdHV1YWFhgcaNGyvT9PT0lAaOjJ7UAUzs0hQjIyO8evUKd+/eRaZMmTBmzBjkzZsXV65cwcCBAzFnzhzUqVMHT548wdatW6Gjo5OozwaRtomLi1N+uFy8eBFNmjTB7NmzAQDdu3dHgwYNEBMTA0dHR9y7dw93797FL7/8gjdv3mDs2LEajJwyus/Pz48ePUK5cuXg5uaGHTt2oHfv3pg/fz7at2+P0NBQ/PPPPzAzM0OzZs3g4eGhPDWIfX8/yZMnD5YsWYICBQpg4sSJyo88Nm6o46VYDYm/rPT5ZdRevXrh0KFDOHnyJGxsbJRfb0ePHoW9vT3s7e0xb948DstBGYJ8Nji3r68vNm/eDF1dXQwePBgDBw4EADRq1AiXL1/Gu3fvULBgQRgYGODo0aPQ19fnOG6kEQmP3V27dqFkyZLYs2cPbt++jWrVqqFNmzaYPn06/vjjDwCfWvOuXr2Kfv36Zagx177H/fv30a9fP7x+/RqzZs1SHgFJnzCx07CwsDC1S0UXLlxA//790adPHzRv3lwpj46Ohp6ennKiYFJHGcnw4cOxdOlSTJs2DVFRUdi9ezfu3LmD33//HUOGDAEAnDt3Dh8+fECWLFng6uoKHR0dfk5IIxL2B/X29saSJUtw9uxZXL16FV5eXoiMjMS8efOUrgNhYWFo1qwZ8uXLhzlz5mgy9HTjzp07GDlyJGbMmJFh7xj+GiZ2GrR+/Xp07NgRU6ZMQfny5ZU+c02aNEFQUJBya/fnncaFg4xSBvL06VPUr18fQ4cORcuWLQEADx8+xMKFC7Ft2zb06dMHffv2TTSftj4mjNKPp0+fYvr06ahVqxbq1q0LABg/fjxGjRqF5cuXo0iRItDT08PgwYPx6tUrXLp0SekvxnP8t0VFRcHAwEDTYaQ5POulovgcOv7fatWqoV+/fti6dStatmyJIUOG4Pnz55g5cyZCQkKwYsUKAEj05cQPPGUkpqameP36NQIDA5UyZ2dn9OjRAxYWFhgzZoxydxzwv88XkzrSpB07dsDBwQHbt29X69A/YsQI9O/fH97e3qhevTq6dOmCuLg4+Pr6Qk9PD7GxsTzHJxGTui9ji10qSdh6EBQUhNjYWNjZ2QEAAgICcPr0aYwaNQp2dnbInDkzIiIi4OzsjLlz58LQ0FCToROlmi+1sr179w7t2rVTHhmUPXt2ZVrHjh3x+PFjhIaGYtCgQWjWrFlqh0z0RVFRUejRoweWL1+OlStXol27dmrT7969i9DQUFhaWsLFxYVdByjF8CdtKkg4VMO4ceNQv3595dLrrl27lGdYXrx4URmD69ixY7h58yZ/kVCGkTCpu3fvHq5evYqQkBBYWlqiU6dO2LJlCxYvXownT54AAMLDw/Hu3Ts0bdoUlpaWOHr0qCbDpwzsS6MTGBgYYP78+WjZsiX69u2LU6dOAfhfi3K+fPlQunRp5M2bVxnhgEkdpQS22KWiMWPGYNGiRZg3bx6qVauGypUrQ6VSYefOncidO7daS4WPjw88PT2hq6vL/hak9RIe4yNGjMCOHTsQHh4OAwMDtGjRAmPHjsW6deswcOBAFClSBFZWVvj333+VwUr79u2LCxcu4NSpUxzMlVJVwh8k586dQ1RUFExNTZU+03FxcWjZsiWOHTuGnTt3omLFipoMlzIAttilgtjYWAQFBeHAgQNYsGABmjdvjmvXruHJkyfo2bMnXFxc1OoCn4Zv0NXVRUxMDJM60mohISHKMT5t2jQsX74cc+fORUBAAIoVK6YM1Nq2bVts3LgRlSpVAgBUqFABf//9NwDgxYsXKFKkCPvVUapKeDVm+PDhaNmyJbp164by5ctj1KhRePbsGXR0dLBp0yZUq1YNzZo1w5EjRzQcNWm9VHhsWYYUGRkpHz58UF4HBARInjx5JCIiQg4cOCBmZmayaNEiEREJCwuTJUuWyNu3bzUVLpFG7N27V9q1ayfh4eHy/v17qVOnjvK52Ldvn1hYWCjPSI6MjEw0/5MnT2TYsGGSOXNmuXnzZqrGThRvwoQJYmdnJ6dPnxaRT899ValU0rNnT3n27JmIfHpWbPXq1aVOnTqaDJUyACZ2P8G2bdukSZMmUrx4cRk3bpxSXqZMGWnatKmYm5vLsmXLlPL79+9LhQoVZN++fZoIl0hjpk6dKvr6+vLkyRMRESlZsqQ8ePBAjh8/LmZmZkpSFxERIfPnz5crV64o875//1569uwpefLkkWvXrmkkfiJ/f39p0qSJbN++XUREduzYIZkyZZIuXbqIrq6u9OzZUzm+4+LiJDY2VpPhUgbAxC6FLV68WCwsLKRv377Sp08f0dXVlfnz54uIyNy5c8XOzk4aNWqk1A8PD5d69eqJh4eHxMTEaCpsIo0ICwuTsmXLSvfu3UVEpH79+lK4cGExMzOTVatWKfWeP38ulStXVisTEXnz5o3SIkKkCcHBwbJhwwYJCwuT8+fPi729vcydO1dERAYMGCB6enrStm1befXqlTIPkzv6mXgLTgpavnw5evbsiS1btqBRo0YAgMDAQMTGxuL9+/do1KgRbt++jdOnT6Nu3bqwt7fH7du3ERISgsuXL0NXV5eDqlKGYmxsDHd3dxw4cACRkZEYMWIEOnfujAIFCijDQ4SGhqJjx46Ii4tDmzZtlHlFBJkzZ9ZQ5JQRfen8bGVlhXr16sHU1BQ+Pj4oV64cOnbsCODTA+k9PDzg7++vdqzyHE8/E++KTSEnTpxAtWrV4O3tjVGjRinlrq6uiIuLg7+/PypVqoSyZcuiQIECWLduHTJnzoxcuXJh5MiRfPYrZTjxx/ubN2/g7OyMoUOHYvDgwViyZAmmTp0KPT09ODg44P3794iIiICvry+f/UoakzCp27VrF968eQNzc3PUrVsXpqamiI2NRbNmzaCjo4ONGzdCT08PjRs3Ru/evVGtWrVEyyD6WZjYpZD79++jY8eOyJQpE0aOHIlSpUqhadOmuHHjBiZMmAALCwv0798fBgYG2Lt3L3LkyKE2P7+sSNv5+PjAxMQERYoUUQbnjh//a+DAgbh27Rp8fHygp6eHgIAArFmzBgYGBsiePTs6deqk3CXOHz+U2iTBcDx9+/bF2rVrYWFhAZVKhaioKOzatQslSpTAhg0b0Lp1a1SpUgVBQUEAgGvXrvExYZSqmNiloPv376NXr17Q1dVFSEgIPn78iO3bt8PR0REAcOXKFZQqVQo7duxQLtUSZQTBwcFo3bo19u/fjwoVKsDT0xMdO3aElZUVdHR0cOjQITRo0ACbNm366meDP35IExImZJcvX0afPn0we/ZsODk54fXr1xgyZAhOnTqFc+fOIW/evNi6dStOnDgBS0tLjB07VnlMGI9dSi1M7FLY/fv30a1bN1y6dAnLli1D8+bNERcXB5VKhatXr6JNmzZYunQp3N3dNR0qUao7cuQI9u/fj2XLlqFAgQIoWbIkRo8eDRsbG/Tr1w++vr7YtWsXsmTJoulQidRs3rwZq1atgr6+PrZv3648FejDhw9o0qQJgoODcerUKRgZGaklg2xlptTGi/0pLE+ePFi8eDHKlSuHVatW4fTp09DR0YFKpcLo0aORLVs2uLm5aTpMIo2oUaMGZsyYgZs3b6JixYo4e/Ys8uXLh+7duyM4OBgA8O+//2o4SiJ1UVFROHPmDG7fvo179+4pSV1MTAxMTU3RsWNHvH37FoGBgQCgdsmVSR2lNiZ2P4GzszPmzZsHEcHkyZNx5swZNG3aFPfu3cOhQ4eU5wISZURxcXHIlSsXpkyZgr///htDhgzBy5cvsW3bNpw7dw7btm3TdIiUwX1+fjYwMMD48ePRoUMHBAcHo1evXoiMjFSSNjs7O0RHRyM8PFwT4RKp4aXYn+j+/fvo27cvDh06hNy5c8PPzw/6+vpsmif6zOvXr+Hn54fNmzdj/vz5/HyQxiS8c9XX1xdRUVHQ19dH2bJlERERgYkTJ2Lfvn0oXLgwvL29ERwcjGHDhuH9+/fKFRoiTWJi95PduXMHCxcuxMyZMzmkCdFn4vsifX7HID8npAkJj8Nhw4Zh8+bNMDMzg7+/P5o1a4bRo0cja9asmDx5MubOnQtdXV1Uq1YNFhYWWLBgAYyNjTmkCWkcE7tUxC8r0nbnzp2DiYkJChQoAENDQ7VpHO6B0os5c+Zg4sSJ2L17N8qWLYvRo0dj8uTJOHbsGNzd3fHhwwdMnToV+/fvR/ny5TF16lQYGBggIiICRkZGmg6fMjj+rEhFTOpIm61cuRLNmjXDyZMn8f79e6W8Q4cO8PHxUVrmiNKa+D518f9eunQJ/fv3R9myZbF161bMnTsXs2fPhru7Oz5+/AhTU1MMGDAA1apVw4ULFzB27FhERkYyqaM0gYkdEf2w/fv3o1+/fliwYAHat2+PrFmzAvjf2HNjxozB8+fP2WJHaY6IKJdOb9++DQC4desWChQoAF9fX3To0AGTJk1C165dER0djRkzZuDIkSMwNzfH8OHD4eHhgW3btmHKlCma3AwiBRM7IvphZ86cQbFixdC4cWNYWFgo5bq6uujfvz+sra3x4sULDUZIlFjC7gEDBgyAp6cnAMDT0xN9+vRBxYoVsWDBAnTp0gUAEBYWhmPHjuH69euIjY2Fubk5Bg4ciFatWqFt27Ya2w6ihHhtkIh+mIGBAYKCgjB79mzUrVsXgYGBePfuHYyMjBAcHIyAgAAsWrQIXbt2xfPnz+Hh4cHLVqRRCZO6a9eu4eHDh1i7di0AoFatWjh9+jQsLS2V57wGBgaiffv2iIiIQJ8+faCrq4vY2FhYWFhgxIgRbI2mNIM3TxDRD7tz5w42bNiADRs2IGvWrBARhISEwMzMDJaWljh79iyio6ORJ08eWFlZ4cKFC/wipDRh/fr1WLp0KfT09LB7926YmpoCANauXYuVK1fi2rVrcHZ2RlxcHHR1dXHu3Dno6+vzMWGUZjGxI6IfEt/yERsbiyZNmqBSpUro378/IiMjYWhoiIiICAwePBhWVlZo3749cuXKBR0dHd4lSxpx7949BAcHQ1dXF6VKlcLChQsxe/ZshIaG4ubNm0r/UAB48OABzp07h1evXsHe3h5NmzaFrq4uRzigNI1HJhH9kPjkTFdXF/nz54evry9evnwJW1tbAEBERARu3ryJX375BY6OjgDAsb5II9asWYMpU6bg2bNnMDMzQ4sWLTBr1ixkypQJo0aNQvfu3TF79mzY2dkBAFxcXODi4qK2jNjYWCZ1lKbx6CSiJPtWK1vBggXh4+ODOXPmwMPDA3FxcZg1axaCg4PRoUMHpR6TOkptS5YsQe/evTFnzhw4OzvDx8cHGzduRK5cudC3b1+8fv0amzdvxrBhwzBp0iTY2tp+8XIrL79SWsdLsUSUbG/evEGWLFm+OG306NHYtWsXbty4gRIlSsDGxgY+Pj7sl0Qa4+PjgyZNmmDXrl3Kna+hoaGoXLkyHBwc4OPjAwCYN28etmzZgrx582Ls2LHIkSOHBqMm+j782UxE37R79274+fkBAIYMGYKZM2ciOjparU784K5jxozB7t274evri127dmHv3r3KM5KZ1FFqi4yMxMGDB5E7d248fvxYKbewsECRIkWgUqkQHh4OAOjZsyd++eUXnDlzBqtXr9ZQxEQ/hpdiieg/vXnzBkuXLsW5c+fg6emJLVu24OLFi9DX11erp6Ojo/Sdy5UrF3LlyqVMi4uLY78k0ghDQ0OMGjUKhoaGWLt2Ld6/f4+hQ4di//79WLduHY4cOQITExOlNblHjx6wtbVF48aNNR060XfhpVgi+qIFCxage/fuAIDHjx+jQoUKCAwMxIYNG9CsWTNER0cnSu6I0qqXL19iwoQJuHr1KhwcHLBnzx7MmzcPXl5eyg+Sz2/qYdcBSo94KZaIEjl48CBWrVqlXG5VqVRwcnKCm5sb+vTpg2vXril95vjbkNIDW1tbDBs2DCVKlMDRo0dRrVo1eHl5AYByDH9+Uw+TOkqP2GJHRInExsZCpVJBR0cHR48eRfXq1REVFQV/f38MHjwYvr6++Ouvv+Dq6qrMk3CIE6K0KjAwEBMmTMClS5fQqFEjDB48GMC37/gmSi/YYkdEiejq6kJHRwd+fn7w8PBA3759YWBggHz58mHMmDEoW7Ys6tevjytXrgAAfv31V6xatUrDURN9m42NDYYNG4bSpUtj9+7dGDFiBAAwqSOtwRY7IlJ83mohIvjzzz/RrVs3dOnSBTNmzAAAXL9+HePHj8eOHTtQokQJvHnzBnfv3mWfO0o3Xr58iUGDBsHIyAhLlixhYkdag4kdESUyd+5cFC5cGNWqVYOIYP369ejYsSO6d++OmTNnAgBevXqFgwcPIigoCL169YKenh4ftUTpytu3b2FlZcVH3JFWYWJHRIlUqFABd+/exc6dO1GhQgW15K5Hjx5Ky11CvIOQ0is+4o60CY9kogwufmDhhM6cOQM3Nzc0b94cp0+fhkqlQqtWrbBixQosXrwYnTp1SjQPkzpKr5jUkTbh0UyUwcV/qQUHBwP439APu3fvRsmSJdGiRQu15G7WrFm4f/8+hzkhIkqDeCmWKINKePlp48aN6N27N86ePYs8efKo9TeqWbMmHj58iDVr1qBChQpqy2C/JCKitIUtdkQZkIgoSZ2Pjw8qVKgABwcHNGvWDPfv34dKpVIu0Q4YMAD+/v6oU6cOrl+/rrYcJnVERGkLEzuiDCZhK9vEiRPRvXt3fPz4Efv374eBgQEaN26M+/fvK4mfgYEBBg8ejG7duqFw4cKaDJ2IiL6BiR1RBpIwqbt8+TJu3bqFNWvWIG/evMiaNSv2798PExMTeHp6Yt++ffDz88Ps2bMRFRWFKVOmQFdXF7GxsRreCiIi+hr2sSPKIObPn4/Xr1/D29sbGzZswNy5c/Hhwwfs3r0bTk5OynAl4eHhaNSoES5fvgwTExPY2tri3LlzHHyYiCgdYIsdUQawbNky9OrVS7mUmidPHhgZGeHevXs4fPgwgE/DlcTExMDExASHDh3Cnj17sHXrVly4cAH6+vqIiYnR5CYQEVESsMWOSMstWbIEPXr0wJYtW9C4cWOl/MmTJ2jfvj1iY2PRt29fNGzYEAAQFRUFAwMDtWVw8GEiovSBLXZEWszHxwddu3bFjh071JK6IUOGICYmBrNnz4auri4WL16M3bt3A/h0s8Tnv/eY1BERpQ9M7Ii0VGRkJA4ePIjcuXPD399fKW/UqBH2798PIyMjFClSBDNnzkR0dDSWLl2KLVu2AOAwJkRE6RWf1k2kpQwNDTFq1CgYGhpi48aNEBGcOXMGjx8/xo4dO5A9e3aICIoVK4YZM2agbdu2uHjxIlq0aKHp0ImI6Duxjx2Rlnv58iUmTJiAffv24d27d7hx4wZy5Mih9JuLHwLlwYMHyJ07N5+bSUSUjvEMTqTlbG1tMWLECHh6esLJyQkbN24E8KnfXFxcnHLZ1cXFBTo6OhynjogoHWOLHVEGEd9yd+nSJTRu3BiDBw8GwOe9EhFpEyZ2RBnIy5cvMXHiRFy+fBlVq1bF+PHjNR0SERGlIF6KJcpAbG1tMWzYMDg7OyMoKCjRsCZERJS+scWOKAN6+/YtrKysoKOjw0uxRERahIkdUQYWFxfHu2CJiLQIEzsiIiIiLcGf6kRERERagokdERERkZZgYkdERESkJZjYEREREWkJJnZEREREWoKJHREREZGWYGJHRJQMJ06cgEqlQkhIiKZDISJKhIkdEaVb7dq1g0qlSvT34MEDTYeGq1ev4pdffoGdnR0MDQ3h4OCA+vXrY8+ePXyUGxH9NEzsiChdq127Nl68eKH25+TkpNGYdu3ahXLlyiEsLAxr1qzB7du3ceDAATRu3BgjRozAu3fvvjifiCAmJiaVoyUibcLEjojSNUNDQ9ja2qr96erqAgBOnjyJMmXKwNDQEHZ2dhgyZIha4hQZGYlevXohW7ZsMDIyQoUKFXDp0iW15f/111/ImzcvjI2NUbVqVQQEBPxnPB8+fEDHjh1Rr1497Nu3DzVr1kTu3LlRoEABdOzYEdevX4elpSWA/13W3b9/P0qWLAlDQ0OcOXPmm3GtXr0aVlZWauv18fFRe+avt7c3XF1dsWTJEtjb28PExAQtWrT4alJJRNqBiR0RaaVnz56hbt26KF26NK5fv45FixZhxYoVGD9+vFJn0KBB2L59O9asWYMrV67AxcUFtWrVwtu3bwEAT58+RZMmTeDp6Ylr167h999/x5AhQ/5zvYcOHcKbN28waNCgr9ZJmIABwJAhQzB58mTcvn0bRYsW/WZcSfXgwQNs2bIFe/bswYEDB3D16lV069YtWcsgonRGiIjSKS8vL9HV1RVTU1Plr1mzZiIiMmzYMMmXL5/ExcUp9RcsWCBmZmYSGxsrYWFhoq+vL+vXr1emR0VFSfbs2WXq1KkiIjJ06FApWLCg2joHDx4sACQ4OPiLMU2ePFkAyNu3b5UyX19ftRj37NkjIiLHjx8XAOLj46PUTUpcq1atEktLS7X17ty5UxKe0kePHi26urry77//KmX79+8XHR0defHixdd3KhGla3qaTSuJiH5M1apVsWjRIuW1qakpAOD27dtwc3NTax1zd3dHWFgY/v33X4SEhCA6Ohru7u7KdH19fZQpUwa3b99WllG2bFm19bm5uSU7xqJFi+LatWsAgDx58iTqR1eqVCnl/w8fPvxmXEmVK1cu5MiRQy32uLg43L17F7a2tsneDiJK+5jYEVG6ZmpqChcXF02HociTJw8A4O7duyhXrhyAT/0A/yvG+GQ0qXR0dBLdWRsdHZ3MSIlIG7GPHRFppQIFCuD8+fNqCdDZs2dhbm6OnDlzwtnZGQYGBjh79qwyPTo6GpcuXULBggWVZfj6+qot98KFC/+53po1ayJz5syYMmXKd8WdlLisra3x/v17fPjwQakT3yKY0JMnT/D8+XO12HV0dJAvX77vio2I0j4mdkSklbp164anT5+iZ8+euHPnDnbt2oXRo0ejX79+0NHRgampKbp27YqBAwfiwIEDuHXrFjp16oTw8HB07NgRANClSxfcv38fAwcOxN27d7FhwwasXr36P9drZmaG5cuXY9++fahXrx4OHjyIR48e4caNG5g6dSoAKHftfklS4ipbtixMTEwwbNgwPHz48KtxGRkZwcvLC9evX8fp06fRq1cvtGjRgpdhibSZpjv5ERF9Ly8vL2nYsOFXp584cUJKly4tBgYGYmtrK4MHD5bo6Ghl+sePH6Vnz56SNWtWMTQ0FHd3d/H19VVbxp49e8TFxUUMDQ2lYsWKsnLlyv+8eSLepUuXpFmzZpItWzbR09OTLFmySK1atWTTpk3KDR3xN098vqykxLVz505xcXERY2NjqV+/vixdujTRzRPFihWThQsXSvbs2cXIyEiaNWumdlMHEWkflQiHQCci0jbe3t7w8fH54iVaItJevBRLREREpCWY2BERERFpCV6KJSKi/2vHDkgAAAAABP1/3Y/QFREw4dgBAEwIOwCACWEHADAh7AAAJoQdAMCEsAMAmBB2AAATwg4AYELYAQBMBJ1430GQ4+cNAAAAAElFTkSuQmCC\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "import matplotlib.pyplot as plt\n", + "grouped = stacked_all1.groupby(['product_type', 'store']).size().unstack(fill_value=0)\n", + "\n", + "# Step 2: Plot stacked bar chart\n", + "grouped.plot(kind='bar', stacked=True)\n", + "\n", + "# Step 3: Customize\n", + "plt.title('Number of Products by Type and Store')\n", + "plt.xlabel('Product Type')\n", + "plt.ylabel('Count of Products')\n", + "plt.legend(title='Store')\n", + "plt.xticks(rotation=45)\n", + "plt.tight_layout()\n", + "\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 487 + }, + "id": "W2w6IoqZMI4B", + "outputId": "9a647f8d-2774-4066-fc1d-6d6312896945" + }, + "execution_count": 269, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "grouped = stacked_all1.groupby(['store', 'product_type'])['price'].mean().reset_index()" + ], + "metadata": { + "id": "kvxZaMFAMNeq" + }, + "execution_count": 270, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "pivot_df = grouped.pivot(index='product_type', columns='store', values='price')" + ], + "metadata": { + "id": "3nPwO3hzMQ8p" + }, + "execution_count": 271, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "pivot_df.plot(marker='o') # Optional: marker='o' puts dots on data points\n", + "plt.title(\"Average Price per Product Category by Store\")\n", + "plt.xlabel(\"Product Type\")\n", + "plt.ylabel(\"Average Price\")\n", + "plt.xticks(rotation=45) # Rotate category labels if needed\n", + "plt.legend(title='Store')\n", + "plt.grid(True)\n", + "plt.tight_layout()\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 487 + }, + "id": "jzVJgOMwMUj4", + "outputId": "532b0d70-a27c-4abc-d9ac-a179c9af6e73" + }, + "execution_count": 272, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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0(2 Pack ) Dole Canned Crushed Pineapple in 100...1.372500Canned Fruit16.0Fruit & Vegetables
1(12 Cans) Arizona Arnold Palmer Lite Half & Ha...0.476522Beverages138.0Beverages
2(12 Cans) Bush's Original Baked Beans, Canned ...1.498750Protein192.0Protein
3(12 pack) Annie's Yummy Bunnies and Cheddar, M...0.197000Pasta72.0Grain
4(12 pack) Barilla Classic Non-GMO, Kosher Cert...1.380000Pasta192.0Grain
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NaN \n", + "1 (12 Cans) Bush's Original Baked Beans, Canned ... NaN \n", + "2 (12 pack) Annie's Yummy Bunnies and Cheddar, M... NaN \n", + "3 (12 pack) Barilla Classic Non-GMO, Kosher Cert... NaN \n", + "4 (12 pack) Barilla Gluten Free Fettuccine Pasta... NaN \n", + "\n", + " Giant_product_type giant_quantity_oz Giant_food_group walmart_price \\\n", + "0 NaN NaN NaN 0.476522 \n", + "1 NaN NaN NaN 1.498750 \n", + "2 NaN NaN NaN 0.197000 \n", + "3 NaN NaN NaN 1.380000 \n", + "4 NaN NaN NaN 2.620000 \n", + "\n", + " Walmart_product_type walmart_quantity_oz Walmart_food_group target_price \\\n", + "0 Beverages 138.0 Beverages NaN \n", + "1 Protein 192.0 Protein NaN \n", + "2 Pasta 72.0 Grain NaN \n", + "3 Pasta 192.0 Grain NaN \n", + "4 Pasta 144.0 Grain NaN \n", + "\n", + " Target_product_type target_quantity_oz Target_food_group \n", + "0 NaN NaN NaN \n", + "1 NaN NaN NaN \n", + "2 NaN NaN NaN \n", + "3 NaN NaN NaN \n", + "4 NaN NaN NaN " + ], + "text/html": [ + "\n", + "
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productgiant_unit_price_ozGiant_product_typegiant_quantity_ozGiant_food_groupwalmart_priceWalmart_product_typewalmart_quantity_ozWalmart_food_grouptarget_priceTarget_product_typetarget_quantity_ozTarget_food_group
0(12 Cans) Arizona Arnold Palmer Lite Half & Ha...NaNNaNNaNNaN0.476522Beverages138.0BeveragesNaNNaNNaNNaN
1(12 Cans) Bush's Original Baked Beans, Canned ...NaNNaNNaNNaN1.498750Protein192.0ProteinNaNNaNNaNNaN
2(12 pack) Annie's Yummy Bunnies and Cheddar, M...NaNNaNNaNNaN0.197000Pasta72.0GrainNaNNaNNaNNaN
3(12 pack) Barilla Classic Non-GMO, Kosher Cert...NaNNaNNaNNaN1.380000Pasta192.0GrainNaNNaNNaNNaN
4(12 pack) Barilla Gluten Free Fettuccine Pasta...NaNNaNNaNNaN2.620000Pasta144.0GrainNaNNaNNaNNaN
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+ }, + { + "cell_type": "code", + "source": [ + "import pandas as pd\n", + "from thefuzz import fuzz\n", + "from thefuzz import process" + ], + "metadata": { + "id": "6PQlPTWOwmrz" + }, + "execution_count": 288, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "def fuzzy_merge(df1, df2, key1, key2, threshold=80):\n", + " s = df2[key2].dropna().tolist()\n", + "\n", + " matches = df1[key1].apply(lambda x: process.extractOne(x, s, scorer=fuzz.token_sort_ratio) if pd.notnull(x) else None)\n", + "\n", + " df1['best_match'] = matches.apply(lambda x: x[0] if x and x[1] >= threshold else None)\n", + " df1['match_score'] = matches.apply(lambda x: x[1] if x else None)\n", + "\n", + " merged = df1.merge(df2, left_on='best_match', right_on=key2, how='outer', suffixes=('', '_matched'))\n", + " return merged\n", + "\n", + "# Step 1: Rename product columns to 'product'\n", + "g = g.rename(columns={'Giant_product_name': 'product'})\n", + "w = w.rename(columns={'product': 'product'})\n", + "t = t.rename(columns={'product': 'product'})\n", + "\n", + "# Step 2: Normalize product names\n", + "for df in [g, w, t]:\n", + " df['product'] = df['product'].str.lower().str.strip()\n", + "\n", + "# Step 3: Fuzzy join Giant and Walmart\n", + "merged_gw = fuzzy_merge(g, w, key1='product', key2='product', threshold=85)\n", + "\n", + "# Step 4: Prepare Target dataset\n", + "t = t.rename(columns={'product': 'product_target'})\n", + "merged_gw['product'] = merged_gw['product'].fillna(merged_gw['best_match']).str.lower().str.strip()\n", + "\n", + "# Step 5: Fuzzy join with Target\n", + "final_merged = fuzzy_merge(merged_gw, t, key1='product', key2='product_target', threshold=85)\n", + "\n", + "# Step 6: Rename for clarity\n", + "filtered1 = final_merged.rename(columns={\n", + " 'giant_unit_price_oz': 'giant_price',\n", + " 'walmart_price': 'walmart_price',\n", + " 'target_price': 'target_price'\n", + "})\n", + "\n", + "# Step 7: View result\n", + "print(filtered1[['product', 'giant_price', 'walmart_price', 'target_price']].head())" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "WFkjBknIw6vM", + "outputId": "d0f10d5e-1c80-4e62-cdff-dd8a5f1476d9" + }, + "execution_count": 289, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + " product giant_price walmart_price target_price\n", + "0 NaN NaN NaN 0.030391\n", + "1 NaN NaN NaN 0.05858\n", + "2 NaN NaN NaN 0.473333\n", + "3 NaN NaN NaN 0.473333\n", + "4 NaN NaN NaN 0.473333\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import numpy as np" + ], + "metadata": { + "id": "1suF-x_qz97B" + }, + "execution_count": 290, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "fuzzy = filtered1[\n", + " filtered1[['giant_price', 'walmart_price', 'target_price']].notna().sum(axis=1) >= 2\n", + "]\n", + "\n", + "len(fuzzy)\n", + "fuzzy_ar = np.array(fuzzy)\n", + "\n", + "#print(fuzzy_ar.shape)" + ], + "metadata": { + "id": "C-asiPDCzzhv" + }, + "execution_count": 291, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "fuzzy.head()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 747 + }, + "id": "VQmXK-ey0EEP", + "outputId": "303ee6e6-ac04-43f7-e866-2706f96c0a18" + }, + "execution_count": 292, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " product giant_price \\\n", + "10 annie's deluxe shells & cheddar rice & pasta s... 0.6 \n", + "11 annie's deluxe shells & cheddar rice & pasta s... 0.6 \n", + "12 annie's deluxe shells & cheddar rice & pasta s... 0.6 \n", + "13 annie's deluxe shells & cheddar rice & pasta s... 0.6 \n", + "14 annie's deluxe shells & cheddar rice & pasta s... 0.6 \n", + "\n", + " Giant_product_type giant_quantity_oz Giant_food_group \\\n", + "10 Pasta 11.0 Grain \n", + "11 Pasta 11.0 Grain \n", + "12 Pasta 11.0 Grain \n", + "13 Pasta 11.0 Grain \n", + "14 Pasta 11.0 Grain \n", + "\n", + " best_match match_score \\\n", + "10 annie's deluxe gluten free rice pasta shells &... 89.0 \n", + "11 annie's deluxe gluten free rice pasta shells &... 89.0 \n", + "12 annie's deluxe gluten free rice pasta shells &... 89.0 \n", + "13 annie's deluxe gluten free rice pasta shells &... 89.0 \n", + "14 annie's deluxe gluten free rice pasta shells &... 89.0 \n", + "\n", + " product_matched walmart_price Walmart_product_type walmart_quantity_oz \\\n", + "10 NaN NaN NaN NaN \n", + "11 NaN NaN NaN NaN \n", + "12 NaN NaN NaN NaN \n", + "13 NaN NaN NaN NaN \n", + "14 NaN NaN NaN NaN \n", + "\n", + " Walmart_food_group product_target \\\n", + "10 NaN annie's deluxe gluten free rice pasta shells &... \n", + "11 NaN annie's deluxe gluten free rice pasta shells &... \n", + "12 NaN annie's deluxe gluten free rice pasta shells &... \n", + "13 NaN annie's deluxe gluten free rice pasta shells &... \n", + "14 NaN annie's deluxe gluten free rice pasta shells &... \n", + "\n", + " target_price Target_product_type target_quantity_oz Target_food_group \n", + "10 0.535455 Pasta 11.0 Grain \n", + "11 0.535455 Pasta 11.0 Grain \n", + "12 0.535455 Pasta 11.0 Grain \n", + "13 0.535455 Pasta 11.0 Grain \n", + "14 0.535455 Pasta 11.0 Grain " + ], + "text/html": [ + "\n", + "
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productgiant_priceGiant_product_typegiant_quantity_ozGiant_food_groupbest_matchmatch_scoreproduct_matchedwalmart_priceWalmart_product_typewalmart_quantity_ozWalmart_food_groupproduct_targettarget_priceTarget_product_typetarget_quantity_ozTarget_food_group
10annie's deluxe shells & cheddar rice & pasta s...0.6Pasta11.0Grainannie's deluxe gluten free rice pasta shells &...89.0NaNNaNNaNNaNNaNannie's deluxe gluten free rice pasta shells &...0.535455Pasta11.0Grain
11annie's deluxe shells & cheddar rice & pasta s...0.6Pasta11.0Grainannie's deluxe gluten free rice pasta shells &...89.0NaNNaNNaNNaNNaNannie's deluxe gluten free rice pasta shells &...0.535455Pasta11.0Grain
12annie's deluxe shells & cheddar rice & pasta s...0.6Pasta11.0Grainannie's deluxe gluten free rice pasta shells &...89.0NaNNaNNaNNaNNaNannie's deluxe gluten free rice pasta shells &...0.535455Pasta11.0Grain
13annie's deluxe shells & cheddar rice & pasta s...0.6Pasta11.0Grainannie's deluxe gluten free rice pasta shells &...89.0NaNNaNNaNNaNNaNannie's deluxe gluten free rice pasta shells &...0.535455Pasta11.0Grain
14annie's deluxe shells & cheddar rice & pasta s...0.6Pasta11.0Grainannie's deluxe gluten free rice pasta shells &...89.0NaNNaNNaNNaNNaNannie's deluxe gluten free rice pasta shells &...0.535455Pasta11.0Grain
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productgiant_priceGiant_product_typeGiant_food_groupwalmart_priceWalmart_product_typeWalmart_food_grouptarget_priceTarget_product_typeTarget_food_group
10annie's deluxe shells & cheddar rice & pasta s...0.6PastaGrainNaNNaNNaN0.535455PastaGrain
11annie's deluxe shells & cheddar rice & pasta s...0.6PastaGrainNaNNaNNaN0.535455PastaGrain
12annie's deluxe shells & cheddar rice & pasta s...0.6PastaGrainNaNNaNNaN0.535455PastaGrain
13annie's deluxe shells & cheddar rice & pasta s...0.6PastaGrainNaNNaNNaN0.535455PastaGrain
14annie's deluxe shells & cheddar rice & pasta s...0.6PastaGrainNaNNaNNaN0.535455PastaGrain
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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "variable_name": "fuzz_filt" + } + }, + "metadata": {}, + "execution_count": 354 + } + ] + }, + { + "cell_type": "code", + "source": [ + "y_giant = fuzz_filt['giant_price']\n", + "y_walmart = fuzz_filt['walmart_price']\n", + "y_target = fuzz_filt['target_price']" + ], + "metadata": { + "id": "lN-PFLS431T6" + }, + "execution_count": 355, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# Check for missing values in target variables\n", + "print(\"NaNs in y_giant:\", y_giant.isna().sum())\n", + "print(\"NaNs in y_walmart:\", y_walmart.isna().sum())\n", + "print(\"NaNs in y_target:\", y_target.isna().sum())" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "iK7pQgh04Gz9", + "outputId": "26718563-9279-4223-e70e-d0aa9ba04c28" + }, + "execution_count": 356, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "NaNs in y_giant: 59432\n", + "NaNs in y_walmart: 2067201\n", + "NaNs in y_target: 830\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "# Drop rows where any target variable has NaN\n", + "df_clean = fuzz_filt.dropna(subset=['giant_price', 'walmart_price', 'target_price'])\n", + "\n", + "# Redefine target variables after cleaning\n", + "y_giant = df_clean['giant_price']\n", + "y_walmart = df_clean['walmart_price']\n", + "y_target = df_clean['target_price']\n", + "\n", + "df_clean['target_price'] = pd.to_numeric(df_clean['target_price'], errors='coerce')" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "eOf9xRKF4JXA", + "outputId": "0fbc5839-60ff-4ec8-bb7e-44901aa4cad7" + }, + "execution_count": 357, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + ":9: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " df_clean['target_price'] = pd.to_numeric(df_clean['target_price'], errors='coerce')\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "# Fill NaNs with the mean of each target variable\n", + "df_clean['giant_price'].fillna(df_clean['giant_price'].mean(), inplace=True)\n", + "df_clean['walmart_price'].fillna(df_clean['walmart_price'].mean(), inplace=True)\n", + "df_clean['target_price'].fillna(df_clean['target_price'].mean(), inplace=True)\n", + "\n", + "X = df_clean.drop(columns=['product', 'giant_price', 'target_price', 'walmart_price'])\n", + "\n", + "# Redefine target variables\n", + "y_giant = df_clean['giant_price']\n", + "y_walmart = df_clean['walmart_price']\n", + "y_target = df_clean['target_price']" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "YUP-ywEd4RY4", + "outputId": "f10bc6f4-7e51-48e8-9a15-fb1af8880039" + }, + "execution_count": 367, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + ":2: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " df_clean['giant_price'].fillna(df_clean['giant_price'].mean(), inplace=True)\n", + ":3: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " df_clean['walmart_price'].fillna(df_clean['walmart_price'].mean(), inplace=True)\n", + ":4: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " df_clean['target_price'].fillna(df_clean['target_price'].mean(), inplace=True)\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "df_clean.head()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 206 + }, + "id": "iYZ8J_FfYhUd", + "outputId": "7151bfb8-d28f-4373-8756-181425ef8873" + }, + "execution_count": 368, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " product giant_price \\\n", + "298 arizona arnold palmer lite half & half iced te... 0.02 \n", + "299 arizona arnold palmer lite half & half iced te... 0.04 \n", + "300 arizona arnold palmer lite half & half iced te... 0.05 \n", + "3413 chobani non fat black cherry on the bottom gre... 0.19 \n", + "3414 chobani non fat black cherry on the bottom gre... 0.26 \n", + "\n", + " Giant_product_type Giant_food_group walmart_price Walmart_product_type \\\n", + "298 Beverages Beverages 0.000000 Beverages \n", + "299 Beverages Beverages 0.000000 Beverages \n", + "300 Beverages Beverages 0.000000 Beverages \n", + "3413 Yogurt Dairy 0.881132 Yogurt \n", + "3414 Yogurt Dairy 0.881132 Yogurt \n", + "\n", + " Walmart_food_group target_price Target_product_type Target_food_group \\\n", + "298 Beverages 0.030391 Beverages Beverages \n", + "299 Beverages 0.030391 Beverages Beverages \n", + "300 Beverages 0.030391 Beverages Beverages \n", + "3413 Dairy 0.216509 Yogurt Dairy \n", + "3414 Dairy 0.216509 Yogurt Dairy \n", + "\n", + " food_group \n", + "298 Beverages \n", + "299 Beverages \n", + "300 Beverages \n", + "3413 Dairy \n", + "3414 Dairy " + ], + "text/html": [ + "\n", + "
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productgiant_priceGiant_product_typeGiant_food_groupwalmart_priceWalmart_product_typeWalmart_food_grouptarget_priceTarget_product_typeTarget_food_groupfood_group
298arizona arnold palmer lite half & half iced te...0.02BeveragesBeverages0.000000BeveragesBeverages0.030391BeveragesBeveragesBeverages
299arizona arnold palmer lite half & half iced te...0.04BeveragesBeverages0.000000BeveragesBeverages0.030391BeveragesBeveragesBeverages
300arizona arnold palmer lite half & half iced te...0.05BeveragesBeverages0.000000BeveragesBeverages0.030391BeveragesBeveragesBeverages
3413chobani non fat black cherry on the bottom gre...0.19YogurtDairy0.881132YogurtDairy0.216509YogurtDairyDairy
3414chobani non fat black cherry on the bottom gre...0.26YogurtDairy0.881132YogurtDairy0.216509YogurtDairyDairy
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\"Pasta\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Giant_food_group\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"Beverages\",\n \"Dairy\",\n \"Grain\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"walmart_price\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.5332042089033261,\n \"min\": 0.0,\n \"max\": 5.78125,\n \"num_unique_values\": 90,\n \"samples\": [\n 0.09557692307692306,\n 0.27699999999999997,\n 0.0405\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Walmart_product_type\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 12,\n \"samples\": [\n \"Other\",\n \"Pasta\",\n \"Beverages\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Walmart_food_group\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"Beverages\",\n \"Dairy\",\n \"Grain\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"target_price\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.01725974970209263,\n \"min\": 0.0071285714285714286,\n \"max\": 0.6010752688172042,\n \"num_unique_values\": 35,\n \"samples\": [\n 0.021812500000000002,\n 0.3325,\n 0.017085714285714287\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Target_product_type\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 9,\n \"samples\": [\n \"Bread\",\n \"Yogurt\",\n \"Milk\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Target_food_group\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 6,\n \"samples\": [\n \"Beverages\",\n \"Dairy\",\n \"Grain\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"food_group\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"Beverages\",\n \"Dairy\",\n \"Grain\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" + } + }, + "metadata": {}, + "execution_count": 368 + } + ] + }, + { + "cell_type": "code", + "source": [ + "df_clean['food_group'] = df_clean[['Walmart_food_group', 'Giant_food_group', 'Target_food_group']]\\\n", + " .bfill(axis=1).iloc[:, 0]\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "damJixt8YMbW", + "outputId": "45dd7ed6-c640-4e8c-e258-bacc4b2bf733" + }, + "execution_count": 369, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + ":1: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " df_clean['food_group'] = df_clean[['Walmart_food_group', 'Giant_food_group', 'Target_food_group']]\\\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "X_encoded.head()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 273 + }, + "id": "hc154FzR7pMo", + "outputId": "a79401dd-05c3-4e9d-e2b4-5c2ed0cf2adb" + }, + "execution_count": 370, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " Giant_product_type_Bread Giant_product_type_Canned Fruit \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Giant_product_type_Canned Vegetables Giant_product_type_Cheese \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Giant_product_type_Milk Giant_product_type_Pasta \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Giant_product_type_Prepared Food Giant_product_type_Protein \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Giant_product_type_Rice Giant_product_type_Yogurt ... \\\n", + "298 False False ... \n", + "299 False False ... \n", + "300 False False ... \n", + "3413 False True ... \n", + "3414 False True ... \n", + "\n", + " Target_product_type_Milk Target_product_type_Prepared Food \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Target_product_type_Protein Target_product_type_Rice \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Target_product_type_Yogurt Target_food_group_Dairy \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 True True \n", + "3414 True True \n", + "\n", + " Target_food_group_Fruit & Vegetables Target_food_group_Grain \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Target_food_group_Prepared Food Target_food_group_Protein \n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + "[5 rows x 45 columns]" + ], + "text/html": [ + "\n", + "
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Giant_product_type_BreadGiant_product_type_Canned FruitGiant_product_type_Canned VegetablesGiant_product_type_CheeseGiant_product_type_MilkGiant_product_type_PastaGiant_product_type_Prepared FoodGiant_product_type_ProteinGiant_product_type_RiceGiant_product_type_Yogurt...Target_product_type_MilkTarget_product_type_Prepared FoodTarget_product_type_ProteinTarget_product_type_RiceTarget_product_type_YogurtTarget_food_group_DairyTarget_food_group_Fruit & VegetablesTarget_food_group_GrainTarget_food_group_Prepared FoodTarget_food_group_Protein
298FalseFalseFalseFalseFalseFalseFalseFalseFalseFalse...FalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
299FalseFalseFalseFalseFalseFalseFalseFalseFalseFalse...FalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
300FalseFalseFalseFalseFalseFalseFalseFalseFalseFalse...FalseFalseFalseFalseFalseFalseFalseFalseFalseFalse
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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "variable_name": "X_encoded" + } + }, + "metadata": {}, + "execution_count": 370 + } + ] + }, + { + "cell_type": "code", + "source": [ + "X_encoded = pd.get_dummies(X, drop_first=True)" + ], + "metadata": { + "id": "G5sLMGXj8DfZ" + }, + "execution_count": 371, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "from sklearn.linear_model import LinearRegression\n", + "\n", + "model_g = LinearRegression().fit(X_encoded, y_giant)\n", + "model_w = LinearRegression().fit(X_encoded, y_walmart)\n", + "model_t = LinearRegression().fit(X_encoded, y_target)" + ], + "metadata": { + "id": "yywcx-mp4179" + }, + "execution_count": 372, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "from sklearn.metrics import mean_absolute_error\n", + "\n", + "# Evaluate for Giants\n", + "y_giant_pred = model_g.predict(X_encoded)\n", + "giant_r2 = model_g.score(X_encoded, y_giant)\n", + "giant_mae = mean_absolute_error(y_giant, y_giant_pred)\n", + "\n", + "# Evaluate for Walmart\n", + "y_walmart_pred = model_w.predict(X_encoded)\n", + "walmart_r2 = model_w.score(X_encoded, y_walmart)\n", + "walmart_mae = mean_absolute_error(y_walmart, y_walmart_pred)\n", + "\n", + "# Evaluate for Target\n", + "y_target_pred = model_t.predict(X_encoded)\n", + "target_r2 = model_t.score(X_encoded, y_target)\n", + "target_mae = mean_absolute_error(y_target, y_target_pred)\n", + "\n", + "# Print the results\n", + "print(\"Giants R²:\", giant_r2)\n", + "print(\"Giants MAE:\", giant_mae)\n", + "print(\"Walmart R²:\", walmart_r2)\n", + "print(\"Walmart MAE:\", walmart_mae)\n", + "print(\"Target R²:\", target_r2)\n", + "print(\"Target MAE:\", target_mae)\n", + "\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "teqC-mO95X7c", + "outputId": "01445c98-edaa-490a-85ed-6a8d4e9f574b" + }, + "execution_count": 402, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Giants R²: 0.8178788959058548\n", + "Giants MAE: 0.28426788736820696\n", + "Walmart R²: 0.27980200802253996\n", + "Walmart MAE: 0.19415794666534536\n", + "Target R²: 0.4235874386845714\n", + "Target MAE: 0.0010923836461450287\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "print(\"Feature count:\", len(X_encoded.columns)) # Number of features in X\n", + "print(\"Importance count for Giants:\", len(importance_giant)) # Number of feature importances for Giants\n", + "print(\"Importance count for Walmart:\", len(importance_walmart)) # Number of feature importances for Walmart\n", + "print(\"Importance count for Target:\", len(importance_target)) # Number of feature importances for Target\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "HvG4ED6682sQ", + "outputId": "f7bbd63f-f568-46f6-d359-33a366b96f62" + }, + "execution_count": 374, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Feature count: 51\n", + "Importance count for Giants: 29\n", + "Importance count for Walmart: 29\n", + "Importance count for Target: 29\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "print(X_encoded.shape) # Check how many features are in X after transformations\n", + "print(X_encoded.head()) # Check the feature names or actual values\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "fHoZgfN99UPz", + "outputId": "7f4c3169-0c18-4846-d238-307fe6e74317" + }, + "execution_count": 375, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "(7731, 51)\n", + " Giant_product_type_Bread Giant_product_type_Canned Fruit \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Giant_product_type_Canned Vegetables Giant_product_type_Cheese \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Giant_product_type_Milk Giant_product_type_Pasta \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Giant_product_type_Prepared Food Giant_product_type_Protein \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Giant_product_type_Rice Giant_product_type_Yogurt ... \\\n", + "298 False False ... \n", + "299 False False ... \n", + "300 False False ... \n", + "3413 False True ... \n", + "3414 False True ... \n", + "\n", + " Target_food_group_Fruit & Vegetables Target_food_group_Grain \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " Target_food_group_Prepared Food Target_food_group_Protein \\\n", + "298 False False \n", + "299 False False \n", + "300 False False \n", + "3413 False False \n", + "3414 False False \n", + "\n", + " food_group_Dairy food_group_Fruit & Vegetables food_group_Grain \\\n", + "298 False False False \n", + "299 False False False \n", + "300 False False False \n", + "3413 True False False \n", + "3414 True False False \n", + "\n", + " food_group_Other food_group_Prepared Food food_group_Protein \n", + "298 False False False \n", + "299 False False False \n", + "300 False False False \n", + "3413 False False False \n", + "3414 False False False \n", + "\n", + "[5 rows x 51 columns]\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from sklearn.linear_model import LinearRegression\n", + "\n", + "# Fit the linear regression model for each target (Giants, Walmart, and Target)\n", + "model_g = LinearRegression().fit(X_encoded, y_giant)\n", + "model_w = LinearRegression().fit(X_encoded, y_walmart)\n", + "model_t = LinearRegression().fit(X_encoded, y_target)\n", + "\n", + "# Get the absolute value of the coefficients (importance)\n", + "importance_giant = np.abs(model_g.coef_)\n", + "importance_walmart = np.abs(model_w.coef_)\n", + "importance_target = np.abs(model_t.coef_)\n", + "\n", + "# Create DataFrames to store feature importances for each target\n", + "importance_df = pd.DataFrame({\n", + " 'Feature': X_encoded.columns,\n", + " 'Giants Importance': importance_giant,\n", + " 'Walmart Importance': importance_walmart,\n", + " 'Target Importance': importance_target\n", + "})\n", + "\n", + "# Sort each column of feature importances\n", + "importance_df = importance_df.sort_values(by=['Giants Importance', 'Walmart Importance', 'Target Importance'], ascending=False)\n", + "\n", + "# Display the feature importance matrix\n", + "importance_df" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "8HtJ99xD8hjk", + "outputId": "a6cfb83d-cfc1-438e-bbe5-187704184729" + }, + "execution_count": 376, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " Feature Giants Importance \\\n", + "34 Target_product_type_Cheese 3.475858 \n", + "18 Walmart_product_type_Cheese 1.829874 \n", + "3 Giant_product_type_Cheese 1.829874 \n", + "39 Target_product_type_Yogurt 1.205796 \n", + "7 Giant_product_type_Protein 1.164522 \n", + "14 Giant_food_group_Protein 1.164522 \n", + "50 food_group_Protein 1.164522 \n", + "23 Walmart_product_type_Protein 1.164522 \n", + "31 Walmart_food_group_Protein 1.164522 \n", + "40 Target_food_group_Dairy 1.144475 \n", + "35 Target_product_type_Milk 1.125587 \n", + "4 Giant_product_type_Milk 0.708348 \n", + "19 Walmart_product_type_Milk 0.708348 \n", + "25 Walmart_product_type_Yogurt 0.677116 \n", + "37 Target_product_type_Protein 0.666667 \n", + "44 Target_food_group_Protein 0.666667 \n", + "9 Giant_product_type_Yogurt 0.618815 \n", + "10 Giant_food_group_Dairy 0.502711 \n", + "26 Walmart_food_group_Dairy 0.444409 \n", + "45 food_group_Dairy 0.444409 \n", + "22 Walmart_product_type_Prepared Food 0.068505 \n", + "30 Walmart_food_group_Prepared Food 0.068505 \n", + "13 Giant_food_group_Prepared Food 0.068505 \n", + "6 Giant_product_type_Prepared Food 0.068505 \n", + "49 food_group_Prepared Food 0.068505 \n", + "43 Target_food_group_Prepared Food 0.060246 \n", + "36 Target_product_type_Prepared Food 0.060246 \n", + "20 Walmart_product_type_Other 0.058302 \n", + "29 Walmart_food_group_Other 0.058302 \n", + "48 food_group_Other 0.058302 \n", + "47 food_group_Grain 0.046310 \n", + "28 Walmart_food_group_Grain 0.046310 \n", + "12 Giant_food_group_Grain 0.046310 \n", + "33 Target_product_type_Canned Fruit 0.042778 \n", + "41 Target_food_group_Fruit & Vegetables 0.042778 \n", + "21 Walmart_product_type_Pasta 0.039506 \n", + "5 Giant_product_type_Pasta 0.039506 \n", + "8 Giant_product_type_Rice 0.020173 \n", + "24 Walmart_product_type_Rice 0.020173 \n", + "1 Giant_product_type_Canned Fruit 0.016618 \n", + "16 Walmart_product_type_Canned Fruit 0.016618 \n", + "0 Giant_product_type_Bread 0.013369 \n", + "15 Walmart_product_type_Bread 0.013369 \n", + "17 Walmart_product_type_Canned Vegetables 0.011160 \n", + "2 Giant_product_type_Canned Vegetables 0.011160 \n", + "32 Target_product_type_Bread 0.008889 \n", + "42 Target_food_group_Grain 0.006111 \n", + "11 Giant_food_group_Fruit & Vegetables 0.005459 \n", + "46 food_group_Fruit & Vegetables 0.005459 \n", + "27 Walmart_food_group_Fruit & Vegetables 0.005459 \n", + "38 Target_product_type_Rice 0.002778 \n", + "\n", + " Walmart Importance Target Importance \n", + "34 0.510942 0.214116 \n", + "18 0.163911 0.000059 \n", + "3 0.163911 0.000059 \n", + "39 0.293777 0.020616 \n", + "7 0.018031 0.000121 \n", + "14 0.018031 0.000121 \n", + "50 0.018031 0.000121 \n", + "23 0.018031 0.000121 \n", + "31 0.018031 0.000121 \n", + "40 0.175258 0.003144 \n", + "35 0.979977 0.196645 \n", + "4 0.390811 0.000059 \n", + "19 0.390811 0.000059 \n", 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FeatureGiants ImportanceWalmart ImportanceTarget Importance
34Target_product_type_Cheese3.4758580.5109420.214116
18Walmart_product_type_Cheese1.8298740.1639110.000059
3Giant_product_type_Cheese1.8298740.1639110.000059
39Target_product_type_Yogurt1.2057960.2937770.020616
7Giant_product_type_Protein1.1645220.0180310.000121
14Giant_food_group_Protein1.1645220.0180310.000121
50food_group_Protein1.1645220.0180310.000121
23Walmart_product_type_Protein1.1645220.0180310.000121
31Walmart_food_group_Protein1.1645220.0180310.000121
40Target_food_group_Dairy1.1444750.1752580.003144
35Target_product_type_Milk1.1255870.9799770.196645
4Giant_product_type_Milk0.7083480.3908110.000059
19Walmart_product_type_Milk0.7083480.3908110.000059
25Walmart_product_type_Yogurt0.6771160.1157740.000013
37Target_product_type_Protein0.6666670.0030170.011746
44Target_food_group_Protein0.6666670.0030170.011746
9Giant_product_type_Yogurt0.6188150.1062920.000105
10Giant_food_group_Dairy0.5027110.1206090.000223
26Walmart_food_group_Dairy0.4444090.1111260.000131
45food_group_Dairy0.4444090.1111260.000131
22Walmart_product_type_Prepared Food0.0685050.0603590.000121
30Walmart_food_group_Prepared Food0.0685050.0603590.000121
13Giant_food_group_Prepared Food0.0685050.0603590.000121
6Giant_product_type_Prepared Food0.0685050.0603590.000121
49food_group_Prepared Food0.0685050.0603590.000121
43Target_food_group_Prepared Food0.0602460.0273890.003471
36Target_product_type_Prepared Food0.0602460.0273890.003471
20Walmart_product_type_Other0.0583020.0094820.000092
29Walmart_food_group_Other0.0583020.0094820.000092
48food_group_Other0.0583020.0094820.000092
47food_group_Grain0.0463100.0905810.000165
28Walmart_food_group_Grain0.0463100.0905810.000165
12Giant_food_group_Grain0.0463100.0905810.000165
33Target_product_type_Canned Fruit0.0427780.1847320.135775
41Target_food_group_Fruit & Vegetables0.0427780.1847320.135775
21Walmart_product_type_Pasta0.0395060.0135820.000055
5Giant_product_type_Pasta0.0395060.0135820.000055
8Giant_product_type_Rice0.0201730.2729190.000055
24Walmart_product_type_Rice0.0201730.2729190.000055
1Giant_product_type_Canned Fruit0.0166180.1648520.000076
16Walmart_product_type_Canned Fruit0.0166180.1648520.000076
0Giant_product_type_Bread0.0133690.1687570.000055
15Walmart_product_type_Bread0.0133690.1687570.000055
17Walmart_product_type_Canned Vegetables0.0111600.1049160.000076
2Giant_product_type_Canned Vegetables0.0111600.1049160.000076
32Target_product_type_Bread0.0088890.2707010.094182
42Target_food_group_Grain0.0061110.3419510.029876
11Giant_food_group_Fruit & Vegetables0.0054590.0599360.000151
46food_group_Fruit & Vegetables0.0054590.0599360.000151
27Walmart_food_group_Fruit & Vegetables0.0054590.0599360.000151
38Target_product_type_Rice0.0027780.6126520.064306
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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "variable_name": "importance_df", + "summary": "{\n \"name\": \"importance_df\",\n \"rows\": 51,\n \"fields\": [\n {\n \"column\": \"Feature\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 51,\n \"samples\": [\n \"Walmart_product_type_Canned Vegetables\",\n \"Walmart_product_type_Canned Fruit\",\n \"Target_food_group_Grain\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Giants Importance\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.6735323548530344,\n \"min\": 0.002777777777780128,\n \"max\": 3.4758578871133508,\n \"num_unique_values\": 45,\n \"samples\": [\n 0.011159616775124155,\n 0.05830150057704508,\n 0.046310375994213754\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Walmart Importance\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.1788279932320809,\n \"min\": 0.0030166666666658305,\n \"max\": 0.9799768791308989,\n \"num_unique_values\": 48,\n \"samples\": [\n 0.0094821950143619,\n 0.10491568590947142,\n 0.009482195014361301\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Target Importance\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.048806477711709574,\n \"min\": 1.3138586555349586e-05,\n \"max\": 0.21411590824469445,\n \"num_unique_values\": 46,\n \"samples\": [\n 7.55468726925734e-05,\n 9.197010588687257e-05,\n 9.197010588685517e-05\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" + } + }, + "metadata": {}, + "execution_count": 376 + } + ] + }, + { + "cell_type": "code", + "source": [ + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "# Set up the figure\n", + "plt.figure(figsize=(15, 8))\n", + "\n", + "# Extract data to annotate\n", + "data = importance_df.set_index('Feature').T\n", + "\n", + "# Create the heatmap without annotations first\n", + "ax = sns.heatmap(data, cmap='Blues', cbar=True,\n", + " linewidths=1, linecolor='black')\n", + "\n", + "# Annotate manually with custom formatting\n", + "for y in range(data.shape[0]):\n", + " for x in range(data.shape[1]):\n", + " value = data.iloc[y, x]\n", + " text = f\"{value:.2f}\".lstrip('0') # Remove leading zero\n", + " ax.text(x + 0.5, y + 0.5, text,\n", + " ha='center', va='center', color='black', fontsize=12)\n", + "\n", + "# Add title and labels\n", + "plt.title('Feature Importance Comparison across Targets', fontsize=16)\n", + "plt.xlabel('Feature', fontsize=14)\n", + "plt.ylabel('Store', fontsize=14)\n", + "\n", + "# Rotate tick labels\n", + "plt.xticks(rotation=90, ha='center', fontsize=12)\n", + "plt.yticks(rotation=0, fontsize=12)\n", + "\n", + "# Tight layout\n", + "plt.tight_layout()\n", + "plt.subplots_adjust(left=0.15, bottom=0.25, right=0.95, top=0.9)\n", + "\n", + "# Show plot\n", + "plt.show()\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 972 + }, + "id": "5mMBF-R4-NYX", + "outputId": "f9d12e0b-0c0f-42fd-ab84-092281aa4c4b" + }, + "execution_count": 377, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import learning_curve\n", + "from sklearn.linear_model import LinearRegression\n", + "from sklearn.model_selection import train_test_split" + ], + "metadata": { + "id": "YvASGQ0qUVgM" + }, + "execution_count": 378, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "y = pd.concat([y_walmart, y_target, y_giant], axis=1)\n" + ], + "metadata": { + "id": "9RaVnMC5Ueaz" + }, + "execution_count": 379, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "y.columns = ['walmart_price', 'target_price', 'giant_price']" + ], + "metadata": { + "id": "nHv-C0zMUpFT" + }, + "execution_count": 380, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "from sklearn.model_selection import train_test_split\n", + "\n", + "X_train, X_test, y_train, y_test = train_test_split(X_encoded, y, test_size=0.2, random_state=42)" + ], + "metadata": { + "id": "ew8t-OTLUp4C" + }, + "execution_count": 381, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# Initialize the Linear Regression model\n", + "model = LinearRegression()\n", + "\n", + "# Generate the learning curve data\n", + "train_sizes, train_scores, test_scores = learning_curve(\n", + " model, X_train, y_train,\n", + " train_sizes=np.linspace(0.1, 1.0, 10), # Sizes of the training set to test\n", + " cv=5, # 5-fold cross-validation\n", + " scoring='neg_mean_squared_error', # Metric for evaluation (you can change this)\n", + " n_jobs=-1 # Use all CPU cores for parallel processing\n", + ")\n" + ], + "metadata": { + "id": "HjOzfL6xUttD" + }, + "execution_count": 382, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# Calculate the mean and standard deviation of the scores\n", + "train_mean = -train_scores.mean(axis=1) # Negative because we used 'neg_mean_squared_error'\n", + "test_mean = -test_scores.mean(axis=1)\n", + "train_std = train_scores.std(axis=1)\n", + "test_std = test_scores.std(axis=1)" + ], + "metadata": { + "id": "z7KDjtCaVL9y" + }, + "execution_count": 383, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "plt.figure(figsize=(10, 6))\n", + "\n", + "# Plot the training and testing error\n", + "plt.plot(train_sizes, train_mean, label=\"Training Error\", color=\"red\", linestyle='-', marker='o')\n", + "plt.plot(train_sizes, test_mean, label=\"Testing Error\", color=\"blue\", linestyle='-', marker='o')\n", + "\n", + "# Plot the standard deviation as shaded areas\n", + "plt.fill_between(train_sizes, train_mean - train_std, train_mean + train_std, color=\"red\", alpha=0.2)\n", + "plt.fill_between(train_sizes, test_mean - test_std, test_mean + test_std, color=\"blue\", alpha=0.2)\n", + "\n", + "# Add titles and labels\n", + "plt.title(\"Learning Curve for Linear Regression\")\n", + "plt.xlabel(\"Training Set Size\")\n", + "plt.ylabel(\"Mean Squared Error (MSE)\")\n", + "plt.legend()\n", + "plt.grid(True)\n", + "\n", + "# Show the plot\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 564 + }, + "id": "bduY8FLyVOwi", + "outputId": "06b26cb9-32c6-4be1-c198-b39232bdfbf7" + }, + "execution_count": 384, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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+ }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "# X_encoded is your one-hot encoded feature matrix (including food_group info)\n", + "# y contains columns: ['walmart_price', 'target_price', 'giant_price']\n", + "\n", + "model = LinearRegression()\n", + "model.fit(X_encoded, y)\n", + "\n", + "# Predict on the same (or test) set\n", + "y_pred = model.predict(X_encoded) # shape: (n_samples, 3)\n" + ], + "metadata": { + "id": "bLVYynxsVUNp" + }, + "execution_count": 385, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# Turn predictions into a DataFrame\n", + "y_pred_df = pd.DataFrame(y_pred, columns=['walmart_pred', 'target_pred', 'giant_pred'])\n", + "\n", + "# Add the corresponding food_group column from original (unencoded) data\n", + "y_pred_df['food_group'] = df_clean['food_group'].values\n", + "\n", + "y_pred_df\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 687 + }, + "id": "KZWhf8lBVu_x", + "outputId": "656a07a2-068c-4a4a-dbb1-a59c8e265df4" + }, + "execution_count": 389, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " walmart_pred target_pred giant_pred food_group\n", + "0 0.137022 0.308403 0.164056 Beverages\n", + "1 0.137022 0.308403 0.164056 Beverages\n", + "2 0.137022 0.308403 0.164056 Beverages\n", + "3 0.376336 0.285248 0.320976 Dairy\n", + "4 0.376336 0.285248 0.320976 Dairy\n", + "... ... ... ... ...\n", + "7726 0.438817 0.309007 0.506579 Prepared Food\n", + "7727 0.438817 0.309007 0.506579 Prepared Food\n", + "7728 0.438817 0.309007 0.506579 Prepared Food\n", + "7729 0.438817 0.309007 0.506579 Prepared Food\n", + "7730 0.438817 0.309007 0.506579 Prepared Food\n", + "\n", + "[7731 rows x 4 columns]" + ], + "text/html": [ + "\n", + "
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walmart_predtarget_predgiant_predfood_group
00.1370220.3084030.164056Beverages
10.1370220.3084030.164056Beverages
20.1370220.3084030.164056Beverages
30.3763360.2852480.320976Dairy
40.3763360.2852480.320976Dairy
...............
77260.4388170.3090070.506579Prepared Food
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7731 rows × 4 columns

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\n" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "dataframe", + "variable_name": "y_pred_df", + "summary": "{\n \"name\": \"y_pred_df\",\n \"rows\": 7731,\n \"fields\": [\n {\n \"column\": \"walmart_pred\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.28204537489288384,\n \"min\": 1.0547118733938987e-15,\n \"max\": 1.2615064102564078,\n \"num_unique_values\": 20,\n \"samples\": [\n 0.13702206847235765,\n 0.4388170345217887,\n 1.2615064102564078\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"target_pred\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.01123326565872748,\n \"min\": 0.037458333333333704,\n \"max\": 0.5199791666666669,\n \"num_unique_values\": 13,\n \"samples\": [\n 0.3090074914907208,\n 0.30900749149072065,\n 0.30840311650917906\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"giant_pred\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.5731396733209921,\n \"min\": 0.11444444444444483,\n \"max\": 7.320000000000007,\n \"num_unique_values\": 20,\n \"samples\": [\n 0.1640563991323266,\n 0.5065789473684216,\n 0.13888888888888934\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"food_group\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 7,\n \"samples\": [\n \"Beverages\",\n \"Dairy\",\n \"Grain\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" + } + }, + "metadata": {}, + "execution_count": 389 + } + ] + }, + { + "cell_type": "code", + "source": [ + "# Group by food_group and average predictions for each store\n", + "grouped_predictions = y_pred_df.groupby('food_group')[['walmart_pred', 'target_pred', 'giant_pred']].mean()\n", + "\n", + "# Display the result\n", + "print(grouped_predictions)\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "9ztgrmcTZzET", + "outputId": "07bd8d6e-d072-4a7c-fa31-29a8366e3fea" + }, + "execution_count": 390, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + " walmart_pred target_pred giant_pred\n", + "food_group \n", + "Beverages 0.137022 0.308403 0.164056\n", + "Dairy 0.398420 0.309890 1.612684\n", + "Fruit & Vegetables 0.512564 0.308516 0.128463\n", + "Grain 0.329830 0.307722 0.321248\n", + "Other 0.179786 0.309007 0.222857\n", + "Prepared Food 0.438106 0.308917 0.505014\n", + "Protein 0.046910 0.309177 5.996259\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "X_train, X_test, y_train, y_test = train_test_split(X_encoded, y, test_size=0.2, random_state=42)\n", + "\n" + ], + "metadata": { + "id": "A7Ho_-EJZ_Cr" + }, + "execution_count": 393, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "y_pred_test = model.predict(X_test)" + ], + "metadata": { + "id": "g9UtJ6AgaX8a" + }, + "execution_count": 394, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# Predict on test set\n", + "y_pred_test = model.predict(X_test)\n", + "\n", + "# Calculate residuals\n", + "residuals_df = pd.DataFrame({\n", + " 'walmart': y_test['walmart_price'].values - y_pred_test[:, 0],\n", + " 'target': y_test['target_price'].values - y_pred_test[:, 1],\n", + " 'giant': y_test['giant_price'].values - y_pred_test[:, 2],\n", + " 'walmart_pred': y_pred_test[:, 0],\n", + " 'target_pred': y_pred_test[:, 1],\n", + " 'giant_pred': y_pred_test[:, 2]\n", + "})\n", + "\n", + "# Plot\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "fig, axes = plt.subplots(1, 3, figsize=(18, 5), sharey=True)\n", + "\n", + "sns.residplot(x='walmart_pred', y='walmart', data=residuals_df, lowess=True, ax=axes[0], color='blue')\n", + "axes[0].set_title('Walmart Residuals')\n", + "axes[0].set_xlabel('Predicted Price')\n", + "axes[0].set_ylabel('Residual')\n", + "\n", + "sns.residplot(x='target_pred', y='target', data=residuals_df, lowess=True, ax=axes[1], color='green')\n", + "axes[1].set_title('Target Residuals')\n", + "axes[1].set_xlabel('Predicted Price')\n", + "\n", + "sns.residplot(x='giant_pred', y='giant', data=residuals_df, lowess=True, ax=axes[2], color='red')\n", + "axes[2].set_title('Giant Residuals')\n", + "axes[2].set_xlabel('Predicted Price')\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 507 + }, + "id": "LpSud2zyaZdM", + "outputId": "4faf6b82-8035-47ab-d757-73cc48a2640b" + }, + "execution_count": 395, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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fmL09vMO9eTxm+91mq+z5V15ulgsl9Iu0igrprbekTZukzEzpoovMOgMADq5jR2nzZiktreHbOuyww7Ru3To99dRTSklJUUFBgc477zxNnjxZnSIxiSDQiArKCnT2m2dr0/5NymyVqXnj5ik5Ljki+xrVY5RGdh+pFTtWKKcoR+0S2ymrUxY9/ADA4jIyMmoM32xpMTHmyYNAh+6cNavmsoqKyuUEfwAANFs2o1m1gg4uLy9PaWlpys3NVWpqarSrE5CVK6VBgyrv//STNHBgzXLhGKli2zapc+fAttlY75qmUIdwe+op6frrzXkY3W7zeVQN/bzLH3/cDF2DFcx7IdhjOGOGdO+9/r1U0tKku+6Sbr45uG01J3l50ujR5u9Qly7SwoWSRT5iADSyptwWacp1Q8sx4OkBWp2zusby/u36a9XkMFzlBgBokio8FZq9dLauPO7KsLRFPvvsM82YMUOzZs1S9+7dw1JHX1tJUqO3lB55RHrySWnjxoZvKyZGKixkqE8AACwm0PM2AffPycvLC3jnkTxR9PTTT+uhhx7Szp07NWjQID355JMaNmxYUNt4+22z51hDeid9+6101FGV97/5RgqyGvWqLbzxBoDhDrwcjsADP+/6SIduTaEOkXDUUebx9s7t5A37pMoL92Jj/d9fTcGMGdItt9RcnptbubwlBn+ZmWbPHa8dO8wgtFs3szckAETCypUra11us9kUHx+vbt26yel0hrTtFTtWyJXioqcTGl1dgZ8krc5ZrQFPD4hq8Ge7p/bGqTHNgg1SAGhCZnw9Q/ctuU/79+8P2zYvvPBCFRUVqVevXkpMTFSsd6idA/bu3Ru2fTWKv/0tfF+4KyrMuf7uuis82wMAAE1KwLFXq1atAp742O12h1yhg3n77bd100036dlnn9VRRx2lxx57TGPGjNHatWuVnp4e8HauukqaMkW6447Q2ky1HQZvQBOuEKoxAy+Hw3+Y90B7l117beSG+nzppcDLWW2oz6wsKT6+MvSrTXy8Wa6pqKgwf2cOZsoUswdjSxrqs3rgV9XmzeZ6gj8AkTB48GBfu8w7aEPVdlpsbKwuvPBCzZo1S/Hx8UFt+y9z/6L+XfszpxkaVUFZQZ2Bn9fqnNUqKCuI2FCfB1NX4OddR/AHAKGZ8fUM3b7wdpV7yqUwfpQ+9thj4dtYtD38sPlFO5xXPa9bF75tAQCAJiXg4T3/97//+f7/xx9/aMqUKZowYYKOOeYYSdLSpUv18ssva/r06Ro/fnxEKnvUUUfpyCOP1FMHkiaPx6OMjAz97W9/05T6EglVdn+Mjc1VRUWqYmKk6dODC/4CyT0b2g6rPqRnXaoO9blqlXToofU/ZsEC6dxzpaIiKTFRWrvWv4efFNnhIQPVFOoQKV98YQ4FWTVo9fIO79mmjfTxx9KQIcFvPxLH7oUXpCuuqL/c889Ll18e+P6tLC8vsHm5cnMZ6hNApXANoTlv3jz9/e9/16233uob8eDbb7/VjBkzNG3aNFVUVGjKlCm68MIL9fDDDwdVt74P9dV+7VeKM0WzzphF8IdGMfrl0Vr0x6J6y43qPkoLxy9shBpVOljgVxXBX3RV/VprVEkOqn/drWudUS1tCGUd+2Jf7Cu4fbkNty6cc6EKygrMFSWS7leTHWo8asN7xsdLxcXhmdfFa9Qoc14KAABgGYGeUwppTr/Ro0fr8ssv17hx4/yWv/HGG3ruuef0+eefB13h+pSVlSkxMVFz5szROeec41s+fvx47d+/X/Pmzat3G96Dkpi4U4aRrpISm1q3lrZuLZdUIYfDobgqY5oXFxdLkpxOp+x2+4EhPStkt5fLMOwyjMphs+x2s6zH49Q339g1bJhUUVGh8vJy/fvfdv3735Vl77yzRHfeaSguLk4Oh0NSZVmbzaaEhMor8m22EtlshjyeOEmOA0u9dbDJ46ksa7d7y8aqshOnW3Z7mQzDJsOI94U8JSUlMgxDsbGxijnQNcvtdqusrExJSWbZyjqUymbz1LrdwkKbXw+C0tJSeTwev+16PB6VlpZKkhISEnxli4rKVFTkVkVFjNzuWJWWSkVFHuXnl+nYY21+x1eqkM3mkWHYq9TBkM1WpnnzpMTEOMXG2g70MquQVCGn06HExFjFxEgOhyG3u1QOh6Hk5HhfWcMo95V1Out+7SWpvLxcFRX1v0+qvp52u91veLUBA0q0dm1dr6ddyclOdeggFRRIzz1XohNPrPt9UvW4e1/PuLg4xcTUfJ/4v56V7xPD8H/t69ruiBGx+u672t9TVd8nQ4Z4tHRp/a99MO+TsrIyud1uxcTE+IZkMQxDJSUlQZeNj4/39YSp7/Wsr2z//tK6dZW/95J3GDz/z4h+/aTVq4N7n1R9PYN57QMtW9vvfUPK1vZ6BlM2mNc+1PdJba9nON4n4f6MONjr2RzfJ835M6Jq2aqv/d69e9W2bdsGn8waNmyY7r33Xo0ZM8Zv+fz583XXXXfp22+/1fvvv6+bb75ZGzZsCGib3naS43aHbAk2eTwexThi1MrZqrJQ1XNNRi3L6lp+kLK1jSRhyJCtWuHaloVatuo+DeNA2Wr19W2jyvKGlPXWxzCMGs+5tt6a4Sjr5bf8IPUNR9nqw8IGWt+dBTvl9lQZLcS7quo3FZvksDnUMbmj33Z92zEqTyxXf43Nh9v8tlu1bLm7XG7DLbvsinXE+spuzdtaow5Vn3P15Z1TOtc4Ce7lMTy+7XrLVD8RXrW+NdYb/vcNc0Gt2/Ftw6Ya9WloABDo9iK9LwDNUIRCv5KSEpWVlfktC2X73rbSTknpqvyTUC7JY7PJbhiqOoho+YEyDtX5Z82nzGaTR1KcYVT5ZimV2+2yG4acO3dKHTqYz8dmk2GzKc7jqXJWwSxrMwzFV/nsrLPsRRfJNns23xf5vhhyWb4vRub7Yl2vJ+eU6i7LZwSfEdVfz+b8GRHoOaWQJmtZunSphg4dWmP50KFD9e2334ayyXrl5OTI7Xarw4FGjleHDh20c+fOWh9TWlqqvLw8v5sk9elzimJi9is21uyF8/e/vyKXy6UHH3zQ7/EnnXSSXC6Xb/tHHSWlp7+jrCyXMjPv9St72GFnKivLpfj4jb6hPj/88EO5XC699dYdfmXnzRsrl8ulNWvW+JYtWLBALpdLN910k1/Z/v0vVVaWS8nJK3zL0tKWKCvLpT59rvEr+5e/XKmsLJdSU5f5lqWkLFdWlkv9+l3mC/w8Humaa27WMcecqrlzv9Yff5g9/ubM+U1HHHFVjeeWnv6OMjIeVmJi5ZBLMTH71L79u+rbd74mTZLGj5cuukg67LD16thxhQYN2qtjjjGHqOzb161WrfaoVasCtW0rJSWZI1MkJcWpffsEdeoUq65dpV69pMMPt2v48PhqgZ8kxcgw4uQ/Iq0ZDJ51llMnnmjT8cdLxx4rHXtsjI49Nl5Dh8ZqwACpTx+pVy+b+vSJV69eCerQwaY2bczeV2lpsUpLS1B8fJwcDsnpNOuXklKhlJRSdexoqGtXqXt3qWvXYrVuvUtdu+7X4MHS0KHS0UdLHTuuV3r6Ko0YUaZTT5XOPFMaPnynOnf+SoMHr9Yll5hzSLZuLe3atVBt234ghyPX9ywSEn5Xhw6vqHXr/1N+vvmeLCmRbr31LfXp86xuv32HnnxSevpp6eabf1O/fo/o5JPf0YsvmsObvvKKNGrUf3Toof/S9Om/V9nuOvXocae6dJnpdyQ7dXpe3bvfpcTENZozR3r3XenBB//QoYfeq5EjZ+n116XXXpNefVU67bS31b//A9qxo3L+nLi4Xera9VF16vQfv+22a/e+srMf0g03/KSXXpJefll65JFsDRhwn4488lG98Yb05pvSW29J48b9V4ceeo9uvnmp5syR5s6VZs/er8MP/4eOOOIeffCB9OGH0kcfSX/961wNHPh33XbbQs2fL332mfTf/xZo0KCbNWjQTVq0SFq8WPrf/6QbbpirwYP/pr///UN99ZX09dfS//5Xpqysq3XEEVdpyZJSffed9P330l13zdWQIZdrypS39NNPZg/bX36Rhg4dr6FDL9U33+RpzRrzd+PBB9/XkUf+WVOmPK/ffzfnTl+zRurX7y869NDzFRu7u8pxmKvBg4/3/R55f83PPPNMuVwubawy8br3M+KOO/w/I8aODfwz4tJLL5XL5dKKFZWfEUuWLJHL5dI11/h/Rlx55ZVyuVxatqzyM2L58uVyuVy67LLL/Mped911crlcfhdx/Pzzz3K5XDUu+Ljtttvkcrn0ySef+JatX79eLpdL5557rl/ZqVOnyuVyae7cub5lW7dulcvl0qmnnupX9r777pPL5dKbb77pW5aTkyOXy6WRI0f6lX300Uflcrn04osv+pYVFBTI5XLJ5XL5DTs9c+ZMuVwuzZxZ+bvhdrt9ZQsKCnzLX3zxRblcLj366KN++xs5cqRcLpdycnJ8y9588025XC7dd999fmVPPfVUuVwubd261bds7ty5crlcmjp1ql/Zc889Vy6XS+vXr/ct++STT+RyuXTbbbf5lR03bpxcLpd+/vln37LPP/9cLpdL1113nV/Zyy67TC6XS8uXL/ctW7ZsmVwul6688kq/stdcc41cLpeWLFniW7ZixQq5XC5deumlfmVvuukmuVwuLViwwLdszZo1crlcGjt2rF/ZO+64Qy6XSx9++KFv2caNG+VyuXTmmWf6lb333nvlcrn0zjvv+Jbt3LlTLpdLJ510kl/ZBx98UC6XS6+88opv2f79+32vZ1VPPvmkXC6XnnvuOd+ykpISX1lvQ02SnnvuOblcLj355JN+2/CWrTrnzCuvBNaOkOT33m+In3/+WZmZmTWWZ2Zm+t4TgwcP1o4dO+rcRl3tJLfhVoWnQh55VOYu0+6i3ZW3wiq32pbVtfwgZXcV7qpx211Yc3lty0Itu7Ngp++2q3CXdhbu9Fu2s7D25Q0pu6Ngh3YU7NDOwsr/V11W1/KGlPXetudvr7wVbDeXFWz3Wx6ustvyt/ndtheY62pbXvW+23CbZz+9N69qy9yGu8Z2t+ZtNW/5W33b8y3Lq7Isf2udZXcV7lJOUY52F+32K1tbHeqqmyS/41P9VvU9UfU9Wf2WXZTtu+UU5VTeinO0p3iP77a3eK/2lpi3fSX7/G77S/ebt5L9yi3N9bvlleb5bvll+b5bQVmB362wvNB3Kyov8t2KK4r9biUVJb5bqbvU71bmLvPdyj3lvluFp8Lv5jbcvpvH8PhuRrV/ABCowsJCXXvttUpPT1dSUpJat27tdwtEXW2lBPn/SYiV5KwW+HmXx+igf9Z84qqFdZK01enUG+np+rhtW6l3b9/yCf36yTV4sNYkJvqWLWjTRq6sLN1UpZwkXdq/v1xZWVqRXDk09pK0NLl++43vi3xf9OH7oqkpfF9855135HK5dO+9/udmOadk4jPCxGeEqSV+RgR6Timk2bcyMjL0/PPP16jICy+8oIyMjFA2GRHTp0/XPffcU+d6u90cYjGMc0X7ufJKc06v6ioqUmWzuTV0aKy++04qLZVWrWql/Pwh2rx5gF/ZfftGKz//SJWVVYadxcU9tXnzLSor66Tx482AqLRU+r//u1k2W7mKi/v4yhYUDNbKlf9PHk+CbDYpNtY7l9zTkqQLL6y6t36SXq5R3127LqnlObTTrl3mL2qV97kkc4zRVauqLouV1FWS1JTnyvZ4pLIy8yalSJKys6uWSJWUquzs6ssPlyR99VXVZV0lddX+/ZWhj+n0GvstLu7j95p5t71//wRJ0kMPVS3dX9Kd2rxZ+vLLqssnS/Kfh7u4eIA2bHikxv62b/+b7/+Vn5+9JN2njRulb76pWnp8jceXlXXW5s131FienW2+mZ5+uurSDpLMhsrFF1ddfpGki/TEE9ITT3iXtZE0Q5J09tk1yz72mFQ5LUOKJPOP6+jRNcuuWydV/j11SnpJkjRiRNWyF0q6UKtXVy0rSeYfhAMjFx8wVtJY/fqrf9lVq95TdTk5Fygn5wKZ13Wa+vaVdux4Rh5PoSZM6KR27czhdbOzB2vLlpu0ZEm6/v1vc1liorR160jl5e3UkiXJ2rvXXLZ5c5LKyjqouDhJxcXmCC/hHN0FgLX069dP999/v5577jnflWDl5eW6//771a9fP0nStm3balwsVVV97SQAABpLjR7bB3pL2+w23zqPxyPDMBTjiJHZadYmwzDkdrtls9l8V3JLUkV5he/KcW+PYI/HY17pbrP7/nbabDaVlpbK8BiKc8bJYXf49lVaWiq73W5eiX2gDiUlJXK73UqIT5DjwAgrHrdHxcXFstvtSkxM9F21XVRUJHeFWwkJCb56uN1uFRQUyG63KzWl8ursosIilZeXKzEx0XcVvtvtVl5enmw2my+kssmmgoIClZaWKikpyXf1ucft0b59+ySb1K5tO18d8vPzVVJcouTkZCUeCIgMw1D2gS+dHTt09NUhPz9fRYVFSkpOUkpKiu/4ek80derUqXK7efnKz89XcnKyWrVq5dvG1q1bZZNNnTt3lt1ul81mU15ennL35yo5OVlt2rTxld2yZYsMw1BpYqnvcnR7uV0eeQJ6z9Tntttu0+LFi/XMM8/okksu0dNPP61t27Zp1qxZuv/++wPaRjTaSlWvzO9eWqq/1nKR+1urV6vU5v9bc1hhoa7Ztk3JVU5MS1KS261Yj0cyuHACAICWIqThPT/++GP96U9/Uu/evXXUgW5t3377rX777Te99957Ou2008Je0VCG9ywtLfV125TMoRgyMjIUH79LUntVVNjk8Ug33VSho45yq6LCrooKc5jJ0lIpP79cpaVSRUWMyspseuABSfIcuHkHafByq+o1W2lpUm5uXQM3oC7x8Ybi471BbNVj5pE5EIZNlc1gQ5Kh3r0lt9umigqbKiqkigrjwE+pvNzm+z/Q3CQmSklJhhISDCUl2ZSUZFNiopSQ4FFCgqHERCklxaGkJLNsXFy5EhMNJSc7lJrqUGKi5HS65XRWKDFRat3a6Strt5coNtZQXBxDMTAUA0MxNMXhPb/++mudddZZstvtGnhggt+ff/5ZbrdbH330kY4++mi9+uqr2rlzp2699dZat1FXOynj3gwlpiWq1F2q4vJi/fuEf6t3695y2B2+4yZJJaXmcYuLi/MN6VjhrlBFRYXsdrviYuMCKmuz2fyOm7dOMTExle9Xd4XcFeZJrKq/B6GUtTvs5gljSW6PWxXlFZJNcsZVKVtWKhmSI8ZRb9my8jIZHuOgZb09lMrKymQY/mW9J6Gr17e8vFwej0cOh8Pv9yCYst6hzOLi4nzv14qKCrndbr+yhmEctKzdYVdsTOVr7z2WsXGxla9nRYUq3OZrX/V94isbG1v5GXjgNar62s/4eobe//V98ySzw6hsBnokm8cmw2ZIDumcvufo5uE3+71G3pP0brdbFRV1v54xsTG+suUV5bronYuUXZxdo0lvM2wy7IbaJbVTTnGOOQyt22a+jjG1l/U2Tz+/9HPz/XegDt5j6X3tY2JifK+9YRh+r6f39G1ZeZkv2IiJiZFNNnmMytczIb7yc62ivEJuj1sxDv/PtdLSUvNz2Gl+DttsNpWXl5uvfYxDcTFxNV57p9Ppez3LK8yyVbdrk833uxzv9P8M9Hg8vt9773LvZ6szrvIz0Psa2e12v9eopKTE936w2+2yyWZ+RpRXyO7wL1tWWlbjb09FReXnSdXnXFJaIhlSXGyc32dERUWFbLL5hzkHyvr97XF7VFZu/k2rety9zy02xizrDXPKysrMkMhZ+fevrKzM9zfN+3vkdrtr/A22yabSMvPvX1xsXK2/ywnxCX7vKY/bU+Nvmvd3LjGhsgeQ97X3lvWGOd7jXvVvWkV5ha+d5P39NAxDpSXmdr1lve+piooKxThi/EK0qn//fL9z3vcf7STaSVXKDn9huH7c82PlZ36xpAfCM7xnt27d9Morr2jkyJFKTU3VDz/8oN69e+vVV1/Vm2++qY8//rjebdTVVsqV/5x+dZ35qTiwzqHKsxhuSRU2m2yGobgqZb1nmRrjzJEhSW3bykhOlt3pNIc8iouTJzZWRlycbPHxvuWeuDh5HA4pPl4xCQm+suUOhxQbK3tCghwHlntiYlRxYAiluORkX9kym02emBjFJCUpxvwSKrfDoTKbTTanU/GpqeZV+eL7Ip+DLe9zUGJ4T84p8RnBZ0T4zymFFPpJ5lVZzzzzjK+rcP/+/XXVVVdFtKffUUcdpWHDhvm6RXo8HnXr1k3XXnutpkyZUu/jveOvq/GnXW7yYmPNnkNOp9l7yL8nW+3OOkvq2dN8THx85eOr/qzr/7Uti42t7LkUTA+mQN7BhmH25PMGgAe7lZcHVi6Yxzz6qLRvX+DPSZL+9CfJ7Tbr7b1Vv1/bsmBG2D3iCPNY2+3+P6v/v7BQWrHC3H5d7HZzONfkZPN4V715Lyys61bf+qa2jZbC4fAGi5W9EEP9f13rY2LqrwfQnAQ66XIg8vPz9frrr2vdunWSpL59++rPf/6zUlJSGlS3mDtilJCcoBh7jIZ2HqpP//JpjXnagHC79bNb9fDSh+std8sxt+ihkx+qt1x9lm1dpmP+c0z9BYNkTKMnBQAE6vy3z9d7a6qMnhLGOf2Sk5O1atUqdevWTV27dtXcuXM1bNgwbdy4UYcffrjf8GuB8rXjFIUzSocfLlUZgq3ZiYkxTw4dCAqD+hnpx9hpBwMAmoZAzymFfLo1IyOjxhizkXbTTTdp/PjxGjp0qIYNG6bHHntMhYWFmjhxYqPWI9xataoMv7ztil9+qf9xN95ozkvndErVhm8OWnm5d1hLUyChWy2dK5ssm80MMLzz9jW2RYukKsNYB2TOnND2FUxg+v33gZWbP1+aMEEqKpIOTGPgJzXVDHD+/W9pzJjA929lS5dKw4fXX27mTKlHDzM4LSqq/BnK/6tcZNoo3G4pP9+8RUpcXGhhYaD/T0jgOxqan/LycvXr108fffSRrrrqqrBv32azqaCsQDH2GI3pNYbAD43isPTDwlquPjOXz6y/kKRLBl6iV1e+GlBZAj8ACM4r572i9+6rOWVCOPTs2VMbN25Ut27d1K9fP73zzjsaNmyYPvzwQ78hSS3j88+ltm0DL+9wmF/orMJ7xXRhYbRrUpP3RFIo4WKkg0mHo/76A4BV5ORIAweaPWdat5ZWrpTatYt2rSwp4NBv5cqVOuyww2S327Vy5cqDlvUOMxVuF154obKzszV16lTt3LlTgwcP1qeffnrQ+WrqYrPpwHB2NXugVe+NVn3ZQwe5uPj9981yp5wSeF1q6wGWmSlt3lz3Y7p1kx6pMl1bQ0M/Sbr6aumZZxq+HdQ0fHjwoV9T0q6d2aZs08Z8f2/ZYs4lGR8vZWRIxcVm27wlfQ4fE2DngKuvDt8+KyrMY101DGxIiFh9G4WFjf+90DuPZqTmVpXM4C+cvROr/9/bQxpoLLGxsX4TRIedISXFJinWEav5G+brxmNuJPhDxKUnpcthc8ht1P2HyGFzKD0pPSz721cU2BAM+4r2yZhmyHbPwT/oCfwAIHiJsYk6usvRWrZtWdi3PXHiRP300086/vjjNWXKFJ155pl66qmnVF5erkeqnkyxiiFDgiv/2WfS9OnS6tXmF67YWKl7d/Nq3qws84rSsjL55rfx/j/Qnw15jNW43ZVfopsau71xez0G81iHgy/KAAKXnOx/4ceOHVL79uaJtxB657d0AYd+gwcP1s6dO5Wenq7BgwfLZjPnAajOO59BpFx77bW69tprG7SN556TJk4MfVi5Bx80h1A8MJ2hJOmbb6RhwyrvT50q/fOf9W9r6tTal2/aVHfw162buT7cnn3WDP1+/DGw8j/+KA0eHP56SNJvv0mHHBJYOSvYujW48medFZl6hCorS+rb17zAoksX8z3oZRjS3r3mhRhZWdGrYzQYxsHbsOGeKz0mRkp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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "# gradient boosting\n", + "from sklearn.ensemble import HistGradientBoostingRegressor\n", + "from sklearn.multioutput import MultiOutputRegressor\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "# Step 1: Define your features and multi-targets\n", + "X = X_encoded # Your encoded features\n", + "y = df_clean[['walmart_price', 'target_price', 'giant_price']] # Target prices\n", + "\n", + "# Step 2: Split into train/test sets\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n", + "\n", + "# Step 3: Initialize and fit the model\n", + "model = MultiOutputRegressor(HistGradientBoostingRegressor(random_state=42))\n", + "model.fit(X_train, y_train)\n", + "\n", + "# Step 4: Predict on test set\n", + "y_pred_test = model.predict(X_test)\n" + ], + "metadata": { + "id": "fSqSLVdGasjK" + }, + "execution_count": 396, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "from sklearn.metrics import mean_absolute_error, r2_score\n", + "\n", + "print(\"R² scores:\")\n", + "print(\"Walmart:\", r2_score(y_test['walmart_price'], y_pred_test[:, 0]))\n", + "print(\"Target:\", r2_score(y_test['target_price'], y_pred_test[:, 1]))\n", + "print(\"Giant:\", r2_score(y_test['giant_price'], y_pred_test[:, 2]))\n", + "\n", + "print(\"\\nMAE scores:\")\n", + "print(\"Walmart:\", mean_absolute_error(y_test['walmart_price'], y_pred_test[:, 0]))\n", + "print(\"Target:\", mean_absolute_error(y_test['target_price'], y_pred_test[:, 1]))\n", + "print(\"Giant:\", mean_absolute_error(y_test['giant_price'], y_pred_test[:, 2]))\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "eHCjL-vDav0C", + "outputId": "2cda6039-03ae-4d21-b636-8271419a81e4" + }, + "execution_count": 397, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "R² scores:\n", + "Walmart: 0.2986245369722108\n", + "Target: 0.2888565200285652\n", + "Giant: 0.8102036903507994\n", + "\n", + "MAE scores:\n", + "Walmart: 0.18241650899825254\n", + "Target: 0.002397275073270999\n", + "Giant: 0.2916779968067358\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "param_grid = {\n", + " 'estimator__max_iter': [100, 200], # Number of boosting iterations\n", + " 'estimator__max_depth': [None, 5, 10], # Maximum tree depth\n", + " 'estimator__learning_rate': [0.05, 0.1, 0.2], # Boosting shrinkage\n", + " 'estimator__l2_regularization': [0.0, 1.0], # Regularization\n", + "}\n" + ], + "metadata": { + "id": "nuL1bbz_a4si" + }, + "execution_count": 398, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "from sklearn.ensemble import HistGradientBoostingRegressor\n", + "from sklearn.multioutput import MultiOutputRegressor\n", + "from sklearn.model_selection import GridSearchCV\n", + "\n", + "# Base model\n", + "base_model = MultiOutputRegressor(HistGradientBoostingRegressor(random_state=42))\n", + "\n", + "# Grid search\n", + "grid_search = GridSearchCV(\n", + " estimator=base_model,\n", + " param_grid=param_grid,\n", + " scoring='neg_mean_absolute_error', # Use MAE or R^2 depending on goal\n", + " cv=3, # 3-fold cross-validation\n", + " verbose=2,\n", + " n_jobs=-1 # Use all processors\n", + ")\n", + "\n", + "# Fit search on training data\n", + "grid_search.fit(X_train, y_train)\n", + "\n", + "# Best parameters and score\n", + "print(\"Best Parameters:\")\n", + "print(grid_search.best_params_)\n", + "\n", + "print(\"\\nBest Score (Negative MAE):\")\n", + "print(grid_search.best_score_)\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "QIv9rZ8Xa6oU", + "outputId": "58f5a42e-8c3a-496a-d41c-e4cb9deaa4e5" + }, + "execution_count": 399, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Fitting 3 folds for each of 36 candidates, totalling 108 fits\n", + "Best Parameters:\n", + "{'estimator__l2_regularization': 0.0, 'estimator__learning_rate': 0.2, 'estimator__max_depth': 5, 'estimator__max_iter': 200}\n", + "\n", + "Best Score (Negative MAE):\n", + "-0.16563490284611762\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import pandas as pd\n", + "\n", + "# Residuals = actual - predicted\n", + "residuals_df = pd.DataFrame({\n", + " 'walmart': y_test['walmart_price'].values - y_pred_test[:, 0],\n", + " 'target': y_test['target_price'].values - y_pred_test[:, 1],\n", + " 'giant': y_test['giant_price'].values - y_pred_test[:, 2],\n", + " 'walmart_pred': y_pred_test[:, 0],\n", + " 'target_pred': y_pred_test[:, 1],\n", + " 'giant_pred': y_pred_test[:, 2]\n", + "})\n", + "\n", + "# Set up subplots\n", + "fig, axes = plt.subplots(1, 3, figsize=(18, 5), sharey=True)\n", + "\n", + "# Walmart\n", + "sns.residplot(x='walmart_pred', y='walmart', data=residuals_df, ax=axes[0], lowess=True, color='blue')\n", + "axes[0].set_title('Walmart Residuals')\n", + "axes[0].set_xlabel('Predicted Price')\n", + "axes[0].set_ylabel('Residual')\n", + "\n", + "# Target\n", + "sns.residplot(x='target_pred', y='target', data=residuals_df, ax=axes[1], lowess=True, color='green')\n", + "axes[1].set_title('Target Residuals')\n", + "axes[1].set_xlabel('Predicted Price')\n", + "\n", + "# Giant\n", + "sns.residplot(x='giant_pred', y='giant', data=residuals_df, ax=axes[2], lowess=True, color='red')\n", + "axes[2].set_title('Giant Residuals')\n", + "axes[2].set_xlabel('Predicted Price')\n", + "\n", + "# Layout\n", + "plt.tight_layout()\n", + "plt.show()\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 507 + }, + "id": "mluJUa8-bsex", + "outputId": "93b9dbfd-4470-4595-ee4c-7eec45e45999" + }, + "execution_count": 400, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "from sklearn.model_selection import learning_curve\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Use just one target (e.g., Walmart)\n", + "y_single = y['walmart_price']\n", + "\n", + "# Base estimator\n", + "model = HistGradientBoostingRegressor(random_state=42)\n", + "\n", + "# Learning curve\n", + "train_sizes, train_scores, test_scores = learning_curve(\n", + " model, X, y_single,\n", + " train_sizes=np.linspace(0.1, 1.0, 10),\n", + " cv=5,\n", + " scoring='neg_mean_absolute_error',\n", + " n_jobs=-1,\n", + " verbose=1\n", + ")\n", + "\n", + "# Convert negative MAE to positive\n", + "train_scores_mean = -np.mean(train_scores, axis=1)\n", + "test_scores_mean = -np.mean(test_scores, axis=1)\n", + "\n", + "# Plot\n", + "plt.figure(figsize=(8, 6))\n", + "plt.plot(train_sizes, train_scores_mean, 'o-', label='Training MAE')\n", + "plt.plot(train_sizes, test_scores_mean, 'o-', label='Validation MAE')\n", + "plt.title('Learning Curve (Walmart)')\n", + "plt.xlabel('Training Set Size')\n", + "plt.ylabel('Mean Absolute Error')\n", + "plt.legend()\n", + "plt.grid(True)\n", + "plt.tight_layout()\n", + "plt.show()\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 659 + }, + "id": "3g3gZ-Yob3uJ", + "outputId": "968e79bb-63a3-4def-f40c-4cee08997f70" + }, + "execution_count": 401, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "[learning_curve] Training set sizes: [ 618 1236 1855 2473 3092 3710 4328 4947 5565 6184]\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 2 concurrent workers.\n", + "[Parallel(n_jobs=-1)]: Done 50 out of 50 | elapsed: 14.7s finished\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ] + } + ] +} \ No newline at end of file diff --git a/Nguyen + Cao Final Project/Giant.xlsm b/Nguyen + Cao Final Project/Giant.xlsm new file mode 100644 index 0000000..2338499 Binary files /dev/null and b/Nguyen + Cao Final Project/Giant.xlsm differ diff --git a/Nguyen + Cao Final Project/Nguyen & Cao - DATA 400 Final Project.pptx b/Nguyen + Cao Final Project/Nguyen & Cao - DATA 400 Final Project.pptx new file mode 100644 index 0000000..592c4dd Binary files /dev/null and b/Nguyen + Cao Final Project/Nguyen & Cao - DATA 400 Final Project.pptx differ diff --git a/Nguyen + Cao Final Project/Target.xlsm b/Nguyen + Cao Final Project/Target.xlsm new file mode 100644 index 0000000..87359f0 Binary files /dev/null and b/Nguyen + Cao Final Project/Target.xlsm differ diff --git a/Nguyen + Cao Final Project/Walmart.xlsx b/Nguyen + Cao Final Project/Walmart.xlsx new file mode 100644 index 0000000..95f8447 Binary files /dev/null and b/Nguyen + Cao Final Project/Walmart.xlsx differ diff --git a/Nguyen + Cao Final Project/readme.txt b/Nguyen + Cao Final Project/readme.txt new file mode 100644 index 0000000..a04c5ef --- /dev/null +++ b/Nguyen + Cao Final Project/readme.txt @@ -0,0 +1,64 @@ +├── Data +│ ├── Walmart.xlsx +│ ├── Target.xlsx +│ └── Giant.xlsx +├── Scripts +│ └── Analysis.ipynb +├── Outputs +│ ├── Visualizations +│ ├── Multi-linear regression model +│ └── Hyperparameter tuning +└── README.md + +Same Product, Different Price: A Comparative Study of Retail Pricing Strategies +I. Overview: +- This project investigates how the same branded groceries products are priced differently across major U.S. retailers, specifically Walmart, Target, and Giant. By analyzing pricing patterns, the study aims to +uncover whether certain stores consistently offer lower/higher prices, and if pricing varies by product category or unit size. These findings may inform consumer behavior insights and shed light on each store’s +pricing strategy. + +II. Directory Structure +1. Data + a. Walmart.xlsx + b. Target.xlsx + c. Giant.xlsx + +2. Scripts + a. Analysis.ipynb + +3. Outputs + a. Visualizations + b. Multi-linear regression model + c. Hyperparameter tuning + +4. README.md + +III. Data Sources + - Produced listings and prices exported from each retailer’s website in Spring 2025 + - Key columns across Walmart, Target, Giant datasets: + o Product_url_link + o Product_brand + o Product_type + o Product_price_per_unit + o Product_price + +IV. Main Processing Steps + 1. Load and clean Products Data + • For each retailer (Walmart, Target, Giant), data from the groceries categories is loaded and cleaned in Excel + • Standardize column names, units, and price formats; remove null or product brands irrelevant to the initial list + 2. Normalize unit prices + • Convert all pricing to standard per-ounce in dollar format for fair comparison + 3. Fuzzy match products + • Install thefuzz package and use thefuzz to identify samebranded, same quantity across retailers + 4. Statistical analysis + • EDA + • Linear regression + • Hyperparameter tuning + • Visualizations + +V. Installation/Requirements + - Excel + - Python language + - Pandas, numpy, matplotlib, thefuzz, seaborn, sklearn.linear_model + +VI. References + - Cite sources: Walmart.com, Target.com, GiantFood.com diff --git a/Presentation 1.pdf b/Presentation 1.pdf new file mode 100644 index 0000000..bbdf6a0 Binary files /dev/null and b/Presentation 1.pdf differ diff --git a/Project Description.md b/Project Description.md new file mode 100644 index 0000000..68d949c --- /dev/null +++ b/Project Description.md @@ -0,0 +1,15 @@ +# Project Description +My mini-project will explore the environmental impacts on rat presence in New York City. I plan to use rat inspection data as the primary inputs of the model and join environmental data like temperature, weather, seasons, etc to inform the model. This outputs will include preddictions of rat sightings based on these factors and ultimately be used to generate predictions and examine hotspots in the city. This will allow city officials and pest companies to target thir surveillance and thus treatment to reduce this issue in NYC. + +# Dataset +The main dataset of this project will be the Rodent Inspection Dataset from NYC Open Data: https://data.cityofnewyork.us/Health/Rodent-Inspection/p937-wjvj/data. I will also be web scraping weather/temperature/seasons data to support these pursuits. Lastly, I will also find the shapefile version of the rodent insepction data and join the outputs to create a hotspots/targetted map. + +# Methodologies +a. Data Cleaning: I plan to go through and subset the data to only include places with rodent activity/presence. Clean and compile weather/environmental data from different sources pertaining to different negihborhoods in NYC. Scrape any data relevant to funding sources for the rodent issue. +b. Data Wrangling: Join environmental monitoring data with Rodent Insepction Datasheet. Clean and filter accordingly +c. Modeling: Split and train dataset with a Regression or time-series model. +d. Tune: Tune hyperparameters and adjust features based on the results. +e. Combine and import to ArcGIS for hotspot mapping. + +# Impact on Stakeholders +This project will impact communities in NYC and the policymakers who are working to address this issue. Rodent infestations in the city is a big hygiene and thus public health issue. This project will identify hotspots of rodents in the city and find ways to stretch the budget and allocate funding and resources to combat the areas impacted most. diff --git a/cao m - 400 mini proj.pptx b/cao m - 400 mini proj.pptx new file mode 100644 index 0000000..976f1c1 Binary files /dev/null and b/cao m - 400 mini proj.pptx differ diff --git a/mcao_idea2.md b/mcao_idea2.md new file mode 100644 index 0000000..586e274 --- /dev/null +++ b/mcao_idea2.md @@ -0,0 +1,28 @@ +Project Title: Optimize Meals and Profits at Dickinson Farmworks + +Below is the proposal for John Park and I's DATA 300 project. I am submitting this as a backup project plan with the following revisions: + +More parameters (temp, season, break down soups sold into 15 min intervals) +One hot encoding instead of label encoding +Perform tree and regression models again +Visualize the data using PowerBI/Tableau + +Project Description + +Farmworks is a farm-to-table store that prepares meals from fresh ingredients supplied by the Dickinson College Farm. This business serves Dickinson students and faculty and the greater Carlisle area to aim zero-waste emission within the store and strengthen the community. A recent conversation with Jenn Halpin, Director of Dickinson College Farm, suggested that Farmworks is reaching capacity in the number of meals they can produce each day and are therefore running out of food before the business closes. Our goal is to optimize the number of soups and salads the head chef should make, in order to maximize their profits (of each business day 11a to 2p). To pursue this project, we will collect historical data on menu items, amount of food produced and served, cost to produce each meal, timestamp, and potentially weather data to inform the model. Additionally, we will consider the number of workers to scale its influence on the production side. + +We plan to apply linear regression and decision trees models to identify significant various factors and generate how many more meals need to be produced. The model will find a balance between the needs of the community and maximize the business profits. We are hopeful that the outputs of the project will inform Farmwork's’ discussion with college leadership to expand budget for another chef and attract more customers by consistently satisfying the demand. + + +Dataset + +We are in the process of collecting data from the Farmworks’ business system (Square) that contains time, date, # of meals served, what they bought (salad, soup, ½ soup, ½ salad or empanadas). We will also receive data on the base estimate cost of each soup and information related to menu rotations and food preparation. We may also choose to include weather data and see how that feature informs our model. + +For specific features, we plan to include the historical menu data (categorical), number of meals sold (numerical, continuous), special menu items (e.g. empanadas, breakfast, etc.) (categorical), day of the week (categorical), number of servings made (categorical), # of servings sold per hour and estimate cost (numerical), and potentially number of workers/total labor hours (numerical) and weather data (numerical (temp), categorical (cloudy, raining, etc.)). + + +Evaluation + +To evaluate our model’s performance in predicting optimal meal production, we will use regression metrics, including Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared values (R^2). The MAE and RMSE metrics will assist in identifying and adjusting significant prediction gaps. R-squared will determine our model’s effectiveness in capturing key demand features. If it leads to overfitting, we may switch to the adjusted R-squared metric. These metrics will assess the model’s accuracy in predicting the meal quantities, classified by each menu cycle, and effectiveness in meeting the equilibrium point of the meal’s input cost and revenue. After the initial evaluation, we will tune hyperparameters and refine features, especially weather and labor productivity, to improve the model’s performance. The model’s sensitivity to weather and seasonal menu changes will be ensured to maintain a consistent performance. + +After collecting and performing initial tests, we may potentially increase the features and experiment with decision trees. diff --git a/readme b/readme new file mode 100644 index 0000000..a04c5ef --- /dev/null +++ b/readme @@ -0,0 +1,64 @@ +├── Data +│ ├── Walmart.xlsx +│ ├── Target.xlsx +│ └── Giant.xlsx +├── Scripts +│ └── Analysis.ipynb +├── Outputs +│ ├── Visualizations +│ ├── Multi-linear regression model +│ └── Hyperparameter tuning +└── README.md + +Same Product, Different Price: A Comparative Study of Retail Pricing Strategies +I. Overview: +- This project investigates how the same branded groceries products are priced differently across major U.S. retailers, specifically Walmart, Target, and Giant. By analyzing pricing patterns, the study aims to +uncover whether certain stores consistently offer lower/higher prices, and if pricing varies by product category or unit size. These findings may inform consumer behavior insights and shed light on each store’s +pricing strategy. + +II. Directory Structure +1. Data + a. Walmart.xlsx + b. Target.xlsx + c. Giant.xlsx + +2. Scripts + a. Analysis.ipynb + +3. Outputs + a. Visualizations + b. Multi-linear regression model + c. Hyperparameter tuning + +4. README.md + +III. Data Sources + - Produced listings and prices exported from each retailer’s website in Spring 2025 + - Key columns across Walmart, Target, Giant datasets: + o Product_url_link + o Product_brand + o Product_type + o Product_price_per_unit + o Product_price + +IV. Main Processing Steps + 1. Load and clean Products Data + • For each retailer (Walmart, Target, Giant), data from the groceries categories is loaded and cleaned in Excel + • Standardize column names, units, and price formats; remove null or product brands irrelevant to the initial list + 2. Normalize unit prices + • Convert all pricing to standard per-ounce in dollar format for fair comparison + 3. Fuzzy match products + • Install thefuzz package and use thefuzz to identify samebranded, same quantity across retailers + 4. Statistical analysis + • EDA + • Linear regression + • Hyperparameter tuning + • Visualizations + +V. Installation/Requirements + - Excel + - Python language + - Pandas, numpy, matplotlib, thefuzz, seaborn, sklearn.linear_model + +VI. References + - Cite sources: Walmart.com, Target.com, GiantFood.com