From 6dcdb2f3de1c926cb56e2346e5efa197b547d90d Mon Sep 17 00:00:00 2001 From: NamelessW0lf Date: Mon, 21 Nov 2022 12:52:23 +0100 Subject: [PATCH] visuals --- Bonus 1/Bonus1.ipynb | 358 ++++++++++++++++++++++++++++++++++++------- 1 file changed, 300 insertions(+), 58 deletions(-) diff --git a/Bonus 1/Bonus1.ipynb b/Bonus 1/Bonus1.ipynb index 279a51a..0165d63 100644 --- a/Bonus 1/Bonus1.ipynb +++ b/Bonus 1/Bonus1.ipynb @@ -2,53 +2,38 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Collecting mlxtend\n", - " Downloading mlxtend-0.21.0-py2.py3-none-any.whl (1.3 MB)\n", - "Requirement already satisfied: scipy>=1.2.1 in c:\\users\\win10\\anaconda3\\envs\\datascience\\lib\\site-packages (from mlxtend) (1.5.2)\n", + "Requirement already satisfied: mlxtend in c:\\users\\win10\\anaconda3\\envs\\datascience\\lib\\site-packages (0.19.0)\n", + "Requirement already satisfied: 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joblib>=0.13.2 in c:\\users\\win10\\anaconda3\\envs\\datascience\\lib\\site-packages (from mlxtend) (0.17.0)\n", - "Requirement already satisfied: numpy>=1.16.2 in c:\\users\\win10\\anaconda3\\envs\\datascience\\lib\\site-packages (from mlxtend) (1.19.2)\n", - "Installing collected packages: mlxtend\n", - "Successfully installed mlxtend-0.19.0\n" + "Requirement already satisfied: threadpoolctl>=2.0.0 in c:\\users\\win10\\anaconda3\\envs\\datascience\\lib\\site-packages (from scikit-learn>=0.20.3->mlxtend) (2.1.0)\n", + "Requirement already satisfied: numpy>=1.16.2 in c:\\users\\win10\\anaconda3\\envs\\datascience\\lib\\site-packages (from mlxtend) (1.19.2)\n" ] } ], @@ -80,7 +65,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -90,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -107,7 +92,7 @@ "Name: Sale_Price, dtype: float64" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -118,7 +103,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -127,7 +112,7 @@ "" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, @@ -164,7 +149,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -393,7 +378,7 @@ "31 Longitude -0.251397" ] }, - "execution_count": 6, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -406,7 +391,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -422,7 +407,7 @@ " 'Mas_Vnr_Area']" ] }, - "execution_count": 7, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -433,7 +418,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -442,7 +427,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -633,7 +618,7 @@ "[2930 rows x 8 columns]" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -644,7 +629,264 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "def histplot_all_12(data, width, height, nr_cols, nr_rows):\n", + " figure, axes = plt.subplots(nr_rows, nr_cols) # setting the number of rows and columns of the plotted diagrams\n", + " figure.set_size_inches(width, height) # setting the size of the diagrams\n", + " cols = data.columns # extracting the column names \n", + " # with z set to 0, iterating over the columns of the dataframe to plot all 12 diagrams using seaborns histplot method !\n", + " z = 0\n", + " for i in range(nr_rows):\n", + " for j in range(nr_cols):\n", + "\n", + " sns.histplot(bins=20, data=data[cols[z]], ax=axes[i, j])\n", + " z = z+1\n", + "\n", + " plt.tight_layout(pad=1.08, h_pad=1, w_pad=1, rect=(0,0,4,4))\n", + "\n", + "def streudiagramm(x_achse, y_achse):\n", + " # Grundlegendes Streudiagramm erstellen\n", + " plt.plot(x_achse, y_achse, 'o')\n", + "\n", + " # Erhalten Sie m (Steigung) und b (Achsenabschnitt) der linearen Regressionslinie\n", + " m, b = np.polyfit(x_achse, y_achse, 1)\n", + "\n", + " # Lineare Regressionslinie zum Streudiagramm hinzufügen \n", + " plt.plot(x_achse, m*x_achse+b)\n", + " # sns.regplot(x_achse, y_achse, ci=None)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sale_price = df[\"Sale_Price\"]\n", + "streudiagramm(sale_price, df_top[\"Gr_Liv_Area\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", 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/nubrPkkex498XINBnj/rnDHMOe9IWpob+1w9N0we6yrlUCiF2m70Yyv0IuC12ZPMlpu1fLNnZpzhUIqIlZgIUyaMHFDjZojHClmAyceOZNK4Fuat3JrTfoiXKGVzQfh9drKJWz6uwVyeX8zNyUJtjzKlrlMTKFO0GFRSpmg++L2Rfr7OWueTdU/xvw1zXWPFiljxy0L0y3JMZkR+c9kmzzo06XML/ee1YlXV8TcoVp2aglP/i0G1C3oq1VJgqxhcFPsN18dvc419sfNfeajX8/MaCn6p8H4XWwFumDzWt/JikmFNcTZ865TwDK1RqqVgVy5lEHKh2Kn/RgaWbWhjxt0b6eqxdXkSoZdv1C/i0vr7XeNn7ruezTq6yOd2wkiPn/vwgKqFfqUYDmpuZNbyzVkjVdLXRtWwysyXQl57mNnZ5SSXMghhvS4T9DzI5cM6b+VWE/MEXhErO3UoZ++bzau8uyQ2JN+J9Holbe0dxOuEeExc71fSfx0krG9Xyt5I2DWAKolCX3tY2dnlJpcyCGF9JizwIke8koauuXcTyza0ec61pCJ4N7v4XcPlroiVNb0f4sN7b+OYfbeUTMyz0dWrDGmod0V05PI1PzW6KdMqs9op9LX7RYlVWhijV/SOF2FeqGyFniNBvw4mhb+WOVS289Cgq1xjd3afyDe7vxDZGiu7Orp48tqBfvBhWSpjpkeiVMsqMx8Kfe35RvpEjVzKIISFCXqOBP2w1nK2qFfEyuyui1jYU5761jERGuolUPchv3+ua88e47sX4tWxqJaTZQp97dUUxpiaVOW32RvmhcoEPUeCflhrYSWWztTYKr4Td3cFKnbEih/pURHZOgUln+P3z5WryFTLKjMfwnjtuWZnVwKluFCZoOdI0A9rrVRY9ItYOWvfbP6sHyjaeWM+X1+TpPu+vf6ZMvXm9CIXkammVWau1PJrz0axL1QWh54HQTrTt7V3uHpLZqK5Mc7uzu6KioYZRCc/it/ESbENfWNhR6zEEr1B00muvv0yN60fpVHNWBx6yPhdZdO/1geV50oqBfBudnFPwyxG1b3WN/bGu8fz6HG3MHfVdl7dl/1bybCmOE0N9X0XxPY9nZ5FqbzEPCbiWn3XqlvDMLwIJOgichpwExADFqrq3LTHhwJ3AK2JY/6Xqv40ZFsjTzVvhHpFrPwydjLnfmMpw+tinA2cfcxhWZteC84GY+oFcfTMFYHt6FEdUF/EvtobhkOQFnQx4IfAyTgNodeKyHJVfTpl2leAp1X1bBEZAWwVkUWq2lkUqyNKNW6EfqJuE3c0zHGNze66iJ/0nMkNk8dCnTvONlsLMmVgckku+w2C800oVdTzFXAv1xnYBcKoXIKs0I8FnlPV5wESzaDPBVIFXYH9RUSA/YA3ge6QbY081bQROiW2ijlpESvTOq/gwd5j+u7PWr65r0ZNcpOypbmR849uYfFjL/vW/U4VZPC+CPg1hVAIJbPOK5txxi82gtC3l1FL2Z1GdRAku6MFeDnl/vbEWCo3Ax8CdgCbgK+r6oCgXxGZJiLrRGTdzp070x+uOJZtaOP4uQ8zeuaKvtog8Vjldrh1Ilbu4MXBU11ifta+2Yzae6dLzMHx/SeTbVLrUyxd+zLHfWCY5zmSgpxKshVZaobmvAuO8rUzjG9CXu6xrl4dsDFdK9mdRnUQZIXupVDpS6dTgSeBE4FDgIdE5A+q+rbrSaoLgAXgRLnkbG2E8Frh3bO+jd4QWo2VGq+IlTf0XZy973peySNipatHefT5N30f39He4enuSI9M8YtiCSM5J5eLQjW60ozqJIigbwdGptw/GGclnsrFwFx1YiCfE5EXgCOAx0Oxsoz4hSj6lQCoJA6W1/njoMtdY4/1HsEXOmewm8JEM9N1bWhjPFDxJi9XjAATjxhRkG2Qm3usFrI7jeogiKCvBQ4VkdFAG3AhMDVtzjbgJOAPIvJe4HDg+TANLSV+seRt7R1csfRJ1r30ZkWv2ibIX1g66NuusTu7J/LN7ktKUmPFK0yzo6uHy5c+ybyVW/sumpPGtbDupTddTSUUuGd9G+Pff0BBfm0/v32qDx0sDNKoLLIKuqp2i8hXgZU4YYu3qepmEZmeeHw+8G3gZyKyCWcRdbWqvlFEu4tGtlhyBRat2cbgeF2g2iBRwis1/4GeY5jedUWZLBpI+mp99ZadA96DMEqO+oU8eo3ZhqhRKVimaBrZ4qgrke/UL2Rq/cOuse92XcgtPeeUyaLsJLM9M3UR8mojZxjVjmWK5kAlu1JSEXq5v+Eajqh72TV+SeeVrOo9ukxWBSf5PuRaua+WuwQZhgl6Gn5tyCqFJvby9OAvDBg/ed/3eFYPDv182Ypk5cvQxjjLNrSxp3NgOoOfX7uWuwQZBpigu1i2oY32ChXzd7OLuxtmMTqlxgrA2L230s7+gY8TjwlDGurZ1dHF0MZ4xjozAvQWyWX3933dnk2ZmxvjzDpnjKdAV0svSsPIFxP0BMlmzpUWRf5B2c5v0mqs7NShfGzfD+jO8e2tS0R4DBlUz6xzxgBk7KWZdHtk2nOI1wm9eBfaykRPr+IVBDpkUL2vONdylyDDABP0PiqtmbNXjZXvdE1hQc/ZOR9LgLqUUrVJV8Wg+swhjG3tHQxrivum6YOTfdncGGfIoPoB0STZGk54kUmca7lLkGGACXoflbKKuzD2MHPjC11jl3Vewcq0tPxcUAauoDu6egKJbZD9hvaOLnZ1dHluUvplg/qRSZxruUuQYYAJeh/RLqyl/Hv9nUyrd5eZPXvfbDYVsStQmCgDNymTP17t4eIxAcW18s8mzlZO16h1al7QU7NCo8YgOvlh/CY+E1KNlSjgtUkZZpJPruV0LczRqCZqWtCDNA4uBwfwNnc3zOIDda/2jT3eezgXd15VcI2VKODl3vIT4mKKq4U5GtVGTQu6X4eh9J6Uyza0ceVdG4sSb53KIdLGqkEzXGNLuk/g37svLUmNlVIRlU1KC3M0qo2aFvRsYW7LNrT1NXAoJsfXbWJRWsTKnK4p3JpHxEqpyNQAe1hTHPDfMA2jWmIYWJijUW1Uz7IvD/xWigc1N/Z9HS+mmE+OrebFwVNdYn5Z5xWM2ntnZMU8JsLnjmvlhsljaYy7288J8LnjWtnwrVO49uwxnoX0AVZviUZzk0zvv2FUIjUt6DNOPXyAKCUjKYrX8Fm5pn4RLw6eynfjP+4bPTvRFaiQ8MNS0KPKPevbAAZ0Gbph8lhmTzoScHzQfiv4tvYODrnmPkYlOj0t29CWtz3pXaNyOVam998wKpGadrkAiTK4jnCnppVnypDMh0F0cnP8fzg59kTf2N90f87edz07GB7quYpNR1cPV961kV5VmpviDG2Ms6O9o69VW9L/3JIhFDS1ZV2+G5GFbmpamKNRbdSsoHtFuOzr7q9vLgJh7IEewNv8ouE6Dql7pW9sbe9hXNx5Fe/QVPgJikBzlhou0C/IqS6ptvYOZty9EXDEcuIRI7hjzbas58t3IzKMTc1cwxwNI8rUrMslkxhA4WJ+iLTx4uCpPDF4ep+YL+0+gUP2/i8XdM6KpJgn/eNDBuV/ne/qUa771WYgN195PhuRtqlpGG4C/eeKyGnATTgdixaq6lyPOScANwJx4A1V/XRoVhaBYonBx+v+zJ0N33GNRT1iBZwre49qoBV1NpKr9lz+lvlsRFrtFsNwk1XQRSQG/BA4Gadh9FoRWa6qT6fMaQZ+BJymqttE5D1Fsjc0/ErDDm10Qu6a4nXsyaHF3Gdjq/leyiYnwGWdl7Oy99jCDC0RxWimF7ScQr4bkVa7xTDcBFmhHws8p6rPA4jIEuBc4OmUOVOBe1V1G4Cqvh62oUnCSNVetqGNXXu9fcSSiLUbFI8FEHRlZv1iptf/2jV6zr5v85QekpNN1URz4qLoJbjJ+PVkY4yWAjYibVPTMNwEEfQWILWP2XZgQtqcw4C4iPwW2B+4SVVvTz+QiEwDpgG0trbmbGwYqdrJY/j5yJMNLjI1unAiVn7AybH1fWNv6n6cte87FRexUgyStdRLIbi2qWkY/QQRdK/8kHQ5rAeOBk4CGoFHRWSNqj7jepLqAmABOE2iczU2jKiGbPHlSf+rl7vAK2JlXe9hfD7CESvphBW9k4nU8EUTXMMoHUEEfTswMuX+wcAOjzlvqOpuYLeI/B44CniGEAm6kZnJLZNto+6t3fsYe92DLv+6V42Vu7o/zTXdl9JDLP0QZaG5Mc6ezm46szTpUHVK0wZt5uG3l1An4NeEyIpcGUZ5CBK2uBY4VERGi0gDcCGwPG3OL4FPiki9iDThuGT+Eq6pwVK1ky6VtvYOVw3uZAZhtgiIPV29fWL+sbrNvDh4qkvM53RNYdTeO7mq+7LIiHljPMasc8bwzPVncOPksbRkeI0xCSbmAtw4eSxPf/v0vtosqfSq91e3JKkhoIZhlIasgq6q3cBXgZU4In2Xqm4WkekiMj0x5y/AA8BTwOM4oY1/DtvYIKna2eLLvY6RzmcTNVYWN1zfNza98/LI1lhJfX2TxrXwyMwTudGj1kpjPBa4YmR9rF+u/fYTsh3J4sENo7QEikNX1fuA+9LG5qfdnwfMC8+0gQTZZPMTkbb2DkbPXMFBzY2cf3QLq7fsTPORKzPrlzC9/leu55277z/ZqB8M/bWETfrrTv5NZi3f3PeNY3C8jkH1dVmzQMFJEEruTfiFHyYjVfyweHDDKC0Vl/qfbZMtU+xz0gVzx5ptfW6EQXTyg/gPOCUlYuUt3Y8zKyxixU88U8sZvLWni3hMMvq/U0leJPzivc8/uoV71rd5bjJbPLhhlJ6KE/RszDj1cK5Y+mRWdwB7/saqtIiV9b2H8i+dV1dMxEoSP/H0cj919SjDmuLs6ujKKurJi0S2b0aL1mxz/b0FOP9oi24xjFJTdYKerVLiIdLGQw1XUSf9EhS1iJVcEAb60JP4uZ/a93Rxw+SxGdvvpV8k/L4Zrd6yc8DFU4lOzXPDqCWqTtDBu2zrx+o2uzY5AeZ2Xcj8nnNKaVpoJDMuk2LqFSqYqdZJ+qp7aGMcEUfsc0kA8nNvtbV3sGxDm63SDaOEVKWgp/p8L4j9lnnxBa7Hv9T5de7vTU92rSy8vCWpSVbLNrSxp7Pb87k72jv45rJNfc0oUl0p1549xlOEvWL7IXMrOotFN4zSIlrstEEfxo8fr+vWrSvOwVV5ZtG/cdhzC13DlRKxUig3ZnGnJDn+kAN4YtuuAZudc8470iXCXrXjG+MxBsfrsrboS2+4HZQwavYYRjUiIutVdbzXY9W1Qu/eB7+4GLau4LDE0Nvsx+l7r6eNaDQmLjYCXPerzYHa5z3y1zcHjHmVUvCL7Q9yjnxi0cOo2WMYtUh1NLjY/Te4+ViY/R7YusIZO/hYmPkyR+1dUDNiDo77o9DG1ukiXEiCUD6x6NmSwwzD8KayV+hvPAs3H4PLi3vUVDjnBxBzXlrQmtxGP81pqf75/g3zjUW3TkSGkR+VKegv/AF+fpZ77KRr4RNX9Bc0T+CVFFPtZNqoTKUhJp7FvJLbKkk/dlt7R+BjJkltuB2EVJ95nU8Gar6Zp0H88fn67M3Xb0SJyhP0nVvdYn7Bz2DMP/pO90qBr3ayCW9MhCkTRrLIp93cro6uAX5sJdiFQoCLjmvti6AJQvq5vMQ839V+EH98vj578/UbUaPyfOhDR8LHvwaXroJZuzKKeZJJ41pyanwck0x1BCub5sY4f51zBrMnHZmxeqWXHzvICj2fpCK/GvWp78LgeH4f1SD++Hx99ubrN6JG5Ql6QxOcMhsO9oza8SUX/2tvmUI5CyFbBckkuzu7+0oJTzzCe7N44hEjCvJX5/pcv/mp78Jbe7pcZZALPXbqeL4+e/P1G1Gj8gQ9T3LxvyYbRVcKTfE65px3ZF8vz0x09ShX3rWR0TNXsPixlz3nrN6yM+PfK9v3l1x93UHn57P6DVJDP8icfI9tGKWkZgQ9SB30JJXmax82ZBDgrL6D0KOK4u2rBscXnCmqRaGviUa6uOfj687lvcl19Rukhn6QOfke2zBKSSBBF5HTRGSriDwnIjMzzDtGRHpE5J/CMzEcJo1rYc55R1alf7ytvYMr79oYuK1coSSzP1+ceyY3JDokSWI8Pcs0CMn3JvU4Xl2SIPfVr9ex020MMiffYxtGKcma+i8iMZzeoCfj9A5dC0xR1ac95j0E7AVuU9W7Mx23qKn/GRg9c0VO4XeGm1id8P0Ljiq6aPmVGzDBNGqdTKn/QVboxwLPqerzqtoJLAHO9Zj3NeAe4PW8LS0BtebfbG6MZ+wxmis9QTpjhICtfg0jd4LE8rUAqbtn23GaQPchIi3APwInAsf4HUhEpgHTAFpbW3O1NRRqKdEoHhNmnTOGdS+9OaAJRSGk13opFtm6UxmG4SaIoHs5ndO14UbgalXtkQw+alVdACwAx+US0MY+wsjKS68DXqnuF5H+jE4/hjQ4b28mMQ/aji4VC8szjGgSRNC3AyNT7h8M7EibMx5YkhDz4cAZItKtqsvCMBJyy8oLKvyVKuaQXczBida57lebM75OVRjSEGN3Z/BvLLXmtjKMSiGID30tcKiIjBaRBuBCYHnqBFUdraqjVHUUcDfw5TDFHIJn5SWFvy2x+k4KfzIhJfXxWiBb5UWFnNxPFpZnGNEl6wpdVbtF5KvASiCGE8GyWUSmJx6fX2QbgeBZeV61wDu6erjyro2Af5p5LRPU5TKsKe7qaGSFqQwjWgQqcKKq9wH3pY15Crmqfr5wswaSqT9mkmUb2nxXpD2qVbkZmmsVxHzwqpxohakMI3pUTKZokKy8bGnh1SbmEI6YN8brPP+2nzuulWFNcdo7urh86ZOMve7BPteVFaYyjOhRMeVz06NTvL7iW/RF7sTrhDnnfQRw/20nHjGCpWtfdmWftnd0MeMXjuvKClMZRvSoGEGH7HHJQTrrxHyaJ9QiMRG6epV5K7cy49TDXc2cj5/7sGcpgeT8IC4wwzBKS8W4XIKQrchTYzzGlAkjAxeCqmYa47G+C1t6JBBkXmnvaO+wwlSGEUGqStDT08WbG+MMa4q7UsdnTzqS849uyVoCtpoRBu4npPu/M620D2putNR8w4ggFeVyCUKQdPHVW3ZWdFJRofi99tRV+YxTD2fG3QMrOMbrpG8Vbqn5hhEtqk7Qg2Abd96krsqTQn3drzb3hYLm2vjZMIzSUrWC7pX0Ak4kRzWszgWoqxPP6ofJBKB5K7d6blwOa4qzt6t3QGnadP+3rcANo7LIWg+9WBSzHrpXLe14nYBQsiYQpSBeJzTU13nWYWmMxzj/6BbuWd/mWVMcMoeAGoYRTTLVQ6/KFbpX0ktXwPz2UmRehkVXr/KepgaamxiwEu/o6mH1lp3MOe9IX+EOKuCW4m8YlUFVCnohPvIX5p7JqJkrQrSmuGQLLyzUbWIp/oZROVRV2GKSfJNbkv1GK6nv6EHNjUXtPm8p/oZROVSloHslvcTrhHgss1BPmTDS9TvqJDcyi5nkYyn+hlE5VKXLxa/uS+pYU0OMPZ09KM6KfMqEkcye5GwWJn/fsWZbWexvbowzYv8Gnn19t++cmMiARJ5i+Lktxd8wKoeqjHIpFsfPfThjrRjB8cGns2xDG5cvfTLr8VuaG/vqqeR7rrDxihhKRsqYD90wSk/NRbkUi2wNppub4oAjgrOWb6a9w0nIGdYUpzFeR0dXr++x010k2VwapVohB6lyaRhGNAi0QheR04CbcDoWLVTVuWmPXwRcnbj7DvAlVd2Y6ZilWqEXEnL3zWWbWPzYyyWvzhikImR69yDDMGqDglboIhIDfgicjNMweq2ILFfVp1OmvQB8WlXfEpHTgQXAhMJNL4xCQu6+uWxT2XzoQS4gb+3psvBBwzBcBIlyORZ4TlWfV9VOYAlwbuoEVf2Tqr6VuLsGODhcM/OjkJC7xY+9XCyzQsPCBw3DSCWIoLcAqeq2PTHmxyXA/V4PiMg0EVknIut27twZ3Mo88fNDt7V3cPzch131v9OplCYYFj5oGEaSIILuFbztqXYiMhFH0K/2elxVF6jqeFUdP2LEiOBW5kmmjUOvpg6pVEpykYUPGoaRJIigbwdSM20OBnakTxKRjwALgXNV9W/hmFcY2ToYZXJZFDO5KKxsLusQZBhGKkHCFtcCh4rIaKANuBCYmjpBRFqBe4F/VtVnQrcyT1JD7vxiuv1cFsnkorCjXGIifP+zR7HupTdZtGZbToXABPoSomoxfNCKhBlGZoKGLZ4B3IgTtnibql4vItMBVHW+iCwEzgdeSjyl2y+sJkmpE4v8EnVSk3kyMXrmCk/xFeCGyWM9u/t44ZcQlOn4pUggijq1nOBkFzIjlUxhi4G+/avqfap6mKoeoqrXJ8bmq+r8xO1LVXWYqo5N/GQU83JQaL2TrAWwAi61cy2kZT5yh1otEpa8kLW1d6Bk3/sxapuayRTNNeMxfVU08YgRA5pFAOze182s5Zs966171Vbfva+bZRvamDSuxXWOoY1x4jFxrfIb4zEmHjGC4+c+nNXmYq7iorBCrNUiYZkuZLZKN9KpGUGH4C3VvBKS7lnfxvlHt7DiqVf6emwCfen9XihORmf6/Gvu3cS6l950XSDaO7qI1wnDmuK07+nyvIj4JUYVs2Z5VOqh12qRsFq9kBn5UZXlcwvFb1W0estOmhqCXwNbmhs953d09bD4sZc9uyo1NdTzwtwzeWTmiazesjOQm6GY7oiouDqKWSI4ypgrzsgFE3QPMq2Kgq6MkmLjN98vciZ1ftDVWTFXcVFZIU4a18Kc846kpbkRwblY1sKGaK1eyIz8qCmXS1Cyfb33eqxO4F2D4+zq6HL5ma/71WaXyyWJXwGu1JVXUDdDMd0RUXJ1FNpOrxKxapdGLtgK3YNMqyK/ZKVehX3dvdwweSyPzDyxb9Pznb3dA+bGY05DjWwrr6Crs2Ku4myFWH4mjWvhkZkn9rniTMwNP2yF7kGQVdGVd20csMJOjz6Yt3KrZ/TLkIZ6Zk86kvHvPyDjOYKuzoq5irMVomFUDtaxKE+CJAKFnSwUhfBBwzDKS8GJRcZAgkQfhBmhYAkmhmFkwwQ9T7L5lpdtaGNP50D/OcBbu/cxeuaKrCV8U4lK+GAmlm1o4/i5Dwd+bbnONwwjM+ZDz5NMvmWvuiOp7En0Fs0lSSdb+GC53TG5JiBFJWHJMKoJE/QC8Auj81pN+xE0jTtT+GAUxDHXFHVLaTeM8DGXSxHINekmyPxMLp4ouGNyTUCKSsKSYVQTJuh5kM33m+umZ5D5mTIloyCOYVWRtJR2w8gfE/QcCRJtkq1TUiq5JOn4JZhEQRxzTUCyhCXDCB8T9BwJ4t5IX003N8YZ1hRHcKovNjfGQ61HEgVxzLXWSq3WZjGMYhK0Y9FpwE04HYsWqurctMcl8fgZwB7g86r6RKZjVmpiUa7JQqWKPil3lIthGKUhU2JR1igXEYkBPwROxmkYvVZElqvq0ynTTgcOTfxMAG5J/K46cilWVcrok1osXGUYhpsgLpdjgedU9XlV7QSWAOemzTkXuF0d1gDNInJgyLZGglzcG1GIPjEMo3YIIugtwMsp97cnxnKdg4hME5F1IrJu586dudoaCXLx/UYh+sQwjNohSGKReIylu5GDzEFVFwALwPGhBzh3JAnq3ohSLXHDMKqfICv07cDIlPsHAzvymFNzRCH6xDCM2iGIoK8FDhWR0SLSAFwILE+bsxz4f+JwHLBLVV8J2daKw0LzDMMoJVldLqraLSJfBVbihC3epqqbRWR64vH5wH04IYvP4YQtXlw8kysLiz4xDKNUBCrOpar34Yh26tj8lNsKfCVc0wzDMIxcsExRwzCMKsEE3TAMo0owQTcMw6gSTNANwzCqhEDFuYpyYpGdwEsBpg4H3iiyOYViNoaD2RgOZmM4RNXG96vqCK8HyiboQRGRdX6VxaKC2RgOZmM4mI3hUAk2pmMuF8MwjCrBBN0wDKNKqARBX1BuAwJgNoaD2RgOZmM4VIKNLiLvQzcMwzCCUQkrdMMwDCMAJuiGYRjVgqpG9gc4DdiKU8VxZhGOfxvwOvDnlLEDgIeAZxO/h6U8dk3Clq3AqSnjRwObEo/9D/2urEHA0sT4Y8ColOf8S+IczwL/ksHGkcBq4C/AZuDrUbMTGAw8DmxM2Hhd1GxMmRsDNgC/jqKNwIuJYz8JrIuojc3A3cAWnM/lx6JkI3B44u+X/HkbuDxKNhbrp2Qnytkw5x/vr8AHgAYcsfhwyOf4FPBR3IL+PRIXD2Am8N3E7Q8nbBgEjE7YFks89njiQy3A/cDpifEvA/MTty8Elqb8gz6f+D0scXuYj40HAh9N3N4feCZhS2TsTBxvv8TteOIDflyUbEyx9V+BO+kX9EjZiCPow9PGombjz4FLE7cbcAQ+Ujam6cirwPujamOomlaqE+VsmPNHXJly/xrgmiKcZxRuQd8KHJi4fSCw1ev8OPXhP5aYsyVlfApwa+qcxO16nKwzSZ2TeOxWYEpAe38JnBxVO4Em4AlgQtRsxOmktQo4kX5Bj5qNLzJQ0CNjI/Au4AUSK9Uo2phm1ynAI1G2McyfKPvQAzWeLgLv1US3pcTv92SxpyVx28vOvueoajewC3h3hmNlRERGAeNwVsCRslNEYiLyJI4L6yFVjZyNwI3AVUBvyljUbFTgQRFZLyLTImjjB4CdwE9FZIOILBSRIRGzMZULgcWJ21G1MTSiLOiBGk+XED97MtmZz3O8Ty6yH3APcLmqvh01O1W1R1XH4qyCjxWRf4iSjSJyFvC6qq7PYFdZbUxwvKp+FDgd+IqIfCpiNtbjuClvUdVxwG4c90WUbHQO4rTMPAf4RQb7ympj2ERZ0MvVePo1ETkQIPH79Sz2bE/c9rKz7zkiUg8MBd7McCxPRCSOI+aLVPXeqNoJoKrtwG9xNrSjZOPxwDki8iKwBDhRRO6ImI2o6o7E79eB/wOOjZiN24HtiW9g4GyOfjRiNiY5HXhCVV9L3I+ijeFSKt9Orj84K4HncTYpkpuiY4pwnlG4fejzcG+cfC9xewzujZPn6d84WYuzCZjcODkjMf4V3BsndyVuH4DjhxyW+HkBOMDHPgFuB25MG4+MncAIoDlxuxH4A3BWlGxMs/cE+n3okbERGALsn3L7TzgXxsjYmJj7B+DwxO1ZCfsiZWNi/hLg4ij+zxTrp+zCneUf7wycqI6/At8owvEXA68AXThX1ktw/GCrcEKOVqW+GcA3ErZsJbHbnRgfD/w58djN9Ic2Dcb5uvcczm75B1Ke84XE+HOpHzoPGz+B85XtKfrDsM6Ikp3AR3BCAZ9KHP9bifHI2Jhm7wn0C3pkbMTxT2+kP/zzG1GzMTFvLLAu8X4vwxGuqNnYBPwNGJoyFikbi/Fjqf+GYRhVQpR96IZhGEYOmKAbhmFUCSbohmEYVYIJumEYRpVggm4YhlElmKAbhmFUCSbohmEYVcL/B5rkoG4MZTk8AAAAAElFTkSuQmCC", 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", 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", 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J5vfrRyi8jinnrLLaUR+VnjFXfE3j9WXw0Pdh787ifV9ZDH/9dVAOt3ARx5egK6VOBG4BEsAdWusFDsd9BlgBnKW1fjA0K2sMr1jkMGZHdtewYhatjs50gZhb7bK7dikDgBW3H7PbYNE2qaUgOcgPxvt1m92br+/nXH63x4lKv7eyJxdpDWvug44Li/cNbYIzFsOnZoZzrSrjmfqvlEoAtwGzgAnAOUqpCQ7H/QJYFraRtYbbD8ZJ7C+/f02gdHA/Pz6zaC1ctj5Q1UGvAcAvTqn4Yz6e4rIlq11TzuefNrHotW4Y79fummYUMH18s69z+d0eJyr93spSZiPbC8/fmku3v7apUMxHHg7ffQrm74S5W2pGzMHfDH0ysEFrvRFAKXUfcDrwiuW4HwIPAZ8J1cIaxG1W6iTEvdreH2zFmNV6xS5ZZ0BemX9Wgg4ATtj5jKePb/Z1t2D8f/n9a/o+HyfM79d6zVSyjt2Z/sxRDTy0Kk3r6JGOolKTKet5qvHeQnEzZfbAf/wC/vTL4n2HTIbT/hk+MX5g14g4fgS9BXjL9HwrMMV8gFKqBfgKMAMXQVdKzQHmAIwaNSqorTWD2w/GLRnDwMkNYhf+ZcYtTtutCqHdD9lNtDW5sMLp45t55rXtnv5164952oLlvgcL43XW951MKIY11LOzO2N7bfM1py1Yzm7Leb18xlFYvCwXsXpve3bCU9fk0u6tHDETTr4Rmg6tvF1Vwo+g260OWH9vNwN/p7XuVS6LCVrrxcBiyMWh+7QxMlQqlMtNlA3sCh25+c294qvtBhkFnDt1VKAytGb77lrxZsFzv/71oHcLAxWgUn3GYS5eRiGsNAo2+OJ/3oEn2uHVR4v3HTUbZv4cGkdW3q4I4EfQtwLmIe4QYJvlmFbgvryYHwCcpJTq0Vp3hGFkFKhUKJeftGkDqw1OAqTAMyklqChOH99cINh+8Bsp4TZYOPm2ByKu1W5mEoXGFFGwwZX334DHfgSbny3e99lLYPpPoGFY5e2KGH7qob8IHKGUGquUagDOBgqGRq31WK31GK31GOBB4KJaEnOobJu3tkktPDd3Bi0+BMVsw0AXs4zrblpwMs/NneH6Q37mte2+zmnFj3/dbdHyoVXp0NuTVbvGexT610bBhiK2rYbbP5db2PznYwrFfMbVcPV7uYXNmT8XMc/jKeha6x7gEnLRK68C92ut1ymlLlRK2cQB1SbVCFPzisaw2uB0/K69PaGLYKnv28/g0japhTOPtR9MyiEypURZhNm7MwohkFGwAYCNfyxsBvHuuv59p9wMP92RE/HjroBEsrK2xQBfceha6yeAJyzbFjkc++2BmxU9gtyW+/FF+jnG6gapU8o2msMcs92d6UWpXOitQVe3c73vUv2mfmK5rfid9XZ0prn3hbcc94clMqW+dzv3xKVLVnPtY+u45tSJgV0U1Xb5VNUGreGVDlg6p7gZRGIInPkbmHB6eW2oIaQFnU/83pb7adnV0Zmm/cE1Bce0P7jGdpZndoPc+PWjbG2YPr6575pQKOYGdjPbgXRct/s8kglFUyrZN8s9r4S2boZNbmGIYYiM3Xu/bMlqrupY6/lap8Vno1FG0Nl6tV0+Fbchm4UX/6U/RvyBb/eL+f4Hwzcfzc3Cr35XxDwgkvrvE7+Lhn7Spq99bF1RLZFMr+bax9w70zjZ4CcrFIpntgNJ8Q47tM1cd8YNpzDKoNi9dw3cveJNx/hzPzZ2Z3o9v0crXp9lJaJPyh6qGMFmELWICHoA/ERS+PFF2pVHddvuZcNlDjVNrFhntgP1m4YVtucVP2/gFkYZFKf3qLFvJuHXRuiv+BhU1J0GkUpFn4ReQ8atGcSYL+SaQXz88PCuJ4igh81AfZFBhaCjM+3oWzdjN7ONgu8W/NWdSSjFjV8/KjTBcVsDsBN7v3dB5uPDsDUypWX9EqNmELWICHrI+EmbbkolHYtKBfmh+vE3G2iKZ3R+U7wHesvv9XovN4tdQ4SBugbaZ47jsiWrbTNS7Qa0oAuxYS3cRib6xI0IN4MYbIigh4BVYM48tsU15X3+aRM9W435Ea0gs0a7mHanOioLl63nsiWr+54/tCpd8i2/n1LB1n6gVrut/mTr+S5bspqVWz7gurYjfX0WxrVXbvmgqGZMMqHYtbeHsXMfL/jcmxqTvlxiBmHd5UTlLqqIGmgGUYtIC7oB4tY+C5wXmY6+9knbWbohYHa1SZJ1qq+IlJsIWrFr52UdMKaPb+b3a94ussnpOn5bojm1iksoRVZrR3eRAm466+iiQcPpfE7Hu9HRmS4owTusIcG+nmxBazrjs3Mq1ZtK1gGqbO3TItWercaaQcQVtxZ0IugBMItgU2MSrXGtx23Xid74Ibr9UP1Ee7gxrCFBU2NDgZ3mIlXgr16MF376b46d+7jvgcfK5gUn9z32E2FiDBJ+Yv+Hp5Ls2tdTEG3kNni5Xffms44uaxRKVWus1HAziLgigh4CQaIc3DDPbJ1+qAMRQcj56Fdf82XHQWNIfV2gxhBueM0WnWbUXlg/p6CfvbXaotV1FAQFjncSCaV44/qTAp8zsgyiZhBxRZpEh0DQKAcnzItZTmFipWRhmunqzjBm7uO2+7ozvaG8D/P53BZy7dxHXlgXZkv57DO9um/QSnd129ZX94vb9+FnQTryZHthxa/gySuL9408HL6yCA6dXHm7hMCIoPskrKgCP4tZpYhgNXHqaBSkRZydu8RvspEfSpXdZEK51qn3U0AtkmT2wH/eAM/eWLyvpRVOvxU+8emymxGbkr0xQQTdJwOdNYP/VOogJXRLYURjkj2ZbGgDhnWQ6uhM0/7AmoLFRTeSCcXCrx5VtGgbhUFtWEO9Y536sFPjyy5uEWsGEfmSvTFEBN0npc6a3boEuWG4Y0r1QTuRrFNcc+pEAMfQyaDns4rawmXrfYs5YDt99nKzhL0W4IRx/nKnxvsRNzvB97Qpws0gYpc0FQNE0H1i/UGbo1zcoiP8/OjdZmahu19U4UMnu8E74Qdgv6H1Re8v6ACUyeqiH7GXi+vMY1toHT3S9rOxCz8MEuZppk7lFnbN4Z1GjoFR7KwSGaF2gt/+4BrQ9L1PYxAY9tEWvrTh57DlT8UXmnpxrhnEkP0GbPNAiUXSVMwQQQ+A3Sxt/mkTi7ZZRdxNsG1/qA+s4drH1rFjd4aEj7T+IGR6dZ8QOZ11194eTjnqIF9RIV2WZBuvRCEnrD/i4S7ZtACPv/R2XyKR3Wdr/cxLvcvJ6v4BaiBt9bzwEjc7wTeHXE5Um/jH5CI+XfcWPG05yYyrYdqPIlc/PLJJUzFGBD0AV3WsLYiWMH7Q159xpGOSjdettO0PNav7shLLEUWxLV8y1omu7gwPrUpz5rEtPP7S264ZktYf38Jl60uaCVvP4xXabNjk1srPvD1s15VBWC4CL3GzE/zP1b3MTcnbOVB1FZ/wlJvhmG9BXXQrZPstPSH4J7rfdsTo6Ezbhr51Z3q5dMlqJv3sSds62F6tvapxe5lK1tl2/jbTnenlmde209jgPObb/fjc3s+IxiTnTR1Fsq7w6nZ+eOvMPwh23YT8dn8qhXRXd8kdiwxb013dRd9Jsk6xe1+uDEGdyt33nFS3gvVDvsnmobO5p+Ef+sR8r05y4b5LGbPnHqYNfRhaz6+amPvt5lRKpyjBHZmh+8Rr5rljdybn0wRfvmBju5droRwY5QO8sBMZM3Y/PqeZpoK+xdglL75VvNOC1+fSlLJ3HzjdEV1/xpF9Wbhedygq/z4+2LWXbp+fVSmuF6utmn5ff1M+k7Vr915mJ5bz8+SdRa9/R4+kvecHPNs7sW9btWe4QSNXQi/ZO8gRQfcgSCy04Z82/4G63Up3dKbZta8nVHvDxsn+lqaUra96zMftjzfqjAO2zT2sn5uXy+WUow6y3e52R2RufO2UeAWwKV9yYNLPnvQt6KW4XpyabIweXs+5vQ8zJ3kPWMatV7Kjac9cQNfwT9M+cxxnAhsjFMctkSvVRQTdhVJioa0zcjc/4cJl64vELWqM+XiKD3bts7Xfbjbm5nJxmxlbq0x6VTZ85rXtruexYh1knBabE6aRJKjbJ6j7zGxTij1cXv8A36v/A+wtPO753gnM6/keW/QnUfQPOAZREkqJXKku4kN3oZSUc+vinpufsJp/5H7LKa3YuMPRfqcZphNu+4w7FnNvVDecPju3CAlzv9Bzptgn0Ji3D3dw6zjdPQSJzujoTDOSD7kxeTubh87m1aHfyYl5nqfrPsdn9tzOmD33MDtzFVv0JwNfoxo42Rd1u2sFmaG7EFRwjTRx8Jf15xVOd8QnhrH5/d2BZvGpZKKgHntTY5KP9vQUlYQ1H5NK1jn61Xu17quNbi1PG2bUiFGH3e8AqoHD5z3BOVMOpXX0yIIqik7cteJN7lrxZl9+AMC9L7xFr9YklOKcKYcW1FR3Eu5UfR3apmSuL991vhlE24anaLOUC7+r5wRu6DmHn531OQA+WroWYhYBIpEr1UWqLbrgFuqWrFMkE/31yUc0Jrnm1ImOpXEht9A1/7SJjjHoBdc+fCR3f/+zdHSmHTvr2HGzTU1wP4PLYfMexyu501r+N4hdXrQ0pTwXK51I1Cl6g2Sm4q+muFPVS6P2uu+s0XdfhUcuhvSqol3/3NPGrT1t7KWhb5tRNjiudU7iandckPK5JeLlQ3dq8uA2EBiNjo2ZoJ907iAz4WENCXbv67U91/BUEqVyvmHrD+2qjrUFSTNOGO/ZK647aHKREVlSjlhxJ7xKGTsVFzPKE5uxvv76z+zmuJevcmwG8YU/HsFbO/e52iQIdoigD4COzrRjzRNjgcraOMFPGOJ5JlG3Xi+sVH+vmat1lnpVx9o+F4QbXg0fDIKIulOnpjqF551DqZi/Pzs3QZ2CXfuKv4cRjUk6f9ov6Mbrp/au5JbkbXxM7S6+WNsiOOrsPj9OpDoRCbHCTdBlUdSDtkktjiVSrQt5GvcORmbuXvGm70SkUvFyQ5gTnDo60zzz2nayWtPSlGJEo7Mv2u8s2q8OJxOqwIduRJq0NKXKlgwE/Qt1TqF2dmIOpugXrWH1vbQ9MoFXE2fx24aFfWLepYdxRfJKmL8z9+/ocwqc8pJUI5QDWRT1QfvMcUXlYI3sxlIFWJOrdnjpktUFRbwqHfmyLZ/laA0/rCSZXl3g7unVuk/k/biBSsG8UBfkM68jy8WpJ2H+7KJ9m7IHcnnmB/xFfyq3YS98vjPtKNKSVCOEjQi6X6wRD/nnYQhwuqubS/Od6yvtRz64KRXqXUFYZHo1d78wMDE3R/Oku7r7Ys+tVTDdsls1MIR9/LD+YS6pfyS3w3zr0dLKedu/wZ8+bLa1Qep7C5XElw9dKXUicAuQAO7QWi+w7D8X+Lv804+AH2it17idMy4+dHBe5AxSZjaKGD7bMKNVqoU1FDNIdIWdP7s5uZdL9V2cW28tXQhP907ihMv/T18ziFIXzwWhFAbUU1QplQBuA74EbAVeVEo9qrV+xXTYJuCLWusdSqlZwGJgysBNjwZu2W83nXV0JDrr+MWIgjHquV+2ZLVjA+SoM6IxaRuxExTjdf/y7yu4aPciZiX+XHTMg73HcV3mXLrYn5amFCeYxNzrDkeyJIVK4cflMhnYoLXeCKCUug84HegTdK3186bjVwCHhGlktXGrx2KIgTnErZyRGaVghASaa4WbB6FyiXkqWee7FkopmCNNvHCMjX7/DXjsR7RtfpY2yN2D5tlw+Lc46/UZvJ/pXyBW5O7Ipi1YzvTxzb5qxhuLrxKfLZQbT5eLUuqrwIla6+/ln38DmKK1vsTh+CuA8cbxln1zgDkAo0aNOnbLli0DNL8y2N1Sm1vL2f2wk4lcyGAUhN2c9ATlqw1uxfBVtz+4piw1a4Y1JPjKMd5uFuv3N1Ft4pcNv2acsvHRz7iaR4Z9lRue2ujZmcpPWKbh1gL7nqQS2SIEZUBx6EqprwEzLYI+WWv9Q5tjpwO3A5/XWr/vdt44+dChsOpiKT/sqOA3hjyu10vUKfYfUs/O7n5XzMJl6xn94YsuzSBugmO+DXV1jvHhpfQvNZcTcFuHEf+6EIQB+dDJ+c3NlYwOAbbZXOSvgTuAWV5iHkfcmjbHRcyh8gu4lb5eb1bnhVdz1IfPMKvja7SpHkyZ9ezVSS7NXMS/ZyezacEpBa93ikkvZY2kV2seWpWmdfRIqUIoVAQ/gv4icIRSaiyQBs4GCoJwlVKjgKXAN7TWr4duZYSQH2BlKOWuR5F1bAbxth7JjzM/4P9l+5tB2CWMBf1+vezszvQy/9F1juswdUrR4RKrLghB8BR0rXWPUuoSYBm5JaM7tdbrlFIX5vcvAn4KfBy4XeWy4XqcbgniTqXjxAcrmpyP3Clb0yBJDxckHuOK5ANF+17NHsoVmQtZp8cW7XOqAOj2/SbrlGvVSidh7+rOODbd7tVaYtWF0JBaLgEJs9aK4I4hmEv+/CbmYJnGfDOI75rqhxuYm0HYYY34seJWRXJEY5LGhnrHBVi3xWZjgfjy+9c4NtbIai3RL4InUpwrZMzhZ3GN4Y4LCqivU+yX3clVybs4M/GnomMe753M/My32U6T67n8LkC6tadzK20LeBZycyrJa0aiXwQ3BrooOuixVlM0l6AV90v5OJj3uC55JzMSq4v23d1zAgt6zmFf/X6kkgl2ZjJ9IaSPv/R2UQu7IE0WnCJzFPQVVHNqRD2iMWnbPs+IRffzNyM9OIVSEUH3wOpiMYeu2YUwCgPjCLWVhclfc3TdG0X77JpB0JMlqzXDU0m2dXXzzGvbuebU3MJnqUk87TPH2bpdzI2unRohX3PqRNeOPXYlgu2QxXehFETQPfBK69bEKw49ihyjXueXyV8xpu6/i/b9LPMNftc7k6xLpedMr+4baI3Z8pnHuou3U9amsd2rmbUd6a7uvkHDaTCx7ndy2UkPTqEUxIfugZs/1YzTrbaIvT3T6zodm0H8eN+FLM1+Af+trIuxfu7W9nl25ZDPmnyoZyq/W0E2ozVdEFdJXBpdSNmC6CA+9BIxd4n3wk7MQcS8H80Zdc/yy4ZFRXu69DAuy1zEM9lJIV6tELNfev6j6wrEHCCT1Z61182uEzeXTBChc5rRQy5qJgoC2tGZLijfkO7qpv3BNQX2C9FABN2Bjs40d5epucJgoY4s5yf+wNXJu4v2FTWDqACGuyRoCj9QVEPdKZqlFN+3tdGFXcORasaqX/vYuqJaPJlezbWPrRNBjxgi6A64+VEFZ4awj7+pf5iLjWYQJjqzf8XfZubwX3rgxThV3qfS6CP5yMDIygwDp0iYMHzfTuUHqhX54nT36bRdqB4i6A5IlIF/9mc38+rvYXb98qJ9T/dO4urM+WzjgHAvqnP+6svvt++jYrd2YWRl+slAtWKdJdtFqwQJjXRD6r4IpSKC7oDEmLvTTBfXJn/HSTbNIB7q/TzXZc5jBx8r2/WbGpO0P2ifdQk5MU/YRJB0Z3ppSiVJJrKBS/qaZ8le0SwDwa3+fjVoSiVt3VRNKedG4kJ1EEF3wG4GNtgjVkard1hQfwefTbxStO+Onln8sudr7GZoRWz5aE8Gt94ZLU0pxxntzu4M504dxb0vvGU7ICQTylHszecsV5Pncs7+S2H+aRNto4LmnzbR5VVCNRBBd8BpBmbURB8sTFSb+MfkIj5d91bRvhsyX+c3vaeQqcKfkZuYG+Ln9F01NSZ5aFXacXbfm9WeGZ/lpJyz/1qwR3BG4tB9YE39/5+9PfRGoRVRmfhs3TpuSt7OJ9WOon1XZr7DPb0z0C6JPtVm2uEj2fx+t20mr99mFU2pJHt7spGPDxcGHxKHPgDsUv+TdYraqrWoOanuBW5K3s4Q1VOwx2gG8YfsZAaS6FNJnn/jgz4RN4t5QinOPLbFVzjqzu4MN511tMxKhVgxqAXdT/abXQhZJqttF9ziRB1Z/qH+Ds6u/2PRPrtmEHHC6VsxOggNd1jkM2M0ABcBF+LEoBV0v8kbTgtrcRTzIezjN8kbOS5RnAHr1gwibKYdPpKvtY5y7NFaTrozvQxN1pFKJhxT/JMJVbUFSEEYCNF1hJYZt+QNg47ONHXK3s0Ql5Ctj/ERTzW0s3nobNYP/XaRmLft/Rlj9tzDrH2/qIiYAzy/8QPaJrXw3NwZtDSlQhVzP06hHbszXH/GkX11Wcxf8YjGJAu/epTMzIVYMmhn6F7JG8YM3m4mnkomcND5SHAQ7/PUkHb2U3ts9x+/90Y264MqbFU/Wufq5FzXdmToyTKpZB2ZrHaNMU8oJe4UoSYZtILulbzhVDY3oRTXn3EklznU8qgWbs0g3tEjOGXvP/AewytvmAN3r3iT1tEjB5TApciFIH60p6cvRnp3JkuyTjmGHUI83WWC4IdB63JpnzmOVDJRsM2IX+7oTDuKTFZr2ia1RKJe9RFqKw83/JTNQ2fz/NC/KRDzv2T/igl77mTMnnuYuve2SIk59FcmtPse/NDSlGLTgpNpbKi3rZzY2FDf51Kxe60g1CKDdobuVrbUWBy1wxByv51nwsatGcTfZ87jd70z6SW4QFYDa0MIvzN1c9akm+vsprOOjlTGpSCUm0Er6GCfuj1twXJHkTaLgVcZ1TA5Pt8MYrhNM4jL913IQwNsBlEtEvmFCON7mLZguaeoK+DMY/u/NzfXmWQ4CoONQS3odrgt0g2pL/ZQlSfkzrkZxE7dyGWZi1iePSb0q1Yaqy/bz12PBn6/5m2eeW0727q6aWpMkqxTBW4X68ArAi4MFkTQLbgt0nV1Z5i3dC0rt3xg21l+ILg1g9icPZAfV7gZRBCM1mtB69xYfdl+3S9d3Zm+xKAduzMkE4qmVJKd3RmZhQuDGqnlYsGux6OVsGblQ9jHJfUd/LC+o2jf6uzhtGcuCKUZRLkxsmaN//18Pl51UcbOfTzQZ9zSlOK5uTMCvEIQ4onUcgmAn1niQMR8f3Yzt/5ezq1/umjf8t6juTpzPmmaB3CFymO4Toz/zZ9PUyrJrn09BXHhVj+4HUHDGaX5gyCIoNsSZJHOD810MT/5O06uUjOIamJXM0UDz7y23fV1TvXoU8k6dtvUzq10GKmfOkCCUGlE0F0YSJOL0eodrq+/g89FoBlEFPGaUXuFlVYzFDFqTZwFwcCXoCulTgRuARLAHVrrBZb9Kr//JGA38G2t9V9CtrXi2InK9PHNPLQqbetjd2sGsTDzdRZXqRlEFPEzo3aLUKnm7DhqTZwFwcBzUVQplQBeB74EbAVeBM7RWr9iOuYk4IfkBH0KcIvWeorbeUtZFO3oTDP/0XV9t/EjGpNcc+rEgh9Rbvb0Et1uLW1CJO7NIOJOKlnH3p4sTv1GjMqOP1n6Up+rRik4d8ooWkeP5MqH1xY0jE7WwX5Dk3TtztDUmETrXG1082O3X8x5U0cVhFQarwky8FjdOdPHN/edU9w78aIcrjm3RVE/gv5ZYL7Wemb++TwArfX1pmN+DfxRa31v/vl64Hit9dtO5w0q6B2d6aK+hpArdWpUx+voTPPjJaspr5RrZtX9mZuTtzNEFfqH9+p6LstcxBPZKcQx0UcoL346HvmJspLOSfHA7rsM47tzE3Q/U8cWwOxD2JrfFvSYAbFw2foiMQfI9Oq+krcLl60vi5grspyb+L9sHjqbzUPP5VcNt/SJ+Tt6BLP3/YQxe+5h3N5/44nsVETMBTus5ZntcCoKF/Q8QvXxU6I7bPw4dO3Uyaqsfo5BKTUHmAMwatQoH5fux20RzdgXZuhaPT1ckPg97cn7i/a9mj2U9swFvKwPC+16wuDA62/U79+whGlGH68S3eXAj6BvBQ41PT8E2FbCMWitFwOLIedyCWKoW1yyscA2kFKsACn2cHn9A3yv/g9F+57vncC8nu+xRX+y5PMLgtdisN+/4ShU+xTc8SrRXQ78uFxeBI5QSo1VSjUAZwOPWo55FPimyjEV2OnmPy+F9pnjSNYV3wiY24W1zxwXePlxBB9yY/J2Ng+dzatDv1Mg5k/0TuYze25jzJ57mJ25SsRcGBB+wiv9lBOWipHxwK1Ed7nwnKFrrXuUUpcAy8iFLd6ptV6nlLowv38R8AS5CJcN5MIWzw/bUGMRwS3KxfjfK8rlYN7j75O/5YREZ9G+u3tO4Bc9Z/Mhw8J+C0IZqEaUy/BUEqWga3fhY2tESilRLk6hshLlEj+qUe1z8NRyefc1eORiSNtc8wtXwHHtkBy8iT6CIMSDwVvL5c0X4OELYMem4n1f/jlMuRAStf0RCIIweKg9NXv9SVj6fdjTVbyvbREcdTaR7vAsCIJQIvEXdK1hzX3QcWHxvqHD4YzfwKdmVt4uQRCEChNPQc/2wgu/hmXziveNGAtfWQSjplbeLkEQhCoSP0Hf9Cz86ymF21pa4fRb4ROfro5NgiAIESB+gr7fJ3L/H/FlOPmX0HSo+/GCIAiDhPgJevM4mL+z2lYIgiBEDqnrKgiCUCOIoAuCINQIIuiCIAg1ggi6IAhCjSCCLgiCUCOIoAuCINQIIuiCIAg1ggi6IAhCjVC1euhKqe3AFh+HHgC8V2ZzBorYGA5iYziIjeEQVRtHa62b7XZUTdD9opRa6VTMPSqIjeEgNoaD2BgOcbDRirhcBEEQagQRdEEQhBohDoK+uNoG+EBsDAexMRzExnCIg40FRN6HLgiCIPgjDjN0QRAEwQci6IIgCLWC1jqy/4ATgfXABmBuGc5/J/Au8LJp20jgKeC/8v+PMO2bl7dlPTDTtP1YYG1+3z/R78oaAizJb38BGGN6zbfy1/gv4FsuNh4KPAO8CqwDfhQ1O4GhwJ+BNXkbr42ajaZjE0An8Pso2ghszp97NbAyojY2AQ8Cr5H7u/xslGwExuU/P+Pfh8ClUbKxXP8qdqHAhuV+eG8AhwEN5MRiQsjXOA44hkJBv4H84AHMBX6Rfzwhb8MQYGzetkR+35/zf9QK+AMwK7/9ImBR/vHZwBLTD3Rj/v8R+ccjHGw8CDgm/3h/4PW8LZGxM3++/fKPk/k/8KlRstFk64+Be+gX9EjZSE7QD7Bsi5qN/wp8L/+4gZzAR8pGi468A4yOqo2halqlLhTYsNyHuMz0fB4wrwzXGUOhoK8HDso/PghYb3d9YFnexoOA10zbzwF+bT4m/7ieXNaZMh+T3/dr4Byf9j4CfCmqdgKNwF+AKVGzETgEeBqYQb+gR83GzRQLemRsBD4GbCI/U42ijRa7vgw8F2Ubw/wXZR96C/CW6fnW/LZyc6DW+m2A/P+f8LCnJf/Yzs6+12ite4CdwMddzuWKUmoMMIncDDhSdiqlEkqp1eRcWE9prSNnI3Az8LdA1rQtajZq4Eml1Cql1JwI2ngYsB34rVKqUyl1h1JqWMRsNHM2cG/+cVRtDI0oC7qy2aYrbkU/Tva42VnKa+wvrtR+wEPApVrrD6Nmp9a6V2t9NLlZ8GSl1P+Kko1KqVOAd7XWq1zsqqqNeaZprY8BZgEXK6WOi5iN9eTclL/SWk8CdpFzX0TJxtxJlGoATgMecLGvqjaGTZQFfSu5BUGDQ4BtFbjufyulDgLI//+uhz1b84/t7Ox7jVKqHhgOfOByLluUUklyYn631nppVO0E0Fp3AX8kt6AdJRunAacppTYD9wEzlFJ3RcxGtNbb8v+/CzwMTI6YjVuBrfk7MMgtjh4TMRsNZgF/0Vr/d/55FG0Ml0r5doL+IzcT2EhukcJYFJ1YhuuModCHvpDChZMb8o8nUrhwspH+hZMXyS0CGgsnJ+W3X0zhwsn9+ccjyfkhR+T/bQJGOtingH8DbrZsj4ydQDPQlH+cAp4FTomSjRZ7j6ffhx4ZG4FhwP6mx8+TGxgjY2P+2GeBcfnH8/P2RcrG/PH3AedH8TdTrn9VF26PH95J5KI63gCuLMP57wXeBjLkRtbvkvODPU0u5Ohp85cBXJm3ZT351e789lbg5fy+W+kPbRpK7nZvA7nV8sNMr/lOfvsG8x+djY2fJ3fL9hL9YVgnRclO4K/JhQK+lD//T/PbI2Ojxd7j6Rf0yNhIzj+9hv7wzyujZmP+uKOBlfnvu4OccEXNxkbgfWC4aVukbCzHP0n9FwRBqBGi7EMXBEEQAiCCLgiCUCOIoAuCINQIIuiCIAg1ggi6IAhCjSCCLgiCUCOIoAuCINQI/x+SIzUiwwQMXAAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "streudiagramm(sale_price, df_top[\"Mas_Vnr_Area\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -656,7 +898,7 @@ "dtype: int64" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -667,7 +909,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -677,7 +919,7 @@ "dtype: int64" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -688,7 +930,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -794,7 +1036,7 @@ "[2930 rows x 2 columns]" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -805,7 +1047,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -1017,7 +1259,7 @@ "[5 rows x 80 columns]" ] }, - "execution_count": 13, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -1030,7 +1272,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -1134,7 +1376,7 @@ "4 1998 0 " ] }, - "execution_count": 14, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -1147,7 +1389,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -1169,7 +1411,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -1179,7 +1421,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -1189,7 +1431,7 @@ "dtype: int64" ] }, - "execution_count": 17, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -1207,7 +1449,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -1220,7 +1462,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -1235,7 +1477,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -1298,7 +1540,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -1364,7 +1606,7 @@ "3 0.778857 0.123152 StackingCVRegressor" ] }, - "execution_count": 24, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -1375,7 +1617,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -1441,7 +1683,7 @@ "3 0.791277 0.078536 StackingCVRegressor" ] }, - "execution_count": 25, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" }