{ "metadata": { "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.10-final" }, "orig_nbformat": 2, "kernelspec": { "name": "python3", "display_name": "Python 3.8.10 64-bit", "metadata": { "interpreter": { "hash": "767d51c1340bd893661ea55ea3124f6de3c7a262a8b4abca0554b478b1e2ff90" } } } }, "nbformat": 4, "nbformat_minor": 2, "cells": [ { "source": [ "# Dataset preparation" ], "cell_type": "markdown", "metadata": {} }, { "source": [ "## Download " ], "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " Date AveragePrice Total Volume 4046 4225 \\\n", "count 18249 18249.000000 1.824900e+04 1.824900e+04 1.824900e+04 \n", "unique 169 NaN NaN NaN NaN \n", "top 2016-02-28 NaN NaN NaN NaN \n", "freq 108 NaN NaN NaN NaN \n", "mean NaN 1.405978 8.506440e+05 2.930084e+05 2.951546e+05 \n", "std NaN 0.402677 3.453545e+06 1.264989e+06 1.204120e+06 \n", "min NaN 0.440000 8.456000e+01 0.000000e+00 0.000000e+00 \n", "25% NaN 1.100000 1.083858e+04 8.540700e+02 3.008780e+03 \n", "50% NaN 1.370000 1.073768e+05 8.645300e+03 2.906102e+04 \n", "75% NaN 1.660000 4.329623e+05 1.110202e+05 1.502069e+05 \n", "max NaN 3.250000 6.250565e+07 2.274362e+07 2.047057e+07 \n", "\n", " 4770 Total Bags Small Bags Large Bags XLarge Bags \\\n", "count 1.824900e+04 1.824900e+04 1.824900e+04 1.824900e+04 18249.000000 \n", "unique NaN NaN NaN NaN NaN \n", "top NaN NaN NaN NaN NaN \n", "freq NaN NaN NaN NaN NaN \n", "mean 2.283974e+04 2.396392e+05 1.821947e+05 5.433809e+04 3106.426507 \n", "std 1.074641e+05 9.862424e+05 7.461785e+05 2.439660e+05 17692.894652 \n", "min 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000 \n", "25% 0.000000e+00 5.088640e+03 2.849420e+03 1.274700e+02 0.000000 \n", "50% 1.849900e+02 3.974383e+04 2.636282e+04 2.647710e+03 0.000000 \n", "75% 6.243420e+03 1.107834e+05 8.333767e+04 2.202925e+04 132.500000 \n", "max 2.546439e+06 1.937313e+07 1.338459e+07 5.719097e+06 551693.650000 \n", "\n", " type year region \n", "count 18249 18249.000000 18249 \n", "unique 2 NaN 54 \n", "top conventional NaN Northeast \n", "freq 9126 NaN 338 \n", "mean NaN 2016.147899 NaN \n", "std NaN 0.939938 NaN \n", "min NaN 2015.000000 NaN \n", "25% NaN 2015.000000 NaN \n", "50% NaN 2016.000000 NaN \n", "75% NaN 2017.000000 NaN \n", "max NaN 2018.000000 NaN " ], "text/html": "
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DateAveragePriceTotal Volume404642254770Total BagsSmall BagsLarge BagsXLarge Bagstypeyearregion
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unique169NaNNaNNaNNaNNaNNaNNaNNaNNaN2NaN54
top2016-02-28NaNNaNNaNNaNNaNNaNNaNNaNNaNconventionalNaNNortheast
freq108NaNNaNNaNNaNNaNNaNNaNNaNNaN9126NaN338
meanNaN1.4059788.506440e+052.930084e+052.951546e+052.283974e+042.396392e+051.821947e+055.433809e+043106.426507NaN2016.147899NaN
stdNaN0.4026773.453545e+061.264989e+061.204120e+061.074641e+059.862424e+057.461785e+052.439660e+0517692.894652NaN0.939938NaN
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25%NaN1.1000001.083858e+048.540700e+023.008780e+030.000000e+005.088640e+032.849420e+031.274700e+020.000000NaN2015.000000NaN
50%NaN1.3700001.073768e+058.645300e+032.906102e+041.849900e+023.974383e+042.636282e+042.647710e+030.000000NaN2016.000000NaN
75%NaN1.6600004.329623e+051.110202e+051.502069e+056.243420e+031.107834e+058.333767e+042.202925e+04132.500000NaN2017.000000NaN
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" }, "metadata": {}, "execution_count": 1 } ], "source": [ "# https://www.kaggle.com/datasets/jessicali9530/animal-crossing-new-horizons-nookplaza-dataset\n", "\n", "!mkdir aitech-ium/data\n", "!kaggle datasets download -p aitech-ium/data -d neuromusic/avocado-prices\n", "!unzip -o aitech-ium/data/avocado-prices.zip -d aitech-ium/data/\n", "!rm aitech-ium/data/avocado-prices.zip\n", "\n", "import pandas as pd\n", "import seaborn as sns\n", "\n", "cols = list(pd.read_csv(\"aitech-ium/data/avocado.csv\", nrows=1))\n", "# print(\"###\\n\", cols, \"\\n###\")\n", "avocados = pd.read_csv(\"aitech-ium/data/avocado.csv\", usecols=cols[1:])\n", "avocados.describe(include=\"all\")" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "conventional 9126\norganic 9123\nName: type, dtype: int64\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": {}, "execution_count": 42 }, { "output_type": "display_data", "data": { "text/plain": "
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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n" }, "metadata": { "needs_background": "light" } } ], "source": [ "print(avocados[\"type\"].value_counts())\n", "sns.pairplot(data=avocados.loc[:, [\"AveragePrice\", 'Total Volume', \"Total Bags\", \"type\"]], hue=\"type\")" ] }, { "source": [ "## Split the data with CLI" ], "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": 21, "metadata": { "tags": [] }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "18250 aitech-ium/data/avocado.csv\n", " 9126 conventional\n", " 9123 organic\n", " 1 type\n", "ser\n", "dobry\n", "tail: error writing 'standard output': Broken pipe\n", " 2000 aitech-ium/data/avocado.data.test\n", " 14000 aitech-ium/data/avocado.data.train\n", " 2249 aitech-ium/data/avocado.data.valid\n", " 18249 total\n" ] } ], "source": [ "!wc -l aitech-ium/data/avocado.csv\n", "# !head -n 5 aitech-ium/data/avocado.csv\n", "!cut -f 12 -d \",\" aitech-ium/data/avocado.csv | sort | uniq -c\n", "!echo ser\n", "!grep -P \"^$\" -n aitech-ium/data/avocado.csv\n", "!echo dobry\n", "\n", "# shuffle and split the data\n", "!tail -n +2 aitech-ium/data/avocado.csv | shuf > aitech-ium/data/avocado_shuf.csv\n", "!head -n 14000 aitech-ium/data/avocado_shuf.csv > aitech-ium/data/avocado.data.train\n", "!tail -n +14001 aitech-ium/data/avocado_shuf.csv | head -n 2249 > aitech-ium/data/avocado.data.valid\n", "!tail -n 2000 aitech-ium/data/avocado_shuf.csv > aitech-ium/data/avocado.data.test\n", "!rm aitech-ium/data/avocado_shuf.csv\n", "\n", "# Verify the length of the splitted data\n", "!wc -l aitech-ium/data/avocado.data*" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Train by TYPE\n", " 6998 conventional\n", " 7002 organic\n", "Train by REGION\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "Dev by TYPE\n", " 1140 conventional\n", " 1109 organic\n", "Dev by REGION\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "Test by TYPE\n", " 988 conventional\n", " 1012 organic\n", "Test by REGION\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n" ] } ], "source": [ "!echo \"Train by TYPE\"\n", "!cut -f 12 -d \",\" aitech-ium/data/avocado.data.train | sort | uniq -c\n", "!echo \"Train by REGION\"\n", "!cut -f 14 -d \",\" aitech-ium/data/avocado.data.train | sort | uniq -c\n", "!echo \"Dev by TYPE\"\n", "!cut -f 12 -d \",\" aitech-ium/data/avocado.data.valid | sort | uniq -c\n", "!echo \"Dev by REGION\"\n", "!cut -f 14 -d \",\" aitech-ium/data/avocado.data.valid | sort | uniq -c\n", "!echo \"Test by TYPE\"\n", "!cut -f 12 -d \",\" aitech-ium/data/avocado.data.test | sort | uniq -c\n", "!echo \"Test by REGION\"\n", "!cut -f 14 -d \",\" aitech-ium/data/avocado.data.test | sort | uniq -c" ] }, { "source": [ "## Split data with sklearn (wihtout normalization)" ], "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "TYPE\n organic 7044\nconventional 6956\nName: type, dtype: int64 \n\nconventional 1152\norganic 1097\nName: type, dtype: int64 \n\nconventional 1018\norganic 982\nName: type, dtype: int64\nREGION\n DallasFtWorth 276\nCalifornia 270\nPlains 270\nBoise 270\nChicago 269\nStLouis 268\nTotalUS 268\nColumbus 267\nLosAngeles 266\nBoston 265\nWestTexNewMexico 265\nLouisville 265\nSanDiego 265\nRoanoke 265\nDetroit 264\nSyracuse 263\nMidsouth 263\nPhoenixTucson 262\nCharlotte 262\nPittsburgh 262\nSacramento 262\nSeattle 261\nAlbany 261\nRichmondNorfolk 261\nBaltimoreWashington 261\nHartfordSpringfield 260\nHouston 259\nPortland 259\nGrandRapids 259\nCincinnatiDayton 258\nSouthCarolina 258\nNortheast 258\nBuffaloRochester 258\nLasVegas 257\nNorthernNewEngland 257\nOrlando 256\nWest 256\nPhiladelphia 256\nHarrisburgScranton 255\nNewYork 255\nJacksonville 255\nSouthCentral 254\nGreatLakes 254\nNashville 254\nIndianapolis 254\nSpokane 252\nDenver 251\nTampa 251\nRaleighGreensboro 250\nAtlanta 248\nSanFrancisco 248\nNewOrleansMobile 247\nSoutheast 247\nMiamiFtLauderdale 243\nName: region, dtype: int64 \n\nIndianapolis 53\nSpokane 51\nAtlanta 49\nOrlando 49\nPortland 49\nRaleighGreensboro 49\nNewOrleansMobile 49\nSoutheast 49\nSouthCentral 48\nHouston 48\nHarrisburgScranton 47\nCincinnatiDayton 46\nSeattle 46\nGrandRapids 46\nNortheast 46\nJacksonville 46\nBaltimoreWashington 45\nGreatLakes 45\nNashville 45\nBoston 44\nMiamiFtLauderdale 44\nSouthCarolina 44\nWest 43\nPittsburgh 43\nRoanoke 43\nNorthernNewEngland 42\nSyracuse 41\nCharlotte 41\nTampa 40\nDetroit 40\nNewYork 40\nDenver 40\nBoise 40\nRichmondNorfolk 40\nSanFrancisco 39\nPhoenixTucson 39\nLosAngeles 39\nPhiladelphia 39\nSanDiego 39\nHartfordSpringfield 38\nMidsouth 38\nLasVegas 37\nSacramento 37\nWestTexNewMexico 37\nColumbus 36\nCalifornia 35\nLouisville 35\nChicago 35\nTotalUS 34\nPlains 34\nBuffaloRochester 33\nStLouis 33\nAlbany 31\nDallasFtWorth 30\nName: region, dtype: int64 \n\nMiamiFtLauderdale 51\nSanFrancisco 51\nTampa 47\nBuffaloRochester 47\nDenver 47\nAlbany 46\nLasVegas 44\nPhiladelphia 43\nNewYork 43\nNewOrleansMobile 42\nSoutheast 42\nAtlanta 41\nHartfordSpringfield 40\nWest 39\nNashville 39\nRaleighGreensboro 39\nGreatLakes 39\nNorthernNewEngland 39\nSacramento 39\nLouisville 38\nJacksonville 37\nMidsouth 37\nStLouis 37\nRichmondNorfolk 37\nPhoenixTucson 37\nHarrisburgScranton 36\nSouthCarolina 36\nTotalUS 36\nSouthCentral 36\nCharlotte 35\nColumbus 35\nSpokane 35\nSanDiego 34\nDetroit 34\nCincinnatiDayton 34\nPlains 34\nNortheast 34\nChicago 34\nSyracuse 34\nPittsburgh 33\nOrlando 33\nWestTexNewMexico 33\nLosAngeles 33\nGrandRapids 33\nCalifornia 33\nDallasFtWorth 32\nBaltimoreWashington 32\nSeattle 31\nHouston 31\nIndianapolis 31\nRoanoke 30\nPortland 30\nBoston 29\nBoise 28\nName: region, dtype: int64\n" ] } ], "source": [ "from sklearn.model_selection import train_test_split\n", "# import pandas as pd\n", "\n", "# avocado_data = pd.read_csv(\"aitech-ium/data/avocado.csv\"\n", "avocado_train, avocado_test = train_test_split(avocados, test_size=2000, random_state=3337)\n", "avocado_train, avocado_valid = train_test_split(avocado_train, test_size=2249, random_state=3337)\n", "print(\"TYPE\\n\", avocado_train[\"type\"].value_counts(), \"\\n\")\n", "print(avocado_valid[\"type\"].value_counts(), \"\\n\")\n", "print(avocado_test[\"type\"].value_counts())\n", "\n", "print(\"REGION\\n\", avocado_train[\"region\"].value_counts(), \"\\n\")\n", "print(avocado_valid[\"region\"].value_counts(), \"\\n\")\n", "print(avocado_test[\"region\"].value_counts())" ] }, { "source": [ "## Stats" ], "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " Date AveragePrice Total Volume 4046 4225 \\\n", "count 14000 14000.000000 1.400000e+04 1.400000e+04 1.400000e+04 \n", "unique 169 NaN NaN NaN NaN \n", "top 2016-06-12 NaN NaN NaN NaN \n", "freq 92 NaN NaN NaN NaN \n", "mean NaN 1.407189 8.577465e+05 2.943651e+05 2.983259e+05 \n", "std NaN 0.402507 3.512504e+06 1.286667e+06 1.221671e+06 \n", "min NaN 0.460000 4.199800e+02 0.000000e+00 0.000000e+00 \n", "25% NaN 1.100000 1.079131e+04 8.442675e+02 2.986128e+03 \n", "50% NaN 1.370000 1.043413e+05 8.506395e+03 2.829617e+04 \n", "75% NaN 1.660000 4.309278e+05 1.100946e+05 1.496662e+05 \n", "max NaN 3.050000 6.250565e+07 2.274362e+07 2.047057e+07 \n", "\n", " 4770 Total Bags Small Bags Large Bags XLarge Bags \\\n", "count 1.400000e+04 1.400000e+04 1.400000e+04 1.400000e+04 14000.000000 \n", "unique NaN NaN NaN NaN NaN \n", "top NaN NaN NaN NaN NaN \n", "freq NaN NaN NaN NaN NaN \n", "mean 2.325363e+04 2.417999e+05 1.843618e+05 5.421891e+04 3219.144964 \n", "std 1.097271e+05 1.002859e+06 7.596825e+05 2.451956e+05 18655.349004 \n", "min 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000 \n", "25% 0.000000e+00 4.990578e+03 2.766528e+03 1.251150e+02 0.000000 \n", "50% 1.791100e+02 3.928295e+04 2.595689e+04 2.591535e+03 0.000000 \n", "75% 6.202515e+03 1.103743e+05 8.358725e+04 2.139652e+04 117.240000 \n", "max 2.546439e+06 1.937313e+07 1.338459e+07 5.719097e+06 551693.650000 \n", "\n", " type year region \n", "count 14000 14000.000000 14000 \n", "unique 2 NaN 54 \n", "top organic NaN DallasFtWorth \n", "freq 7044 NaN 276 \n", "mean NaN 2016.145000 NaN \n", "std NaN 0.935052 NaN \n", "min NaN 2015.000000 NaN \n", "25% NaN 2015.000000 NaN \n", "50% NaN 2016.000000 NaN \n", "75% NaN 2017.000000 NaN \n", "max NaN 2018.000000 NaN " ], "text/html": "
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" }, "metadata": {}, "execution_count": 12 } ], "source": [ "avocado_train.describe(include=\"all\")" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " Date AveragePrice Total Volume 4046 4225 \\\n", "count 2249 2249.000000 2.249000e+03 2.249000e+03 2.249000e+03 \n", "unique 169 NaN NaN NaN NaN \n", "top 2016-10-23 NaN NaN NaN NaN \n", "freq 23 NaN NaN NaN NaN \n", "mean NaN 1.390044 8.298634e+05 2.933153e+05 2.889813e+05 \n", "std NaN 0.397718 3.174887e+06 1.177087e+06 1.153117e+06 \n", "min NaN 0.480000 8.456000e+01 0.000000e+00 0.000000e+00 \n", "25% NaN 1.090000 1.126096e+04 8.691600e+02 3.189790e+03 \n", "50% NaN 1.360000 1.152561e+05 8.641100e+03 3.117744e+04 \n", "75% NaN 1.650000 4.378228e+05 1.125450e+05 1.464013e+05 \n", "max NaN 3.120000 4.293982e+07 1.652980e+07 1.605408e+07 \n", "\n", " 4770 Total Bags Small Bags Large Bags XLarge Bags \\\n", "count 2.249000e+03 2.249000e+03 2.249000e+03 2.249000e+03 2249.000000 \n", "unique NaN NaN NaN NaN NaN \n", "top NaN NaN NaN NaN NaN \n", "freq NaN NaN NaN NaN NaN \n", "mean 2.191039e+04 2.256549e+05 1.701284e+05 5.289702e+04 2629.450240 \n", "std 9.944203e+04 8.715969e+05 6.567467e+05 2.284520e+05 12926.389037 \n", "min 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000 \n", "25% 0.000000e+00 5.343010e+03 2.788080e+03 1.306400e+02 0.000000 \n", "50% 2.226900e+02 4.117010e+04 2.669590e+04 3.004010e+03 0.000000 \n", "75% 6.583030e+03 1.107834e+05 8.087928e+04 2.367152e+04 139.150000 \n", "max 1.800066e+06 1.505188e+07 1.066694e+07 4.081398e+06 303536.640000 \n", "\n", " type year region \n", "count 2249 2249.000000 2249 \n", "unique 2 NaN 54 \n", "top conventional NaN Indianapolis \n", "freq 1152 NaN 53 \n", "mean NaN 2016.138284 NaN \n", "std NaN 0.954479 NaN \n", "min NaN 2015.000000 NaN \n", "25% NaN 2015.000000 NaN \n", "50% NaN 2016.000000 NaN \n", "75% NaN 2017.000000 NaN \n", "max NaN 2018.000000 NaN " ], "text/html": "
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" }, "metadata": {}, "execution_count": 13 } ], "source": [ "avocado_valid.describe(include=\"all\")" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " Date AveragePrice Total Volume 4046 4225 \\\n", "count 2000 2000.000000 2.000000e+03 2.000000e+03 2.000000e+03 \n", "unique 169 NaN NaN NaN NaN \n", "top 2015-12-20 NaN NaN NaN NaN \n", "freq 22 NaN NaN NaN NaN \n", "mean NaN 1.415420 8.242943e+05 2.831668e+05 2.798972e+05 \n", "std NaN 0.409075 3.337410e+06 1.206530e+06 1.134934e+06 \n", "min NaN 0.440000 3.855500e+02 0.000000e+00 0.000000e+00 \n", "25% NaN 1.100000 1.082229e+04 9.649675e+02 2.981325e+03 \n", "50% NaN 1.390000 1.165548e+05 9.738985e+03 3.166765e+04 \n", "75% NaN 1.670000 4.437962e+05 1.186674e+05 1.543340e+05 \n", "max NaN 3.250000 4.632453e+07 1.550361e+07 1.789639e+07 \n", "\n", " 4770 Total Bags Small Bags Large Bags XLarge Bags \\\n", "count 2.000000e+03 2.000000e+03 2.000000e+03 2.000000e+03 2000.000000 \n", "unique NaN NaN NaN NaN NaN \n", "top NaN NaN NaN NaN NaN \n", "freq NaN NaN NaN NaN NaN \n", "mean 2.098755e+04 2.402396e+05 1.805931e+05 5.679278e+04 2853.757120 \n", "std 9.989487e+04 9.906869e+05 7.455384e+05 2.521909e+05 15234.162205 \n", "min 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000 \n", "25% 0.000000e+00 5.381578e+03 3.326650e+03 1.459475e+02 0.000000 \n", "50% 1.916000e+02 4.297953e+04 2.854382e+04 2.693255e+03 0.000000 \n", "75% 6.259010e+03 1.168878e+05 8.530548e+04 2.462513e+04 210.415000 \n", "max 1.993645e+06 1.292398e+07 9.918256e+06 3.917570e+06 311439.990000 \n", "\n", " type year region \n", "count 2000 2000.000000 2000 \n", "unique 2 NaN 54 \n", "top conventional NaN MiamiFtLauderdale \n", "freq 1018 NaN 51 \n", "mean NaN 2016.179000 NaN \n", "std NaN 0.957297 NaN \n", "min NaN 2015.000000 NaN \n", "25% NaN 2015.000000 NaN \n", "50% NaN 2016.000000 NaN \n", "75% NaN 2017.000000 NaN \n", "max NaN 2018.000000 NaN " ], "text/html": "
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" }, "metadata": {}, "execution_count": 14 } ], "source": [ "avocado_test.describe(include=\"all\")" ] }, { "source": [ "## Cleaning" ], "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Empty DataFrame\n", "Columns: [Date, AveragePrice, Total Volume, 4046, 4225, 4770, Total Bags, Small Bags, Large Bags, XLarge Bags, type, year, region]\n", "Index: []" ], "text/html": "
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DateAveragePriceTotal Volume404642254770Total BagsSmall BagsLarge BagsXLarge Bagstypeyearregion
\n
" }, "metadata": {}, "execution_count": 27 } ], "source": [ "avocados[avocados.isna().any(axis=1)]" ] }, { "source": [ "## Normalization" ], "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ " Date AveragePrice Total Volume 4046 4225 4770 \\\n", "0 2015-12-27 -0.188689 -0.227716 -0.230816 -0.199902 -0.212091 \n", "1 2015-12-20 -0.139020 -0.230427 -0.231103 -0.208054 -0.211997 \n", "2 2015-12-13 -1.182069 -0.212085 -0.231007 -0.154478 -0.211325 \n", "3 2015-12-06 -0.809551 -0.223444 -0.230741 -0.185350 -0.211864 \n", "4 2015-11-29 -0.312861 -0.231538 -0.230891 -0.208719 -0.211834 \n", "\n", " Total Bags Small Bags Large Bags XLarge Bags type year region \n", "0 -0.234170 -0.232647 -0.222352 -0.17558 conventional 2015 Albany \n", "1 -0.233350 -0.231568 -0.222335 -0.17558 conventional 2015 Albany \n", "2 -0.234730 -0.233399 -0.222311 -0.17558 conventional 2015 Albany \n", "3 -0.237096 -0.236568 -0.222186 -0.17558 conventional 2015 Albany \n", "4 -0.236718 -0.236154 -0.221924 -0.17558 conventional 2015 Albany \n", " Date AveragePrice Total Volume 4046 4225 4770 \\\n", "0 2015-12-27 0.316726 0.001026 0.000046 0.002660 0.000019 \n", "1 2015-12-20 0.323843 0.000877 0.000030 0.002181 0.000023 \n", "2 2015-12-13 0.174377 0.001890 0.000035 0.005332 0.000051 \n", "3 2015-12-06 0.227758 0.001262 0.000050 0.003516 0.000029 \n", "4 2015-11-29 0.298932 0.000815 0.000041 0.002142 0.000030 \n", "\n", " Total Bags Small Bags Large Bags XLarge Bags type year region \n", "0 0.000449 0.000643 0.000016 0.0 conventional 2015 Albany \n", "1 0.000491 0.000703 0.000017 0.0 conventional 2015 Albany \n", "2 0.000420 0.000601 0.000018 0.0 conventional 2015 Albany \n", "3 0.000300 0.000424 0.000023 0.0 conventional 2015 Albany \n", "4 0.000319 0.000447 0.000035 0.0 conventional 2015 Albany \n", "Train\n", " Date AveragePrice Total Volume 4046 4225 \\\n", "count 14000 14000.000000 14000.000000 14000.000000 14000.000000 \n", "unique 169 NaN NaN NaN NaN \n", "top 2016-06-12 NaN NaN NaN NaN \n", "freq 92 NaN NaN NaN NaN \n", "mean NaN 0.344195 0.013721 0.012943 0.014573 \n", "std NaN 0.143241 0.056195 0.056573 0.059679 \n", "min NaN 0.007117 0.000005 0.000000 0.000000 \n", "25% NaN 0.234875 0.000171 0.000037 0.000146 \n", "50% NaN 0.330961 0.001668 0.000374 0.001382 \n", "75% NaN 0.434164 0.006893 0.004841 0.007311 \n", "max NaN 0.928826 1.000000 1.000000 1.000000 \n", "\n", " 4770 Total Bags Small Bags Large Bags XLarge Bags \\\n", "count 14000.000000 14000.000000 14000.000000 14000.000000 14000.000000 \n", "unique NaN NaN NaN NaN NaN \n", "top NaN NaN NaN NaN NaN \n", "freq NaN NaN NaN NaN NaN \n", "mean 0.009132 0.012481 0.013774 0.009480 0.005835 \n", "std 0.043090 0.051765 0.056758 0.042873 0.033815 \n", "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "25% 0.000000 0.000258 0.000207 0.000022 0.000000 \n", "50% 0.000070 0.002028 0.001939 0.000453 0.000000 \n", "75% 0.002436 0.005697 0.006245 0.003741 0.000213 \n", "max 1.000000 1.000000 1.000000 1.000000 1.000000 \n", "\n", " type year region \n", "count 14000 14000.000000 14000 \n", "unique 2 NaN 54 \n", "top organic NaN DallasFtWorth \n", "freq 7044 NaN 276 \n", "mean NaN 2016.145000 NaN \n", "std NaN 0.935052 NaN \n", "min NaN 2015.000000 NaN \n", "25% NaN 2015.000000 NaN \n", "50% NaN 2016.000000 NaN \n", "75% NaN 2017.000000 NaN \n", "max NaN 2018.000000 NaN \n", "\n", "Valid\n", " Date AveragePrice Total Volume 4046 4225 \\\n", "count 2249 2249.000000 2249.000000 2249.000000 2249.000000 \n", "unique 169 NaN NaN NaN NaN \n", "top 2016-10-23 NaN NaN NaN NaN \n", "freq 23 NaN NaN NaN NaN \n", "mean NaN 0.338094 0.013275 0.012897 0.014117 \n", "std NaN 0.141537 0.050794 0.051755 0.056330 \n", "min NaN 0.014235 0.000000 0.000000 0.000000 \n", "25% NaN 0.231317 0.000179 0.000038 0.000156 \n", "50% NaN 0.327402 0.001843 0.000380 0.001523 \n", "75% NaN 0.430605 0.007003 0.004948 0.007152 \n", "max NaN 0.953737 0.686975 0.726788 0.784252 \n", "\n", " 4770 Total Bags Small Bags Large Bags XLarge Bags \\\n", "count 2249.000000 2249.000000 2249.000000 2249.000000 2249.000000 \n", "unique NaN NaN NaN NaN NaN \n", "top NaN NaN NaN NaN NaN \n", "freq NaN NaN NaN NaN NaN \n", "mean 0.008604 0.011648 0.012711 0.009249 0.004766 \n", "std 0.039051 0.044990 0.049067 0.039945 0.023430 \n", "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "25% 0.000000 0.000276 0.000208 0.000023 0.000000 \n", "50% 0.000087 0.002125 0.001995 0.000525 0.000000 \n", "75% 0.002585 0.005718 0.006043 0.004139 0.000252 \n", "max 0.706895 0.776946 0.796957 0.713644 0.550191 \n", "\n", " type year region \n", "count 2249 2249.000000 2249 \n", "unique 2 NaN 54 \n", "top conventional NaN Indianapolis \n", "freq 1152 NaN 53 \n", "mean NaN 2016.138284 NaN \n", "std NaN 0.954479 NaN \n", "min NaN 2015.000000 NaN \n", "25% NaN 2015.000000 NaN \n", "50% NaN 2016.000000 NaN \n", "75% NaN 2017.000000 NaN \n", "max NaN 2018.000000 NaN \n", "\n", "Test\n", " Date AveragePrice Total Volume 4046 4225 \\\n", "count 2000 2000.000000 2000.000000 2000.000000 2000.000000 \n", "unique 169 NaN NaN NaN NaN \n", "top 2015-12-20 NaN NaN NaN NaN \n", "freq 22 NaN NaN NaN NaN \n", "mean NaN 0.347125 0.013186 0.012450 0.013673 \n", "std NaN 0.145578 0.053394 0.053049 0.055442 \n", "min NaN 0.000000 0.000005 0.000000 0.000000 \n", "25% NaN 0.234875 0.000172 0.000042 0.000146 \n", "50% NaN 0.338078 0.001863 0.000428 0.001547 \n", "75% NaN 0.437722 0.007099 0.005218 0.007539 \n", "max NaN 1.000000 0.741125 0.681669 0.874250 \n", "\n", " 4770 Total Bags Small Bags Large Bags XLarge Bags \\\n", "count 2000.000000 2000.000000 2000.000000 2000.000000 2000.000000 \n", "unique NaN NaN NaN NaN NaN \n", "top NaN NaN NaN NaN NaN \n", "freq NaN NaN NaN NaN NaN \n", "mean 0.008242 0.012401 0.013493 0.009930 0.005173 \n", "std 0.039229 0.051137 0.055701 0.044096 0.027613 \n", "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "25% 0.000000 0.000278 0.000249 0.000026 0.000000 \n", "50% 0.000075 0.002219 0.002133 0.000471 0.000000 \n", "75% 0.002458 0.006034 0.006373 0.004306 0.000381 \n", "max 0.782915 0.667108 0.741021 0.684998 0.564516 \n", "\n", " type year region \n", "count 2000 2000.000000 2000 \n", "unique 2 NaN 54 \n", "top conventional NaN MiamiFtLauderdale \n", "freq 1018 NaN 51 \n", "mean NaN 2016.179000 NaN \n", "std NaN 0.957297 NaN \n", "min NaN 2015.000000 NaN \n", "25% NaN 2015.000000 NaN \n", "50% NaN 2016.000000 NaN \n", "75% NaN 2017.000000 NaN \n", "max NaN 2018.000000 NaN \n" ] } ], "source": [ "from sklearn.preprocessing import StandardScaler, MinMaxScaler\n", "\n", "float_cols = ['AveragePrice','Total Volume','4046','4225','4770','Total Bags','Small Bags','Large Bags','XLarge Bags']\n", "\n", "avocados.loc[:, float_cols] = StandardScaler().fit_transform(avocados.loc[:, float_cols])\n", "print(avocados.head())\n", "\n", "avocados.loc[:, float_cols] = MinMaxScaler().fit_transform(avocados.loc[:, float_cols])\n", "print(avocados.head())\n", "\n", "avocado_train, avocado_test = train_test_split(avocados, test_size=2000, random_state=3337)\n", "avocado_train, avocado_valid = train_test_split(avocado_train, test_size=2249, random_state=3337)\n", "\n", "print(\"Train\\n\", avocado_train.describe(include=\"all\"), \"\\n\")\n", "print(\"Valid\\n\", avocado_valid.describe(include=\"all\"), \"\\n\")\n", "print(\"Test\\n\", avocado_test.describe(include=\"all\"))" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": {}, "execution_count": 37 }, { "output_type": "display_data", "data": { "text/plain": "
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\n" }, "metadata": { "needs_background": "light" } } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "fig, axes = plt.subplots(1, 3, figsize=(24,8)) # (3, 2)\n", "sns.histplot(avocado_train[\"type\"], ax=axes[0]) # axes[0,0])\n", "# sns.histplot(avocado_train[\"region\"], ax=axes[0,1])\n", "sns.histplot(avocado_valid[\"type\"], ax=axes[1]) # axes[1,0])\n", "# sns.histplot(avocado_valid[\"region\"], ax=axes[1,1])\n", "sns.histplot(avocado_test[\"type\"], ax=axes[2]) # axes[2,0])\n", "# sns.histplot(avocado_test[\"region\"], ax=axes[2,1])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ] }