diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..de8c392 --- /dev/null +++ b/.gitignore @@ -0,0 +1,4 @@ + +**/.DS_Store +**/*.ipynb_checkpoints/ +__pycache__/ diff --git a/ETL.ipynb b/ETL.ipynb new file mode 100644 index 0000000..5b641c1 --- /dev/null +++ b/ETL.ipynb @@ -0,0 +1,1984 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Importaciones" + ] + }, + { + "cell_type": "code", + "execution_count": 230, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import pylab as plt\n", + "import seaborn as sns\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "sns.set_context(\"poster\")\n", + "sns.set(rc={\"figure.figsize\": (12.,6.)})\n", + "sns.set_style(\"whitegrid\")" + ] + }, + { + "cell_type": "code", + "execution_count": 231, + "metadata": {}, + "outputs": [], + "source": [ + "from src.exploring_functions import *" + ] + }, + { + "cell_type": "code", + "execution_count": 232, + "metadata": {}, + "outputs": [], + "source": [ + "medidas1 = pd.read_csv('./data/measurements.csv',sep=',',decimal=',')\n", + "medidas2 = pd.read_excel('./data/measurements2.xlsx')" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Infomación general de los datos" + ] + }, + { + "cell_type": "code", + "execution_count": 233, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 233, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medidas1.equals(medidas2)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Los dos dataframes son iguales, por lo que nos quedamos solo con uno." + ] + }, + { + "cell_type": "code", + "execution_count": 234, + "metadata": {}, + "outputs": [], + "source": [ + "medidas = medidas1.copy()" + ] + }, + { + "cell_type": "code", + "execution_count": 235, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(388, 12)" + ] + }, + "execution_count": 235, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medidas.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 236, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 388 entries, 0 to 387\n", + "Data columns (total 12 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 distance 388 non-null float64\n", + " 1 consume 388 non-null float64\n", + " 2 speed 388 non-null int64 \n", + " 3 temp_inside 376 non-null float64\n", + " 4 temp_outside 388 non-null int64 \n", + " 5 specials 93 non-null object \n", + " 6 gas_type 388 non-null object \n", + " 7 AC 388 non-null int64 \n", + " 8 rain 388 non-null int64 \n", + " 9 sun 388 non-null int64 \n", + " 10 refill liters 13 non-null float64\n", + " 11 refill gas 13 non-null object \n", + "dtypes: float64(4), int64(5), object(3)\n", + "memory usage: 36.5+ KB\n" + ] + } + ], + "source": [ + "medidas.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 237, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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countmeanstdmin25%50%75%max
distance388.019.65283522.6678371.311.8014.619.0216.1
consume388.04.9123711.0331723.34.304.75.312.2
speed388.041.92783513.59852414.032.7540.550.090.0
temp_inside376.021.9295211.01045519.021.5022.022.525.5
temp_outside388.011.3582476.991542-5.07.0010.016.031.0
AC388.00.0773200.2674430.00.000.00.01.0
rain388.00.1237110.3296770.00.000.00.01.0
sun388.00.0824740.2754410.00.000.00.01.0
refill liters13.037.1153858.58728210.037.6038.039.045.0
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" + ], + "text/plain": [ + " count mean std min 25% 50% 75% max\n", + "distance 388.0 19.652835 22.667837 1.3 11.80 14.6 19.0 216.1\n", + "consume 388.0 4.912371 1.033172 3.3 4.30 4.7 5.3 12.2\n", + "speed 388.0 41.927835 13.598524 14.0 32.75 40.5 50.0 90.0\n", + "temp_inside 376.0 21.929521 1.010455 19.0 21.50 22.0 22.5 25.5\n", + "temp_outside 388.0 11.358247 6.991542 -5.0 7.00 10.0 16.0 31.0\n", + "AC 388.0 0.077320 0.267443 0.0 0.00 0.0 0.0 1.0\n", + "rain 388.0 0.123711 0.329677 0.0 0.00 0.0 0.0 1.0\n", + "sun 388.0 0.082474 0.275441 0.0 0.00 0.0 0.0 1.0\n", + "refill liters 13.0 37.115385 8.587282 10.0 37.60 38.0 39.0 45.0" + ] + }, + "execution_count": 237, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medidas.describe().T" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Como se puede observar, las columnas 'distance', 'consume', 'temp_inside' deberían ser tipo float y están como tipo object." + ] + }, + { + "cell_type": "code", + "execution_count": 238, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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distanceconsumespeedtemp_insidetemp_outsidespecialsgas_typeACrainsunrefill litersrefill gas
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" + ], + "text/plain": [ + " distance consume speed temp_inside temp_outside specials gas_type AC \\\n", + "0 28.0 5.0 26 21.5 12 NaN E10 0 \n", + "1 12.0 4.2 30 21.5 13 NaN E10 0 \n", + "2 11.2 5.5 38 21.5 15 NaN E10 0 \n", + "3 12.9 3.9 36 21.5 14 NaN E10 0 \n", + "4 18.5 4.5 46 21.5 15 NaN E10 0 \n", + "\n", + " rain sun refill liters refill gas \n", + "0 0 0 45.0 E10 \n", + "1 0 0 NaN NaN \n", + "2 0 0 NaN NaN \n", + "3 0 0 NaN NaN \n", + "4 0 0 NaN NaN " + ] + }, + "execution_count": 238, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medidas.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 239, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "distance 0\n", + "consume 0\n", + "speed 0\n", + "temp_inside 12\n", + "temp_outside 0\n", + "specials 295\n", + "gas_type 0\n", + "AC 0\n", + "rain 0\n", + "sun 0\n", + "refill liters 375\n", + "refill gas 375\n", + "dtype: int64" + ] + }, + "execution_count": 239, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medidas.isna().sum()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Estudio de columnas específicas" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ahora se van a estudiar las columnas de refill, que tienen una gran cantidad de nulos" + ] + }, + { + "cell_type": "code", + "execution_count": 240, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " distance consume speed temp_inside temp_outside specials \\\n", + "0 28.0 5.0 26 21.5 12 NaN \n", + "44 5.4 3.3 32 21.5 7 NaN \n", + "82 10.5 3.6 42 20.0 10 NaN \n", + "106 162.7 5.5 75 23.0 1 NaN \n", + "139 16.1 5.4 24 21.5 7 rain \n", + "171 44.4 4.8 38 21.5 8 NaN \n", + "191 43.7 4.7 44 22.0 9 half rain half sun \n", + "192 12.1 4.2 43 22.0 4 NaN \n", + "234 19.0 4.5 29 22.5 10 NaN \n", + "274 25.7 4.9 50 22.0 10 rain \n", + "313 11.3 4.3 38 22.0 17 NaN \n", + "325 16.6 3.7 49 22.0 17 NaN \n", + "349 18.3 4.3 46 22.0 16 NaN \n", + "\n", + " gas_type AC rain sun refill liters refill gas \n", + "0 E10 0 0 0 45.0 E10 \n", + "44 SP98 0 0 0 37.6 SP98 \n", + "82 SP98 0 0 0 37.7 SP98 \n", + "106 SP98 0 0 0 45.0 SP98 \n", + "139 E10 0 1 0 38.0 E10 \n", + "171 E10 0 0 0 38.3 E10 \n", + "191 SP98 0 1 0 10.0 SP98 \n", + "192 SP98 0 0 0 39.0 SP98 \n", + "234 E10 0 0 0 39.0 E10 \n", + "274 SP98 0 1 0 41.0 SP98 \n", + "313 SP98 0 0 0 37.0 SP98 \n", + "325 E10 0 0 0 37.7 E10 \n", + "349 SP98 0 0 0 37.2 SP98 " + ] + }, + "execution_count": 240, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medidas[medidas['refill gas'].notnull()]" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Como se puede comprobar, la columnas refill gas solo tiene 13 valores no nulos y todos ellos son iguales a la columna gas_type por lo que no aporta información adicinal." + ] + }, + { + "cell_type": "code", + "execution_count": 241, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " distance consume speed temp_inside temp_outside specials \\\n", + "0 28.0 5.0 26 21.5 12 NaN \n", + "44 5.4 3.3 32 21.5 7 NaN \n", + "82 10.5 3.6 42 20.0 10 NaN \n", + "106 162.7 5.5 75 23.0 1 NaN \n", + "139 16.1 5.4 24 21.5 7 rain \n", + "171 44.4 4.8 38 21.5 8 NaN \n", + "191 43.7 4.7 44 22.0 9 half rain half sun \n", + "192 12.1 4.2 43 22.0 4 NaN \n", + "234 19.0 4.5 29 22.5 10 NaN \n", + "274 25.7 4.9 50 22.0 10 rain \n", + "313 11.3 4.3 38 22.0 17 NaN \n", + "325 16.6 3.7 49 22.0 17 NaN \n", + "349 18.3 4.3 46 22.0 16 NaN \n", + "\n", + " gas_type AC rain sun refill liters refill gas \n", + "0 E10 0 0 0 45.0 E10 \n", + "44 SP98 0 0 0 37.6 SP98 \n", + "82 SP98 0 0 0 37.7 SP98 \n", + "106 SP98 0 0 0 45.0 SP98 \n", + "139 E10 0 1 0 38.0 E10 \n", + "171 E10 0 0 0 38.3 E10 \n", + "191 SP98 0 1 0 10.0 SP98 \n", + "192 SP98 0 0 0 39.0 SP98 \n", + "234 E10 0 0 0 39.0 E10 \n", + "274 SP98 0 1 0 41.0 SP98 \n", + "313 SP98 0 0 0 37.0 SP98 \n", + "325 E10 0 0 0 37.7 E10 \n", + "349 SP98 0 0 0 37.2 SP98 " + ] + }, + "execution_count": 241, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medidas[medidas['refill liters'].notnull()]" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "La columna 'refill liters' no tiene más que 13 valores no nulos." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ahora se va estudiar la columna specials, que tiene una gran cantidad de nulos" + ] + }, + { + "cell_type": "code", + "execution_count": 242, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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distanceconsumespeedtemp_insidetemp_outsidespecialsgas_typeACrainsunrefill litersrefill gas
4012.44.05521.57AC rainE10110NaNNaN
414.55.02921.57ACE10100NaNNaN
5011.85.12921.55rainSP98010NaNNaN
5313.16.14621.56rainSP98010NaNNaN
55153.54.98221.53rainSP98010NaNNaN
.......................................
3815.53.73324.528sunSP98001NaNNaN
38213.63.73324.528sunSP98001NaNNaN
38416.14.33825.031ACSP98100NaNNaN
38615.44.64225.031ACSP98100NaNNaN
38714.75.02525.030ACSP98100NaNNaN
\n", + "

93 rows × 12 columns

\n", + "
" + ], + "text/plain": [ + " distance consume speed temp_inside temp_outside specials gas_type \\\n", + "40 12.4 4.0 55 21.5 7 AC rain E10 \n", + "41 4.5 5.0 29 21.5 7 AC E10 \n", + "50 11.8 5.1 29 21.5 5 rain SP98 \n", + "53 13.1 6.1 46 21.5 6 rain SP98 \n", + "55 153.5 4.9 82 21.5 3 rain SP98 \n", + ".. ... ... ... ... ... ... ... \n", + "381 5.5 3.7 33 24.5 28 sun SP98 \n", + "382 13.6 3.7 33 24.5 28 sun SP98 \n", + "384 16.1 4.3 38 25.0 31 AC SP98 \n", + "386 15.4 4.6 42 25.0 31 AC SP98 \n", + "387 14.7 5.0 25 25.0 30 AC SP98 \n", + "\n", + " AC rain sun refill liters refill gas \n", + "40 1 1 0 NaN NaN \n", + "41 1 0 0 NaN NaN \n", + "50 0 1 0 NaN NaN \n", + "53 0 1 0 NaN NaN \n", + "55 0 1 0 NaN NaN \n", + ".. .. ... ... ... ... \n", + "381 0 0 1 NaN NaN \n", + "382 0 0 1 NaN NaN \n", + "384 1 0 0 NaN NaN \n", + "386 1 0 0 NaN NaN \n", + "387 1 0 0 NaN NaN \n", + "\n", + "[93 rows x 12 columns]" + ] + }, + "execution_count": 242, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medidas[medidas.specials.notna()]" + ] + }, + { + "cell_type": "code", + "execution_count": 243, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "rain 32\n", + "sun 27\n", + "AC rain 9\n", + "ac 8\n", + "AC 6\n", + "snow 3\n", + "sun ac 3\n", + "AC snow 1\n", + "half rain half sun 1\n", + "AC sun 1\n", + "AC Sun 1\n", + "ac rain 1\n", + "Name: specials, dtype: int64" + ] + }, + "execution_count": 243, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medidas.specials.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 244, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " specials sun\n", + "191 half rain half sun 0\n", + "***********\n", + " specials AC\n", + "334 ac 0\n", + "***********\n", + "Empty DataFrame\n", + "Columns: [specials, sun]\n", + "Index: []\n" + ] + } + ], + "source": [ + "print(medidas[(medidas.sun==0) & (medidas.specials.str.contains('sun', na=False))] [[\"specials\",\"sun\"]])\n", + "print('***********')\n", + "print(medidas[(medidas.AC==0) & (medidas.specials.str.contains('AC|ac', na=False))] [[\"specials\",\"AC\"]])\n", + "print('***********')\n", + "print(medidas[(medidas.rain==0) & (medidas.specials.str.contains('rain', na=False))] [[\"specials\",\"sun\"]])" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Se comprueba que la columna specials contiene practicamente la misma informacion que las columnas \"AC\", \"rain\" y \"sun\". El único dato que aporta a mayores es \"snow\"" + ] + }, + { + "cell_type": "code", + "execution_count": 245, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 245, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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ABDtxcrjWI0yqy+37BSbXuF/14nOf+1wefPDBdHd3Z9q0adm4cWNmzZqV9evXZ82aNXn66acza9asdHd3V2NeAMYwY3pDbrl3e63HmDQ9j6+s9QjAFDbuUL7++uvzd3/3d2fcfuONN+b5558f78MDAEBNeGc+AAAoEMoAAFAglAEAoEAoAwBAgVAGAIACoQwAAAVCGQAACoQyAAAUCGUAACgQygAAUCCUAQCgQCgDAECBUAYAgAKhDAAABUIZAAAKhDIAABQIZQAAKBDKAABQIJQBAKBAKAMAQIFQBgCAAqEMAAAFQhkAAAqEMgAAFAhlAAAoEMoAAFAglAEAoEAoAwBAgVAGAIACoQwAAAVCGQAACoQyAAAUCGUAACioWihv3rw58+fPz759+5Ike/bsyYoVK7J06dLceeedOXLkSLUOBQAAE64qofzqq69mz549aW1tTZKMjIzk/vvvT2dnZ3p7e9PR0ZHHHnusGocCAIBJMe5QPnHiRDZs2JD169eP3tbf35/GxsZ0dHQkSVatWpWdO3eO91AAADBpxh3KTz31VFasWJG5c+eO3jYwMJA5c+aMftzc3JyRkZEcO3ZsvIcDAIBJMW08X/yNb3wj/f39ue+++6o1z2n6+/sn5HHfT19fX02Oe7mz94nV3t5e6xFgQpzrc4fnmMln57Vh79UzrlB++eWX8/rrr2fJkiVJkrfeeiuf/OQnc/vtt+fAgQOjnzc4OJj6+vo0NTWd1+MvXLgwjY2N4xnxvPX19QmKGrB34EKdy3OH55jJZ+e1Ye/nZ2hoaMwTs+O69OLuu+/OV7/61bz00kt56aWX8qEPfShf/OIXc9ddd+X48ePZvXt3kmTbtm1ZtmzZeA4FAACTalxnlM+mvr4+GzduTFdXV4aGhtLa2ppNmzZNxKEAAGBCVDWUX3rppdH/vWjRovT09FTz4QEAYNJ4Zz4AACgQygAAUCCUAQCgQCgDAECBUAYAgAKhDAAABUIZAAAKhDIAABQIZQAAKBDKAABQIJQBAKBAKAMAQIFQBgCAAqEMAAAFQhkAAAqEMgAAFAhlAAAoEMoAAFAglAEAoEAoAwBAgVAGAIACoQwAAAVCGQAACoQyAAAUCGUAACgQygAAUCCUAQCgQCiTEyeHaz1C2tvbJ/V4F8P3DABc3KbVegBqb8b0htxy7/ZajzGpeh5fWesRAICLnDPKAABQIJQBAKBAKAMAQIFQBgCAAqEMAAAF43rVi6NHj+aBBx7I9773vcyYMSM33HBDNmzYkObm5uzZsyednZ0ZGhpKa2trNm3alKuvvrpacwMAwIQa1xnlurq63HXXXent7U1PT0+uv/76PPbYYxkZGcn999+fzs7O9Pb2pqOjI4899li1ZgYAgAk3rlBuamrKzTffPPrxTTfdlAMHDqS/vz+NjY3p6OhIkqxatSo7d+4c36QAADCJqnaN8sjISJ577rksXrw4AwMDmTNnzuh9zc3NGRkZybFjx6p1OAAAmFBVe2e+hx9+ODNnzsxtt92Wf/qnf6rKY/b391flcc5XX19fTY5bK5P99tEXC3/OMDWc6+/y5fY7fzGw89qw9+qpSih3d3fnjTfeyDPPPJP6+vq0tLTkwIEDo/cPDg6mvr4+TU1N5/W4CxcuTGNjYzVGPGd9fX2C4jLhzxmmhnP5XfbcPvnsvDbs/fwMDQ2NeWJ23JdePPHEE+nv78+WLVsyY8aMJD8O3OPHj2f37t1Jkm3btmXZsmXjPRQAAEyacZ1R/ta3vpVnn3028+bNy6pVq5Ikc+fOzZYtW7Jx48Z0dXWd9vJwAABwqRhXKP/CL/xCXnvtteJ9ixYtSk9Pz3geHgAAasY78wEAQIFQBgCAAqEMAAAFQhkAAAqEMgAAFAhlAC5ZJ04On9PnTaU3YDjX7xkYv6q9hTUATLYZ0xtyy73baz3GpOp5fGWtR4DLhjPKAABQIJQBAC4yF3qJzaV8mdHFeFmRSy8AAC4yLiu6ODijDAAABUIZAAAKhDIAABQIZQAAKBDKAABQIJQBAKBAKAMAQIFQBgCAAqEMAAAFQhkAAAqEMgAAFAhlAAAoEMoAwEXtxMnhWo/AZWparQcAABjLjOkNueXe7bUeY1L1PL6y1iMQZ5QBAKBIKAMAQIFQBgCAAqEMAAAFQhkAAAqEMpclLzUEALwfLw/HZclLDQEA78cZZQC4hFwqfyPW3t5e6xFg3JxRBoBLiL8Rg8kzoWeU9+/fn1tvvTVLly7Nrbfemu9+97sTeTgAAKiaCQ3lrq6urF69Or29vVm9enU6Ozsn8nAAAFA1ExbKR44cyd69e7N8+fIkyfLly7N3794MDg5O1CGr4v8s+MVajwAAwEVgwq5RHhgYyHXXXZeGhoYkSUNDQ2bPnp2BgYE0NzeP+bWVSiVJcuLEiYka76ymNdTl9s4dk37cWvp/D/3fNF3ZUOsxJtXQ0JDv+TLge576LrfvN/E9Xy4u1+95sv2kNX/Snu9VVznbPePU39+fz372s3nxxRdHb/vd3/3dbNq0Kb/4i2OftX3nnXeyb9++iRgLAABO09bWlquuuuqM2yfsjHJLS0sOHjyY4eHhNDQ0ZHh4OIcOHUpLS8v7fu2VV16Ztra2TJ8+PXV1dRM1IgAAl7FKpZKTJ0/myiuvLN4/YaF89dVXZ8GCBdmxY0dWrlyZHTt2ZMGCBe972UWS1NfXF6seAACq6YorrjjrfRN26UWSvP7661mzZk1++MMfZtasWenu7s7P//zPT9ThAACgaiY0lAEA4FLlLawBAKBAKAMAQIFQBgCAAqEMAAAFQhkAAAom7HWUL3bd3d3p7e3N97///fT09KStrS1J8pWvfCVPPfVUTp06lQ984AN59NFHc/3119d42qnj6NGjeeCBB/K9730vM2bMyA033JANGzakubk5e/bsSWdnZ4aGhtLa2ppNmzbl6quvrvXIl7yxdn7vvffm61//et5+++288sorZ33Bdc7f2fb+gx/8IJ2dnXn77bczbdq0/NIv/VK6urrGfB1Pzt3Z9t7U1JRPfOIT+d///d8kybXXXpvPfe5zmTt3bo0nvvSN9RzzE2vXrs0LL7zgeaaKxtr7/Pnz09bWlvr6H58P3bhxY+bPn1/jiS9RlcvUyy+/XDlw4EDld37ndyqvvfZapVKpVI4dO1b5tV/7tcp3vvOdSqVSqXz5y1+u3HnnnbUcc8o5evRo5Wtf+9rox3/5l39ZWbt2bWV4eLjysY99rPLyyy9XKpVKZcuWLZU1a9bUaswp5Ww7r1QqlX//93+vHD58uNLW1lb50Y9+VKsRp6Sz7f3NN9+svPrqq5VKpVIZHh6u3HPPPZXNmzfXaswpZ6yf9x/+8Iejt//t3/5t5U//9E8nfb6paKydVyqVyj//8z9X1q5d63mmysbau11Xz2V76UVHR8cZb6f9xhtv5JprrsmHP/zhJMlv/dZv5atf/WoGBwdrMeKU1NTUlJtvvnn045tuuikHDhxIf39/Ghsb09HRkSRZtWpVdu7cWasxp5Sz7TxJfuM3fsNZ+wlytr3PnTs3H/nIR5L8+F1If/mXf3n0z4PxG+vn/aff8fVHP/rR6Nk2xmesnR89ejSbN2/O2rVrazXelDXW3qkezxI/5cMf/nAOHz6cb37zm0mSnp6eJMnAwEAtx5qyRkZG8txzz2Xx4sUZGBjInDlzRu9rbm7OyMhIjh07VrsBp6Cf3jmT52x7P378eP7+7//en8cEKe39U5/6VD760Y/mH//xH/PQQw/VcLqp6b0737BhQz7zmc+c9n9SqL7Sz/rtt9+elStX5vHHH8+JEydqON2lTSj/lKuuuip/9Vd/lUcffTR/8Ad/kCNHjmTWrFlpaGio9WhT0sMPP5yZM2fmtttuq/Uolw07r43S3k+dOpU///M/z6//+q9nyZIlNZxu6irt/W/+5m/yr//6r/m93/u9/PVf/3UNp5uafnrn//AP/5Dp06fnt3/7t2s91pT33p/1r3zlK3nhhReydevWfPvb386WLVtqPOGlSyi/x2/+5m/mueeeywsvvJDbbrstx48fz8/93M/Veqwpp7u7O2+88UaefPLJ1NfXp6Wl5bS/MhocHEx9fX2amppqN+QU896dMzlKex8eHs59992XD3zgA1m3bl2NJ5yaxvp5r6+vzx/+4R9m+/btNZpuanrvzv/zP/8zX/va17J48eLRM53Lly/Pt7/97RpPOrWUftZ/cmnpz/7sz+bjH/94XnnllVqOeEm7bF/14mzefvvtXHvttRkZGckTTzyRVatWZebMmbUea0p54okn0t/fny984QuZMWNGkmThwoU5fvx4du/enY6Ojmzbti3Lli2r8aRTR2nnTLzS3kdGRrJmzZo0NDTkL/7iL1JXV1fjKaee0t5/8m9NfvJKDDt37vQqAFVU2vn69euzfv360c+ZP39+duzY4VUvqqi09x/84AdpbGzMFVdckVOnTqW3tzcLFiyo8aSXrrpKpVKp9RC18Mgjj2TXrl05fPhwPvjBD6apqSkvvvhiHnroobzyyis5efJkPvrRj+bBBx9MY2NjrcedMr71rW9l+fLlmTdv3ujLYc2dOzdbtmzJK6+8kq6urtNeHu6aa66p8cSXvrF2/ulPfzrf/OY3c/DgwcyePTttbW354he/WOOJp4az7f3jH/94/uiP/ui0l25atGhRurq6ajnulHG2vX/mM5/J2rVrc/LkySRJa2trHnroIS//WQVjPcf8tPnz53t5uCo6297vuuuudHZ2pq6uLqdOncqv/uqv5sEHH7T3C3TZhjIAAIzFhYoAAFAglAEAoEAoAwBAgVAGAIACoQwAAAVCGQAACoQyAAAUCGUAACj4/2odoCwVhyHRAAAAAElFTkSuQmCC", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "medidas.temp_outside.hist()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Limpieza de columnas" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Se van a eliminar aquellas columnas que no aportan información:\n", + "- refill gas: porque todos sus valores no nulos son iguales a gas_type\n", + "- refill liters: la mayoria de los valores son nulos y el objetivo es seleccionar el mejor tipo de combustible, por lo que los litros rellenados en el trayecto no aportan información relevante" + ] + }, + { + "cell_type": "code", + "execution_count": 247, + "metadata": {}, + "outputs": [], + "source": [ + "medidas.drop(columns=['refill gas','refill liters'],inplace=True)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ahora se va a hacer un get dummies de la columna special para sacar la columna \"snow\" y se van a corregir las diferencias con las columnas \"sun\", \"AC y \"rain\" en aquellas filas donde no coincidan. Por último se va a eliminar la columna \"specials\"." + ] + }, + { + "cell_type": "code", + "execution_count": 248, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "rain 32\n", + "sun 27\n", + "AC rain 9\n", + "ac 8\n", + "AC 6\n", + "snow 3\n", + "sun ac 3\n", + "AC snow 1\n", + "half rain half sun 1\n", + "AC sun 1\n", + "AC Sun 1\n", + "ac rain 1\n", + "Name: specials, dtype: int64" + ] + }, + "execution_count": 248, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "medidas.specials.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 249, + "metadata": {}, + "outputs": [], + "source": [ + "for i in medidas[(medidas.sun==0) & (medidas.specials.str.contains('sun', na=False))].index:\n", + " medidas.loc[i, \"sun\"]=1\n", + "\n", + "for i in medidas[(medidas.AC==0) & (medidas.specials.str.contains('AC|ac', na=False))].index:\n", + " medidas.loc[i, \"AC\"]=1\n", + "\n", + "for i in medidas[(medidas.rain==0) & (medidas.specials.str.contains('rain', na=False))].index:\n", + " medidas.loc[i, \"rain\"]=1\n", + "\n", + "medidas['snow'] = 0\n", + "for i in medidas[medidas.specials.str.contains('snow', na=False)].index:\n", + " medidas.loc[i, \"snow\"]=1\n", + "\n", + "medidas.drop(columns=['specials'],inplace=True)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ahora se va a hacer la transformación de las columnas object que deberían ser float" + ] + }, + { + "cell_type": "code", + "execution_count": 250, + "metadata": {}, + "outputs": [], + "source": [ + "for e in ['distance', 'consume', 'temp_inside']:\n", + " # Lo primero es cambiar las ',' por '.' para poder hacer la transformación\n", + " medidas[e] = medidas[e].apply(lambda x : str(x).replace(',', '.'))\n", + " # Ahora hay que cambiar el tipo de columa\n", + " medidas[e] = medidas[e].astype(float)" + ] + }, + { + "cell_type": "code", + "execution_count": 251, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 388 entries, 0 to 387\n", + "Data columns (total 10 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 distance 388 non-null float64\n", + " 1 consume 388 non-null float64\n", + " 2 speed 388 non-null int64 \n", + " 3 temp_inside 376 non-null float64\n", + " 4 temp_outside 388 non-null int64 \n", + " 5 gas_type 388 non-null object \n", + " 6 AC 388 non-null int64 \n", + " 7 rain 388 non-null int64 \n", + " 8 sun 388 non-null int64 \n", + " 9 snow 388 non-null int64 \n", + "dtypes: float64(3), int64(6), object(1)\n", + "memory usage: 30.4+ KB\n" + ] + } + ], + "source": [ + "medidas.info()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Las columnas ya tienen el tipo de dato adecuado, ahora se puede seguir con la limpieza de la columna 'temp_inside' que es la única con nulos, pero como solo hay 12 valores nulos de 388, son una cantidad pequeña y se van a eliminar" + ] + }, + { + "cell_type": "code", + "execution_count": 252, + "metadata": {}, + "outputs": [], + "source": [ + "medidas.dropna(inplace=True)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Se va a crear una nueva columna que almacene la diferencia de temperatura exterior e interior del vehículo, ya que parece un dato relevante." + ] + }, + { + "cell_type": "code", + "execution_count": 253, + "metadata": {}, + "outputs": [], + "source": [ + "medidas['temp_difference']= medidas.apply(lambda x: x.temp_outside - x.temp_inside, axis=1)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Se cambian a minusculas todos los nombres de columnas del dataframe" + ] + }, + { + "cell_type": "code", + "execution_count": 254, + "metadata": {}, + "outputs": [], + "source": [ + "nuevas_columna = {columna:(columna.replace(\" \", \"_\").replace(\".\", \"_\").lower()) for columna in list(medidas.keys())}\n", + "medidas.rename(columns=nuevas_columna, inplace=True)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ahora ya está el dataframe limpio, por lo que se van a exportar los datos" + ] + }, + { + "cell_type": "code", + "execution_count": 255, + "metadata": {}, + "outputs": [], + "source": [ + "medidas.to_csv(\"./data/measurements_clean.csv\",index=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 256, + "metadata": {}, + "outputs": [], + "source": [ + "medidas = pd.read_csv('./data/measurements_clean.csv')\n", + "donwcast_df(medidas, verbose=0)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visualizaciones" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Se va a comprobar si están o no balanceados los datos en función del combustible" + ] + }, + { + "cell_type": "code", + "execution_count": 257, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "El porcentaje de datos con gas_type_E10 es: 0.4175531914893617\n", + "El porcentaje de datos con gas_type_SP98 es: 0.5824468085106383\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "medidas.gas_type.value_counts().plot(kind='bar', figsize=(16,8));\n", + "print('El porcentaje de datos con gas_type_E10 es:', len(medidas[medidas.gas_type==\"E10\"].index)/medidas.shape[0])\n", + "print('El porcentaje de datos con gas_type_SP98 es:', len(medidas[medidas.gas_type==\"SP98\"].index)/medidas.shape[0])" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Se va a estudiar la correación de la columna consumo" + ] + }, + { + "cell_type": "code", + "execution_count": 258, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(20,20)) \n", + "\n", + "color_map = sns.diverging_palette(220, 20, as_cmap=True) # Paleta de colores\n", + "\n", + "sns.heatmap(medidas.corr(), \n", + " cmap=color_map,\n", + " square=True, #que los datos se vean como cuadrados\n", + " linewidth=0.5, #ancho de línea\n", + " vmax=1,\n", + " vmin=-1,\n", + " annot=True,\n", + " cbar_kws={\"shrink\": .7\n", + " },# barra lateral\n", + " xticklabels=True,\n", + " yticklabels=True\n", + ");" + ] + }, + { + "cell_type": "code", + "execution_count": 259, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/rodrigo/miniconda3/envs/ironhack/lib/python3.8/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(medidas.consume,medidas.gas_type);" + ] + }, + { + "cell_type": "code", + "execution_count": 260, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.scatterplot(x=\"consume\", y=\"distance\", hue='gas_type', size = 'temp_difference', data=medidas);" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Se puede ver un alto consumo para muchos trayectos con poca distancia. Suponiendo que los datos de consumo son de l/km estos datos son para consumos en reposo. Debido a esto se van a eliminar los datos de trayectos con consumos por encima de 6.5 l/km" + ] + }, + { + "cell_type": "code", + "execution_count": 261, + "metadata": {}, + "outputs": [], + "source": [ + "medidas.drop(medidas[(medidas['consume'] >6.5)].index, inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 262, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(20,20)) \n", + "\n", + "color_map = sns.diverging_palette(220, 20, as_cmap=True) # Paleta de colores\n", + "\n", + "sns.heatmap(medidas.corr(), \n", + " cmap=color_map,\n", + " square=True, #que los datos se vean como cuadrados\n", + " linewidth=0.5, #ancho de línea\n", + " vmax=1,\n", + " vmin=-1,\n", + " annot=True,\n", + " cbar_kws={\"shrink\": .7\n", + " },# barra lateral\n", + " xticklabels=True,\n", + " yticklabels=True\n", + ");" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Según se puede observar en la matriz de correlación; parece haber una correción positiva entre la temperatura exterior y el consumo de gasolina" + ] + }, + { + "cell_type": "code", + "execution_count": 263, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/rodrigo/miniconda3/envs/ironhack/lib/python3.8/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variables as keyword args: x, y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(medidas.consume,medidas.gas_type);" + ] + }, + { + "cell_type": "code", + "execution_count": 264, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "E10 = medidas[medidas.gas_type == 'E10']\n", + "SP98 = medidas[medidas.gas_type == 'SP98']\n", + "graf = sns.kdeplot(x=medidas.consume, hue=medidas.gas_type)\n", + "graf.axvline(x=E10.consume.median(), c=\"red\", label=\"E10\")\n", + "graf.axvline(x=SP98.consume.median(), c=\"green\", label=\"SP98\")\n", + "plt.legend();" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Tal y como parecen indicar el boxplot y la gráfica de densidad, el consumo de los coches con \"E10\" es mayor que el de los coches con \"SP98\"" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "ironhack", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Predictions.ipynb b/Predictions.ipynb new file mode 100644 index 0000000..a1e8bd4 --- /dev/null +++ b/Predictions.ipynb @@ -0,0 +1,351 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Predicciones" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import pylab as plt\n", + "import seaborn as sns\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "sns.set_context(\"poster\")\n", + "sns.set(rc={\"figure.figsize\": (12.,6.)})\n", + "sns.set_style(\"whitegrid\")" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "from src.exploring_functions import *" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Logistic regression" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import roc_auc_score, roc_curve, auc" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "medidas = pd.read_csv('./data/measurements_clean.csv')\n", + "medidas = pd.get_dummies(medidas, columns=['gas_type'])\n", + "donwcast_df(medidas, verbose=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [], + "source": [ + "X, y = medidas.drop(columns=['consume', 'gas_type_SP98', 'gas_type_E10']), medidas.gas_type_SP98\n", + "\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "El modelo que se va a emplear es la regresion logística, que permite predecir que tipo de combustible usa un coche en función de los datos que se dan" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/rodrigo/miniconda3/envs/ironhack/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:814: ConvergenceWarning: lbfgs failed to converge (status=1):\n", + "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", + "\n", + "Increase the number of iterations (max_iter) or scale the data as shown in:\n", + " https://scikit-learn.org/stable/modules/preprocessing.html\n", + "Please also refer to the documentation for alternative solver options:\n", + " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", + " n_iter_i = _check_optimize_result(\n" + ] + } + ], + "source": [ + "modelo = LogisticRegression().fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "LogisticRegression(max_iter=70, multi_class='multinomial')\n", + "Train: 0.6333333333333333\n", + "Test: 0.5\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/rodrigo/miniconda3/envs/ironhack/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:814: ConvergenceWarning: lbfgs failed to converge (status=1):\n", + "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", + "\n", + "Increase the number of iterations (max_iter) or scale the data as shown in:\n", + " https://scikit-learn.org/stable/modules/preprocessing.html\n", + "Please also refer to the documentation for alternative solver options:\n", + " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", + " n_iter_i = _check_optimize_result(\n" + ] + } + ], + "source": [ + "logreg=LogisticRegression(tol=0.0001, \n", + " max_iter=70,\n", + " solver='lbfgs', \n", + " multi_class='multinomial',)\n", + "\n", + "logreg.fit(X=X_train, y=y_train)\n", + "y_pred=logreg.predict(X=X_test)\n", + "train_score=logreg.score(X_train, y_train) \n", + "test_score=logreg.score(X_test, y_test)\n", + "\n", + "print(logreg)\n", + "print('Train:', train_score)\n", + "print('Test:', test_score) " + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fpr, tpr, _ = roc_curve(y_test, logreg.predict_proba(X_test)[:, 1])\n", + "roc_auc = auc(fpr, tpr)\n", + "\n", + "plt.figure()\n", + "plt.plot(fpr, tpr, color='red', label='ROC curve (area = %0.3f)' % roc_auc)\n", + "plt.plot([0, 1], [0, 1], color='black', lw=2, linestyle='--')\n", + "plt.xlim([0.0, 1.0])\n", + "plt.ylim([0.0, 1.05])\n", + "plt.xlabel('False Positive Rate')\n", + "plt.ylabel('True Positive Rate')\n", + "plt.title('ROC Curve')\n", + "plt.legend(loc=\"upper left\")\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Se comprueba como la curva ROC nos da la información de que el modelo es prácticamente aleatorio a la hora de predecir que tipo de combustible lleva un coche. Esto puede indicar dos cosas:\n", + "* Que el la regresión logística no es un modelo adecuado para predecir en este caso\n", + "* Que con los datos que tenemos no se puede predecir si un coche lleva un tipo de combustible u otro, lo que indicaría que no hay una diferencia entre ambos grupos" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Se va a intentar predecir el tipo de combustible con un modelo de RANDOM FOREST" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Random Forest" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.ensemble import RandomForestRegressor as RFR" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [], + "source": [ + "medidas = pd.read_csv('./data/measurements_clean.csv')\n", + "donwcast_df(medidas, verbose=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "RandomForestRegressor()" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "rfr=RFR()\n", + "y_data = medidas['consume']\n", + "x_data = medidas.drop('consume', axis=1)\n", + "X_data = x_data.drop(columns = ['gas_type','temp_inside'], axis=1)\n", + "X_train, X_test, y_train, y_test = train_test_split(X_data, y_data, test_size=0.2)\n", + "rfr.fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([4.02099999, 4.54200006, 5.49799987, 3.87957616, 4.10799997,\n", + " 4.40700001, 4.90299998, 4.91499999, 6.66390013, 9.68099991])" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_pred=rfr.predict(X_test)\n", + "\n", + "y_pred[:10]" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train rfr: 0.9346741842931301\n", + "Test rfr: 0.6326711094524495\n" + ] + } + ], + "source": [ + "train_score=rfr.score(X_train, y_train) \n", + "test_score=rfr.score(X_test, y_test)\n", + "\n", + "print('Train rfr:', train_score)\n", + "print('Test rfr:', test_score) " + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Al igual que en el caso de la regresión logistica, random forest no consigue predecir con fiabilidad el combustible de los diferentes trayectos, esto nos indica que el gas utilizado no es una variable especialmente relevante en el consumo. " + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Conclusiones" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- No se puede predecir el combustible usado por un coche a partir del consumo.\n", + "- Las variables más relevantes para el consumo es la temperatura exterior y si habia o no lluvia en el trayecto.\n", + "- Viendo que el consumo es similar sin tener en cuenta el combustible usado, seria interesante mirar los precios y elegir el combustible más barato" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "ironhack", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.5" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/measurements.csv b/data/measurements.csv similarity index 100% rename from measurements.csv rename to data/measurements.csv diff --git a/measurements2.xlsx b/data/measurements2.xlsx similarity index 100% rename from measurements2.xlsx rename to data/measurements2.xlsx diff --git a/data/measurements_clean.csv b/data/measurements_clean.csv new file mode 100644 index 0000000..1fe4980 --- /dev/null +++ b/data/measurements_clean.csv @@ -0,0 +1,377 @@ +distance,consume,speed,temp_inside,temp_outside,gas_type,ac,rain,sun,snow,temp_difference +28.0,5.0,26,21.5,12,E10,0,0,0,0,-9.5 +12.0,4.2,30,21.5,13,E10,0,0,0,0,-8.5 +11.2,5.5,38,21.5,15,E10,0,0,0,0,-6.5 +12.9,3.9,36,21.5,14,E10,0,0,0,0,-7.5 +18.5,4.5,46,21.5,15,E10,0,0,0,0,-6.5 +8.3,6.4,50,21.5,10,E10,0,0,0,0,-11.5 +7.8,4.4,43,21.5,11,E10,0,0,0,0,-10.5 +12.3,5.0,40,21.5,6,E10,0,0,0,0,-15.5 +4.9,6.4,26,21.5,4,E10,0,0,0,0,-17.5 +11.9,5.3,30,21.5,9,E10,0,0,0,0,-12.5 +12.4,5.6,42,21.5,4,E10,0,0,0,0,-17.5 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information about the data transformation. It goes from 0 to 2. + + Returns: + DataFrame: Dataframe with column type combination that uses less memory. + ''' + if verbose >= 1: + # Print initial state + start_mem_usg = df.memory_usage().sum() / 1024**2 + print("Memory usage of properties dataframe is :",start_mem_usg," MB") + + if objet_to_category: + for e in df.select_dtypes('object').columns: + + if verbose == 2: + # Print current column type + print("******************************") + print("Column: ",e) + print("dtype before: object") + + df[e]=df[e].astype('category') + + if verbose == 2: + # Print new column type + print("dtype after: ",df[e].dtype) + print("******************************") + + for e in df.select_dtypes('integer').columns: + + if verbose == 2: + # Print current column type + print("******************************") + print("Column: ",e) + print("dtype before: category") + + df[e]=pd.to_numeric(df[e], downcast='integer') + + if verbose == 2: + # Print new column type + print("dtype after: ",df[e].dtype) + print("******************************") + + for e in df.select_dtypes('float').columns: + + if verbose == 2: + # Print current column type + print("******************************") + print("Column: ",e) + print("dtype before: float") + + df[e]=pd.to_numeric(df[e], downcast='float') + + if verbose == 2: + # Print new column type + print("dtype after: ",df[e].dtype) + print("******************************") + + if verbose >= 1: + # Print final result + print("___MEMORY USAGE AFTER COMPLETION:___") + mem_usg = df.memory_usage().sum() / 1024**2 + print("Memory usage is: ",mem_usg," MB") + print("This is ",100*mem_usg/start_mem_usg,"% of the initial size") \ No newline at end of file