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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": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe().T" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "30a7f01a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([nan, 'AC rain', 'AC', 'rain', 'snow', 'AC snow',\n", + " 'half rain half sun', 'sun', 'AC sun', 'sun ac', 'ac', 'AC Sun',\n", + " 'ac rain'], dtype=object)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.specials.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "8c522072", + "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": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.specials.value_counts() #30 valores que contiene AC" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "aa3054c2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 358\n", + "1 30\n", + "Name: ac, dtype: int64" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.ac.value_counts() #30 valores que contiene AC" + ] + }, + { + "cell_type": "markdown", + "id": "40011cf0", + "metadata": {}, + "source": [ + "##### Columna specials,los dummies estan bien hechos salvo la columna snow que no está contemplada, así que haremos una nueva columna" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "1887571c", + "metadata": {}, + "outputs": [], + "source": [ + "df.specials.fillna('unknown', inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "93d9cb20", + "metadata": {}, + "outputs": [], + "source": [ + "df['snow'] = df['specials'].str.contains('snow', regex=True).astype(int) #Hechos los dummies tambien para snow" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "09109453", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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distanceconsumespeedtemp_insidetemp_outsidespecialsgas_typeacrainsunrefill_litersrefill_gassnow
11812.44.63823.01snowSP98010NaNNaN1
12411.84.63823.00snowSP98010NaNNaN1
12512.26.35723.00snowSP98010NaNNaN1
18112.37.15222.50AC snowE10110NaNNaN1
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" + ], + "text/plain": [ + " distance consume speed temp_inside temp_outside specials gas_type \\\n", + "118 12.4 4.6 38 23.0 1 snow SP98 \n", + "124 11.8 4.6 38 23.0 0 snow SP98 \n", + "125 12.2 6.3 57 23.0 0 snow SP98 \n", + "181 12.3 7.1 52 22.5 0 AC snow E10 \n", + "\n", + " ac rain sun refill_liters refill_gas snow \n", + "118 0 1 0 NaN NaN 1 \n", + "124 0 1 0 NaN NaN 1 \n", + "125 0 1 0 NaN NaN 1 \n", + "181 1 1 0 NaN NaN 1 " + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df[df['snow']== 1]" + ] + }, + { + "cell_type": "code", + "execution_count": 131, + "id": "e731d976", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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distanceconsumespeedtemp_insidetemp_outsidespecialsgas_typeacrainsunsnowrefill_litersrefill_gas
028.05.02621.512unknownE10000045.0E10
112.04.23021.513unknownE100000NaNNaN
211.25.53821.515unknownE100000NaNNaN
312.93.93621.514unknownE100000NaNNaN
418.54.54621.515unknownE100000NaNNaN
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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 unknown E10 0 \n", + "1 12.0 4.2 30 21.5 13 unknown E10 0 \n", + "2 11.2 5.5 38 21.5 15 unknown E10 0 \n", + "3 12.9 3.9 36 21.5 14 unknown E10 0 \n", + "4 18.5 4.5 46 21.5 15 unknown E10 0 \n", + "\n", + " rain sun snow refill_liters refill_gas \n", + "0 0 0 0 45.0 E10 \n", + "1 0 0 0 NaN NaN \n", + "2 0 0 0 NaN NaN \n", + "3 0 0 0 NaN NaN \n", + "4 0 0 0 NaN NaN " + ] + }, + "execution_count": 131, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "columnas = ['distance', 'consume', 'speed', 'temp_inside', 'temp_outside',\n", + " 'specials', 'gas_type', 'ac', 'rain', 'sun','snow', 'refill_liters',\n", + " 'refill_gas']\n", + "df = df.reindex(columns=columnas)\n", + "df.head()" + ] + }, + { + "cell_type": "markdown", + "id": "cff0fb4d", + "metadata": {}, + "source": [ + "##### Conpletado el dummies de SNOW dropeo specials" + ] + }, + { + "cell_type": "code", + "execution_count": 227, + "id": "1183b59a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 0.966495\n", + "45.0 0.005155\n", + "37.7 0.005155\n", + "39.0 0.005155\n", + "37.6 0.002577\n", + "38.0 0.002577\n", + "38.3 0.002577\n", + "10.0 0.002577\n", + "41.0 0.002577\n", + "37.0 0.002577\n", + "37.2 0.002577\n", + "Name: refill_liters, dtype: float64" + ] + }, + "execution_count": 227, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.refill_liters.fillna('0', inplace=True)\n", + "df.refill_liters.value_counts('0')" + ] + }, + { + "cell_type": "code", + "execution_count": 228, + "id": "44594ce3", + "metadata": {}, + "outputs": [], + "source": [ + "df.to_excel('consumos.xlsx', index = False)" + ] + }, + { + "cell_type": "markdown", + "id": "11995b17", + "metadata": {}, + "source": [ + "##### Vamos a ver la matriz de correlaciones" + ] + }, + { + "cell_type": "code", + "execution_count": 168, + "id": "5c82a2b0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 168, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "corr = df.corr().abs() #matriz correlaciones\n", + "\n", + "mask = np.triu(np.ones_like(corr, dtype=bool)) #Enmascaramos la diagonal superior\n", + "\n", + "f, ax = plt.subplots(figsize=(11, 9)) #Tamaño\n", + "\n", + "sns.heatmap(corr, mask=mask, cmap='coolwarm',annot=True, vmax=1, vmin=0,\n", + " square=True, linewidths=.5, cbar_kws={\"shrink\": .5})" + ] + }, + { + "cell_type": "markdown", + "id": "2337cafd", + "metadata": {}, + "source": [ + "##### Queremos mirar el consumo, lo que tienes mas peso según nuestra matriz es:\n", + "- TEMP_OUTSIDE\n", + "- RAIN\n", + "- SPEED" + ] + }, + { + "cell_type": "markdown", + "id": "4939ef28", + "metadata": {}, + "source": [ + "#### TEMP_OUTSIDE" + ] + }, + { + "cell_type": "code", + "execution_count": 182, + "id": "46473ac6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 182, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df['temp_bins'] = pd.qcut(df['temp_outside'], 5)\n", + "sns.barplot(x='temp_bins', y='consume', hue='gas_type',data=df)" + ] + }, + { + "cell_type": "markdown", + "id": "53f04301", + "metadata": {}, + "source": [ + "### RAIN" + ] + }, + { + "cell_type": "code", + "execution_count": 185, + "id": "9f53ff2c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 185, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.barplot(data=df, y=\"consume\", x =\"rain\" , hue=\"gas_type\")" + ] + }, + { + "cell_type": "markdown", + "id": "f19e9b22", + "metadata": {}, + "source": [ + "### SPEED:" + ] + }, + { + "cell_type": "code", + "execution_count": 188, + "id": "3ec5c678", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 188, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df['speed_bins'] = pd.qcut(df['speed'], 5)\n", + "sns.barplot(x='speed_bins', y='consume', hue='gas_type',data=df)" + ] + }, + { + "cell_type": "markdown", + "id": "49e00630", + "metadata": {}, + "source": [ + "### Vamos a separar unos y otros en 2 DF para verlo por separado:" + ] + }, + { + "cell_type": "code", + "execution_count": 195, + "id": "ce4450f1", + "metadata": {}, + "outputs": [], + "source": [ + "e10 = df[df.gas_type == 'E10']\n", + "sp98 = df[df.gas_type == 'SP98']" + ] + }, + { + "cell_type": "markdown", + "id": "ad375692", + "metadata": {}, + "source": [ + "### PARA E10:" + ] + }, + { + "cell_type": "code", + "execution_count": 233, + "id": "cebdca87", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "e10['temp_bins'] = pd.qcut(e10['temp_outside'], 5)\n", + "temp = sns.barplot(x='temp_bins', y='consume',data=e10, color='blue')\n", + "temp.axhline(y = e10.consume.mean(), c=\"red\", label=\"mean\");" + ] + }, + { + "cell_type": "code", + "execution_count": 213, + "id": "6be1273d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rain = sns.barplot(data=e10, y=\"consume\", x =\"rain\")\n", + "rain.axhline(y=e10.consume.mean(), c=\"red\", label=\"mean\");" + ] + }, + { + "cell_type": "code", + "execution_count": 235, + "id": "7bc5ef69", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "e10['speed_bins'] = pd.qcut(e10['speed'], 5)\n", + "speed = sns.barplot(x='speed_bins', y='consume',data=e10,color='blue')\n", + "speed.axhline(y=e10.consume.mean(), c=\"red\", label=\"mean\");\n" + ] + }, + { + "cell_type": "markdown", + "id": "ad82d327", + "metadata": {}, + "source": [ + "### PARA SP98" + ] + }, + { + "cell_type": "code", + "execution_count": 226, + "id": "1abebf39", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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k/6mqy6vqziGPL/Z4XKyd3iujjuHt9Wz3c99h9QReBGysqu+3x/RGhrff4HZvraprgQfnPgXsA+xN8wd/L+C7QzYx8Wsxj7Haoq3bo9vbj2H4RZgLaYuRx8KY2TLNtliZAZ/mwqgnV9Wt8yzzG0m+BWwA3jpkkSfRXE273e3tY9uf+3toxusD/0BzhroQRwBHJPlKksuTDDsA5qvLogxpqyOAe5J8MsnVSd6XId1cTN4GNwM/nWRdkj1pwungIcs9tN3W1PZ1mCH7/3XgxUkemeRA4Bd3Vc8pHAOLPR4XbJz3ypzlzwFmgZ8G/teQRab2+lXVZcAlwJ3tz0VVtXm+MhfzWkzYFr8CfC7J7cAbgD+Yr16tsdpijGNhPlM9LldkwNNM4HPPfAtU1RlVdRjwW8B/HLLIfHPhjDVPzpj2pOmmeS7weuCsJI+doC6LNbet9gT+BfDvgJ+nOfN+05D1JqpTewbzb4Dzgb8BbgW2LXa7U7DT/lfVxcDngL8FPkbTLdB5PRd5PC7GLt8rOxVY9WbgicBmYNjnE1OrZ9uv/TM005Q8CTghybM7LHOStng78JKqWgucQ9NlNZV6jXEszGeqx8lKDfgf0vxrBzz04dY1Sa4Zsux5DP9X93aaA2u7wblwHponpz0bfQzw/QXW9Xbg01X147ZL4iaawB+3Lou1U1u1ZV1dzTTN24BPAf9sRL0naoOq+mxVPbOqjqfZz2/Ot91W13MQzd1/quq9VXV0Vb2A5g0zbz2ncAwMWsjxuBgP2/9dqaoHaP5QD+tim+br9yrg8rab8D6azx2Om6/MRb4WY7VFkhng6VX11fah82k+LxhZr9akbTHqWJjPVI/LFRnw7dnimiT7tPd/u33DHg2QZDBAX8qQN3DbV7o1yXFtH9a/Zkff3GeA7Z+Ivwb4QtsvOlKS30/yqiFPfYqmG4C2S+AImg9jxq3LosxtK5o5gA5oD2KAE4Abh6w6sg2SfGNYWUke3/4+gObDoLNGbPekdjTAoTR/7K6YeMfGNHf/k6xJ8rj29lE0H/5dPKKeE+3/KFM4HhdsyOs/qo7ZPlKkLf/lwLD9vAh4YZID2tf5he1j870HRrkNeE6SPZPsBTyH5j+HuSZ+Pw4zblsAPwAek+SI9v4LRtRr4rYY51jYham0xUMm+UR2KX+As4Hnj3ju/cANwDU0fXw/O/DcNQO31wPX04zk+AA7pmbYB/g/NP3KV9D0221f52+ALTRnA7cDL2ofvxA4fkhdQvPv3Y3AdcBJk9Slfe5NLG4UzU5tRXPAXtvW50PA3u3j7wFeMV8b0Pybe9OIcj7W7ueNc/bzFcB7Bu7/drufNzEwUqR97lKmP4rmof1v92t7HS8Hjh5YbrH7v6E9Jh5sf797GsfjYo+BIa//w45hmpO5r7THxPXAubQjPtp6nTWw/lvadrkZePPA46PeAz/flvOPwPeAG9rH1wB/QhOeNwKnT/JaDCw7ySiaXbZF+/ir2rb4entMPnlKbTHfsTCqLp20RVWt6IB/BvCR5a7HQH0u6nDbC35zT7utgJcBb+1wXy9l+gG/ava/i2Ngqd4rXb4HdlHuJAFvWwz8dPmFH4tSVVenuTBmTTV9hstdnxfteqnJJXk78GvAJxa6jWm2VVWNfYHXpJJcQvOh74+nud3Vsv+jLPYYWKr3SlfvgVGSHEbTJsOGVg5lW8xZr/2rIEnqmRX5IaskafEMeEnqKQNeknrKgNeqluSxSX59Gcp9bkbMCpjkc0OuZpaWnAGv1e6xNBddrRhV9ZKqume56yEZ8Frt/gDYPlf2+5L8+yRfSzPn+X8BaCdI+0aSs9LMEX9ukue3E8R9M8mx7XLvTvKRJF9oH//VXZT96CQXpJlz/4+T7NFu59YkB7blbk7yp2nmRL84yb7tMm9t17s2yXldNpB2Xwa8Vrt3At+qZhqLjTRTIxwLHA0cMzC51VNorjI8imYmxV8CfoFmUrb/MLC9o2guMT8e+M9JnjhP2ccC7wCeBhwGvHrIMofTTCf9szQTYW2f/+WdwDOq6iiaMfDS1Bnw6pMXtj9XA1fRBPn2uUFuqarrqupBmkvJ/7qai0Cuo/nCiu0+XVU/rKq7aS41n28u+yuqmdTtAZppHH5hyDK3VNU17e0rB8q6Fjg3yckMn+1SWjQDXn0S4PernZiuqp5SVWe3z90/sNyDA/cfhJ2u6J575d98VwKOs+xguQ8MlPVS4AzgGODKduZAaaoMeK12W4H929sXAW9J+12jSZ60fQbMCbwyyT7tjJTPpZmdc5Rjkxza9r2/DvjyOAW0yx9cVZcAp9F8UDz0+1GlxfCsQataVX2v/bD0epr5xj8KXNbMiMt9wMk0Z87jugL4C+AQ4Herar75vy+j+ZD3acCXgAvGLGMN8OdJHkPzX8d/d9SNuuBcNFIrybtpZuv7o+WuizQNdtFIUk95Bi/NI8nTgI/Mefj+qnrmctRHmoQBL0k9ZReNJPWUAS9JPWXAS1JPGfCS1FP/HwjjPzMa+kVsAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sp98['temp_bins'] = pd.qcut(sp98['temp_outside'], 5)\n", + "temp = sns.barplot(x='temp_bins', y='consume',data=sp98,color=\"orange\")\n", + "temp.axhline(y = sp98.consume.mean(), c=\"red\", label=\"mean\");" + ] + }, + { + "cell_type": "code", + "execution_count": 220, + "id": "1cf0c4ab", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rain = sns.barplot(data=sp98, y=\"consume\", x =\"rain\")\n", + "rain.axhline(y=sp98.consume.mean(), c=\"red\", label=\"mean\");" + ] + }, + { + "cell_type": "code", + "execution_count": 224, + "id": "5275b59e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sp98['speed_bins'] = pd.qcut(sp98['speed'], 5)\n", + "speed = sns.barplot(x='speed_bins', y='consume',data=sp98, color=\"orange\")\n", + "speed.axhline(y=sp98.consume.mean(), c=\"red\", label=\"mean\");" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "85b3b89a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c26695b8", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "412ed922", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d7bbb125", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "21d14b52", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": 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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": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe().T" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "30a7f01a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([nan, 'AC rain', 'AC', 'rain', 'snow', 'AC snow',\n", + " 'half rain half sun', 'sun', 'AC sun', 'sun ac', 'ac', 'AC Sun',\n", + " 'ac rain'], dtype=object)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.specials.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "8c522072", + "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": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.specials.value_counts() #30 valores que contiene AC" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "aa3054c2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 358\n", + "1 30\n", + "Name: ac, dtype: int64" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.ac.value_counts() #30 valores que contiene AC" + ] + }, + { + "cell_type": "markdown", + "id": "40011cf0", + "metadata": {}, + "source": [ + "##### Columna specials,los dummies estan bien hechos salvo la columna snow que no está contemplada, así que haremos una nueva columna" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "1887571c", + "metadata": {}, + "outputs": [], + "source": [ + "df.specials.fillna('unknown', inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "93d9cb20", + "metadata": {}, + "outputs": [], + "source": [ + "df['snow'] = df['specials'].str.contains('snow', regex=True).astype(int) #Hechos los dummies tambien para snow" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "09109453", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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distanceconsumespeedtemp_insidetemp_outsidespecialsgas_typeacrainsunrefill_litersrefill_gassnow
11812.44.63823.01snowSP98010NaNNaN1
12411.84.63823.00snowSP98010NaNNaN1
12512.26.35723.00snowSP98010NaNNaN1
18112.37.15222.50AC snowE10110NaNNaN1
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" + ], + "text/plain": [ + " distance consume speed temp_inside temp_outside specials gas_type \\\n", + "118 12.4 4.6 38 23.0 1 snow SP98 \n", + "124 11.8 4.6 38 23.0 0 snow SP98 \n", + "125 12.2 6.3 57 23.0 0 snow SP98 \n", + "181 12.3 7.1 52 22.5 0 AC snow E10 \n", + "\n", + " ac rain sun refill_liters refill_gas snow \n", + "118 0 1 0 NaN NaN 1 \n", + "124 0 1 0 NaN NaN 1 \n", + "125 0 1 0 NaN NaN 1 \n", + "181 1 1 0 NaN NaN 1 " + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df[df['snow']== 1]" + ] + }, + { + "cell_type": "code", + "execution_count": 131, + "id": "e731d976", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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distanceconsumespeedtemp_insidetemp_outsidespecialsgas_typeacrainsunsnowrefill_litersrefill_gas
028.05.02621.512unknownE10000045.0E10
112.04.23021.513unknownE100000NaNNaN
211.25.53821.515unknownE100000NaNNaN
312.93.93621.514unknownE100000NaNNaN
418.54.54621.515unknownE100000NaNNaN
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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 unknown E10 0 \n", + "1 12.0 4.2 30 21.5 13 unknown E10 0 \n", + "2 11.2 5.5 38 21.5 15 unknown E10 0 \n", + "3 12.9 3.9 36 21.5 14 unknown E10 0 \n", + "4 18.5 4.5 46 21.5 15 unknown E10 0 \n", + "\n", + " rain sun snow refill_liters refill_gas \n", + "0 0 0 0 45.0 E10 \n", + "1 0 0 0 NaN NaN \n", + "2 0 0 0 NaN NaN \n", + "3 0 0 0 NaN NaN \n", + "4 0 0 0 NaN NaN " + ] + }, + "execution_count": 131, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "columnas = ['distance', 'consume', 'speed', 'temp_inside', 'temp_outside',\n", + " 'specials', 'gas_type', 'ac', 'rain', 'sun','snow', 'refill_liters',\n", + " 'refill_gas']\n", + "df = df.reindex(columns=columnas)\n", + "df.head()" + ] + }, + { + "cell_type": "markdown", + "id": "cff0fb4d", + "metadata": {}, + "source": [ + "##### Conpletado el dummies de SNOW dropeo specials" + ] + }, + { + "cell_type": "code", + "execution_count": 227, + "id": "1183b59a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 0.966495\n", + "45.0 0.005155\n", + "37.7 0.005155\n", + "39.0 0.005155\n", + "37.6 0.002577\n", + "38.0 0.002577\n", + "38.3 0.002577\n", + "10.0 0.002577\n", + "41.0 0.002577\n", + "37.0 0.002577\n", + "37.2 0.002577\n", + "Name: refill_liters, dtype: float64" + ] + }, + "execution_count": 227, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.refill_liters.fillna('0', inplace=True)\n", + "df.refill_liters.value_counts('0')" + ] + }, + { + "cell_type": "code", + "execution_count": 228, + "id": "44594ce3", + "metadata": {}, + "outputs": [], + "source": [ + "df.to_excel('consumos.xlsx', index = False)" + ] + }, + { + "cell_type": "markdown", + "id": "11995b17", + "metadata": {}, + "source": [ + "##### Vamos a ver la matriz de correlaciones" + ] + }, + { + "cell_type": "code", + "execution_count": 168, + "id": "5c82a2b0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 168, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "corr = df.corr().abs() #matriz correlaciones\n", + "\n", + "mask = np.triu(np.ones_like(corr, dtype=bool)) #Enmascaramos la diagonal superior\n", + "\n", + "f, ax = plt.subplots(figsize=(11, 9)) #Tamaño\n", + "\n", + "sns.heatmap(corr, mask=mask, cmap='coolwarm',annot=True, vmax=1, vmin=0,\n", + " square=True, linewidths=.5, cbar_kws={\"shrink\": .5})" + ] + }, + { + "cell_type": "markdown", + "id": "2337cafd", + "metadata": {}, + "source": [ + "##### Queremos mirar el consumo, lo que tienes mas peso según nuestra matriz es:\n", + "- TEMP_OUTSIDE\n", + "- RAIN\n", + "- SPEED" + ] + }, + { + "cell_type": "markdown", + "id": "4939ef28", + "metadata": {}, + "source": [ + "#### TEMP_OUTSIDE" + ] + }, + { + "cell_type": "code", + "execution_count": 182, + "id": "46473ac6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 182, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df['temp_bins'] = pd.qcut(df['temp_outside'], 5)\n", + "sns.barplot(x='temp_bins', y='consume', hue='gas_type',data=df)" + ] + }, + { + "cell_type": "markdown", + "id": "53f04301", + "metadata": {}, + "source": [ + "### RAIN" + ] + }, + { + "cell_type": "code", + "execution_count": 185, + "id": "9f53ff2c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 185, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.barplot(data=df, y=\"consume\", x =\"rain\" , hue=\"gas_type\")" + ] + }, + { + "cell_type": "markdown", + "id": "f19e9b22", + "metadata": {}, + "source": [ + "### SPEED:" + ] + }, + { + "cell_type": "code", + "execution_count": 188, + "id": "3ec5c678", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 188, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df['speed_bins'] = pd.qcut(df['speed'], 5)\n", + "sns.barplot(x='speed_bins', y='consume', hue='gas_type',data=df)" + ] + }, + { + "cell_type": "markdown", + "id": "49e00630", + "metadata": {}, + "source": [ + "### Vamos a separar unos y otros en 2 DF para verlo por separado:" + ] + }, + { + "cell_type": "code", + "execution_count": 195, + "id": "ce4450f1", + "metadata": {}, + "outputs": [], + "source": [ + "e10 = df[df.gas_type == 'E10']\n", + "sp98 = df[df.gas_type == 'SP98']" + ] + }, + { + "cell_type": "markdown", + "id": "ad375692", + "metadata": {}, + "source": [ + "### PARA E10:" + ] + }, + { + "cell_type": "code", + "execution_count": 233, + "id": "cebdca87", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "e10['temp_bins'] = pd.qcut(e10['temp_outside'], 5)\n", + "temp = sns.barplot(x='temp_bins', y='consume',data=e10, color='blue')\n", + "temp.axhline(y = e10.consume.mean(), c=\"red\", label=\"mean\");" + ] + }, + { + "cell_type": "code", + "execution_count": 213, + "id": "6be1273d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rain = sns.barplot(data=e10, y=\"consume\", x =\"rain\")\n", + "rain.axhline(y=e10.consume.mean(), c=\"red\", label=\"mean\");" + ] + }, + { + "cell_type": "code", + "execution_count": 235, + "id": "7bc5ef69", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "e10['speed_bins'] = pd.qcut(e10['speed'], 5)\n", + "speed = sns.barplot(x='speed_bins', y='consume',data=e10,color='blue')\n", + "speed.axhline(y=e10.consume.mean(), c=\"red\", label=\"mean\");\n" + ] + }, + { + "cell_type": "markdown", + "id": "ad82d327", + "metadata": {}, + "source": [ + "### PARA SP98" + ] + }, + { + "cell_type": "code", + "execution_count": 226, + "id": "1abebf39", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sp98['temp_bins'] = pd.qcut(sp98['temp_outside'], 5)\n", + "temp = sns.barplot(x='temp_bins', y='consume',data=sp98,color=\"orange\")\n", + "temp.axhline(y = sp98.consume.mean(), c=\"red\", label=\"mean\");" + ] + }, + { + "cell_type": "code", + "execution_count": 220, + "id": "1cf0c4ab", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "rain = sns.barplot(data=sp98, y=\"consume\", x =\"rain\")\n", + "rain.axhline(y=sp98.consume.mean(), c=\"red\", label=\"mean\");" + ] + }, + { + "cell_type": "code", + "execution_count": 224, + "id": "5275b59e", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sp98['speed_bins'] = pd.qcut(sp98['speed'], 5)\n", + "speed = sns.barplot(x='speed_bins', y='consume',data=sp98, color=\"orange\")\n", + "speed.axhline(y=sp98.consume.mean(), c=\"red\", label=\"mean\");" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "85b3b89a", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c26695b8", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "412ed922", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d7bbb125", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "21d14b52", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": 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