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@asvcode
Last active January 24, 2019 17:31
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd \n",
"import matplotlib.pyplot as plt\n",
"import re\n",
"import seaborn as sns\n",
"%matplotlib inline\n",
"\n",
"from scipy import stats\n",
"from scipy.stats import norm\n",
"\n",
"import warnings\n",
"warnings.simplefilter(\"ignore\", UserWarning)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>date</th>\n",
" <th>Temperature</th>\n",
" <th>Humidity</th>\n",
" <th>Light</th>\n",
" <th>CO2</th>\n",
" <th>HumidityRatio</th>\n",
" <th>Occupancy</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2015-02-04 17:51:00</td>\n",
" <td>23.18</td>\n",
" <td>27.2720</td>\n",
" <td>426.0</td>\n",
" <td>721.25</td>\n",
" <td>0.004793</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2015-02-04 17:51:59</td>\n",
" <td>23.15</td>\n",
" <td>27.2675</td>\n",
" <td>429.5</td>\n",
" <td>714.00</td>\n",
" <td>0.004783</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2015-02-04 17:53:00</td>\n",
" <td>23.15</td>\n",
" <td>27.2450</td>\n",
" <td>426.0</td>\n",
" <td>713.50</td>\n",
" <td>0.004779</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2015-02-04 17:54:00</td>\n",
" <td>23.15</td>\n",
" <td>27.2000</td>\n",
" <td>426.0</td>\n",
" <td>708.25</td>\n",
" <td>0.004772</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2015-02-04 17:55:00</td>\n",
" <td>23.10</td>\n",
" <td>27.2000</td>\n",
" <td>426.0</td>\n",
" <td>704.50</td>\n",
" <td>0.004757</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" date Temperature Humidity Light CO2 HumidityRatio \\\n",
"0 2015-02-04 17:51:00 23.18 27.2720 426.0 721.25 0.004793 \n",
"1 2015-02-04 17:51:59 23.15 27.2675 429.5 714.00 0.004783 \n",
"2 2015-02-04 17:53:00 23.15 27.2450 426.0 713.50 0.004779 \n",
"3 2015-02-04 17:54:00 23.15 27.2000 426.0 708.25 0.004772 \n",
"4 2015-02-04 17:55:00 23.10 27.2000 426.0 704.50 0.004757 \n",
"\n",
" Occupancy \n",
"0 1 \n",
"1 1 \n",
"2 1 \n",
"3 1 \n",
"4 1 "
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"d = pd.read_csv('occupancy_data/datatraining.csv')\n",
"d.head()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 8143 entries, 0 to 8142\n",
"Data columns (total 7 columns):\n",
"date 8143 non-null object\n",
"Temperature 8143 non-null float64\n",
"Humidity 8143 non-null float64\n",
"Light 8143 non-null float64\n",
"CO2 8143 non-null float64\n",
"HumidityRatio 8143 non-null float64\n",
"Occupancy 8143 non-null int64\n",
"dtypes: float64(5), int64(1), object(1)\n",
"memory usage: 445.4+ KB\n"
]
}
],
"source": [
"d.info()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>count</th>\n",
" <th>mean</th>\n",
" <th>std</th>\n",
" <th>min</th>\n",
" <th>25%</th>\n",
" <th>50%</th>\n",
" <th>75%</th>\n",
" <th>max</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Temperature</th>\n",
" <td>8143.0</td>\n",
" <td>20.619084</td>\n",
" <td>1.016916</td>\n",
" <td>19.000000</td>\n",
" <td>19.700000</td>\n",
" <td>20.390000</td>\n",
" <td>21.390000</td>\n",
" <td>23.180000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Humidity</th>\n",
" <td>8143.0</td>\n",
" <td>25.731507</td>\n",
" <td>5.531211</td>\n",
" <td>16.745000</td>\n",
" <td>20.200000</td>\n",
" <td>26.222500</td>\n",
" <td>30.533333</td>\n",
" <td>39.117500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Light</th>\n",
" <td>8143.0</td>\n",
" <td>119.519375</td>\n",
" <td>194.755805</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>256.375000</td>\n",
" <td>1546.333333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>CO2</th>\n",
" <td>8143.0</td>\n",
" <td>606.546243</td>\n",
" <td>314.320877</td>\n",
" <td>412.750000</td>\n",
" <td>439.000000</td>\n",
" <td>453.500000</td>\n",
" <td>638.833333</td>\n",
" <td>2028.500000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>HumidityRatio</th>\n",
" <td>8143.0</td>\n",
" <td>0.003863</td>\n",
" <td>0.000852</td>\n",
" <td>0.002674</td>\n",
" <td>0.003078</td>\n",
" <td>0.003801</td>\n",
" <td>0.004352</td>\n",
" <td>0.006476</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Occupancy</th>\n",
" <td>8143.0</td>\n",
" <td>0.212330</td>\n",
" <td>0.408982</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" count mean std min 25% \\\n",
"Temperature 8143.0 20.619084 1.016916 19.000000 19.700000 \n",
"Humidity 8143.0 25.731507 5.531211 16.745000 20.200000 \n",
"Light 8143.0 119.519375 194.755805 0.000000 0.000000 \n",
"CO2 8143.0 606.546243 314.320877 412.750000 439.000000 \n",
"HumidityRatio 8143.0 0.003863 0.000852 0.002674 0.003078 \n",
"Occupancy 8143.0 0.212330 0.408982 0.000000 0.000000 \n",
"\n",
" 50% 75% max \n",
"Temperature 20.390000 21.390000 23.180000 \n",
"Humidity 26.222500 30.533333 39.117500 \n",
"Light 0.000000 256.375000 1546.333333 \n",
"CO2 453.500000 638.833333 2028.500000 \n",
"HumidityRatio 0.003801 0.004352 0.006476 \n",
"Occupancy 0.000000 0.000000 1.000000 "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"d.describe().T"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"dt = pd.read_csv('occupancy_data/datatraining.txt')\n",
"dt['date'] = pd.to_datetime(dt[\"date\"])\n",
"df_idx = dt.set_index([\"date\"], drop=True)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1c3855095c0>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"data = df_idx[['Occupancy']]\n",
"data.plot(y='Occupancy')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Data Analysis"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Distribution"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\avird\\Anaconda3\\envs\\fastai_gpu\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
" return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" mu = 20.62 and sigma = 1.02\n",
"\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.distplot(d['Temperature'] , fit=norm);\n",
"\n",
"# Get the fitted parameters used by the function\n",
"(mu, sigma) = norm.fit(d['Temperature'])\n",
"print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
"\n",
"#Now plot the distribution\n",
"plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
" loc='best')\n",
"plt.ylabel('Frequency')\n",
"plt.title('Temperature')\n",
"\n",
"#Get also the QQ-plot\n",
"fig = plt.figure()\n",
"res = stats.probplot(d['Temperature'], plot=plt)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" mu = 3.07 and sigma = 0.05\n",
"\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#We use the numpy fuction log1p which applies log(1+x) to all elements of the column\n",
"d[\"Temperature\"] = np.log1p(d[\"Temperature\"])\n",
"\n",
"#Check the new distribution \n",
"sns.distplot(d['Temperature'] , fit=norm);\n",
"\n",
"# Get the fitted parameters used by the function\n",
"(mu, sigma) = norm.fit(d['Temperature'])\n",
"print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
"\n",
"#Now plot the distribution\n",
"plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
" loc='best')\n",
"plt.ylabel('Frequency')\n",
"plt.title('Temperature')\n",
"\n",
"#Get also the QQ-plot\n",
"fig = plt.figure()\n",
"res = stats.probplot(d['Temperature'], plot=plt)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1c386eaf470>"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"data = df_idx[['Temperature']]\n",
"data.plot(y='Temperature')"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" mu = 25.73 and sigma = 5.53\n",
"\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.distplot(d['Humidity'] , fit=norm);\n",
"\n",
"# Get the fitted parameters used by the function\n",
"(mu, sigma) = norm.fit(d['Humidity'])\n",
"print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
"\n",
"#Now plot the distribution\n",
"plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
" loc='best')\n",
"plt.ylabel('Frequency')\n",
"plt.title('Humidity')\n",
"\n",
"#Get also the QQ-plot\n",
"fig = plt.figure()\n",
"res = stats.probplot(d['Humidity'], plot=plt)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1c3870fe400>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"data = df_idx[['Humidity']]\n",
"data.plot(y='Humidity')"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" mu = 3.26 and sigma = 0.21\n",
"\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#We use the numpy fuction log1p which applies log(1+x) to all elements of the column\n",
"d[\"Humidity\"] = np.log1p(d[\"Humidity\"])\n",
"\n",
"#Check the new distribution \n",
"sns.distplot(d['Humidity'] , fit=norm);\n",
"\n",
"# Get the fitted parameters used by the function\n",
"(mu, sigma) = norm.fit(d['Humidity'])\n",
"print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
"\n",
"#Now plot the distribution\n",
"plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
" loc='best')\n",
"plt.ylabel('Frequency')\n",
"plt.title('Humidity')\n",
"\n",
"#Get also the QQ-plot\n",
"fig = plt.figure()\n",
"res = stats.probplot(d['Humidity'], plot=plt)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" mu = 606.55 and sigma = 314.30\n",
"\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.distplot(d['CO2'] , fit=norm);\n",
"\n",
"# Get the fitted parameters used by the function\n",
"(mu, sigma) = norm.fit(d['CO2'])\n",
"print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
"\n",
"#Now plot the distribution\n",
"plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
" loc='best')\n",
"plt.ylabel('Frequency')\n",
"plt.title('CO2')\n",
"\n",
"#Get also the QQ-plot\n",
"fig = plt.figure()\n",
"res = stats.probplot(d['CO2'], plot=plt)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" mu = 6.32 and sigma = 0.38\n",
"\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#We use the numpy fuction log1p which applies log(1+x) to all elements of the column\n",
"d[\"CO2\"] = np.log1p(d[\"CO2\"])\n",
"\n",
"#Check the new distribution \n",
"sns.distplot(d['CO2'] , fit=norm);\n",
"\n",
"# Get the fitted parameters used by the function\n",
"(mu, sigma) = norm.fit(d['CO2'])\n",
"print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
"\n",
"#Now plot the distribution\n",
"plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
" loc='best')\n",
"plt.ylabel('Frequency')\n",
"plt.title('CO2')\n",
"\n",
"#Get also the QQ-plot\n",
"fig = plt.figure()\n",
"res = stats.probplot(d['CO2'], plot=plt)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1c38713aef0>"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"data = df_idx[['CO2']]\n",
"data.plot(y='CO2')"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" mu = 0.00 and sigma = 0.00\n",
"\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"sns.distplot(d['HumidityRatio'] , fit=norm);\n",
"\n",
"# Get the fitted parameters used by the function\n",
"(mu, sigma) = norm.fit(d['HumidityRatio'])\n",
"print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
"\n",
"#Now plot the distribution\n",
"plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
" loc='best')\n",
"plt.ylabel('Frequency')\n",
"plt.title('HumidityRatio')\n",
"\n",
"#Get also the QQ-plot\n",
"fig = plt.figure()\n",
"res = stats.probplot(d['HumidityRatio'], plot=plt)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" mu = 0.00 and sigma = 0.00\n",
"\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#We use the numpy fuction log1p which applies log(1+x) to all elements of the column\n",
"d[\"HumidityRatio\"] = np.log1p(d[\"HumidityRatio\"])\n",
"\n",
"#Check the new distribution \n",
"sns.distplot(d['HumidityRatio'] , fit=norm);\n",
"\n",
"# Get the fitted parameters used by the function\n",
"(mu, sigma) = norm.fit(d['HumidityRatio'])\n",
"print( '\\n mu = {:.2f} and sigma = {:.2f}\\n'.format(mu, sigma))\n",
"\n",
"#Now plot the distribution\n",
"plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)],\n",
" loc='best')\n",
"plt.ylabel('Frequency')\n",
"plt.title('HumidityRatio')\n",
"\n",
"#Get also the QQ-plot\n",
"fig = plt.figure()\n",
"res = stats.probplot(d['HumidityRatio'], plot=plt)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1c388519b38>"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"data = df_idx[['HumidityRatio']]\n",
"data.plot(y='HumidityRatio')"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"d = d.drop(['date', 'Light'], axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Temperature</th>\n",
" <th>Humidity</th>\n",
" <th>CO2</th>\n",
" <th>HumidityRatio</th>\n",
" <th>Occupancy</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>3.185526</td>\n",
" <td>3.341872</td>\n",
" <td>6.582371</td>\n",
" <td>0.004782</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>3.184284</td>\n",
" <td>3.341713</td>\n",
" <td>6.572283</td>\n",
" <td>0.004772</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3.184284</td>\n",
" <td>3.340916</td>\n",
" <td>6.571583</td>\n",
" <td>0.004768</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3.184284</td>\n",
" <td>3.339322</td>\n",
" <td>6.564208</td>\n",
" <td>0.004760</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>3.182212</td>\n",
" <td>3.339322</td>\n",
" <td>6.558907</td>\n",
" <td>0.004746</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Temperature Humidity CO2 HumidityRatio Occupancy\n",
"0 3.185526 3.341872 6.582371 0.004782 1\n",
"1 3.184284 3.341713 6.572283 0.004772 1\n",
"2 3.184284 3.340916 6.571583 0.004768 1\n",
"3 3.184284 3.339322 6.564208 0.004760 1\n",
"4 3.182212 3.339322 6.558907 0.004746 1"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"d.head()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"((8143, 4), (8143, 1))"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X = d.iloc[:,:-1].values\n",
"y = d.iloc[:,-1].values\n",
"y = y.reshape(-1,1)\n",
"X.shape, y.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Covariance Matrix"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.preprocessing import StandardScaler\n",
"X_std = StandardScaler().fit_transform(X)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Covariance matrix \n",
"[[ 1.00012282 -0.16559439 0.61800664 0.14981426]\n",
" [-0.16559439 1.00012282 0.36110729 0.94336243]\n",
" [ 0.61800664 0.36110729 1.00012282 0.58932792]\n",
" [ 0.14981426 0.94336243 0.58932792 1.00012282]]\n"
]
}
],
"source": [
"import numpy as np\n",
"mean_vec = np.mean(X_std, axis=0)\n",
"cov_mat = (X_std - mean_vec).T.dot((X_std - mean_vec)) / (X_std.shape[0]-1)\n",
"print('Covariance matrix \\n%s' %cov_mat)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Eigenvectors \n",
"[[ 0.23753216 -0.74986087 0.5894609 -0.18391028]\n",
" [ 0.53767983 0.46899078 0.16768635 -0.68031562]\n",
" [ 0.51806792 -0.41006276 -0.74841427 -0.05770827]\n",
" [ 0.62135699 0.22272148 0.25356106 0.7071191 ]]\n",
"\n",
"Eigenvalues \n",
"[2.36507816 1.39715233 0.23280163 0.00545916]\n"
]
}
],
"source": [
"cov_mat = np.cov(X_std.T)\n",
"\n",
"eig_vals, eig_vecs = np.linalg.eig(cov_mat)\n",
"\n",
"print('Eigenvectors \\n%s' %eig_vecs)\n",
"print('\\nEigenvalues \\n%s' %eig_vals)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Everything ok!\n"
]
}
],
"source": [
"for ev in eig_vecs:\n",
" np.testing.assert_array_almost_equal(1.0, np.linalg.norm(ev))\n",
"print('Everything ok!')"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Eigenvalues in descending order:\n",
"2.364787719414532\n",
"1.396980750511877\n",
"0.23277304302719148\n",
"0.005458487046397058\n"
]
}
],
"source": [
"# Make a list of (eigenvalue, eigenvector) tuples\n",
"eig_pairs = [(np.abs(eig_vals[i]), eig_vecs[:,i]) for i in range(len(eig_vals))]\n",
"\n",
"# Sort the (eigenvalue, eigenvector) tuples from high to low\n",
"eig_pairs.sort()\n",
"eig_pairs.reverse()\n",
"\n",
"# Visually confirm that the list is correctly sorted by decreasing eigenvalues\n",
"print('Eigenvalues in descending order:')\n",
"for i in eig_pairs:\n",
" print(i[0])"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~avirdee/2.embed\" height=\"525px\" width=\"100%\"></iframe>"
],
"text/plain": [
"<plotly.tools.PlotlyDisplay object>"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import plotly.plotly as py\n",
"tot = sum(eig_vals)\n",
"var_exp = [(i / tot)*100 for i in sorted(eig_vals, reverse=True)]\n",
"cum_var_exp = np.cumsum(var_exp)\n",
"\n",
"trace1 = dict(\n",
" type='bar',\n",
" x=['PC %s' %i for i in range(1,5)],\n",
" y=var_exp,\n",
" name='Individual'\n",
")\n",
"\n",
"trace2 = dict(\n",
" type='scatter',\n",
" x=['PC %s' %i for i in range(1,5)], \n",
" y=cum_var_exp,\n",
" name='Cumulative'\n",
")\n",
"\n",
"data = [trace1, trace2]\n",
"\n",
"layout=dict(\n",
" title='Explained variance by different principal components',\n",
" yaxis=dict(\n",
" title='Explained variance in percent'\n",
" ),\n",
" annotations=list([\n",
" dict(\n",
" x=1.16,\n",
" y=1.05,\n",
" xref='paper',\n",
" yref='paper',\n",
" text='Explained Variance',\n",
" showarrow=False,\n",
" )\n",
" ])\n",
")\n",
"\n",
"fig = dict(data=data, layout=layout)\n",
"py.iplot(fig, filename='selecting-principal-components')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# K Fold"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {},
"outputs": [],
"source": [
"n_folds = 5\n",
"\n",
"def rmsle_cv(model):\n",
" kf = KFold(n_folds, shuffle=True, random_state=42).get_n_splits(d.values)\n",
" rmse= np.sqrt(-cross_val_score(model, d.values, y_train, scoring=\"neg_mean_squared_error\", cv = kf))\n",
" return(rmse)"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.preprocessing import StandardScaler\n",
"Sc_x = StandardScaler()\n",
"Sc_y = StandardScaler()\n",
"X = Sc_x.fit_transform(X)\n",
"y = Sc_y.fit_transform(y)"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.model_selection import KFold, cross_val_score, train_test_split\n",
"X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.0, random_state=7)"
]
},
{
"cell_type": "code",
"execution_count": 101,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.linear_model import Lasso\n",
"from sklearn.pipeline import make_pipeline\n",
"from sklearn.preprocessing import RobustScaler\n",
"lasso = make_pipeline(RobustScaler(), Lasso(alpha =0.0005, random_state=1))"
]
},
{
"cell_type": "code",
"execution_count": 102,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Lasso score: 1.0006 (0.0241)\n",
"\n"
]
}
],
"source": [
"score = rmsle_cv(lasso)\n",
"print(\"\\nLasso score: {:.4f} ({:.4f})\\n\".format(score.mean(), score.std()))"
]
},
{
"cell_type": "code",
"execution_count": 103,
"metadata": {},
"outputs": [],
"source": [
"from sklearn.ensemble import GradientBoostingRegressor\n",
"GBoost = GradientBoostingRegressor(n_estimators=3000, learning_rate=0.05,\n",
" max_depth=4, max_features='sqrt',\n",
" min_samples_leaf=15, min_samples_split=10, \n",
" loss='huber', random_state =5)"
]
},
{
"cell_type": "code",
"execution_count": 106,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"GBoost score: 1.0861 (0.0497)\n",
"\n"
]
}
],
"source": [
"score = rmsle_cv(GBoost)\n",
"print(\"\\nGBoost score: {:.4f} ({:.4f})\\n\".format(score.mean(), score.std()))"
]
},
{
"cell_type": "code",
"execution_count": 105,
"metadata": {},
"outputs": [],
"source": [
"import xgboost as xgb\n",
"model_xgb = xgb.XGBRegressor(colsample_bytree=0.4603, gamma=0.0468, \n",
" learning_rate=0.05, max_depth=3, \n",
" min_child_weight=1.7817, n_estimators=2200,\n",
" reg_alpha=0.4640, reg_lambda=0.8571,\n",
" subsample=0.5213, silent=1,\n",
" random_state =7, nthread = -1)"
]
},
{
"cell_type": "code",
"execution_count": 110,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"XGBoost score: 1.2026 (0.2036)\n",
"\n"
]
}
],
"source": [
"score = rmsle_cv(model_xgb)\n",
"print(\"\\nXGBoost score: {:.4f} ({:.4f})\\n\".format(score.mean(), score.std()))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.6.6"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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