{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# *Bike Rentals by Registered and Casual Riders*\n", "\n", "______\n", "### Luke Dengler\n", "### Numerical Methods and Statistics - End of Semester Project\n", "\n", "_____\n", "\n", "This project will analyze the effect of a few different variables on the number of bike rentals at a bike sharing station in Washington, DC. The variables which will be analyzed are the temperature and the weather conditions on a scale of 1-4. Hopefully we will be able to see trends in the number of rentals as the weather and temperature change.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Importing the data set\n", "\n", "The file containing the data will be read in and managed pandas package.\n", "\n", "(Imports for the project are also made here)\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 178, "metadata": { "collapsed": true }, "outputs": [], "source": [ "%matplotlib inline\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import matplotlib as mpl\n", "import numpy as np\n", "import scipy.stats as ss\n", "import seaborn as sns\n", "import scipy.optimize\n", "sns.set_style('whitegrid')\n", "sns.set_context('notebook')\n" ] }, { "cell_type": "code", "execution_count": 179, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 10886 entries, 0 to 10885\n", "Data columns (total 12 columns):\n", "datetimes 10886 non-null object\n", "season 10886 non-null int64\n", "holiday 10886 non-null int64\n", "workingday 10886 non-null int64\n", "weather 10886 non-null int64\n", "temp 10886 non-null float64\n", "atemp 10886 non-null float64\n", "humidity 10886 non-null int64\n", "windspeed 10886 non-null float64\n", "casual 10886 non-null int64\n", "registered 10886 non-null int64\n", "counts 10886 non-null int64\n", "dtypes: float64(3), int64(8), object(1)\n", "memory usage: 1020.6+ KB\n" ] } ], "source": [ "#the data is read in from the csv\n", "all_data = pd.read_csv('Dengler_L_Project/train.csv')\n", "all_data.info()" ] }, { "cell_type": "code", "execution_count": 180, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#The datetime column is converted to useble dates instead of the string they are\n", "dates = pd.to_datetime(all_data.datetimes)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Checking for missing data\n", "\n", "We will now check for unsual data. The first check will be whether any numbers are NaN values or above a certain value.\n", "\n", "Each list of values is checked for having bad values by checking that each element of the array is both valid and is in a reasonable range for the data it is describing.\n", "\n", "In the following cell the number of bad values is counted and if a list contains no bad values a message stating such is printed out." ] }, { "cell_type": "code", "execution_count": 181, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "None of the 'season' data is invalid\n", "None of the 'holiday' data is invalid\n", "None of the 'workingDay' data is invalid\n", "None of the 'weather' data is invalid\n", "None of the 'temp' data is invalid\n", "None of the 'atemp' data is invalid\n", "None of the 'humidity' data is invalid\n", "None of the 'windspeed' data is invalid\n", "None of the 'casual' data is invalid\n", "None of the 'registered' data is invalid\n", "None of the 'counts' data is invalid\n", "\n", "\n", "All of these printing as such shows that there should be no missing or errored data.\n" ] } ], "source": [ "badSeasonCount = (np.logical_and(np.isnan(all_data.season), all_data.season>4))\n", "total=0\n", "for i in badSeasonCount:\n", " if(i):\n", " total += 1\n", "if(total ==0):\n", " print(\"None of the 'season' data is invalid\")\n", "\n", " \n", "badHolidayCount = (np.logical_and(np.isnan(all_data.holiday), all_data.holiday>1))\n", "total=0\n", "for i in badHolidayCount:\n", " if(i):\n", " total += 1\n", "if(total ==0):\n", " print(\"None of the 'holiday' data is invalid\")\n", " \n", " \n", "badWorkCount = (np.logical_and(np.isnan(all_data.workingday), all_data.workingday>1))\n", "total=0\n", "for i in badWorkCount:\n", " if(i):\n", " total += 1\n", "if(total ==0):\n", " print(\"None of the 'workingDay' data is invalid\")\n", " \n", " \n", "badWeatherCount = (np.logical_and(np.isnan(all_data.weather), all_data.weather>4))\n", "total=0\n", "for i in badWeatherCount:\n", " if(i):\n", " total += 1\n", "if(total ==0):\n", " print(\"None of the 'weather' data is invalid\")\n", " \n", " \n", "badTempCount = (np.logical_and(np.isnan(all_data.temp), all_data.temp>50))\n", "total=0\n", "for i in badTempCount:\n", " if(i):\n", " total += 1\n", "if(total ==0):\n", " print(\"None of the 'temp' data is invalid\")\n", " \n", " \n", "badaTempCount = (np.logical_and(np.isnan(all_data.atemp), all_data.atemp>50))\n", "total=0\n", "for i in badaTempCount:\n", " if(i):\n", " total += 1\n", "if(total ==0):\n", " print(\"None of the 'atemp' data is invalid\")\n", " \n", " \n", "badHumidCount = (np.logical_and(np.isnan(all_data.humidity), all_data.humidity>4))\n", "total=0\n", "for i in badHumidCount:\n", " if(i):\n", " total += 1\n", "if(total ==0):\n", " print(\"None of the 'humidity' data is invalid\")\n", " \n", " \n", "badWindCount = (np.logical_and(np.isnan(all_data.windspeed), all_data.windspeed>25))\n", "total=0\n", "for i in badWindCount:\n", " if(i):\n", " total += 1\n", "if(total ==0):\n", " print(\"None of the 'windspeed' data is invalid\")\n", " \n", " \n", "badCasualCount = (np.logical_and(np.isnan(all_data.casual), all_data.casual>1000))\n", "total=0\n", "for i in badCasualCount:\n", " if(i):\n", " total += 1\n", "if(total ==0):\n", " print(\"None of the 'casual' data is invalid\")\n", " \n", "badRegisteredCount = (np.logical_and(np.isnan(all_data.registered), all_data.registered>1000))\n", "total=0\n", "for i in badRegisteredCount:\n", " if(i):\n", " total += 1\n", "if(total ==0):\n", " print(\"None of the 'registered' data is invalid\") \n", "\n", "badCountsCount = (np.logical_and(np.isnan(all_data.counts), all_data.counts>1000))\n", "total=0\n", "for i in badCountsCount:\n", " if(i):\n", " total += 1\n", "if(total ==0):\n", " print(\"None of the 'counts' data is invalid\") \n", " \n", "\n", "print(\"\\n\\nAll of these printing as such shows that there should be no missing or errored data.\")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Under the assumption that there is no wrong data we can proceed without fixing the data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### A First Look\n", "\n", "Plotting the number of casual and registered riders for the first 168 points will give us about 7 days of data to look at." ] }, { "cell_type": "code", "execution_count": 182, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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xHW1IzvNOxnMGed7JRDKeMyTneTf0nOPxmcmQgUQikUgkEikIJBKJRCKRSEEg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\nQYMGYUkNNXMb0jMOAO3bt8ekSZMwceJEPPPMMzb3b4j3Ojs7G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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(dates[0:168], all_data.casual[0:168], 'b', label = \"casual\")\n", "plt.plot(dates[0:168], all_data.registered[0:168], 'r', label = \"registered\")\n", "plt.plot(dates[0:168], all_data.counts[0:168], 'g', label = \"total\")\n", "plt.legend(loc = 'upper left')\n", "plt.xlabel('Date and Time')\n", "plt.ylabel('Counts')\n", "plt.title(\"Counts for the first 7 days of points\", fontsize = 20)\n", "plt.figure(figsize=(15,5), dpi = 1000)\n", "plt.gcf().autofmt_xdate()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Seeing these 7 peaks for the for 7 days I can see that there is a are not many rentals during the late night hours, using this information I am going to remove these late night hours from the data to be analyzed. I am doing this to remove many of the 0 rental points, that occur during the night hours, from my analysis\n", "\n", "\n", "The $isDaytime$ array will hold $True$ if the value is between 7am and 9pm and $false$ otherwise.\n", "\n", "By knowing which locations in the array are during the day time we can make an array that contains only the values from the day time and keeps them in order.\n", "\n", "After this cell is run, slicing a data array by this $isDaytime$ array will remove all of the late night data points." ] }, { "cell_type": "code", "execution_count": 183, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#extracting the hour from the date time\n", "hours =[]\n", "for date in dates:\n", " hours.append(date.hour)\n", "\n", "isDaytime = []\n", "for i in hours:\n", " if(7" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "xvals = all_data.weather[isDaytime]\n", "yvals = all_data.counts[isDaytime]\n", "\n", "fig = sns.violinplot(xvals, yvals)\n", "plt.gca().set_xticklabels(['Nice', 'Mild', 'Bad', 'Severe'])\n", "plt.xlabel(\"Weather\")\n", "plt.ylabel(\"Number of Bikes rented\")\n", "plt.title(\"Weather and Rental Counts\", fontsize = 20)\n", "plt.ylim([0, 1200])\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "##### Note that the severe weather category has very few entries so the violin shape has been compressed to a very short line." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Correlation and Regression\n", "##### Null Hypothesis: There is no correlation between the weather and the number of rentals.\n", "\n", "Will will determine whether there is a correlation between the weather and the rental count using the spearman correlation test." ] }, { "cell_type": "code", "execution_count": 186, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "P-value: 1.35e-60\n" ] } ], "source": [ "cor_weatherAndCounts = ss.spearmanr(xvals, yvals)[1]\n", "\n", "print(\"P-value: {:.3}\".format(cor_weatherAndCounts))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Correlation Results:\n", "#### P-value = $1.35 * 10^-60$\n", "\n", "This p-value is less than .05, we reject the null hypothesis and conclude there is a correlation between the weather and the number of rentals.\n", "\n", "We can now try to make a regression for this relationship. The relation beween these two values seems to be **linear**.\n", "\n", "\n", "#### Linear Model:\n", "Starting with a linear model we will optimize this equation:\n", "$$ R = \\beta_0 * W + \\beta_1 $$\n", "Where:\n", "$$R = Number\\ of\\ Rentals,\\ \\ W = Weather\\ Condition\\ Number $$\n", "\n", "\n", "The defined function takes in values for $\\beta_0$ and $\\beta_1$ and returns what the sum of the sum of the squares of the residuals.\n", "\n", "The optimize funtion will find values for $\\beta_0$ and $\\beta_1$ which minimize this total." ] }, { "cell_type": "code", "execution_count": 187, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "B0 = -58.44 B1 = 370.9\n" ] } ], "source": [ "def bestFit(x, b0, b1):\n", " '''This function uses beta values an an x array to make a yHat value '''\n", " return x*b0 + b1\n", " \n", "def SSR(args):\n", " '''Given an array of 2 betas, the sum of the squares of the residuals is calcualted by using the previous function \n", " for a yHat then summing the square of the difference between the '''\n", " b0 = args[0]\n", " b1 = args[1]\n", " yhat = bestFit(xvals, b0, b1)\n", " ssr = np.sum((yhat - yvals)**2)\n", " return ssr\n", "\n", "optResult = scipy.optimize.minimize(SSR, x0=[-75, 300])\n", "\n", "print(\"B0 = {:.4} B1 = {:.4}\".format(optResult.x[0], optResult.x[1]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Results of minimizing the sum of the squares of the residuals\n", "The line that was determined to best fit the graph was:\n", "\n", "$$ R = -58.44 * W + 370.9 $$\n", "\n", "Now we will plot this line and the residuals:\n" ] }, { "cell_type": "code", "execution_count": 188, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(0, 1200)" ] }, "execution_count": 188, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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T9+nTR1oAYc+ePRg1ahQUCgXCw8MRERGBEydOIC8vD1qtVmoqfOihh6yuXEYI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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = sns.violinplot(xvals, yvals)\n", "plt.plot([0, 1, 2, 3], bestFit(np.array([1, 2, 3, 4]), optResult.x[0], optResult.x[1]), 'bo-')\n", "#the negative 1 adjustment in the x-values is an adjustmen to make the line allign properly. It has no effect on calculations\n", "plt.gca().set_xticklabels(['Nice', 'Mild', 'Bad', 'Severe'])\n", "plt.xlabel(\"Weather\")\n", "plt.ylabel(\"Number of Bikes rented\")\n", "plt.title(\"Weather and Rental Counts With Estimation\", fontsize = 20)\n", "plt.ylim([0, 1200])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### We can see that the line fits across the median values fairly well and is a little high to compensate for the tall peaks.\n", "\n", "### Histogramming the residuals:\n", "\n", "Taking the expected counts subtracting the actual rental count for each weather value will give us the residuals which we will plot.\n", "\n", "We will also run a Shapiro-Wilkes test to see if the residuals are normally distributed.\n", "\n", "###### Null Hypothesis: The data is normally distributed." ] }, { "cell_type": "code", "execution_count": 189, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 189, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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lGg0Ft956K02aNKnQ1qNHDzw8yjbbuXNnMjMzAUhJSWHAgAFYrVZ8fX3x8/Mj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\nIiKAQoGIiIg4KBSIiIgIoFA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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "resids = yvals - bestFit(xvals, optResult.x[0], optResult.x[1])\n", "\n", "plt.hist(resids)\n", "plt.title(\"Residuals of the Linear Best Fit\", fontsize = 20)\n", "plt.xlabel(\"Difference in estimated and actual\")\n", "plt.ylabel(\"Count\")\n" ] }, { "cell_type": "code", "execution_count": 190, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "P-value: 1.401298464324817e-45\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.5/site-packages/scipy/stats/morestats.py:1329: UserWarning: p-value may not be accurate for N > 5000.\n", " warnings.warn(\"p-value may not be accurate for N > 5000.\")\n" ] } ], "source": [ "normality = ss.shapiro(resids)\n", "print(\"P-value:\", normality[1])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### With a p-value much less than .05 we reject the null hypothesis. The residuals are not normal. This tells us that the regression line we chose to use was not a good model for the data.\n", "\n", "#### Perhaps using a different model equation would help with this, or there are simply too many different variables to use a single variable to predict counts despite the strong correlation.\n", "\n", "##### It should be noted that the Shapiro-Wilkes test is not accurate over 5000 samples, and we used ~6000 samples, however the result is so far from .05 that we will assume this limitation will not affect our results.\n", "______\n", "______\n", "______" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Temperature and Count Correlation\n", "\n", "Using the temperature in degree Celsius and the number of rentals.\n", "\n", "To do this we will go through the same process as before.\n", "\n", "#### First Lets plot the relationship\n", "\n" ] }, { "cell_type": "code", "execution_count": 191, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(0, 1100)" ] }, "execution_count": 191, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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xAKKsAdWJmvKve6PVcqtmDXTjCGRdAwPiI7Ert7DaNXKdqFXjKLi5VP2GFQGG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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "xvals2 = all_data.temp[isDaytime]\n", "yvals2 = all_data.counts[isDaytime]\n", "\n", "#fig = sns.violinplot(all_data.temp[isDaytime], all_data.counts[isDaytime])\n", "plt.plot(xvals2, yvals2, 'o')\n", "plt.xlabel(\"Temperature (Degrees Celsius)\")\n", "plt.ylabel(\"Number of Rentals\")\n", "plt.title(\"Temperatures and Counts Plot\", fontsize = 20)\n", "plt.ylim([0, 1100])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Testing for a correlation between Temperature and Rental Counts\n", "Using a spearman correlation test we will see if there is a correlation.\n", "\n", "###### Null Hypothesis: The temperature and rental counts are not correlated." ] }, { "cell_type": "code", "execution_count": 192, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "P-value: 8.036e-290\n" ] } ], "source": [ "cor_tempAndCount = ss.spearmanr(xvals2, yvals2)[1]\n", "\n", "print(\"P-value: {:.4}\".format(cor_tempAndCount))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Correlation Results:\n", "#### P-value = $8.036 x 10 ^ {-290}$\n", "\n", "This p-value is less than .05, we reject the null hypothesis and conclude there is a correlation between the temperature and the number of rentals.\n", "\n", "We can now try to make a regression for this relationship. The relation beween the data could be a **negative polynomial**. This also makes sense in the context, as temperatures get to be too far from a comfortable range the willingness to ride a bike decreases.\n", "\n", "\n", "#### Polynomial Model:\n", "Starting with a linear model we will optimize this equation:\n", "$$ R = \\beta_0 *T^2 + \\beta_1 * T + \\beta_2 $$\n", "Where:\n", "$$R = Number\\ of\\ Rentals,\\ \\ T = Temperature\\ in\\ C^\\circ$$\n", "\n", "\n", "This time the function will take in values for $\\beta_0$, $\\beta_1$, and $\\beta_2$ and returns what the sum of the sum of the squares of the residuals.\n", "\n", "\n", "BasinHopping is also used for this equation to minimize the residiuals. This method will avoid getting caught in local minimums by \"hopping\" out of \"basins\"." ] }, { "cell_type": "code", "execution_count": 193, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "500\n", " fun: 158542271.76543796\n", " lowest_optimization_result: fun: 158542271.76543796\n", " hess_inv: array([[ 1.85700794e-08, -7.84274559e-07, 7.04873597e-06],\n", " [ -7.84274559e-07, 3.43780272e-05, -3.24519579e-04],\n", " [ 7.04873597e-06, -3.24519579e-04, 3.33216258e-03]])\n", " jac: array([ 0., 0., 0.])\n", " message: 'Optimization terminated successfully.'\n", " nfev: 110\n", " nit: 8\n", " njev: 22\n", " status: 0\n", " success: True\n", " x: array([ -0.35395953, 24.27707356, -48.65081377])\n", " message: ['requested number of basinhopping iterations completed successfully']\n", " minimization_failures: 5000\n", " nfev: 136124\n", " nit: 5000\n", " njev: 15225\n", " x: array([ -0.35395953, 24.27707356, -48.65081377])\n", "B0 = -0.354 B1 = 24.28 B2 = -48.65\n" ] } ], "source": [ "\n", "def bestFit2(x, b0, b1, b2):\n", " '''This takes in 3 betas to make a yHat for the temperature data'''\n", " return b0*x**2 + x*b1 + b2\n", " \n", "def SSR2(args):\n", " '''This uses the same method as in the first example to calculate the Sum of the squares\n", " of the residual.'''\n", " b0 = args[0]\n", " b1 = args[1]\n", " b2 = args[2]\n", " yhat = bestFit2(xvals2, b0, b1, b2)\n", " ssr = np.sum((yhat - yvals2)**2)\n", " return ssr\n", "\n", "print(bestFit2(10, -5,100,0))\n", "\n", "\n", "#optResult2 = scipy.optimize.minimize(SSR2, x0=[0, 0,0])\n", "optResult2 = scipy.optimize.basinhopping(SSR2, x0 = [-5,25,-50], niter = 5000)\n", "print(optResult2)\n", "beta0 = optResult2.x[0]\n", "beta1 = optResult2.x[1]\n", "beta2 = optResult2.x[2]\n", "print(\"B0 = {:.4} B1 = {:.4} B2 = {:.4}\".format(optResult2.x[0], optResult2.x[1], optResult2.x[2]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Results of minimizing the sum of the squares of the residuals\n", "The line that was determined to best fit the graph was:\n", "\n", "$$ R = -0.354 * T^2 + 24.28 * T -48.65$$\n", "\n", "Now we will plot this line and the residuals:" ] }, { "cell_type": "code", "execution_count": 194, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(0, 1200)" ] }, "execution_count": 194, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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eWLlyJT7++GNs3rwZn332GTw9PREZGYnHHnvMYjOrdh5q5mkQ9N6WmzF79mx8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\nqL2hB5Rzp7P9NhhpZIWIZs2a4eOPPwZQaX4Q/1/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bDl0GoE9qcEoToPV8uUqmh09dB0Br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\nA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WzftR7ngQce4KuvvuLOO+/kpZde4sYbb+SVV17BbDYzd+5cVq9ezeTJkwG4cOECX3zx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\nvZBChEQikUgkknohhQiJRCKRSCT14v8DHNcCacyYiDgAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(xvals2, yvals2, 'o')\n", "plt.plot(np.linspace(0, 45,100) , bestFit2(np.linspace(0, 45,100), beta0, beta1, beta2), 'r-')\n", "plt.xlabel(\"Temperature (Degrees Celsius)\")\n", "plt.ylabel(\"Number of Bikes rented\")\n", "plt.title(\"Temperature and Rental Counts With Estimation\", fontsize = 20)\n", "plt.ylim([0, 1200])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### This negative exponential function fits the data fairl well, it seems to go through the middle of the data again and is still missing the upper peaks.\n", "\n", "### Histogramming the residuals:\n", "\n", "Again we will take the expected values from our newly optimized function and subtract the actual values \n", "\n", "We will also run a Shapiro-Wilkes test to see if the residuals are normally distributed.\n", "\n", "###### Null Hypothesis: The data is normally distributed." ] }, { "cell_type": "code", "execution_count": 195, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 195, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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WcWut+q4uBYA/8n9jxcw+BAYGuroUEZFrikKBVIpba9XntjoNXV2GiIhcgs4p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\n/gP0Gn9jbBnrrQAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "resids2 = yvals2 - bestFit2(xvals2, optResult2.x[0], optResult2.x[1], optResult2.x[2])\n", "\n", "plt.hist(resids2)\n", "plt.title(\"Residuals of the Linear Best Fit for Temperature\", fontsize = 16)\n", "plt.xlabel(\"Difference in estimated and actual\")\n", "plt.ylabel(\"Count\")\n" ] }, { "cell_type": "code", "execution_count": 196, "metadata": { "collapsed": false, "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "P-value: 5.044674471569341e-44\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.5/site-packages/scipy/stats/morestats.py:1329: UserWarning: p-value may not be accurate for N > 5000.\n", " warnings.warn(\"p-value may not be accurate for N > 5000.\")\n" ] } ], "source": [ "normality2 = ss.shapiro(resids2)\n", "print(\"P-value:\", normality2[1])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### With a p-value much less than .05 we reject the null hypothesis. The residuals are not normal. This tells us that the regression line we chose to use was not a good model for the data. However, looking at how the data is distributed it may be very challenging to find a best fit line that will have normally distributed residuals. We will discuss this in the conclussion.\n", "\n", "#### Again we could use a different model to model the equation to attempt to find a better fit.\n", "\n", "##### Again we should note that the Shapiro-Wilkes test is not accurate over 5000 samples, and we used ~6000 samples, and the result is so far from .05 that we will assume this limitation will not affect our results.\n", "______\n", "______\n", "______\n", "\n", "## Conclussion:\n", "\n", "While both of these regressions ended up not being strong fits for the data they did give us insight to how we could further analyze the data. \n", "\n", "Seeing as both histograms have a very similar shape, a longer left tail and a very short right tale. This disticntly shows us that the error in our regression line is not normally distributed. This occurs because the regression line can not represent how the data has a few values with a great number of riders and then many values with fewer or even zero rentals. The high rental numbers end up pulling the average values above the bulk of the values that are down around 0 rentals. Perhaps finding another way to remove some of the consistently low values that are caused by other factors would allow for a better estimate of the values that we are interested in. \n", "\n", "Another possible explanation for this error could be that we are not looking at enough of the facors. Perhaps we should be looking more factors simultaneously to estimate the number of riders. \n", "\n", "Based on some literature, tne last consideration should be the nature of data. It is possible that the data's \"random error\" or \"noise\" is not normal but rather of a binomial or Poisson distribution. This would make sense because there is a large population of people that can use these bikes and each person has a probability of renting a bike at a given time. With this in mind we would expect a Poisson distribution of the number of rentals and this would lead to a Poisson distribution of error which more closely matches the residuals that were found.\n", "\n", "\n", "\n", "______\n", "______\n", "\n", "\n", "## Finally a Visual Look at the Number of Rentals Compared to both Factors" ] }, { "cell_type": "code", "execution_count": 197, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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MS0sL2dnZ3f78D37wA3bs2EFTUxNLly7lnnvu4a677uLee+9l7dq1jBgxgqee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\nHHHvZgB/RVy+BiIE/wPn27gR2y4hK6uWL3xhDqmpfv7wh/dpaIATJw5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efPJJANauXcsz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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from mpl_toolkits.mplot3d import Axes3D\n", "fig = plt.figure()\n", "ax = fig.add_subplot(111, projection='3d')\n", "ax.scatter(xvals, xvals2, yvals, zdir='z', s=20, c='b', depthshade=True)\n", "\n", "ax.set_xlabel('Weather')\n", "ax.set_ylabel('Temperature (C)')\n", "ax.set_zlabel('Rental Count')\n", "\n", "plt.show() " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### What we can see in this plot\n", "\n", "We can see the 4 distinct weather values and as the weather gets to be harsher we can see that the high numbers of rentals start to be less frequent while the low number of rentals stays fairly dense. This shows us that as we expect, people are less likely to want to rent a bike in harsh weather.\n", "\n", "We can also see across all 4 weather values the affect of temperature. As the temperature gets low, there are no data points that have a high number of rentals.\n", "\n", "The last very interesting thing that we can see from this plot that could not possibly be seen in the earlier plots is that as the weather gets harsher the distribution of teperatures changes drastically. The harsher weather clusters have a much lower average temperature because they have much fewer high temperature data points." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Another Interesting Plot to Look at\n", "\n", "Lets look at some data that has a known relationship. We will be plotting the \"feels like\" temperature as a function of temperature and windspeed. We know that these values are related because the \"feels like\" temperature is determined by the real temperature and the wind speed. Due to the sheer number of data points it has been decided to only plot every 10^{th} point to make the data more visible. We have also made the axis disproportianate to show the shape of the data a little better." ] }, { "cell_type": "code", "execution_count": 198, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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Gca26HvqLgB6j1DTN0l1EhsObtRXYZSG0A5m+83wSjERT+sHBTDDtvHm0vtbe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\n4eLikuF33bp1IzAwEIDu3buze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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from mpl_toolkits.mplot3d import Axes3D\n", "fig = plt.figure()\n", "ax = fig.add_subplot(111, projection='3d')\n", "ax.scatter(all_data.temp[::10], all_data.windspeed[::10], all_data.atemp[::10], zdir='z', s=20, c='b', depthshade=True)\n", "\n", "\n", "ax.set_xlim([0, 60])\n", "ax.set_ylim([0, 30])\n", "ax.set_zlim([0, 100])\n", "ax.set_xlabel('Real Temperature (C)')\n", "ax.set_ylabel('WindSpeed (km/hr)')\n", "ax.set_zlabel('\"Feels Like\" Temp (C)')\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This plot shows that as temperature increases so does the \"Feels like\" Temperature. It is hard see what how the wind affects the \"Feels like\" temp because of the nature of the graphics and the minimum effect of the wind speed. Perhaps by selecting a different graphic for the points this could be more visible." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Appendix:\n", "_______\n", "\n", "### A) Data Source:\n", "\n", "Hadi Fanaee Tork using data from Capital Bikeshare \n", "28 May 2014 \n", "\n", "Fanaee-T, Hadi, and Gama, Joao, Event labeling combining ensemble detectors and background knowledge, Progress in Artificial Intelligence (2013): pp. 1-15, Springer Berlin Heidelberg.\n", "\n", "https://www.kaggle.com/c/bike-sharing-demand/data?sampleSubmission.csv\n", "\n", "______\n", "\n", "### B) Data Key:\n", "\n", "Data Fields \n", "* **datetimes** - hourly date + timestamp \n", "* **season** - 1 = spring, 2 = summer, 3 = fall, 4 = winter \n", "* **holiday** - whether the day is considered a holiday \n", "* **workingday** - whether the day is neither a weekend nor holiday \n", "* **weather** - \n", " * 1: Clear, Few clouds, Partly cloudy, Partly cloudy \n", " * 2: Mist + Cloudy, Mist + Broken clouds, Mist + Few clouds, Mist \n", " * 3: Light Snow, Light Rain + Thunderstorm + Scattered clouds, Light Rain + Scattered clouds \n", " * 4: Heavy Rain + Ice Pallets + Thunderstorm + Mist, Snow + Fog \n", "\n", "* **temp** - temperature in Celsius \n", "* **atemp** - \"feels like\" temperature in Celsius \n", "* **humidity**- relative humidity \n", "* **windspeed** - wind speed \n", "* **casual** - number of non-registered user rentals initiated \n", "* **registered** - number of registered user rentals initiated \n", "* **counts** - number of total rentals\n", "\n", "______\n", "\n", "### C) Poisson Data Information Sources: \n", "\n", "\n", "\n", "R Data Analysis Examples: Poisson Regression \n", "UCLA: Statistical Consulting Group. \n", "Accessed 4/28/16 \n", "http://www.ats.ucla.edu/stat/r/dae/poissonreg.htm\n", "\n", "\n", "\n", "Germán Rodríguez \n", "Princeton University Course Notes. Fall 2015 \n", "http://data.princeton.edu/wws509/notes/c4.pdf\n", "\n", "\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "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": "3.5.1" } }, "nbformat": 4, "nbformat_minor": 0 }