diff --git a/is/kaggle/ExerciseSheetKaggle.ipynb b/is/kaggle/ExerciseSheetKaggle.ipynb new file mode 100644 index 0000000..8744b56 --- /dev/null +++ b/is/kaggle/ExerciseSheetKaggle.ipynb @@ -0,0 +1,933 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "preamble": true + }, + "source": [ + "(Defining latex commands: not to be shown...)\n", + "$$\n", + "\\newcommand{\\norm}[1]{\\left \\| #1 \\right \\|}\n", + "\\DeclareMathOperator{\\minimize}{minimize}\n", + "\\DeclareMathOperator{\\maximize}{maximize}\n", + "\\newcommand{\\real}{\\mathbb{R}}\n", + "\\newcommand{\\blasso}{\\beta^{\\mathrm{LASSO}}}\n", + "\\newcommand{\\bzero}{\\beta^0}\n", + "\\newcommand{\\bLS}{\\hat{\\beta}^{\\mathrm{LS}}}\n", + "$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Weight shrinkage competition\n", + "\n", + "In this competition you will work on a real world dataset. The objective is to try and predict weight of some person using historical data collected over several years.\n", + "\n", + "The competition is hosted on [Kaggle website](https://inclass.kaggle.com/c/weightshrinkage). This competition is by invitiation only, we will send out invitations to all emails registered on the Google mailing list. You can participate in groups of two or individually, Kaggle will help you how to participate in groups.\n", + "\n", + "In order to get a full mark for this competition you should get pass the benchmark evaluation. In this sheet you will get an idea how to do that." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Interploation techniques\n", + "\n", + "The dataset you will be working with is an instance of a time series. Time series are different from what you may typically see in Machine Learning problems. The most important distinction between a time series and other datasets is that data points are no longer iid (**i**ndependently and **i**dentically **d**istributed).\n", + "\n", + "Analysis of time series is a rich field of study. Here we show you one very simple method to work with time series. The dataset you download from the website contains many NA (**N**ot **A**ssigned) values. These missing values arise naturally in many datasets. Sometimes measurements are not made for every record or sometimes the data is corrupted. In this case, most NA values are cases where no measurement was made.\n", + "\n", + "Since the dataset is a time series one simple approach is to fill in the NA values with neighboring values. This works particularly well when missing values are scattered and there are no missing values in long continuous ranges. Unfortunately our dataset suffers from this issue but we will use this technique as a first step. Feel free to use other methods to improve your result. Our objective is to fill in missing values for the *Weight* vector which is our target variable via interpolation.\n", + "\n", + "## Interpolation in Python\n", + "\n", + "You can do interpolation in Python using many different packages. Here we use [Pandas](http://pandas.pydata.org/) which is a common library for data analysis. The difference between Pandas and Numpy is the way data is layed out in memory which makes many operations efficient and easy.\n", + "\n", + "As usual we start with loading the package:" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pandas provide similar, and sometimes more advanced, functionalities for loading different kinds of data. One if its particular strength is in working with time series data." + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
IDFoodWeightWeightCaloriesProteinsLipidsCarbohydratesRemarks
Date
2013-06-11 401 30.92 91.3 2107 156 43 270 NaN
2013-06-12 402 30.31 91.4 2057 125 40 293 NaN
2013-06-13 403 34.11 91.2 2151 119 33 341 NaN
2013-06-14 404 NaN 91.7 NaN NaNNaN NaN VisitTo
2013-06-15 405 28.95 NaN 2418 160 47 311 NaN
2013-06-16 406 NaN 91.8 NaN NaNNaN NaN VisitTo
2013-06-17 407 31.00 92.6 2211 171 49 264 NaN
2013-06-18 408 36.42 NaN 2274 167 23 342 NaN
2013-06-19 409 38.14 91.9 2274 137 33 346 NaN
2013-06-20 410 NaN 91.7 NaN NaNNaN NaN VisitTo
\n", + "
" + ], + "text/plain": [ + " ID FoodWeight Weight Calories Proteins Lipids \\\n", + "Date \n", + "2013-06-11 401 30.92 91.3 2107 156 43 \n", + "2013-06-12 402 30.31 91.4 2057 125 40 \n", + "2013-06-13 403 34.11 91.2 2151 119 33 \n", + "2013-06-14 404 NaN 91.7 NaN NaN NaN \n", + "2013-06-15 405 28.95 NaN 2418 160 47 \n", + "2013-06-16 406 NaN 91.8 NaN NaN NaN \n", + "2013-06-17 407 31.00 92.6 2211 171 49 \n", + "2013-06-18 408 36.42 NaN 2274 167 23 \n", + "2013-06-19 409 38.14 91.9 2274 137 33 \n", + "2013-06-20 410 NaN 91.7 NaN NaN NaN \n", + "\n", + " Carbohydrates Remarks \n", + "Date \n", + "2013-06-11 270 NaN \n", + "2013-06-12 293 NaN \n", + "2013-06-13 341 NaN \n", + "2013-06-14 NaN VisitTo \n", + "2013-06-15 311 NaN \n", + "2013-06-16 NaN VisitTo \n", + "2013-06-17 264 NaN \n", + "2013-06-18 342 NaN \n", + "2013-06-19 346 NaN \n", + "2013-06-20 NaN VisitTo " + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = pd.read_csv(\"./datasets/kag_train.csv\",index_col='Date',parse_dates='Date')\n", + "data[400:410]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This line loads the data, treats *Date* field in the dataset as Datetime and sets *Date* column as the index of the loaded Table. The standard data structure in Pandas is *Dataframe*, a dataframe contains several *Series* with the same index. If the index is a time series Panda will automatically constructs appropriate indexing. Also note that Pandas detects NA values automatically." + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAElCAYAAAD5r2lGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nGIZhGD3D/wPgTbK5MtCyEgAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "%matplotlib inline\n", + "data['Weight'].plot(marker = 'x',title='reported Weight')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we would like to perform interpolation for missing values in the *Weight* column. To do so we first select the column we would like to make the interpolation for and then apply the $\\texttt{interpolate}$ function on the Series we selected." + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
IDFoodWeightWeightCaloriesProteinsLipidsCarbohydratesRemarksWeightInter
Date
2013-06-11 401 30.92 91.3 2107 156 43 270 NaN 91.30
2013-06-12 402 30.31 91.4 2057 125 40 293 NaN 91.40
2013-06-13 403 34.11 91.2 2151 119 33 341 NaN 91.20
2013-06-14 404 NaN 91.7 NaN NaNNaN NaN VisitTo 91.70
2013-06-15 405 28.95 NaN 2418 160 47 311 NaN 91.75
2013-06-16 406 NaN 91.8 NaN NaNNaN NaN VisitTo 91.80
2013-06-17 407 31.00 92.6 2211 171 49 264 NaN 92.60
2013-06-18 408 36.42 NaN 2274 167 23 342 NaN 92.25
2013-06-19 409 38.14 91.9 2274 137 33 346 NaN 91.90
2013-06-20 410 NaN 91.7 NaN NaNNaN NaN VisitTo 91.70
\n", + "
" + ], + "text/plain": [ + " ID FoodWeight Weight Calories Proteins Lipids \\\n", + "Date \n", + "2013-06-11 401 30.92 91.3 2107 156 43 \n", + "2013-06-12 402 30.31 91.4 2057 125 40 \n", + "2013-06-13 403 34.11 91.2 2151 119 33 \n", + "2013-06-14 404 NaN 91.7 NaN NaN NaN \n", + "2013-06-15 405 28.95 NaN 2418 160 47 \n", + "2013-06-16 406 NaN 91.8 NaN NaN NaN \n", + "2013-06-17 407 31.00 92.6 2211 171 49 \n", + "2013-06-18 408 36.42 NaN 2274 167 23 \n", + "2013-06-19 409 38.14 91.9 2274 137 33 \n", + "2013-06-20 410 NaN 91.7 NaN NaN NaN \n", + "\n", + " Carbohydrates Remarks WeightInter \n", + "Date \n", + "2013-06-11 270 NaN 91.30 \n", + "2013-06-12 293 NaN 91.40 \n", + "2013-06-13 341 NaN 91.20 \n", + "2013-06-14 NaN VisitTo 91.70 \n", + "2013-06-15 311 NaN 91.75 \n", + "2013-06-16 NaN VisitTo 91.80 \n", + "2013-06-17 264 NaN 92.60 \n", + "2013-06-18 342 NaN 92.25 \n", + "2013-06-19 346 NaN 91.90 \n", + "2013-06-20 NaN VisitTo 91.70 " + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data['WeightInter'] = data['Weight'].interpolate()\n", + "data[400:410]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Comparing the values in *Weight* and *WeightInter* we can see pandas used a linear interpolation to fill in null values in our dataset. We can now store the results and make a submission on Kaggle.\n", + "\n", + "# Kaggle submission\n", + "\n", + "In order to make a submission we should make predictions for specific dates, indexed by ID. The first step is to load the indices from *test.csv* file." + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
ID
0 183
1 184
2 185
3 186
4 187
5 192
6 197
7 203
8 209
9 210
\n", + "
" + ], + "text/plain": [ + " ID\n", + "0 183\n", + "1 184\n", + "2 185\n", + "3 186\n", + "4 187\n", + "5 192\n", + "6 197\n", + "7 203\n", + "8 209\n", + "9 210" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "test = pd.read_csv(\"./datasets/kag_test.csv\")\n", + "test[:10]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note that we did not use *ID* as the index therefore pandas created an index for us. Now we use the $\\texttt{join}$ operation to join these indices to our original dataset. In order to join two so-called frames we need to set the Index column of the our training set to *ID*. This will allow us to join two frames on this column." + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
IDFoodWeightWeightCaloriesProteinsLipidsCarbohydratesRemarksWeightInter
0 183NaNNaN 2201 93 47 327 NaN 92.083333
1 184NaNNaN 2387 159 59 300 NaN 91.966667
2 185NaNNaN 2106 87 30 370 NaN 91.850000
3 186NaNNaN 1914 78 30 328 NaN 91.733333
4 187NaNNaN 2311 106 38 374 NaN 91.616667
5 192NaNNaN NaN NaN NaN NaN Lazy 91.533333
6 197NaNNaN 2359 148 33 311 NaN 91.575000
7 203NaNNaN 2488 97 115 262 NaN 91.320000
8 209NaNNaN 2826 129 90 367 NaN 90.850000
9 210NaNNaN 2197 137 51 295 NaN 90.825000
\n", + "
" + ], + "text/plain": [ + " ID FoodWeight Weight Calories Proteins Lipids Carbohydrates Remarks \\\n", + "0 183 NaN NaN 2201 93 47 327 NaN \n", + "1 184 NaN NaN 2387 159 59 300 NaN \n", + "2 185 NaN NaN 2106 87 30 370 NaN \n", + "3 186 NaN NaN 1914 78 30 328 NaN \n", + "4 187 NaN NaN 2311 106 38 374 NaN \n", + "5 192 NaN NaN NaN NaN NaN NaN Lazy \n", + "6 197 NaN NaN 2359 148 33 311 NaN \n", + "7 203 NaN NaN 2488 97 115 262 NaN \n", + "8 209 NaN NaN 2826 129 90 367 NaN \n", + "9 210 NaN NaN 2197 137 51 295 NaN \n", + "\n", + " WeightInter \n", + "0 92.083333 \n", + "1 91.966667 \n", + "2 91.850000 \n", + "3 91.733333 \n", + "4 91.616667 \n", + "5 91.533333 \n", + "6 91.575000 \n", + "7 91.320000 \n", + "8 90.850000 \n", + "9 90.825000 " + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data = data.set_index('ID')\n", + "predictions = test.join(data,on='ID')\n", + "predictions[:10]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can now observe that *WeightInter* contains predictions for all IDs. The only thing left now is to save the results and make a submission." + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "predictions[['ID','WeightInter']].to_csv('sampleSubmission.csv',\n", + " header = ['ID','Weight'],\n", + " index_label=False,index=False)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The first 5 lines of the file will look like this:" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ID,Weight\r\n", + "183,92.08333333333334\r\n", + "184,91.96666666666667\r\n", + "185,91.85\r\n", + "186,91.73333333333333\r\n" + ] + } + ], + "source": [ + "!head -5 myFirstSubmission" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Remarks\n", + "\n", + "This was the first step to build a model for predicting the weight. What else can be done?\n", + "\n", + "In order to predict time series values, one often computes a trendline using the target variable only (as you have just done for the weight), and then one considers the residuals between the observed values and this trendline. Those residuals are then regressed on the predictor variables (here: calories, proteins, etc.). \n", + "\n", + "That is, if you want to obtain better predictions, you may either use more sophisticated interpolation methods that yield better trendlines or you use regression methods (e.g. those from the lecture) in order to find a good model for the residuals using the predictor variables. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Working with categorical data\n", + "\n", + "If you want to use the Remark column to make predictions, you will have to find a way to handle categorical data. There are several ways to do so. Let us present two of them.\n", + "\n", + "1. Predict the mean of the output variable (for example the Weight, or its residual), conditionnally to the value of Remark.\n", + "2. Convert the categorical data to numerical data, and use any standard regression method (for example linear regression).\n", + "\n", + "To convert categorical data to numerical data, again, there are several options. Here are two of them.\n", + "\n", + "1. If you have only 2 categories, then you are fine by just assigning 1 number to the first, and another to the second category: for example 0 and 1. However, usually, if you have more than 2 categories, it is a bad idea to assign each category a randomly chosen number. This is because 1 is nearer from 2 than it is from 3, but it may not make any sense to say that the first category is more similar to the second than it is to the third.\n", + "2. Make a vector with length the number of different categories, where all entries are set to 0, except that of the active category, which is set to 1. For example, if you want to model data with 3 categories, say \"VisitOf\",\"VisitTo\",\"NoRemark\", then you would use a vector $v$ of length 3, where $v=(0,0,1)$, $v=(0,1,0)$ and $v=(1,0,0)$ encode respectively \"NoRemark\", \"VisitTo\", \"VisitOf\". Note that some would prefer an encoding like: $v = (0,0)$, $v=(0,1)$ and $v=(1,0)$.\n", + "\n", + "Finally, note that you are free to build new categories and more generally new features. You may for example merge different categories into a single one, or create new categories like \"isNA\" and \"isNotNA\". Or create new numerical vectors like the average food weight during the past 7 days, etc." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# A final piece of advice\n", + "\n", + "There are as many models to predict the weights as you may think of. However, very simple models offen yield among the best results if used with the right input features.\n", + "Thus, before starting to think about which (sophisticated) prediction method you may use, have a very close look at the data and think twice at what could be the relevant features to your problem. And if not provided, construct them!" + ] + } + ], + "metadata": { + "annotations": { + "author": "", + "categories": [ + "intelligent-systems-1-2015" + ], + "date": "2015-05-21", + "location": "Kaggle Website", + "parent": "IS_SS2015", + "submission_date": "2015-06-11", + "subtitle": "Exercise Sheet 5, Kaggle competition", + "tags": [ + "IntelligenSystems", + "Course" + ], + "title": "Intelligent Systems 1 - Summer Semester 2015" + }, + "celltoolbar": "Edit Metadata", + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.8" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/is/kaggle/ExerciseSheetKaggle.pdf b/is/kaggle/ExerciseSheetKaggle.pdf new file mode 100644 index 0000000..2bb5805 --- /dev/null +++ b/is/kaggle/ExerciseSheetKaggle.pdf Binary files differ diff --git a/is/kaggle/sampleSubmission.csv b/is/kaggle/sampleSubmission.csv new file mode 100644 index 0000000..cb02221 --- /dev/null +++ b/is/kaggle/sampleSubmission.csv @@ -0,0 +1,101 @@ +ID,Weight +183,92.0 +184,92.0 +185,92.0 +186,92.0 +187,92.0 +192,92.0 +197,92.0 +203,92.0 +209,92.0 +210,92.0 +226,92.0 +247,92.0 +257,92.0 +268,92.0 +271,92.0 +288,92.0 +292,92.0 +317,92.0 +341,92.0 +365,92.0 +422,92.0 +441,92.0 +494,92.0 +535,92.0 +581,92.0 +593,92.0 +625,92.0 +638,92.0 +639,92.0 +649,92.0 +657,92.0 +670,92.0 +685,92.0 +690,92.0 +700,92.0 +708,92.0 +724,92.0 +740,92.0 +743,92.0 +758,92.0 +765,92.0 +789,92.0 +809,92.0 +816,92.0 +835,92.0 +844,92.0 +861,92.0 +863,92.0 +873,92.0 +892,92.0 +127,92.0 +160,92.0 +191,92.0 +195,92.0 +196,92.0 +212,92.0 +222,92.0 +229,92.0 +233,92.0 +250,92.0 +254,92.0 +260,92.0 +265,92.0 +270,92.0 +272,92.0 +278,92.0 +286,92.0 +293,92.0 +296,92.0 +299,92.0 +373,92.0 +408,92.0 +489,92.0 +490,92.0 +537,92.0 +542,92.0 +543,92.0 +544,92.0 +545,92.0 +546,92.0 +550,92.0 +561,92.0 +562,92.0 +567,92.0 +611,92.0 +618,92.0 +619,92.0 +634,92.0 +646,92.0 +683,92.0 +689,92.0 +720,92.0 +751,92.0 +812,92.0 +837,92.0 +857,92.0 +859,92.0 +877,92.0 +1048,92.0 +1050,92.0 diff --git a/is/kaggle/test.csv b/is/kaggle/test.csv new file mode 100644 index 0000000..5cc25ae --- /dev/null +++ b/is/kaggle/test.csv @@ -0,0 +1,101 @@ +ID +183 +184 +185 +186 +187 +192 +197 +203 +209 +210 +226 +247 +257 +268 +271 +288 +292 +317 +341 +365 +422 +441 +494 +535 +581 +593 +625 +638 +639 +649 +657 +670 +685 +690 +700 +708 +724 +740 +743 +758 +765 +789 +809 +816 +835 +844 +861 +863 +873 +892 +127 +160 +191 +195 +196 +212 +222 +229 +233 +250 +254 +260 +265 +270 +272 +278 +286 +293 +296 +299 +373 +408 +489 +490 +537 +542 +543 +544 +545 +546 +550 +561 +562 +567 +611 +618 +619 +634 +646 +683 +689 +720 +751 +812 +837 +857 +859 +877 +1048 +1050 diff --git a/is/kaggle/train.csv b/is/kaggle/train.csv new file mode 100644 index 0000000..c5d60ab --- /dev/null +++ b/is/kaggle/train.csv @@ -0,0 +1,1063 @@ +ID,Date,FoodWeight,Weight,Calories,Proteins,Lipids,Carbohydrates,Remarks +1,2012-05-07,NA,NA,1795,110,47,242,"" +2,2012-05-08,NA,NA,1975,93,69,258,"" +3,2012-05-09,NA,NA,2319,159,51,263,"" +4,2012-05-10,NA,NA,1686,107,23,204,"" +5,2012-05-11,NA,NA,1980,90,39,313,"" +6,2012-05-12,NA,NA,2112,161,64,247,"" +7,2012-05-13,NA,NA,2081,97,83,231,"" +8,2012-05-14,NA,NA,2029,98,28,345,"" +9,2012-05-15,NA,NA,2092,113,55,284,"" +10,2012-05-16,NA,NA,2241,119,69,294,"" +11,2012-05-17,NA,NA,NA,NA,NA,NA,"GetTogether" +12,2012-05-18,NA,NA,NA,NA,NA,NA,"GetTogether" +13,2012-05-19,NA,NA,NA,NA,NA,NA,"GetTogether" +14,2012-05-20,NA,NA,NA,NA,NA,NA,"GetTogether" +15,2012-05-21,NA,NA,2057,183,49,220,"" +16,2012-05-22,NA,NA,2256,144,52,303,"" +17,2012-05-23,NA,NA,2217,168,39,288,"" +18,2012-05-24,NA,NA,1893,93,53,252,"" +19,2012-05-25,NA,NA,2176,131,61,268,"" +20,2012-05-26,NA,NA,2113,126,54,270,"" +21,2012-05-27,NA,NA,2177,151,17,317,"" +22,2012-05-28,NA,NA,2210,107,59,301,"" +23,2012-05-29,NA,NA,2701,153,79,329,"" +24,2012-05-30,NA,NA,2434,145,64,303,"" +25,2012-05-31,NA,NA,2289,116,35,369,"" +26,2012-06-01,NA,NA,NA,NA,NA,NA,"VisitOf" +27,2012-06-02,NA,NA,NA,NA,NA,NA,"VisitOf" +28,2012-06-03,NA,NA,NA,NA,NA,NA,"VisitOf" +29,2012-06-04,NA,NA,NA,NA,NA,NA,"VisitOf" +30,2012-06-05,NA,NA,NA,NA,NA,NA,"VisitOf" +31,2012-06-06,NA,NA,2269,125,77,263,"" +32,2012-06-07,NA,NA,2293,82,86,278,"" +33,2012-06-08,NA,NA,2202,138,75,234,"" +34,2012-06-09,NA,NA,2338,116,63,311,"" +35,2012-06-10,NA,NA,2709,142,103,284,"" +36,2012-06-11,NA,NA,2456,138,155,292,"" +37,2012-06-12,NA,NA,2060,130,50,263,"" +38,2012-06-13,NA,NA,NA,NA,NA,NA,"OnTravel" +39,2012-06-14,NA,NA,2256,117,72,276,"" +40,2012-06-15,NA,NA,2189,127,90,211,"" +41,2012-06-16,NA,NA,NA,NA,NA,NA,"Other" +42,2012-06-17,NA,NA,2130,98,66,283,"" +43,2012-06-18,NA,NA,2560,149,57,361,"" +44,2012-06-19,NA,NA,2198,161,73,205,"" +45,2012-06-20,NA,NA,2747,134,68,382,"" +46,2012-06-21,NA,NA,2297,83,50,367,"" +47,2012-06-22,NA,NA,2235,120,48,324,"" +48,2012-06-23,NA,NA,2046,96,64,262,"" +49,2012-06-24,NA,NA,NA,NA,NA,NA,"Ill" +50,2012-06-25,NA,NA,NA,NA,NA,NA,"Ill" +51,2012-06-26,NA,NA,2144,114,82,235,"" +52,2012-06-27,NA,NA,NA,NA,NA,NA,"Other" +53,2012-06-28,NA,NA,2310,79,81,308,"" +54,2012-06-29,NA,NA,2250,127,61,282,"" +55,2012-06-30,NA,NA,2139,70,52,342,"" +56,2012-07-01,NA,NA,2087,131,62,242,"" +57,2012-07-02,NA,NA,2281,129,57,38,"" +58,2012-07-03,NA,NA,2571,128,100,263,"" +59,2012-07-04,NA,NA,2178,111,63,275,"" +60,2012-07-05,NA,NA,2276,145,77,241,"" +61,2012-07-06,NA,NA,2123,129,65,244,"" +62,2012-07-07,NA,NA,NA,NA,NA,NA,"GetTogether" +63,2012-07-08,NA,NA,NA,NA,NA,NA,"GetTogether" +64,2012-07-09,NA,NA,1900,138,60,186,"" +65,2012-07-10,NA,NA,2224,155,56,262,"" +66,2012-07-11,NA,NA,2387,110,58,339,"" +67,2012-07-12,NA,NA,2312,119,38,373,"" +68,2012-07-13,NA,NA,NA,NA,NA,NA,"Restaurant" +69,2012-07-14,NA,NA,1975,85,53,284,"" +70,2012-07-15,NA,NA,2426,127,83,342,"" +71,2012-07-16,NA,NA,2094,143,53,261,"" +72,2012-07-17,NA,NA,2388,169,62,273,"" +73,2012-07-18,NA,NA,2001,108,62,246,"" +74,2012-07-19,NA,NA,2251,108,57,324,"" +75,2012-07-20,NA,NA,2824,132,108,316,"" +76,2012-07-21,NA,NA,2113,99,68,271,"" +77,2012-07-22,NA,NA,NA,NA,NA,NA,"Restaurant" +78,2012-07-23,NA,NA,2484,160,55,383,"" +79,2012-07-24,NA,NA,2211,132,50,302,"" +80,2012-07-25,NA,NA,2238,114,44,341,"" +81,2012-07-26,NA,NA,2258,106,71,281,"" +82,2012-07-27,NA,NA,2042,85,63,276,"" +83,2012-07-28,NA,NA,2772,161,92,311,"" +84,2012-07-29,NA,NA,2420,146,78,300,"" +85,2012-07-30,NA,NA,2293,169,72,235,"" +86,2012-07-31,NA,NA,2262,104,62,307,"" +87,2012-08-01,NA,NA,2247,119,79,272,"" +88,2012-08-02,NA,NA,2345,182,36,315,"" +89,2012-08-03,NA,NA,2615,122,84,341,"" +90,2012-08-04,NA,NA,2494,129,72,347,"" +91,2012-08-05,NA,NA,NA,NA,NA,NA,"Restaurant" +92,2012-08-06,NA,NA,2503,131,72,352,"" +93,2012-08-07,NA,NA,2200,195,23,353,"" +94,2012-08-08,NA,NA,2170,164,40,284,"" +95,2012-08-09,NA,NA,2278,155,56,283,"" +96,2012-08-10,NA,NA,NA,NA,NA,NA,"VisitOf" +97,2012-08-11,NA,NA,NA,NA,NA,NA,"Holiday" +98,2012-08-12,NA,NA,NA,NA,NA,NA,"Holiday" +99,2012-08-13,NA,NA,NA,NA,NA,NA,"Holiday" +100,2012-08-14,NA,NA,NA,NA,NA,NA,"Holiday" +101,2012-08-15,NA,NA,NA,NA,NA,NA,"Holiday" +102,2012-08-16,NA,NA,NA,NA,NA,NA,"Holiday" +103,2012-08-17,NA,NA,NA,NA,NA,NA,"Holiday" +104,2012-08-18,NA,NA,NA,NA,NA,NA,"Holiday" +105,2012-08-19,NA,NA,NA,NA,NA,NA,"Holiday" +106,2012-08-20,NA,NA,NA,NA,NA,NA,"Holiday" +107,2012-08-21,NA,NA,NA,NA,NA,NA,"Holiday" +108,2012-08-22,NA,NA,NA,NA,NA,NA,"Holiday" +109,2012-08-23,NA,NA,NA,NA,NA,NA,"Holiday" +110,2012-08-24,NA,NA,NA,NA,NA,NA,"Holiday" +111,2012-08-25,NA,NA,2351,123,74,293,"" +112,2012-08-26,NA,NA,2271,119,95,228,"" +113,2012-08-27,NA,NA,2581,143,60,361,"" +114,2012-08-28,NA,NA,2335,162,62,263,"" +115,2012-08-29,NA,NA,NA,NA,NA,NA,"Other" +116,2012-08-30,NA,NA,1945,131,42,250,"" +117,2012-08-31,NA,NA,NA,NA,NA,NA,"" +118,2012-09-01,NA,NA,2849,170,104,301,"" +119,2012-09-02,NA,NA,2027,115,83,198,"" +120,2012-09-03,NA,NA,1773,81,48,247,"" +121,2012-09-04,NA,NA,NA,NA,NA,NA,"VisitTo" +122,2012-09-05,NA,NA,1881,88,40,265,"" +123,2012-09-06,NA,91.4,2090,115,52,249,"" +124,2012-09-07,NA,NA,2341,108,82,285,"" +125,2012-09-08,NA,92.2,2468,128,83,295,"" +126,2012-09-09,NA,92.6,2010,137,43,237,"" +127,2012-09-10,NA,NA,2048,118,48,275,"" +128,2012-09-11,NA,92,2285,110,58,324,"" +129,2012-09-12,NA,91.7,1958,127,50,244,"" +130,2012-09-13,NA,91.4,NA,NA,NA,NA,"Holiday" +131,2012-09-14,NA,NA,NA,NA,NA,NA,"Holiday" +132,2012-09-15,NA,NA,NA,NA,NA,NA,"Holiday" +133,2012-09-16,NA,NA,NA,NA,NA,NA,"Holiday" +134,2012-09-17,NA,NA,NA,NA,NA,NA,"Holiday" +135,2012-09-18,NA,NA,NA,NA,NA,NA,"Holiday" +136,2012-09-19,NA,NA,NA,NA,NA,NA,"Holiday" +137,2012-09-20,NA,NA,NA,NA,NA,NA,"Holiday" +138,2012-09-21,NA,NA,NA,NA,NA,NA,"Holiday" +139,2012-09-22,NA,NA,NA,NA,NA,NA,"Holiday" +140,2012-09-23,NA,NA,NA,NA,NA,NA,"Holiday" +141,2012-09-24,NA,NA,NA,NA,NA,NA,"Holiday" +142,2012-09-25,NA,NA,NA,NA,NA,NA,"Holiday" +143,2012-09-26,NA,NA,NA,NA,NA,NA,"Holiday" +144,2012-09-27,NA,NA,NA,NA,NA,NA,"Holiday" +145,2012-09-28,NA,NA,NA,NA,NA,NA,"Holiday" +146,2012-09-29,NA,NA,NA,NA,NA,NA,"Holiday" +147,2012-09-30,NA,NA,NA,NA,NA,NA,"Holiday" +148,2012-10-01,NA,93.6,2082,86,85,237,"" +149,2012-10-02,NA,94,2131,132,48,293,"" +150,2012-10-03,NA,93.3,1976,93,46,294,"" +151,2012-10-04,NA,93.2,2221,187,69,205,"" +152,2012-10-05,NA,NA,NA,NA,NA,NA,"Funeral" +153,2012-10-06,NA,93.3,2142,150,41,288,"" +154,2012-10-07,NA,93.3,2152,120,43,314,"" +155,2012-10-08,NA,94,2563,167,77,282,"" +156,2012-10-09,NA,92.3,2218,102,37,349,"" +157,2012-10-10,NA,92.1,2376,109,72,315,"" +158,2012-10-11,NA,93.1,2163,110,52,298,"" +159,2012-10-12,NA,NA,2250,104,55,325,"" +160,2012-10-13,NA,NA,2496,80,68,371,"" +161,2012-10-14,NA,91.9,NA,NA,NA,NA,"VisitTo" +162,2012-10-15,NA,NA,NA,NA,NA,NA,"VisitTo" +163,2012-10-16,NA,NA,NA,NA,NA,NA,"VisitTo" +164,2012-10-17,NA,NA,NA,NA,NA,NA,"VisitTo" +165,2012-10-18,NA,NA,NA,NA,NA,NA,"VisitTo" +166,2012-10-19,NA,NA,NA,NA,NA,NA,"VisitTo" +167,2012-10-20,NA,94.2,NA,NA,NA,NA,"Restaurant" +168,2012-10-21,NA,94.1,2050,118,98,163,"" +169,2012-10-22,NA,93.5,2578,147,52,370,"" +170,2012-10-23,NA,NA,NA,NA,NA,NA,"VisitOf" +171,2012-10-24,NA,NA,NA,NA,NA,NA,"OperationAtHospital" +172,2012-10-25,NA,NA,NA,NA,NA,NA,"OperationAtHospital" +173,2012-10-26,NA,NA,NA,NA,NA,NA,"OperationAtHospital" +174,2012-10-27,NA,NA,NA,NA,NA,NA,"OperationAtHospital" +175,2012-10-28,NA,NA,NA,NA,NA,NA,"OperationAtHospital" +176,2012-10-29,NA,92,1820,84,39,276,"" +177,2012-10-30,NA,92.2,1968,109,47,269,"" +178,2012-10-31,NA,91.4,2368,94,53,370,"" +179,2012-11-01,NA,91.8,1953,89,63,276,"" +180,2012-11-02,NA,92.1,1897,95,40,277,"" +181,2012-11-03,NA,92.2,NA,NA,NA,NA,"Restaurant" +182,2012-11-04,NA,92.2,2353,101,57,340,"" +183,2012-11-05,NA,NA,2201,93,47,327,"" +184,2012-11-06,NA,NA,2387,159,59,300,"" +185,2012-11-07,NA,NA,2106,87,30,370,"" +186,2012-11-08,NA,NA,1914,78,30,328,"" +187,2012-11-09,NA,NA,2311,106,38,374,"" +188,2012-11-10,NA,91.5,1811,96,51,212,"" +189,2012-11-11,NA,91.2,2257,125,45,332,"" +190,2012-11-12,NA,91.4,NA,NA,NA,NA,"ComputerFailure" +191,2012-11-13,NA,NA,2297,121,44,343,"" +192,2012-11-14,NA,NA,NA,NA,NA,NA,"Lazy" +193,2012-11-15,NA,91.6,NA,NA,NA,NA,"VisitTo" +194,2012-11-16,NA,91.8,2390,146,77,257,"" +195,2012-11-17,NA,NA,2236,104,67,289,"" +196,2012-11-18,NA,NA,2174,102,63,292,"" +197,2012-11-19,NA,NA,2359,148,33,311,"" +198,2012-11-20,NA,91.5,2648,115,68,388,"" +199,2012-11-21,NA,91,3316,111,78,538,"" +200,2012-11-22,NA,NA,NA,NA,NA,NA,"VisitTo" +201,2012-11-23,NA,NA,2154,81,70,293,"" +202,2012-11-24,NA,NA,2452,133,81,295,"" +203,2012-11-25,NA,NA,2488,97,115,262,"" +204,2012-11-26,NA,91.4,2314,128,42,335,"" +205,2012-11-27,NA,91,2164,100,39,347,"" +206,2012-11-28,NA,91.1,2226,91,43,320,"" +207,2012-11-29,NA,90.9,NA,NA,NA,NA,"VisitOf" +208,2012-11-30,NA,NA,NA,NA,NA,NA,"VisitOf" +209,2012-12-01,NA,NA,2826,129,90,367,"" +210,2012-12-02,NA,NA,2197,137,51,295,"" +211,2012-12-03,NA,90.8,2547,151,58,346,"" +212,2012-12-04,NA,NA,2268,104,54,324,"" +213,2012-12-05,NA,91.2,2473,146,65,317,"" +214,2012-12-06,NA,91.2,2456,97,71,341,"" +215,2012-12-07,NA,NA,NA,NA,NA,NA,"VisitTo" +216,2012-12-08,NA,92.6,2678,95,94,355,"" +217,2012-12-09,NA,92.4,NA,NA,NA,NA,"Restaurant" +218,2012-12-10,NA,93,2105,116,36,320,"" +219,2012-12-11,NA,92.1,2041,137,33,289,"" +220,2012-12-12,NA,91.3,2607,99,68,386,"" +221,2012-12-13,NA,92,2305,107,82,289,"" +222,2012-12-14,NA,NA,2291,157,76,225,"" +223,2012-12-15,NA,92,2844,88,64,468,"" +224,2012-12-16,NA,91.9,2583,85,75,384,"" +225,2012-12-17,NA,91.1,3023,164,85,382,"" +226,2012-12-18,NA,NA,2138,80,86,249,"" +227,2012-12-19,NA,91.8,3135,135,88,437,"" +228,2012-12-20,NA,91.8,2328,123,43,354,"" +229,2012-12-21,NA,NA,NA,NA,NA,NA,"VisitOf" +230,2012-12-22,NA,91.6,2551,111,48,406,"" +231,2012-12-23,NA,92.6,NA,NA,NA,NA,"Holiday" +232,2012-12-24,NA,93.6,NA,NA,NA,NA,"Holiday" +233,2012-12-25,NA,NA,NA,NA,NA,NA,"Holiday" +234,2012-12-26,NA,92.4,NA,NA,NA,NA,"Holiday" +235,2012-12-27,NA,NA,NA,NA,NA,NA,"Holiday" +236,2012-12-28,NA,NA,NA,NA,NA,NA,"Holiday" +237,2012-12-29,NA,NA,NA,NA,NA,NA,"Holiday" +238,2012-12-30,NA,NA,NA,NA,NA,NA,"Holiday" +239,2012-12-31,NA,NA,NA,NA,NA,NA,"Holiday" +240,2013-01-01,NA,NA,NA,NA,NA,NA,"Holiday" +241,2013-01-02,NA,NA,NA,NA,NA,NA,"Holiday" +242,2013-01-03,NA,NA,NA,NA,NA,NA,"Holiday" +243,2013-01-04,NA,NA,NA,NA,NA,NA,"Holiday" +244,2013-01-05,NA,NA,NA,NA,NA,NA,"Holiday" +245,2013-01-06,NA,92.3,NA,NA,NA,NA,"" +246,2013-01-07,NA,93.2,2337,169,53,284,"" +247,2013-01-08,NA,NA,2668,123,62,395,"" +248,2013-01-09,NA,91.8,2418,127,55,338,"" +249,2013-01-10,NA,92.6,2891,101,72,444,"" +250,2013-01-11,NA,NA,2543,118,71,350,"" +251,2013-01-12,NA,NA,NA,NA,NA,NA,"Other" +252,2013-01-13,NA,NA,NA,NA,NA,NA,"Other" +253,2013-01-14,NA,NA,2349,147,80,260,"" +254,2013-01-15,NA,NA,2392,130,76,291,"" +255,2013-01-16,NA,NA,2239,91,69,308,"" +256,2013-01-17,NA,93.8,2560,124,72,337,"" +257,2013-01-18,NA,NA,2182,92,87,254,"" +258,2013-01-19,NA,91.8,2235,93,80,275,"" +259,2013-01-20,NA,92.4,2286,116,81,271,"" +260,2013-01-21,NA,NA,2854,150,88,362,"" +261,2013-01-22,NA,91.4,2342,121,45,348,"" +262,2013-01-23,NA,91.7,2239,132,64,281,"" +263,2013-01-24,NA,91.6,3149,104,69,519,"Funeral" +264,2013-01-25,NA,92.1,2275,151,82,223,"" +265,2013-01-26,NA,NA,2283,100,56,342,"" +266,2013-01-27,27.69,91.4,2866,82,93,431,"VisitTo" +267,2013-01-28,24.91,91.6,1959,116,39,281,"" +268,2013-01-29,29.38,NA,2900,178,92,337,"" +269,2013-01-30,35.24,NA,2215,97,33,377,"" +270,2013-01-31,26.27,NA,2250,95,33,387,"" +271,2013-02-01,23.85,NA,2266,80,71,314,"" +272,2013-02-02,NA,NA,NA,NA,NA,NA,"Restaurant" +273,2013-02-03,27.26,92.2,2862,134,104,335,"" +274,2013-02-04,24.36,92.2,2237,186,56,274,"" +275,2013-02-05,24.27,92,2228,135,49,299,"" +276,2013-02-06,29.48,91.7,2379,106,89,277,"" +277,2013-02-07,23.87,90.8,1967,107,25,321,"" +278,2013-02-08,20.9,NA,2054,79,55,305,"" +279,2013-02-09,27.94,90.2,2299,127,60,322,"" +280,2013-02-10,NA,90.5,NA,NA,NA,NA,"Other" +281,2013-02-11,22.43,91,2101,83,55,309,"" +282,2013-02-12,27.54,90.7,2363,122,46,355,"" +283,2013-02-13,25.03,90.9,2167,88,54,333,"" +284,2013-02-14,25.3,90.3,2278,88,89,269,"" +285,2013-02-15,30.88,90.5,2528,132,67,337,"" +286,2013-02-16,27.6,NA,2109,120,69,240,"" +287,2013-02-17,18.12,90.6,1877,109,51,240,"" +288,2013-02-18,26.23,NA,2373,113,76,303,"" +289,2013-02-19,28.29,89.7,2681,114,75,382,"" +290,2013-02-20,22.52,90.2,2151,86,56,333,"" +291,2013-02-21,26.01,90.4,2267,88,78,288,"" +292,2013-02-22,24.05,NA,2416,154,82,261,"" +293,2013-02-23,28.92,NA,2658,157,90,300,"" +294,2013-02-24,25.33,90.5,2370,116,60,319,"" +295,2013-02-25,27.65,90,2398,91,68,342,"" +296,2013-02-26,24.21,NA,2203,126,67,268,"" +297,2013-02-27,NA,NA,NA,NA,NA,NA,"VisitTo" +298,2013-02-28,NA,NA,NA,NA,NA,NA,"VisitTo" +299,2013-03-01,20.65,NA,2306,122,72,284,"" +300,2013-03-02,23.9,92.3,2463,130,82,292,"" +301,2013-03-03,22.21,91.6,2133,127,56,276,"" +302,2013-03-04,29.13,91.2,2350,104,67,327,"" +303,2013-03-05,27.4,90.1,2294,111,70,302,"" +304,2013-03-06,23.42,90.5,2126,91,51,318,"" +305,2013-03-07,24.32,90.1,2153,117,53,295,"" +306,2013-03-08,28.73,NA,2542,119,90,307,"" +307,2013-03-09,24.53,90.9,3029,117,125,356,"" +308,2013-03-10,NA,90.3,NA,NA,NA,NA,"Restaurant" +309,2013-03-11,26.45,91.6,2034,129,48,266,"" +310,2013-03-12,29.78,91.2,3109,180,109,344,"" +311,2013-03-13,23.82,90.5,2139,124,54,281,"" +312,2013-03-14,22.89,90,2748,134,74,377,"" +313,2013-03-15,26.42,90.2,2681,120,103,318,"" +314,2013-03-16,NA,90.6,NA,NA,NA,NA,"VisitOfFamily" +315,2013-03-17,NA,91.4,NA,NA,NA,NA,"VisitOfFamily" +316,2013-03-18,29.95,92.1,2224,97,39,366,"" +317,2013-03-19,34.63,NA,3129,133,64,500,"" +318,2013-03-20,20.08,91.3,2265,104,65,313,"" +319,2013-03-21,NA,90.5,NA,NA,NA,NA,"Restaurant" +320,2013-03-22,23.21,91.8,2307,119,83,269,"" +321,2013-03-23,NA,90.3,NA,NA,NA,NA,"VisitOf" +322,2013-03-24,NA,91.4,NA,NA,NA,NA,"VisitOf" +323,2013-03-25,25.26,91.4,2491,122,75,327,"" +324,2013-03-26,23.08,90.6,2485,95,47,402,"" +325,2013-03-27,27.71,91,2416,131,67,312,"" +326,2013-03-28,31.35,91.4,3029,156,82,413,"" +327,2013-03-29,25.21,89.8,1880,79,47,315,"" +328,2013-03-30,NA,NA,NA,NA,NA,NA,"Holiday" +329,2013-03-31,20.97,NA,2172,66,66,265,"Holiday" +330,2013-04-01,21.58,NA,2050,75,54,298,"Holiday" +331,2013-04-02,27.56,NA,2161,113,49,312,"Holiday" +332,2013-04-03,24.93,NA,2098,96,60,310,"Holiday" +333,2013-04-04,26.19,NA,2292,118,88,250,"Holiday" +334,2013-04-05,16.91,NA,1987,91,110,256,"Holiday" +335,2013-04-06,NA,NA,NA,NA,NA,NA,"Other" +336,2013-04-07,NA,NA,NA,NA,NA,NA,"Other" +337,2013-04-08,29.78,90.7,3600,138,83,566,"" +338,2013-04-09,30.94,90.5,2476,163,95,227,"" +339,2013-04-10,28.4,90.2,2799,135,107,254,"" +340,2013-04-11,26.34,90,2283,110,31,383,"" +341,2013-04-12,33.11,NA,3457,193,91,446,"" +342,2013-04-13,NA,NA,NA,NA,NA,NA,"VisitTo" +343,2013-04-14,21.54,91.9,2589,112,99,316,"" +344,2013-04-15,21.24,91.8,2092,135,56,258,"" +345,2013-04-16,24.33,91.1,2798,110,104,356,"" +346,2013-04-17,26.66,90.6,2339,124,50,341,"" +347,2013-04-18,42.18,NA,2667,102,68,407,"" +348,2013-04-19,32.87,91,3343,145,124,410,"" +349,2013-04-20,NA,90.7,NA,NA,NA,NA,"Restaurant" +350,2013-04-21,27.9,92.5,2205,126,60,284,"" +351,2013-04-22,NA,NA,NA,NA,NA,NA,"Restaurant" +352,2013-04-23,38.75,91.7,3545,190,90,483,"" +353,2013-04-24,13.57,90.9,1077,69,46,96,"Other" +354,2013-04-25,22.21,89.9,2396,66,85,288,"Other" +355,2013-04-26,NA,90.5,NA,NA,NA,NA,"VisitOfFamily" +356,2013-04-27,NA,91.7,NA,NA,NA,NA,"" +357,2013-04-28,NA,NA,NA,NA,NA,NA,"" +358,2013-04-29,NA,91.3,NA,NA,NA,NA,"" +359,2013-04-30,25.12,NA,2868,107,88,402,"" +360,2013-05-01,22.65,92,2404,203,107,228,"" +361,2013-05-02,NA,92.1,NA,NA,NA,NA,"" +362,2013-05-03,NA,NA,NA,NA,NA,NA,"" +363,2013-05-04,NA,92,NA,NA,NA,NA,"" +364,2013-05-05,NA,92.6,NA,NA,NA,NA,"" +365,2013-05-06,34.89,NA,2231,126,49,317,"" +366,2013-05-07,36.6,93.6,2447,98,87,313,"" +367,2013-05-08,27.67,92.8,2701,136,73,365,"" +368,2013-05-09,NA,92.4,NA,NA,NA,NA,"VisitTo" +369,2013-05-10,NA,NA,NA,NA,NA,NA,"VisitTo" +370,2013-05-11,NA,NA,NA,NA,NA,NA,"VisitTo" +371,2013-05-12,NA,NA,NA,NA,NA,NA,"VisitTo" +372,2013-05-13,22.07,93.5,2374,141,70,291,"" +373,2013-05-14,39.15,NA,3075,205,89,361,"" +374,2013-05-15,29.35,92.5,2231,83,62,331,"" +375,2013-05-16,30.89,92.6,3637,147,163,396,"" +376,2013-05-17,26.25,91.4,2444,108,73,334,"" +377,2013-05-18,NA,91.7,NA,NA,NA,NA,"VisitOf" +378,2013-05-19,NA,92,NA,NA,NA,NA,"VisitOf" +379,2013-05-20,NA,92.5,NA,NA,NA,NA,"VisitOf" +380,2013-05-21,28.68,NA,3166,160,77,444,"" +381,2013-05-22,32.27,92.1,2109,102,45,319,"" +382,2013-05-23,NA,92.6,NA,NA,NA,NA,"GetTogether" +383,2013-05-24,NA,NA,NA,NA,NA,NA,"" +384,2013-05-25,NA,NA,NA,NA,NA,NA,"VisitTo" +385,2013-05-26,NA,NA,NA,NA,NA,NA,"OnTravel" +386,2013-05-27,NA,92.5,NA,NA,NA,NA,"VisitOf" +387,2013-05-28,26.82,93.5,2331,126,50,343,"" +388,2013-05-29,21.93,93.1,2268,116,62,307,"" +389,2013-05-30,34.14,92.6,2700,136,85,342,"" +390,2013-05-31,35.38,92.4,2957,158,48,469,"" +391,2013-06-01,NA,92.9,NA,NA,NA,NA,"VisitOf" +392,2013-06-02,13.67,NA,2114,75,115,191,"" +393,2013-06-03,27.37,91.9,2297,124,57,314,"" +394,2013-06-04,35.21,91.2,2351,90,54,327,"" +395,2013-06-05,35.44,92,3290,135,111,430,"" +396,2013-06-06,33.83,91.2,2228,140,45,309,"" +397,2013-06-07,32.03,92.1,2217,95,65,306,"" +398,2013-06-08,NA,NA,NA,NA,NA,NA,"VisitTo" +399,2013-06-09,23.83,92.6,2134,122,62,264,"" +400,2013-06-10,23.15,91.9,2558,126,66,358,"" +401,2013-06-11,30.92,91.3,2107,156,43,270,"" +402,2013-06-12,30.31,91.4,2057,125,40,293,"" +403,2013-06-13,34.11,91.2,2151,119,33,341,"" +404,2013-06-14,NA,91.7,NA,NA,NA,NA,"VisitTo" +405,2013-06-15,28.95,NA,2418,160,47,311,"" +406,2013-06-16,NA,91.8,NA,NA,NA,NA,"VisitTo" +407,2013-06-17,31,92.6,2211,171,49,264,"" +408,2013-06-18,36.42,NA,2274,167,23,342,"" +409,2013-06-19,38.14,91.9,2274,137,33,346,"" +410,2013-06-20,NA,91.7,NA,NA,NA,NA,"VisitTo" +411,2013-06-21,NA,NA,NA,NA,NA,NA,"VisitTo" +412,2013-06-22,NA,NA,NA,NA,NA,NA,"GetTogether" +413,2013-06-23,NA,NA,NA,NA,NA,NA,"VisitTo" +414,2013-06-24,26.52,92.6,2165,169,65,215,"" +415,2013-06-25,27.39,93.4,2579,159,57,346,"" +416,2013-06-26,NA,93.6,NA,NA,NA,NA,"VisitTo" +417,2013-06-27,26.34,93.6,2375,162,42,327,"" +418,2013-06-28,33.96,91.6,2666,176,78,305,"" +419,2013-06-29,26.26,92.1,2290,189,60,241,"" +420,2013-06-30,23.59,92,2235,128,76,248,"" +421,2013-07-01,27.55,91.6,2351,145,49,328,"" +422,2013-07-02,28.25,NA,2398,139,74,286,"" +423,2013-07-03,28.31,92.4,2601,159,70,322,"" +424,2013-07-04,NA,NA,NA,NA,NA,NA,"GetTogether" +425,2013-07-05,NA,NA,NA,NA,NA,NA,"GetTogether" +426,2013-07-06,NA,NA,NA,NA,NA,NA,"GetTogether" +427,2013-07-07,NA,93.7,NA,NA,NA,NA,"" +428,2013-07-08,27.41,93.6,2284,116,86,244,"" +429,2013-07-09,NA,94.6,NA,NA,NA,NA,"VisitOf" +430,2013-07-10,NA,94.6,NA,NA,NA,NA,"VisitOf" +431,2013-07-11,NA,NA,NA,NA,NA,NA,"VisitOf" +432,2013-07-12,NA,NA,NA,NA,NA,NA,"VisitOf" +433,2013-07-13,NA,NA,NA,NA,NA,NA,"VisitOf" +434,2013-07-14,NA,NA,NA,NA,NA,NA,"VisitOf" +435,2013-07-15,NA,NA,NA,NA,NA,NA,"VisitOf" +436,2013-07-16,NA,NA,NA,NA,NA,NA,"VisitOf" +437,2013-07-17,NA,NA,NA,NA,NA,NA,"VisitOf" +438,2013-07-18,NA,NA,NA,NA,NA,NA,"VisitOf" +439,2013-07-19,NA,NA,NA,NA,NA,NA,"VisitOf" +440,2013-07-20,NA,NA,NA,NA,NA,NA,"VisitOf" +441,2013-07-21,23.7,NA,2179,148,62,247,"" +442,2013-07-22,26.38,94.5,2176,158,53,264,"" +443,2013-07-23,39.64,93.3,2126,162,47,253,"" +444,2013-07-24,23.71,93.5,2040,150,71,197,"" +445,2013-07-25,31.75,91.9,2105,163,30,293,"" +446,2013-07-26,38.24,92.5,2217,125,78,272,"" +447,2013-07-27,NA,93.1,NA,NA,NA,NA,"" +448,2013-07-28,NA,NA,NA,NA,NA,NA,"Holiday" +449,2013-07-29,NA,NA,NA,NA,NA,NA,"Holiday" +450,2013-07-30,NA,NA,NA,NA,NA,NA,"Holiday" +451,2013-07-31,NA,NA,NA,NA,NA,NA,"Holiday" +452,2013-08-01,NA,NA,NA,NA,NA,NA,"Holiday" +453,2013-08-02,NA,NA,NA,NA,NA,NA,"Holiday" +454,2013-08-03,NA,NA,NA,NA,NA,NA,"Holiday" +455,2013-08-04,NA,NA,NA,NA,NA,NA,"Holiday" +456,2013-08-05,NA,NA,NA,NA,NA,NA,"Holiday" +457,2013-08-06,NA,NA,NA,NA,NA,NA,"Holiday" +458,2013-08-07,NA,NA,NA,NA,NA,NA,"Holiday" +459,2013-08-08,NA,NA,NA,NA,NA,NA,"Holiday" +460,2013-08-09,NA,NA,NA,NA,NA,NA,"Holiday" +461,2013-08-10,NA,NA,NA,NA,NA,NA,"Holiday" +462,2013-08-11,NA,NA,NA,NA,NA,NA,"Holiday" +463,2013-08-12,NA,NA,NA,NA,NA,NA,"Holiday" +464,2013-08-13,NA,NA,NA,NA,NA,NA,"Holiday" +465,2013-08-14,NA,NA,NA,NA,NA,NA,"Holiday" +466,2013-08-15,NA,NA,NA,NA,NA,NA,"Holiday" +467,2013-08-16,NA,NA,NA,NA,NA,NA,"Holiday" +468,2013-08-17,NA,NA,NA,NA,NA,NA,"Holiday" +469,2013-08-18,NA,NA,NA,NA,NA,NA,"Holiday" +470,2013-08-19,NA,NA,NA,NA,NA,NA,"Holiday" +471,2013-08-20,NA,NA,NA,NA,NA,NA,"Holiday" +472,2013-08-21,NA,NA,NA,NA,NA,NA,"Holiday" +473,2013-08-22,NA,NA,NA,NA,NA,NA,"Holiday" +474,2013-08-23,NA,NA,NA,NA,NA,NA,"Holiday" +475,2013-08-24,NA,NA,NA,NA,NA,NA,"Holiday" +476,2013-08-25,NA,NA,NA,NA,NA,NA,"Holiday" +477,2013-08-26,23.54,96.3,2024,175,34,249,"" +478,2013-08-27,23.4,96.6,2042,150,27,296,"" +479,2013-08-28,28.15,96.5,2190,152,52,282,"" +480,2013-08-29,25.38,95,1972,147,70,189,"" +481,2013-08-30,19.62,94.7,2044,132,65,229,"" +482,2013-08-31,NA,94.8,NA,NA,NA,NA,"" +483,2013-09-01,NA,NA,NA,NA,NA,NA,"VisitOf" +484,2013-09-02,NA,NA,NA,NA,NA,NA,"VisitOf" +485,2013-09-03,NA,NA,NA,NA,NA,NA,"VisitOf" +486,2013-09-04,NA,NA,NA,NA,NA,NA,"VisitOf" +487,2013-09-05,21.62,96.1,2306,168,79,227,"" +488,2013-09-06,22.09,95.9,2109,148,59,241,"" +489,2013-09-07,24.26,NA,2386,155,64,275,"" +490,2013-09-08,17.56,NA,2241,82,117,214,"" +491,2013-09-09,NA,94.6,NA,NA,NA,NA,"VisitTo" +492,2013-09-10,NA,94.6,NA,NA,NA,NA,"VisitOf" +493,2013-09-11,18.3,95.5,2023,195,39,222,"" +494,2013-09-12,NA,NA,NA,NA,NA,NA,"VisitOf" +495,2013-09-13,23.6,95.2,2113,150,44,275,"" +496,2013-09-14,25.96,94.9,2451,171,83,269,"" +497,2013-09-15,NA,NA,NA,NA,NA,NA,"VisitOf" +498,2013-09-16,24.99,96.1,2523,129,40,407,"" +499,2013-09-17,27.52,96,2138,164,28,303,"" +500,2013-09-18,31.6,95.3,2272,178,45,287,"" +501,2013-09-19,26.88,94.6,2194,112,71,268,"" +502,2013-09-20,NA,NA,NA,NA,NA,NA,"VisitTo" +503,2013-09-21,NA,NA,NA,NA,NA,NA,"VisitTo" +504,2013-09-22,NA,NA,NA,NA,NA,NA,"VisitTo" +505,2013-09-23,29.85,NA,2443,161,59,314,"" +506,2013-09-24,NA,NA,NA,NA,NA,NA,"VisitOf" +507,2013-09-25,NA,NA,NA,NA,NA,NA,"VisitOf" +508,2013-09-26,27.63,NA,3092,198,101,334,"" +509,2013-09-27,21.81,NA,2238,150,55,270,"" +510,2013-09-28,NA,NA,NA,NA,NA,NA,"VisitTo" +511,2013-09-29,NA,NA,NA,NA,NA,NA,"VisitTo" +512,2013-09-30,30.49,NA,2385,150,73,278,"" +513,2013-10-01,NA,NA,NA,NA,NA,NA,"OnTravel" +514,2013-10-02,NA,NA,NA,NA,NA,NA,"Holiday" +515,2013-10-03,NA,NA,NA,NA,NA,NA,"Holiday" +516,2013-10-04,NA,NA,NA,NA,NA,NA,"Holiday" +517,2013-10-05,NA,NA,NA,NA,NA,NA,"Holiday" +518,2013-10-06,NA,NA,NA,NA,NA,NA,"Holiday" +519,2013-10-07,20.64,96.5,2585,105,99,328,"" +520,2013-10-08,26.51,97.1,2843,161,76,385,"" +521,2013-10-09,27.77,96.1,2575,252,62,249,"" +522,2013-10-10,29.9,95.7,2218,156,45,286,"" +523,2013-10-11,30.11,95.1,2262,179,49,259,"" +524,2013-10-12,27.48,94.8,2725,182,20,448,"" +525,2013-10-13,28.42,94.3,2116,159,40,272,"" +526,2013-10-14,34.2,94.7,2359,170,27,350,"" +527,2013-10-15,29.17,94.7,2198,177,44,271,"" +528,2013-10-16,28.06,95.1,2979,189,84,357,"" +529,2013-10-17,28.5,94.2,2165,163,76,202,"" +530,2013-10-18,27.36,94.7,2275,158,54,275,"" +531,2013-10-19,NA,NA,NA,NA,NA,NA,"VisitTo" +532,2013-10-20,NA,NA,NA,NA,NA,NA,"GetTogether" +533,2013-10-21,NA,NA,NA,NA,NA,NA,"Funeral" +534,2013-10-22,21.73,NA,2485,172,93,237,"" +535,2013-10-23,26.05,NA,2297,140,62,281,"" +536,2013-10-24,25.52,95.1,2214,193,60,222,"" +537,2013-10-25,21.5,NA,2375,182,62,268,"" +538,2013-10-26,NA,NA,NA,NA,NA,NA,"VisitTo" +539,2013-10-27,NA,NA,NA,NA,NA,NA,"VisitTo" +540,2013-10-28,22.84,96.1,2501,185,67,290,"" +541,2013-10-29,27.41,95.6,2697,183,82,323,"" +542,2013-10-30,26.17,NA,2326,181,45,295,"" +543,2013-10-31,27.75,NA,2022,147,50,299,"" +544,2013-11-01,25.2,NA,2311,152,45,319,"" +545,2013-11-02,24.21,NA,2802,125,112,336,"" +546,2013-11-03,26.38,NA,2923,137,83,420,"" +547,2013-11-04,20.74,95.2,2091,150,55,254,"" +548,2013-11-05,32.72,95.1,2342,183,30,326,"" +549,2013-11-06,29.21,94.3,2037,156,26,290,"" +550,2013-11-07,27.72,NA,2082,111,69,251,"" +551,2013-11-08,25.76,93.7,2213,150,56,273,"" +552,2013-11-09,NA,94.7,NA,NA,NA,NA,"VisitOf" +553,2013-11-10,NA,NA,NA,NA,NA,NA,"VisitOf" +554,2013-11-11,NA,NA,NA,NA,NA,NA,"VisitOf" +555,2013-11-12,NA,94.4,NA,NA,NA,NA,"VisitOf" +556,2013-11-13,NA,NA,NA,NA,NA,NA,"VisitOf" +557,2013-11-14,19.07,95.9,1979,185,70,145,"" +558,2013-11-15,NA,NA,NA,NA,NA,NA,"VisitTo" +559,2013-11-16,NA,NA,NA,NA,NA,NA,"VisitTo" +560,2013-11-17,24.65,96.3,2731,98,151,241,"" +561,2013-11-18,23.62,NA,2213,171,58,249,"" +562,2013-11-19,27.75,NA,2472,175,39,351,"" +563,2013-11-20,36.34,95.2,2517,159,57,339,"" +564,2013-11-21,NA,94.8,NA,NA,NA,NA,"VisitTo" +565,2013-11-22,24.31,94.6,2050,164,37,260,"" +566,2013-11-23,NA,94.4,NA,NA,NA,NA,"Alone" +567,2013-11-24,25.14,NA,2264,155,65,263,"" +568,2013-11-25,26.33,94.4,2565,175,75,291,"" +569,2013-11-26,28.81,94.5,2362,89,86,305,"" +570,2013-11-27,25.79,94.9,2263,179,61,237,"" +571,2013-11-28,34.78,93.9,2688,224,55,314,"" +572,2013-11-29,NA,94.4,NA,NA,NA,NA,"VisitTo" +573,2013-11-30,NA,NA,NA,NA,NA,NA,"VisitTo" +574,2013-12-01,NA,NA,NA,NA,NA,NA,"VisitTo" +575,2013-12-02,NA,NA,NA,NA,NA,NA,"VisitTo" +576,2013-12-03,NA,NA,NA,NA,NA,NA,"VisitOf" +577,2013-12-04,NA,NA,NA,NA,NA,NA,"VisitOf" +578,2013-12-05,NA,NA,NA,NA,NA,NA,"VisitOf" +579,2013-12-06,NA,NA,NA,NA,NA,NA,"VisitOf" +580,2013-12-07,23.24,96.2,2258,132,73,243,"" +581,2013-12-08,28.07,NA,2887,155,119,298,"" +582,2013-12-09,26.92,NA,2392,173,67,270,"" +583,2013-12-10,29.45,95.6,2176,161,52,259,"" +584,2013-12-11,27.84,95,2366,162,50,305,"" +585,2013-12-12,28.51,93.9,2072,169,51,229,"" +586,2013-12-13,25.4,94.1,2350,150,56,305,"" +587,2013-12-14,NA,NA,NA,NA,NA,NA,"VisitOf" +588,2013-12-15,27.27,95.1,2414,167,80,254,"" +589,2013-12-16,23.19,95.4,2294,157,58,283,"" +590,2013-12-17,NA,NA,NA,NA,NA,NA,"" +591,2013-12-18,21.59,NA,2430,155,82,266,"" +592,2013-12-19,26.49,95,2185,163,54,260,"" +593,2013-12-20,20.75,NA,2995,50,141,387,"Holiday" +594,2013-12-21,NA,NA,NA,NA,NA,NA,"Holiday" +595,2013-12-22,NA,NA,NA,NA,NA,NA,"Holiday" +596,2013-12-23,NA,NA,NA,NA,NA,NA,"Holiday" +597,2013-12-24,NA,NA,NA,NA,NA,NA,"Holiday" +598,2013-12-25,NA,NA,NA,NA,NA,NA,"Holiday" +599,2013-12-26,NA,NA,NA,NA,NA,NA,"Holiday" +600,2013-12-27,NA,NA,NA,NA,NA,NA,"Holiday" +601,2013-12-28,NA,NA,NA,NA,NA,NA,"Holiday" +602,2013-12-29,NA,NA,NA,NA,NA,NA,"Holiday" +603,2013-12-30,NA,NA,NA,NA,NA,NA,"Holiday" +604,2013-12-31,NA,NA,NA,NA,NA,NA,"Holiday" +605,2014-01-01,NA,NA,NA,NA,NA,NA,"Holiday" +606,2014-01-02,NA,NA,NA,NA,NA,NA,"Holiday" +607,2014-01-03,NA,NA,NA,NA,NA,NA,"Holiday" +608,2014-01-04,NA,NA,NA,NA,NA,NA,"Holiday" +609,2014-01-05,20.75,96,2995,50,141,387,"" +610,2014-01-06,NA,NA,NA,NA,NA,NA,"" +611,2014-01-07,26.03,NA,2660,158,79,310,"" +612,2014-01-08,30.22,NA,2284,164,60,242,"" +613,2014-01-09,23.39,NA,2291,215,67,199,"" +614,2014-01-10,25.8,96.3,2431,149,54,326,"" +615,2014-01-11,26.13,95.8,2209,178,71,210,"" +616,2014-01-12,NA,95.7,NA,NA,NA,NA,"Restaurant" +617,2014-01-13,35.23,97.5,2613,154,61,352,"" +618,2014-01-14,22.57,NA,2325,166,81,223,"" +619,2014-01-15,21.34,NA,2187,142,89,217,"" +620,2014-01-16,27.86,95.9,2129,152,47,259,"" +621,2014-01-17,23.19,95.9,2312,189,73,227,"" +622,2014-01-18,NA,NA,NA,NA,NA,NA,"" +623,2014-01-19,NA,NA,NA,NA,NA,NA,"" +624,2014-01-20,26.81,NA,2362,171,68,269,"" +625,2014-01-21,29.25,NA,2217,180,47,272,"" +626,2014-01-22,27.13,NA,2258,154,42,315,"" +627,2014-01-23,NA,95.3,NA,NA,NA,NA,"VisitOfAndVisitTo" +628,2014-01-24,23.04,96.3,2325,113,88,245,"" +629,2014-01-25,NA,96.6,NA,NA,NA,NA,"Restaurant" +630,2014-01-26,20.11,96.1,2262,168,81,210,"" +631,2014-01-27,29.39,96.2,2311,143,52,303,"" +632,2014-01-28,21.91,95.4,2171,155,54,279,"" +633,2014-01-29,26.06,95.4,2091,187,52,211,"" +634,2014-01-30,26.27,NA,2182,168,62,248,"" +635,2014-01-31,NA,95.6,NA,NA,NA,NA,"VisitOfFamily" +636,2014-02-01,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +637,2014-02-02,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +638,2014-02-03,26.11,NA,2108,155,45,252,"" +639,2014-02-04,28.67,NA,2491,143,88,259,"" +640,2014-02-05,17.7,95.9,2006,151,52,219,"" +641,2014-02-06,23.11,95.1,2018,155,73,178,"" +642,2014-02-07,NA,NA,NA,NA,NA,NA,"Funeral" +643,2014-02-08,NA,94.7,NA,NA,NA,NA,"VisitOf" +644,2014-02-09,NA,95.2,NA,NA,NA,NA,"VisitOf" +645,2014-02-10,27.31,96.7,2105,121,53,303,"" +646,2014-02-11,19.71,NA,2255,163,53,286,"" +647,2014-02-12,25.96,95,2068,169,51,247,"" +648,2014-02-13,26.82,94.7,1990,172,43,214,"" +649,2014-02-14,24.06,NA,2145,145,86,208,"" +650,2014-02-15,NA,94.4,NA,NA,NA,NA,"Restaurant" +651,2014-02-16,NA,95.2,NA,NA,NA,NA,"VisitOfFamily" +652,2014-02-17,NA,NA,2145,139,54,271,"" +653,2014-02-18,20.23,95,2040,166,55,210,"" +654,2014-02-19,21.51,NA,2589,153,117,243,"" +655,2014-02-20,NA,95.1,NA,NA,NA,NA,"VisitTo" +656,2014-02-21,23.83,96.2,2182,136,73,235,"" +657,2014-02-22,24.06,NA,2212,116,64,286,"" +658,2014-02-23,22.26,96.5,2140,130,56,243,"" +659,2014-02-24,NA,95,NA,NA,NA,NA,"" +660,2014-02-25,24.34,95.6,2258,167,55,267,"" +661,2014-02-26,NA,NA,NA,NA,NA,NA,"Holiday" +662,2014-02-27,NA,NA,NA,NA,NA,NA,"Holiday" +663,2014-02-28,NA,NA,NA,NA,NA,NA,"Holiday" +664,2014-03-01,NA,NA,NA,NA,NA,NA,"Holiday" +665,2014-03-02,NA,NA,NA,NA,NA,NA,"Holiday" +666,2014-03-03,24.92,96.5,1903,134,65,204,"" +667,2014-03-04,39.11,96.9,2740,166,57,385,"" +668,2014-03-05,21.19,96.2,2220,147,75,231,"" +669,2014-03-06,25.12,NA,2196,167,35,279,"" +670,2014-03-07,25.26,NA,2199,124,36,331,"" +671,2014-03-08,NA,95.1,NA,NA,NA,NA,"VisitOfFamily" +672,2014-03-09,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +673,2014-03-10,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +674,2014-03-11,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +675,2014-03-12,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +676,2014-03-13,17.82,96.6,2032,153,67,193,"" +677,2014-03-14,23.63,96.1,2645,140,128,230,"" +678,2014-03-15,17.98,NA,2613,114,64,394,"" +679,2014-03-16,NA,95,NA,NA,NA,NA,"VisitTo" +680,2014-03-17,NA,NA,NA,NA,NA,NA,"VisitTo" +681,2014-03-18,NA,NA,NA,NA,NA,NA,"VisitTo" +682,2014-03-19,NA,NA,NA,NA,NA,NA,"VisitTo" +683,2014-03-20,16.51,NA,1519,97,29,215,"" +684,2014-03-21,23.19,96.5,2658,86,140,255,"" +685,2014-03-22,NA,NA,NA,NA,NA,NA,"VisitOf" +686,2014-03-23,NA,NA,NA,NA,NA,NA,"VisitOf" +687,2014-03-24,NA,NA,NA,NA,NA,NA,"VisitOf" +688,2014-03-25,NA,NA,NA,NA,NA,NA,"VisitOf" +689,2014-03-26,NA,NA,NA,NA,NA,NA,"VisitOf" +690,2014-03-27,23.53,NA,1914,131,49,230,"" +691,2014-03-28,21.82,96.6,2146,138,57,260,"" +692,2014-03-29,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +693,2014-03-30,NA,96.6,NA,NA,NA,NA,"VisitOfFamily" +694,2014-03-31,17.15,NA,2048,132,58,253,"" +695,2014-04-01,31,96,2083,167,63,206,"" +696,2014-04-02,27.09,95.5,2076,204,38,219,"" +697,2014-04-03,27.79,94.9,1986,196,48,181,"" +698,2014-04-04,29.01,94.8,2024,158,29,273,"" +699,2014-04-05,22.78,94.7,2031,153,52,230,"" +700,2014-04-06,23.94,NA,2041,165,37,248,"" +701,2014-04-07,29.82,95.6,2164,148,47,284,"" +702,2014-04-08,27.76,94.7,1956,187,56,172,"" +703,2014-04-09,33.89,93.8,2006,130,34,282,"" +704,2014-04-10,26.86,93.9,2106,158,66,215,"" +705,2014-04-11,30.84,94,2138,157,47,267,"" +706,2014-04-12,24.82,93.5,1983,141,55,222,"" +707,2014-04-13,22.07,93.7,2047,146,67,202,"" +708,2014-04-14,29.06,NA,2281,183,32,297,"" +709,2014-04-15,26.11,92.7,2360,151,72,232,"" +710,2014-04-16,34,93.8,2065,177,36,229,"" +711,2014-04-17,31.01,93.6,2074,170,25,287,"" +712,2014-04-18,26.32,93.4,2199,212,47,214,"" +713,2014-04-19,NA,93.2,NA,NA,NA,NA,"GetTogether" +714,2014-04-20,NA,NA,NA,NA,NA,NA,"GetTogether" +715,2014-04-21,NA,NA,NA,NA,NA,NA,"GetTogether" +716,2014-04-22,NA,94,NA,NA,NA,NA,"Restaurant" +717,2014-04-23,16.44,95.4,2159,152,86,190,"" +718,2014-04-24,27.02,94.4,2226,152,46,275,"" +719,2014-04-25,24.53,94.3,2235,143,73,245,"" +720,2014-04-26,NA,NA,NA,NA,NA,NA,"Restaurant" +721,2014-04-27,NA,94,NA,NA,NA,NA,"VisitOf" +722,2014-04-28,24.03,94.6,2209,162,91,176,"" +723,2014-04-29,NA,93.7,NA,NA,NA,NA,"VisitTo" +724,2014-04-30,NA,NA,NA,NA,NA,NA,"VisitOf" +725,2014-05-01,NA,95.5,NA,NA,NA,NA,"VisitOf" +726,2014-05-02,NA,95.4,NA,NA,NA,NA,"VisitOf" +727,2014-05-03,26.24,95.5,2174,151,87,189,"" +728,2014-05-04,NA,95.4,NA,NA,NA,NA,"VisitTo" +729,2014-05-05,24.36,95.1,2087,194,34,244,"" +730,2014-05-06,28.28,95.1,2191,158,62,240,"" +731,2014-05-07,17.6,94.4,2072,135,62,231,"" +732,2014-05-08,20.78,94.2,2095,134,59,247,"" +733,2014-05-09,NA,93.6,NA,NA,NA,NA,"Restaurant" +734,2014-05-10,24.02,94.4,1843,158,28,243,"" +735,2014-05-11,20.86,93.8,1853,166,45,187,"" +736,2014-05-12,26.64,93.5,2227,168,57,251,"" +737,2014-05-13,28.5,93.1,2659,194,102,232,"" +738,2014-05-14,NA,93.7,NA,NA,NA,NA,"GetTogether" +739,2014-05-15,NA,NA,NA,NA,NA,NA,"GetTogether" +740,2014-05-16,21.96,NA,2790,121,109,293,"" +741,2014-05-17,30.78,95.2,2530,140,86,305,"" +742,2014-05-18,NA,95.1,NA,NA,NA,NA,"VisitOfFamily" +743,2014-05-19,26.28,NA,2137,168,41,264,"" +744,2014-05-20,25.18,NA,2042,158,48,233,"" +745,2014-05-21,28.65,94.7,2219,188,79,185,"" +746,2014-05-22,26.91,93.5,1814,148,59,170,"" +747,2014-05-23,21.01,93.8,2292,170,64,252,"" +748,2014-05-24,NA,92.8,NA,NA,NA,NA,"VisitOfFamily" +749,2014-05-25,NA,93.5,NA,NA,NA,NA,"VisitOfFamily" +750,2014-05-26,26.31,93.9,2186,175,82,179,"" +751,2014-05-27,23.7,NA,2181,137,79,222,"" +752,2014-05-28,NA,92.9,NA,NA,NA,NA,"Holiday" +753,2014-05-29,NA,NA,NA,NA,NA,NA,"Holiday" +754,2014-05-30,NA,NA,NA,NA,NA,NA,"Holiday" +755,2014-05-31,NA,NA,NA,NA,NA,NA,"Holiday" +756,2014-06-01,27.36,94.6,2268,162,77,225,"" +757,2014-06-02,NA,95,NA,NA,NA,NA,"Lazy" +758,2014-06-03,19.91,NA,1950,155,71,162,"" +759,2014-06-04,21.33,94,2073,206,63,166,"" +760,2014-06-05,25.72,94.4,1846,168,42,182,"" +761,2014-06-06,30.93,94.4,2230,161,60,256,"" +762,2014-06-07,NA,94,NA,NA,NA,NA,"VisitOfFamily" +763,2014-06-08,NA,94.1,NA,NA,NA,NA,"VisitOfFamily" +764,2014-06-09,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +765,2014-06-10,27.32,NA,1956,143,67,191,"" +766,2014-06-11,19.61,94.3,1904,77,87,242,"" +767,2014-06-12,NA,93.5,NA,NA,NA,NA,"VisitOf" +768,2014-06-13,NA,93.5,NA,NA,NA,NA,"VisitOf" +769,2014-06-14,NA,NA,NA,NA,NA,NA,"VisitOf" +770,2014-06-15,NA,NA,NA,NA,NA,NA,"VisitOf" +771,2014-06-16,18.88,94.6,1741,147,44,185,"" +772,2014-06-17,25.08,94.4,3246,178,144,363,"" +773,2014-06-18,22,NA,2625,145,68,350,"" +774,2014-06-19,NA,NA,NA,NA,NA,NA,"VisitOf" +775,2014-06-20,17.8,NA,2011,151,60,214,"" +776,2014-06-21,24.1,94.1,2362,112,83,287,"" +777,2014-06-22,NA,94,NA,NA,NA,NA,"" +778,2014-06-23,26.79,94.7,1667,143,30,205,"" +779,2014-06-24,NA,NA,NA,NA,NA,NA,"VisitOf" +780,2014-06-25,NA,NA,NA,NA,NA,NA,"VisitOf" +781,2014-06-26,NA,NA,NA,NA,NA,NA,"VisitOf" +782,2014-06-27,NA,95.4,NA,NA,NA,NA,"VisitOf" +783,2014-06-28,NA,NA,NA,NA,NA,NA,"VisitOf" +784,2014-06-29,NA,NA,NA,NA,NA,NA,"VisitOf" +785,2014-06-30,25.29,95.4,2299,181,56,263,"" +786,2014-07-01,30.79,94.7,1912,149,39,242,"" +787,2014-07-02,27.37,94.3,2065,190,57,196,"" +788,2014-07-03,34.66,94,2417,198,55,277,"" +789,2014-07-04,27.98,NA,2219,139,91,241,"" +790,2014-07-05,NA,NA,NA,NA,NA,NA,"Holiday" +791,2014-07-06,NA,NA,NA,NA,NA,NA,"Holiday" +792,2014-07-07,NA,NA,NA,NA,NA,NA,"Holiday" +793,2014-07-08,NA,NA,NA,NA,NA,NA,"Holiday" +794,2014-07-09,NA,NA,NA,NA,NA,NA,"Holiday" +795,2014-07-10,NA,NA,NA,NA,NA,NA,"Holiday" +796,2014-07-11,NA,NA,NA,NA,NA,NA,"Holiday" +797,2014-07-12,NA,NA,NA,NA,NA,NA,"Holiday" +798,2014-07-13,NA,NA,NA,NA,NA,NA,"Holiday" +799,2014-07-14,NA,NA,NA,NA,NA,NA,"Holiday" +800,2014-07-15,NA,NA,NA,NA,NA,NA,"Holiday" +801,2014-07-16,NA,NA,NA,NA,NA,NA,"Holiday" +802,2014-07-17,NA,NA,NA,NA,NA,NA,"Holiday" +803,2014-07-18,NA,NA,NA,NA,NA,NA,"Holiday" +804,2014-07-19,NA,NA,NA,NA,NA,NA,"Holiday" +805,2014-07-20,NA,98.2,NA,NA,NA,NA,"VisitTo" +806,2014-07-21,NA,99,NA,NA,NA,NA,"" +807,2014-07-22,23.11,98.6,1949,106,56,253,"" +808,2014-07-23,28.77,97.5,2355,193,78,223,"" +809,2014-07-24,24.75,NA,2030,163,45,248,"" +810,2014-07-25,26.54,97,2081,148,70,223,"" +811,2014-07-26,NA,96.6,NA,NA,NA,NA,"LessThan2000Calories" +812,2014-07-27,29.99,NA,2374,203,81,203,"" +813,2014-07-28,22.09,96.4,2046,168,47,235,"" +814,2014-07-29,23.53,96.3,2122,139,29,325,"" +815,2014-07-30,31.74,95.3,1895,165,47,210,"" +816,2014-07-31,29.49,NA,2048,156,49,248,"" +817,2014-08-01,29.74,95.2,2308,188,66,239,"" +818,2014-08-02,25.21,95.2,1828,166,42,205,"" +819,2014-08-03,28.02,95,2139,131,62,260,"" +820,2014-08-04,21.33,94.5,1942,141,39,254,"" +821,2014-08-05,24.54,94.8,1939,175,48,190,"" +822,2014-08-06,NA,95.2,NA,NA,NA,NA,"GetTogether" +823,2014-08-07,NA,NA,NA,NA,NA,NA,"GetTogether" +824,2014-08-08,NA,NA,NA,NA,NA,NA,"GetTogether" +825,2014-08-09,NA,NA,NA,NA,NA,NA,"GetTogether" +826,2014-08-10,NA,NA,NA,NA,NA,NA,"GetTogether" +827,2014-08-11,NA,NA,NA,NA,NA,NA,"GetTogether" +828,2014-08-12,NA,96.6,NA,NA,NA,NA,"GetTogether" +829,2014-08-13,NA,96.7,NA,NA,NA,NA,"Alone" +830,2014-08-14,NA,96.8,NA,NA,NA,NA,"VisitTo" +831,2014-08-15,NA,97.2,NA,NA,NA,NA,"Funeral" +832,2014-08-16,23.26,97.3,1860,133,48,215,"" +833,2014-08-17,25.89,96.6,2094,158,58,237,"" +834,2014-08-18,20.55,95.9,2190,166,85,189,"" +835,2014-08-19,25.6,NA,2066,143,48,259,"" +836,2014-08-20,26.07,94.5,2098,152,33,294,"" +837,2014-08-21,32.48,NA,2024,167,38,254,"" +838,2014-08-22,30.38,95.2,2029,159,66,196,"" +839,2014-08-23,29.5,95.2,2238,141,28,345,"" +840,2014-08-24,NA,94.3,NA,NA,NA,NA,"Restaurant" +841,2014-08-25,19.57,95.5,2052,180,52,210,"" +842,2014-08-26,25.95,94.6,2046,151,62,219,"" +843,2014-08-27,25.68,95.6,2275,178,73,227,"" +844,2014-08-28,26.69,NA,2434,139,59,332,"" +845,2014-08-29,29.42,95.3,2521,185,80,254,"" +846,2014-08-30,NA,95.2,NA,NA,NA,NA,"Restaurant" +847,2014-08-31,16.73,NA,1978,95,75,230,"" +848,2014-09-01,NA,NA,2311,145,78,254,"" +849,2014-09-02,NA,95.1,2240,172,37,299,"" +850,2014-09-03,NA,94.2,2005,147,57,221,"" +851,2014-09-04,NA,95.1,NA,NA,NA,NA,"" +852,2014-09-05,NA,95.2,2440,139,51,348,"" +853,2014-09-06,NA,95.2,1931,126,65,204,"" +854,2014-09-07,NA,95.3,2347,144,74,270,"" +855,2014-09-08,NA,94.4,1972,172,61,180,"" +856,2014-09-09,NA,93.8,2152,159,33,302,"" +857,2014-09-10,NA,NA,1939,191,47,180,"" +858,2014-09-11,NA,92.9,2080,183,62,195,"" +859,2014-09-12,NA,NA,2445,188,78,239,"" +860,2014-09-13,NA,93.9,NA,NA,NA,NA,"Restaurant" +861,2014-09-14,NA,NA,2013,133,74,194,"" +862,2014-09-15,NA,94.1,NA,NA,NA,NA,"VisitTo" +863,2014-09-16,NA,NA,NA,NA,NA,NA,"Other" +864,2014-09-17,NA,94.4,1876,123,65,191,"" +865,2014-09-18,NA,94.8,2091,154,59,233,"" +866,2014-09-19,NA,94.5,2114,127,65,254,"" +867,2014-09-20,NA,94.8,1862,111,44,253,"" +868,2014-09-21,NA,95,1887,156,43,226,"" +869,2014-09-22,NA,93.4,2062,144,44,258,"" +870,2014-09-23,NA,94,2071,139,59,242,"" +871,2014-09-24,NA,93.1,1691,138,44,178,"" +872,2014-09-25,NA,NA,NA,NA,NA,NA,"OnTravel" +873,2014-09-26,NA,NA,NA,NA,NA,NA,"VisitTo" +874,2014-09-27,NA,94.6,2178,132,72,242,"" +875,2014-09-28,NA,94.3,2376,121,108,232,"" +876,2014-09-29,NA,93.9,2185,63,74,264,"" +877,2014-09-30,NA,NA,2094,147,52,250,"" +878,2014-10-01,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +879,2014-10-02,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +880,2014-10-03,NA,96.1,2602,131,82,362,"" +881,2014-10-04,NA,NA,NA,NA,NA,NA,"VisitOf" +882,2014-10-05,NA,NA,NA,NA,NA,NA,"VisitOf" +883,2014-10-06,NA,96,1901,103,42,273,"" +884,2014-10-07,NA,95,2642,151,101,284,"" +885,2014-10-08,NA,NA,2286,108,94,249,"" +886,2014-10-09,NA,94.3,2589,144,101,267,"" +887,2014-10-10,NA,95,NA,NA,NA,NA,"Other" +888,2014-10-11,NA,NA,NA,NA,NA,NA,"VisitOf" +889,2014-10-12,NA,NA,NA,NA,NA,NA,"VisitOf" +890,2014-10-13,NA,NA,NA,NA,NA,NA,"VisitTo" +891,2014-10-14,NA,NA,NA,NA,NA,NA,"VisitTo" +892,2014-10-15,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +893,2014-10-16,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +894,2014-10-17,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +895,2014-10-18,NA,NA,NA,NA,NA,NA,"Holiday" +896,2014-10-19,NA,NA,NA,NA,NA,NA,"Holiday" +897,2014-10-20,NA,97.6,2156,120,72,248,"" +898,2014-10-21,NA,97,NA,NA,NA,NA,"" +899,2014-10-22,NA,NA,NA,NA,NA,NA,"" +900,2014-10-23,NA,NA,2240,186,52,204,"" +901,2014-10-24,NA,NA,NA,NA,NA,NA,"Ill" +902,2014-10-25,NA,NA,NA,NA,NA,NA,"Ill" +903,2014-10-26,NA,NA,NA,NA,NA,NA,"Ill" +904,2014-10-27,NA,NA,NA,NA,NA,NA,"Ill" +905,2014-10-28,NA,NA,NA,NA,NA,NA,"Ill" +906,2014-10-29,NA,NA,NA,NA,NA,NA,"Ill" +907,2014-10-30,NA,NA,NA,NA,NA,NA,"Ill" +908,2014-10-31,NA,NA,NA,NA,NA,NA,"VisitTo" +909,2014-11-01,NA,NA,NA,NA,NA,NA,"VisitTo" +910,2014-11-02,NA,95.5,2229,102,70,290,"" +911,2014-11-03,NA,NA,2267,125,74,267,"" +912,2014-11-04,NA,NA,NA,NA,NA,NA,"VisitTo" +913,2014-11-05,NA,NA,NA,NA,NA,NA,"VisitTo" +914,2014-11-06,NA,NA,NA,NA,NA,NA,"Lazy" +915,2014-11-07,NA,NA,NA,NA,NA,NA,"Lazy" +916,2014-11-08,NA,NA,NA,NA,NA,NA,"Lazy" +917,2014-11-09,NA,95.7,NA,NA,NA,NA,"VisitOfFamily" +918,2014-11-10,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +919,2014-11-11,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +920,2014-11-12,NA,96.9,NA,NA,NA,NA,"" +921,2014-11-13,NA,96.1,2298,161,84,219,"" +922,2014-11-14,NA,96.3,3141,177,133,303,"" +923,2014-11-15,NA,95,1968,110,32,302,"" +924,2014-11-16,NA,NA,2085,125,40,297,"" +925,2014-11-17,NA,94.9,2131,151,70,219,"" +926,2014-11-18,NA,NA,NA,NA,NA,NA,"VisitOf" +927,2014-11-19,NA,94.9,2094,149,60,235,"" +928,2014-11-20,NA,94.3,2068,166,60,210,"" +929,2014-11-21,NA,94.9,2450,176,85,242,"" +930,2014-11-22,NA,94.3,NA,NA,NA,NA,"Restaurant" +931,2014-11-23,NA,NA,NA,NA,NA,NA,"VisitTo" +932,2014-11-24,NA,95.6,NA,NA,NA,NA,"Other" +933,2014-11-25,NA,96.3,2386,159,95,218,"" +934,2014-11-26,NA,94.6,2188,157,72,220,"" +935,2014-11-27,NA,94.5,2250,112,107,207,"" +936,2014-11-28,NA,94.9,2567,110,76,353,"" +937,2014-11-29,NA,95.4,2163,180,57,236,"" +938,2014-11-30,NA,NA,NA,NA,NA,NA,"VisitOf" +939,2014-12-01,NA,95.6,1795,135,47,207,"" +940,2014-12-02,NA,95.4,NA,NA,NA,NA,"VisitOf" +941,2014-12-03,NA,NA,NA,NA,NA,NA,"VisitOf" +942,2014-12-04,NA,NA,2364,142,60,310,"" +943,2014-12-05,NA,95.4,NA,NA,NA,NA,"" +944,2014-12-06,NA,94.9,NA,NA,NA,NA,"" +945,2014-12-07,NA,NA,NA,NA,NA,NA,"" +946,2014-12-08,NA,NA,NA,NA,NA,NA,"" +947,2014-12-09,NA,NA,NA,NA,NA,NA,"" +948,2014-12-10,NA,NA,NA,NA,NA,NA,"" +949,2014-12-11,NA,NA,NA,NA,NA,NA,"" +950,2014-12-12,NA,NA,NA,NA,NA,NA,"" +951,2014-12-13,NA,NA,NA,NA,NA,NA,"" +952,2014-12-14,NA,NA,NA,NA,NA,NA,"" +953,2014-12-15,NA,NA,NA,NA,NA,NA,"" +954,2014-12-16,NA,NA,NA,NA,NA,NA,"" +955,2014-12-17,NA,NA,NA,NA,NA,NA,"" +956,2014-12-18,NA,NA,NA,NA,NA,NA,"" +957,2014-12-19,NA,NA,NA,NA,NA,NA,"" +958,2014-12-20,NA,NA,NA,NA,NA,NA,"" +959,2014-12-21,NA,NA,NA,NA,NA,NA,"" +960,2014-12-22,NA,NA,NA,NA,NA,NA,"" +961,2014-12-23,NA,NA,NA,NA,NA,NA,"" +962,2014-12-24,NA,NA,NA,NA,NA,NA,"" +963,2014-12-25,NA,NA,NA,NA,NA,NA,"" +964,2014-12-26,NA,NA,NA,NA,NA,NA,"" +965,2014-12-27,NA,NA,NA,NA,NA,NA,"" +966,2014-12-28,NA,NA,NA,NA,NA,NA,"" +967,2014-12-29,NA,NA,NA,NA,NA,NA,"" +968,2014-12-30,NA,NA,NA,NA,NA,NA,"" +969,2014-12-31,NA,NA,NA,NA,NA,NA,"" +970,2015-01-01,NA,NA,NA,NA,NA,NA,"" +971,2015-01-02,NA,NA,NA,NA,NA,NA,"" +972,2015-01-03,NA,NA,NA,NA,NA,NA,"" +973,2015-01-04,NA,NA,NA,NA,NA,NA,"" +974,2015-01-05,NA,NA,NA,NA,NA,NA,"" +975,2015-01-06,NA,NA,NA,NA,NA,NA,"" +976,2015-01-07,NA,NA,NA,NA,NA,NA,"" +977,2015-01-08,NA,NA,NA,NA,NA,NA,"" +978,2015-01-09,NA,NA,NA,NA,NA,NA,"" +979,2015-01-10,NA,NA,NA,NA,NA,NA,"" +980,2015-01-11,NA,NA,NA,NA,NA,NA,"" +981,2015-01-12,NA,NA,NA,NA,NA,NA,"" +982,2015-01-13,NA,NA,NA,NA,NA,NA,"" +983,2015-01-14,NA,NA,NA,NA,NA,NA,"" +984,2015-01-15,NA,NA,NA,NA,NA,NA,"" +985,2015-01-16,NA,NA,NA,NA,NA,NA,"" +986,2015-01-17,NA,NA,NA,NA,NA,NA,"" +987,2015-01-18,NA,NA,NA,NA,NA,NA,"" +988,2015-01-19,NA,NA,NA,NA,NA,NA,"" +989,2015-01-20,NA,NA,NA,NA,NA,NA,"" +990,2015-01-21,NA,NA,NA,NA,NA,NA,"" +991,2015-01-22,NA,NA,NA,NA,NA,NA,"" +992,2015-01-23,NA,NA,NA,NA,NA,NA,"" +993,2015-01-24,NA,NA,NA,NA,NA,NA,"" +994,2015-01-25,NA,NA,NA,NA,NA,NA,"" +995,2015-01-26,NA,NA,NA,NA,NA,NA,"" +996,2015-01-27,NA,NA,NA,NA,NA,NA,"" +997,2015-01-28,NA,NA,NA,NA,NA,NA,"" +998,2015-01-29,NA,NA,NA,NA,NA,NA,"" +999,2015-01-30,NA,NA,NA,NA,NA,NA,"" +1000,2015-01-31,NA,NA,NA,NA,NA,NA,"" +1001,2015-02-01,NA,NA,NA,NA,NA,NA,"" +1002,2015-02-02,NA,NA,NA,NA,NA,NA,"" +1003,2015-02-03,NA,NA,NA,NA,NA,NA,"" +1004,2015-02-04,NA,NA,NA,NA,NA,NA,"" +1005,2015-02-05,NA,NA,NA,NA,NA,NA,"" +1006,2015-02-06,NA,NA,NA,NA,NA,NA,"" +1007,2015-02-07,NA,NA,NA,NA,NA,NA,"" +1008,2015-02-08,NA,NA,NA,NA,NA,NA,"" +1009,2015-02-09,NA,NA,NA,NA,NA,NA,"" +1010,2015-02-10,NA,NA,NA,NA,NA,NA,"" +1011,2015-02-11,NA,NA,NA,NA,NA,NA,"" +1012,2015-02-12,NA,NA,NA,NA,NA,NA,"" +1013,2015-02-13,NA,NA,NA,NA,NA,NA,"" +1014,2015-02-14,NA,NA,NA,NA,NA,NA,"" +1015,2015-02-15,NA,NA,NA,NA,NA,NA,"" +1016,2015-02-16,NA,NA,NA,NA,NA,NA,"" +1017,2015-02-17,NA,NA,NA,NA,NA,NA,"" +1018,2015-02-18,NA,NA,NA,NA,NA,NA,"" +1019,2015-02-19,NA,NA,NA,NA,NA,NA,"" +1020,2015-02-20,NA,NA,NA,NA,NA,NA,"" +1021,2015-02-21,NA,NA,NA,NA,NA,NA,"" +1022,2015-02-22,NA,NA,NA,NA,NA,NA,"" +1023,2015-02-23,NA,NA,NA,NA,NA,NA,"" +1024,2015-02-24,NA,NA,NA,NA,NA,NA,"" +1025,2015-02-25,NA,NA,NA,NA,NA,NA,"" +1026,2015-02-26,NA,NA,NA,NA,NA,NA,"" +1027,2015-02-27,NA,NA,NA,NA,NA,NA,"" +1028,2015-02-28,NA,NA,NA,NA,NA,NA,"" +1029,2015-03-01,NA,NA,NA,NA,NA,NA,"" +1030,2015-03-02,NA,NA,NA,NA,NA,NA,"" +1031,2015-03-03,NA,NA,NA,NA,NA,NA,"" +1032,2015-03-04,NA,NA,NA,NA,NA,NA,"" +1033,2015-03-05,NA,NA,NA,NA,NA,NA,"" +1034,2015-03-06,NA,NA,NA,NA,NA,NA,"" +1035,2015-03-07,NA,NA,NA,NA,NA,NA,"" +1036,2015-03-08,NA,NA,NA,NA,NA,NA,"" +1037,2015-03-09,NA,NA,NA,NA,NA,NA,"" +1038,2015-03-10,NA,NA,NA,NA,NA,NA,"" +1039,2015-03-11,NA,NA,NA,NA,NA,NA,"" +1040,2015-03-12,NA,NA,NA,NA,NA,NA,"" +1041,2015-03-13,NA,NA,NA,NA,NA,NA,"" +1042,2015-03-14,NA,NA,NA,NA,NA,NA,"" +1043,2015-03-15,NA,NA,NA,NA,NA,NA,"" +1044,2015-03-16,NA,NA,NA,NA,NA,NA,"" +1045,2015-03-17,NA,NA,NA,NA,NA,NA,"" +1046,2015-03-18,NA,NA,NA,NA,NA,NA,"" +1047,2015-03-19,NA,NA,NA,NA,NA,NA,"" +1048,2015-03-20,NA,NA,1879,125,49,222,"" +1049,2015-03-21,NA,NA,NA,NA,NA,NA,"" +1050,2015-03-22,NA,NA,1816,143,62,173,"" +1051,2015-03-23,NA,98.2,NA,NA,NA,NA,"Restaurant" +1052,2015-03-24,NA,98.3,1961,140,28,280,"" +1053,2015-03-25,NA,97.8,2040,110,54,274,"" +1054,2015-03-26,NA,97.4,2241,155,48,292,"" +1055,2015-03-27,NA,97.7,NA,NA,NA,NA,"VisitOf" +1056,2015-03-28,NA,NA,NA,NA,NA,NA,"VisitOfFamily" +1057,2015-03-29,NA,NA,NA,NA,NA,NA,"VisitTo" +1058,2015-03-30,NA,97.9,2013,104,60,260,"" +1059,2015-03-31,NA,97.8,NA,NA,NA,NA,"VisitOf" +1060,2015-04-01,NA,97.7,2162,141,84,207,"" +1061,2015-04-02,NA,97.4,2329,108,55,349,"" +1062,2015-04-03,NA,96.5,1814,104,56,210,""