{ "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "Complete Example of Working With Real Data\n", "====\n", "\n", "## Unit 13, Lecture 1\n", "\n", "*Numerical Methods and Statistics*\n", "\n", "----\n", "\n", "#### Prof. Andrew White, Mar 29 2016" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "scrolled": false }, "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", "sns.set_style('whitegrid')\n", "sns.set_context('notebook')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The Challenges and Solutions to Dealing with Real Data\n", "===\n", "\n", "This lecture is the solution to an analysis we did in class. I'll try to put each iteration we tried in lecture so that you can see how each cell was improved. We're trying to answer three questions:\n", "\n", "1. Is the amount you sleep tonight correlated with how much you slept last night?\n", "2. Can you predict how much you'll sleep?\n", "3. Is there a correlation between exercise and how good your sleep is?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Examining the Raw Data - Daily Summary\n", "===" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 102 entries, 0 to 101\n", "Data columns (total 33 columns):\n", "Date 102 non-null object\n", "Steps 102 non-null int64\n", "Calories 102 non-null int64\n", "HR_Lowest 102 non-null int64\n", "HR_Highest 102 non-null int64\n", "HR_Average 102 non-null int64\n", "Total_Miles_Moved 102 non-null float64\n", "Active_Hours 102 non-null int64\n", "Floors_Climbed 102 non-null int64\n", "UV_Exposure_Minutes 102 non-null int64\n", "Total_Seconds_All_Activities 85 non-null float64\n", "Total_Calories_All_Activities 85 non-null float64\n", "Sleep_Events 85 non-null float64\n", "Sleep_Total_Calories 85 non-null float64\n", "Total_Seconds_Slept 85 non-null float64\n", "Run_Events 85 non-null float64\n", "Run_Total_Seconds 85 non-null float64\n", "Total_Miles_Run 85 non-null float64\n", "Run_Total_Calories 85 non-null float64\n", "Bike_Events 85 non-null float64\n", "Bike_Total_Seconds 85 non-null float64\n", "Total_Miles_Biked 85 non-null float64\n", "Bike_Total_Calories 85 non-null float64\n", "Exercise_Events 85 non-null float64\n", "Exercise_Total_Seconds 85 non-null float64\n", "Exercise_Total_Calories 85 non-null float64\n", "Guided_Workout_Events 85 non-null float64\n", "Guided_Workout_Total_Seconds 85 non-null float64\n", "Guided_Workout_Total_Calories 85 non-null float64\n", "Golf_Events 85 non-null float64\n", "Golf_Total_Seconds 85 non-null float64\n", "Total_Miles_Golfed 85 non-null float64\n", "Golf_Total_Calories 85 non-null float64\n", "dtypes: float64(24), int64(8), object(1)\n", "memory usage: 27.1+ KB\n" ] } ], "source": [ "daily_data = pd.read_csv('Fitness Data/day.csv')\n", "daily_data.info()" ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "ename": "ValueError", "evalue": "could not convert string to float: '2016-04-11'", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;31m#Attempt 1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdaily_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDate\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdaily_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mHR_Average\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mplot\u001b[1;34m(*args, 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\u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m/opt/conda/lib/python3.5/site-packages/numpy/core/numeric.py\u001b[0m in \u001b[0;36masarray\u001b[1;34m(a, dtype, order)\u001b[0m\n\u001b[0;32m 472\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 473\u001b[0m \"\"\"\n\u001b[1;32m--> 474\u001b[1;33m \u001b[1;32mreturn\u001b[0m \u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morder\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0morder\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 475\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 476\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0masanyarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0morder\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;31mValueError\u001b[0m: could not convert string to float: '2016-04-11'" ] }, { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Attempt 1\n", "plt.plot(daily_data.Date, daily_data.HR_Average)" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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7GWm6MEsOM1K8cjHQSgOY20hO9p4oLWiXqjWOE7DMq66cG2uV6q44uXu7Yk2L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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Problem: The dates were treated as strings\n", "#Solution: Convert them\n", "dates = pd.to_datetime(daily_data.Date)\n", "plt.plot(dates, daily_data.HR_Average)" ] }, { "cell_type": "code", "execution_count": 152, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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NyZAVPdCwGnOS7WQOVDE7XSwFqJgrF0sdHorZ+E5ULtaY61dXSm/86u2Moywp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\n7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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Problem: The x-axis is crowded\n", "#Solution: Websearch reveals there is a method for this\n", "\n", "dates = pd.to_datetime(daily_data.Date)\n", "plt.plot(dates, daily_data.HR_Average)\n", "plt.gcf().autofmt_xdate()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The second set of data - Activites\n", "====" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Int64Index: 133 entries, 0 to 132\n", "Data columns (total 50 columns):\n", "Date 133 non-null object\n", "Start_Time 133 non-null object\n", "Event_Type 133 non-null object\n", "Duration_Seconds 133 non-null int64\n", "Seconds_Paused 133 non-null int64\n", "Calories_Burned 133 non-null int64\n", "Calories_Burned_Carbs 35 non-null float64\n", "Calories_Burned_Fats 35 non-null float64\n", "HR_Lowest 131 non-null float64\n", "HR_Peak 131 non-null float64\n", "HR_Average 131 non-null float64\n", "UV_Exposure_Minutes 133 non-null int64\n", "Total_Miles_Moved 35 non-null float64\n", "Cardio_Benefit 35 non-null object\n", "Minutes_Under_50%_HR 35 non-null float64\n", "Minutes_In_HRZ_Very_Light_50%_60% 35 non-null float64\n", "Minutes_In_HRZ_Light_60%_70% 35 non-null float64\n", "Minutes_In_HRZ_Moderate_70%_80% 35 non-null float64\n", "Minutes_In_HRZ_Hard_80%_90% 35 non-null float64\n", "Minutes_In_HRZ_Very_Hard_90%_Plus 35 non-null float64\n", "HR_Finish 35 non-null float64\n", "HR_Recovery_Rate_1_Min 24 non-null float64\n", "HR_Recovery_Rate_2_Min 19 non-null float64\n", "Recovery_Time_Seconds 35 non-null float64\n", "Bike_Average_MPH 0 non-null float64\n", "Bike_Max_MPH 0 non-null float64\n", "Elevation_Highest_Feet 20 non-null float64\n", "Elevation_Lowest_Feet 20 non-null float64\n", "Elevation_Gain_Feet 20 non-null float64\n", "Elevation_Loss_Feet 20 non-null float64\n", "Wake_Up_Time 93 non-null object\n", "Seconds_Awake 98 non-null float64\n", "Seconds_Asleep_Total 98 non-null float64\n", "Seconds_Asleep_Restful 98 non-null float64\n", "Seconds_Asleep_Light 98 non-null float64\n", "Wake_Ups 98 non-null float64\n", "Seconds_to_Fall_Asleep 98 non-null float64\n", "Sleep_Efficiency 98 non-null float64\n", "Sleep_Restoration 92 non-null object\n", "Sleep_HR_Resting 93 non-null float64\n", "Sleep_Auto_Detect 98 non-null object\n", "GW_Plan_Name 0 non-null float64\n", "GW_Reps_Performed 0 non-null float64\n", "GW_Rounds_Performed 0 non-null float64\n", "Golf_Course_Name 0 non-null float64\n", "Golf_Course_Par 0 non-null float64\n", "Golf_Total_Score 0 non-null float64\n", "Golf_Par_or_Better 0 non-null float64\n", "Golf_Pace_of_Play_Minutes 0 non-null float64\n", "Golf_Longest_Drive_Yards 0 non-null float64\n", "dtypes: float64(39), int64(4), object(7)\n", "memory usage: 53.0+ KB\n" ] } ], "source": [ "activities = pd.read_csv('Fitness Data/activity.csv')\n", "activities.info()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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8/B3tWNaPHrMNcwx6KNIw+GfPH68BADasmSfbNbPFMi8rzkeJTomOzqEZl1cD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PAAAF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\nCCkAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "adates = pd.to_datetime(activities.Date)\n", "plt.plot(adates, activities.Seconds_Asleep_Total)\n", "plt.gcf().autofmt_xdate()" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0 23210\n", "1 22929\n", "2 21746\n", "3 16135\n", "4 NaN\n", "5 20749\n", "6 NaN\n", "7 20224\n", "8 15875\n", "9 27613\n", "Name: Seconds_Asleep_Total, dtype: float64\n", "0 Sleep\n", "1 Sleep\n", "2 Sleep\n", "3 Sleep\n", "4 Run\n", "5 Sleep\n", "6 Run\n", "7 Sleep\n", "8 Sleep\n", "9 Sleep\n", "Name: Event_Type, dtype: object\n", "0 2016-01-01\n", "1 2016-01-02\n", "2 2016-01-04\n", "3 2016-01-04\n", "4 2016-01-04\n", "5 2016-01-05\n", "6 2016-01-06\n", "7 2016-01-07\n", "8 2016-01-07\n", "9 2016-01-08\n", "Name: Date, dtype: object\n", "0 2016-01-01 00:46:55\n", "1 2016-01-02 23:04:51\n", "2 2016-01-04 23:07:02\n", "3 2016-01-04 00:09:01\n", "4 2016-01-04 07:27:36\n", "5 2016-01-05 23:31:01\n", "6 2016-01-06 09:00:08\n", "7 2016-01-07 22:57:57\n", "8 2016-01-07 03:20:11\n", "9 2016-01-08 23:52:26\n", "Name: Start_Time, dtype: object\n" ] } ], "source": [ "#Problem: Some of the data is missing?\n", "#Solution: Analyze the raw data and we see that each row is an activity. For \"running\" activity no \"sleep\" data is recorder\n", "\n", "print(activities.Seconds_Asleep_Total[0:10])\n", "print(activities.Event_Type[0:10])\n", "print(activities.Date[0:10])\n", "print(activities.Start_Time[0:10])" ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [], "source": [ "#Problem: How to remove the extra rows\n", "#Solution: Find all NaNs and remove those rows\n", "sleep_valid = np.invert(np.isnan(activities.Seconds_Asleep_Total))\n", "sleep_valid = np.logical_and(activities.Seconds_Asleep_Total > 500, sleep_valid)\n", "sleep_dates = adates[sleep_valid]\n", "sleep_hours = activities.Seconds_Asleep_Total[sleep_valid] / (60 * 60)" ] }, { "cell_type": "code", "execution_count": 151, "metadata": {}, "outputs": [ { "data": { "image/png": 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R2pIuH/pPTBtuNFIIpWhVVN1X9hooy8QY8v7m+v3RsiRTafBpAQ6bBR6XzdBm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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(sleep_dates, sleep_hours)\n", "plt.xlabel('Date')\n", "plt.ylabel('Hours Asleep')\n", "plt.gcf().autofmt_xdate()" ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0 2016-01-01 00:46:55\n", "1 2016-01-02 23:04:51\n", "2 2016-01-04 23:07:02\n", "3 2016-01-04 00:09:01\n", "5 2016-01-05 23:31:01\n", "Name: Start_Time, dtype: datetime64[ns]\n", "0 2016-01-01\n", "1 2016-01-02\n", "2 2016-01-04\n", "3 2016-01-04\n", "5 2016-01-05\n", "Name: Date, dtype: datetime64[ns]\n" ] } ], "source": [ "#Problem: Some of these sleep times seem unreasonable. Let's see what time I went to bed at\n", "sleep_start_times = pd.to_datetime(activities.Start_Time)[sleep_valid]\n", "print(sleep_start_times[0:5])\n", "print(sleep_dates[0:5])" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2016-01-01 00:46:55\n", "2015-12-31 00:46:55\n" ] } ], "source": [ "#Problem: If we went to bed after midnight, we assign that to the following day\n", "#Solution: We will write a function that takes in a sleep time and returns what the actual day should be\n", "\n", "#Let's see how to move a date\n", "\n", "t = sleep_start_times[0]\n", "\n", "print(t)\n", "print(pd.DateOffset(-1) + t)" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2015-12-31 00:00:00\n" ] } ], "source": [ "#Problem: That moves the sleep 24 hours. We actually don't want the time to bed, just the date\n", "#Solution: Use normalize\n", "\n", "print( (pd.DateOffset(-1) + t).normalize())" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2016-01-01 00:46:55 2015-12-31 00:00:00\n" ] } ], "source": [ "def get_nearest_sleepytime(date):\n", " sleep_hour = date.time().hour\n", " if 0 <= sleep_hour <= 6:\n", " return (pd.DateOffset(-1) + date).normalize()\n", " else:\n", " return date.normalize()\n", "print(t, get_nearest_sleepytime(t))" ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "collapsed": true }, "outputs": [], "source": [ "#Now apply it to all dates\n", "sleep_dates = []\n", "for st in sleep_start_times:\n", " sleep_dates.append(get_nearest_sleepytime(st))\n", "sleep_dates = np.array(sleep_dates)" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[Timestamp('2015-12-31 00:00:00') Timestamp('2016-01-02 00:00:00')\n", " Timestamp('2016-01-04 00:00:00') Timestamp('2016-01-03 00:00:00')\n", " Timestamp('2016-01-05 00:00:00')]\n", "0 2016-01-01 00:46:55\n", "1 2016-01-02 23:04:51\n", "2 2016-01-04 23:07:02\n", "3 2016-01-04 00:09:01\n", "5 2016-01-05 23:31:01\n", "Name: Start_Time, dtype: datetime64[ns]\n" ] } ], "source": [ "print(sleep_dates[0:5])\n", "print(sleep_start_times[0:5])" ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "collapsed": true }, "outputs": [], "source": [ "#Problem: Now our sleeps are out of order! \n", "#If we try to correlate how much sleep I have tonight vs last night, we will have a problem\n", "#\n", "#Solution: Sort them based on date and re-order them\n", "\n", "o_sleep_dates = np.sort(sleep_dates)" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0 1 3 2 4]\n" ] } ], "source": [ "#Problem: I can sort my dates, but how do I rearrange my sleep_hours?\n", "#Solution: Use the argsort command\n", "\n", "reorder = np.argsort(sleep_dates)\n", "print(reorder[0:5])" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0 6.447222\n", "1 6.369167\n", "3 4.481944\n", "2 6.040556\n", "4 NaN\n", "Name: Seconds_Asleep_Total, dtype: float64\n", "[Timestamp('2015-12-31 00:00:00') Timestamp('2016-01-02 00:00:00')\n", " Timestamp('2016-01-03 00:00:00') Timestamp('2016-01-04 00:00:00')\n", " Timestamp('2016-01-05 00:00:00')]\n" ] } ], "source": [ "o_sleep_dates = sleep_dates[reorder]\n", "o_sleep_hours = sleep_hours[reorder]\n", "\n", "print(o_sleep_hours[0:5])\n", "print(o_sleep_dates[0:5])" ] }, { "cell_type": "code", "execution_count": 70, "metadata": { "collapsed": true }, "outputs": [], "source": [ "#Problem: We have NaNS again!\n", "#Solution: Our sleep_hours is a Pandas Series, not Numpy Arrays. It remembers the original indices. \n", "#Remember we removed all our Nans previously. We can convert to a numpy array use the values command\n", "\n", "o_sleep_hours = sleep_hours.values[reorder]" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "91\n", "93\n" ] } ], "source": [ "#Problem: We want to know if we have duplicates\n", "#Solution: Get the unique set and see if it's the same length\n", "\n", "print(len(np.unique(o_sleep_dates)))\n", "print(len(o_sleep_dates))" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[1 1 1 1 1 1 1 1 1 1]\n", "[Timestamp('2016-01-19 00:00:00') Timestamp('2016-01-22 00:00:00')]\n" ] } ], "source": [ "#Problem: We have duplicates!\n", "#Solution: Identify the non-unique elements by seeing which unique elements occur more than once\n", "\n", "uniq, counts = np.unique(o_sleep_dates, return_counts=True)\n", "print(counts[0:10])\n", "non_uniq = uniq[counts > 1]\n", "print(non_uniq)" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 0.40555556 4.77138889]\n", "[ 7.06666667 0.58083333]\n" ] } ], "source": [ "#Problem: Can we grab all the repeats for the non-unique elements?\n", "#Solution:\n", "for i in non_uniq:\n", " print(o_sleep_hours[o_sleep_dates == i])" ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [], "source": [ "#Problem: We now need to make a new dataset that has no repeats\n", "#Solution: Use a for loop and a sum to combine all the sleeps together which are non-unique\n", "\n", "clean_sleep_dates = np.unique(o_sleep_dates)\n", "clean_sleep_hours = np.empty(len(np.unique(o_sleep_dates)))\n", "clean_i = 0\n", "for i in range(len(clean_sleep_hours)):\n", " clean_sleep_hours[i] = np.sum(o_sleep_hours[o_sleep_dates == clean_sleep_dates[i]])" ] }, { "cell_type": "code", "execution_count": 80, "metadata": { "collapsed": true }, "outputs": [], "source": [ "#Just set them equal to our new ordered, cleaned data\n", "\n", "sleep_dates = clean_sleep_dates\n", "sleep_hours = clean_sleep_hours" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Data is Clean - Now Analyze\n", "---" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How much do I sleep and is it correlated with last night's sleep?\n", "===" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Build a confidence interval" ] }, { "cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "I sleep 5.85 +/- 0.26 hours per night\n" ] } ], "source": [ "serror = np.std(sleep_hours, ddof=1) / np.sqrt(len(sleep_hours))\n", "print('I sleep {:.3} +/- {:.2} hours per night'.format(np.mean(sleep_hours), ss.norm.ppf(0.975) * serror))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "See if there is a correlation between tonight and last night" ] }, { "cell_type": "code", "execution_count": 150, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(sleep_hours[:-1], sleep_hours[1:], 'o')\n", "plt.xlabel('Hours Slept Last Night')\n", "plt.ylabel('Hours Asleep')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "SpearmanrResult(correlation=-0.18116639914392724, pvalue=0.087480218009651625)" ] }, "execution_count": 83, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ss.spearmanr(sleep_hours[:-1], sleep_hours[1:])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There is no corelation. Perhaps if I don't sleep mcuh in multiple nights, I sleep more. Let's try the average of the last few nights" ] }, { "cell_type": "code", "execution_count": 220, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Shortened running mean at 26 for length 3\n", "Shortened running mean at 27 for length 3\n", "Shortened running mean at 30 for length 3\n", "Shortened running mean at 34 for length 3\n", "Shortened running mean at 51 for length 3\n", "Shortened running mean at 52 for length 3\n", "Shortened running mean at 88 for length 3\n", "Shortened running mean at 89 for length 3\n", "Shortened running mean at 90 for length 3\n", "[Timestamp('2015-12-31 00:00:00') Timestamp('2016-01-02 00:00:00')\n", " Timestamp('2016-01-03 00:00:00') Timestamp('2016-01-04 00:00:00')]\n", "[ 6.44722222 6.36916667 4.48194444 6.04055556]\n", "[ 6.40819444 5.63055556]\n" ] } ], "source": [ "#Problem: Need a way to compute a running mean. We also \n", "#have gaps in our sleep data\n", "#Solution: We'll write a function\n", "\n", "def runningMean(t,x, N):\n", " y = np.zeros(len(x))\n", " for ctr in range(len(x)):\n", " #need to account for gaps.\n", " \n", " #increment 1-by-1 upwards and stop once we exceed the number of\n", " #days forward we want (N)\n", " offset = 0\n", " delta = t[ctr + offset] - t[ctr]\n", " while delta.days < N:\n", " if(ctr + offset == len(t) - 1):\n", " #we can't go any farther forward\n", " break\n", " offset += 1\n", " delta = t[ctr + offset] - t[ctr]\n", " #be conservative, do not go too far forward.\n", " #Go back if we went too far forward\n", " if(delta.days > N and offset > 1):\n", " offset -= 1\n", " elif(offset == 0):\n", " offset = 1\n", " #Give warning of shortened mean\n", " if((t[min(len(t) - 1, ctr + offset)] - t[ctr]).days != N):\n", " print('Shortened running mean at {} for length {}'.format(ctr, N))\n", " y[ctr] = np.mean(x[ctr:(ctr + offset)])\n", " return y\n", "\n", "forward_three = runningMean(sleep_dates, sleep_hours, 3)\n", "\n", "print(sleep_dates[0:4])\n", "print(sleep_hours[0:4])\n", "print(forward_three[:2])" ] }, { "cell_type": "code", "execution_count": 221, "metadata": {}, "outputs": [ { "data": { "image/png": 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hD/j973+Pm266Cdu3b5/WQGczimiXIg4VE2MVI0DKBO4Oe0t63pDsB+J61FituGRlA4Ck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\nhGePj2JLhxe9HeQ6FAbjSmXzjJApyTSvBTWVzRsaGkr+eb2AOo2dvUR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5W02lM++g3Yek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\nLYQQQuiMJG8hhBBCZyR5CyGEEDrz/xI9RBYqhEIBAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(sleep_dates, forward_three)\n", "plt.plot(sleep_dates, sleep_hours)\n", "plt.xlabel('Date')\n", "plt.ylabel('Hours Asleep')\n", "plt.gcf().autofmt_xdate()" ] }, { "cell_type": "code", "execution_count": 222, "metadata": {}, "outputs": [ { "data": { "image/png": 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vvIlUtPdpNFrrs94Lx3NAz9MwW83YsGFD0e/7zNFBwA2sWXUB/AMRnPCfRduK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\nlJC4d8+oevEWBEEur+pTiPfR0U7oNCw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mOgsYJt3ylvqaZ4h5K58HgFNOserAjkZU26Z6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\n+/btdOrUCT8/P2JiYvD396d+/fo8+eSTt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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Problem: Why is our average on the first night different than how much we slept?\n", "#Solution: The running mean function looks forward by N on the first night.\n", "#We care about the average of the last few nights\n", "\n", "plt.plot(sleep_dates[3:], forward_three[:-3])\n", "plt.plot(sleep_dates, sleep_hours)\n", "plt.xlabel('Date')\n", "plt.ylabel('Hours Asleep')\n", "plt.gcf().autofmt_xdate()" ] }, { "cell_type": "code", "execution_count": 223, "metadata": {}, "outputs": [ { "data": { "image/png": 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l4TJfLCZDLpPAG2Bx7Pw0KktUqCpT49DJsYT9CxYLwzDhFqf/9PfX4L/tXI3V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TAAAg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\nfMVYZYpAQgAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Problem: The graph looks awful\n", "#Solution: Make it look nice\n", "line = plt.plot(sleep_dates, sleep_hours, linewidth=0.4)\n", "plt.plot(sleep_dates[3:], forward_three[:-3], color=line[0].get_color())\n", "plt.xlabel('Date')\n", "plt.ylabel('Hours Asleep')\n", "plt.gcf().autofmt_xdate()" ] }, { "cell_type": "code", "execution_count": 224, "metadata": {}, "outputs": [ { "data": { "image/png": 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kd1ZzG5PEAsakPZa9KBut20Q3ucjlxCqnE9d6n7vx1QM61t7Vd7y1vYvJYjBeLlYSENAB\n0/sB2/TqX9Xa0cOa0jRlYxew/ut+490uMtOzR8+WbAZ2qisDKmeO15baxgEB3SvbdcolP87Sh/sI\n6ACqnDleBdEWhcPhXBfFc7LVA9F7tX7l2lcUjVqDHs/2eHSyrv10lk/F64U4dKRDdQ3u33bTNCw3\nQ6oYgwbSkO2xKFPmDCTq2k93XD5enST5YjlZMn6dpQ/3OWpBd3Z26r777lNjY6Py8vK0fv16zZgx\nw62yAUbK5liUKXMGEnXtpzsun2iMXXK/q9u07mS/ztKH+xwF9AMPPKB58+bp5z//uXp6enTq1Cm3\nygUYLxtf/KbsQ53oQiHeWHm8Vn5v2eOFtJtBZWJ3MnczQ6psB/THH3+sffv26cEHH/z0jfLzNWLE\nCNcKBmSKG8GazS9+E/ahTnahkG4rv3eyWKaDKldbNCZiSq8IzGc7oJuamnTeeefpnnvu0fvvv68v\nfvGLuu+++3TOOee4WT7AVW4Fq4lf/JkW70LB7sqAbASVid3JpvSKwHwhy7IGTxFNwd/+9jddc801\nevHFFzVt2jQ98MADKiws1O233x73NZFI/HEnIBv+Z2eLjrZ3DzpeMmqo/vuykpivee/QSb11oFPH\njndrzMihuvSiQv32/7Yp1l9OXkj6wbXjE7522oRzXauP17136KT29Pv9zHX592PnfANus7tixnYL\nurS0VKWlpZo2bZokqaqqSk8//XTS1/lhaU8kEvF8PfxQByn9erS++Ers4x09Md+nrqFJ2+o/u7A8\n2t6tbfVtKh41XK0x1vKWlxb1vU+8106ceMGA1lJQz4UkhcPSjcsyVCBJN+Q1xWylX794etxbfGb6\nfGRj7kKQP1OmcdIwtR3QxcXFGjdunA4ePKgLLrhAe/fuVUVFhe2CANmQ7gSddJe+9O+e9XI3uGkz\nn+0yrTvZxElrMJejWdz333+/7rrrLvX09KisrEwbNmxwq1xARqQ77hlvDPPfHae0dnk44Re/ieOf\nqfBbiJgwya6Xly/akH2OAvrCCy/Utm3b3CoLkHHptqgStbiTffF7dTlNOiHSv6VdXJSvG/IysxOY\nX1r0Xr1oQ26w1ScCJ50WlZOZxpmYpZyNoEo1RM5uaR9t785IS9tPLXqvXrQhN9jqE0jAydaebm8L\nmo17UUup3+4yW1tW+mlrzFzdVxjeRAsaSMLJGKab45/ZGr9M9XaX2equ9VO3sGmT1mA2AhowTLxu\n7GwFVbz7Nve3pbYxa9216f4c08arY5Xn/9z1XzkrD7yDLm7AIIm6sbN9Z6t44Sx9elGQre7adH5O\ntoYBUmVaeeAttKCBDLDbikvUjZ3NPZyTje/2zmLvfe7h/8zivn7x9JzeMMS0ZUymlQfeQkADLnMy\n6zhRN3Y2xy/jlaNX70VB/zH2SCQSd3cup1IdyzdtvNq08sBbCGjAZfFaTQ8/H+lrCdtZdy0lDio3\nx17jlWNofp6+842Zxrb+TFvGZFp54C2MQQMuS9T6TDYGaXdc1+2xzng/z+RwlsxbxpRueeoamrT6\nkV26cu0rA5a0IZhoQQMuG110TswbafQXbwzSbje222OdXl0OZFq50ymPnzZkgTsIaCAHEo1B2lk7\nnYmxTpP2sE6HaeVOtTxMKMPZ6OIGXNbWcSrpczKxVjgbPweZw4QynI0WNOCyeBOD+us/BvneoZPa\nuGuXo8ld2VyC5SexJtYV5KgsTCjD2QhoeIJpu0MlEi8sQyHp86VFA8pe19CkbfVtfc+xO+5o2tir\nF8Qb8102e7TC4eyXh4ssnI2AhvESTZ7JVWsnkVxtrGHa2Kvp4v3u9xzo1I3LslwYcZGFwQhoGC9R\niN34X0VZLk1qTN9Yw0s9EqmwU594v/tjx7szUcSUcJGF/pgkBuP5efJMLiZ3+W1/aLv1ife7HzNy\naCaKCaSNgIbx/DxDORcba/jp/sqS/frE+x3Pvcj7nyv4AwEN45m2O5SbKmeO17LZozVhXJGG5IU0\nYVyR1i4PZ7Sb0289EnbrUzlzvNYuDw/63U+bcG4migmkjTFoGC/R5JlIpCXHpXNu2oRzdeOy7E0b\n9ttyHif1iTXm64fPFPyBgIYnmDh5xqsTrfy2nMdv9QF6EdCADV7eN9lvy3n8Vh+gFwEN2OD1fZNN\n7JFwwm/1ASQCGrDFbxOt3JTprn+vDi0A6SKgARv8NtHKLZnu+vfy0AKQLkfLrBYsWKArrrhC1dXV\n+vrXv+5WmQDj+XnplxOZXmPttzXcQCKOWtChUEjPPfecRo4c6VZ5AE9gYlJsdrv+U+22ZmgBQeIo\noC3LUjQadassQEIm3RpQYmJSLHa6/tPptmZoAUHiqIs7FArppptu0rJly/TSSy+5VSZgkHj7Lb93\n6GSui4Z+7HT9p9JtXdfQpNWP7NL/Nse+z7YpQwu95bxy7Sta/cguz+5vDjM4akFv3rxZY8eOVVtb\nm1asWKGJEydq1qxZbpUN6GParQERm52u/2Td1me3sHvlhaTys+6vnUtMYIPbQpZlWW680RNPPKGC\nggKtWLEi7nMikcF/ZEAqfrS5SbE+qXkh6QfX8uXnZf+zs0VH2wff4rFk1FD992UlSR83hZNyvnfo\npN460Kljx7s1ZuRQXXpRIXuC+0g4bG8rX9st6K6uLkWjURUUFOjkyZPas2ePVq1alfR1dgtqkkgk\n4vl6eK0On9/VEXPscczIoZ6qRyxeOxfx2K3HDXmxW8jXL56u8Mzxan3xlZiva+3oycjvzW497Jaz\nrqFJ2+o/q//R9m5tq2/TxIkX2G55B/0zZRInDVPbAd3a2qpVq1YpFArpzJkzWrJkiebOnWu7IEAi\n8fZb5taA6TNto49k3eJemRhmt5xe35UOmWM7oMvKyvTyyy+7WRYgrnhf4gVR7jyUDrfHSfuHfXFR\nvm7Ia7L1PolmxHvlZhh2y8nSMcTDTmLwDG4N6JybrbWzw/5oe3dGJkV5Zc253XJ6pYcA2UdAAx7i\ntHvazdZaNrtmc7Hm3M7v2k45vdJDgOwjoAGPSNQ9LSmlMHGztebnrtlsLpnySg8Bso+ABjwiXov1\nN68eUGt7V9//E4WJm601P3fNZnviFrvSIRZHO4kByJ54Ldb+4dxfrJCpnDlea5eHNWFckYbkhTRh\nXJHWLg/bCgc/3zDEz70D8A5a0IBHxGuxxhMvTNxqrZ3dNVtclK/rF0/3RUvQz70D8A4CGvCIeN3T\nxaOGx2xFZyNM+od9JBJR2LBwtjupjolbMAEBDXhEvMlEkgiTGJxM9GLiFkxAQAMekqh7mjAZyOlE\nLyZuIdcIaMAHCJPBTJnoZdrWqvAOAhqAL5kw0YtbUMIJllkB8CUTloEl6mYHkqEFDcCXTJjoZUo3\nO7yJgIbxvDyG5+Wy+0Gux+ZN6GaHdxHQMJqdMTxTQpHxR7CeGk4wBg2jpTuG1xuKh450KBq1+kKx\nrqEpk8WMifFHuLm1KoIn6y1oU1o38IZ0x/CyfZODRBh/hJT7bnZ4V9Zb0Ka0buAN5XHG6uKN4ZkU\niumWHQD6M6KLmy4/xJPuUhmTQtGEZT4AvMuISWJ0+SGedJfKmDQpx4RlPgC8y4iApssPiaQzhmda\nKDL+CMAuIwKaLj+4iVDMDBMmeJpQBiBbsh7Qa5eHjWndAEiNCWu6TSgDkE1ZD2haN4D3mLB8zYQy\nANlkxCxuAGYzYfmaCWUAsslxQEejUS1dulS33nqrG+UBYCATlq+ZUAYgmxwH9KZNm1RRUeFGWQAY\nyoQ13SaUAcgmRwHd3NysN998UzU1NW6VB4CBTNhT2oQyANnkaJLY+vXrtW7dOnV2MgYE+J0JEzxN\nKAOQLbZb0Lt371ZxcbGmTJkiy7LcLBMAAIEXsmym62OPPaZXXnlFQ4YM0enTp3XixAktWrRIDz30\nUNzXRCKDt2AEAMDPwuGwrdfZDuj+3nnnHf3617/Wk08+mfB5kUjEdkFN4od6+KEOkj/q4Yc6SNTD\nJH6og+SPejipA+ugAQAwkCs7iV188cW6+OKL3XgrAAAgWtAAABiJgAYAwEAENAAABiKgAQAwEAEN\nAICBCGgAAAzkyjIrBFNdQ5O21Dbqw5ZOlZcUqmbhJPZJBgCXENCwpa6hSQ8//9nWrYeOdPT9n5AG\nAOfo4oYtW2ob0zoOAEgPLWjY8mFL7FuMHo5zHP4Sa3ijINeFAnyGFjRsKS8pjHm8LM5x+Efv8Mah\nIx2KRq2+4Y33Dp3MddEAXyGgYUvNwklpHYd/xBvG2HOA3hPATXRxw5beiWBbaht1uKVTZcziDox4\nwxvHjndnuSSAvxHQsK1y5ngCOYDKSwp16EjHoONjRg7NQWkA/6KLG0Ba4g1jzL2I+QeAm2hBA0hL\nvOGNgmhLjkv2GTbRgR8Q0ADSFmt4IxIxI6DZRAd+QRc3AF9hEx34BQENwFfYRAd+QUAD8BU20YFf\nENAAfIVNdOAXTBID4CtsogO/IKAB+A6b6MAP6OIGAMBABDQAAAay3cX9ySef6LrrrlN3d7fOnDmj\nqqoqrVq1ys2yAQAQWLYDetiwYdq0aZOGDx+uM2fO6Nprr1VlZaWmT5/uZvkAAAgkR13cw4cPl/Rp\na7qnp8eVAgEAAIcBHY1GVV1drTlz5mjOnDm0ngEAcImjgM7Ly9OOHTtUV1en/fv364MPPnCrXAAA\nBFrIsizLjTf6xS9+oXPPPVcrVqyI+5xIJBL3MQAA/CgcDtt6ne1JYm1tbRo6dKgKCwt16tQp1dfX\na+XKlUlfZ7egJolEIp6vhx/qIPmjHn6og0Q9TOKHOkj+qIeThqntgD527JjuvvtuRaNRRaNRXXbZ\nZZo3b57tggDIrLqGJm2pbdSHLZ0qZ/tLwHi2A/oLX/iCtm/f7mZZAGRIXUOTHn7+syv5Q0c6+v5P\nSANmYicxIAC21DamdRxA7hHQQAB82NIZ8/jhOMcB5B4BDQRAeUlhzONlcY4DyD0CGgiAmoWT0joO\nIPe4HzQQAL0TwbbUNupwS6fKmMUNGI+ABgKicuZ4AhnwELq4AQAwEAENAICBCGgAAAxEQAMAYCAC\nGgAAAxHQAAAYiIAGAMBABDQAAAZioxIgg7gHMwC7CGggQ7gHMwAn6OIGMoR7MANwgoAGMoR7MANw\ngoAGMoR7MANwgoAGMoR7MANwgkliQIZwD2YAThDQQAZxD2YAdtHFDQCAgQhoAAAMREADAGAg22PQ\nzc3NWrdunf71r38pLy9PNTU1uv76690sGwAAgWU7oIcMGaJ77rlHU6ZM0YkTJ3TVVVdpzpw5qqio\ncLN8AAAEku0u7jFjxmjKlCmSpIKCAlVUVOjo0aOuFQwAgCBzZQy6qalJ77//vqZPn+7G2wEAEHiO\nA/rEiRO6/fbbde+996qgoMCNMgEAEHghy7Isuy/u6enRLbfcosrKSt1www1Jnx+JRJI+BwAAPwmH\nw7Ze5yig161bp/POO0/33HOP3bcAAAAx2A7oSCSi5cuXa/LkyQqFQgqFQrrzzjtVWVnpdhkBAAgc\nRy1oAACQGewkBgCAgQhoAAAMREADAGAg1+8H/cknn+i6665Td3e3zpw5o6qqKq1atWrAc9555x3d\ndtttKisrkyQtWrRIt912m9tFcSwajWrZsmUqKSnRk08+Oejxn/70p6qrq9Pw4cP14IMP9u2sZppE\n9fDKuViwYIFGjBihvLw85efna+vWrYOeY/r5SFYHr5yLzs5O3XfffWpsbFReXp7Wr1+vGTNmDHiO\n6eciWR28cC4OHjyoO++8U6FQSJZl6fDhw7rjjjsG3RPB9HORSj28cD42btyorVu3KhQKafLkydqw\nYYOGDRs24DlpnwsrA06ePGlZlmX19PRYNTU11v79+wc8/vbbb1u33HJLJn60q37zm99Ya9asiVnW\n3bt3WzfffLNlWZb17rvvWjU1NdkuXsoS1cMr52LBggVWe3t73Me9cD6S1cEr5+J73/uetXXrVsuy\nLKu7u9vq7Owc8LgXzkWyOnjlXPQ6c+aMNWfOHOujjz4acNwL56K/ePUw/Xw0NzdbCxYssE6fPm1Z\nlmXdcccd1vbt2wc8x865yEgX9/DhwyV92pru6enJxI/IuObmZr355puqqamJ+Xhtba2qq6slSTNm\nzFBnZ6dJloaBAAAERUlEQVRaW1uzWcSUJKuHV1iWpWg0GvdxL5yPZHXwgo8//lj79u3TsmXLJEn5\n+fkaMWLEgOeYfi5SqYPX1NfXq7y8XOPGjRtw3PRzcbZ49fCCaDSqrq4u9fT06NSpUxo7duyAx+2c\ni4wEdDQaVXV1tebMmaM5c+bE3KO7oaFBV155pVauXKkPPvggE8VwZP369Vq3bp1CoVDMx48eParS\n0tK+/5eUlKilpSVbxUtZsnpI5p8LSQqFQrrpppu0bNkyvfTSS4Me98L5SFYHyfxz0dTU1Lc50dKl\nS/X9739fp06dGvAc089FKnWQzD8X/e3cuVOXX375oOOmn4uzxauHZPb5KCkp0YoVKzR//nxVVlaq\nsLBQs2fPHvAcO+ciIwGdl5enHTt2qK6uTvv37x/0y5w6dap2796tl19+Wdddd52+/e1vZ6IYtu3e\nvVvFxcWaMmWKLA8vE0+lHqafi16bN2/W9u3b9atf/UovvPCC9u3bl+sipS1ZHbxwLnp6enTgwAF9\n85vf1Pbt23XOOefoqaeeynWx0pJKHbxwLnp1d3frjTfe0Ne+9rVcF8WRRPUw/Xx0dHSotrZWu3bt\n0ltvvaWTJ0/qd7/7neP3zegs7hEjRuiSSy7RW2+9NeB4QUFBXzf4vHnz1N3drfb29kwWJS1/+ctf\n9MYbb2jhwoVas2aN3n77ba1bt27Ac8aOHavm5ua+/zc3N6ukpCTbRU0olXqYfi569XYXjR49WosW\nLdJ777036HHTz0eyOnjhXJSWlqq0tFTTpk2TJFVVVenAgQMDnmP6uUilDl44F73q6uo0depUjR49\netBjpp+L/hLVw/TzUV9fr7KyMo0aNUpDhgzRokWL1NDQMOA5ds6F6wHd1tamzs5OSdKpU6dUX1+v\niRMnDnhO/373v/71r5KkUaNGuV0U27773e9q9+7dqq2t1WOPPaZLLrlEDz300IDnLFy4UDt27JAk\nvfvuuyoqKlJxcXEuihtXKvUw/VxIUldXl06cOCFJOnnypPbs2aNJkyYNeI7p5yOVOnjhXBQXF2vc\nuHE6ePCgJGnv3r2qqKgY8BzTz0UqdfDCuej12muvafHixTEfM/1c9JeoHqafj/PPP1/79+/X6dOn\nZVmWa38Xri+zOnbsmO6++25Fo1FFo1Fddtllmjdvnl588UWFQiFdc801ev3117V582bl5+frnHPO\n0eOPP+52MTKifx3mzZunN998U4sWLdLw4cO1YcOGXBcvZV47F62trVq1apVCoZDOnDmjJUuWaO7c\nuZ46H6nUwQvnQpLuv/9+3XXXXerp6VFZWZk2bNjgqXMhJa+DV85FV1eX6uvr9eMf/7jvmNfOhZS8\nHqafj+nTp6uqqkrV1dXKz8/X1KlTdfXVVzs+F+zFDQCAgdhJDAAAAxHQAAAYiIAGAMBABDQAAAYi\noAEAMBABDQCAgQhoAAAMREADAGCg/w8hY3cUNNu0hAAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(forward_three[:-3], sleep_hours[3:], 'o')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 225, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "SpearmanrResult(correlation=-0.078616462963615227, pvalue=0.4665701528891194)" ] }, "execution_count": 225, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ss.spearmanr(forward_three[:-3], sleep_hours[3:])" ] }, { "cell_type": "code", "execution_count": 226, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Shortened running mean at 0 for length 1\n", "Shortened running mean at 28 for length 1\n", "Shortened running mean at 30 for length 1\n", "Shortened running mean at 31 for length 1\n", "Shortened running mean at 32 for length 1\n", "Shortened running mean at 34 for length 1\n", "Shortened running mean at 35 for length 1\n", "Shortened running mean at 53 for length 1\n", "Shortened running mean at 90 for length 1\n", "1 SpearmanrResult(correlation=-0.18116639914392724, pvalue=0.087480218009651625)\n", "Shortened running mean at 27 for length 2\n", "Shortened running mean at 28 for length 2\n", "Shortened running mean at 29 for length 2\n", "Shortened running mean at 31 for length 2\n", "Shortened running mean at 33 for length 2\n", "Shortened running mean at 52 for length 2\n", "Shortened running mean at 53 for length 2\n", "Shortened running mean at 89 for length 2\n", "Shortened running mean at 90 for length 2\n", "2 SpearmanrResult(correlation=-0.20287708546135511, pvalue=0.056551433321119331)\n", "Shortened running mean at 26 for length 3\n", "Shortened running mean at 27 for length 3\n", "Shortened running mean at 30 for length 3\n", "Shortened running mean at 34 for length 3\n", "Shortened running mean at 51 for length 3\n", "Shortened running mean at 52 for length 3\n", "Shortened running mean at 88 for length 3\n", "Shortened running mean at 89 for length 3\n", "Shortened running mean at 90 for length 3\n", "3 SpearmanrResult(correlation=-0.078616462963615227, pvalue=0.4665701528891194)\n", "Shortened running mean at 25 for length 4\n", "Shortened running mean at 26 for length 4\n", "Shortened running mean at 29 for length 4\n", "Shortened running mean at 30 for length 4\n", "Shortened running mean at 31 for length 4\n", "Shortened running mean at 32 for length 4\n", "Shortened running mean at 33 for length 4\n", "Shortened running mean at 50 for length 4\n", "Shortened running mean at 51 for length 4\n", "Shortened running mean at 87 for length 4\n", "Shortened running mean at 88 for length 4\n", "Shortened running mean at 89 for length 4\n", "Shortened running mean at 90 for length 4\n", "4 SpearmanrResult(correlation=-0.085386746373113651, pvalue=0.4316608474463457)\n", "Shortened running mean at 24 for length 5\n", "Shortened running mean at 25 for length 5\n", "Shortened running mean at 28 for length 5\n", "Shortened running mean at 29 for length 5\n", "Shortened running mean at 49 for length 5\n", "Shortened running mean at 50 for length 5\n", "Shortened running mean at 86 for length 5\n", "Shortened running mean at 87 for length 5\n", "Shortened running mean at 88 for length 5\n", "Shortened running mean at 89 for length 5\n", "Shortened running mean at 90 for length 5\n", "5 SpearmanrResult(correlation=-0.10156139440539648, pvalue=0.35212858518921475)\n", "Shortened running mean at 23 for length 6\n", "Shortened running mean at 24 for length 6\n", "Shortened running mean at 27 for length 6\n", "Shortened running mean at 30 for length 6\n", "Shortened running mean at 32 for length 6\n", "Shortened running mean at 48 for length 6\n", "Shortened running mean at 49 for length 6\n", "Shortened running mean at 85 for length 6\n", "Shortened running mean at 86 for length 6\n", "Shortened running mean at 87 for length 6\n", "Shortened running mean at 88 for length 6\n", "Shortened running mean at 89 for length 6\n", "Shortened running mean at 90 for length 6\n", "6 SpearmanrResult(correlation=-0.11612272816103186, pvalue=0.2899039910119301)\n", "Shortened running mean at 22 for length 7\n", "Shortened running mean at 23 for length 7\n", "Shortened running mean at 26 for length 7\n", "Shortened running mean at 28 for length 7\n", "Shortened running mean at 29 for length 7\n", "Shortened running mean at 31 for length 7\n", "Shortened running mean at 47 for length 7\n", "Shortened running mean at 48 for length 7\n", "Shortened running mean at 84 for length 7\n", "Shortened running mean at 85 for length 7\n", "Shortened running mean at 86 for length 7\n", "Shortened running mean at 87 for length 7\n", "Shortened running mean at 88 for length 7\n", "Shortened running mean at 89 for length 7\n", "Shortened running mean at 90 for length 7\n", "7 SpearmanrResult(correlation=0.0044952920927407106, pvalue=0.96762842232263013)\n", "Shortened running mean at 21 for length 8\n", "Shortened running mean at 22 for length 8\n", "Shortened running mean at 25 for length 8\n", "Shortened running mean at 27 for length 8\n", "Shortened running mean at 28 for length 8\n", "Shortened running mean at 46 for length 8\n", "Shortened running mean at 47 for length 8\n", "Shortened running mean at 83 for length 8\n", "Shortened running mean at 84 for length 8\n", "Shortened running mean at 85 for length 8\n", "Shortened running mean at 86 for length 8\n", "Shortened running mean at 87 for length 8\n", "Shortened running mean at 88 for length 8\n", "Shortened running mean at 89 for length 8\n", "Shortened running mean at 90 for length 8\n", "8 SpearmanrResult(correlation=0.01679190630116284, pvalue=0.88023439963072803)\n", "Shortened running mean at 20 for length 9\n", "Shortened running mean at 21 for length 9\n", "Shortened running mean at 24 for length 9\n", "Shortened running mean at 26 for length 9\n", "Shortened running mean at 27 for length 9\n", "Shortened running mean at 30 for length 9\n", "Shortened running mean at 31 for length 9\n", "Shortened running mean at 45 for length 9\n", "Shortened running mean at 46 for length 9\n", "Shortened running mean at 82 for length 9\n", "Shortened running mean at 83 for length 9\n", "Shortened running mean at 84 for length 9\n", "Shortened running mean at 85 for length 9\n", "Shortened running mean at 86 for length 9\n", "Shortened running mean at 87 for length 9\n", "Shortened running mean at 88 for length 9\n", "Shortened running mean at 89 for length 9\n", "Shortened running mean at 90 for length 9\n", "9 SpearmanrResult(correlation=-0.03897432548622675, pvalue=0.72810940434431681)\n", "Shortened running mean at 19 for length 10\n", "Shortened running mean at 20 for length 10\n", "Shortened running mean at 23 for length 10\n", "Shortened running mean at 25 for length 10\n", "Shortened running mean at 26 for length 10\n", "Shortened running mean at 28 for length 10\n", "Shortened running mean at 29 for length 10\n", "Shortened running mean at 44 for length 10\n", "Shortened running mean at 45 for length 10\n", "Shortened running mean at 81 for length 10\n", "Shortened running mean at 82 for length 10\n", "Shortened running mean at 83 for length 10\n", "Shortened running mean at 84 for length 10\n", "Shortened running mean at 85 for length 10\n", "Shortened running mean at 86 for length 10\n", "Shortened running mean at 87 for length 10\n", "Shortened running mean at 88 for length 10\n", "Shortened running mean at 89 for length 10\n", "Shortened running mean at 90 for length 10\n", "10 SpearmanrResult(correlation=0.0068879855465221315, pvalue=0.95133607283110755)\n", "Shortened running mean at 18 for length 11\n", "Shortened running mean at 19 for length 11\n", "Shortened running mean at 22 for length 11\n", "Shortened running mean at 24 for length 11\n", "Shortened running mean at 25 for length 11\n", "Shortened running mean at 27 for length 11\n", "Shortened running mean at 30 for length 11\n", "Shortened running mean at 43 for length 11\n", "Shortened running mean at 44 for length 11\n", "Shortened running mean at 80 for length 11\n", "Shortened running mean at 81 for length 11\n", "Shortened running mean at 82 for length 11\n", "Shortened running mean at 83 for length 11\n", "Shortened running mean at 84 for length 11\n", "Shortened running mean at 85 for length 11\n", "Shortened running mean at 86 for length 11\n", "Shortened running mean at 87 for length 11\n", "Shortened running mean at 88 for length 11\n", "Shortened running mean at 89 for length 11\n", "Shortened running mean at 90 for length 11\n", "11 SpearmanrResult(correlation=-0.060103141115799348, pvalue=0.5963911655184273)\n", "Shortened running mean at 17 for length 12\n", "Shortened running mean at 18 for length 12\n", "Shortened running mean at 21 for length 12\n", "Shortened running mean at 23 for length 12\n", "Shortened running mean at 24 for length 12\n", "Shortened running mean at 26 for length 12\n", "Shortened running mean at 29 for length 12\n", "Shortened running mean at 42 for length 12\n", "Shortened running mean at 43 for length 12\n", "Shortened running mean at 79 for length 12\n", "Shortened running mean at 80 for length 12\n", "Shortened running mean at 81 for length 12\n", "Shortened running mean at 82 for length 12\n", "Shortened running mean at 83 for length 12\n", "Shortened running mean at 84 for length 12\n", "Shortened running mean at 85 for length 12\n", "Shortened running mean at 86 for length 12\n", "Shortened running mean at 87 for length 12\n", "Shortened running mean at 88 for length 12\n", "Shortened running mean at 89 for length 12\n", "Shortened running mean at 90 for length 12\n", "12 SpearmanrResult(correlation=-0.058519961051606624, pvalue=0.60845114820743817)\n", "Shortened running mean at 16 for length 13\n", "Shortened running mean at 17 for length 13\n", "Shortened running mean at 20 for length 13\n", "Shortened running mean at 22 for length 13\n", "Shortened running mean at 23 for length 13\n", "Shortened running mean at 25 for length 13\n", "Shortened running mean at 28 for length 13\n", "Shortened running mean at 41 for length 13\n", "Shortened running mean at 42 for length 13\n", "Shortened running mean at 78 for length 13\n", "Shortened running mean at 79 for length 13\n", "Shortened running mean at 80 for length 13\n", "Shortened running mean at 81 for length 13\n", "Shortened running mean at 82 for length 13\n", "Shortened running mean at 83 for length 13\n", "Shortened running mean at 84 for length 13\n", "Shortened running mean at 85 for length 13\n", "Shortened running mean at 86 for length 13\n", "Shortened running mean at 87 for length 13\n", "Shortened running mean at 88 for length 13\n", "Shortened running mean at 89 for length 13\n", "Shortened running mean at 90 for length 13\n", "13 SpearmanrResult(correlation=-0.090023900150482422, pvalue=0.43314192915958449)\n", "Shortened running mean at 15 for length 14\n", "Shortened running mean at 16 for length 14\n", "Shortened running mean at 19 for length 14\n", "Shortened running mean at 21 for length 14\n", "Shortened running mean at 22 for length 14\n", "Shortened running mean at 24 for length 14\n", "Shortened running mean at 27 for length 14\n", "Shortened running mean at 40 for length 14\n", "Shortened running mean at 41 for length 14\n", "Shortened running mean at 77 for length 14\n", "Shortened running mean at 78 for length 14\n", "Shortened running mean at 79 for length 14\n", "Shortened running mean at 80 for length 14\n", "Shortened running mean at 81 for length 14\n", "Shortened running mean at 82 for length 14\n", "Shortened running mean at 83 for length 14\n", "Shortened running mean at 84 for length 14\n", "Shortened running mean at 85 for length 14\n", "Shortened running mean at 86 for length 14\n", "Shortened running mean at 87 for length 14\n", "Shortened running mean at 88 for length 14\n", "Shortened running mean at 89 for length 14\n", "Shortened running mean at 90 for length 14\n", "14 SpearmanrResult(correlation=-0.050134076449865922, pvalue=0.66501358741064176)\n" ] }, { "data": { "image/png": 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igk2C/GwFDfm4uDgUFxdDq9UiICAAKSkpeOONN7ock5SUhA0bNsBkMqG1tRWZ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\nd3B1daWoqAiAiRMnkp6ejkwmo6qqCo1Gw4wZM3B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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Problem: Still no correlation. Can we check all possible running-averages?\n", "#Solution:\n", "\n", "days_back = []\n", "pval = []\n", "for N in range(1, 15):\n", " running = runningMean(sleep_dates, sleep_hours, N)\n", " result = ss.spearmanr(running[:-N], sleep_hours[N:])\n", " days_back.append(N)\n", " pval.append(result.pvalue)\n", " print(N, result)\n", "plt.plot(days_back, pval)\n", "plt.xlabel('Days Back Included in Analysis')\n", "plt.ylabel('P-Value')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 227, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Shortened running mean at 27 for length 2\n", "Shortened running mean at 28 for length 2\n", "Shortened running mean at 29 for length 2\n", "Shortened running mean at 31 for length 2\n", "Shortened running mean at 33 for length 2\n", "Shortened running mean at 52 for length 2\n", "Shortened running mean at 53 for length 2\n", "Shortened running mean at 89 for length 2\n", "Shortened running mean at 90 for length 2\n" ] }, { "data": { "image/png": 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eFspeRAmxa52IyEYRAzpjZ1o2CkxMXrP1JjVqBieH/7SBQU5ELqs5K601ZbIY\ng5OUwCAnIpfU3JXWmjJZTMYlWsn5cYyciFxSY9dRW8PWMe/6E4fcq6UwGITxxKGxCXJE1mCLnIhc\nUnOvo7Z1zNsZl2glbWCQE5EU7N0tbY/rqO8c887IysPstYdM1sgFWEgpDHIicgqNBbUSdw6z9zLK\nlmrkAiykFI6RE5HqLI0fN3c82xR7X0dtqUZnu46ctIMtciJSnaXxY6W6pe15OZilGp3xOnItc6Ur\nBBjkRKQ6SyEoQ7e0NTXyOnLHUGIoxpmxa52IVGdpHXIZuqVlqNFVKDEU48zYIici1VmaeCZDt7QM\nNboKV7tCgEFORKqzJgRl6JaWoUZXIMNQjD0xyInILEdOGFIqBF1p0hPdZO9LC50dg5yITNLChCEt\nfAaynasNczDIicgkLSwpqoXPQE3jSsMcnLVORCZpYcKQFj4DkSWqBrnBYEBsbCxeeOEFNcsgIhMs\nXRImAy18BiJLVA3yrVu3IigoSM0SiMgMLVwXrYXPQGSJakF+7do1pKenY9KkSWqVQESNsPda5GrQ\nwmcgskS1yW4rVqxAfHw8yso4VkXkrLQwYUgLn4GoMaq0yA8fPowOHTogODgYQgg1SiAiItIEnVAh\nSf/6179i165dcHd3R3V1Na5fv45Ro0Zh9erVZp+j1ze8uJ+IiEjLQkNDLT5GlSC/1cmTJ/HRRx9h\n06ZNjT5Or9db9YGo6biPHYP7WXncx8rjPlaetfuY15ETERFJTPWV3X7/+9/j97//vdplEBERSYkt\nciIiIokxyImIiCTGICciIpIYg5yIiEhiDHIiIiKJMciJiIgkpvrlZ0RalZGVh51p2bicX4bAjt6Y\nFNmDa34Tkd0xyIkUkJGVhzWf/rascO7VUuPPXmoVRUSaxK51IgXsTMu2aTsRUVOxRU6kgMv5pm/P\neyW/DICPY4shVXBohRyFQU6kgMCO3si9Wtpge0BHbxWqIUdrbGiFYU72xq51IgVMiuxh03bSFg6t\nkCOxRU6kgPpW1860bFzJL0PALV2ren2+ytWR0hofWiGyLwY5kUIiBnRmN6qL4tAKORK71omI7IxD\nK+RIbJETEdlZY0Mr9TirneyFQU5EpIDGhlY4q53siV3rREQOxlntZE8MciIiB+OsdrInBjkRkYMF\nmpm9zlnt1BQMciIiB+OsdrInTnYjInIwa2a1E1mLQU5EpAIuGET2wq51IiIiiTHIiYiIJKZK1/qN\nGzfw+OPgAk8jAAAVMUlEQVSPo6amBnV1dYiKisKsWbPUKIWIiEhqqgR5y5YtsXXrVnh6eqKurg5T\np05FREQE+vXrp0Y5RERE0lKta93T0xPAzdZ5bW2tWmUQERFJTbUgNxgMiImJwZAhQzBkyBC2xomI\niJpAtSB3c3NDamoqMjIycPr0aVy4cEGtUoiIiKSlE0IItYt499130aZNG0yfPt3sY/R6vdl/IyIi\n0qLQ0FCLj1FlsltRURFatGgBb29vVFVVITMzEzNmzLD4PGs+EDWdXq/nPnYA7mflcR8rj/tYedY2\nYFUJ8oKCArz66qswGAwwGAwYM2YMhg0bpkYpRJqWkZWHnWnZuJxfhkAuA0qkSaoEea9evZCSkqLG\nWxO5jIysPKz59Lcz+tyrpcafGeZE2sGV3Yg0amdatk3biUhODHIijbqcX2Zy+xUz24lITgxyIo0K\n7OhtcnuAme1EJCcGOZFGTYrsYdN2IpIT70dOpFH1E9p2pmXjSn4ZAjhrnUiTGOREGhYxoDODm0jj\n2LVOREQkMQY5ERGRxBjkREREEmOQExERSYxBTkREJDEGORERkcQY5ERERBJjkBMREUmMC8IQkRHv\nX04kHwY5EQHg/cuJZMWudSICwPuXE8mKQU5EAHj/ciJZMciJCADvX04kKwY5EQHg/cuJZMXJbkQE\ngPcvJ5IVg5yIjHj/ciL5sGudiIhIYgxyIiIiiTHIiYiIJKbKGPm1a9cQHx+PX375BW5ubpg0aRKe\neOIJNUohIiKSmipB7u7ujoSEBAQHB+P69euYOHEihgwZgqCgIDXKISIikpYqXet+fn4IDg4GAHh5\neSEoKAg///yzGqUQERFJTfUx8ry8PJw/fx79+vVTuxQiIiLpqBrk169fx5w5c7BgwQJ4eXmpWQoR\nEZGUdEIIocYb19bW4vnnn0dERASefPJJi4/X6/UWH0NERKQloaGhFh+jWpDHx8fjrrvuQkJCghpv\nT0REpAmqBLler8e0adPQs2dP6HQ66HQ6vPTSS4iIiHB0KURERFJTrUVOREREzaf6rHUiIiJqOgY5\nERGRxBjkREREEnPq+5HfuHEDjz/+OGpqalBXV4eoqCjMmjVL7bI0yWAwIC4uDh07dsSmTZvULkeT\nRowYgbZt28LNzQ0eHh5ITExUuyTNKSsrw8KFC5GdnQ03NzesWLEC/fv3V7ssTcnJycFLL70EnU4H\nIQSuXLmCF198kffLsLOPP/4YiYmJ0Ol06NmzJ1auXImWLVuafKxTB3nLli2xdetWeHp6oq6uDlOn\nTkVERARXgVPA1q1bERQUhPLycrVL0SydTodt27ahXbt2apeiWcuXL8ewYcOwfv161NbWoqqqSu2S\nNKdbt25ITU0FcLMBEBERgVGjRqlclbbk5+dj27Zt2L9/P1q2bIm5c+di3759iImJMfl4p+9a9/T0\nBHCzdV5bW6tyNdp07do1pKenY9KkSWqXomlCCBgMBrXL0Kzy8nKcOnUKcXFxAAAPDw+0bdtW5aq0\nLTMzE4GBgejUqZPapWiOwWBAZWWl8YT0nnvuMftYpw9yg8GAmJgYDBkyBEOGDGFrXAErVqxAfHw8\ndDqd2qVomk6nw9NPP424uDh8/vnnapejOXl5ecZFpmJjY7Fo0SK2yBW2b98+jB07Vu0yNKdjx46Y\nPn06hg8fjoiICHh7e2Pw4MFmH+/0Qe7m5obU1FRkZGTg9OnTuHDhgtolacrhw4fRoUMHBAcHg0sK\nKGv79u1ISUnB3/72N3z22Wc4deqU2iVpSm1tLc6ePYvHHnsMKSkpaN26NTZv3qx2WZpVU1ODgwcP\n4k9/+pPapWhOaWkp0tLScOjQIRw5cgQVFRXYvXu32cc7fZDXa9u2LQYOHIgjR46oXYqmfPPNNzh4\n8CAiIyMxb948nDhxAvHx8WqXpUn1XWO+vr4YNWoUvv32W5Ur0hZ/f3/4+/sjJCQEABAVFYWzZ8+q\nXJV2ZWRk4IEHHoCvr6/apWhOZmYmAgIC0L59e7i7u2PUqFHIysoy+3inDvKioiKUlZUBAKqqqpCZ\nmYnu3burXJW2/OUvf8Hhw4eRlpaGv/71rxg4cCBWr16tdlmaU1lZievXrwMAKioqcPToUfTo0UPl\nqrSlQ4cO6NSpE3JycgAAx48fR1BQkMpVadfevXsxbtw4tcvQpHvvvRenT59GdXU1hBAWj2WnnrVe\nUFCAV199FQaDAQaDAWPGjMGwYcPULovIZoWFhZg1axZ0Oh3q6uoQHR2NoUOHql2W5rz22muYP38+\namtrERAQgJUrV6pdkiZVVlYiMzMTS5YsUbsUTerXrx+ioqIQExMDDw8P9OnTB5MnTzb7eK61TkRE\nJDGn7lonIiKixjHIiYiIJMYgJyIikhiDnIiISGIMciIiIokxyImIiCTGICe7Ky0tRf/+/bFixQq1\nS2mSkydPGm+8US87OxsjRoxQqaKb1qxZg759+6KoqMjiY019BiVlZWUhOjoaEydOxMmTJx3ynj/9\n9BMGDRpkl9c6cOCA2ZX2lixZgpiYGMTExKBv374YM2YMYmJiEBsba/dljV9++WUMHz4csbGxiIqK\nwrRp0xpdmpMIcPIFYUhOu3fvxoMPPoi9e/ciPj4eHh72O8zq6urg7u5ut9czx9QNZOx9UxmDwQA3\nN+vOpQ0GA3bt2oWwsDDs2rULTz31lMXnOPImOF988QViY2Px9NNPN/g3JX9n9vqMaWlp6Nu3r3F5\n11u9/vrrxv+PjIzEhg0bFF0xbubMmZgyZQoA4Ny5c5g7dy5KSkowbdo0xd6T5MYgJ7tLSkpCfHw8\nNm/ejLS0NERFRaGqqgrDhw/Hl19+ifbt2wMAVq1ahbZt2+LPf/4zTp8+jbffftu4jOmcOXMwbNgw\n/PTTT4iLi0NsbCxOnDiBKVOmIDAwEO+8847x1rYvvPACxowZAwC4ePEiEhISUFlZid69e+Py5cv4\nn//5HwwbNgwFBQVYunQprl27hqqqKowbNw4zZsyw6jPd2fLKyMjAunXrYDAY4OvriyVLliAgIAAp\nKSk4dOgQ1q9fDwC3/ZySkoJdu3bBy8sLly5dwpo1a3DgwAHs3bsXrVu3hk6nw9atW03eejM9PR1d\nunTBnDlz8MYbbxiDvKqqCq+88gouXrwIDw8PdOvWDevWrTP5/E2bNuHGjRto0aIFEhIS0L9/fwBA\namoq/vGPf6Curg7e3t5488030bVrV6SkpGD37t1o1aoVLl++DD8/P6xevbrB7RS3bNmC/fv3o3Xr\n1ti9ezd27NiBP/3pTxg7diyOHz+OXr16YdmyZdi8ebOxdRkSEoJFixbB09MTGzduxI8//ojy8nLk\n5ubigQcewIwZM/DWW2/h6tWrGDlypE3r/9fV1WHGjBkoKSlBdXU1QkJCsGTJEnh4eCArKwtLly6F\nEAK1tbWYOXMmfHx8cPDgQRw7dgyJiYl46qmnMGHCBLPHwa3HwmeffYbc3FwsXLgQ33zzDR577DGk\npqaid+/eeP311/Hggw9i4sSJOHz4MN555x0YDAZ06NABb775JgICAix+luDgYCQkJGDRokWYNm0a\n8vPzMX/+fFRUVKC6uhqRkZF46aWXUFVVhZEjR2LXrl3Gtc8XL16Mzp0747HHHkN8fDxycnLg7u6O\nHj16YO3atVbvT5KAILKjc+fOiREjRgghhNi1a5d49tlnjf/22muviW3btgkhhKitrRVDhw4V//3v\nf0VpaamIiYkRBQUFQgghfv75ZxERESHKyspEXl6e6NWrl9i/f7/xdUpLS4XBYBBCCFFYWCgiIiJE\naWmpEEKI2NhYsXv3biGEEN9++60IDg4Whw8fFkIIMX36dPH1118LIYS4ceOGeOyxx0RmZmaDz3Di\nxAnRv39/ERMTY/xv9OjRxs9VWFgoBg0aJC5evCiEEGLnzp1i0qRJQgghkpOTxZw5c4yvdevPycnJ\nYsCAAeLKlStCCCGKi4tFWFiYqK6uFkIIcf36dVFXV2dyv/75z38WycnJQgghoqKixOnTp4UQQvzr\nX/8SzzzzzG37pv4zxMXFCSGEuHz5spgyZYooLy8XQgiRnZ0thg8fLoQQ4uuvvxYzZswQN27cEEII\nkZ6eLh599FFjvf379xe5ublCCCE2bNggZs+ebbK+V199VXz66afGn//whz+IxYsXG39OT08X48aN\nE9evXxdCCBEfHy/Wrl1rfN0//vGPory8XBgMBjF+/HjxzDPPiJqaGlFRUSHCw8PFpUuXGrxnXl6e\nGDRokMl6iouLjf8fHx8vduzYIYQQYubMmWLv3r3GfysrKzNZvzl/+MMfRHZ2tvHnixcvinHjxgkh\nhHj33XfFo48+Kj766CMhhBAjR44UV69eFQUFBWLgwIEiJydHCCHEjh07jPv4TvPnzzfWWu+XX34R\nvXv3FiUlJaK6ulpUVlYKIW4ew48//rjxGF61apV4//33jZ8rPDxcFBcXi/3794vnn3/e+Hr1xwhp\nB1vkZFdJSUmIiYkBAIwaNQrLli3Dzz//jHvuuQcxMTFYvnw5pk2bhvT0dAQFBaFTp05IT09HXl4e\nnnvuOWNrx93dHZcuXUL79u3RunVrjB492vgev/zyCxISEnDp0iW4u7ujtLQUOTk56N69Oy5cuGC8\nkUPfvn3Rq1cvADfXhj558iR+/fVX43tUVFTg4sWLCA8Pb/A57r//fiQmJhp/zs7OxgsvvAAAOHPm\nDIKDg4038ImLi8OSJUtQUVFhcf+Ehoaic+fOAABvb2906dIF8fHxGDJkCIYPH442bdo0eE5RURFO\nnjxpvJlNTEwMEhMT0a9fP/Tq1Qs//vgjli5dioceegjDhw9v8PwjR47gypUrmDZtmvGzGwwGFBUV\n4dChQ/jPf/6DyZMnG1ub9Tcqqq+3S5cuAIBJkyZh/PjxFj9jvfrjAACOHTuGsWPHGj/f5MmTsWLF\nCsybNw8A8PDDD8PLywsA0KtXLwQHB8PDw8PYy3D58mUEBgZa9b4GgwEffvghjhw5grq6OpSVlcHT\n0xMAMHDgQLz//vu4dOkShgwZgn79+ln9eUzp3r07ysrKUFhYiGPHjuEvf/kLPvjgA/zxj3+Em5sb\n/P39ceDAAYSEhKBr164AgEceeQRLly5FdXU1WrVqZdP71dbW4q233sL//d//Abi5hv/58+cRHh6O\nxx9/HE899RSef/55pKamYtiwYWjXrh369OmD1atXY9myZXjooYd4vwoNYpCT3dTU1GDPnj1o1aoV\nUlNTjd2XKSkpeP755xEaGorr16/jhx9+QGpqKiZOnGh8bu/evbFt27YGr/nTTz8Zv4Trvfnmm4iM\njMTGjRsB3LxdZXV1daO1GQwG6HQ6JCUlWT0u3RTu7u63db3eWdetQe3m5obPP/8c33zzDY4dO4aJ\nEydiy5Yt6Nmz523PSU1NRW1tLaKjowHc7DqurKzEa6+9hoCAAOzZswfHjh1Deno61q1b12BylBAC\nDz/8MN56660G9QohEBcXh9mzZzf7s9/J1EmJOS1btjT+v7u7+20/u7m5oa6uzurX2r17N7KysrB9\n+3Z4enrigw8+QG5uLgDgySefxIgRI3Ds2DEsXboUQ4cOxYsvvmj1a5sycOBAHDx4EGVlZXjooYfw\n5ptvIj09HQMHDjT7HFvG9s+cOYN77rkHPj4+2LBhA6qqqpCcnAwPDw8sWLDAeIzdd9996NWrF9LS\n0rB9+3asWrUKABAYGIg9e/YgMzPTeIzs2bPHrnNXSF2ctU52c+DAAXTv3t14W9SDBw9iy5YtSE5O\nNj4mNjYWH330EU6dOoWoqCgAwIABA5Cbm4sTJ04YH3frDGJxx/h0WVkZ7rvvPgDAv//9b1y+fBnA\nzXvW33///dizZw8A4Pvvv8cPP/wAAPDy8kJYWBg2bdpkfJ1r166hsLDQ6s9XX0f//v1x/vx54+0y\nk5OT0adPH7Rp0wZdunTBf/7zH9TU1ODGjRv45z//afb1rl+/jl9++QVhYWGYPXs2evbsiezs7AaP\nS0lJwXvvvYe0tDSkpaXh8OHDCAkJwf79+5Gfnw83NzdERkYiISEBv/76K0pKSm57/tChQ3HkyBFc\nuHDBuK1+/44YMQKpqanIz88HcPOE5/vvvzc+7ptvvjHu36SkpCbPEg8PD8e+fftQUVEBIQQSExPt\ncve3O48N4Obxcdddd8HT0xNlZWXG4wEAcnNzERAQgMmTJ+OJJ57AmTNnANw8PsrLy5tUw6BBg7Bp\n0yaEhYUBAB588EF8+OGHxp6eBx98EN9//z0uXboE4OZ+7Nevn1Wt8fPnz+Ott94yzuUoLS2Fn58f\nPDw8cPXqVRw6dOi2xz/++ONYtmwZvLy80LdvXwA3j3M3NzeMHDkSCQkJKCgoQGlpaZM+KzknnpKR\n3SQnJxtbjfUefPBBCCFw6tQphIWFYcKECRg5ciTi4uKMX2Q+Pj54//33sWrVKqxcuRI3btxAYGCg\nMXTvbL3MmzcPixcvxoYNGxASEoLevXsb/23VqlVYuHAhNm/ejJ49e6JXr17GyWNr167FihUrMH78\neAgh0LZtW6xYsQIdOnSw6vPV1+Hr64vVq1dj3rx5qKurg6+vL9asWQPgZsiHh4dj7Nix6NixI3r1\n6oWCggKTr1deXo7Zs2ejuroaBoMBDzzwAEaNGnXbY86cOYOSkpIGATpu3DgkJyfD19fXOHHJYDDg\n+eefh5+fn/EkAwC6dOmCNWvWYOHChaiurkZNTQ1+97vfISQkBGFhYXjppZcwc+ZMGAwG1NTUYPTo\n0XjggQcAAL/73e+watUq5ObmGie72bKv6kVEROCHH34wzsbu27evcajC1te6VVlZmXE4QQiBoKAg\nrF+/HmlpaRgzZgzuvvtuhIWFoaqqCgCwbds2nDhxAi1atECrVq3w2muvAQAmTJiAhIQEfPnll41O\ndjNVS3h4OBYsWGAM7vDwcKSkpBhb5B06dMDKlSsxd+5cCCHg6+trbC2bsmnTJuzYsQMVFRXw8/PD\nrFmzjMNFTz75JF588UVER0ejU6dODYaFwsPD4eHhgccee8y47fz588YJkAaDAbNnzzZOiCNt4G1M\nSVMqKiqMXboXL17EE088gS+//BLe3t4qVyaflJQU42xrksPly5fxxBNP4KuvvrpteIK0jS1y0pSs\nrCysXr0aQgjodDosW7aMIU4uYd26dfjiiy+QkJDAEHcxbJETERFJjJPdiIiIJMYgJyIikhiDnIiI\nSGIMciIiIokxyImIiCTGICciIpLY/wPcDacwFRrMDgAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "running = runningMean(sleep_dates, sleep_hours, 2)\n", "plt.plot(running[:-2], sleep_hours[2:], 'o')\n", "plt.ylabel('Hours Asleep')\n", "plt.xlabel('Average Hours Asleep from Last Two Days')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So it appears there is a correlation only with two days back." ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "Part 2: Create Model for Sleep\n", "===\n", "\n", "We'll regress our sleep tonight to sleep to the last two nights. We'll ignore the difficulty of non-contiguous data." ] }, { "cell_type": "code", "execution_count": 228, "metadata": {}, "outputs": [], "source": [ "import numpy.linalg as lin\n", "\n", "x_mat = np.column_stack( (np.ones(len(sleep_hours[2:])), sleep_hours[:-2], sleep_hours[1:-1]) )\n", "y = sleep_hours[2:]\n", "beta = lin.inv(x_mat.transpose().dot(x_mat)).dot(x_mat.transpose()).dot(y)" ] }, { "cell_type": "code", "execution_count": 229, "metadata": {}, "outputs": [ { "data": { "image/png": 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dfyJyDavhvm3bNowZMwaBgYF4/fXXkZeXh3nz5mHo0KGeaB+RrGXnFuHLPWe7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\n94dWqwUA/OY3v8Gf//znLt/T0NCA3Nx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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(x_mat.dot(beta),y, 'o')\n", "plt.plot(np.linspace(4,8,10), np.linspace(4,8,10))\n", "plt.xlabel('Predicted Sleep')\n", "plt.ylabel('Observed Sleep')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 230, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(0.9835946559906006, 0.32443320751190186)" ] }, "execution_count": 230, "metadata": {}, "output_type": "execute_result" } ], "source": [ "resids = y - x_mat.dot(beta)\n", "ss.shapiro(resids)" ] }, { "cell_type": "code", "execution_count": 231, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "8.47651398408\n", "5.76085393616\n", "7.31057033458\n", "4.85563392018\n" ] } ], "source": [ "def predicted_sleep(last_night, last_last_night):\n", " return beta[0] + beta[1] * last_last_night + beta[2] * last_night\n", "\n", "print(predicted_sleep(0, 0))\n", "print(predicted_sleep(6, 6))\n", "print(predicted_sleep(3, 2))\n", "print(predicted_sleep(8, 8))" ] }, { "cell_type": "code", "execution_count": 232, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "8.476513984080393 +/- 1.5804994596185127\n", "5.760853936158573 +/- 1.5804994596185127\n", "7.310570334577289 +/- 1.5804994596185127\n", "4.855633920184634 +/- 1.5804994596185127\n" ] } ], "source": [ "#Problem: Let's do a confidence interval for prediction. How do we get standard error in prediction?\n", "#Solution: It's the same as standard error in residual, since residual is prediciton - observed\n", "resids_se2 = np.sum(resids**2) / (len(sleep_hours[2:]) - 3)\n", "def predicted_sleep_interval(last_night, last_last_night, confidence=0.90):\n", " center = beta[0] + beta[1] * last_last_night + beta[2] * last_night\n", " width = ss.t.ppf(confidence, len(sleep_hours[2:]) - 3) * np.sqrt(resids_se2)\n", " return '{} +/- {}'.format(center, width)\n", "\n", "print(predicted_sleep_interval(0, 0))\n", "print(predicted_sleep_interval(6, 6))\n", "print(predicted_sleep_interval(3, 2))\n", "print(predicted_sleep_interval(8, 8))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Part 3: Correlation with Day of Week\n", "===" ] }, { "cell_type": "code", "execution_count": 233, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Problem: How do I get the day of week?\n", "#Solutoin: Websearch reveals this:\n", "\n", "plt.plot(pd.to_datetime(sleep_dates).dayofweek, sleep_hours, 'o')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 234, "metadata": {}, "outputs": [ { "data": { "image/png": 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QRBkp/WYhLnu83pECZkjuD/DRzl9A1VrudzXLMdh89FUAwK4T72LmkJfQMbG/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\nEREZDMubiIjIYP4/LKW/U5yLkGkAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Problem: Points are hard to see\n", "#Solution: Use swarm plot (from Seaborn)\n", "\n", "sns.swarmplot(pd.to_datetime(sleep_dates).dayofweek, sleep_hours)\n", "plt.ylabel('Hours Asleep')\n", "plt.xlabel('Day of Week')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 235, "metadata": {}, "outputs": [ { "data": { "image/png": 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FDNNJztDryCg4x+5I7WZ0n+tZ+OnPCFqt17u6nWl8svUpAFbvfJHLRv+ZrlnD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\n7DImT57ML37xCwAWLVrE+vXr+dnPfsa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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Problem: The day of week is an integer\n", "#Solutoin: Set the x labels\n", "sns.swarmplot(pd.to_datetime(sleep_dates).dayofweek, sleep_hours)\n", "plt.gca().set_xticklabels(['Sun', 'Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat'])\n", "plt.ylabel('Hours Asleep')\n", "plt.xlabel('Day of Week')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 236, "metadata": {}, "outputs": [ { "data": { "image/png": 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Gl8TgrVVqkafPRWVlJdxuN5R+1kTFSsAFa7W1tb6C84cOHcLLL7+Mvr4+yRsW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\nbBDOlUhb5Hbv3g2P24OcBTw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MBgM0Gg3WrVuHjRs3Or1fUVGRW9sV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\nSExMpN9DP6BWq7F582abtLkWYeHhyMrKErdhxK84+9IgSv6vqKgI+/f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LKHgT4kXOnj1r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\nhBBCvAwFb0IIIcTL/H/S538ucRGt4wAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Problem: Can we provide more information than just the points\n", "#Solution Use a violin/boxplot. It shows you the spread of data, mean, and confidence interval\n", "\n", "fig = sns.violinplot(pd.to_datetime(sleep_dates).dayofweek, sleep_hours)\n", "plt.gca().set_xticklabels(['Sun', 'Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat'])\n", "plt.ylabel('Hours Asleep')\n", "plt.xlabel('Day of Week')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Part 4: Comparing Calories with Sleep\n", "===\n", "\n", "This part requires combining two datasets." ] }, { "cell_type": "code", "execution_count": 134, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2015-12-31 6.447222\n", "2016-01-02 6.369167\n", "2016-01-03 4.481944\n", "dtype: float64\n", "Date\n", "2016-01-01 2005\n", "2016-01-02 1930\n", "2016-01-03 2024\n", "dtype: int64\n" ] } ], "source": [ "#Problem: How will pandas know how to join the two datasets?\n", "#Solution: Create a series and set the index to be the dates. We'll use that for our join\n", "\n", "sleep_series = pd.Series(sleep_hours, index=pd.to_datetime(sleep_dates))\n", "calories_series = pd.Series(daily_data.Calories.values, index=pd.to_datetime(daily_data.Date))\n", "\n", "print(sleep_series[0:3])\n", "print(calories_series[0:3])" ] }, { "cell_type": "code", "execution_count": 135, "metadata": {}, "outputs": [], "source": [ "#join two datasets \n", "#The inner means if days are missing, they are discareded\n", "joined_data = pd.concat([sleep_series, calories_series], axis=1, join='inner', keys=['hours','calories'])" ] }, { "cell_type": "code", "execution_count": 137, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "SpearmanrResult(correlation=-0.076426934059877299, pvalue=0.47401442828725215)" ] }, "execution_count": 137, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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yoQ3MjuwtP1Cj0TPXfBfuG/ec9b1g2+sk80N02nLoDiMCAOCckIEvSZ06dZIkbd26VcuX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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(joined_data.calories, joined_data.hours, 'o')\n", "plt.xlabel('Calories')\n", "plt.ylabel('Hourse Asleep')\n", "ss.spearmanr(joined_data.calories, joined_data.hours)" ] } ], "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": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 1 }