dmd/ariel commute.ipynb

## ariel commute.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ariel's Commute\n",
    "\n",
    "How long does Ariel's commute take, and does it matter when she leaves?\n",
    "\n",
    "Ariel grabbed her data from [Moves](https://accounts.moves-app.com/export). Here I'm going to see how time-of-day affects her commute duration.\n",
    "\n",
    "Side note: Kudos to Moves for *excellent* export facilities. Absolutely wonderful. They give you the data in every format and breakdown imaginable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "import pandas as pd\n",
    "import seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Type</th>\n",
       "      <th>Name</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Duration</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4897</th>\n",
       "      <td> 3/1/15</td>\n",
       "      <td> place</td>\n",
       "      <td>                   Home</td>\n",
       "      <td>2015-03-01 05:00:00</td>\n",
       "      <td> 2015-03-01T11:17:27-05:00</td>\n",
       "      <td> 40647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4898</th>\n",
       "      <td> 3/1/15</td>\n",
       "      <td>  move</td>\n",
       "      <td>              transport</td>\n",
       "      <td>2015-03-01 16:17:27</td>\n",
       "      <td> 2015-03-01T11:49:20-05:00</td>\n",
       "      <td>  1913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4899</th>\n",
       "      <td> 3/1/15</td>\n",
       "      <td>  move</td>\n",
       "      <td>                walking</td>\n",
       "      <td>2015-03-01 16:49:19</td>\n",
       "      <td> 2015-03-01T11:56:58-05:00</td>\n",
       "      <td>   459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4900</th>\n",
       "      <td> 3/1/15</td>\n",
       "      <td> place</td>\n",
       "      <td> Place in Cambridgeport</td>\n",
       "      <td>2015-03-01 16:56:59</td>\n",
       "      <td> 2015-03-01T14:12:03-05:00</td>\n",
       "      <td>  8104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4901</th>\n",
       "      <td> 3/1/15</td>\n",
       "      <td>  move</td>\n",
       "      <td>                walking</td>\n",
       "      <td>2015-03-01 19:12:03</td>\n",
       "      <td> 2015-03-01T14:19:04-05:00</td>\n",
       "      <td>   421</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date   Type                    Name               Start  \\\n",
       "4897  3/1/15  place                    Home 2015-03-01 05:00:00   \n",
       "4898  3/1/15   move               transport 2015-03-01 16:17:27   \n",
       "4899  3/1/15   move                 walking 2015-03-01 16:49:19   \n",
       "4900  3/1/15  place  Place in Cambridgeport 2015-03-01 16:56:59   \n",
       "4901  3/1/15   move                 walking 2015-03-01 19:12:03   \n",
       "\n",
       "                            End  Duration  \n",
       "4897  2015-03-01T11:17:27-05:00     40647  \n",
       "4898  2015-03-01T11:49:20-05:00      1913  \n",
       "4899  2015-03-01T11:56:58-05:00       459  \n",
       "4900  2015-03-01T14:12:03-05:00      8104  \n",
       "4901  2015-03-01T14:19:04-05:00       421  "
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('storyline.csv')\n",
    "df['Start'] = pd.to_datetime(df['Start'])\n",
    "# we only want since the current commute started\n",
    "df = df[df['Start'] > '2015-03-01']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Later I'm going to only want the time of day, not the date, so set all dates to 1970-01-01."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df['Start'] = df['Start'].apply(lambda x: x.replace(year=1970, month=1, day=1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I want to know which transport rows go between Home and Koch, so I make two new columns shifting name up and down so I can match against those."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Type</th>\n",
       "      <th>Name</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Duration</th>\n",
       "      <th>prev_name</th>\n",
       "      <th>next_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4897</th>\n",
       "      <td> 3/1/15</td>\n",
       "      <td> place</td>\n",
       "      <td>                   Home</td>\n",
       "      <td>1970-01-01 05:00:00</td>\n",
       "      <td> 2015-03-01T11:17:27-05:00</td>\n",
       "      <td> 40647</td>\n",
       "      <td>                    NaN</td>\n",
       "      <td>              transport</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4898</th>\n",
       "      <td> 3/1/15</td>\n",
       "      <td>  move</td>\n",
       "      <td>              transport</td>\n",
       "      <td>1970-01-01 16:17:27</td>\n",
       "      <td> 2015-03-01T11:49:20-05:00</td>\n",
       "      <td>  1913</td>\n",
       "      <td>                   Home</td>\n",
       "      <td>                walking</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4899</th>\n",
       "      <td> 3/1/15</td>\n",
       "      <td>  move</td>\n",
       "      <td>                walking</td>\n",
       "      <td>1970-01-01 16:49:19</td>\n",
       "      <td> 2015-03-01T11:56:58-05:00</td>\n",
       "      <td>   459</td>\n",
       "      <td>              transport</td>\n",
       "      <td> Place in Cambridgeport</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4900</th>\n",
       "      <td> 3/1/15</td>\n",
       "      <td> place</td>\n",
       "      <td> Place in Cambridgeport</td>\n",
       "      <td>1970-01-01 16:56:59</td>\n",
       "      <td> 2015-03-01T14:12:03-05:00</td>\n",
       "      <td>  8104</td>\n",
       "      <td>                walking</td>\n",
       "      <td>                walking</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4901</th>\n",
       "      <td> 3/1/15</td>\n",
       "      <td>  move</td>\n",
       "      <td>                walking</td>\n",
       "      <td>1970-01-01 19:12:03</td>\n",
       "      <td> 2015-03-01T14:19:04-05:00</td>\n",
       "      <td>   421</td>\n",
       "      <td> Place in Cambridgeport</td>\n",
       "      <td>              transport</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date   Type                    Name               Start  \\\n",
       "4897  3/1/15  place                    Home 1970-01-01 05:00:00   \n",
       "4898  3/1/15   move               transport 1970-01-01 16:17:27   \n",
       "4899  3/1/15   move                 walking 1970-01-01 16:49:19   \n",
       "4900  3/1/15  place  Place in Cambridgeport 1970-01-01 16:56:59   \n",
       "4901  3/1/15   move                 walking 1970-01-01 19:12:03   \n",
       "\n",
       "                            End  Duration               prev_name  \\\n",
       "4897  2015-03-01T11:17:27-05:00     40647                     NaN   \n",
       "4898  2015-03-01T11:49:20-05:00      1913                    Home   \n",
       "4899  2015-03-01T11:56:58-05:00       459               transport   \n",
       "4900  2015-03-01T14:12:03-05:00      8104                 walking   \n",
       "4901  2015-03-01T14:19:04-05:00       421  Place in Cambridgeport   \n",
       "\n",
       "                   next_name  \n",
       "4897               transport  \n",
       "4898                 walking  \n",
       "4899  Place in Cambridgeport  \n",
       "4900                 walking  \n",
       "4901               transport  "
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['prev_name'] = df['Name'].shift(1)\n",
    "df['next_name'] = df['Name'].shift(-1)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "koch = 'MIT Koch Day Care Ctr'\n",
    "east = df.loc[(df.Name == 'transport') & (df.prev_name == 'Home') & (df.next_name == koch) ]\n",
    "west = df.loc[(df.Name == 'transport') & (df.next_name == 'Home') & (df.prev_name == koch) ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Type</th>\n",
       "      <th>Name</th>\n",
       "      <th>Start</th>\n",
       "      <th>End</th>\n",
       "      <th>Duration</th>\n",
       "      <th>prev_name</th>\n",
       "      <th>next_name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4945</th>\n",
       "      <td>  3/5/15</td>\n",
       "      <td> move</td>\n",
       "      <td> transport</td>\n",
       "      <td>1970-01-01 12:49:44</td>\n",
       "      <td> 2015-03-05T08:45:36-05:00</td>\n",
       "      <td> 3352</td>\n",
       "      <td> Home</td>\n",
       "      <td> MIT Koch Day Care Ctr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4983</th>\n",
       "      <td>  3/9/15</td>\n",
       "      <td> move</td>\n",
       "      <td> transport</td>\n",
       "      <td>1970-01-01 11:50:58</td>\n",
       "      <td> 2015-03-09T08:32:02-04:00</td>\n",
       "      <td> 2464</td>\n",
       "      <td> Home</td>\n",
       "      <td> MIT Koch Day Care Ctr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5059</th>\n",
       "      <td> 3/16/15</td>\n",
       "      <td> move</td>\n",
       "      <td> transport</td>\n",
       "      <td>1970-01-01 12:03:33</td>\n",
       "      <td> 2015-03-16T08:40:40-04:00</td>\n",
       "      <td> 2227</td>\n",
       "      <td> Home</td>\n",
       "      <td> MIT Koch Day Care Ctr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5075</th>\n",
       "      <td> 3/17/15</td>\n",
       "      <td> move</td>\n",
       "      <td> transport</td>\n",
       "      <td>1970-01-01 12:16:17</td>\n",
       "      <td> 2015-03-17T08:49:58-04:00</td>\n",
       "      <td> 2021</td>\n",
       "      <td> Home</td>\n",
       "      <td> MIT Koch Day Care Ctr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5093</th>\n",
       "      <td> 3/18/15</td>\n",
       "      <td> move</td>\n",
       "      <td> transport</td>\n",
       "      <td>1970-01-01 12:21:08</td>\n",
       "      <td> 2015-03-18T08:51:00-04:00</td>\n",
       "      <td> 1792</td>\n",
       "      <td> Home</td>\n",
       "      <td> MIT Koch Day Care Ctr</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date  Type       Name               Start                        End  \\\n",
       "4945   3/5/15  move  transport 1970-01-01 12:49:44  2015-03-05T08:45:36-05:00   \n",
       "4983   3/9/15  move  transport 1970-01-01 11:50:58  2015-03-09T08:32:02-04:00   \n",
       "5059  3/16/15  move  transport 1970-01-01 12:03:33  2015-03-16T08:40:40-04:00   \n",
       "5075  3/17/15  move  transport 1970-01-01 12:16:17  2015-03-17T08:49:58-04:00   \n",
       "5093  3/18/15  move  transport 1970-01-01 12:21:08  2015-03-18T08:51:00-04:00   \n",
       "\n",
       "      Duration prev_name              next_name  \n",
       "4945      3352      Home  MIT Koch Day Care Ctr  \n",
       "4983      2464      Home  MIT Koch Day Care Ctr  \n",
       "5059      2227      Home  MIT Koch Day Care Ctr  \n",
       "5075      2021      Home  MIT Koch Day Care Ctr  \n",
       "5093      1792      Home  MIT Koch Day Care Ctr  "
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "east.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x114a86c90>]"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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iVgC3AccC+4HzM/OJeX8XkqRZG1gAIuJy4EPAM+2mU4BrM/Pann1WA5e0r60A7o+I7wEX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\ncPIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114359b50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(west.Start,west.Duration,'.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's get rid of outliers.\n",
    "\n",
    "Yes, obviously if you leave work in the middle of the day, there's zero traffic, but we don't want those 5 points driving the entire model, so let's drop them. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "west = west.ix[(west.Start > 7.5e13) & (west.Start < 8e13)].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10edf4390>]"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1143cc650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(west.Start,west.Duration,'.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10ef164d0>]"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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l+VlAl5GdBXQccKO7b87PAtoAnAIcAi5y92faZBr4L1HFxZw/5uyg/KG1zN+DsauC03UA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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ee27490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(east.Start,east.Duration,'.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "east = east.ix[(east.Start > 4.2e13) & (east.Start < 5e13)].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10f034e50>]"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ef2ecd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(east.Start,east.Duration,'.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How long does the commute take?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x113eefc50>"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11424d050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hist([k/60 for k in east.Duration], 15, [20, 60])\n",
    "# using pyplot.hist instead of DataFrame.hist so I can /60 to get minutes\n",
    "title('Eastbound')\n",
    "xlabel('Minutes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x10f042ad0>"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MT1LjPcCVVIcIApydmZfMToWViHgKcA4wDLSBv6W6JMIFDEhfwqR1zmPA+nNMRCwCfgQc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\nV2WUyQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f83a850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hist([k/60 for k in west.Duration], 15, [20, 60])\n",
    "title('Westbound')\n",
    "xlabel('Minutes')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Write to file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "east.to_csv('east.csv')\n",
    "west.to_csv('west.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Now, do some statistics."
   ]
  }
 ],
 "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": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}