lyft_writeup.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lyft Data Set Analysis \n",
    "### By Alejandro Fosado and Brandon Lee"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Summary of Conclusions\n",
    "In this study, we determined a driver's lifetime value, projected lifetime, and experience group. Using these three metrics, we also were able to provide two recommendations to help improve Lyft earnings and driver satisfaction. To find any of these values, we first had to clean the data which we completed in the “lyft_competition_cleaning.ipynb” file. Code for all visualizations in the notebook can be found in \"graphing_methods.py\"\n",
    "\n",
    "\n",
    "The lifetime value of a driver is predominantly based on the total fare generated, number of rides per day, and average pick-up times. To calculate a single, cohesive value, we first had to normalize the data and give each different category a different weight. Many of the other values, such as number of prime rides or total number of rides are incorporated in total fare, so these statistics became redundant.\n",
    "\n",
    "The projected lifetime of a driver was hard to estimate accurately due to the data set containing only data from a three month period. We used the formula where average driver lifetime is equal to one over the churn rate. This gave us 8.2 months as the projected average driver's lifetime.\n",
    "\n",
    "To determine driver behavior, we decided to use the k-means clustering algorithm which resulted in three distinct groups: starting, average, and experienced drivers. The average lifetime values for each group are 500 dollars, 3000 dollars, and 7000 dollars respectively. This grouping then helped us generate our business recommendations.\n",
    "\n",
    "Our two recommendations revolve around converting more starting and average drivers to experienced drivers while keeping experienced drivers active. There are many programs from Lyft that try to bring in new customers, but Lyft lacks systems to retain consistent drivers. One method that we recommend is a long-term ride per day program. A driver that has a history of higher number of rides per day may receive a higher pay. The second recommendation is introducing a loyalty program where drivers rank up based upon total number of rides. Both these recommendations help ensure experienced drivers are satisfied and convert new drivers into becoming experienced drivers. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#use %matplotlib inline if viewing from notebook, %matplotlib notebook for pdf conversion\n",
    "%matplotlib notebook\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.cluster import KMeans\n",
    "from mpl_toolkits import mplot3d\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn import linear_model\n",
    "from graphing_methods import figure_one, figure_two, figure_three, figure_four"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#read in tables\n",
    "rides_ts = pd.read_csv('../ride_timestamps.csv')\n",
    "#table created in lyft_competion_cleaning.ipynb\n",
    "driver_full = pd.read_csv('../driver_full.csv')\n",
    "driver_full = driver_full.set_index('driver_id')\n",
    "#convert from string to datetime objects\n",
    "rides_ts['timestamp'] = pd.to_datetime(rides_ts['timestamp'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Driver's Lifetime Value\n",
    "We believe that a driver's lifetime value should be defined by three factors: total fare revenue generated, number of rides per day, and average pickup times. We chose this criteria because it is important that the drivers generate revenue as this is how the company will turn a profit. We believe that the number of rides per day should also be taken into consideration as it is important that these drivers work consistenly and when needed. We also chose to consider average pickup time as it is important the drivers provide quality customer service by being more efficient with their time. Using this criteria we created a formula to calculate the lifetime value of a driver (pickup time and rides per day are normalized):\n",
    "### Lifetime Value = Total Revenue * (1 + tanh(Pickup Time) * .05 + tanh(Rides Per Day) * .10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#normalizing values and calculating lifetime value\n",
    "driver_full['lifetime_val'] = driver_full['total_fares']*(1+np.tanh(driver_full['pickup_time'].transform(\n",
    "    lambda x:(x - x.mean())/x.std()))*.05+np.tanh(driver_full['rides_per_day'].transform(\n",
    "    lambda x:(x - x.mean())/x.std()))*.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Main Factors Affecting Driver's Lifetime Value\n",
    "The main factors affecting a driver's lifetime value are ride frequency, pickup times and total fares collected. This is fairly straightforward as they are the values used in the calculation of a driver's lifetime value. Many other factors have a large effect on a drivers lifetime value but are redundant to mention as they are taken into account by the total fare calculation. For example, total number of rides:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "    // Updates the figure title.\n",
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       "\n",
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       "\n",
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       "\n",
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       "    // Request the server to send over a new figure.\n",
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       "\n",
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       "\n",
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       "    // Called whenever the canvas gets updated.\n",
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       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
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       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
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       "\n",
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       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R^2 value for this model is: 0.9673281979940891\n"
     ]
    }
   ],
   "source": [
    "figure_one(driver_full)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see above, the number of rides a driver gives is highly correlated with their lifetime value. This makes sense as more rides means more fares, which in turn is a direct contributor to the driver's lifetime value. From this we can also infer that total distance and drive time of a driver is also highly correlated with driver's lifetime value as those factors also contribute to more fares. Furthermore, the number of rides during prime time and days working for Lyft also are contributors to more total fares so those factors also contribute to a greater lifetime value."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Average Projected Lifetime of a Driver"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While we could just compute the mean of the lifetime column in our driver_full table, we feel this would not accurately estimate the average projected lifetime of a driver as many drivers will continue their Lyft careers beyond the data set's timeframe. This is because the datasets only span about a three month time period as seen below by finding the difference between the first and last ride timestamps:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timedelta('90 days 19:02:32')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(rides_ts['timestamp']) - min(rides_ts['timestamp'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Knowing this limitation we decided on using this formula to project an average driver lifetime:\n",
    "### Projected Lifetime = 1 / (Churn Rate)\n",
    "To calculate the churn rate, the percentage of drivers who have decided not to stay with Lyft over the three month period, we calculated the percent of drivers inactive for more than seven days, meaning that they did not give a ride in the last week of the dataset. Using this formula we get that the projected lifetime of a driver is around 8.2 months."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.205882352941178"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "churn_rate = np.count_nonzero([driver_full['time_inactive']>7])/len(driver_full)\n",
    "#we must then multiply this number by three becuase the churn rate was calcuated over a three month period\n",
    "proj_lifetime = 1/(churn_rate)*3\n",
    "proj_lifetime"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Do All Drivers Act Alike?\n",
    "In order to answer this question, we have decided to use the k-means clustering algorithm to find groups (clusters) in the data. After some experimentation, we found that the data can be separated into three different clusters. Here we use a normalized version of the driver_full table to apply the k-means clustering algorithm:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get an idea of what the clustering looks like, we can plot the clusters and the columns which we used to compute lifetime value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
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       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
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       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
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       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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\" width=\"1200\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "driver_full = figure_two(driver_full)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As seen above we have three clusters representing what we believe to be three different types of drivers. We call these groups starting, average, and experienced drivers. Below we will explore the differences between these groups:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"2500\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure_three(driver_full)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The starting driver group is the most sporadic of all the groups as it contains the most outliers. Generally, starting drivers have around 50 total rides and around 2-3 rides per day. These drivers have a very low estimated lifetime values of around 500 dollars. The average drivers have a much larger amount of total rides of around 150 and give around 4-5 rides per day. These drivers have an estimated lifetime value of around 3000 dollars. Lastly, we have the experienced drivers. These drivers are the most important to the company as they have, on average, the most total rides, rides per day, and estimated lifetime value. This group has around 475 total rides and gives around 7-8 rides per day with an estimated lifetime value of around 7000 dollars. Below we will explore the contributions of each group to the company."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"2500\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure_four(driver_full)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above we see that the second largest group is the starting drivers. These drivers make up 40% of the Lyft drivers but only contribute to 8% of the total fare revenue and have the worst median pickup times. The largest group, the average drivers generate a little over half of the total fare revenue with a better median pickup time than the starting group. The smallest group, the experienced drivers make up 18% of the Lyft drivers but contribute 41% of total fare revenue. The experienced group also has the best median pickup time."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Business Recommendations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After analyzing the dataset provided, it is evident that Lyft drivers are split into three separate groups. These groups are based upon the various inputs considered for a driver’s lifetime value. The three groups are split into: experienced drivers, average drivers, and starting drivers. There are two main recommendations: retaining experienced drivers through incentives or benefits and converting starting drivers into experienced drivers. \n",
    "\n",
    "The first recommendation of retaining experienced drivers is supported by statistics showing that although experienced drivers make up only 18% of driver population, they account for 41% of the fare contribution. This means that keeping the experienced drivers happy will greatly benefit Lyft’s earnings and lead to a higher consistency in their drivers. Since total fare is based on rides per day, drivers who have a higher ride rate per day tend to have a higher lifetime value; therefore, implementing a system where more rides per day equates to higher pay for drivers may encourage higher involvement from drivers. Lyft already has a program called the Ride Challenge program, however, this program is very minimal. It only requires 10 rides within a week and the reward is only 25 dollars. This can be beneficial to pull in new drivers who do not consistently drive, but it does not provide much incentive for loyal drivers. \n",
    "\n",
    "Lyft also already provides other incentives, such as the 1k jacket, for long-term drivers. These are great, but lack any sustaining value. It is a simple, one time gift from Lyft, but there does not seem to be another long term benefit plan. The other promotions seem to focus on prime times or day to day benefits. These will not ensure more drivers will become experienced drivers.\n",
    "\n",
    "The second recommendation is a lifetime loyalty program to promote sustained loyalty. Currently, Uber is doing a beta pro system for their drivers. Although we are not drivers for Uber, their ride customer program caught our interest and has helped sustain our use with Uber. The Uber reward system is based upon cancellation rates, arrival rates, star rating, and a point system. Rather than doing it this way, it may be better for Lyft to use a system where to improve ranking, the factors contributing to the driver's lifetime value must increase such as doing more rides per day on a consistent basis, driving more during prime time, and faster pick up times. "
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