Hawaii_climate_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Dependencies\n",
    "\n",
    "%matplotlib notebook\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import style\n",
    "#style.use('fivethirtyeight')\n",
    "style.use('ggplot')\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import datetime as dt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SET UP "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Python SQL toolkit and Object Relational Mapper\n",
    "import sqlalchemy\n",
    "from sqlalchemy.ext.automap import automap_base\n",
    "from sqlalchemy.orm import Session\n",
    "from sqlalchemy import create_engine, func, inspect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Connect to database\n",
    "engine = create_engine(\"sqlite:///Resources/hawaii.sqlite\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Explore Database "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['measurement', 'station']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use the Inspector to explore the database and print the table names\n",
    "inspector = inspect(engine)\n",
    "inspector.get_table_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id INTEGER\n",
      "station TEXT\n",
      "date TEXT\n",
      "prcp FLOAT\n",
      "tobs FLOAT\n"
     ]
    }
   ],
   "source": [
    "# Use Inspector to print the column names and types\n",
    "columns = inspector.get_columns('measurement')\n",
    "for c in columns:\n",
    "    print(c['name'], c[\"type\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id INTEGER\n",
      "station TEXT\n",
      "name TEXT\n",
      "latitude FLOAT\n",
      "longitude FLOAT\n",
      "elevation FLOAT\n"
     ]
    }
   ],
   "source": [
    "# Use Inspector to print the column names and types\n",
    "columns = inspector.get_columns('station')\n",
    "for c in columns:\n",
    "    print(c['name'], c[\"type\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# inspector.get_columns('measurement')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1, 'USC00519397', '2010-01-01', 0.08, 65.0),\n",
       " (2, 'USC00519397', '2010-01-02', 0.0, 63.0),\n",
       " (3, 'USC00519397', '2010-01-03', 0.0, 74.0)]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use engine.execute to select and display the first 3 rows from the measurement table\n",
    "engine.execute('SELECT * FROM measurement LIMIT 3').fetchall()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1, 'USC00519397', 'WAIKIKI 717.2, HI US', 21.2716, -157.8168, 3.0),\n",
       " (2, 'USC00513117', 'KANEOHE 838.1, HI US', 21.4234, -157.8015, 14.6),\n",
       " (3, 'USC00514830', 'KUALOA RANCH HEADQUARTERS 886.9, HI US', 21.5213, -157.8374, 7.0)]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use engine.execute to select and display the first 3 rows from the station table\n",
    "engine.execute('SELECT * FROM station LIMIT 3').fetchall()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Reflect Tables into SQLAlchemy ORM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reflect the existing database into a new model\n",
    "Base = automap_base()\n",
    "# reflect the tables\n",
    "Base.prepare(engine, reflect=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['measurement', 'station']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# View all of the classes that automap found\n",
    "Base.classes.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save references to each table\n",
    "Measurement = Base.classes.measurement\n",
    "Station = Base.classes.station"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a session (link) from Python to the DB\n",
    "session = Session(engine)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Climate Analysis - Precipitation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2010-01-01   2017-08-23\n"
     ]
    }
   ],
   "source": [
    "# Ascertain Earliest Date in data\n",
    "date_first = session.query(Measurement.date).order_by(Measurement.date).first()\n",
    "\n",
    "# Ascertain Latest Date in data\n",
    "date_last = session.query(Measurement.date).order_by(Measurement.date.desc()).first()\n",
    "\n",
    "print(f\"{date_first[0]}   {date_last[0]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Precipitation</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-08-24</th>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08-24</th>\n",
       "      <td>2.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08-24</th>\n",
       "      <td>2.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08-24</th>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08-24</th>\n",
       "      <td>1.22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Precipitation\n",
       "Date                     \n",
       "2016-08-24           0.08\n",
       "2016-08-24           2.15\n",
       "2016-08-24           2.28\n",
       "2016-08-24           0.00\n",
       "2016-08-24           1.22"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Design a query to retrieve the last 12 months of precipitation data \n",
    "precipitation_last12mths = session.query(Measurement.date, Measurement.prcp).\\\n",
    "                           filter(Measurement.date >= '2016-08-24').filter(Measurement.date <= '2017-08-23'). \\\n",
    "                           order_by(Measurement.date).all()\n",
    "\n",
    "\n",
    "# Set above query results to a dataframe and preview\n",
    "df_precipitation = pd.DataFrame(precipitation_last12mths, \n",
    "                   columns=['Date','Precipitation']).set_index(\"Date\")\n",
    "\n",
    "\n",
    "# Convert all NaN's from the precipitation column to zero\n",
    "df_precipitation['Precipitation'] = df_precipitation['Precipitation'].fillna(0)\n",
    "\n",
    "# Sort dataframe by date (index)\n",
    "df_precipitation = df_precipitation.sort_index(ascending=True)\n",
    "\n",
    "df_precipitation.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
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       "}\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=\"829\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define X and Y values\n",
    "x = np.arange(0, len(df_precipitation.index.tolist()), 1)\n",
    "y = df_precipitation[\"Precipitation\"].tolist()\n",
    "\n",
    "# Define variables for x-ticks labels and locations\n",
    "months = [\"Sep\", \"Oct\", \"Nov\", \"Dec\", \"Jan\", \"Feb\", \"Mar\", \"Apr\", \"May\", \"Jun\", \"Jul\", \"Aug\"]\n",
    "month_step = int(len(y) / 12) + 5\n",
    "\n",
    "# Plot bar chart\n",
    "plt.bar(x, y, width=30, color=\"blue\", alpha=0.5, align=\"edge\")\n",
    "\n",
    "# Incorporate other chart properties\n",
    "plt.title(\"Precipitation in Hawaii - Sep 2016 to Aug 2017 \")\n",
    "plt.xlabel(\"Date\")\n",
    "plt.ylabel(\"Precipitation in inches\")\n",
    "xtick_locations = range(56, len(y), month_step)\n",
    "plt.xticks(xtick_locations, months, rotation=90)\n",
    "plt.ylim = max(y) + 1\n",
    "plt.grid(axis='x', alpha=0.20, color='black')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Precipitation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2223.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.159951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.441220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.010000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.110000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>6.700000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Precipitation\n",
       "count    2223.000000\n",
       "mean        0.159951\n",
       "std         0.441220\n",
       "min         0.000000\n",
       "25%         0.000000\n",
       "50%         0.010000\n",
       "75%         0.110000\n",
       "max         6.700000"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use Pandas to calcualte the summary statistics for the precipitation data\n",
    "df_precipitation.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Climate Analysis - Stations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of Stations: 9\n"
     ]
    }
   ],
   "source": [
    "# Count of total number of stations\n",
    "station_count = session.query(func.count(Station.station)).first()\n",
    "\n",
    "# Print results \n",
    "print(f\"Total number of Stations: {str(station_count[0])}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Station</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>USC00519281</td>\n",
       "      <td>2772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>USC00519397</td>\n",
       "      <td>2724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>USC00513117</td>\n",
       "      <td>2709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>USC00519523</td>\n",
       "      <td>2669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>USC00516128</td>\n",
       "      <td>2612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>USC00514830</td>\n",
       "      <td>2202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>USC00511918</td>\n",
       "      <td>1979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>USC00517948</td>\n",
       "      <td>1372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>USC00518838</td>\n",
       "      <td>511</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Station  Count\n",
       "0  USC00519281   2772\n",
       "1  USC00519397   2724\n",
       "2  USC00513117   2709\n",
       "3  USC00519523   2669\n",
       "4  USC00516128   2612\n",
       "5  USC00514830   2202\n",
       "6  USC00511918   1979\n",
       "7  USC00517948   1372\n",
       "8  USC00518838    511"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Which are the most active stations?\n",
    "busy_stations = session.query(Measurement.station, func.count(Measurement.station)).\\\n",
    "                group_by(Measurement.station).order_by(func.count(Measurement.station).desc()).all()\n",
    "\n",
    "# Set above query results to dataframe\n",
    "df_busy_stations = pd.DataFrame(busy_stations , columns=['Station', 'Count'])\n",
    "\n",
    "df_busy_stations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Station with the highest number of observations: USC00519281 - 2772\n"
     ]
    }
   ],
   "source": [
    "# Which station has the highest number of observations?\n",
    "# Set variables and Print results\n",
    "st_busiest = df_busy_stations[\"Station\"][0]\n",
    "st_obs = df_busy_stations[\"Count\"][0]\n",
    "\n",
    "print(f\"Station with the highest number of observations: {st_busiest} - {st_obs}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The maximum temperature at the Station with the highest number of observations is: 85.00 degrees\n",
      "The minimum temperature at the Station with the highest number of observations is: 54.00 degrees\n",
      "The average temperature at the Station with the highest number of observations is: 71.66 degrees\n"
     ]
    }
   ],
   "source": [
    "# Using the station id from the previous query, calculate the lowest temperature recorded, \n",
    "# highest temperature recorded, and average temperature of the most active station?\n",
    "\n",
    "sel = [func.max(Measurement.tobs), \n",
    "       func.min(Measurement.tobs), \n",
    "       func.avg(Measurement.tobs)]\n",
    "\n",
    "st_busiest_obs = session.query(*sel).filter(Measurement.station == st_busiest).all()\n",
    "\n",
    "\n",
    "print(f\"The maximum temperature at the Station with the highest number of observations is: \\\n",
    "{st_busiest_obs[0][0]:.2f} degrees\")\n",
    "\n",
    "print(f\"The minimum temperature at the Station with the highest number of observations is: \\\n",
    "{st_busiest_obs[0][1]:.2f} degrees\")\n",
    "\n",
    "print(f\"The average temperature at the Station with the highest number of observations is: \\\n",
    "{st_busiest_obs[0][2]:.2f} degrees\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Retrieve last 12 months of temperature observations\n",
    "# Filter by the station with the highest number of observations.\n",
    "st_busiest_12mth_obs = session.query(Measurement.tobs).filter(Measurement.date >= '2016-08-24').\\\n",
    "                       filter(Measurement.station == st_busiest).all()\n",
    "\n",
    "# Convert result above to dataframe\n",
    "df_st_busiest_12mth_obs = pd.DataFrame(st_busiest_12mth_obs, columns=['tobs'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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=\"810\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define plot parameters\n",
    "data = pd.DataFrame(st_busiest_12mth_obs, columns=['tobs'])\n",
    "\n",
    "# Plot histogram\n",
    "data.plot.hist(grid=True, bins=12, rwidth=1,color='blue')\n",
    "\n",
    "# Incorporate other plot properties\n",
    "plt.title('Temperature observations in Hawaii - Sep 2016 to Aug 2017 ')\n",
    "plt.xlabel('Temperature')\n",
    "plt.ylabel('Frequency')\n",
    "plt.legend(loc='best')\n",
    "plt.grid(axis='x', alpha=0.20, color ='black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernel_info": {
   "name": "python3"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  },
  "nteract": {
   "version": "0.9.1"
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}