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OLD_preprocess_GWR.ipynb
ddea7b1c1968Romain_branch

OLD_preprocess_GWR.ipynb
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			{
			"cells": [
			{
			"cell_type": "code",
			"execution_count": 1,
			"metadata": {},
			"outputs": [
			{
			"name": "stderr",
			"output_type": "stream",
			"text": [
			"/home/walch/.local/lib/python3.6/site-packages/dask/config.py:129: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.\n",
			" data = yaml.load(f.read()) or {}\n",
			"/home/walch/.local/lib/python3.6/site-packages/distributed/config.py:20: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.\n",
			" defaults = yaml.load(f)\n"
			]
			}
			],
			"source": [
			"import numpy as np\n",
			"import pandas as pd\n",
			"import geopandas as gpd\n",
			"import xarray as xr\n",
			"\n",
			"import os\n",
			"import calendar\n",
			"\n",
			"%matplotlib notebook\n",
			"import matplotlib.pyplot as plt"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 2,
			"metadata": {},
			"outputs": [],
			"source": [
			"def get_yearly_sum( ds, var = None ):\n",
			"# create an xarray datasets that contains, for each timestamp in \"ds\", the number of repetitions of that hour in the month\n",
			"# and sums all values over a year \n",
			"\n",
			" days_of_each_month = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]\n",
			" month = range(1,13)\n",
			" \n",
			" days_of_month = pd.DataFrame( data = [ month, days_of_each_month ], index = ['month', 'n_days'] ).transpose()\n",
			" \n",
			" timestamps = ds.timestamp.to_dataframe()\n",
			" timestamps['month'] = timestamps.timestamp.dt.month\n",
			" \n",
			" days_of_month = timestamps.merge( days_of_month, on = 'month', how = 'left' ).drop( columns = 'month' ).set_index('timestamp').to_xarray()\n",
			" \n",
			" if var is not None:\n",
			" annual_sum = (ds[var] * days_of_month.n_days).sum( dim = 'timestamp' )\n",
			" else:\n",
			" annual_sum = (ds * days_of_month.n_days).sum( dim = 'timestamp' )\n",
			" \n",
			" week_weighted = annual_sum.sel( daytype = 'weekday' ) * 5/7 + annual_sum.sel( daytype = 'weekend' ) * 2/7\n",
			" return week_weighted"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"# Load GWR"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 3,
			"metadata": {},
			"outputs": [],
			"source": [
			"GWR_fp = '/work/hyenergy/raw/GWR_Reg-BL/GWR_MADD_Export_MADD-20200715-A3_20200722' # 'D:\\Building_data\\OFS\\Buildings\\'"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Building information"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 4,
			"metadata": {},
			"outputs": [],
			"source": [
			"BLD_fp = 'GWR_MADD_GEB-10_Data_MADD-20200715-A3_20200722.dsv'\n",
			"BLD_cols = ['EGID', 'GKODE', 'GKODN', 'GSTAT', 'GKAT', 'GKLAS', 'GGDENR', 'GDEKT']\n",
			"GWR = pd.read_csv(os.path.join(GWR_fp, BLD_fp), sep = '\\t', usecols = BLD_cols)\n",
			"\n",
			"# Extract only those dwellings that are currently active (\"Wohnung bestehend\")\n",
			"BLD = GWR[GWR.GSTAT == 1004]"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 5,
			"metadata": {
			"scrolled": true
			},
			"outputs": [
			{
			"data": {
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			" <thead>\n",
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			" <th></th>\n",
			" <th>EGID</th>\n",
			" <th>GKODE</th>\n",
			" <th>GKODN</th>\n",
			" <th>GSTAT</th>\n",
			" <th>GKAT</th>\n",
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			" <td>1242.0</td>\n",
			" <td>6810</td>\n",
			" <td>JU</td>\n",
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			" <td>400002711</td>\n",
			" <td>2582389.601</td>\n",
			" <td>1252071.656</td>\n",
			" <td>1004.0</td>\n",
			" <td>1020.0</td>\n",
			" <td>1110.0</td>\n",
			" <td>6810</td>\n",
			" <td>JU</td>\n",
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			"<p>2238851 rows × 8 columns</p>\n",
			"</div>"
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			"text/plain": [
			" EGID GKODE GKODN GSTAT GKAT GKLAS GGDENR \\\n",
			"0 1600000 2679684.326 1237449.553 1004.0 1020.0 1122.0 1 \n",
			"1 1600001 2679702.150 1237493.958 1004.0 1030.0 1110.0 1 \n",
			"2 1600002 2679713.052 1237475.814 1004.0 1030.0 1121.0 1 \n",
			"3 1600003 2679655.455 1237516.450 1004.0 1020.0 1122.0 1 \n",
			"4 1600005 2679749.269 1237529.346 1004.0 1020.0 1110.0 1 \n",
			"... ... ... ... ... ... ... ... \n",
			"2355720 400002687 2582696.000 1250531.000 1004.0 1060.0 1242.0 6810 \n",
			"2355721 400002711 2582389.601 1252071.656 1004.0 1020.0 1110.0 6810 \n",
			"2355722 400002734 2581458.869 1251234.498 1004.0 1060.0 NaN 6810 \n",
			"2355724 400002737 2582121.030 1251281.432 1004.0 1060.0 NaN 6810 \n",
			"2355725 400002738 2582035.889 1251386.630 1004.0 1020.0 1110.0 6810 \n",
			"\n",
			" GDEKT \n",
			"0 ZH \n",
			"1 ZH \n",
			"2 ZH \n",
			"3 ZH \n",
			"4 ZH \n",
			"... ... \n",
			"2355720 JU \n",
			"2355721 JU \n",
			"2355722 JU \n",
			"2355724 JU \n",
			"2355725 JU \n",
			"\n",
			"[2238851 rows x 8 columns]"
			]
			},
			"execution_count": 5,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"BLD"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 6,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"2238851"
			]
			},
			"execution_count": 6,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"len(BLD)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 7,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"2238851"
			]
			},
			"execution_count": 7,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"len(BLD.EGID.unique())"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Dwelling information"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 8,
			"metadata": {},
			"outputs": [],
			"source": [
			"DWL_fp = 'GWR_MADD_WHG-10_Data_MADD-20200715-A3_20200722.dsv'\n",
			"DWL_cols = ['EGID', 'EWID', 'WSTAT', 'WNART']\n",
			"DWL = pd.read_csv(os.path.join(GWR_fp, DWL_fp), sep = '\\t', usecols = DWL_cols)\n",
			"\n",
			"# Extract only those dwellings that are currently active (\"Wohnung bestehend\")\n",
			"DWL = DWL[DWL.WSTAT == 3004]\n",
			"DWL = DWL.merge(GWR[['EGID', 'GDEKT']], on = 'EGID', how = 'left')"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 9,
			"metadata": {},
			"outputs": [
			{
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			" 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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
			" // select the cell after this one\n",
			" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
			" IPython.notebook.select(index + 1);\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": {
			"text/html": [
			"<img 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			"data": {
			"text/plain": [
			"<matplotlib.axes._subplots.AxesSubplot at 0x2b9c38c06d68>"
			]
			},
			"execution_count": 9,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"DWL.WNART.plot.hist(range = (3010, 3070), bins = 60)"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"# Aggregate dwelling information"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 10,
			"metadata": {},
			"outputs": [],
			"source": [
			"DWL_count = DWL.groupby('EGID').EWID.count()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 11,
			"metadata": {},
			"outputs": [],
			"source": [
			"BLD_w_dwell = BLD.merge(DWL_count.rename('N_DWELL'), left_on = 'EGID', right_index = True, how = 'left')"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 12,
			"metadata": {},
			"outputs": [
			{
			"data": {
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			" <thead>\n",
			" <tr style=\"text-align: right;\">\n",
			" <th></th>\n",
			" <th>EGID</th>\n",
			" <th>GKODE</th>\n",
			" <th>GKODN</th>\n",
			" <th>GSTAT</th>\n",
			" <th>GKAT</th>\n",
			" <th>GKLAS</th>\n",
			" <th>GGDENR</th>\n",
			" <th>GDEKT</th>\n",
			" <th>N_DWELL</th>\n",
			" </tr>\n",
			" </thead>\n",
			" <tbody>\n",
			" <tr>\n",
			" <th>0</th>\n",
			" <td>1600000</td>\n",
			" <td>2679684.326</td>\n",
			" <td>1237449.553</td>\n",
			" <td>1004.0</td>\n",
			" <td>1020.0</td>\n",
			" <td>1122.0</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>3.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>1</th>\n",
			" <td>1600001</td>\n",
			" <td>2679702.150</td>\n",
			" <td>1237493.958</td>\n",
			" <td>1004.0</td>\n",
			" <td>1030.0</td>\n",
			" <td>1110.0</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>1.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>2</th>\n",
			" <td>1600002</td>\n",
			" <td>2679713.052</td>\n",
			" <td>1237475.814</td>\n",
			" <td>1004.0</td>\n",
			" <td>1030.0</td>\n",
			" <td>1121.0</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>2.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>3</th>\n",
			" <td>1600003</td>\n",
			" <td>2679655.455</td>\n",
			" <td>1237516.450</td>\n",
			" <td>1004.0</td>\n",
			" <td>1020.0</td>\n",
			" <td>1122.0</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>3.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>4</th>\n",
			" <td>1600005</td>\n",
			" <td>2679749.269</td>\n",
			" <td>1237529.346</td>\n",
			" <td>1004.0</td>\n",
			" <td>1020.0</td>\n",
			" <td>1110.0</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>1.0</td>\n",
			" </tr>\n",
			" </tbody>\n",
			"</table>\n",
			"</div>"
			],
			"text/plain": [
			" EGID GKODE GKODN GSTAT GKAT GKLAS GGDENR GDEKT \\\n",
			"0 1600000 2679684.326 1237449.553 1004.0 1020.0 1122.0 1 ZH \n",
			"1 1600001 2679702.150 1237493.958 1004.0 1030.0 1110.0 1 ZH \n",
			"2 1600002 2679713.052 1237475.814 1004.0 1030.0 1121.0 1 ZH \n",
			"3 1600003 2679655.455 1237516.450 1004.0 1020.0 1122.0 1 ZH \n",
			"4 1600005 2679749.269 1237529.346 1004.0 1020.0 1110.0 1 ZH \n",
			"\n",
			" N_DWELL \n",
			"0 3.0 \n",
			"1 1.0 \n",
			"2 2.0 \n",
			"3 3.0 \n",
			"4 1.0 "
			]
			},
			"execution_count": 12,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"BLD_w_dwell.head()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 13,
			"metadata": {},
			"outputs": [],
			"source": [
			"BLD_wo_dwell = BLD_w_dwell[BLD_w_dwell.N_DWELL.isna()]"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 14,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/html": [
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			" <th></th>\n",
			" <th>EGID</th>\n",
			" <th>GKODE</th>\n",
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			" <th>GKLAS</th>\n",
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			" <th>N_DWELL</th>\n",
			" </tr>\n",
			" </thead>\n",
			" <tbody>\n",
			" <tr>\n",
			" <th>148</th>\n",
			" <td>1600164</td>\n",
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			" <td>1235705.939</td>\n",
			" <td>1004.0</td>\n",
			" <td>1060.0</td>\n",
			" <td>NaN</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>NaN</td>\n",
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			" <tr>\n",
			" <th>289</th>\n",
			" <td>2248722</td>\n",
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			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>NaN</td>\n",
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			" <tr>\n",
			" <th>297</th>\n",
			" <td>2331567</td>\n",
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			" <td>NaN</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>NaN</td>\n",
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			" <tr>\n",
			" <th>302</th>\n",
			" <td>2331626</td>\n",
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			" <td>1060.0</td>\n",
			" <td>NaN</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>NaN</td>\n",
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			" <tr>\n",
			" <th>474</th>\n",
			" <td>210059303</td>\n",
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			" <td>1264.0</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
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			" <td>1060.0</td>\n",
			" <td>1271.0</td>\n",
			" <td>6810</td>\n",
			" <td>JU</td>\n",
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			" <tr>\n",
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			" <td>6810</td>\n",
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			" <tr>\n",
			" <th>2355724</th>\n",
			" <td>400002737</td>\n",
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			" <td>6810</td>\n",
			" <td>JU</td>\n",
			" <td>NaN</td>\n",
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			"</table>\n",
			"<p>486819 rows × 9 columns</p>\n",
			"</div>"
			],
			"text/plain": [
			" EGID GKODE GKODN GSTAT GKAT GKLAS GGDENR \\\n",
			"148 1600164 2679245.818 1235705.939 1004.0 1060.0 NaN 1 \n",
			"289 2248722 2678955.717 1237813.694 1004.0 1060.0 NaN 1 \n",
			"297 2331567 2679303.568 1237620.968 1004.0 1060.0 NaN 1 \n",
			"302 2331626 2679253.787 1235848.235 1004.0 1060.0 NaN 1 \n",
			"474 210059303 2679006.578 1237791.709 1004.0 1040.0 1264.0 1 \n",
			"... ... ... ... ... ... ... ... \n",
			"2355685 190180356 2581597.698 1249749.147 1004.0 1060.0 1271.0 6810 \n",
			"2355697 190594811 2581218.955 1251349.763 1004.0 1060.0 1252.0 6810 \n",
			"2355720 400002687 2582696.000 1250531.000 1004.0 1060.0 1242.0 6810 \n",
			"2355722 400002734 2581458.869 1251234.498 1004.0 1060.0 NaN 6810 \n",
			"2355724 400002737 2582121.030 1251281.432 1004.0 1060.0 NaN 6810 \n",
			"\n",
			" GDEKT N_DWELL \n",
			"148 ZH NaN \n",
			"289 ZH NaN \n",
			"297 ZH NaN \n",
			"302 ZH NaN \n",
			"474 ZH NaN \n",
			"... ... ... \n",
			"2355685 JU NaN \n",
			"2355697 JU NaN \n",
			"2355720 JU NaN \n",
			"2355722 JU NaN \n",
			"2355724 JU NaN \n",
			"\n",
			"[486819 rows x 9 columns]"
			]
			},
			"execution_count": 14,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"BLD_wo_dwell"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 15,
			"metadata": {},
			"outputs": [
			{
			"data": {
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			" <td>1004.0</td>\n",
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			" <td>6810</td>\n",
			" <td>JU</td>\n",
			" <td>NaN</td>\n",
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			" </tbody>\n",
			"</table>\n",
			"<p>486819 rows × 9 columns</p>\n",
			"</div>"
			],
			"text/plain": [
			" EGID GKODE GKODN GSTAT GKAT GKLAS GGDENR \\\n",
			"148 1600164 2679245.818 1235705.939 1004.0 1060.0 NaN 1 \n",
			"289 2248722 2678955.717 1237813.694 1004.0 1060.0 NaN 1 \n",
			"297 2331567 2679303.568 1237620.968 1004.0 1060.0 NaN 1 \n",
			"302 2331626 2679253.787 1235848.235 1004.0 1060.0 NaN 1 \n",
			"474 210059303 2679006.578 1237791.709 1004.0 1040.0 1264.0 1 \n",
			"... ... ... ... ... ... ... ... \n",
			"2355685 190180356 2581597.698 1249749.147 1004.0 1060.0 1271.0 6810 \n",
			"2355697 190594811 2581218.955 1251349.763 1004.0 1060.0 1252.0 6810 \n",
			"2355720 400002687 2582696.000 1250531.000 1004.0 1060.0 1242.0 6810 \n",
			"2355722 400002734 2581458.869 1251234.498 1004.0 1060.0 NaN 6810 \n",
			"2355724 400002737 2582121.030 1251281.432 1004.0 1060.0 NaN 6810 \n",
			"\n",
			" GDEKT N_DWELL \n",
			"148 ZH NaN \n",
			"289 ZH NaN \n",
			"297 ZH NaN \n",
			"302 ZH NaN \n",
			"474 ZH NaN \n",
			"... ... ... \n",
			"2355685 JU NaN \n",
			"2355697 JU NaN \n",
			"2355720 JU NaN \n",
			"2355722 JU NaN \n",
			"2355724 JU NaN \n",
			"\n",
			"[486819 rows x 9 columns]"
			]
			},
			"execution_count": 15,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"BLD_wo_dwell"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 16,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"0.2174414465277055"
			]
			},
			"execution_count": 16,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"len(BLD_wo_dwell) / len(BLD_w_dwell)"
			]
			},
			{
			"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>EGID</th>\n",
			" <th>GKODE</th>\n",
			" <th>GKODN</th>\n",
			" <th>GSTAT</th>\n",
			" <th>GKAT</th>\n",
			" <th>GKLAS</th>\n",
			" <th>GGDENR</th>\n",
			" <th>N_DWELL</th>\n",
			" </tr>\n",
			" </thead>\n",
			" <tbody>\n",
			" <tr>\n",
			" <th>count</th>\n",
			" <td>2.238851e+06</td>\n",
			" <td>2.234544e+06</td>\n",
			" <td>2.234544e+06</td>\n",
			" <td>2238851.0</td>\n",
			" <td>2.238786e+06</td>\n",
			" <td>2.092268e+06</td>\n",
			" <td>2.238851e+06</td>\n",
			" <td>1.752032e+06</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>mean</th>\n",
			" <td>8.302224e+07</td>\n",
			" <td>2.650929e+06</td>\n",
			" <td>1.209844e+06</td>\n",
			" <td>1004.0</td>\n",
			" <td>1.030483e+03</td>\n",
			" <td>1.142526e+03</td>\n",
			" <td>2.958916e+03</td>\n",
			" <td>2.642059e+00</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>std</th>\n",
			" <td>1.200185e+08</td>\n",
			" <td>6.688400e+04</td>\n",
			" <td>5.232642e+04</td>\n",
			" <td>0.0</td>\n",
			" <td>1.705643e+01</td>\n",
			" <td>5.810497e+01</td>\n",
			" <td>2.140808e+03</td>\n",
			" <td>4.361880e+00</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>min</th>\n",
			" <td>1.000000e+00</td>\n",
			" <td>2.486181e+06</td>\n",
			" <td>1.075511e+06</td>\n",
			" <td>1004.0</td>\n",
			" <td>1.010000e+03</td>\n",
			" <td>1.110000e+03</td>\n",
			" <td>1.000000e+00</td>\n",
			" <td>1.000000e+00</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>25%</th>\n",
			" <td>8.232625e+05</td>\n",
			" <td>2.604458e+06</td>\n",
			" <td>1.175083e+06</td>\n",
			" <td>1004.0</td>\n",
			" <td>1.020000e+03</td>\n",
			" <td>1.110000e+03</td>\n",
			" <td>7.930000e+02</td>\n",
			" <td>1.000000e+00</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>50%</th>\n",
			" <td>1.725612e+06</td>\n",
			" <td>2.660103e+06</td>\n",
			" <td>1.226108e+06</td>\n",
			" <td>1004.0</td>\n",
			" <td>1.020000e+03</td>\n",
			" <td>1.110000e+03</td>\n",
			" <td>2.886000e+03</td>\n",
			" <td>1.000000e+00</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>75%</th>\n",
			" <td>1.911256e+08</td>\n",
			" <td>2.701770e+06</td>\n",
			" <td>1.252479e+06</td>\n",
			" <td>1004.0</td>\n",
			" <td>1.030000e+03</td>\n",
			" <td>1.122000e+03</td>\n",
			" <td>4.821000e+03</td>\n",
			" <td>2.000000e+00</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>max</th>\n",
			" <td>5.020145e+08</td>\n",
			" <td>2.832034e+06</td>\n",
			" <td>1.295317e+06</td>\n",
			" <td>1004.0</td>\n",
			" <td>1.080000e+03</td>\n",
			" <td>1.278000e+03</td>\n",
			" <td>6.810000e+03</td>\n",
			" <td>4.600000e+02</td>\n",
			" </tr>\n",
			" </tbody>\n",
			"</table>\n",
			"</div>"
			],
			"text/plain": [
			" EGID GKODE GKODN GSTAT GKAT \\\n",
			"count 2.238851e+06 2.234544e+06 2.234544e+06 2238851.0 2.238786e+06 \n",
			"mean 8.302224e+07 2.650929e+06 1.209844e+06 1004.0 1.030483e+03 \n",
			"std 1.200185e+08 6.688400e+04 5.232642e+04 0.0 1.705643e+01 \n",
			"min 1.000000e+00 2.486181e+06 1.075511e+06 1004.0 1.010000e+03 \n",
			"25% 8.232625e+05 2.604458e+06 1.175083e+06 1004.0 1.020000e+03 \n",
			"50% 1.725612e+06 2.660103e+06 1.226108e+06 1004.0 1.020000e+03 \n",
			"75% 1.911256e+08 2.701770e+06 1.252479e+06 1004.0 1.030000e+03 \n",
			"max 5.020145e+08 2.832034e+06 1.295317e+06 1004.0 1.080000e+03 \n",
			"\n",
			" GKLAS GGDENR N_DWELL \n",
			"count 2.092268e+06 2.238851e+06 1.752032e+06 \n",
			"mean 1.142526e+03 2.958916e+03 2.642059e+00 \n",
			"std 5.810497e+01 2.140808e+03 4.361880e+00 \n",
			"min 1.110000e+03 1.000000e+00 1.000000e+00 \n",
			"25% 1.110000e+03 7.930000e+02 1.000000e+00 \n",
			"50% 1.110000e+03 2.886000e+03 1.000000e+00 \n",
			"75% 1.122000e+03 4.821000e+03 2.000000e+00 \n",
			"max 1.278000e+03 6.810000e+03 4.600000e+02 "
			]
			},
			"execution_count": 17,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"BLD_w_dwell.describe()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 18,
			"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",
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			" } 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",
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			" this.supports_binary = (this.ws.binaryType != undefined);\n",
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			" 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",
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			" this.ws.onopen = function () {\n",
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			" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
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			" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
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			"\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",
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			"\n",
			"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
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			"\n",
			"\n",
			"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
			"\n",
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			"\n",
			"mpl.figure.prototype._init_canvas = function() {\n",
			" var fig = this;\n",
			"\n",
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			"\n",
			" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
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			"\n",
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			" 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",
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			"\n",
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			" pass_mouse_events = false;\n",
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			" 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",
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			" event.step = -1;\n",
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			" 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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
			" // select the cell after this one\n",
			" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
			" IPython.notebook.select(index + 1);\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"
			},
			{
			"data": {
			"text/plain": [
			"<matplotlib.legend.Legend at 0x2b9c38c1e710>"
			]
			},
			"execution_count": 18,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"plt.figure()\n",
			"BLD_w_dwell.N_DWELL.plot.hist(range = (1,50), bins = 49)\n",
			"plt.legend()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 19,
			"metadata": {
			"scrolled": false
			},
			"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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
			" // select the cell after this one\n",
			" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
			" IPython.notebook.select(index + 1);\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": {
			"text/html": [
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\" width=\"640\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/plain": [
			"<matplotlib.legend.Legend at 0x2b9c3af0a240>"
			]
			},
			"execution_count": 19,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"plt.figure()\n",
			"BLD_w_dwell.dropna(subset = ['N_DWELL']).GKAT.plot.hist(range = (1010, 1080), bins = 7, label = 'With dwelling info', alpha = 0.7)\n",
			"BLD_wo_dwell.GKAT.plot.hist(range = (1010, 1080), bins = 7, label = 'Without dwelling info', alpha = 0.7)\n",
			"plt.legend()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 20,
			"metadata": {
			"scrolled": false
			},
			"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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
			" // select the cell after this one\n",
			" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
			" IPython.notebook.select(index + 1);\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=\"640\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			},
			{
			"data": {
			"text/plain": [
			"<matplotlib.legend.Legend at 0x2b9c3b84bc88>"
			]
			},
			"execution_count": 20,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"plt.figure()\n",
			"BLD_w_dwell.dropna(subset = ['N_DWELL']).GKLAS.plot.hist(range = (1110, 1280), bins = 17, label = 'With dwelling info', alpha = 0.7)\n",
			"BLD_wo_dwell.GKLAS.plot.hist(range = (1110, 1280), bins = 17, label = 'Without dwelling info', alpha = 0.7)\n",
			"plt.legend()"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"# Estimate approximate energy demand\n",
			"Only information with entry in \"WHG\", but all \"WHG\" considered - anything with 1 WHG is a SFH, anything with > 1 WHG is a MFH."
			]
			},
			{
			"cell_type": "code",
			"execution_count": 21,
			"metadata": {},
			"outputs": [],
			"source": [
			"demand_fp = '/work/hyenergy/output/demand' # \n",
			"residential_demand = xr.open_dataset(os.path.join(demand_fp, 'electricity_demand_residential.nc')) "
			]
			},
			{
			"cell_type": "code",
			"execution_count": 22,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/html": [
			"<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
			"<defs>\n",
			"<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
			"<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
			"<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
			"<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
			"</symbol>\n",
			"<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
			"<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
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			"</defs>\n",
			"</svg>\n",
			"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
			" *\n",
			" */\n",
			"\n",
			":root {\n",
			" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
			" --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
			" --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
			" --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
			" --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
			" --xr-background-color: var(--jp-layout-color0, white);\n",
			" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
			" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
			"}\n",
			"\n",
			"html[theme=dark],\n",
			"body.vscode-dark {\n",
			" --xr-font-color0: rgba(255, 255, 255, 1);\n",
			" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
			" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
			" --xr-border-color: #1F1F1F;\n",
			" --xr-disabled-color: #515151;\n",
			" --xr-background-color: #111111;\n",
			" --xr-background-color-row-even: #111111;\n",
			" --xr-background-color-row-odd: #313131;\n",
			"}\n",
			"\n",
			".xr-wrap {\n",
			" display: block;\n",
			" min-width: 300px;\n",
			" max-width: 700px;\n",
			"}\n",
			"\n",
			".xr-text-repr-fallback {\n",
			" /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
			" display: none;\n",
			"}\n",
			"\n",
			".xr-header {\n",
			" padding-top: 6px;\n",
			" padding-bottom: 6px;\n",
			" margin-bottom: 4px;\n",
			" border-bottom: solid 1px var(--xr-border-color);\n",
			"}\n",
			"\n",
			".xr-header > div,\n",
			".xr-header > ul {\n",
			" display: inline;\n",
			" margin-top: 0;\n",
			" margin-bottom: 0;\n",
			"}\n",
			"\n",
			".xr-obj-type,\n",
			".xr-array-name {\n",
			" margin-left: 2px;\n",
			" margin-right: 10px;\n",
			"}\n",
			"\n",
			".xr-obj-type {\n",
			" color: var(--xr-font-color2);\n",
			"}\n",
			"\n",
			".xr-sections {\n",
			" padding-left: 0 !important;\n",
			" display: grid;\n",
			" grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
			"}\n",
			"\n",
			".xr-section-item {\n",
			" display: contents;\n",
			"}\n",
			"\n",
			".xr-section-item input {\n",
			" display: none;\n",
			"}\n",
			"\n",
			".xr-section-item input + label {\n",
			" color: var(--xr-disabled-color);\n",
			"}\n",
			"\n",
			".xr-section-item input:enabled + label {\n",
			" cursor: pointer;\n",
			" color: var(--xr-font-color2);\n",
			"}\n",
			"\n",
			".xr-section-item input:enabled + label:hover {\n",
			" color: var(--xr-font-color0);\n",
			"}\n",
			"\n",
			".xr-section-summary {\n",
			" grid-column: 1;\n",
			" color: var(--xr-font-color2);\n",
			" font-weight: 500;\n",
			"}\n",
			"\n",
			".xr-section-summary > span {\n",
			" display: inline-block;\n",
			" padding-left: 0.5em;\n",
			"}\n",
			"\n",
			".xr-section-summary-in:disabled + label {\n",
			" color: var(--xr-font-color2);\n",
			"}\n",
			"\n",
			".xr-section-summary-in + label:before {\n",
			" display: inline-block;\n",
			" content: '►';\n",
			" font-size: 11px;\n",
			" width: 15px;\n",
			" text-align: center;\n",
			"}\n",
			"\n",
			".xr-section-summary-in:disabled + label:before {\n",
			" color: var(--xr-disabled-color);\n",
			"}\n",
			"\n",
			".xr-section-summary-in:checked + label:before {\n",
			" content: '▼';\n",
			"}\n",
			"\n",
			".xr-section-summary-in:checked + label > span {\n",
			" display: none;\n",
			"}\n",
			"\n",
			".xr-section-summary,\n",
			".xr-section-inline-details {\n",
			" padding-top: 4px;\n",
			" padding-bottom: 4px;\n",
			"}\n",
			"\n",
			".xr-section-inline-details {\n",
			" grid-column: 2 / -1;\n",
			"}\n",
			"\n",
			".xr-section-details {\n",
			" display: none;\n",
			" grid-column: 1 / -1;\n",
			" margin-bottom: 5px;\n",
			"}\n",
			"\n",
			".xr-section-summary-in:checked ~ .xr-section-details {\n",
			" display: contents;\n",
			"}\n",
			"\n",
			".xr-array-wrap {\n",
			" grid-column: 1 / -1;\n",
			" display: grid;\n",
			" grid-template-columns: 20px auto;\n",
			"}\n",
			"\n",
			".xr-array-wrap > label {\n",
			" grid-column: 1;\n",
			" vertical-align: top;\n",
			"}\n",
			"\n",
			".xr-preview {\n",
			" color: var(--xr-font-color3);\n",
			"}\n",
			"\n",
			".xr-array-preview,\n",
			".xr-array-data {\n",
			" padding: 0 5px !important;\n",
			" grid-column: 2;\n",
			"}\n",
			"\n",
			".xr-array-data,\n",
			".xr-array-in:checked ~ .xr-array-preview {\n",
			" display: none;\n",
			"}\n",
			"\n",
			".xr-array-in:checked ~ .xr-array-data,\n",
			".xr-array-preview {\n",
			" display: inline-block;\n",
			"}\n",
			"\n",
			".xr-dim-list {\n",
			" display: inline-block !important;\n",
			" list-style: none;\n",
			" padding: 0 !important;\n",
			" margin: 0;\n",
			"}\n",
			"\n",
			".xr-dim-list li {\n",
			" display: inline-block;\n",
			" padding: 0;\n",
			" margin: 0;\n",
			"}\n",
			"\n",
			".xr-dim-list:before {\n",
			" content: '(';\n",
			"}\n",
			"\n",
			".xr-dim-list:after {\n",
			" content: ')';\n",
			"}\n",
			"\n",
			".xr-dim-list li:not(:last-child):after {\n",
			" content: ',';\n",
			" padding-right: 5px;\n",
			"}\n",
			"\n",
			".xr-has-index {\n",
			" font-weight: bold;\n",
			"}\n",
			"\n",
			".xr-var-list,\n",
			".xr-var-item {\n",
			" display: contents;\n",
			"}\n",
			"\n",
			".xr-var-item > div,\n",
			".xr-var-item label,\n",
			".xr-var-item > .xr-var-name span {\n",
			" background-color: var(--xr-background-color-row-even);\n",
			" margin-bottom: 0;\n",
			"}\n",
			"\n",
			".xr-var-item > .xr-var-name:hover span {\n",
			" padding-right: 5px;\n",
			"}\n",
			"\n",
			".xr-var-list > li:nth-child(odd) > div,\n",
			".xr-var-list > li:nth-child(odd) > label,\n",
			".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
			" background-color: var(--xr-background-color-row-odd);\n",
			"}\n",
			"\n",
			".xr-var-name {\n",
			" grid-column: 1;\n",
			"}\n",
			"\n",
			".xr-var-dims {\n",
			" grid-column: 2;\n",
			"}\n",
			"\n",
			".xr-var-dtype {\n",
			" grid-column: 3;\n",
			" text-align: right;\n",
			" color: var(--xr-font-color2);\n",
			"}\n",
			"\n",
			".xr-var-preview {\n",
			" grid-column: 4;\n",
			"}\n",
			"\n",
			".xr-var-name,\n",
			".xr-var-dims,\n",
			".xr-var-dtype,\n",
			".xr-preview,\n",
			".xr-attrs dt {\n",
			" white-space: nowrap;\n",
			" overflow: hidden;\n",
			" text-overflow: ellipsis;\n",
			" padding-right: 10px;\n",
			"}\n",
			"\n",
			".xr-var-name:hover,\n",
			".xr-var-dims:hover,\n",
			".xr-var-dtype:hover,\n",
			".xr-attrs dt:hover {\n",
			" overflow: visible;\n",
			" width: auto;\n",
			" z-index: 1;\n",
			"}\n",
			"\n",
			".xr-var-attrs,\n",
			".xr-var-data {\n",
			" display: none;\n",
			" background-color: var(--xr-background-color) !important;\n",
			" padding-bottom: 5px !important;\n",
			"}\n",
			"\n",
			".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
			".xr-var-data-in:checked ~ .xr-var-data {\n",
			" display: block;\n",
			"}\n",
			"\n",
			".xr-var-data > table {\n",
			" float: right;\n",
			"}\n",
			"\n",
			".xr-var-name span,\n",
			".xr-var-data,\n",
			".xr-attrs {\n",
			" padding-left: 25px !important;\n",
			"}\n",
			"\n",
			".xr-attrs,\n",
			".xr-var-attrs,\n",
			".xr-var-data {\n",
			" grid-column: 1 / -1;\n",
			"}\n",
			"\n",
			"dl.xr-attrs {\n",
			" padding: 0;\n",
			" margin: 0;\n",
			" display: grid;\n",
			" grid-template-columns: 125px auto;\n",
			"}\n",
			"\n",
			".xr-attrs dt, dd {\n",
			" padding: 0;\n",
			" margin: 0;\n",
			" float: left;\n",
			" padding-right: 10px;\n",
			" width: auto;\n",
			"}\n",
			"\n",
			".xr-attrs dt {\n",
			" font-weight: normal;\n",
			" grid-column: 1;\n",
			"}\n",
			"\n",
			".xr-attrs dt:hover span {\n",
			" display: inline-block;\n",
			" background: var(--xr-background-color);\n",
			" padding-right: 10px;\n",
			"}\n",
			"\n",
			".xr-attrs dd {\n",
			" grid-column: 2;\n",
			" white-space: pre-wrap;\n",
			" word-break: break-all;\n",
			"}\n",
			"\n",
			".xr-icon-database,\n",
			".xr-icon-file-text2 {\n",
			" display: inline-block;\n",
			" vertical-align: middle;\n",
			" width: 1em;\n",
			" height: 1.5em !important;\n",
			" stroke-width: 0;\n",
			" stroke: currentColor;\n",
			" fill: currentColor;\n",
			"}\n",
			"</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n",
			"Dimensions: (daytype: 2, timestamp: 288)\n",
			"Coordinates:\n",
			" * timestamp (timestamp) datetime64[ns] 2001-01-15 ... 2001-12-15T23:00:00\n",
			" * daytype (daytype) object 'weekday' 'weekend'\n",
			"Data variables:\n",
			" appart (timestamp, daytype) float64 162.3 181.7 141.5 ... 233.7 227.8\n",
			" maison (timestamp, daytype) float64 298.2 344.7 261.2 ... 377.5 411.3\n",
			" communal_app (timestamp, daytype) float64 78.93 102.5 74.45 ... 39.51 55.79</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-bc99ea05-1ff2-4980-86fb-6f5938f9b764' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bc99ea05-1ff2-4980-86fb-6f5938f9b764' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>daytype</span>: 2</li><li><span class='xr-has-index'>timestamp</span>: 288</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c2574ea8-85d1-461d-9893-df36ddd0f69d' class='xr-section-summary-in' type='checkbox' checked><label for='section-c2574ea8-85d1-461d-9893-df36ddd0f69d' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>timestamp</span></div><div class='xr-var-dims'>(timestamp)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2001-01-15 ... 2001-12-15T23:00:00</div><input id='attrs-c3e64032-624c-4eb6-acc1-c7721c5e936e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c3e64032-624c-4eb6-acc1-c7721c5e936e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c3eed7c-d0aa-4e90-bf0e-3d62cc269549' class='xr-var-data-in' type='checkbox'><label for='data-5c3eed7c-d0aa-4e90-bf0e-3d62cc269549' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(['2001-01-15T00:00:00.000000000', '2001-01-15T01:00:00.000000000',\n",
			" '2001-01-15T02:00:00.000000000', ..., '2001-12-15T21:00:00.000000000',\n",
			" '2001-12-15T22:00:00.000000000', '2001-12-15T23:00:00.000000000'],\n",
			" dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>daytype</span></div><div class='xr-var-dims'>(daytype)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>'weekday' 'weekend'</div><input id='attrs-2f347dff-a3cf-4a82-b062-8d7fee06bba2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2f347dff-a3cf-4a82-b062-8d7fee06bba2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d3dfb54-c0da-4e6d-b858-e982194e361a' class='xr-var-data-in' type='checkbox'><label for='data-7d3dfb54-c0da-4e6d-b858-e982194e361a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(['weekday', 'weekend'], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8b913e80-63c7-4b47-8595-8d2403059eca' class='xr-section-summary-in' type='checkbox' checked><label for='section-8b913e80-63c7-4b47-8595-8d2403059eca' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>appart</span></div><div class='xr-var-dims'>(timestamp, daytype)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8f2b071a-8e80-4e4a-abff-31e4344da20a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8f2b071a-8e80-4e4a-abff-31e4344da20a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe95b265-0dcd-42a0-a74b-761d9de0ea07' class='xr-var-data-in' type='checkbox'><label for='data-fe95b265-0dcd-42a0-a74b-761d9de0ea07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[162.267134, 181.725886],\n",
			" [141.511422, 147.918781],\n",
			" [128.611598, 133.756344],\n",
			" ...,\n",
			" [419.152541, 397.512196],\n",
			" [325.779659, 298.243901],\n",
			" [233.661016, 227.804876]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>maison</span></div><div class='xr-var-dims'>(timestamp, daytype)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5148bdc0-f14f-430a-82c4-577d3f5dc878' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5148bdc0-f14f-430a-82c4-577d3f5dc878' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff83113c-15c1-43de-a2b8-7f0fa3dddd1b' class='xr-var-data-in' type='checkbox'><label for='data-ff83113c-15c1-43de-a2b8-7f0fa3dddd1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[298.236713, 344.72222 ],\n",
			" [261.159419, 277.777777],\n",
			" [252.00483 , 259.861109],\n",
			" ...,\n",
			" [584.516907, 600.138891],\n",
			" [462.94686 , 511.527781],\n",
			" [377.487921, 411.250001]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>communal_app</span></div><div class='xr-var-dims'>(timestamp, daytype)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-93f422d5-4a79-4957-9375-0bc310dea7a7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-93f422d5-4a79-4957-9375-0bc310dea7a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4667d46-ec61-455e-a131-e1dc2cab0285' class='xr-var-data-in' type='checkbox'><label for='data-a4667d46-ec61-455e-a131-e1dc2cab0285' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 78.928615, 102.469514],\n",
			" [ 74.450955, 96.675081],\n",
			" [ 74.450955, 96.675081],\n",
			" ...,\n",
			" [ 47.892617, 57.937453],\n",
			" [ 37.279445, 52.63209 ],\n",
			" [ 39.51387 , 55.786709]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-24a63f65-489c-44a2-8400-511152809903' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-24a63f65-489c-44a2-8400-511152809903' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
			],
			"text/plain": [
			"<xarray.Dataset>\n",
			"Dimensions: (daytype: 2, timestamp: 288)\n",
			"Coordinates:\n",
			" * timestamp (timestamp) datetime64[ns] 2001-01-15 ... 2001-12-15T23:00:00\n",
			" * daytype (daytype) object 'weekday' 'weekend'\n",
			"Data variables:\n",
			" appart (timestamp, daytype) float64 ...\n",
			" maison (timestamp, daytype) float64 ...\n",
			" communal_app (timestamp, daytype) float64 ..."
			]
			},
			"execution_count": 22,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"residential_demand"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"### Compute national statistics"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 23,
			"metadata": {},
			"outputs": [],
			"source": [
			"BLD_dwell = BLD_w_dwell.dropna(subset = ['N_DWELL'])\n",
			"SFH = BLD_dwell[BLD_dwell.N_DWELL == 1]\n",
			"MFH = BLD_dwell[BLD_dwell.N_DWELL > 1]"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 24,
			"metadata": {},
			"outputs": [],
			"source": [
			"residential_demand['N_SFH_CH'] = len(SFH)\n",
			"residential_demand['N_DWELL_CH'] = len(DWL[DWL.EGID.isin(MFH.EGID)])"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 25,
			"metadata": {},
			"outputs": [],
			"source": [
			"residential_demand['demand_CH'] = ( residential_demand['N_SFH_CH'] * residential_demand['maison'] \n",
			" + residential_demand['N_DWELL_CH'] * ( residential_demand['appart'] \n",
			" + residential_demand['communal_app'] ) ) / 1e9"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 26,
			"metadata": {},
			"outputs": [
			{
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			"array(14263.29257344)</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7f5d4374-3bb6-406d-bed9-c8b1b253bc26' class='xr-array-in' type='checkbox' checked><label for='section-7f5d4374-3bb6-406d-bed9-c8b1b253bc26' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.426e+04</span></div><div class='xr-array-data'><pre>array(14263.29257344)</pre></div></div></li><li class='xr-section-item'><input id='section-9f31efc2-e820-4f15-bced-048d7899cbaa' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9f31efc2-e820-4f15-bced-048d7899cbaa' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-28dd3704-1a03-4cb5-9ec7-8e67f5c613b3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-28dd3704-1a03-4cb5-9ec7-8e67f5c613b3' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
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			},
			"execution_count": 26,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"get_yearly_sum(residential_demand, var = 'demand_CH')"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 27,
			"metadata": {},
			"outputs": [
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			"<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
			" *\n",
			" */\n",
			"\n",
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			" --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
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			" --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
			" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
			"}\n",
			"\n",
			"html[theme=dark],\n",
			"body.vscode-dark {\n",
			" --xr-font-color0: rgba(255, 255, 255, 1);\n",
			" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
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			" --xr-background-color: #111111;\n",
			" --xr-background-color-row-even: #111111;\n",
			" --xr-background-color-row-odd: #313131;\n",
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			"\n",
			".xr-wrap {\n",
			" display: block;\n",
			" min-width: 300px;\n",
			" max-width: 700px;\n",
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			"\n",
			".xr-text-repr-fallback {\n",
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			"\n",
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			" padding-bottom: 6px;\n",
			" margin-bottom: 4px;\n",
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			"\n",
			".xr-header > div,\n",
			".xr-header > ul {\n",
			" display: inline;\n",
			" margin-top: 0;\n",
			" margin-bottom: 0;\n",
			"}\n",
			"\n",
			".xr-obj-type,\n",
			".xr-array-name {\n",
			" margin-left: 2px;\n",
			" margin-right: 10px;\n",
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			"\n",
			".xr-obj-type {\n",
			" color: var(--xr-font-color2);\n",
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			"\n",
			".xr-sections {\n",
			" padding-left: 0 !important;\n",
			" display: grid;\n",
			" grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
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			"\n",
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			"\n",
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			"\n",
			".xr-section-item input:enabled + label {\n",
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			"\n",
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			" color: var(--xr-font-color2);\n",
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			"\n",
			".xr-section-summary > span {\n",
			" display: inline-block;\n",
			" padding-left: 0.5em;\n",
			"}\n",
			"\n",
			".xr-section-summary-in:disabled + label {\n",
			" color: var(--xr-font-color2);\n",
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			"\n",
			".xr-section-summary-in + label:before {\n",
			" display: inline-block;\n",
			" content: '►';\n",
			" font-size: 11px;\n",
			" width: 15px;\n",
			" text-align: center;\n",
			"}\n",
			"\n",
			".xr-section-summary-in:disabled + label:before {\n",
			" color: var(--xr-disabled-color);\n",
			"}\n",
			"\n",
			".xr-section-summary-in:checked + label:before {\n",
			" content: '▼';\n",
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			"\n",
			".xr-section-summary-in:checked + label > span {\n",
			" display: none;\n",
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			"\n",
			".xr-section-summary,\n",
			".xr-section-inline-details {\n",
			" padding-top: 4px;\n",
			" padding-bottom: 4px;\n",
			"}\n",
			"\n",
			".xr-section-inline-details {\n",
			" grid-column: 2 / -1;\n",
			"}\n",
			"\n",
			".xr-section-details {\n",
			" display: none;\n",
			" grid-column: 1 / -1;\n",
			" margin-bottom: 5px;\n",
			"}\n",
			"\n",
			".xr-section-summary-in:checked ~ .xr-section-details {\n",
			" display: contents;\n",
			"}\n",
			"\n",
			".xr-array-wrap {\n",
			" grid-column: 1 / -1;\n",
			" display: grid;\n",
			" grid-template-columns: 20px auto;\n",
			"}\n",
			"\n",
			".xr-array-wrap > label {\n",
			" grid-column: 1;\n",
			" vertical-align: top;\n",
			"}\n",
			"\n",
			".xr-preview {\n",
			" color: var(--xr-font-color3);\n",
			"}\n",
			"\n",
			".xr-array-preview,\n",
			".xr-array-data {\n",
			" padding: 0 5px !important;\n",
			" grid-column: 2;\n",
			"}\n",
			"\n",
			".xr-array-data,\n",
			".xr-array-in:checked ~ .xr-array-preview {\n",
			" display: none;\n",
			"}\n",
			"\n",
			".xr-array-in:checked ~ .xr-array-data,\n",
			".xr-array-preview {\n",
			" display: inline-block;\n",
			"}\n",
			"\n",
			".xr-dim-list {\n",
			" display: inline-block !important;\n",
			" list-style: none;\n",
			" padding: 0 !important;\n",
			" margin: 0;\n",
			"}\n",
			"\n",
			".xr-dim-list li {\n",
			" display: inline-block;\n",
			" padding: 0;\n",
			" margin: 0;\n",
			"}\n",
			"\n",
			".xr-dim-list:before {\n",
			" content: '(';\n",
			"}\n",
			"\n",
			".xr-dim-list:after {\n",
			" content: ')';\n",
			"}\n",
			"\n",
			".xr-dim-list li:not(:last-child):after {\n",
			" content: ',';\n",
			" padding-right: 5px;\n",
			"}\n",
			"\n",
			".xr-has-index {\n",
			" font-weight: bold;\n",
			"}\n",
			"\n",
			".xr-var-list,\n",
			".xr-var-item {\n",
			" display: contents;\n",
			"}\n",
			"\n",
			".xr-var-item > div,\n",
			".xr-var-item label,\n",
			".xr-var-item > .xr-var-name span {\n",
			" background-color: var(--xr-background-color-row-even);\n",
			" margin-bottom: 0;\n",
			"}\n",
			"\n",
			".xr-var-item > .xr-var-name:hover span {\n",
			" padding-right: 5px;\n",
			"}\n",
			"\n",
			".xr-var-list > li:nth-child(odd) > div,\n",
			".xr-var-list > li:nth-child(odd) > label,\n",
			".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
			" background-color: var(--xr-background-color-row-odd);\n",
			"}\n",
			"\n",
			".xr-var-name {\n",
			" grid-column: 1;\n",
			"}\n",
			"\n",
			".xr-var-dims {\n",
			" grid-column: 2;\n",
			"}\n",
			"\n",
			".xr-var-dtype {\n",
			" grid-column: 3;\n",
			" text-align: right;\n",
			" color: var(--xr-font-color2);\n",
			"}\n",
			"\n",
			".xr-var-preview {\n",
			" grid-column: 4;\n",
			"}\n",
			"\n",
			".xr-var-name,\n",
			".xr-var-dims,\n",
			".xr-var-dtype,\n",
			".xr-preview,\n",
			".xr-attrs dt {\n",
			" white-space: nowrap;\n",
			" overflow: hidden;\n",
			" text-overflow: ellipsis;\n",
			" padding-right: 10px;\n",
			"}\n",
			"\n",
			".xr-var-name:hover,\n",
			".xr-var-dims:hover,\n",
			".xr-var-dtype:hover,\n",
			".xr-attrs dt:hover {\n",
			" overflow: visible;\n",
			" width: auto;\n",
			" z-index: 1;\n",
			"}\n",
			"\n",
			".xr-var-attrs,\n",
			".xr-var-data {\n",
			" display: none;\n",
			" background-color: var(--xr-background-color) !important;\n",
			" padding-bottom: 5px !important;\n",
			"}\n",
			"\n",
			".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
			".xr-var-data-in:checked ~ .xr-var-data {\n",
			" display: block;\n",
			"}\n",
			"\n",
			".xr-var-data > table {\n",
			" float: right;\n",
			"}\n",
			"\n",
			".xr-var-name span,\n",
			".xr-var-data,\n",
			".xr-attrs {\n",
			" padding-left: 25px !important;\n",
			"}\n",
			"\n",
			".xr-attrs,\n",
			".xr-var-attrs,\n",
			".xr-var-data {\n",
			" grid-column: 1 / -1;\n",
			"}\n",
			"\n",
			"dl.xr-attrs {\n",
			" padding: 0;\n",
			" margin: 0;\n",
			" display: grid;\n",
			" grid-template-columns: 125px auto;\n",
			"}\n",
			"\n",
			".xr-attrs dt, dd {\n",
			" padding: 0;\n",
			" margin: 0;\n",
			" float: left;\n",
			" padding-right: 10px;\n",
			" width: auto;\n",
			"}\n",
			"\n",
			".xr-attrs dt {\n",
			" font-weight: normal;\n",
			" grid-column: 1;\n",
			"}\n",
			"\n",
			".xr-attrs dt:hover span {\n",
			" display: inline-block;\n",
			" background: var(--xr-background-color);\n",
			" padding-right: 10px;\n",
			"}\n",
			"\n",
			".xr-attrs dd {\n",
			" grid-column: 2;\n",
			" white-space: pre-wrap;\n",
			" word-break: break-all;\n",
			"}\n",
			"\n",
			".xr-icon-database,\n",
			".xr-icon-file-text2 {\n",
			" display: inline-block;\n",
			" vertical-align: middle;\n",
			" width: 1em;\n",
			" height: 1.5em !important;\n",
			" stroke-width: 0;\n",
			" stroke: currentColor;\n",
			" fill: currentColor;\n",
			"}\n",
			"</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n",
			"Dimensions: (daytype: 2, timestamp: 288)\n",
			"Coordinates:\n",
			" * timestamp (timestamp) datetime64[ns] 2001-01-15 ... 2001-12-15T23:00:00\n",
			" * daytype (daytype) object 'weekday' 'weekend'\n",
			"Data variables:\n",
			" appart (timestamp, daytype) float64 162.3 181.7 141.5 ... 233.7 227.8\n",
			" maison (timestamp, daytype) float64 298.2 344.7 261.2 ... 377.5 411.3\n",
			" communal_app (timestamp, daytype) float64 78.93 102.5 74.45 ... 39.51 55.79\n",
			" N_SFH_CH int64 1129018\n",
			" N_DWELL_CH int64 3499954\n",
			" demand_CH (timestamp, daytype) float64 1.181 1.384 1.051 ... 1.382 1.457</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ed3a2356-4e00-47fd-af33-f5b1e9a0fd40' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ed3a2356-4e00-47fd-af33-f5b1e9a0fd40' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>daytype</span>: 2</li><li><span class='xr-has-index'>timestamp</span>: 288</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-75171493-8c2f-4458-bb53-b8fedd28aec2' class='xr-section-summary-in' type='checkbox' checked><label for='section-75171493-8c2f-4458-bb53-b8fedd28aec2' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>timestamp</span></div><div class='xr-var-dims'>(timestamp)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2001-01-15 ... 2001-12-15T23:00:00</div><input id='attrs-3c0c926a-d688-48d0-9e1d-7c02b0076631' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3c0c926a-d688-48d0-9e1d-7c02b0076631' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c685e29c-df68-48a9-bb68-3ccf1c0a6975' class='xr-var-data-in' type='checkbox'><label for='data-c685e29c-df68-48a9-bb68-3ccf1c0a6975' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(['2001-01-15T00:00:00.000000000', '2001-01-15T01:00:00.000000000',\n",
			" '2001-01-15T02:00:00.000000000', ..., '2001-12-15T21:00:00.000000000',\n",
			" '2001-12-15T22:00:00.000000000', '2001-12-15T23:00:00.000000000'],\n",
			" dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>daytype</span></div><div class='xr-var-dims'>(daytype)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>'weekday' 'weekend'</div><input id='attrs-4b53a2f6-e00b-4e0c-95d7-50ba99c0cdee' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4b53a2f6-e00b-4e0c-95d7-50ba99c0cdee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a608795-f61a-4035-99b9-6629bfcdcd63' class='xr-var-data-in' type='checkbox'><label for='data-6a608795-f61a-4035-99b9-6629bfcdcd63' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(['weekday', 'weekend'], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8faf5e68-672b-4171-8a47-8ca9a9873f14' class='xr-section-summary-in' type='checkbox' checked><label for='section-8faf5e68-672b-4171-8a47-8ca9a9873f14' class='xr-section-summary' >Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>appart</span></div><div class='xr-var-dims'>(timestamp, daytype)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>162.3 181.7 141.5 ... 233.7 227.8</div><input id='attrs-3b61fc28-6d2b-467e-b5ef-3119d862e2aa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b61fc28-6d2b-467e-b5ef-3119d862e2aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b47369e-4d07-4bd4-9fb5-439afb8e9266' class='xr-var-data-in' type='checkbox'><label for='data-9b47369e-4d07-4bd4-9fb5-439afb8e9266' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[162.267134, 181.725886],\n",
			" [141.511422, 147.918781],\n",
			" [128.611598, 133.756344],\n",
			" ...,\n",
			" [419.152541, 397.512196],\n",
			" [325.779659, 298.243901],\n",
			" [233.661016, 227.804876]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>maison</span></div><div class='xr-var-dims'>(timestamp, daytype)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>298.2 344.7 261.2 ... 377.5 411.3</div><input id='attrs-dda9aea1-71c1-4b00-9582-aac78739ec0f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dda9aea1-71c1-4b00-9582-aac78739ec0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c672ce0d-02ee-4980-a400-89298a4d401a' class='xr-var-data-in' type='checkbox'><label for='data-c672ce0d-02ee-4980-a400-89298a4d401a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[298.236713, 344.72222 ],\n",
			" [261.159419, 277.777777],\n",
			" [252.00483 , 259.861109],\n",
			" ...,\n",
			" [584.516907, 600.138891],\n",
			" [462.94686 , 511.527781],\n",
			" [377.487921, 411.250001]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>communal_app</span></div><div class='xr-var-dims'>(timestamp, daytype)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>78.93 102.5 74.45 ... 39.51 55.79</div><input id='attrs-9d77a2e8-f6ac-4d34-b880-8410068ec48d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9d77a2e8-f6ac-4d34-b880-8410068ec48d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-197970ff-ba2f-4468-8e49-085a3d442941' class='xr-var-data-in' type='checkbox'><label for='data-197970ff-ba2f-4468-8e49-085a3d442941' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 78.928615, 102.469514],\n",
			" [ 74.450955, 96.675081],\n",
			" [ 74.450955, 96.675081],\n",
			" ...,\n",
			" [ 47.892617, 57.937453],\n",
			" [ 37.279445, 52.63209 ],\n",
			" [ 39.51387 , 55.786709]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N_SFH_CH</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1129018</div><input id='attrs-2105a346-63d9-4b04-8b91-f9f1faf2e400' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2105a346-63d9-4b04-8b91-f9f1faf2e400' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0078b651-1c0b-4132-ad89-0eb9d07d87a7' class='xr-var-data-in' type='checkbox'><label for='data-0078b651-1c0b-4132-ad89-0eb9d07d87a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(1129018)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N_DWELL_CH</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>3499954</div><input id='attrs-6fa9dd75-a7ab-4d0a-b33b-534307ba81cb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6fa9dd75-a7ab-4d0a-b33b-534307ba81cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6404d3d-e8c5-4b4b-aa74-75133a75b74e' class='xr-var-data-in' type='checkbox'><label for='data-d6404d3d-e8c5-4b4b-aa74-75133a75b74e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(3499954)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>demand_CH</span></div><div class='xr-var-dims'>(timestamp, daytype)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.181 1.384 1.051 ... 1.382 1.457</div><input id='attrs-b76c200c-900d-4942-8156-a916af9eb4c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b76c200c-900d-4942-8156-a916af9eb4c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f46e477-b91f-4425-92db-e40165962f59' class='xr-var-data-in' type='checkbox'><label for='data-7f46e477-b91f-4425-92db-e40165962f59' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[1.18088864, 1.38386842],\n",
			" [1.05071207, 1.16968338],\n",
			" [0.99522758, 1.09988726],\n",
			" [0.9818991 , 1.06211953],\n",
			" [0.98282883, 1.06026792],\n",
			" [1.04913918, 1.07913394],\n",
			" [1.37091423, 1.16905806],\n",
			" [1.6193158 , 1.44891639],\n",
			" [1.74584977, 1.76172011],\n",
			" [1.8343837 , 2.20234303],\n",
			" [1.99412028, 2.66018786],\n",
			" [2.70988802, 2.83764227],\n",
			" [2.55078171, 3.08354604],\n",
			" [2.22444157, 2.73753447],\n",
			" [2.08435846, 2.68827119],\n",
			" [1.8984686 , 2.55863822],\n",
			" [1.96553125, 2.61502543],\n",
			" [2.58377525, 3.11161669],\n",
			" [3.32437602, 3.5345543 ],\n",
			" [2.97071322, 2.98105277],\n",
			"...\n",
			" [0.82563854, 0.89720458],\n",
			" [0.88456615, 0.90155178],\n",
			" [1.13921138, 0.9473068 ],\n",
			" [1.41733713, 1.1949344 ],\n",
			" [1.55824794, 1.61319947],\n",
			" [1.69499529, 2.03961787],\n",
			" [1.79902986, 2.25554299],\n",
			" [2.39022011, 2.7251954 ],\n",
			" [2.27487502, 2.7743297 ],\n",
			" [2.12823549, 2.31738737],\n",
			" [1.87151788, 2.38040541],\n",
			" [1.74850835, 2.33628419],\n",
			" [1.93654955, 2.38649693],\n",
			" [2.55446196, 2.94443425],\n",
			" [3.02141284, 3.15191803],\n",
			" [2.84481709, 2.78985428],\n",
			" [2.58878709, 2.50373998],\n",
			" [2.29456668, 2.27162043],\n",
			" [1.7933655 , 1.8055739 ],\n",
			" [1.38229019, 1.45686616]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bcfc528c-bfb9-49ed-a9a4-467a4627baff' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bcfc528c-bfb9-49ed-a9a4-467a4627baff' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
			],
			"text/plain": [
			"<xarray.Dataset>\n",
			"Dimensions: (daytype: 2, timestamp: 288)\n",
			"Coordinates:\n",
			" * timestamp (timestamp) datetime64[ns] 2001-01-15 ... 2001-12-15T23:00:00\n",
			" * daytype (daytype) object 'weekday' 'weekend'\n",
			"Data variables:\n",
			" appart (timestamp, daytype) float64 162.3 181.7 141.5 ... 233.7 227.8\n",
			" maison (timestamp, daytype) float64 298.2 344.7 261.2 ... 377.5 411.3\n",
			" communal_app (timestamp, daytype) float64 78.93 102.5 74.45 ... 39.51 55.79\n",
			" N_SFH_CH int64 1129018\n",
			" N_DWELL_CH int64 3499954\n",
			" demand_CH (timestamp, daytype) float64 1.181 1.384 1.051 ... 1.382 1.457"
			]
			},
			"execution_count": 27,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"residential_demand"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"## Save GWR"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 28,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/html": [
			"<div>\n",
			"<style scoped>\n",
			" .dataframe tbody tr th:only-of-type {\n",
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			"\n",
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			"</style>\n",
			"<table border=\"1\" class=\"dataframe\">\n",
			" <thead>\n",
			" <tr style=\"text-align: right;\">\n",
			" <th></th>\n",
			" <th>EGID</th>\n",
			" <th>GKODE</th>\n",
			" <th>GKODN</th>\n",
			" <th>GSTAT</th>\n",
			" <th>GKAT</th>\n",
			" <th>GKLAS</th>\n",
			" <th>GGDENR</th>\n",
			" <th>GDEKT</th>\n",
			" <th>N_DWELL</th>\n",
			" </tr>\n",
			" </thead>\n",
			" <tbody>\n",
			" <tr>\n",
			" <th>0</th>\n",
			" <td>1600000</td>\n",
			" <td>2679684.326</td>\n",
			" <td>1237449.553</td>\n",
			" <td>1004.0</td>\n",
			" <td>1020.0</td>\n",
			" <td>1122.0</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>3.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>1</th>\n",
			" <td>1600001</td>\n",
			" <td>2679702.150</td>\n",
			" <td>1237493.958</td>\n",
			" <td>1004.0</td>\n",
			" <td>1030.0</td>\n",
			" <td>1110.0</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>1.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>2</th>\n",
			" <td>1600002</td>\n",
			" <td>2679713.052</td>\n",
			" <td>1237475.814</td>\n",
			" <td>1004.0</td>\n",
			" <td>1030.0</td>\n",
			" <td>1121.0</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>2.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>3</th>\n",
			" <td>1600003</td>\n",
			" <td>2679655.455</td>\n",
			" <td>1237516.450</td>\n",
			" <td>1004.0</td>\n",
			" <td>1020.0</td>\n",
			" <td>1122.0</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>3.0</td>\n",
			" </tr>\n",
			" <tr>\n",
			" <th>4</th>\n",
			" <td>1600005</td>\n",
			" <td>2679749.269</td>\n",
			" <td>1237529.346</td>\n",
			" <td>1004.0</td>\n",
			" <td>1020.0</td>\n",
			" <td>1110.0</td>\n",
			" <td>1</td>\n",
			" <td>ZH</td>\n",
			" <td>1.0</td>\n",
			" </tr>\n",
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			"text/plain": [
			" EGID GKODE GKODN GSTAT GKAT GKLAS GGDENR GDEKT \\\n",
			"0 1600000 2679684.326 1237449.553 1004.0 1020.0 1122.0 1 ZH \n",
			"1 1600001 2679702.150 1237493.958 1004.0 1030.0 1110.0 1 ZH \n",
			"2 1600002 2679713.052 1237475.814 1004.0 1030.0 1121.0 1 ZH \n",
			"3 1600003 2679655.455 1237516.450 1004.0 1020.0 1122.0 1 ZH \n",
			"4 1600005 2679749.269 1237529.346 1004.0 1020.0 1110.0 1 ZH \n",
			"\n",
			" N_DWELL \n",
			"0 3.0 \n",
			"1 1.0 \n",
			"2 2.0 \n",
			"3 3.0 \n",
			"4 1.0 "
			]
			},
			"execution_count": 28,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"BLD_dwell.head()"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 29,
			"metadata": {},
			"outputs": [],
			"source": [
			"BLD_dwell.to_csv(os.path.join(GWR_fp, 'GWR_GEB_w_N_WHG.csv'), index = False)"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"# Define function to get demand of cluster"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 30,
			"metadata": {},
			"outputs": [],
			"source": [
			"def get_cluster_demand(BLD_df, demand, dwell_nb = 'N_DWELL', \n",
			" SFH_demand = 'maison', MFH_demand = 'appart', comm_demand = 'communal_app'):\n",
			"\n",
			" SFH = BLD_df[BLD_df[dwell_nb] == 1]\n",
			" MFH = BLD_df[BLD_df[dwell_nb] > 1]\n",
			" \n",
			" building_counts = { 'N_SFH' : len(SFH),\n",
			" 'N_DWELL' : MFH[dwell_nb].sum() }\n",
			" \n",
			" cluster_demand = ( building_counts['N_SFH'] * demand[SFH_demand] \n",
			" + building_counts['N_DWELL'] * (demand[MFH_demand] + demand[comm_demand]) )\n",
			" \n",
			" return [ cluster_demand, building_counts ]"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 31,
			"metadata": {},
			"outputs": [],
			"source": [
			"demand, counts = get_cluster_demand(BLD_dwell[BLD_dwell.GDEKT == 'ZH'], residential_demand)"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 32,
			"metadata": {},
			"outputs": [
			{
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			"\n",
			".xr-section-summary-in:checked + label:before {\n",
			" content: '▼';\n",
			"}\n",
			"\n",
			".xr-section-summary-in:checked + label > span {\n",
			" display: none;\n",
			"}\n",
			"\n",
			".xr-section-summary,\n",
			".xr-section-inline-details {\n",
			" padding-top: 4px;\n",
			" padding-bottom: 4px;\n",
			"}\n",
			"\n",
			".xr-section-inline-details {\n",
			" grid-column: 2 / -1;\n",
			"}\n",
			"\n",
			".xr-section-details {\n",
			" display: none;\n",
			" grid-column: 1 / -1;\n",
			" margin-bottom: 5px;\n",
			"}\n",
			"\n",
			".xr-section-summary-in:checked ~ .xr-section-details {\n",
			" display: contents;\n",
			"}\n",
			"\n",
			".xr-array-wrap {\n",
			" grid-column: 1 / -1;\n",
			" display: grid;\n",
			" grid-template-columns: 20px auto;\n",
			"}\n",
			"\n",
			".xr-array-wrap > label {\n",
			" grid-column: 1;\n",
			" vertical-align: top;\n",
			"}\n",
			"\n",
			".xr-preview {\n",
			" color: var(--xr-font-color3);\n",
			"}\n",
			"\n",
			".xr-array-preview,\n",
			".xr-array-data {\n",
			" padding: 0 5px !important;\n",
			" grid-column: 2;\n",
			"}\n",
			"\n",
			".xr-array-data,\n",
			".xr-array-in:checked ~ .xr-array-preview {\n",
			" display: none;\n",
			"}\n",
			"\n",
			".xr-array-in:checked ~ .xr-array-data,\n",
			".xr-array-preview {\n",
			" display: inline-block;\n",
			"}\n",
			"\n",
			".xr-dim-list {\n",
			" display: inline-block !important;\n",
			" list-style: none;\n",
			" padding: 0 !important;\n",
			" margin: 0;\n",
			"}\n",
			"\n",
			".xr-dim-list li {\n",
			" display: inline-block;\n",
			" padding: 0;\n",
			" margin: 0;\n",
			"}\n",
			"\n",
			".xr-dim-list:before {\n",
			" content: '(';\n",
			"}\n",
			"\n",
			".xr-dim-list:after {\n",
			" content: ')';\n",
			"}\n",
			"\n",
			".xr-dim-list li:not(:last-child):after {\n",
			" content: ',';\n",
			" padding-right: 5px;\n",
			"}\n",
			"\n",
			".xr-has-index {\n",
			" font-weight: bold;\n",
			"}\n",
			"\n",
			".xr-var-list,\n",
			".xr-var-item {\n",
			" display: contents;\n",
			"}\n",
			"\n",
			".xr-var-item > div,\n",
			".xr-var-item label,\n",
			".xr-var-item > .xr-var-name span {\n",
			" background-color: var(--xr-background-color-row-even);\n",
			" margin-bottom: 0;\n",
			"}\n",
			"\n",
			".xr-var-item > .xr-var-name:hover span {\n",
			" padding-right: 5px;\n",
			"}\n",
			"\n",
			".xr-var-list > li:nth-child(odd) > div,\n",
			".xr-var-list > li:nth-child(odd) > label,\n",
			".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
			" background-color: var(--xr-background-color-row-odd);\n",
			"}\n",
			"\n",
			".xr-var-name {\n",
			" grid-column: 1;\n",
			"}\n",
			"\n",
			".xr-var-dims {\n",
			" grid-column: 2;\n",
			"}\n",
			"\n",
			".xr-var-dtype {\n",
			" grid-column: 3;\n",
			" text-align: right;\n",
			" color: var(--xr-font-color2);\n",
			"}\n",
			"\n",
			".xr-var-preview {\n",
			" grid-column: 4;\n",
			"}\n",
			"\n",
			".xr-var-name,\n",
			".xr-var-dims,\n",
			".xr-var-dtype,\n",
			".xr-preview,\n",
			".xr-attrs dt {\n",
			" white-space: nowrap;\n",
			" overflow: hidden;\n",
			" text-overflow: ellipsis;\n",
			" padding-right: 10px;\n",
			"}\n",
			"\n",
			".xr-var-name:hover,\n",
			".xr-var-dims:hover,\n",
			".xr-var-dtype:hover,\n",
			".xr-attrs dt:hover {\n",
			" overflow: visible;\n",
			" width: auto;\n",
			" z-index: 1;\n",
			"}\n",
			"\n",
			".xr-var-attrs,\n",
			".xr-var-data {\n",
			" display: none;\n",
			" background-color: var(--xr-background-color) !important;\n",
			" padding-bottom: 5px !important;\n",
			"}\n",
			"\n",
			".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
			".xr-var-data-in:checked ~ .xr-var-data {\n",
			" display: block;\n",
			"}\n",
			"\n",
			".xr-var-data > table {\n",
			" float: right;\n",
			"}\n",
			"\n",
			".xr-var-name span,\n",
			".xr-var-data,\n",
			".xr-attrs {\n",
			" padding-left: 25px !important;\n",
			"}\n",
			"\n",
			".xr-attrs,\n",
			".xr-var-attrs,\n",
			".xr-var-data {\n",
			" grid-column: 1 / -1;\n",
			"}\n",
			"\n",
			"dl.xr-attrs {\n",
			" padding: 0;\n",
			" margin: 0;\n",
			" display: grid;\n",
			" grid-template-columns: 125px auto;\n",
			"}\n",
			"\n",
			".xr-attrs dt, dd {\n",
			" padding: 0;\n",
			" margin: 0;\n",
			" float: left;\n",
			" padding-right: 10px;\n",
			" width: auto;\n",
			"}\n",
			"\n",
			".xr-attrs dt {\n",
			" font-weight: normal;\n",
			" grid-column: 1;\n",
			"}\n",
			"\n",
			".xr-attrs dt:hover span {\n",
			" display: inline-block;\n",
			" background: var(--xr-background-color);\n",
			" padding-right: 10px;\n",
			"}\n",
			"\n",
			".xr-attrs dd {\n",
			" grid-column: 2;\n",
			" white-space: pre-wrap;\n",
			" word-break: break-all;\n",
			"}\n",
			"\n",
			".xr-icon-database,\n",
			".xr-icon-file-text2 {\n",
			" display: inline-block;\n",
			" vertical-align: middle;\n",
			" width: 1em;\n",
			" height: 1.5em !important;\n",
			" stroke-width: 0;\n",
			" stroke: currentColor;\n",
			" fill: currentColor;\n",
			"}\n",
			"</style><pre class='xr-text-repr-fallback'><xarray.DataArray ()>\n",
			"array(2.31311077)</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1a5ed609-8353-4ca8-b70f-11013d145e32' class='xr-array-in' type='checkbox' checked><label for='section-1a5ed609-8353-4ca8-b70f-11013d145e32' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.313</span></div><div class='xr-array-data'><pre>array(2.31311077)</pre></div></div></li><li class='xr-section-item'><input id='section-14c28e6f-582e-41e7-b0c7-094d58dfa3d2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-14c28e6f-582e-41e7-b0c7-094d58dfa3d2' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-84fb537f-d9a2-4bc4-9439-a669335ab3f1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-84fb537f-d9a2-4bc4-9439-a669335ab3f1' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
			],
			"text/plain": [
			"<xarray.DataArray ()>\n",
			"array(2.31311077)"
			]
			},
			"execution_count": 32,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"get_yearly_sum(demand) / 1e12"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 33,
			"metadata": {},
			"outputs": [
			{
			"data": {
			"text/plain": [
			"{'N_SFH': 131322, 'N_DWELL': 634035.0}"
			]
			},
			"execution_count": 33,
			"metadata": {},
			"output_type": "execute_result"
			}
			],
			"source": [
			"counts"
			]
			},
			{
			"cell_type": "markdown",
			"metadata": {},
			"source": [
			"# Plot dataframe"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 34,
			"metadata": {},
			"outputs": [],
			"source": [
			"residential_demand.coords['timestamp'] = (residential_demand.timestamp.dt.month-1) * 24 + residential_demand.timestamp.dt.hour"
			]
			},
			{
			"cell_type": "code",
			"execution_count": 35,
			"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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
			" // select the cell after this one\n",
			" var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
			" IPython.notebook.select(index + 1);\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=\"1000\">"
			],
			"text/plain": [
			"<IPython.core.display.HTML object>"
			]
			},
			"metadata": {},
			"output_type": "display_data"
			}
			],
			"source": [
			"# PLOTTING ROUTINE\n",
			"plt.figure(figsize = (10, 3))\n",
			"ax = plt.subplot()\n",
			"\n",
			"#plt.plot(tilted_rad_hourly['flat'], label = 'Flat')\n",
			"residential_demand.demand_CH.to_pandas().plot(ax = ax)\n",
			"\n",
			"ax.set_xticks(list(range(12, 24*12, 24)))\n",
			"ax.set_xticklabels(calendar.month_abbr[1:])\n",
			"ax.set_ylabel('Electricity demand ($GW$)')\n",
			"\n",
			"plt.xlabel('')\n",
			"plt.xlim((0, 12*24))\n",
			"\n",
			"ax = plt.gca()\n",
			"ax.set_axisbelow(True)\n",
			"ax.yaxis.grid(linestyle = '--')\n",
			"\n",
			"plt.legend()\n",
			"plt.show()\n",
			"plt.tight_layout()\n",
			"plt.savefig('demand_mapped_CH.pdf')"
			]
			},
			{
			"cell_type": "code",
			"execution_count": null,
			"metadata": {},
			"outputs": [],
			"source": []
			}
			],
			"metadata": {
			"kernelspec": {
			"display_name": "Python 3",
			"language": "python",
			"name": "python3"
			},
			"language_info": {
			"codemirror_mode": {
			"name": "ipython",
			"version": 3
			},
			"file_extension": ".py",
			"mimetype": "text/x-python",
			"name": "python",
			"nbconvert_exporter": "python",
			"pygments_lexer": "ipython3",
			"version": "3.6.7"
			}
			},
			"nbformat": 4,
			"nbformat_minor": 4
			}

hybridPOT/demand_mapping/OLD_preprocess_GWR.ipynbddea7b1c1968Romain_branch

OLD_preprocess_GWR.ipynbView Options

hybridPOT/demand_mapping/OLD_preprocess_GWR.ipynb
ddea7b1c1968Romain_branch

OLD_preprocess_GWR.ipynb
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