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chriddyp/Pandas Widget - Time Series, Search, and Filtering.ipynb

Created January 22, 2015 22:30
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A Collection of Plotly and IPython Widgets
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Pandas Widget - Time Series, Search, and Filtering.ipynb
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"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Exploring NYC 311 Calls\n",
"#### Plotly and IPython Widgets"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from IPython.display import Image\n",
"Image(url='http://i.imgur.com/h5GLIHc.gif')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<img src=\"http://i.imgur.com/h5GLIHc.gif\"/>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 14,
"text": [
"<IPython.core.display.Image at 0x10bcd8390>"
]
}
],
"prompt_number": 14
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pandas as pd\n",
"import datetime\n",
"\n",
"from IPython.html import widgets \n",
"from IPython.display import display, clear_output\n",
"\n",
"import plotly.plotly as py\n",
"from plotly.graph_objs import *\n",
"import plotly\n",
"from plotly.widgets import GraphWidget"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"/Users/chris/anaconda/lib/python2.7/site-packages/pandas/computation/expressions.py:21: UserWarning: The installed version of numexpr 2.0.1 is not supported in pandas and will be not be used\n",
"The minimum supported version is 2.1\n",
"\n",
" \"version is 2.1\\n\".format(ver=ver), UserWarning)\n"
]
},
{
"javascript": [
"window.genUID = function() {\n",
" return 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, function(c) {\n",
" var r = Math.random()*16|0, v = c == 'x' ? r : (r&0x3|0x8);\n",
" return v.toString(16);\n",
" });\n",
"};\n",
"\n",
"require([\"widgets/js/widget\"], function(WidgetManager){\n",
"\n",
" var GraphView = IPython.DOMWidgetView.extend({\n",
" render: function(){\n",
"\n",
" console.log('render!');\n",
"\n",
" var that = this;\n",
"\n",
" var graphId = window.genUID();\n",
" var loadingId = 'loading-'+graphId;\n",
"\n",
"\n",
" var _graph_url = that.model.get('_graph_url');\n",
"\n",
" // variable plotlyDomain in the case of enterprise\n",
" var url_parts = _graph_url.split('/');\n",
" var plotlyDomain = url_parts[0] + '//' + url_parts[2];\n",
"\n",
" if(!('plotlyDomains' in window)){\n",
" window.plotlyDomains = {};\n",
" }\n",
" window.plotlyDomains[graphId] = plotlyDomain;\n",
"\n",
" // Place IFrame in output cell div `$el`\n",
" that.$el.css('width', '100%');\n",
" that.$graph = $(['<iframe id=\"'+graphId+'\"',\n",
" 'src=\"'+_graph_url+'.embed\"',\n",
" 'seamless',\n",
" 'style=\"border: none;\"',\n",
" 'width=\"100%\"',\n",
" 'height=\"600\">',\n",
" '</iframe>'].join(' '));\n",
" that.$graph.appendTo(that.$el);\n",
"\n",
" that.$loading = $('<div id=\"'+loadingId+'\">Initializing...</div>')\n",
" .appendTo(that.$el);\n",
"\n",
" // initialize communication with the iframe\n",
" if(!('pingers' in window)){\n",
" window.pingers = {};\n",
" }\n",
"\n",
" window.pingers[graphId] = setInterval(function() {\n",
" that.graphContentWindow = $('#'+graphId)[0].contentWindow;\n",
" console.log('posting ping: ', plotlyDomain);\n",
" that.graphContentWindow.postMessage({task: 'ping'}, plotlyDomain);\n",
" }, 200);\n",
"\n",
" // Assign a message listener to the 'message' events\n",
" // from iframe's postMessage protocol.\n",
" // Filter the messages by iframe src so that the right message\n",
" // gets passed to the right widget\n",
" if(!('messageListeners' in window)){\n",
" window.messageListeners = {};\n",
" }\n",
"\n",
" window.messageListeners[graphId] = function(e) {\n",
" console.log('message: ', e.data);\n",
" if(_graph_url.indexOf(e.origin)>-1) {\n",
" var frame = document.getElementById(graphId);\n",
"\n",
" if(frame === null){\n",
" // frame doesn't exist in the dom anymore, clean up it's old event listener\n",
" window.removeEventListener('message', window.messageListeners[graphId]);\n",
" clearInterval(window.pingers[graphId]);\n",
" } else if(frame.contentWindow === e.source) {\n",
" // TODO: Stop event propagation, so each frame doesn't listen and filter\n",
" var frameContentWindow = $('#'+graphId)[0].contentWindow;\n",
" var message = e.data;\n",
"\n",
" if('pong' in message && message.pong) {\n",
" $('#loading-'+graphId).hide();\n",
" clearInterval(window.pingers[graphId]);\n",
" that.send({event: 'pong', graphId: graphId});\n",
" } else if (message.type==='hover' ||\n",
" message.type==='zoom' ||\n",
" message.type==='click' ||\n",
" message.type==='unhover') {\n",
"\n",
" // click and hover events contain all of the data in the traces,\n",
" // which can be a very large object and may take a ton of time\n",
" // to pass to the python backend. Strip out the data, and require\n",
" // the user to call get_figure if they need trace information\n",
" if(message.type !== 'zoom') {\n",
" for(var i in message.points) {\n",
" delete message.points[i].data;\n",
" }\n",
" }\n",
" that.send({event: message.type, message: message, graphId: graphId});\n",
" }\n",
" }\n",
" }\n",
" };\n",
"\n",
" window.removeEventListener('message', window.messageListeners[graphId]);\n",
" window.addEventListener('message', window.messageListeners[graphId]);\n",
"\n",
" },\n",
"\n",
" update: function() {\n",
" // Listen for messages from the graph widget in python\n",
" var jmessage = this.model.get('_message');\n",
" var message = JSON.parse(jmessage);\n",
"\n",
" // check for duplicate messages\n",
" if(!('messageIds' in window)){\n",
" window.messageIds = {};\n",
" }\n",
"\n",
" if(!(message.uid in window.messageIds)){\n",
" // message hasn't been received yet, do stuff\n",
" window.messageIds[message.uid] = true;\n",
"\n",
" var plot = $('#'+message.graphId)[0].contentWindow;\n",
" plot.postMessage(message, window.plotlyDomains[message.graphId]);\n",
" }\n",
"\n",
" return GraphView.__super__.update.apply(this);\n",
" }\n",
" });\n",
"\n",
" // Register the GraphView with the widget manager.\n",
" WidgetManager.register_widget_view('GraphView', GraphView);\n",
"});\n",
"\n",
"//@ sourceURL=graphWidget.js\n"
],
"metadata": {},
"output_type": "display_data",
"text": [
"<IPython.core.display.Javascript at 0x107776c50>"
]
}
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"prompt_number": 1
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{
"cell_type": "code",
"collapsed": false,
"input": [
"df = pd.read_csv('https://raw.githubusercontent.com/plotly/widgets/master/ipython-examples/311_150k.csv', parse_dates=True, index_col=1)\n",
"df = df\n",
"df.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"/Users/chris/anaconda/lib/python2.7/site-packages/pandas/io/parsers.py:1154: DtypeWarning:\n",
"\n",
"Columns (8,39,46,47,48) have mixed types. Specify dtype option on import or set low_memory=False.\n",
"\n"
]
},
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Unique Key</th>\n",
" <th>Closed Date</th>\n",
" <th>Agency</th>\n",
" <th>Agency Name</th>\n",
" <th>Complaint Type</th>\n",
" <th>Descriptor</th>\n",
" <th>Location Type</th>\n",
" <th>Incident Zip</th>\n",
" <th>Incident Address</th>\n",
" <th>Street Name</th>\n",
" <th>...</th>\n",
" <th>Bridge Highway Name</th>\n",
" <th>Bridge Highway Direction</th>\n",
" <th>Road Ramp</th>\n",
" <th>Bridge Highway Segment</th>\n",
" <th>Garage Lot Name</th>\n",
" <th>Ferry Direction</th>\n",
" <th>Ferry Terminal Name</th>\n",
" <th>Latitude</th>\n",
" <th>Longitude</th>\n",
" <th>Location</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Created Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2014-11-16 23:46:00</th>\n",
" <td> 29300358</td>\n",
" <td> 11/16/2014 11:46:00 PM</td>\n",
" <td> DSNY</td>\n",
" <td> BCC - Queens East</td>\n",
" <td> Derelict Vehicles</td>\n",
" <td> 14 Derelict Vehicles</td>\n",
" <td> Street</td>\n",
" <td> 11432</td>\n",
" <td> 80-25 PARSONS BOULEVARD</td>\n",
" <td> PARSONS BOULEVARD</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 40.719411</td>\n",
" <td>-73.808882</td>\n",
" <td> (40.719410639341916, -73.80888158860446)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-11-16 02:24:35</th>\n",
" <td> 29299837</td>\n",
" <td> 11/16/2014 02:24:35 AM</td>\n",
" <td> DOB</td>\n",
" <td> Department of Buildings</td>\n",
" <td> Building/Use</td>\n",
" <td> Illegal Conversion Of Residential Building/Space</td>\n",
" <td> NaN</td>\n",
" <td> 10465</td>\n",
" <td> 938 HUNTINGTON AVENUE</td>\n",
" <td> HUNTINGTON AVENUE</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 40.827862</td>\n",
" <td>-73.830641</td>\n",
" <td> (40.827862046105416, -73.83064067165407)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-11-16 02:17:12</th>\n",
" <td> 29297857</td>\n",
" <td> 11/16/2014 02:50:48 AM</td>\n",
" <td> NYPD</td>\n",
" <td> New York City Police Department</td>\n",
" <td> Illegal Parking</td>\n",
" <td> Blocked Sidewalk</td>\n",
" <td> Street/Sidewalk</td>\n",
" <td> 11201</td>\n",
" <td> 229 DUFFIELD STREET</td>\n",
" <td> DUFFIELD STREET</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 40.691248</td>\n",
" <td>-73.984375</td>\n",
" <td> (40.69124772858873, -73.98437529459297)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-11-16 02:15:13</th>\n",
" <td> 29294647</td>\n",
" <td> NaN</td>\n",
" <td> NYPD</td>\n",
" <td> New York City Police Department</td>\n",
" <td> Noise - Street/Sidewalk</td>\n",
" <td> Loud Music/Party</td>\n",
" <td> Street/Sidewalk</td>\n",
" <td> 10040</td>\n",
" <td> 128 NAGLE AVENUE</td>\n",
" <td> NAGLE AVENUE</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 40.861248</td>\n",
" <td>-73.926308</td>\n",
" <td> (40.861247930170535, -73.92630783362215)</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-11-16 02:14:01</th>\n",
" <td> 29300211</td>\n",
" <td> NaN</td>\n",
" <td> NYPD</td>\n",
" <td> New York City Police Department</td>\n",
" <td> Illegal Parking</td>\n",
" <td> Commercial Overnight Parking</td>\n",
" <td> Street/Sidewalk</td>\n",
" <td> 10306</td>\n",
" <td> 625 LINCOLN AVENUE</td>\n",
" <td> LINCOLN AVENUE</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 40.570565</td>\n",
" <td>-74.092229</td>\n",
" <td> (40.57056460126485, -74.09222907551542)</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 51 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": [
" Unique Key Closed Date Agency \\\n",
"Created Date \n",
"2014-11-16 23:46:00 29300358 11/16/2014 11:46:00 PM DSNY \n",
"2014-11-16 02:24:35 29299837 11/16/2014 02:24:35 AM DOB \n",
"2014-11-16 02:17:12 29297857 11/16/2014 02:50:48 AM NYPD \n",
"2014-11-16 02:15:13 29294647 NaN NYPD \n",
"2014-11-16 02:14:01 29300211 NaN NYPD \n",
"\n",
" Agency Name Complaint Type \\\n",
"Created Date \n",
"2014-11-16 23:46:00 BCC - Queens East Derelict Vehicles \n",
"2014-11-16 02:24:35 Department of Buildings Building/Use \n",
"2014-11-16 02:17:12 New York City Police Department Illegal Parking \n",
"2014-11-16 02:15:13 New York City Police Department Noise - Street/Sidewalk \n",
"2014-11-16 02:14:01 New York City Police Department Illegal Parking \n",
"\n",
" Descriptor \\\n",
"Created Date \n",
"2014-11-16 23:46:00 14 Derelict Vehicles \n",
"2014-11-16 02:24:35 Illegal Conversion Of Residential Building/Space \n",
"2014-11-16 02:17:12 Blocked Sidewalk \n",
"2014-11-16 02:15:13 Loud Music/Party \n",
"2014-11-16 02:14:01 Commercial Overnight Parking \n",
"\n",
" Location Type Incident Zip Incident Address \\\n",
"Created Date \n",
"2014-11-16 23:46:00 Street 11432 80-25 PARSONS BOULEVARD \n",
"2014-11-16 02:24:35 NaN 10465 938 HUNTINGTON AVENUE \n",
"2014-11-16 02:17:12 Street/Sidewalk 11201 229 DUFFIELD STREET \n",
"2014-11-16 02:15:13 Street/Sidewalk 10040 128 NAGLE AVENUE \n",
"2014-11-16 02:14:01 Street/Sidewalk 10306 625 LINCOLN AVENUE \n",
"\n",
" Street Name \\\n",
"Created Date \n",
"2014-11-16 23:46:00 PARSONS BOULEVARD \n",
"2014-11-16 02:24:35 HUNTINGTON AVENUE \n",
"2014-11-16 02:17:12 DUFFIELD STREET \n",
"2014-11-16 02:15:13 NAGLE AVENUE \n",
"2014-11-16 02:14:01 LINCOLN AVENUE \n",
"\n",
" ... \\\n",
"Created Date ... \n",
"2014-11-16 23:46:00 ... \n",
"2014-11-16 02:24:35 ... \n",
"2014-11-16 02:17:12 ... \n",
"2014-11-16 02:15:13 ... \n",
"2014-11-16 02:14:01 ... \n",
"\n",
" Bridge Highway Name Bridge Highway Direction Road Ramp \\\n",
"Created Date \n",
"2014-11-16 23:46:00 NaN NaN NaN \n",
"2014-11-16 02:24:35 NaN NaN NaN \n",
"2014-11-16 02:17:12 NaN NaN NaN \n",
"2014-11-16 02:15:13 NaN NaN NaN \n",
"2014-11-16 02:14:01 NaN NaN NaN \n",
"\n",
" Bridge Highway Segment Garage Lot Name Ferry Direction \\\n",
"Created Date \n",
"2014-11-16 23:46:00 NaN NaN NaN \n",
"2014-11-16 02:24:35 NaN NaN NaN \n",
"2014-11-16 02:17:12 NaN NaN NaN \n",
"2014-11-16 02:15:13 NaN NaN NaN \n",
"2014-11-16 02:14:01 NaN NaN NaN \n",
"\n",
" Ferry Terminal Name Latitude Longitude \\\n",
"Created Date \n",
"2014-11-16 23:46:00 NaN 40.719411 -73.808882 \n",
"2014-11-16 02:24:35 NaN 40.827862 -73.830641 \n",
"2014-11-16 02:17:12 NaN 40.691248 -73.984375 \n",
"2014-11-16 02:15:13 NaN 40.861248 -73.926308 \n",
"2014-11-16 02:14:01 NaN 40.570565 -74.092229 \n",
"\n",
" Location \n",
"Created Date \n",
"2014-11-16 23:46:00 (40.719410639341916, -73.80888158860446) \n",
"2014-11-16 02:24:35 (40.827862046105416, -73.83064067165407) \n",
"2014-11-16 02:17:12 (40.69124772858873, -73.98437529459297) \n",
"2014-11-16 02:15:13 (40.861247930170535, -73.92630783362215) \n",
"2014-11-16 02:14:01 (40.57056460126485, -74.09222907551542) \n",
"\n",
"[5 rows x 51 columns]"
]
}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"grouped = df.resample('24H', how='count')"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"slider = widgets.IntSliderWidget()\n",
"slider.min = 1\n",
"slider.value=24\n",
"slider.description = 'Window length (hours)'"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"column_headers_dropdown = widgets.DropdownWidget()\n",
"column_headers_dropdown.values = {column: column for column in df.columns}\n",
"column_headers_dropdown.value = 'Complaint Type'\n",
"column_headers_dropdown.description = 'Select which column to graph (e.g. Tree)'\n",
"\n",
"\n",
"search_complaints_text_input = widgets.TextWidget()\n",
"search_complaints_text_input.description = 'Search complaint types'"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"graph_time_series_agg = GraphWidget('https://plot.ly/~chris/4103')\n",
"graph_time_series_agg.ranges = {'x': [1413648000000, 1416157200000], 'y': [0, 7744.210526315789]}\n",
"graph_complaints = GraphWidget('https://plot.ly/~chris/4103')"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def replot(on_zoom=False):\n",
" search_text = search_complaints_text_input.value\n",
" slider_val = slider.value\n",
" column_name = column_headers_dropdown.value\n",
"\n",
" # Time window that we're looking at\n",
" ranges = graph_time_series_agg.ranges\n",
" xr = ranges['x']\n",
" x1 = datetime.datetime.fromtimestamp(int(xr[0]/1000.))\n",
" x2 = datetime.datetime.fromtimestamp(int(xr[1]/1000.))\n",
"\n",
" # Text value that we're looking at\n",
" search_idx = df['Complaint Type'].str.contains(search_complaints_text_input.value).fillna(False)\n",
" windowed_idx = search_idx & (df.index>x1) & (df.index<x2)\n",
"\n",
" if not on_zoom:\n",
" # Replot the time series aggregate on input change\n",
" grouped = df[search_idx].resample('{}H'.format(slider_val), how='count')\n",
"\n",
" graph_time_series_agg.restyle({\n",
" 'x': [grouped['Complaint Type'].index],\n",
" 'y': [grouped['Complaint Type']],\n",
" 'type': 'bar'\n",
" })\n",
"\n",
" \n",
" # Replot the value counts aggregate\n",
" vc = df[windowed_idx][column_name].value_counts()\n",
" \n",
" graph_complaints.restyle({'x': [vc.index], 'y': [vc.values], 'type': 'bar'})\n",
"\n",
"def on_trait_change():\n",
" replot()\n",
"\n",
"search_complaints_text_input.on_trait_change(on_trait_change, 'value')\n",
"column_headers_dropdown.on_trait_change(on_trait_change, 'value')\n",
"slider.on_trait_change(on_trait_change, 'value')"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def replot_complaints_on_zoom(_, ranges):\n",
" graph_time_series_agg.ranges = ranges\n",
"\n",
" replot(True)\n",
"\n",
"graph_time_series_agg.on_zoom(replot_complaints_on_zoom)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 8
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"display(slider)\n",
"display(search_complaints_text_input)\n",
"display(column_headers_dropdown)\n",
"\n",
"display(graph_time_series_agg)\n",
"display(graph_complaints)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"replot()"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 10
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"graph_time_series_agg.relayout({'title': 'Number of complaints over time'})\n",
"graph_complaints.relayout({'yaxis.title': 'Number of events'})"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 13
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# CSS styling within IPython notebook - feel free to re-use\n",
"from IPython.core.display import HTML\n",
"import urllib2\n",
"\n",
"HTML(urllib2.urlopen('http://bit.ly/1Bf5Hft').read())"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<style>\n",
"\n",
"html {\n",
" font-size: 62.5% !important; }\n",
"body {\n",
" font-size: 1.5em !important; /* currently ems cause chrome bug misinterpreting rems on body element */\n",
" line-height: 1.6 !important;\n",
" font-weight: 400 !important;\n",
" font-family: \"Raleway\", \"HelveticaNeue\", \"Helvetica Neue\", Helvetica, Arial, sans-serif !important;\n",
" color: #222 !important; }\n",
"\n",
"div{ border-radius: 0px !important; }\n",
"div.CodeMirror-sizer{ background: rgb(244, 244, 248) !important; }\n",
"div.input_area{ background: rgb(244, 244, 248) !important; }\n",
"\n",
"div.out_prompt_overlay:hover{ background: rgb(244, 244, 248) !important; }\n",
"div.input_prompt:hover{ background: rgb(244, 244, 248) !important; }\n",
"\n",
"h1, h2, h3, h4, h5, h6 {\n",
" color: #333 !important;\n",
" margin-top: 0 !important;\n",
" margin-bottom: 2rem !important;\n",
" font-weight: 300 !important; }\n",
"h1 { font-size: 4.0rem !important; line-height: 1.2 !important; letter-spacing: -.1rem !important;}\n",
"h2 { font-size: 3.6rem !important; line-height: 1.25 !important; letter-spacing: -.1rem !important; }\n",
"h3 { font-size: 3.0rem !important; line-height: 1.3 !important; letter-spacing: -.1rem !important; }\n",
"h4 { font-size: 2.4rem !important; line-height: 1.35 !important; letter-spacing: -.08rem !important; }\n",
"h5 { font-size: 1.8rem !important; line-height: 1.5 !important; letter-spacing: -.05rem !important; }\n",
"h6 { font-size: 1.5rem !important; line-height: 1.6 !important; letter-spacing: 0 !important; }\n",
"\n",
"@media (min-width: 550px) {\n",
" h1 { font-size: 5.0rem !important; }\n",
" h2 { font-size: 4.2rem !important; }\n",
" h3 { font-size: 3.6rem !important; }\n",
" h4 { font-size: 3.0rem !important; }\n",
" h5 { font-size: 2.4rem !important; }\n",
" h6 { font-size: 1.5rem !important; }\n",
"}\n",
"\n",
"p {\n",
" margin-top: 0 !important; }\n",
" \n",
"a {\n",
" color: #1EAEDB !important; }\n",
"a:hover {\n",
" color: #0FA0CE !important; }\n",
" \n",
"code {\n",
" padding: .2rem .5rem !important;\n",
" margin: 0 .2rem !important;\n",
" font-size: 90% !important;\n",
" white-space: nowrap !important;\n",
" background: #F1F1F1 !important;\n",
" border: 1px solid #E1E1E1 !important;\n",
" border-radius: 4px !important; }\n",
"pre > code {\n",
" display: block !important;\n",
" padding: 1rem 1.5rem !important;\n",
" white-space: pre !important; }\n",
" \n",
"button{ border-radius: 0px !important; }\n",
".navbar-inner{ background-image: none !important; }\n",
"select, textarea{ border-radius: 0px !important; }\n",
"\n",
"</style>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": [
"<IPython.core.display.HTML at 0x1046c3650>"
]
}
],
"prompt_number": 2
}
],
"metadata": {}
}
]
}
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Pandas Widget - Walkthrough.ipynb
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