{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "+ title: Interactive plots of large data sets made easy: Datashader\n", "+ date: 2019-08-15\n", "+ modified: 2020-01-08\n", "+ tags: python, datashader, holoviews, bokeh, maps, holoviz\n", "+ Slug: interactive-large-data-plots-datashader\n", "+ Category: Python\n", "+ Authors: MC\n", "+ Summary: When plotting huge data sets using Python while keeping interactivity, Datashader is paramount. In this post, I demonstrate the abilities of this powerful and convenient library. We use an unique dataset containing a whole year of shared bike usage in Cologne to plot over a million locations on a map." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Get this post as an interactive Jupyter Notebook and execute the code via Binder:\n", "\"Binder\" \n", "*Update*: Now using data from 2019 instead of 2018" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Motivation \n", "\n", "In a [previous post]({filename}/kvb_geoviews1.ipynb), we've look at `GeoViews` as a convenient and powerful Python library for visualizing geo data. We've seen that it is able to plot tens of thousands of points on a map in spite of being fully interactive. In this post, we will explore another library that is part of the [HoloViz](http://holoviz.org/) initiative. [Datashader](http://datashader.org/) is able to visualize truly large datasets by using an optimized rendering pipeline. [HoloViews'](https://holoviews.org) support for Datashader makes plotting millions of data points pretty easy, even while maintaining interactivity. In the following, we will again use our [Cologne bike rental]({filename}/kvb_part1.md) data to demonstrate DataShader's abilities. Get the data [here](https://data.world/mc51/cologne-rental-bike-nextbike-locations-for-2018) and follow along. \n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plotting a whole year of bike locations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Our dataset contains all KVB bike locations for the whole year ~~2018~~ 2019. Thats going to be a lot of data to display at once. But this is where datashader's strength comes into play. Other interactive libraries, i.e. bokeh, plotly etc. embed the data as JSON in an `.hmtl` file and let the browser do all the work. In contrast, datashader renders an image containing the processed data at the appropriate level. Consequently, all the hard work (the computation) is done beforehand.
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the first step, we load the libraries we'll be using:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "
\n", " \n", " Loading BokehJS ...\n", "
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*/\n", " safe: true,\n", " /* Index of renderer in `output_area.display_order` */\n", " index: 0\n", " });\n", " }\n", "\n", " // register the mime type if in Jupyter Notebook environment and previously unregistered\n", " if (root.Jupyter !== undefined) {\n", " var events = require('base/js/events');\n", " var OutputArea = require('notebook/js/outputarea').OutputArea;\n", "\n", " if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n", " register_renderer(events, OutputArea);\n", " }\n", " }\n", "\n", " \n", " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", " root._bokeh_timeout = Date.now() + 5000;\n", " root._bokeh_failed_load = false;\n", " }\n", "\n", " var NB_LOAD_WARNING = {'data': {'text/html':\n", " \"
\\n\"+\n", " \"

\\n\"+\n", " \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n", " \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n", " \"

\\n\"+\n", " \"\\n\"+\n", " \"\\n\"+\n", " \"from bokeh.resources import INLINE\\n\"+\n", " \"output_notebook(resources=INLINE)\\n\"+\n", " \"\\n\"+\n", " \"
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3px;\\n\\tbackground:\\n\\tlinear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\nprogress:not([value])::before {\\n\\tcontent:\\\" \\\";\\n\\tposition:absolute;\\n\\theight: 20px;\\n\\ttop:0;\\n\\tleft:0;\\n\\tright:0;\\n\\tbottom:0;\\n\\tborder-radius: 3px;\\n\\tbackground:\\n\\tlinear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\n@keyframes stripes {\\n from {background-position: 0%}\\n to {background-position: 100%}\\n}\");\n", " },\n", " function(Bokeh) {\n", " inject_raw_css(\"table.panel-df {\\n margin-left: auto;\\n margin-right: auto;\\n border: none;\\n border-collapse: collapse;\\n border-spacing: 0;\\n color: black;\\n font-size: 12px;\\n table-layout: fixed;\\n width: 100%;\\n}\\n\\n.panel-df tr, th, td {\\n text-align: right;\\n vertical-align: middle;\\n padding: 0.5em 0.5em !important;\\n line-height: normal;\\n white-space: normal;\\n max-width: none;\\n border: none;\\n}\\n\\n.panel-df tbody {\\n display: table-row-group;\\n vertical-align: middle;\\n border-color: inherit;\\n}\\n\\n.panel-df tbody tr:nth-child(odd) {\\n background: #f5f5f5;\\n}\\n\\n.panel-df thead {\\n border-bottom: 1px solid black;\\n vertical-align: bottom;\\n}\\n\\n.panel-df tr:hover {\\n background: lightblue !important;\\n cursor: pointer;\\n}\\n\");\n", " },\n", " function(Bokeh) {\n", " inject_raw_css(\".codehilite .hll { background-color: #ffffcc }\\n.codehilite { background: #f8f8f8; }\\n.codehilite .c { color: #408080; font-style: italic } /* Comment */\\n.codehilite .err { border: 1px solid #FF0000 } /* Error */\\n.codehilite .k { color: #008000; font-weight: bold } /* Keyword */\\n.codehilite .o { color: #666666 } /* Operator */\\n.codehilite .ch { color: #408080; font-style: italic } /* Comment.Hashbang */\\n.codehilite .cm { color: #408080; font-style: italic } /* Comment.Multiline */\\n.codehilite .cp { color: #BC7A00 } /* Comment.Preproc */\\n.codehilite .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */\\n.codehilite .c1 { color: #408080; font-style: italic } /* Comment.Single */\\n.codehilite .cs { color: #408080; font-style: italic } /* Comment.Special */\\n.codehilite .gd { color: #A00000 } /* Generic.Deleted */\\n.codehilite .ge { font-style: italic } /* Generic.Emph */\\n.codehilite .gr { color: #FF0000 } /* Generic.Error */\\n.codehilite .gh { color: #000080; font-weight: bold } /* Generic.Heading */\\n.codehilite .gi { color: #00A000 } /* Generic.Inserted */\\n.codehilite .go { color: #888888 } /* Generic.Output */\\n.codehilite .gp { color: #000080; font-weight: bold } /* Generic.Prompt */\\n.codehilite .gs { font-weight: bold } /* Generic.Strong */\\n.codehilite .gu { color: #800080; font-weight: bold } /* Generic.Subheading */\\n.codehilite .gt { color: #0044DD } /* Generic.Traceback */\\n.codehilite .kc { color: #008000; font-weight: bold } /* Keyword.Constant */\\n.codehilite .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */\\n.codehilite .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */\\n.codehilite .kp { color: #008000 } /* Keyword.Pseudo */\\n.codehilite .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */\\n.codehilite .kt { color: #B00040 } /* Keyword.Type */\\n.codehilite .m { color: #666666 } /* Literal.Number */\\n.codehilite .s { color: #BA2121 } /* Literal.String */\\n.codehilite .na { color: #7D9029 } /* Name.Attribute */\\n.codehilite .nb { color: #008000 } /* Name.Builtin */\\n.codehilite .nc { color: #0000FF; font-weight: bold } /* Name.Class */\\n.codehilite .no { color: #880000 } /* Name.Constant */\\n.codehilite .nd { color: #AA22FF } /* Name.Decorator */\\n.codehilite .ni { color: #999999; font-weight: bold } /* Name.Entity */\\n.codehilite .ne { color: #D2413A; font-weight: bold } /* Name.Exception */\\n.codehilite .nf { color: #0000FF } /* Name.Function */\\n.codehilite .nl { color: #A0A000 } /* Name.Label */\\n.codehilite .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */\\n.codehilite .nt { color: #008000; font-weight: bold } /* Name.Tag */\\n.codehilite .nv { color: #19177C } /* Name.Variable */\\n.codehilite .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */\\n.codehilite .w { color: #bbbbbb } /* Text.Whitespace */\\n.codehilite .mb { color: #666666 } /* Literal.Number.Bin */\\n.codehilite .mf { color: #666666 } /* Literal.Number.Float */\\n.codehilite .mh { color: #666666 } /* Literal.Number.Hex */\\n.codehilite .mi { color: #666666 } /* Literal.Number.Integer */\\n.codehilite .mo { color: #666666 } /* Literal.Number.Oct */\\n.codehilite .sa { color: #BA2121 } /* Literal.String.Affix */\\n.codehilite .sb { color: #BA2121 } /* Literal.String.Backtick */\\n.codehilite .sc { color: #BA2121 } /* Literal.String.Char */\\n.codehilite .dl { color: #BA2121 } /* Literal.String.Delimiter */\\n.codehilite .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */\\n.codehilite .s2 { color: #BA2121 } /* Literal.String.Double */\\n.codehilite .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */\\n.codehilite .sh { color: #BA2121 } /* Literal.String.Heredoc */\\n.codehilite .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */\\n.codehilite .sx { color: #008000 } /* Literal.String.Other */\\n.codehilite .sr { color: #BB6688 } /* Literal.String.Regex */\\n.codehilite .s1 { color: #BA2121 } /* Literal.String.Single */\\n.codehilite .ss { color: #19177C } /* Literal.String.Symbol */\\n.codehilite .bp { color: #008000 } /* Name.Builtin.Pseudo */\\n.codehilite .fm { color: #0000FF } /* Name.Function.Magic */\\n.codehilite .vc { color: #19177C } /* Name.Variable.Class */\\n.codehilite .vg { color: #19177C } /* Name.Variable.Global */\\n.codehilite .vi { color: #19177C } /* Name.Variable.Instance */\\n.codehilite .vm { color: #19177C } /* Name.Variable.Magic */\\n.codehilite .il { color: #666666 } /* Literal.Number.Integer.Long */\\n\\n.markdown h1 { margin-block-start: 0.34em }\\n.markdown h2 { margin-block-start: 0.42em }\\n.markdown h3 { margin-block-start: 0.5em }\\n.markdown h4 { margin-block-start: 0.67em }\\n.markdown h5 { margin-block-start: 0.84em }\\n.markdown h6 { margin-block-start: 1.17em }\\n.markdown ul { padding-inline-start: 2em }\\n.markdown ol { padding-inline-start: 2em }\\n.markdown strong { font-weight: 600 }\\n.markdown a { color: -webkit-link }\\n.markdown a { color: -moz-hyperlinkText }\\n\");\n", " },\n", " function(Bokeh) {\n", " Bokeh.set_log_level(\"info\");\n", " },\n", " function(Bokeh) {\n", " \n", " \n", " }\n", " ];\n", "\n", " function run_inline_js() {\n", " \n", " if (root.Bokeh !== undefined || force === true) {\n", " \n", " for (var i = 0; i < inline_js.length; i++) {\n", " inline_js[i].call(root, root.Bokeh);\n", " }\n", " if (force === true) {\n", " display_loaded();\n", " }} else if (Date.now() < root._bokeh_timeout) {\n", " setTimeout(run_inline_js, 100);\n", " } else if (!root._bokeh_failed_load) {\n", " console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n", " root._bokeh_failed_load = true;\n", " } else if (force !== true) {\n", " var cell = $(document.getElementById(\"1390\")).parents('.cell').data().cell;\n", " cell.output_area.append_execute_result(NB_LOAD_WARNING)\n", " }\n", "\n", " }\n", "\n", " if (root._bokeh_is_loading === 0) {\n", " console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n", " run_inline_js();\n", " } else {\n", " load_libs(css_urls, js_urls, function() {\n", " console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n", " run_inline_js();\n", " });\n", " }\n", "}(window));" ], "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"
\\n\"+\n \"

\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"

\\n\"+\n \"\\n\"+\n \"\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"\\n\"+\n \"
\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1390\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) {\n if (callback != null)\n callback();\n });\n } finally {\n delete root._bokeh_onload_callbacks\n }\n console.debug(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(css_urls, js_urls, callback) {\n if (css_urls == null) css_urls = [];\n if (js_urls == null) js_urls = [];\n\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n function on_load() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n run_callbacks()\n }\n }\n\n function on_error() {\n console.error(\"failed to load \" + url);\n }\n\n for (var i = 0; i < css_urls.length; i++) {\n var url = css_urls[i];\n const element = document.createElement(\"link\");\n element.onload = on_load;\n element.onerror = on_error;\n element.rel = \"stylesheet\";\n element.type = \"text/css\";\n element.href = url;\n console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n document.body.appendChild(element);\n }\n\n const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.0.1.min.js\": \"JpP8FXbgAZLkfur7LiK3j9AGBhHNIvF742meBJrjO2ShJDhCG2I1uVvW+0DUtrmc\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.0.1.min.js\": \"xZlADit0Q04ISQEdKg2k3L4W9AwQBAuDs9nJL9fM/WwzL1tEU9VPNezOFX0nLEAz\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.0.1.min.js\": \"4BuPRZkdMKSnj3zoxiNrQ86XgNw0rYmBOxe7nshquXwwcauupgBF2DHLVG1WuZlV\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.0.1.min.js\": \"Dv1SQ87hmDqK6S5OhBf0bCuwAEvL5QYL0PuR/F1SPVhCS/r/abjkbpKDYL2zeM19\"};\n\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var element = document.createElement('script');\n element.onload = on_load;\n element.onerror = on_error;\n element.async = false;\n element.src = url;\n if (url in hashes) {\n element.crossOrigin = \"anonymous\";\n element.integrity = \"sha384-\" + hashes[url];\n }\n console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.head.appendChild(element);\n }\n };var element = document.getElementById(\"1390\");\n if (element == null) {\n console.error(\"Bokeh: ERROR: autoload.js configured with elementid '1390' but no matching script tag was found. \")\n return false;\n }\n\n function inject_raw_css(css) {\n const element = document.createElement(\"style\");\n element.appendChild(document.createTextNode(css));\n document.body.appendChild(element);\n }\n\n \n var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.0.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.0.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.0.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.0.1.min.js\", \"https://unpkg.com/@holoviz/panel@^0.9.5/dist/panel.min.js\"];\n var css_urls = [];\n \n\n var inline_js = [\n function(Bokeh) {\n inject_raw_css(\".json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-row,\\n.json-formatter-row a,\\n.json-formatter-row a:hover {\\n color: black;\\n text-decoration: none;\\n}\\n.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-row .json-formatter-string,\\n.json-formatter-row .json-formatter-stringifiable {\\n color: green;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-row .json-formatter-number {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-boolean {\\n color: red;\\n}\\n.json-formatter-row .json-formatter-null {\\n color: #855A00;\\n}\\n.json-formatter-row .json-formatter-undefined {\\n color: #ca0b69;\\n}\\n.json-formatter-row .json-formatter-function {\\n color: #FF20ED;\\n}\\n.json-formatter-row .json-formatter-date {\\n background-color: rgba(0, 0, 0, 0.05);\\n}\\n.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: blue;\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-bracket {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-key {\\n color: #00008B;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n.json-formatter-dark.json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-dark.json-formatter-row,\\n.json-formatter-dark.json-formatter-row a,\\n.json-formatter-dark.json-formatter-row a:hover {\\n color: white;\\n text-decoration: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-string,\\n.json-formatter-dark.json-formatter-row .json-formatter-stringifiable {\\n color: #31F031;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-number {\\n color: #66C2FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-boolean {\\n color: #EC4242;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-null {\\n color: #EEC97D;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-undefined {\\n color: #ef8fbe;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-function {\\n color: #FD48CB;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-date {\\n background-color: rgba(255, 255, 255, 0.05);\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: #027BFF;\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-bracket {\\n color: #9494FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-key {\\n color: #23A0DB;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-dark.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-dark.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n\");\n },\n function(Bokeh) {\n inject_raw_css(\".widget-box {\\n\\tmin-height: 20px;\\n\\tbackground-color: #f5f5f5;\\n\\tborder: 1px solid #e3e3e3 !important;\\n\\tborder-radius: 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function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n function(Bokeh) {\n \n \n }\n ];\n\n function run_inline_js() {\n \n if (root.Bokeh !== undefined || force === true) {\n \n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }\n if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1390\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(css_urls, js_urls, function() {\n console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));" }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# coding: utf-8\n", "import pandas as pd\n", "import numpy as np\n", "from bokeh.io import output_notebook\n", "output_notebook()\n", "pd.set_option('display.max_columns', 100)\n", "\n", "from holoviews.operation.datashader import datashade\n", "import geoviews as gv\n", "import cartopy.crs as ccrs\n", "from colorcet import fire" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In addition to the standard stack we make use of a few additional libraries to deal with geo spatial data and the visualization process. `Cartopy` let's us deal with the Coordinate Reference System (CRS). `Colorcet` is also part of HoloViz and offers uniform colormaps. Finally, GeoViews and HoloViews deal with the geo spatial data and the plotting of it." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As before, we can now start by reading in a shapefile containing the borders of the districts of Cologne. You can get it [here](https://offenedaten-koeln.de/dataset/stadtteile). For that, we use the `geopandas` library:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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STT_NRdistrictSHAPE_AREASHAPE_LENgeometryarea_km2
0909Flittard7.735915e+0614368.509990POLYGON ((7.01364 51.02217, 7.01349 51.02200, ...7.735915
1905Dellbrück9.946585e+0616722.887925POLYGON ((7.06747 50.99363, 7.06758 50.99357, ...9.946585
2807Brück7.499469e+0612759.921710POLYGON ((7.07104 50.95452, 7.07138 50.95388, ...7.499469
3707Urbach2.291919e+067008.335906POLYGON ((7.09195 50.88922, 7.09249 50.88921, ...2.291919
4501Nippes2.995158e+068434.060948POLYGON ((6.95471 50.97357, 6.95475 50.97332, ...2.995158
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" ], "text/plain": [ " STT_NR district SHAPE_AREA SHAPE_LEN \\\n", "0 909 Flittard 7.735915e+06 14368.509990 \n", "1 905 Dellbrück 9.946585e+06 16722.887925 \n", "2 807 Brück 7.499469e+06 12759.921710 \n", "3 707 Urbach 2.291919e+06 7008.335906 \n", "4 501 Nippes 2.995158e+06 8434.060948 \n", "\n", " geometry area_km2 \n", "0 POLYGON ((7.01364 51.02217, 7.01349 51.02200, ... 7.735915 \n", "1 POLYGON ((7.06747 50.99363, 7.06758 50.99357, ... 9.946585 \n", "2 POLYGON ((7.07104 50.95452, 7.07138 50.95388, ... 7.499469 \n", "3 POLYGON ((7.09195 50.88922, 7.09249 50.88921, ... 2.291919 \n", "4 POLYGON ((6.95471 50.97357, 6.95475 50.97332, ... 2.995158 " ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import geopandas as gpd\n", "\n", "districts = gpd.read_file('./data/Stadtteil_WGS84.shp',\n", " encoding='utf8')\n", "districts['area_km2'] = districts['SHAPE_AREA'] / 1000 / 1000\n", "districts.rename(columns={'STT_NAME': 'district'}, inplace=True)\n", "districts.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Following, we process our bike location data. After reading in the csv, we remove points too far from the median location in order to remove location outliers:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "!wget -O bikes_2019.zip https://query.data.world/s/jqqvvxevfxwyialwsgb6v2acqmv6zg\n", "!unzip bikes_2019.zip" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/mc/dev/envs/jameda/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3063: DtypeWarning: Columns (1) have mixed types.Specify dtype option on import or set low_memory=False.\n", " interactivity=interactivity, compiler=compiler, result=result)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "(1509491, 6)\n" ] } ], "source": [ "# Read in athe bike location data\n", "df = pd.read_csv(\"./2019_bikes.csv\")\n", "df.drop(columns=df.columns[0], inplace=True)\n", "print(df.shape)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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bike_idscrape_weekdayu_idlatlonscrape_datetime
021664Tue3418350.9365406.9483282019-01-01 00:05:02
121619Tue67257850.9539466.9127202019-01-01 00:05:02
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" ], "text/plain": [ " bike_id scrape_weekday u_id lat lon scrape_datetime\n", "0 21664 Tue 34183 50.936540 6.948328 2019-01-01 00:05:02\n", "1 21619 Tue 672578 50.953946 6.912720 2019-01-01 00:05:02" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Exclude location outliers\n", "df = df[ abs(df['lat'] - df['lat'].median()) < 0.08]\n", "df = df[ abs(df['lon'] - df['lon'].median()) < 0.08]\n", "df.head(2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So we have about 1.5 million locations to deal with. How hard is it to plot all of them on a map of the city?" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.holoviews_exec.v0+json": "", "text/html": [ "
\n", "\n", "\n", "\n", "\n", "\n", "
\n", "
\n", "" ], "text/plain": [ ":DynamicMap []\n", " :Overlay\n", " .WMTS.I :WMTS [Longitude,Latitude]\n", " .RGB.I :RGB [lon,lat] (R,G,B,A)\n", " .Polygons.I :Polygons [Longitude,Latitude] (district,area_km2)" ] }, "execution_count": 6, "metadata": { "application/vnd.holoviews_exec.v0+json": { "id": "1004" } }, "output_type": "execute_result" } ], "source": [ "# Load districts as Polygons and Locations as Points and Overlay them on map\n", "polys = gv.Polygons(districts, vdims=['district', 'area_km2'], crs=ccrs.PlateCarree())\n", "points = gv.Points(df, ['lon', 'lat'], crs=ccrs.PlateCarree())\n", "\n", "plot = gv.tile_sources.CartoDark()\\\n", " * datashade(points, expand=False, height=2000, width=2000,\n", " cmap=fire, normalization='eq_hist')\\\n", " * polys.opts(alpha=0.1, color='white', tools=['hover'])\n", "plot.opts(width=700, height=600, bgcolor='black')\n", "#gv.save(plot, \"./img/datashader/map_cologne1.html\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\"DataShader\n", "
Due to the large size this is only an image. Check out the Notebook on Binder to get interactivity
\n", "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Well, turns out the answer is: not very hard! We only need a few lines of code to process and plot all data points.
\n", "Each pixel on the map represents the location of a bike at a certain time. You can clearly see patterns emerge. The main roads can be clearly identified as well as several points of interest like the university and the Cologne cathedral.
\n" ] } ], "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": "3.7.3" } }, "nbformat": 4, "nbformat_minor": 4 }