webgl data visualization

OData (Open Data Protocol) is always a standard I like (OASIS Standard), which provides a powerful access interface for querying and editing data based on restful protocols (Protocol). Although Microsoft launched it, it was born with open standards and open source genes (the first Microsoft opened the code for the OData client). When I have a chance, I'll go over some of the knowledge of OData in more detai

Seaborn Library Handbook Translation Introductory Remarks: Seaborn is actually a more advanced API encapsulation based on Matplotlib, making it easier to draw and, in most cases, using Seaborn to make attractive graphs. I am here to do my best to translate it (the dog has not seen the original computer in English before). ), convenient for everyone to inquire ~ ~ ~ Detailed Introduction can see Seaborn official API and Example Gallery one, style management 1, control picture art style The abil

[Author]: KwuFast Echarts-based Big Data visualization, Echarts pure JS Implementation of the charting tools, the steps for rapid development are as follows:1, the introduction of Echarts-dependent JS Library2, set the display div3, the plot JSvar mychart;var option;//drawing function Drawcharts (Echartshomepath) {//Path configuration require.config ({paths: {echarts: Echartshomepath + ' JS '}})//use requir

"Tags": {"Host": "Mycat"7, for the JSON "QPS": AA of the QSP, equivalent to fields, for field8, for the statistical way, see the basic introduction of its INFLUXDB9. Statistics are often10, for the symbol of the curve, you can add multiple query in a diagram, so that each name corresponds to a different colorFinally click the Save button, at the top there is an icon, save after the selection has 4 blocks of the general's name just definedAt last:650) this.width=650; "src=" Http://s3.51cto.com/wy

Data visualization in the Big Data era is an effective and even unique means of understanding and expressing data. 工欲善其事 its prerequisite, this article for 55 d3.js r , gephi rapha?l google Chart tools,arbor.js data source http://selection.datavisualizatio

A period of time completed a data visualization project, built by the background nodejs+highcharts framework. Let's share the process of the entire development process and the experience of using the Highcharts framework.First, the data readBecause the database is using MySQL database, in Nodejs, you can use the MySQL module in Nodejs for MySQL database operation

Webstorm+webpack+echartsEcharts Feature IntroductionEcharts, a pure Javascript chart library that runs smoothly on PCs and mobile devices, is compatible with most current browsers (Ie8/9/10/11,chrome,firefox,safari, etc.) and relies on lightweight Canvas class libraries Zrender provides intuitive, vivid, interactive and highly customizable data visualization charts.In Echarts 3, more rich interactivity and

Hard to analyze a bunch of big data, unexpectedly no one to see! What do we do? As the saying goes, there is a picture of the truth, a picture wins thousands of words, pleasing the eyeball, the rest are said. If you're starting to get useful information from your data, it's exactly what you need-data visualization. Thi

", layout); Display Display=NewDisplay (VIS); Display.setsize (700, 600); Display.addcontrollistener (NewDragcontrol ()); Display.addcontrollistener (NewPancontrol ()); Display.addcontrollistener (NewZoomcontrol ()); Display.addcontrollistener (NewWheelzoomcontrol ()); Display.addcontrollistener (NewFocuscontrol (1)); Display.addcontrollistener (NewZoomtofitcontrol ()); JFrame JF=NewJFrame (); Jf.setdefaultcloseoperation (Jframe.exit_on_close); Jf.add (display); Jf.pack ();

Learn about graphical calculations for the components used to draw various permutations The 1th part of this two-part series outlines the combined use of SVG and D3, providing some basic examples of creating browsing data visualization representations of social media. Part 2nd will describe the steps for arranging or laying out different graphic components in SVG graphics. You will learn how to use D3 powe

OverviewMany scenarios in the business work need to visualize the data, in order to meet the needs of users, improve the user experience, we have developed more data visualization control. is introduced to everyone, forming a series.Today is the Chronicle of memorabilia control Verticaltimeline, which splits a series of events on a yearly basis, clicking on the y

segmentation situation. The red part is the process of running the program.11, continue to write code, the frequency of the statistical summary, the code implementation as shown.12, the program run, get a TXT and Excel file, inside is about the word frequency statistics information, as shown. The red part is the result of the program running, and there is no error.13. Import these keywords into WordArt for visualization, as shown in.14, set a case, f

Charts are an essential feature point for enterprise-wide Web development. is also "a concrete rendering of data visualization". Today I see Nanyi translation of the "Data Visualization: Basic Chart" article, while combing the company's current project use of the EChart2.0 class library. Nanyi's articles are also suita

In many practical problems, the data given is often visualized for easy observation.Today, the data visualization module in Python is--matplotlib this content system to make it easy to find and use. This article comes from a summary of "data analysis using Python" and some online blogs.1 Matplotlib Introduction Matplot

, where you can design the main body of the new analysis.650) this.width=650; "src=" http://pic.pc6.com/up/2015-1/14224140158935530.jpg "style=" border:0px; "alt=" 14224140158935530.jpg "/>Here, the data source and the new data analysis are done, and the next step is to do a detailed analysis of the data, such as documentation examples.Gender dimension analysis b

= Rev (levels (Uspopage$agegroup)))Operation Result:If you need to draw a percentage stacked chart, simply modify the underlying data based on the work above.The R language implementation code is as follows:# Convert data to percent format Uspopage_prop = ddply (Uspopage, "year", transform, Percent = Thousands/sum (Thousands) * 100) # base function Ggplot (USP Opage_prop, AES (x = year, y = Percent, fill =

That's it. The core component of the large data development platform, the job scheduling system, then discusses one of the faces of the big Data development platform, the data visualization platform. Like a dispatch system, this is another system that many companies may want to build their own wheels ... What the

method is simple to add the marginal carpet function on the basis of the original scatter plot function. The R language implementation code is as follows:# base function Ggplot (Faithful, AES (x = eruptions, y = waiting)) + # Scatter graph function geom_point () + # Marginal carpet function Geom_rug ()　　Operation Result:add a label to a scatter plotThis example uses the following test data set:The method of adding labels to scatter plots is als

! Hoststate::up hoststatetype::hard Servicestate::ok servicestatetype::hard graphiteprefix::jenkins GRAPHITEPO Stfix::swap metrictype::$_servicemetrictype$When you see the above configuration file, there is a question: Why do you want to change the file to this format? The reason is that Nagios's data wants to be transferred to INFLUXDB and needs graphios to act as a porter, Graphios's code is written in Python, where a piece of code is designed to t

= Axes.scatter (type2_x, type2_y, s=40, c= ' green ') Type3 = Axes.scatter (type3_x, type3_y, s=50, c= ' Blue ') Plt.xlabel (the number of miles you earn per year ', Fontproperties=zhfont) Plt.ylabel (percentage of events consumed by you ' playing video games ', Fontproperties=zhfont) Axes.legend ((Type1, type2, Type3), (U ' dislike ', U ' charm General ', U ' very attractive '), loc=2, Prop=zhfont) plt.show ()The resulting scatter plot is as follows:　Summary: This paper briefly introduces Matp