The best 20 data visualization tools for visualization

Source: Internet
Author: User

The best 20 data visualization tools for visualization

Reprinted original URL: http://www.iteye.com/news/28093


Data Visualization makes data more intuitive and lays the foundation for developers to make correct decisions. This article describes 20 different data visualization tools, from simple lists to complex tables, to maps and information charts. Most of these tools are free of charge and hope to help you.

I. Entry level 

First, let's take a look at the tools you are familiar with. They may have unexpected uses. If you are just getting started, you need to know these tools first.

1. Excel

In fact, you can use Excel to calculate complex data, such as cell heat maps and scatter plots. As an entry-level tool, it can quickly search for data or create visual data for internal use. However, because color, line, and style are set by default, makes it difficult to create images for certain professional publications or websites. However, I still recommend that you use Excel.

Excel is a tool in Microsoft Office kit. If you don't have it, other tools can also implement similar functions, such as Google Docs and Google Drive.



2. CSV/JSON

CSV (comma-separated values) and JSON (JavaScript Object symbols) are not a visualization tool, but they are basic data formats. You need to understand their structure and how to obtain data. The following toolkit supports at least one or two data formats.

2. Network Data Visualization 

3. Google Chart API

Some static image tool kits are no longer used by people. The Google Chart Tool website now only provides dynamic chart tools. These tools are powerful and all browsers support SVG, canvas, and VML. However, there is a serious problem: they are generated on the client. if JavaScript is not supported on the device, they are used in a non-networked State, or they are saved in different formats, the problem may occur. Static Images do not have these problems.

However, APIs have all the functions, including bar charts, line charts, maps, and even QR code. You can use Google to find the right Visualization Based on your actual needs without special customization. As a starting point, this is a great tool.



4. Flot)

Float is a great line chart and bar chart creation tool that can be applied to all browsers that support canvas-meaning most mainstream browsers. This is a jQuery library. If you are familiar with jQuery, you can easily perform image callback, style, and behavior operations.

The advantage of floating is that you can access a large number of calling functions, so that you can run your own code. Set a style that allows users to show different effects when hovering, clicking, and moving the mouse. Float gives you more flexibility than other plotting tools. Float does not provide many options, but it can perform common functions well.



5. Rapha mozl (Rafael)

Rafael is another great JavaScript library for creating charts and graphics. The biggest difference from other libraries is that it focuses on SVG and VML output formats. This has advantages and disadvantages. Because SVG is a vector format, it looks good at any resolution, but it creates a DOM node for each element, which is a little slower than creating raster images through canvas. However, the advantage is that you can operate and add events for each DOM element, just like HTML. A large number of web pages demonstrate Rafael's easy creation of common tables and graphics, because it can render SVG at will, and it can create very complex visual effects, you don't have to use other illustrations or Vector Plotting tools.



6. D3

D3 is another JavaScript library that supports SVG rendering. You can not only create simple bar charts and line charts, but also create more complex canvas charts, tree charts, circular set charts, and character clouds. D3 can be used to make complex interactions, but it does not mean that it must be used. It is very important to select the right tool to clearly display the image.



7. Visual. ly

If you need information charts instead of data visualization graphs, the tool you are about to introduce can help you. Visual. ly is very popular and useful. Infographic design is often used on the Internet. It provides a template option that links charts to your Facebook or Twitter account and displays cute cartoon backgrounds. Although its use is limited, it is a useful source of inspiration.



3. Interactive GUI controls 

What will happen if you combine data visualization and GUI controls? With the development of online visualization, buttons, drop-down, and slider evolve into more complex interface elements, allowing you to expand content while changing input parameters and data. Control and content integration. The tools described below can help you explore this feasibility.

8. Crossfilter

We build more complex tools so that customers can quickly view various types of data. Crossfilter is a JavaScript library that can complete all the preceding content. When displaying data, you can also set a limit and view other linked charts.



9. Tangle

Tangle blur the boundaries between controls and content. When you try to describe a complex interaction or equation, you want the user to adjust the input value and give the output result a powerful control method to explore data. You can use the JavaScript library Tangle. Drag to increase or decrease the variable value, and you can see that the chart automatically changes, the effect is amazing.



Iv. Map 

Maps are very difficult to use on the network. Google Maps illustrates how online Maps work first. Google then released the map API, which allows any developer to embed Google Maps into their own websites. Since then, the market has matured a lot. If you are looking for a solution to embed a custom map in a project, there are already many options. The key is to select the most appropriate one.

10. Modest Maps

Modest Maps is a tiny Image Library of only 10 KB. It is the smallest of all the tools described in this article. This makes the basic form of it very limited, but do not underestimate it, install some extensions, similar to Wax, the tool will become very powerful. Existing products include Stamen, Bloom, and MapBox.



11. Leaflet

Leaflet is a tiny map framework developed by the CloudMade team. It is small and lightweight and used to create map applications friendly to mobile pages. Leaflet and Modest Maps are both open-source. You can use them flexibly based on your website needs. This tool has powerful backup functions, so you don't have to worry that they will disappear.



12. Polymaps

Polymaps is also a gallery that can be directly used for data visualization. Polymaps is also a powerful resource library, similar to the CSS selector that allows you to create unique map styles.



13. OpenLayers

OpenLayers is perhaps the most powerful repository. Although there are not many documents, it is difficult to operate, but there are no other tools to use in some aspects. When you need a very special tool that is not provided by other libraries, you can choose OpenLayers.



14. Kartogragh

The marking line in Kartogragh redefined the map. We are used to Mercator projection, but Kartogragh provides more options. If you are not processing world-wide data and want to put your map in a definition box, then using Kartogragh can make your design stand out.



15. CartoDB

CartoDB can easily combine table data with maps. For example, if you enter an address string, it can be converted to the longitude and latitude, and marked on the map. It has five free tables, and others are charged monthly.



5. Advanced data visualization tools 

If you want to achieve high-level data visualization, in addition to simple Web-based tools, you also need more useful things, including desktop applications and programming environments.

16. Processing

Processing is an exemplary tool for interactive visual Processing. It allows you to use simpler code and then compile it into Java in sequence. The Processing. js tool enables your webpage to use Processing without a Java application. Its Objective-C port enables you to use Processing on iOS platform. It is a desktop application that can be used on all platforms. In recent years, there have been a large number of instances and Code on the Internet.



17. NodeBox

NodeBox is an OS X application used to create two-dimensional graphics and data visualization. You need to understand the Python code. In addition, it can easily and quickly adjust the variables and view the results immediately. It is similar to Processing, but NodeBox is not interactive.



Vi. Professional tools 

In addition to the several simple tools described above, there are also professional data processing tools for professionals to use. Industry-standard tools, such as SPSS and SAS, are expensive to order, so they are generally only available to large and academic institutions. The tools we will introduce are available for free and powerful. These open-source software are very useful and have powerful plug-ins and support.

18. R

How many software comes with a search engine? R is a very complex software used to analyze the statistical data packages of large datasets. It has a powerful community and database and takes some time to master. R is the most difficult tool to learn in this article. When you master it, you will feel proud.



19. Weka

Further, when you reach the expert level, you need to expand your capabilities, not only to create data visualization, but also to learn data mining technology. Weka is used for data classification and clustering of various attributes to facilitate data browsing. In addition, it can generate a simple plan.



20. Gephi

When people talk about associativity, social graphs, and relationships, they usually refer to the two nodes in the same network connection. The node here may be someone in the company, the words in the file or the passing players in the football match, but the principle is the same. Gephi is a data browser based on chart visualization. It can not only compress large datasets, create beautiful visual effects, but also clear and organize data.


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