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What is D3.js?

Discuss about the Data Visualization Using D3JS.

Data visualisation defines data in a graphical form, and it helps the decision makers to develop a pattern of data. D3.js or Data Driven Documents is a Javascript Library that is used to develop interactive as well as dynamic data visualisations. D3.js enables users to bind arbitrary data to a Document Object Model (DOM). D3.js applies data-driven transformations to the document. A user can generate HTML table from the array of numbers with the assistance D3.js. D3.js solves the problem’s crux. It provides an effective manipulation of documents by data. D3.js thus avoids proprietary representation and caters flexibility. One can get the full functionalities of web standard such as CSS, HTML and SVG. It requires minimal overhead. Also, D3.js is relatively fast and can support large datasets. D3.js technology supports dynamic behaviours for animations well as interaction. The functional style of D3 enables the code reuse through a collection of community-developed modules as well as official modules.

Selections: D3.js can be used as to modify the documents by using the W3C DOM API. The method names used are verbose. D3.js takes the declarative approach and works on an set of nodes known as selections.  W3C Selectors API defines the selectors, and nearly all the modern browsers support the selectors. The D3.js elements can be selected utilising the predicates; the predicates involve ID, containment, attribute values and class.

D3.js caters various methods for the nodes mutation. D3.js is used to set attributes or styles. The D3.js is useful to register event listeners. D3.js can prove to be useful for adding and removing nodes. The nodes can also be sorted with the help of D3.js. The text content, as well as the HTML code, can be changed with the help of D3.js.

Dynamic Properties: D3.js has some similarities with jQuery. The d3.geoPath function provides functionalities like the conversion of geographic coordinates to SVG path data. D3.js comes with reusable functions and function factories like graphical primitives for the line, area and pie charts.

Enter and Exit: The user can create new nodes for the arriving data. D3.js can be used to remove the outgoing nodes that are obsolete.

Transformation: D3.js does not use a new visual representation. D3.js’s graphical marks come directly from the web standards CSS, HTML and SVG. A user can develop SVG elements using the technology of D3.js and style them with the external stylesheets. The user can use the filter effects, dashed strokes as well as the clipping. The user will not require any new toolkit to use if the browser vendors update themselves and introduce new features.

Features of D3.js

Transitions: D3.js’s interpolators support primitives like numbers and the numbers within the string. The user can be able to extend D3.js interpolators registry to support the data structures as well as the complex properties.

D3.js is open source library, and it enables the users to integrate user’s code to the code samples that are already present within the framework. Thus the users can be able to create their diagrams with the already prevalent charting library. D3.js provides a platform with unique charts. The users can be able to develop their charts with already existing codes that are available within the framework library. The d3.js framework is relatively very easy to use for all the functions. D3.js provides certain functionalities like –

Free and Open Source- D3.js integrates with the large dataset of examples and documentation of functions as well as codes.

Flexible platform- D3.js is flexible, and it can work flawlessly with the prevalent web technologies. It helps to make any modifications within the DOM. Thus D3.js provides similar kinds of flexibility offered by SVG, HTML and CSS.

Highly dynamic- D3.js is highly dynamic; it works relatively fast and responsive. D3.js is dynamic as well as interactive at the same time. The D3.js facilitates the users to explore data by own using skills and creativity. The functionality of DOM is dynamic, the users can be able to add classes or can remove classes and the IDs at any time the user wants.

Capacity to handle a large volume of data- D3.js is relatively better compared to the other frameworks. D3.js provides facility to the users to manage large chunks of data very easily freeing up both resources as well as time.

Aids in writing custom code- There are several customisation options available for D3.js. The users or the coders can build custom codes. Thus, D3.js provides the platform and freedom to the coders so that the coders can experiment and can develop custom code.

Rich Array of plugins- D3.js has a huge plugin collection. The coders have the liberty to use those plugins instead of using the proprietary software’s plugin.

Re-usable code- D3.js has a functional style, and D3.js comes with diverse components and plugins collection, and it helps the coders or the users to reuse the code.

D3.js has several properties like selections, transitions, enter and exit, and data binding.

Besides having several advantages, D3.js also have several disadvantages-

Selections in D3.js

D3.js does not support the old browsers. The developers will have to build a static placeholder so that all the users can view the browsers and the contents of the browsers. If the static placeholder is not used then, the content on the browsers will not be visible to all the users.

D3.js also have data-source imitations. Also, D3.js cannot conceal authentic data. If the users do not want to disclose any data, then it can prove to be challenging for the users to use the D3.js framework or the technology.

D3.js cannot generate predetermined visualisations; it is time-consuming the generate the D3.js visualisations, one can generate the visualisations with the help of quick chart relatively fast compared to D3.js.

It is nearly impossible to visualise large dataset on the web without installing any apps. For this reason, they must use D3.js. The users can be able to develop custom visualisations with the aid of the D3.js. D3.js is web based visualisation library which provides a plethora of APIs to manage the heavy lifting of creating advanced, dynamic and visualisation content online. The users can be able to build own diagrams with the prevalent charting library. The gallery contains the unique charts and D3.js gives the opportunity to the users to develop charts on their own using the codes that are available in the D3.js framework library. D3.js offers several facilities. D3.js is open source and free to use. It offers flexibility, and it is highly dynamic. D3.js can handle large volumes of data, helps coders to write custom codes.

The proposed web application has used the data sets of the athletics of the 2016 Olympics in Rio de Janeiro. The application shows the distribution of gold medals between various countries.

The fraction of the data set has presented in below.

id

name

nationality

sex

dob

height

weight

sport

gold

silver

bronze

736041664

A Jesus Garcia

ESP

male

10/17/1969

1.72

64

athletics

0

0

0

532037425

A Lam Shin

KOR

female

9/23/1986

1.68

56

fencing

0

0

0

435962603

Aaron Brown

CAN

male

5/27/1992

1.98

79

athletics

0

0

1

521041435

Aaron Cook

MDA

male

1/2/1991

1.83

80

taekwondo

0

0

0

33922579

Aaron Gate

NZL

male

11/26/1990

1.81

71

cycling

0

0

0

173071782

Aaron Royle

AUS

male

1/26/1990

1.8

67

triathlon

0

0

0

266237702

Aaron Russell

USA

male

6/4/1993

2.05

98

volleyball

0

0

1

382571888

Aaron Younger

AUS

male

9/25/1991

1.93

100

aquatics

0

0

0

87689776

Aauri Lorena Bokesa

ESP

female

12/14/1988

1.8

62

athletics

0

0

0

997877719

Ababel Yeshaneh

ETH

female

7/22/1991

1.65

54

athletics

0

0

0

343694681

Abadi Hadis

ETH

male

11/6/1997

1.7

63

athletics

0

0

0

591319906

Abbas Abubakar Abbas

BRN

male

5/17/1996

1.75

66

athletics

0

0

0

258556239

Abbas Qali

IOA

male

10/11/1992

   

aquatics

0

0

0

 
Total 11538 rows have been used within the data set.

var svg = dimple.newSvg("#chartContainer",600,410);

The above code is used for generating the SVG file with specific size.

chart.addSeries("nationality",dimple.plot.bar);

The above code is used for plotting, with nationality as series.

It has been found that the Chrome is not able to collect data form external source. That is why the visualization app has been opened in the firefox. The graph shows total amount of gold for a specific sport.

Bryant, N. and Wildfire, J., 2016. Webcharts–A Web-based Charting Library for Custom Interactive Data Visualization. Journal of Open Research Software, 4(1).

Castillo, P.N., 2014. Mastering D3. js. Packt Publishing Ltd.

David, A. and Tauro, C.J., 2015. Web 3D data visualization of spatio temporal data using data driven document (D3js). International Journal of Computer Applications, 111(4).

Friend, S., 2015. Visualizing Relationships between Related Variables: Improving Physics Education through D3. js Network Visualizations.

Gibbs, C., Hernandez, M. and Sennyey, P., 2017. Adopting a distributed model for data services. Code4Lib Journal, 35.

Hanson, B.A. and Seeger, C.J., 2016. D3. js: Introduction to Mapping.

Heydt, M., 2015. D3. js by example. Packt Publishing Ltd.

Kreft, ?., Botzki, A., Coppens, F., Vandepoele, K. and Van Bel, M., 2017. PhyD3: a phylogenetic tree viewer with extended phyloXML support for functional genomics data visualization. Bioinformatics, 33(18), pp.2946-2947.

Kromer, L., Wagner, M., Blumenstein, K., Rind, A. and Aigner, W., 2016. Performance Comparison between Unity and D3. js for Cross-Platform Visualization on Mobile Devices. In Proceedings of the Forum Media Technology (pp. 47-52).

Mattingly, W.A., Kelley, R.R., Chariker, J.H., Weimken, T. and Ramirez, J., 2015. An iterative workflow for creating biomedical visualizations using Inkscape and D3. js. BMC bioinformatics, 16(15), p.P10.

Morales, A.F., 2016. Enriching the statistics learning experience with D3. js interactive animations: Insurance applications of Markov chains. IJERI: International Journal of Educational Research and Innovation, (7), pp.25-37.

Ono, K., Demchak, B. and Ideker, T., 2014. Cytoscape tools for the web age: D3. js and Cytoscape. js exporters. F1000Research, 3.

Strode, G., Thornton, B., Mesev, V. and Johnson, N., 2016. Bivariate Statistical Legends: Mapping Examples on Florida Covariance Data using Scatterplots from Open Source Visual Analytic Tools. The Florida Geographer, 47.

Woodward, K., 2017. Visualizing Cyclic Datasets: Circular Streamgraphs Using D3. js.

Cite This Work

To export a reference to this article please select a referencing stye below:

My Assignment Help. (2019). Data Visualization With D3.js: Overview And Features. Retrieved from https://myassignmenthelp.com/free-samples/data-visualization-using-d3js.

"Data Visualization With D3.js: Overview And Features." My Assignment Help, 2019, https://myassignmenthelp.com/free-samples/data-visualization-using-d3js.

My Assignment Help (2019) Data Visualization With D3.js: Overview And Features [Online]. Available from: https://myassignmenthelp.com/free-samples/data-visualization-using-d3js
[Accessed 24 November 2024].

My Assignment Help. 'Data Visualization With D3.js: Overview And Features' (My Assignment Help, 2019) <https://myassignmenthelp.com/free-samples/data-visualization-using-d3js> accessed 24 November 2024.

My Assignment Help. Data Visualization With D3.js: Overview And Features [Internet]. My Assignment Help. 2019 [cited 24 November 2024]. Available from: https://myassignmenthelp.com/free-samples/data-visualization-using-d3js.

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