Difference between revisions of "Data visualization"

Jump to: navigation, search
(Created page with "{{subst:dime_wiki}}")
 
Line 1: Line 1:
<span style="font-size:150%">
+
Data visualization is creating a visual representation of your data, for example in the form of a chart or a graph. Choosing the right format to visualize your data is critical to effectively communicating the results of your study. Good visualizations can be more memorable and persuasive than pure text.  
<span style="color:#ff0000"> '''NOTE: this article is only a template. Please add content!''' </span>
 
</span>
 
  
  
add introductory 1-2 sentences here
+
== Read First ==
 +
Specific code for data visualization is available on the software-specific tools (e.g. [[iegraph]]). This page discusses general principles for data visualization. [http://www.example.com link title]
 +
 
 +
== Guidelines ==
 +
 
 +
=== What type of data visualization should I use? ===
 +
The best format for data visualization will depend on the type of data and results you wish to display, as well as the medium in which they will be displayed. For example, online interfaces allow for more dynamic visualizations than printed articles.
  
 +
* [https://www.data-to-viz.com/ |[Data to Viz] provides a handy decision tree.
  
 +
* The [http://www.visual-literacy.org/periodic_table/periodic_table.html|Periodic Table of Visualization] provides a catalogue of all data visualization types with visual examples.
  
== Read First ==
+
* Gapminder.org  [https://www.gapminder.org/tools/#$chart-type=bubbles|interactive visualization tools] provide beautiful examples of effective visualizations.
* include here key points you want to make sure all readers understand
 
  
 +
===Stata Visual Library===
 +
The DIME Analytics team has created a [https://worldbank.github.io/Stata-IE-Visual-Library/|Stata Visual Library for Impact Evaluation] which shows examples of graphs and provides the codes used to create them. You can contribute to the library [https://github.com/worldbank/Stata-IE-Visual-Library|on our github].
  
== Guidelines ==
+
=== Data Visualization in R ===
* organize information on the topic into subsections. for each subsection, include a brief description / overview, with links to articles that provide details
+
R has many options for data visualization; the ggplot package is one of the best. Here is a list of [http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html|50 ggplot2 Visualizations with full R code] .
===Subsection 1===
 
===Subsection 2===
 
===Subsection 3===
 
  
 
== Back to Parent ==
 
== Back to Parent ==
This article is part of the topic [[*topic name, as listed on main page*]]
+
This article is part of the topic [[Data Analysis]]
  
  
 
== Additional Resources ==
 
== Additional Resources ==
* list here other articles related to this topic, with a brief description and link
+
* Harvard Business Review Article on [https://hbr.org/2016/06/visualizations-that-really-work|Visualizations that Really Work]
 +
 
 +
 
  
[[Category: *category name* ]]
+
[[Category: Data Analysis]]

Revision as of 15:30, 20 July 2018

Data visualization is creating a visual representation of your data, for example in the form of a chart or a graph. Choosing the right format to visualize your data is critical to effectively communicating the results of your study. Good visualizations can be more memorable and persuasive than pure text.


Read First

Specific code for data visualization is available on the software-specific tools (e.g. iegraph). This page discusses general principles for data visualization. link title

Guidelines

What type of data visualization should I use?

The best format for data visualization will depend on the type of data and results you wish to display, as well as the medium in which they will be displayed. For example, online interfaces allow for more dynamic visualizations than printed articles.

Stata Visual Library

The DIME Analytics team has created a Visual Library for Impact Evaluation which shows examples of graphs and provides the codes used to create them. You can contribute to the library our github.

Data Visualization in R

R has many options for data visualization; the ggplot package is one of the best. Here is a list of ggplot2 Visualizations with full R code .

Back to Parent

This article is part of the topic Data Analysis


Additional Resources