Two Main Reasons for Creating Visuals

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Data Visualization is one of the most important parts of data analysis process.

Using visuals, it converts the process of telling a story about your analysis to a much easier and straightforward aisle to the audience minds.

Let’s show a sneak peek of what you will gain knowledge of at the end of this article:

1. Two main Reasons for creating visuals
2. Best visual patters for humans
3. What is the meaning of design integrity
4. What to do in order to gain good visuals for both exploratory and explanatory analysis

Two Main Reasons for Creating Visuals

Exploratory Analysis

Analysis done when you are searching for insights. These visualization don’t need to be perfect, you are using plots to find insights, but they don’t need to be aesthetically appealing. You are the consumer of these points & you need to be able to find the answers for your questions from these plots.

Explanatory Analysis

Analysis done when you are providing you results for others. These visualizations need to provide you the emphasis necessary to convey your message, they should be accurate, insightful & visually appealing.

Best Visual Patters for Humans

The most accurate visual patterns for humans are:

Position Changes:

For example, the variation of x- & y- coordinates we see in scatter plot:

stackoverflow.com

Length Changes:

When you see difference in box heights comparison we see in bar charts & histograms:

thetablebar.blogspot.com

Design Integrity

The case when having distorting data have no chance to exist.

It’s the key that when you build plots you maintain integrity for the underlying data.

One of the main ways discussed here for looking at the data integrity was with the lie factor. Lie factor depicts the degree to which a visualization misrepresent the data values being plotted.

As the lie factor increases, it implies that the case is worst.

A great example shown in the resource above.

What to Do In Order to Gain Good Visuals for Both Exploratory and Explanatory Analysis

To have a clear and simple visualizations you must stick into some best practices:

Some are general and some are not:

In General:

• Start with a question
• Repetition is a good thing
• Highlight answers
• Call your audience to action

For Exploratory:

• High data-ink ratio
• Using accurate visual encoding
• Keeping data integrity

For Explanatory:

• Focusing on what grabs audience attention
• Use colors only when necessary, simple is often better
• Tell a story when presenting

Thanks for your time and let’s boost our knowledge!