Tips for Data Visualization

Kate Strachnyi
Towards Data Science
2 min readJul 3, 2018

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Your data is only as good as your ability to understand and communicate it, which is why choosing the right visualization/ chart is essential. If you are unable to present the data effectively, key insights may be lost. Information can be visualized in several different ways, each of which is better at providing a specific insight.

When working with data, start with understanding the story you want to tell or relationship you are trying to highlight. This will aid in selecting the right visualization that will deliver your message.

Before starting to visualize data, you should understand the common types of data:

  1. Quantitative — can be counted or measured; numerical
  2. Categorical — can be sorted according to groups or categories
  3. Discrete — has a finite number of possible values
  4. Continuous — measured and has a value within a range

Understanding data relationships is important to the data visualization process. Common data relationships are listed below:

👉 Time Series — tracks changes in values of a metric over time

👉 Nominal Comparison — compares quantitative values of subcategories

👉 Correlation — data with two or more variables that may have a positive or negative correlation to each other

👉 Part-to-Whole-Relationships — subset of data compared to the larger whole

👉 Distribution — shows data distribution around a central value

👉 Deviation — shows how data points relate to each other, to see how far any given point is from the mean

👉 Ranking — shows how two or more values compare to each other in relative magnitude

Other tips:

Use icons to enhance understanding and reduce extra labels/ legends

Order data sets using a logical hierarchy

Visualize data in a way that makes it simple for the audience to compare values

Highlight important information using annotations or callouts

Use one color to represent each category, consistently throughout the presentations/ dashboards

Don’t use 3D charts — it may skew understanding of the information

Avoid using more than 5 colors in a view

Don’t use distracting background colors or those that have gradients

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