What are Best Practices When Creating Exploratory Charts?

Data analysis can be a complex and daunting task, especially when dealing with large amounts of data. To make sense of it all, it’s important to create visual representations of the data using exploratory charts. In this article, we will explore best practices when creating exploratory charts, as well as common pitfalls to avoid.


Best Practices When Creating Exploratory Charts

It’s best to use clear and simple visualizations that are easy to read and understand.

Think of it like a traffic sign – it needs to be clear and concise so that anyone can understand it quickly and easily.

It’s important to create many charts with a variety of chart types when exploring data.

This is like trying on different outfits to see which one looks best on you. By using a variety of chart types, you can see the data from different perspectives and gain a better understanding of the patterns and relationships that exist within the data.

Interactive charts can be very useful for data exploration because they allow you to interact with the data and see how it changes in real time.

By using interactive charts, you can gain a more hands-on understanding of the data and identify patterns and relationships that might not be immediately apparent from static charts.

When visually exploring data, it’s important to create charts quickly to find broad patterns instead of spending too much time polishing the design of the charts.

It’s like looking at a sketch to get an idea of what a painting will look like, rather than spending too much time on the details before you have a clear understanding of the bigger picture.


Navigating the Pitfalls

Avoid distorting the data by using chart types that can be misleading.

It’s also important to avoid using too many colors, labels, or other design elements that can clutter the chart and make it difficult to read.

Avoid using “bells and whistles” like 3D effects when creating exploratory charts.

This is because these effects can distort the data and make it difficult to interpret.

In conclusion, creating exploratory charts is an important part of data analysis. By following best practices and using clear and simple visualizations, creating a variety of charts, using interactive charts, creating charts quickly, and avoiding pitfalls like chart distortion and 3D effects, you can gain a better understanding of your data and make more informed decisions when analyzing it.