TRIMMING makes it SHARPER

As a data visualizer, I have to deal with multiple type of graphs/charts in a day. Though different type of viewer reads and understands the data in different way, one thing which can make them stop looking at your data is if it is very cluttered. Data clutterness usually occurs due to not 'Trimming out' elements which are not critical to the data storytelling. Here are few examples and concepts which require trimming out while presenting data with a story.

Redundancy in data graphs refers to including single information multiple times. For example: On the Y axis, you have data range. Even then, including data label or data table might seem redundant in the graph. Data range, data label and data table, these are used either or for separate purposes, not to use together. Or writing 'Million' in the title to tell all the data are in millions and then again writing the 'In millions' in Y Axis data range.

Non Critical Elements like grid lines, blank legends, which does not add much value to the story, sometimes makes it look very messy and unorganized. Hence, anything which is considered as non critial to the story, should be trimmed out.

Value with lots of digits is another way of cluttering the graphs. If your data value is in Hundred, Thousands, Mn, Bn, or so, use the graph settings to convert the value to different unit (Watch this video for the tip: https://www.youtube.com/watch?v=Ng7JyEUHjSw). Once you use it, the graphs/charts will look far more meaningful and concise.

Decimals in number is very important in terms of low numbers (Mn, Bn) or percentage. Other than that, try to avoid using decimal values in graphs since it will make the value look bigger. We should only use it when a little fraction makes a lot of difference.

What is your idea of trimming out data graphs/charts? Let me know through comments.