The prob­lem with pie charts and how this relates to data visu­al­i­sa­tion as a whole.

Many visu­al­iza­tion types have cropped up just in the past two decades, rid­ing the growth of the inter­net. But they nev­er­the­less share many char­ac­ter­is­tics with the garden-variety pie chart, includ­ing some of its pri­mary weak­nesses and a slew of new ones. Rec­og­niz­ing them will move sci­ence closer to tools that work for users, rather than the other way around. […]

Unfor­tu­nately, the pie chart incor­po­rates tasks that we humans sys­tem­at­i­cally fail to per­form accu­rately, all those exer­cises that come at the bot­tom of the hier­ar­chy of per­cep­tual tasks […]. So although we’re good at com­par­ing lin­ear dis­tances along a scale — judg­ing which of two lines is longer, a task used in bar graphs — and we’re even bet­ter at judg­ing the posi­tion of points along a scale, pie charts don’t bring those skills to bear. They do ask us com­pare angles, but we tend to under­es­ti­mate acute angles, over­es­ti­mate obtuse angles, and take hor­i­zon­tally bisected angles as much larger than their ver­ti­cal coun­ter­parts. The prob­lems worsen when we’re asked to judge area and vol­ume: Reg­u­lar as clock­work, we over­es­ti­mate the size of smaller objects and under­es­ti­mate the size of larger ones, to a much greater degree with vol­ume than with area.

Newer visu­al­iza­tions can have these defects and more.

via Link Banana