Tag: bar plot

A fellow data analyst asked a question? What do we do when we need to draw a stacked bar chart that has too many colors? How do we select the colors so that they are nice but also are easily distinguishable? To answer this question, let’s look at the data similar to what appeared in the original question. I also tried to recreate the actual chart’s style

Slope charts are often suggested as a valid alternative to clustered bar charts, especially for “before and after” cases.

A radar chart (sometimes called “spider charts”) look cool but are, in fact,
pretty lame. So much so that when the data visualization author Stephen Few mentioned them in his book Show me the numbers, he did so in a chapter called “Silly graphs that are best forsaken.”

A data giraffe is a situation where a very prominent data point shades everything else. I learned this term from a post by Pini Yakuel and immediately liked it a lot.

Dr. Richard Brath is a data visualization expert who also blogs from time to time. Each post in Richard’s blog provides a deep, and often unexpected to me, insight into one dataviz aspect or another.

My colleague, Chares Earl, pointed me to this interesting 2010 post that explores different ways to visualize categories of drastically different sizes.

In the data visualization world, not starting a bar chart at zero is a “BIG NO”. Some people protest. “How come can anyone tell me how to start my bar chart? The Paper/Screen can handle anything! If I want to start a bar chart at 10, nobody can stop me!”

Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics. Look at this example from the seaborn documentation site