How to Read a % Graph Chart Tha Is More Than 100% Total

I'll begin this blog article by answering the question that appears in the title. I've found that 100% bar graphs, designed in the conventional manner, are only useful for a limited fix of circumstances. Unlike normal stacked bars, the lengths of 100% stacked confined never vary, for they ever add together up to 100%. Consequently, when multiple 100% stacked confined appear in a graph, they only provide information about the parts of some whole, never well-nigh the wholes and how they differ. Therefore, they would never be advisable when information about totals and the parts of which they are made are both of interest, though normal stacked confined oftentimes piece of work well in this scenario. I've found that 100% stacked bar graphs are only useful in three specific situations, which I'll describe in a moment.

I was prompted to write about this when I recently read the book titled "Storytelling with Data" by Cole Nussbaumer Knafic. Cole likes 100% stacked bars. Several appear in her book. When Cole and I met for lunch final week, before long before parting I asked if she would be interested in discussing matters on which we apparently disagree and suggested 100% stacked bar graphs as our opening topic. She graciously welcomed the opportunity, so I began the discussion via email afterward in the calendar week. Our discussion focused primarily on the following graph that appears in her volume as an exemplar of graphical advice.

This graph displays a role-to-whole relationship between projects for which the goals were missed, met, or exceeded by quarter. A 100% stacked bar graph never serves equally the all-time solution for a fourth dimension series. Stacked segments of bars exercise not display patterns of modify through time as clearly every bit lines. In this item example, only the lesser bar segments, representing missed goals, do a decent job of showing the quarterly blueprint of modify. The top segments, representing exceeded goals, invert the design of modify (i.e., the lower the segment extends, the higher the value is that information technology represents), which is confusing. The middle segments, representing met goals, encode the quarterly values as the heights of the segments, not their tops, which makes the blueprint of change impossible to see.

The post-obit line graph displays the data more effectively in every respect.

Despite the perceptual problems that I identified in Cole's 100% stacked bar graph, she feels that it is superior to the line graph above. Her preference is rooted in the fact that the stacked bar graph intuitively indicates the office-to-whole nature of the relationship betwixt missed, met, and exceeded goals. While it is true that a line graph does not by itself land, "these are parts of a whole," this can be easily made clear in the championship, as I did above. For Cole, the stacked bar graph's ability to declare the parts of a whole nature of the relationship without having to analyze this in the title overcomes its perceptual problems.

Let'due south move on to the three occasions when I believe 100% stacked bars are useful:

1. When the bars consist of only 2 segments (east.g., male and female)
2. When we need to compare the sum of multiple parts among multiple bars
3. When nosotros need to compare the percentages of responses to Likert scales

Hither's an example of the first situation:

Considering the bars are divided into 2 segments only (i.e., women and men), it is easy to read the values of each segment and to compare a specific segment through the entire set of bars. This comparison can exist easily made because each segment is aligned through the entire set of bars (women to the left and men to the right). If a third segment were added, still, the segment in the middle would not be aligned to the left or right, which would make comparisons difficult.

I tin can illustrate the other occasion when 100% stacked bars are useful with the following instance from Cole'south book:

The primary purpose of this graph is to compare the sum of client segments iii, 4 and v in the "United states of america Population" versus the sum of the same three customer segments in among "Our Customers." Assuming that no other comparisons are of import, the two 100% stacked bars do the chore effectively. If I were creating this graph myself, still, I would be tempted to brand a few minor adjustments. Assuming that the customer segments have actual names rather than numbers, which is usually the case, and that the specific guild in which the segments appear in a higher place is not necessary, I would identify the highlighted segments at the bottom of the stacked bars, as I've washed below.

This gives the featured segments a common baseline, which makes the comparing of their heights easier. Although it isn't necessary, I also placed the segment names next to both confined because the vertical positions of the segments are not aligned, which makes it easier to identify the segments on the right.

The concluding occasion involves the comparison of Likert scale responses (east.g., Very Dissatisfied, Dissatisfied, Neutral, Satisfied, Very Satisfied). Cole feels that a conventional 100% stacked bar handles this well, illustrated by the following case from her volume:

This particular design does work well for the following purposes:

1. Comparing Strongly Disagree percentages
2. Comparing the combination of Potent Disagree and Disagree percentages
3. Comparing Strongly Concur percentages
4. Comparing the combination of Agree and Strongly Concur percentages
5. Reading the percentage values for Strongly Disagree
6. Reading the percentage values for the sum of Strongly Disagree and Disagree

Even so, it does non work well for the following purposes:

1. Comparison Disagree percentages
2. Comparing Neutral percentages
3. Comparing Agree percentages
4. Reading percentage values of the individual segments Disagree, Neutral, Agree, or Strongly Agree, because mental math is required
5. Reading the percentage values for the sum of Hold and Strongly Concord, considering mental math is required

Given these item strengths and weaknesses, a 100% stacked bar graph of this design would piece of work well to the caste that the audience only needs to admission its strengths.

Variations on the design of 100% stacked bar graphs usually piece of work meliorate. Nearly of these variations display negative results (e.chiliad., Strongly Disagree and Disagree) as negative values running left from zilch and positive results (e.m., Hold and Strongly Agree) equally positive values running right from goose egg. Here's an example:

Designed in this way, differences betwixt positive and negative results now stand out a bit more, the sum of Concur and Strongly Agree are easier to read, and the Neutral values are both easier to read and compare.

For some purposes, the Neutral results may be eliminated birthday, and for some it may be appropriate to split the Neutral results down the middle, displaying half of them every bit negative and half as positive, as follows:

In cases when it's important to compare each individual segment from bar to bar rather than the sum of negative results (Disagree and Strongly Disagree) or positive results (Concord and Strongly Agree), a separate column of bars for each particular on the Likert scale would piece of work all-time, illustrated beneath.

Other than these few occasions when 100% stacked bar graphs are effective, I'one thousand not aware of any other advisable uses of them. If you're aware of other good uses, delight post and depict your examples in my give-and-take forum.

Take care,

bellesbeity1953.blogspot.com

Source: https://www.perceptualedge.com/blog/?p=2239

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