"Pie charts have weaknesses and dangers inherent in their design and application. First, it is generally inadvisable to attempt to portray more than four or five categories in a circle chart, especially if several small sectors are of approximately the same size. It may be very confusing to differentiate the relative values. Secondly, the pie chart loses effectiveness if an effort is made to compare the component values of several circles, as might occur in a temporal or geographical series. [...] Thirdly, although values are measured by distances along the arc of the circle, there is a tendency to estimate values in terms of areas by size of angle. The 100-percent bar chart is often preferable to the circle chart's angle and area comparison as it is easier to divide into parts, more convenient to use, has sections that may be shaded for contrast with grouping possible by bracketing, and has an easily readable percentage scale outside the bars." (Anna C Rogers, "Graphic Charts Handbook", 1961)
"Since bars represent magnitude by their length, the zero line must be shown and the arithmetic scale must not be broken. Occasionally an excessively long bar in a series of bars may be broken off at the end, and the amount involved shown directly beyond it, without distorting the general trend of the other bars, but this practice applies solely when only one bar exceeds the scale." (Anna C Rogers, "Graphic Charts Handbook", 1961)
"The common bar chart is particularly appropriate for comparing magnitude or size of coordinate items or parts of a total. It is one of the most useful, simple, and adaptable techniques in graphic presentation. The basis of comparison in the bar chart is linear or one-dimensional. The length of each bar or of its components is proportional to the quantity or amount of each category represented." (Anna C Rogers, "Graphic Charts Handbook", 1961)
"If you want to dramatize comparisons in relation to the whole. use a pie chart. If you want to add coherence to the narrative, the pie chart also helps because it depicts a whole. If your main interest is in stressing the relationship of one factor to another, use bar charts. If you wish to achieve all these effects. you can use either type of chart. and decide on the basis of which one is more aesthetically or pictorially interesting." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)
"Some believe that the vertical bar should be used when comparing similar items for different time periods and the horizontal bar for comparing different items for the same time period. However, most people find the vertical-bar format easier to prepare and read. and a more effective way to show most types of comparisons." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)
"The bar or column chart is the easiest type of graphic to prepare and use in reports. It employs a simple form: four straight lines that are joined to construct a rectangle or oblong box. When the box is shown horizontally it is called a bar; when it is shown vertically it is called a column. [...] The bar chart is an effective way to show comparisons between or among two or more items. It has the added advantage of being easily understood by readers who have little or no background in statistics and who are not accustomed to reading complex tables or charts." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)
"The bar graph and the column graph are popular because they are simple and easy to read. These are the most versatile of the graph forms. They can be used to display time series, to display the relationship between two items, to make a comparison among several items, and to make a comparison between parts and the whole (total). They do not appear to be as 'statistical', which is an advantage to those people who have negative attitudes toward statistics. The column graph shows values over time, and the bar graph shows values at a point in time. bar graph compares different items as of a specific time (not over time)." (Anker V Andersen, "Graphing Financial Information: How accountants can use graphs to communicate", 1983)
"The bar of a bar chart has two aspects that can be used to visually decode quantitative information - size (length and area) and the relative position of the end of the bar along the common scale. The changing sizes of the bars is an important and imposing visual factor; thus it is important that size encode something meaningful. The sizes of bars encode the magnitudes of deviations from the baseline. If the deviations have no important interpretation, the changing sizes are wasted energy and even have the potential to mislead." (William S. Cleveland, "Graphical Methods for Data Presentation: Full Scale Breaks, Dot Charts, and Multibased Logging", The American Statistician Vol. 38 (4) 1984)
"A bar graph typically presents either averages or frequencies. It is relatively simple to present raw data (in the form of dot plots or box plots). Such plots provide much more information. and they are closer to the original data. If the bar graph categories are linked in some way - for example, doses of treatments - then a line graph will be much more informative. Very complicated bar graphs containing adjacent bars are very difficult to grasp. If the bar graph represents frequencies. and the abscissa values can be ordered, then a line graph will be much more informative and will have substantially reduced chart junk." (Gerald van Belle, "Statistical Rules of Thumb", 2002)
"Stacked bar graphs do not show data structure well. A trend in one of the stacked variables has to be deduced by scanning along the vertical bars. This becomes especially difficult when the categories do not move in the same direction." (Gerald van Belle, "Statistical Rules of Thumb", 2002)
"Choose scales wisely, as they have a profound influence on the interpretation of graphs. Not all scales require that zero be included, but bar graphs and other graphs where area is judged do require it."
"Distance and detection also play a role in our ability to decode information from graphs. The closer together objects are, the easier it is to judge attributes that compare them. As distance between objects increases, accuracy of judgment decreases. It is certainly easier to judge the difference in lengths of two bars if they are next to one another than if they are pages apart."
"Use of a histogram should be strictly reserved for continuous numerical data or for data that can be effectively modelled as continuous […]. Unlike bar charts, therefore, the bars of a histogram corresponding to adjacent intervals should not have gaps between them, for obvious reasons.
"Generally pie charts are to be avoided, as they can be difficult to interpret particularly when the number of categories is greater than five. Small proportions can be very hard to discern […] In addition, unless the percentages in each of the individual categories are given as numbers it can be much more difficult to estimate them from a pie chart than from a bar chart […]." (Jenny Freeman et al, "How to Display Data", 2008)
"Mosaic plots are defined recursively, i.e., each variable that is introduced in a mosaic plot is plotted conditioned on the groups already established in the plot. As with barcharts, the area of bars or tiles is proportional to the number of observations (or the sum of the observation weights of a class). The direction along which bars are divided by a newly introduced variable is usually alternating, starting with the x-direction." (Martin Theus & Simon Urbanek, "Interactive Graphics for Data Analysis: Principles and Examples", 2009)
"Sorting data is one of the most efficient actions to derive different views of data in order to see the variables from many angles. Sorting is usually not applied to the data itself, but to statistical objects of a plot. We might want to sort the bars in a barchart, the variables in a parallel boxplot or the categories in a boxplot y by x." (Martin Theus & Simon Urbanek, "Interactive Graphics for Data Analysis: Principles and Examples", 2009)
"So what is the difference between a chart or graph and a visualization? […] a chart or graph is a clean and simple atomic piece; bar charts contain a short story about the data being presented. A visualization, on the other hand, seems to contain much more ʻchart junkʼ, with many sometimes complex graphics or several layers of charts and graphs. A visualization seems to be the super-set for all sorts of data-driven design." (Brian Suda, "A Practical Guide to Designing with Data", 2010)
"[...] if you want to show change through time, use a time-series chart; if you need to compare, use a bar chart; or to display correlation, use a scatter-plot - because some of these rules make good common sense." (Alberto Cairo, "The Functional Art", 2011)
"Histograms are often mistaken for bar charts but there are important differences. Histograms show distribution through the frequency of quantitative values (y axis) against defined intervals of quantitative values(x axis). By contrast, bar charts facilitate comparison of categorical values. One of the distinguishing features of a histogram is the lack of gaps between the bars [...]" (Andy Kirk, "Data Visualization: A successful design process", 2012)
"There's a strand of the data viz world that argues that everything could be a bar chart. That’s possibly true but also possibly a world without joy." (Amanda Cox, [interview in ( Scott Berinato's "The Power of Visualization’s 'Aha!' Moments, Harvard Business Review] 2013)
"Visualization is what happens when you make the jump from raw data to bar graphs, line charts, and dot plots. […] In its most basic form, visualization is simply mapping data to geometry and color. It works because your brain is wired to find patterns, and you can switch back and forth between the visual and the numbers it represents. This is the important bit. You must make sure that the essence of the data isn’t lost in that back and forth between visual and the value it represents because if you can’t map back to the data, the visualization is just a bunch of shapes."
"If I had to pick a single go-to graph for categorical data, it would be the horizontal bar chart, which flips the vertical version on its side. Why? Because it is extremely easy to read. The horizontal bar chart is especially useful if your category names are long, as the text is written from left to right, as most audiences read, making your graph legible for your audience." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)
"Sometimes bar charts are avoided because they are common. This is a mistake. Rather, bar charts should be leveraged because they are common, as this means less of a learning curve for your audience." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)
"Visual clutter is one of the most serious issues with bar charts. Using a bar to represent a simple data point is clearly overkill that results in no room for more data. At times, this may make us overlook less obvious things. The population pyramids offer a glaring example of this. But dot plots are not only about reducing clutter and avoiding overstimulation. Because we don’t compare heights, dot plots actually allow us to break the scale to improve resolution, and that’s a big plus over bar charts." (Jorge Camões, "Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel", 2016)
"The radial bar chart, also called the polar bar chart, arranges the bars to radiate outward from the center of a circle. This graph lies lowers on the perceptual ranking list because it is harder to compare the heights of the bars arranged around a circle than when they are arranged along a single flat axis. But this layout does allow you to fit more values in a compact space, and makes the radial bar chart well-suited for showing more data, frequent changes (such as monthly or daily), or changes over a long period of time." (Jonathan Schwabish, "Better Data Visualizations: A guide for scholars, researchers, and wonks", 2021)
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