Bar Chart


Bar chart (bar graph, column chart) is the most common approach to visualize amounts for different categories.

Bars height or length is proportional to the values that they represent for each group. It is the easiest way to compare individual metrics side-by-side.

You can see in the glimpse of an eye which columns are the highest, which are the lowest, and how they compare against each other. If there are two or more sets of categories characteristics, we can group or stack the bars.

Bar charts can be also applied to present amounts for discrete periods of time. For instance totals over a monthly period.


  • Comprasion
  • Proportions
  • Categorical data


The plot is a part of package and can be used in React environment as standalone component.


  • Simple bar chart - displays values for different category items.

  • Grouped bar chart - presents the set of values for different categories. Allows comparison of more than one characteristic of given categories. Grouped bars should have the same order in each cluster and each characteristic should use its own color explained by the legend.

  • Stacked bar chart - shows the set of values that make up a whole for different categories. Bars for individual categories are built from the same set of properties and represent the absolute total. Stacked bars should have the same sequence on each bar. Sometimes the whole is standardized to represent 100%. Stacked bar charts work best when the categories are ordinal in nature. The overall pattern of spread across the whole is important here. Ensure the stacked parts have sufficiently different color hues so they are easy to distinguish and do not merge visually.


Property Description Type Default
data Chart data Record<string, any> -
labelSelector Name of data object property used to create labels on axis string -
minValue Minimum value for axis number or “auto” “auto”
maxValue Maximum value for axis number or “auto” “auto”
keys Keys picked from data object used to generate lines string[] [“value”]
disabledKeys Keys that are disabled for rendering data series string[] []
barPadding Padding between bar groups number 0.1
showValues Show values on bars boolean false
valuesAutocolor Automatically adjust values color boolean true
layout Layout applied on chart bars enum[vertical, horizontal] “vertical”
xScaleSettings X Scale settings ScaleSettings { type: ‘band’ }
yScaleSettings Y Scale settings ScaleSettings { type: ‘linear’ }
xAxisTitle Title for X Axis string -
yAxisTitle Title for Y Axis string -
groupMode Group mode enum[grouped, stacked] “grouped”
stackMode Stack mode enum[normal, percent] “normal”
theme Theme used for chart styling Theme Keen Theme
svgDimensions SVG height and width Dimension “auto”
margins SVG margins Margins { top: 50, right: 20, bottom: 50, left: 40 }


List of theme properties supported by Bar widget.

Property Description Type
colors Colors applied on bars string[]
axisX Axis X theme settings Axis
axisY Axis Y theme settings Axis
gridX Grid X theme settings Grid
girdY Grid Y theme settings Grid
tooltip Tooltip settings Tooltip
bar.values Bar values settings { typography: Typography }


The bars should be proportionally sized according to the values - otherwise the perception can be distorted. The best approach is to set the quantitative scale baseline to zero. This will help you keep a proper ratio for bar length and will prevent the misrepresentation of your data.

Bars can be arranged horizontally or vertically. There is no significant difference in perception between these two orientations. Just use the layout that makes it easier to display the range of values and to read the labels associated with each bar.


Color provides an extra dimension in bar chart visualization. Avoid using more than one hue for a simple bar chart if they do not add any additional meaning. Too many colors can just cause visual noise and make it harder to analyse simple data.

Colors are essential for a grouped bar chart and a stacked chart. For these cases apply hues that are easy to distinguish the different metrics in a glimpse. Low contrast between adjoined bars may cause visual merge of different items. All colors should be explained by the legend.


  • If you include axis-scale labels there is no need to label directly each bar value, as it may lead to label overload.
  • Showing gridlines can help increase the precision of judging values.
  • Sorting the values in the chart improves the readability and explains the visual meaning.
  • Set baseline to zero to avoid misrepresentation and misinterpretation of your data.