Bar charts are versatile tools for comparing values across categories. This section dives into different types of bar charts, from vertical and horizontal to grouped and stacked, exploring their strengths and best use cases.

We'll also look at design principles for creating effective bar charts. From proper proportions and spacing to color choices and ordering, these tips will help you craft clear, impactful visualizations that tell your data story.

Bar chart types and uses

Common use cases for bar charts

• Display and compare values across different categories using rectangular bars
• Vertical bar charts show categories on the x-axis and values on the y-axis
  • More common and easier to read category labels compared to horizontal
• Horizontal bar charts flip the orientation with categories on y-axis and values on x-axis
  • Useful for plotting a large number of categories legibly (countries, survey responses)
  • Negative numbers can be displayed extending to the left of the zero baseline

Variations of bar charts for specific analysis needs

• Grouped bar charts display multiple data series side-by-side for each category
  • Enable comparisons between the series across the categories (sales by region and product)
  • Can become cluttered if there are too many series or categories
• Stacked bar charts place the series bars on top of each other
  • Shows the composition or breakdown of a total value for each category (budget allocation)
  • Can be difficult to compare the sizes of inner series across the categories
• Diverging bar charts use bi-directional bars that extend from a center baseline
  • Show negative and positive values for each category (change in account balance)
  • Vertical or horizontal orientation, often used for likert scale survey data
• Bullet charts compare a primary measure to one or more other measures
  • Uses different shades and a target marker to provide context (actual vs budgeted costs)
  • Less common and not always supported natively in charting applications

Design principles for bar charts

Proportions and spacing of bars and axes

• Bars should be consistently sized with equal widths for accurate comparison
• Distinct spacing between bars, typically around half the width of the bars
• Axis containing values must start at zero to avoid distorting relative bar lengths
  • Diverging bar charts are an exception and may have a non-zero center baseline
• Clearly label axes and gridlines, but keep them visually subtle to not distract

Color and ordering considerations

• Use solid colors for bars, varying hue for multiple series
  • Apply color strategically to highlight key data points, not decoratively
  • Limit to 2-3 colors and ensure they are distinct for color blind friendliness
• Order bars by value or another logical grouping to aid in comparison and storytelling
  • Alphabetical category ordering is rarely analytically useful
  • Consider grouping bars into meaningful segments (by time period, geographic region)
• Avoid using distracting gradients, patterns, or 3D effects on the bars
  • Borders and shading should be used sparingly and intentionally to highlight

Strengths and weaknesses of bar chart designs

Vertical and horizontal bar charts

• Vertical best for comparing a single value across many categories
  • Easier to read category labels, especially longer text
  • Limited in how many bars can legibly fit along the x-axis (about 25 max)
• Horizontal good for large number of categories or negative values
  • Category labels remain legible even with 50+ bars
  • Value labels may overlap if data has a large range requiring a wider x-axis

Grouped and stacked bar charts

• Grouped allows for easy comparison between multiple series for each category
  • Quickly see which series is highest for a category and compare across groups
  • Too many series or categories can make the chart cluttered and hard to read
• Stacked shows percent composition of the whole for each category
  • Focuses on the relative makeup of each bar rather than comparing series
  • Harder to compare inner series and total bar length has no analytical meaning

Diverging and bullet chart use cases

• Diverging stacked useful for visualizing survey data on a likert scale
  • Bi-directional bars show percent breakdown of negative to positive responses
  • Too many segments or unequal spacing makes them hard to interpret
• Bullet charts display actual values in context of targets and ranges
  • Concise format for KPI dashboards to track progress vs goals
  • Less known chart type and not always supported in software applications

Customization for data insights

Annotations and labeling

• Directly label data values on or near the bars for quicker interpretation
  • Especially helpful for stacked or grouped bars to compare series
  • Reduce clutter by abbreviating large numbers and removing unnecessary decimals
• Add reference lines, ranges, or markers to highlight key thresholds or targets
  • Visualize data points that are outliers or above/below a certain value
• Tooltips on hover can display precise values and additional context
  • Provide multiple metrics or the change in value from a previous time period

Interactivity and animations

• Enable filtering or sorting of the categories to let users explore the data
  • Limit the categories displayed based on criteria (top 10, certain region)
  • Rearrange the order of the bars based on the values of a selected series
• Animate the bars growing from the baseline to engage audiences
  • Use in moderation so as not to distract from the data insights
  • Ensure animations have an intuitive interpretation (growing = increasing)

Reinforce key data points and include data details

• Apply redundant encoding to highlight key data points for the audience
  • Display text labels and use color to draw attention to specific bars
  • Order the bars to position key categories at the beginning or end
• Provide data source, timeframe, units and methodology in footnotes
  • Helps establish credibility and answer audience questions upfront
  • Use a legend if abbreviations or encodings (color, shape) need to be defined