Data & Intelligence

Data Visualization – How to Pick the Right Chart? – Part 1

Business background with arrays of data in virtual space

So Many BI Charts, but which one to choose and when? This blog series will help you understand each chart’s uses and its properties.

To determine how to pick the right chart for your data visualization needs, first, you must answer a few questions:

  • How many variables do you want to show in a single chart? One, two, three, many?
  • How many items (data points) will you display for each variable? Only a few or many?
  • Will you display values over a period of time or among items or groups?

Bar charts are good for comparisons, while line charts work better for trends. Scatter plot charts are good for relationships and distributions, but pie charts should be used only for simple compositions — never for comparisons or distributions.

Data visualization- how to pick the right chart

Let’s dig in and review the most commonly used chart types, some examples, and the dos and don’ts for each chart type.

1. Tables

Example of a table

Tables are essentially the source for all the charts. They are best used for comparison, composition, or relationship analysis when only a few variables and data points exist. It would not make much sense to create a chart if the data could be easily interpreted from the table.

Use tables when:

  • You need to compare or look up individual values.
  • You require precise values.
  • The data has to communicate quantitative information, but not trends.


2. Column Charts

Example of a column chart

The column chart is probably the most used chart type. This chart is best used to compare different values when specific values are important, and users are expected to look up and compare individual values between each column.

With column charts, you could compare values for different categories or value changes over time for a single category.

Best practices for column charts:

  • Use column charts for comparison if the number of categories is relatively small — up to five, but not more than seven categories.
  •  If one of your data dimensions is time — including years, quarters, months, weeks, days, or hours — you should always set the time dimension on the horizontal axis.
  • In charts, time should always run from left to right, never from top to bottom.
  • For column charts, the numerical axis must start at zero. Our eyes are very sensitive to the height of columns, and we can draw inaccurate conclusions when those bars are truncated.
  • Avoid using pattern lines or fills. Use border only for highlights.

Only use column charts to show trends if there are a reasonably-low number of data points (less than 20) and if every data point has a clearly-visible value.


3. Column Histograms

Example of a column histogram chart

A histogram is a common variation of column charts used to present the distribution and relationships of a single variable over a set of categories. A good example of a histogram would be a distribution of grades on a school exam or the sizes of pumpkins, divided by size group, in a pumpkin festival.


4. Stacked Column Charts

Example of a stacked column chart

Use stacked column charts to show a composition. Do not use too many composition items (not more than three or four), and make sure the composing parts are relatively similar in size.


5. Bar Charts

Example of a bar chart

Bar charts are essentially horizontal column charts.

If you have long category names, it is best to use bar charts because they give more space for long text. You should also use bar charts, instead of column charts, when the number of categories is greater than seven (but not more than fifteen) or for displaying a set with negative numbers.

  • A typical use of bar charts would be visitor traffic from top referral websites. Referring sites are usually more than five to seven sites, and website names are pretty long, so those should be better horizontally graphed.


6. Bar Histogram Charts

Example of a bar histogram chart

Just like column charts, bar charts can be used to present histograms.

  • A good histogram example is a population distribution by age.


7. Stacked Bar Charts

Example of a stacked bar chart

Stacked bars are not suitable for comparison or relationship analysis. The only common baseline is along the left axis of the chart, so you can only reliably compare values in the first series and for the sum of all series.


8. Line Charts

Example of a line chart

Line charts are among the most frequently used chart types. Use lines when you have a continuous data set. These are best suited for trend-based visualizations of data over a period of time when the number of data points is very high (more than 20).

With line charts, the emphasis is on the continuation of the flow of the values (a trend), but there is still some support for single value comparisons using data markers (only with less than 20 data points.)

A line chart is also an excellent alternative to column charts when the chart is small.


9. Timeline Charts

Example of a timeline chart

The timeline chart is a variation of line charts. The only difference is in functionality — most timeline charts will let you zoom in and out and compress or stretch the time axis to see more details or overall trends. Obviously, any line chart that shows values over a period of time is a timeline chart.

The most common examples of a timeline chart might be:

  • Stock market price changes over time.
  • Website visitors per day for the past 30 days.
  • Sales numbers by day for the previous quarter.

The Dos and Don’ts for Line Charts

  • Use lines to present continuous data in an interval scale, where intervals are equal in size.
  • For line charts, the axis may not start from zero if the intended message of the chart is the rate of change or overall trend, not exact values or comparison. It’s best to start the axis with zero for broad audiences because some people may otherwise misinterpret the chart.
  • In line charts, time should always run from left to right.
  • Do not skip values for consistent data intervals presenting trend information, for example, certain days with zero values.
  • Remove guidelines to emphasize the trend and rate of change and to reduce distraction.
  • Use a proper aspect ratio to show critical information and avoid dramatic slope effects. For the best perception, aim for a 45-degree angle precision.


This is part 1 of this blog series on how to pick the right chart for data visualization. Stay tuned for more!

Happy reading & learning.

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Arpit Malviya

Arpit Malviya has worked at Perficient as a technical consultant. He has been working in the Power BI & Data Analysis field since 2019.

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