Charts are an excellent way to condense large amounts of information into easy-to-understand formats that clearly highlight the points you’d like to make. There are many different chart types available, and sometimes the hardest part is deciding which chart type is best for your need.
When presenting your information, you should think about what you want your readers to take away from the information and make those points stand out. Different types of charts are best for certain circumstances. Decide what you want the take-away to be, then choose the type of graph that will best clearly and concisely present your information.
In this tutorial, we’ll go over some basic types of data and suggestions for the best types of charts for these:
Vertical Bar Charts
Vertical bar charts are best for comparing data that is grouped by discrete categories. Vertical bar charts are best when you don’t have too many groups (less than 10 is usually good). Each bar is separated by blank space which indicates that there is no inherent order to your groups.
Stacked Bar Charts
Stacked bar charts are a great choice if you not only want to convey the size of a group relative to other groups, but also illustrate the parts that make up the whole group.
A histogram is visually interesting combination of a vertical bar chart and a line chart. The continuous variable shown on the X-axis is broken into discrete intervals and the number of data you have in that discrete interval determines the height of the bar. Histograms are great for illustrating distributions of your data.
The horizontal bar chart is similar to a vertical bar chart but is typically used when the number of categories is large ( greater than 10 or so) or you have long labels that you would like to display for each category. It’s much easier to read the labels when they are displayed in proper orientation.
Pie charts are easy to read and fun to look at making them a great choice if you want to understand the parts of a whole. It’s a good practice to order the pieces of your pie according to size an always ensure the total of all the pieces add up to 100%.
Line charts are used to show resulting data relative to a continuous variable - most commonly time or money. They are great for projections of performance beyond your data. If you plot your sales vs. month on a line chart over the past two years, it is easy for the reader to identify any trends that may be useful as you plan for the upcoming year.
A dual axis chart allows you to plot data using two y-axes and a shared x-axis. It’s used with three data sets, one of which is based on a continuous set of data and another which is better suited to being grouped by category. This should be used to visualize a correlation or the lack thereof between these three data sets.
An area chart is similar to a line chart, but the space between the x-axis and the line is filled with a color or pattern. It is useful for showing part-to-whole relations, such as showing individual sales reps’ contribution to total sales for a year. It helps you analyze both overall and individual trend information.
A scatter plot chart will show the relationship between two different variables. Scatter plots are useful for quickly understanding if there is a relationship between to variables. If the data forms a band extending from lower left to upper right, there most likely a positive correlation between the two variables. If the band runs from upper left to lower right, a negative correlation is probable. If it is hard to see a pattern, there is probably no correlation.
A bubble chart is similar to a scatter plot but you can introduce a third variable to the visualization by having the size of the bubble indicate the value of the three variable. Again, really good option for understanding relationships between continuous variables.
Funnel charts are most often used to represent how something moves through different stages in a process. A funnel chart displays values as progressively decreasing proportions amounting to 100 percent in total. Funnel charts start at 100% and ends with a lower percentage indicating how something drops out of the process at each step or stage. A very common use of a funnel chart is to track sales conversions in a sales pipeline.
Used typically to display performance data relative to a goal. A bullet graph reveals progress toward a goal, compares this to another measure, and provides context in the form of a rating or performance.
A heat map shows the relationship between two items and provides rating information, such as high to low or poor to excellent. The rating information is displayed using varying colors or saturation.
A heat map is a two-dimensional representation of data in which values are represented by colors. A simple heat map provides an immediate visual summary of information. More elaborate heat maps allow the viewer to understand complex data sets. There can be many ways to display heat maps, but they all share one thing in common – they use color to communicate relationships between data values that would be would be much harder to understand if presented numerically in a spreadsheet.
A box plot provides you a quick way to visually summarize your data including average values, variation in the data and whether outliers are present. Multiple box plots allow easy comparisons between different groups of continuous data.