Visual analytics is the art of telling stories through data. It’s about using various visual formats to extract insights and convey complex information more effectively than plain text or numbers alone. This overview aims to explore an exhaustive collection of chart types commonly used in visual analytics, from line charts that track trends over time to sunbursts that unravel intricate hierarchical structures.
Line charts – The story of change over time
As one of the most basic and widely used chart types, the line chart is an excellent tool for illustrating the flow of data across time. With a series of data points connected by lines, it helps you understand how a particular measure varies over time. This might track sales figures, stock prices, weather patterns, or other metrics that evolve through different phases.
Line charts are particularly effective in highlighting both gradual and rapid shifts, with the ability to adjust the scales and granularity to suit the specific narrative the data is meant to convey. They are often enhanced with elements such as markers, averages, and moving averages to provide additional context.
Bar charts – Comparing categories
Bar charts stand out for their simplicity and ability to make comparisons between discrete categories. They come in two primary forms: vertical bars, which stack one on top of the other, or horizontal bars, which arrange the dataset side by side.
Bar charts are ideal when showcasing categorical data, such as comparing sales figures across different regions or product lines. With bar charts, you can also display multiple datasets side by side to directly compare values.
Pie charts – Portion size matters
Pie charts present fractions of a whole as slices of a circle, making it easy to visualize relative proportions. They are particularly useful when only relative values are important or when the number of categories is small.
However, while pie charts are visually appealing, they can be problematic when the number of slices increases, as it becomes more challenging for the human eye to perceive the relative sizes accurately. Pie charts are often best used as an introductory visualization or when the message revolves around the high-level distribution of data.
Stacked area charts – The pie chart’s dynamic sibling
Stacked area charts combine bar charts and pie charts into one, showing the size of the different segments within a group of related categories. They illustrate data changes over time while also showcasing the part-to-whole relationships.
These charts are valuable when segmenting metrics, like sales or customer demographics, over a time period. The stacking creates a visual summation, allowing for observations about how the parts change over time as well as how much of each category is accounted for by the total.
Scatter plots – Correlation at first sight
Scatter plots use individual points as data markers, to plot the values of two variables against each other. The location on the horizontal and vertical axis represents the value of each variable for each individual or data point.
These graphs are great for illustrating the relationship between two different metrics and identifying possible correlations that may not be apparent through a different visualization. They are especially useful when dealing with large datasets where points cluster together, indicating possible relationships that can be further investigated.
Heat maps – Color outside of the line
Heat maps use color gradients to show relative magnitude within a two-dimensional matrix. This format makes it easy to identify patterns and anomalies by the variation in hue across rows and columns.
For instance, heat maps can display geographic variations, time series analysis, or categorical information where each cell’s color is determined by one or more quantitative metrics. This chart type is a standout when it comes to identifying and comparing hotspots and coldspots.
Sunbursts – Navigating the complexity of hierarchies
Sunbursts are an excellent way to visualize hierarchical data structures. They look like a flowing, radial chart, typically starting at a central category and branching outwards, with each level of hierarchy being represented by a slice of the circle.
They are particularly useful for data with multiple hierarchical layers, such as categorizing elements by type, attribute, and value. Sunbursts can help visualize the overall composition of data and offer an easier navigation path through complex hierarchies compared to simpler chart types.
Each chart type discussed here serves as a distinct lens through which we can view and interpret data. Whether it is tracking trends, comparing categories, or navigating complex hierarchies, mastering the appropriate chart type is key to crafting effective visual narratives in the field of visual analytics. As the saying goes, a picture is worth a thousand words, and when crafted well, visual analytics can tell those stories in a compelling, insightful, and memorable manner.