Choosing the right data visualization method is like picking the perfect spices in the kitchen: each chart or graph highlights specific features of your data set. Let's explore how to decide between line graphs, bar charts, timelines, histograms, and other visual communication methods.
What is Data Visualization?
Data visualization is the process of translating quantitative information (numbers, statistics, databases) into graphical form (charts, diagrams, graphs). The goal of visualization is to answer questions that may arise for the user. For example, fitness app charts show how many steps and kilometers a user has walked, their heart rate, and how much time they have spent.
Data visualization is used across various fields, from scientific research to news reports and corporate presentations. Data can be displayed using line graphs, histograms, pie charts, or scatter plots.
Principles of Visualization
Accuracy: Data must be accurate and complete. When a designer visualizes information, it should be presented without distortion, ensuring that the graph or chart is a reliable source the user can trust.
Usefulness: Visualization should help users navigate the data by providing context. For example, graphs should include axis labels, notes, and titles. These elements help the user understand what the data is communicating, aiding in interpretation and informed decision-making.
Scalability: Visualizations should be adapted for devices of different sizes, allowing readers to view the data and see details clearly.
Types of Visualization
Trend Graphs: These display data over a specific period and are used to show trends or compare categories. For example, they can depict price changes, health statistics over time, or a chronology.
Rankings or Ranking Charts: These are used to show the position of an element in an ordered list of charts. For instance, rankings are ideal for illustrating the differences between candidates’ election results.
Part-to-Whole Charts: These illustrate how individual elements combine to form a whole. For example, a budget structure chart might look like a pie, with each slice representing a different income source.
Distribution Charts: These help visualize which values occur more frequently and which are rarer. They are often used to display survey results.
Correlation Charts: These show the relationships between variables and are frequently used to illustrate income or life expectancy.
Relationship Charts: These depict how elements are connected or interact. They are often used in social network analysis to show who is at the center of a network, who is on the periphery, and what groups are forming.
Flow Charts: These illustrate how data moves through a system or program, often used to demonstrate how a neural network works, showing how AI receives, processes, and outputs information.
How to Choose the Right Visualization Type
Define Your Goal: What do you want to convey to your audience? Is it to show a trend over time, compare categories, analyze an object’s structure, or demonstrate correlations?
Identify the Data Type: Data can be numerical, categorical, geographical, or other types.
Understand Your Audience: The audience's level of knowledge, context, and other factors influence the choice of visualization method.
Consider Complexity and Volume: Simple data works well with histograms or line graphs, while complex data might be better represented with heat maps or bubble charts.
Don’t Forget Context and Devices: The smaller the screen size, the simpler the type of visualization should be.
Popular Types of Charts
Designers most frequently use:
Line graphs
Histograms
Area charts
Bar charts
Pie charts
Line graphs highlight subtle differences in data.
Histograms are ideal for showing significant differences, comparisons, and data rankings.
Area charts summarize relationships between data sets, illustrating how individual points relate to the whole.
There are two types of area charts: basic area charts and overlapping area charts.
Basic area charts are best for displaying multiple time series, showing how a phenomenon or indicator evolves. They clearly depict how data sets vary.
Overlapping area charts feature time series that overlap each other. It’s advisable not to use more than two time series to avoid obscuring the data.
Bar and pie charts help compare parts to the whole.
Bar charts or histograms show quantities through the length of the bar and use a common baseline.
Pie charts represent parts of a whole using arcs or angles within a circle.
Histograms are more effective than pie charts at reflecting changes over time, as it’s easier for users to compare or see differences in bars of varying lengths.
For example, a bar chart clearly shows how sales figures differ between this quarter and the last for companies Alpha, Beta, Gamma, and Delta.
In the next article, we’ll discuss how to style your charts.
