Data Visualization
Graphical representation of information using charts, graphs, and maps to help people understand trends, patterns and outliers
Clarity
Visualizations should be simple, legible and easy to understand, Use appropriate fonts, clear labels, and color palettes that are colorblind friendly
Accuracy
Visualizations must be accurately represent the data. Avoid misleading techniques such as truncated axes, 3d effects or disproportionates scales. the visual representation should not distort the underlying values
Efficiency
A visualization should be easy to comprehend within seconds, requiring minimal cognitive effort from the viewer
Graphical integrity
The data should be represented truthfully, without distortion
Data-ink ratio
Maximize the proportion of ink used to display data versus non-data elements. The goal is to remove any unnecessary elements that don’t convey information
Small multiples
when presenting a large amount of information, it’s often better to use a series of small, simple graphs rather than one complex, cluttered one
Proximity
objects that are close together are perceived as related
Continuity
our eyes tend to group objects that are aligned, making trends easier to follow
similarity
objects with similar characteristics (like color or shape) are perceived as a group
Focal point
changing a characteristic of one object (like color) can draw attention to it
Figure/ground
Emphasize the main data (foreground) and minimize background elements that could cause confusion
closure
the mind can fill in missing information to perceive a complete object
Categorical data
Use bar charts, stacked bar charts, or pie charts to show counts or proportions for different categories
Quantitative data
use histograms, box plots, or line charts to show distribution, outliers, or changes over time
Time series data
use line charts, or area charts to plot data points over a period of time
Geospatial data
use maps or heat maps to show data associated geographical locations
multivariate data
use scatter plots to show the relationship between two variables or bubble charts and parallel coordinates plots to visualize three or more variables
Textual data
use word clouds to show word frequency or network diagrams to visualize relationships between words
Dashboard
A visual interface that combines multiple visualizations into a consolidated, easy to read format
Tools
Excel, tableau, power bi, python and R
Lie Factor
a way to measure how much a data visualization exaggerates or understates the true differences in the underlying data
