Data Visualization: Glossary

dplyr is one useful tool to manipulate, summarize, and analyze data.

ggplot2 is one useful tool to visualize and analyze data.

A clearly defined research question is essential to a successful analysis and graphical representation of the results.

Be sure to setwd() to point to your data file before importing it.

Import data using read.csv().

Familiarize yourself with your data and its structure prior to analysis.

‘Variables’ are associated with columns in tidy data.

As a descriptor of a specific column of data, ‘variables’ tend to describe numerically continuous data, while ‘categories’ describe discrete or categorical data that is organized in groups.

‘Values’ are associated with cells in a data table.

‘Replicates’ are values with similar variables and categories most often seen in experimental data.

‘Absolute’ values receive context by their units, while ‘relative’ values are standardized in some fashion (i.e., proportion, per unit) for comparison among categories.

Use dplyr to manipulate, summarize, and analyze your data.

Strong research questions and hypotheses direct the goals of data collection and analysis. They have clearly defined answers with deliberate investigation.

A well detailed research question can be answered with a good chart.

A good chart directly and clearly addresses a scientific question.

Use ggplot2 to visualize and analyze data.

Line histograms represent a single variable distributions with many points.

Publication quality figures stand alone to address a scientific question.

Publication quality figures include clear headings, labels, and symbols.

Publication quality figures are often accompanied by a descriptive caption.

Bubble charts represent a relationship with three variables

Tidy data has one value per cell and all similar values in a single column.

Faceted tables represent a comparison among many items or categories.

Multiple good charts can address a single scientific question.

Stacked area charts represent a composition changing over time.

After the hard part of thinking and choosing your scientific question and related chart, implementation should be easy.