Data visualizations are a graphical representation of data that tell a story and can be used to identify trends, patterns, and relationships. Visualizations can be static, animated, or interactive.
Common types of visualizations include:
Bar Charts | Pie Charts | Line Charts |
Compare data across categories | Show proportions of a whole | Show trends over time |
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Histograms | Scatter Plots | Boxplots |
Display the frequency distribution of continuous data | Show the relationships between numerical values | Show the distribution of values along an axis |
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Built in R with ggplot2 |
GIS Maps | Network Graphs | Heat Maps |
Represent data spatially | Plot relationships between data points | Use color to represent density |
Built in ArGIS Pro |
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In order to visualize data, you will need access to visualization software. There are two types of visualization software: Graphical User Interface (GUI) software and code-based software.
Graphical User Interface (GUI)
Excel is a popular spreadsheet editor with a variety of graph and chart options for visualizing data. Excel is FREE for all University of Mississippi faculty, staff, and students as part of the campus-wide Microsoft Office 365 license.
Tableau is a tool with a simple to use "drag-and-drop" interface that allows users to create interactive visualizations and dashboards from a variety of data sources. Tableau Public is FREE to use.
Power BI (Business Intelligence) is a collection of software services, apps, and connectors that work together to turn raw data into static or interactive visualizations. Power BI is s FREE for all University of Mississippi faculty, staff, and students as part of the campus-wide Microsoft Office 365 license.
Code Based
R is a FREE software environment for statistical computing and graphics. R packages such as ggplot2 are used for data visualization.
Python is a free general purpose programming language. Python libraries such as MatPlotLib and Seaborn are used for creating static, animated, and interactive visualizations.
Shiny is a free package that can be used to create interactive data visualizations in either R or Python.
SAS is a computer programming language that can be used to create data visualizations. SAS OnDemand is free for academics and offers both programming and point-and-click interfaces.
The following are curated lists of datasets for visualization. Since any dataset can be visualized, be sure to also check the Datasets section of this guide's "Resources" page.