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Data Visualization

Data visualization resources and services at the Leatherby Libraries

About visualization tools

There are many, many ways to create data visualizations. Many people will already be familiar with Microsoft Excel, certainly the most widespread data visualization tool, but there are other web, desktop, and programmatic options that may be suitable for your purposes.

This page will briefly explain some of the most popular and/or accessible and link to resources on using them. The support Leatherby Libraries can provide for any of them will be limited.

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Each section contains a brief description of the software and a link the related section of the "Resources" page.


Microsoft Excel, which many people likely produced their first data visualizations on, is a capable tool for data viz in the right hands. With some user knowledge of Excel's many menus and functions, it can reproduce some plot types like waffle charts and pictograms that do not appear in its list of options for chart types. The chart default formatting does not always follow best practices, but Excel usually offers enough customization to create clear and accessible visualizations.

However, Excel struggles to produce more complex statistical plots, such as violin plots, interactive visualizations, qualitative data visualizations, and additionally visualizations created in Excel are not computationally reproducible. This means that it may be harder to make corrections or improvements to a manually-designed plot, and someone else may not be able to replicate your plot at all. Users in need of these features may need to look elsewhere.

Stephanie Evergreen's Effective Data Visualization uses Excel for all its demonstration and exercises, because of its widespread availability and familiarity.


Tableau is a popular data analysis and visualization platform used in many parts of the business world. There are many different products in the Tableau family, including a free cloud version available at Tableau Public.


The most common data visualization library for the Python programming language is matplotlib, but there are many other packages that either interact with matplotlib or create plots in other ways to serve many different use cases. Visualizations in Python are created by the computer from Python code, so some level of knowledge of Python is necessary to employ this flexible and powerful tool.


The most popular visualization library for R is the famous ggplot2 package, part of the "tidyverse", a collection of R packages created for data science. R users have created innumerable add-ons building on ggplot2 to create almost any kind of visualization, and the R ecosystem as a whole is heavily oriented towards data science and scientific computing.


Claus Wilke's Fundamentals of Data Visualization, while not a book about ggplot2, uses ggplot2 for all its figures as Wilke goes through fundamentals of visualization construction. He uses the language, called a "grammar" that also inspired ggplot2 - such as elements, geometries, aesthetics, position - when describing the qualities of figures. The code that generated the figures is available in online supplements.

Power BI

Much like Tableau, Microsoft Power BI is a widely used software for data viz and analysis in the business world. Power BI is flexible and much more powerful than its cousin Excel, but with its own learning curve. It can be used for interactive visualizations, dashboards, and to connect to databases or web data sources.


Voyant is a free web-based tool for the analysis and visualization of text documents. It can import text from the web or an uploaded corpus created by the user. Once the data is imported, you can create visualizations including word clouds and term frequency plots.


Datawrapper is a web-based visualization platform that produces beautiful and complex interactive visualizations with no coding knowledge required. A basic account is free, but additional options and export filetypes are available with a paid account. These charts are optimized to be embedded on the web.

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