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Data Visualization

Introduction to data visualization resources at the Georgia Tech Library

Introduction to resources for charts and graphs

From this page you can learn more about: Excel, Tableau, a couple Python libraries, and a couple R libraries

Which is your selected tool on this page?
Excel: 3 votes (23.08%)
Tableau: 4 votes (30.77%)
Python Libraries: 5 votes (38.46%)
R Libraries: 1 votes (7.69%)
Total Votes: 13

Excel

Microsoft Excel is the most commonly used tool to create basic graphics, including color-coded data values, charts, indicators, and interactive slicers and timelines. It also features calculation, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications. All editions of Excel support data visualization through charts, data bars, sparklines, and conditional formatting. These can be used when creating graphical representations.

Pivot Tables and Pivot Charts are a common way to aggregate data values across multiple dimensions, and enable users to see the relationships between these dimensions.

Power Map is an Excel add-in for Microsoft Office 365 Power BI subscribers that enables you to visualize geographic and temporal analytical data on a map. With Power Map you can display geographically related values on an interactive map, and create a virtual tour that shows the data in 3D.

Power Map example

Resources / Tutorials:

Tableau

Tableau is an easy-to-use and powerful visual analytics tool that helps users create and distribute interactive visualization on its shareable dashboard. Tableau can connect to various files sources including relational datasets and Big Data sources for real-time update of the visualization.

Access:

  • Sign up and use free-version Tableau Online
  • You can also find Tableau desktop version in the library data visualization pilot lab

Resources / Tutorials:

Python Libraries

There are a variety of Python libraries that support visualization. Some popular ones include: Plotly, Seaborn, Matplotlib, etc. Each library has its focus and features. Below is an example of Plotly.

R Packages

R is also a popular tool for data science projects. There have been a variety of statistical analysis and graphing packages created for R, some of the most popular ones include: Ggplot2, Leaflet and Plotly.