> For the complete documentation index, see [llms.txt](https://bcds.gitbook.io/handbook/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://bcds.gitbook.io/handbook/digital-scholarship-methods/data/data-projects/visualizaiton-tools.md).

# Visualization Tools

There are a variety of data visualization tools available, many of them open source, to help you explore existing data visualization or to create your own. Below are a few examples.

### Excel 

[Excel](https://www.microsoft.com/en-us/microsoft-365/excel) is a powerful tool for getting meaning out of vast amounts of data and offers a library of chart and graph types to help users visualize their spreadsheet data.

### Tableau

[Tableau ](https://www.tableau.com/)is a data visualization and analytics platform that enables users to connect to a variety of data sources and explore the data in a simplified way. The drag and drop interface makes it very easy to visualize and create interactive dashboards without any programming skills. (Browse the Tableau [public gallery](https://public.tableau.com/en-us/s/gallery) to see examples of visuals and dashboards.)

### **Palladio** 

[Palladio](https://hdlab.stanford.edu/palladio/) is a web-based data visualization tool for analyzing relationships across time and visualize historical or cultural networks.

### Gephi

[Gephi](https://gephi.org/) is free software for visualizing networks. The main website hosts official tutorials and also links to popular community-developed tutorials.

### D3.JS

[*D3*.*js*](https://d3js.org/) is a JavaScript library for producing dynamic, interactive data visualizations in web browsers. It is ideal for people who want to develop some JavaScript Programming skills and offers great power and flexibility.