Excel is a common data visualization tool. This popularity is due, in large part, to its intuitive functionality and ability to handle large data. It offers a variety of quick and efficient ways to store, clean, and visualize data in one convenient environment. In particular, "pivot tables" allow the user to visualize thousands of records, in real time, with only a few mouse clicks. The popularity of Excel stems also from it's broad compatibility with other visualization software. If you're looking for a powerful, efficient, and broadly compatible environment to work with data then Excel may be the correct choice.
Different flavors of Tableau:
Tableau tutorials and training can be found on the official Tableau website as well as through Lynda.
Official Tableau Resources:
R is a free programming language and environment that can be used to create visualizations and perform statistical computing. It is extremely versatile with respect to the types of visualizations that can be made and the manipulation of datasets. Though it may be initially less intuitive than other visualization means, it compensates by rewarding the user with a near endless selection of packages that make cleaning and visualizing data immensely customizable. It's longstanding popularity with researchers, academics, and businesses is a testament to it's utility in numerous contexts. If you want to clean and visualize your data in one place, with practically limitless customization, then R may be the right tool for you.
Download R (Programming Language): https://cran.case.edu/
Download RStudio (IDE): https://www.rstudio.com/
Python is a free, general purpose, and high level programming language that can be used to create data visualizations. Python offers near limitless varieties of visualization capabilities. It is a language that is extremely common across academia and industries. Because it is so common, it is a good choice if you want to integrate visualizations into pre-existing applications. If you have a programming background and are looking for a highly versatile way to visualize data, then Python may be a good option for you.