There are a number of user-friendly tools that provide a graphical interface to make data visualization faster and easier. However, all of these tools have limited capabilities. For example, many will not perform in-depth analysis or statistical tests on your data, and you may find it more efficient to use a programming language that is capable of both analysis and visualization at the same time. There are also currently no easy-to-use tools that allow for animation of data visualizations. Animation achieved in data visualization is often created either frame-by-frame or by using a programming language.
In general, programming allows for more flexibility, transparency and reproducibility of the data visualization process.
|R is a programming language designed for statistics and data analysis. It includes some basic visualization capabilities, but many users employ third-party created functions, or "packages", to enhance visualization options. A popular visualization package for R is ggplot2.|
Python is a popular language for both experts and first-time programmers. Although there are no visualization functions built into Python, there are many visualization libraries available. A commonly used Python visualization library is matplotlib.