Applied Data Visualization with R and ggplot2
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Similar Packages

Other visualization packages exist, such as matplotlib (in Python) and Tableau. The matplotlib and ggplot2 packages are equally popular, and they have similar features. Both are open source and widely used. Which one you would like to use may be a matter of preference. However, although both are programmatic and easy to use, since R was built with statisticians in mind, ggplot2 is considered to have more powerful graphics. More discussion on this topic can be found in the chapter later. Tableau is also very powerful, but it is limited in terms of statistical summaries and advanced data analytics. Tableau is not programmatic, and it is more memory intensive because it is completely interactive.

Excel has also been used for data analysis in the past, but it is not useful for processing the large amounts of data encountered in modern technology. It is interactive and not programmatic; hence, charts and graphs have to be made with interactivity and need to be updated every time more data is added. Packages such as ggplot2 are more powerful in that once the code is written, ggplot is independent of increases in the data, as long as the data structure is maintained. Also, ggplot2 provides a greater number of advanced plots that are not available in Excel.

Read more about Excel versus R at https://www.jessesadler.com/post/excel-vs-r/.

Read more about matplotlib versus R at http://pbpython.com/visualization-tools-1.html.

Read more about matplotlib versus ggplot at https://shiring.github.io/r_vs_python/2017/01/22/R_vs_Py_post.html.