About

DataVizPyR, short for Data Visualization with Python and R, is a place for self contained recipes to make most common graphics/plots. Yes, every plot in datavizpyr.com is reproducible with the code provided in the posts.

Data Viz with Python and R started as a resource for personal use. I can’t count the number of times I google to change label size or way to remove the legend or how to make a specific customization. It started off as personal gists with start to end solutions and now lives in the web. The original purpose was to remove the search pain and it is out in the web to help with others too 🙂

DataVizPyR.com started as a fun project porting personal gists to the current web form over 2019 Christmas Holidays.
As of June 2020, datavizpyr.com has over 100 posts/tutorials containing over 300 plots/graphics showing how to make data visualization using Python and R.

As of May 2021 datavizpyr.com has over 165 posts/tutorials containing over 500 plots/graphics made with Python/R, with about 90 posts covering R and 70 posts covering Python.

As of August 2022 datavizpyr.com has over 220 posts/tutorials containing over 750 plots/graphics made with Python/R, with about 130 posts covering R and 90 posts covering Python.

Now in 2025, it has about 272 posts. It has gone through deep revision to make the content better and useful.

And one of the useful aspects of most posts in the site is acknowledging the fact that you are never given the data in right format to make a good first pass visualization. You always have to massage/munge the data before you actually make a plot. And most posts do cover a lot of the munging and customization you need to make the right plot.

Why Data Analysis and Visualziation in Python and R?

Answer is Why not Data Visualization with Python and R?- the two most useful programming languages for doing data science. Thanks to the fantastic efforts from open source communities in Python and R, we have great toolkits available to make data visualization.

Python has numerous open source data visualization tools that are powerful and expressive, like Matplotlib, Seaborn, and Altair. And R has ggplot2, a mature data visualization tool, suitable for making fantastic visualization. DataVizPyR.com hopes to be a place for learning to make visualization in both Python and R.

Our goal for each post at DataVizPyR.com is to serve two purposes. The first purpose is to offer the code chunk that makes a complete visualization task quickly. This is extremely useful for users who wants the visualization done and understands how to get there. The second purpose is to teach/show the steps and attempts that typically fail to give the right visualization and then show how to fix them. And this is extremely useful for learning to make data visualization. Yes, this may be a lofty goal, but that is what we aim for.

Also check out this site if interested LumiExams.com.