👋 Hey!
Today I’m back at work, and very glad to announce a new section in the Python Graph Gallery! 🎉
R or Python for dataviz?
In the world of data science, 2 main programming languages dominate: R and Python.
They both have pros and cons. But when it comes to Data Visualization, I’ve always been surprised to see how many stunning charts are produced by the R community compared to Python 🤔.
I have no idea why it is the case (and if it is even true). But I spend a lot of time browsing the internet in the quest of great charts and that’s how I feel it.
R is powerful. So is Python.
R is very powerful for dataviz, notably thanks to the ggplot2 package and its extensions.
But Python is pretty awesome too!
Matplotlib is a pretty solid library. It allows to build any kind of chart type with all the customisation you could dream of. Plotly has a Python library too, allowing to create powerful interactive charts.
A list of stunning Python charts
To face this lack of stunning python charts, I created and translated some of my favorite graphics to Python 🙇♂️.
It results in a list of 22 insightful & beautiful charts, coming with their reproducible code and some explanation about it.
![](https://substackcdn.com/image/fetch/w_474,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F26d24f36-e6b7-451a-a4e9-818828b92a38_480x480.png)
![](https://substackcdn.com/image/fetch/w_474,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Febf95905-3f95-48c4-8a3f-95b9fb16ad53_2068x1224.png)
![](https://substackcdn.com/image/fetch/w_474,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Faeffab52-5513-457e-90b4-e0b2871b6316_793x1221.png)
![](https://substackcdn.com/image/fetch/w_474,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F824f013f-7df6-42e0-a59f-abf46af5dfa1_480x480.png)
![](https://substackcdn.com/image/fetch/w_474,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Ffb28b961-47ed-4867-8003-5d31f055c8bb_879x870.png)
![](https://substackcdn.com/image/fetch/w_474,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F2bfff9a5-6a3d-413c-8555-08f2fb5674f3_1202x1408.png)
![](https://substackcdn.com/image/fetch/w_720,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F78620691-7ddf-4fce-8aae-1e128c8c5da2_1502x1386.png)
![](https://substackcdn.com/image/fetch/w_720,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F3d98c645-382f-47c3-9ca2-0acd7b6d2369_893x666.png)
I hope this can be useful to level-up your dataviz skills!
If you know someone who creates some ugly charts with Python, please share this content with them 😋.
If there is some good python viz content I should add, please let me know 🙏
That’s it for today!
Yan
PS: thanks a lot to the original authors of the charts, and to the people who helped me for the translation. They are always cited in the posts. 🙏🙏🙏