While it’s generally considered to be bad practice to import everything into the global namespace, I think it’s fine to do this in an ad-hoc environment such as a notebook as it makes using the many functions plotnine provides more convenient. An additional advantage is that the resulting code more closely resembles the original ggplot2 code. Alternatively, it’s quite common to `import plotnine as p9` and prefix every function with `p9`.
replyDisclaimer: I made the plotnine homepage and cheatsheet.
The issue I find with this pattern in docs/tutorials is that the prefix makes it very obvious which functions are from this library.
replyIt's particularly worthwhile when looking at the bigger examples that might involve another library, or stdlib functions/libs I haven't dealt with before
To each his own. Some drawbacks here are that it means that if you want to copy the code in, you have to add all the “p9”s. And, if you want to make a more complicated demo, with maybe a second import, you now have multiple conventions in your demo codebase.
reply> a new python plotting library
replyWhilst it's still not yet at 1.0.0, it's not that new: the first (0.1.0) release was in 2017: https://pypi.org/project/plotnine/#history
matplotlib's first release was in 2003, making it more than twice as old.
replyBecause most of the time this will be used is not part of a software development project but rather producing publication plots in a script or plots in a notebook. Not what you would want to do when incorporating it into a web app.
replyEven in a notebook it's a pain...
import plotnine as p9
would be nicer.
replyBecause it's aimed at data scientists who would rather be using R...
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