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Live Free or Dichotomize - Using AWK and R to parse 25tb
A story of going from Spark, 8mins, and $20 per AWS query, to mostly R+Awk, 0.1s, and $0.0001 per query.

Pre-processing a massive (25tb) amount of DNA(?) data into a format easily queryable on AWS.
rlang  devops  datascience  ml  aws 
5 days ago by davison
Emulating R plots in Python – A Journey in Data
This was helpful!
One of the simplest R commands that doesn’t have a direct equivalent in Python is plot() for linear regression models (wraps plot.lm() when fed linear models). While python has a vast array of plotting libraries, the more hands-on approach of it necessitates some intervention to replicate R’s plot(), which creates a group of diagnostic plots (residual, qq, scale-location, leverage) to assess model performance when applied to a fitted linear regression model.
statistics  python  tutorial  rlang 
12 weeks ago by madamim
the ggplot flipbook
An iterative approach to building beautiful graphics using GGplot in R.
datascience  rlang  presentation 
march 2019 by davison
From ‘R vs Python’ to ‘R and Python’ – Towards Data Science
If you are into Data Science, the two programming languages that might immediately come to mind are R and Python. However, instead of considering them as two options, more often than not, we end up…
python  rlang  interoperability  resource 
march 2019 by gilberto5757
How to run Python in R | InfoWorld
Learn how to run Python code inside an R script using the reticulate R package
python  rlang  interoperability  howto 
february 2019 by gilberto5757
I can rayshade, and so can you
That’s all I’ve got. I hope you learned something that may save you a bit of pain and confusion if you try out rayshader for yourself. And maybe you’re coming away with just a bit more excitement and inspiration to do so. I’ve certainly enjoyed my time with this package, and I’ll be making more maps in the future (as well as 3D printing some of them!).

If you have suggestions or edits or thoughts on this material, please feel free to create an issue in the git repo or tweet at me at wcmbishop.

Thanks for reading.

Afterthoughts

After writing this post, I found a few more leads on elevation data sources. I thought I’d share these here (though I think the REST API option I described above is still a great starting place).

One is the elevatr R package (vignette here), which uses the National Map Elevation Point Query Service.

Tyler Morgan-Wall also posted some instructions for manually downloading elevation data from a National Map UI here – the instructions from this reddit post are quoted below:
gif  mapping  rayshading  elevations  rlang  Relief  shading 
february 2019 by euler

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