elevatr
drake
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elevatr | drake | |
---|---|---|
1 | 1 | |
188 | 1,330 | |
- | 0.2% | |
6.7 | 6.1 | |
5 days ago | about 2 months ago | |
R | R | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
elevatr
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[OC] 3D Render of a 2000 Geologic Map of Utah Created in Blender
Lots of stuff comes to mind :) One of the most useful to me was using the elevatr package (https://github.com/jhollist/elevatr) in R to get much more high-quality terrain data using the code below:
drake
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Your impression of {targets}? (r package)
The targets package is the official successor to Drake, and has the same primary author (Will Landau). He has explained why he created targets, which includes stronger guardrails for users and better UX.
What are some alternatives?
ip2location-r - Lookup for IP Address Information in R. Supported IPv4 and IPv6
targets - Function-oriented Make-like declarative workflows for R
easystats - :milky_way: The R easystats-project
timevis - 📅 Create interactive timeline visualizations in R
tabulapdf - Bindings for Tabula PDF Table Extractor Library
report - :scroll: :tada: Automated reporting of objects in R
ncaahoopR - An R package for working with NCAA Basketball Play-by-Play Data
fiery - A flexible and lightweight web server
causalglm - Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning
droll - An R package to analyze roll distributions
disk.frame - Fast Disk-Based Parallelized Data Manipulation Framework for Larger-than-RAM Data