R-snippets
R snippets for Sublimetext
Details
Installs
- Total 12K
- Win 6K
- Mac 4K
- Linux 2K
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| Mac | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 |
| Linux | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Readme
- Source
- raw.githubusercontent.com
R-snippets
This package includes a selection of R snippets for Sublimetext that I find useful when using R through SublimeREPL
Check out the project page at http://www.jvcasillas.com/code/projects/R-snippets
Just type the trigger and hit the tab key. For example…
lm
Expands to…
# load lme4 for mixed models
library(lme4)
# random intercept and random slope model
modelName <- lmer(DV ~ fixedFactor1 +* fixedFactor2 + (1 + randomSlope|randomInt), data=df)
summary(modelName)
Main triggers
- “plot”: templates for plotting in base R
- “edit”: options useful for data cleansing and saving
- “desc”: descriptive statistics of data
- “ttest”: distinct types of t-test
- “aov”: distinct analysis of variance models
- “lm”: linear and logistic regression
- “lmem”: linear mixed effects models
Extras
- “subset”: make subsets of a DF
- “read”: read/load/install data/packages into R
- “save”: save plots, dfs, tables, etc.
- “tikz”: template for creating R plots in LaTeX
Note All snippets have the following scopes:
source.r, text.html.markdown.knitr, text.tex.latex, text.html.markdown.rmarkdown
To add
- knitr
- dplyr
- coursera