R-snippets
R snippets for Sublimetext
Details
Installs
- Total 12K
- Win 5K
- Mac 4K
- Linux 2K
| Dec 2 | Dec 1 | Nov 30 | Nov 29 | Nov 28 | Nov 27 | Nov 26 | Nov 25 | Nov 24 | Nov 23 | Nov 22 | Nov 21 | Nov 20 | Nov 19 | Nov 18 | Nov 17 | Nov 16 | Nov 15 | Nov 14 | Nov 13 | Nov 12 | Nov 11 | Nov 10 | Nov 9 | Nov 8 | Nov 7 | Nov 6 | Nov 5 | Nov 4 | Nov 3 | Nov 2 | Nov 1 | Oct 31 | Oct 30 | Oct 29 | Oct 28 | Oct 27 | Oct 26 | Oct 25 | Oct 24 | Oct 23 | Oct 22 | Oct 21 | Oct 20 | Oct 19 | Oct 18 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Windows | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 1 | 1 | 0 | 0 |
| Mac | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| Linux | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 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