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SkillSnap Official GuideUpdated 7/24/2026
R
The language of statistics. Master the Tidyverse for readability, data.table for speed, and ggplot2 for visualization.
Core Syntax & Vectors
Assignment (Standard over '=')<-
Combine into Atomic Vectorc(1, 2)
Sequence generation1:10
1-based indexing (First row)df[1, ]
Check missing values (Never x == NA)is.na(x)
Value in set check%in%
Tidyverse (Data Wrangling)
The Pipe (Chain functions)|> / %>%
Pick rows by conditionfilter()
Pick columns by nameselect()
Create/Modify columnsmutate()
Split-Apply-Combinegroup_by()
Wide to Long (For plotting)pivot_longer()
High Performance (data.table)
Fast CSV Readerfread()
Filter(i), Compute(j), Group(by)DT[i, j, by]
Update by reference (No memory copy):=
Binary search-speed joinssetkey()
Visualization (ggplot2)
Initialize plot & mappingsggplot() + aes()
Scatter plot layergeom_point()
Create small multiplesfacet_wrap(~ var)
Export plot to fileggsave()
Combine multiple plotspatchwork
Statistics & Modeling
Linear Model (Formula Syntax)lm(y ~ x)
Clean model output to dataframebroom::tidy()
Ensure reproducibilityset.seed()
Statistical overviewsummary()
Workflow & Iteration
Apply function to list (Type-safe)purrr::map()
Safe relative file pathshere::here()
Dependency managementrenv
Sanitize column namesjanitor::clean_names()