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LinkedIn Learning

R for Data Science: Lunchbreak Lessons

via LinkedIn Learning

Overview

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Learn R on your lunch break. This weekly series reviews the language features, development tools, and libraries that will make you a more productive R programmer.

Syllabus

Introduction
  • Welcome
  • Exercise files
1. R for Data Science Lessons (Jan-Mar 2018)
  • R built-in data sets
  • Vector math
  • Subsetting
  • R data types: Basic types
  • R data types: Vector
  • R data types: List
  • R data types: Factor
  • R data types: Matrix
  • R data types: Array
  • R data types: Data frame
  • Data frames: Order and merge
  • Data frames: Read and update
2. R for Data Science Lessons (Apr-Jun 2018)
  • Data frames: rbind
  • Dataframes: cbind
  • apply and lapply
  • mapply
  • plot
  • Brackets and double-brackets
  • mean, rowMeans, and colMeans
  • RSQLite
  • sqldf
  • Aggregate
  • Random numbers
  • Pipeline
  • Working with clipboards
3. R for Data Science Lessons (Jul-Sep 2018)
  • Style guides
  • cut
  • split
  • askYesNo
  • cdplot
  • Fun
  • boxplot
  • Histogram
  • Plot to file
  • coplot
  • cowsay
  • table
  • Look inside
4. R for Data Science Lessons (Oct-Dec 2018)
  • barplot
  • Pie chart
  • unlist
  • Joins: Inner and full
  • Joins: Left and right
  • Sets: Union, intersect, and difference
  • Sets: Equal and in
  • colors
  • ifelse
  • spineplot
  • browser
  • debugonce
  • Default mirror
5. R for Data Science Lessons (Jan-Mar 2019)
  • Dealing with NA
  • Using with()
  • Simple string matching
  • grep
  • dotchart
  • fourfoldplot
  • matplot
  • dimnames
  • mosaicplot
  • stemplot
  • stripchart
  • sunflower
  • Switch
6. R for Data Science Lessons (Apr-Jun 2019)
  • Switch on factors
  • Any/all
  • sub, gsub, regex, and backreferences
  • agrep and fuzzy matching
  • combn finds combinations
  • edit, fix, and dataentry
  • zeallot
  • menu
  • person
  • txtProgressBar
  • zip and tar
  • bitwise
  • by is like tapply
  • Update your R
7. R for Data Science Lessons (Jul-Sep 2019)
  • Be careful with transpose
  • Passwords
  • heatmap
  • combine
  • stopifnot
  • weighted.mean
  • chartr
  • file.choose
  • duplicated and unique
  • load and save
  • floor, round, ceiling, and trunc
  • expand.grid
  • Professional groups
8. R for Data Science Lessons (Oct-Dec 2019)
  • Simplify with c
  • Logical operators
  • char.expand
  • complete.cases
  • swirl
  • tryCatch
  • Double colons
  • for loop
  • The 100th episode
  • while loop
  • repeat loop
  • Create your own swirl lesson
  • Logic and flow control
9. R for Data Science Lessons (Jan-Mar 2020)
  • matrix, row, and column
  • cumsum, cumprod, cummax, an dcummin
  • issymetric
  • file.access
  • file.info
  • dput and dget
  • Sort a data frame by multiple columns
  • diag
  • crossprod
  • upper.tri and lower.tri
  • strsplit() splits strings at matched characters
  • Use setnames() to change the name of an object
  • Change the structure of a vector with stack()
10. R for Data Science Lessons (Apr-Jun 2020)
  • Use droplevels() to simplify factors
  • Use .Rmd for documentation
  • Use rep() to create long repetitive vectors
  • Use format() to improve readability
  • Use pmax() and pmin() to discover the scope of paired vectors
  • Use print() for more than you do now
  • Use range() and extendrange() to analyze and manipulate groups of numbers
  • Evaluate the importance of a number with rank()
  • Use saveRDS() and readRDS() to serialize objects
  • Use regular expressions with regexpr() and gregexpr()
  • message
  • regexpr
  • diff
11. R for Data Science Lessons (Jul-Sep 2020)
  • exists
  • formulas
  • RPres
  • lattice: Introduction
  • lattice: xyplot
  • lattice: cloud and wireframe
  • lattice: contourplot
  • lattice: barchart
  • lattice: splom charts
  • lattice: panels
  • lattice: stripplot
  • whichmin and whichmax
  • par: font, size, color
12. R for Data Science Lessons (Oct-Dec 2020)
  • par: margins
  • par: pch and points
  • legend
  • identical
  • Matrix math: Overview of functions
  • Matrix math review
  • matrix: solve systems
  • matrix: solve inverse
  • matrix: backsolve and forwardsolve
  • Matrix: Determinant
  • Arrays and outer
  • Matrix: Crossproduct
  • Matrix SVD and QR decomposition
13. R for Data Science Lessons (Jan-Mar 2021)
  • Matrix: Eigenvalues and eigenvectors
  • Locator
  • on.exit
  • missing
  • nargs
  • tidyverse
  • gutenbergr
  • Create and clean a natural language corpus
  • Remove stopwords from an NLP corpus
  • NLP and term-document matrix
14. R for Data Science Lessons (Apr-Jun 2021)
  • Analyze term-document matrix
  • NLP packages: Tidytext
  • NLP packages: Quanteda
  • NLP packages: Sentiment analysis
  • Word clouds
  • Hidden features of installr
  • Use the Matrix package
  • Create a sparse matrix
  • Sparse matrices, triangles, and more
  • Bootstrap analysis with R
  • checkUsage
15. R for Data Science Lessons (Jul-Sep 2021)
  • Use R on the Raspberry Pi
  • list2df()
  • Introduction to clustering
  • Clustering with kmeans
  • Clustering with pam and clara
  • Understanding silhouette graphs
  • Clustering with fanny
  • Clustering with hclust
  • Clustering with agnes
  • Clustering with diana
  • cutree and identify with hclust
  • Clustering with mona
  • Clustering: dist vs. daisy
16. R for Data Science Lessons (Oct-Dec 2021)
  • Parameterized R markdown
  • Run R on a schedule
  • The new forward pipe operator
  • Backslash lambda functions
  • Dist() in depth
  • Scale()
  • toJSON
  • fromJSON
  • Validate JSON
  • Plotmath and expression
  • Run R in batch mode
  • Explore music
  • BEEP
17. R for Data Science Lessons (Jan-Mar 2022)
  • install.packages
  • old.packages, new.packages, and update.packages
  • library and require
  • Excel in R: SUM
  • Excel in R: IF
  • Excel in R: LOOKUP
  • Excel in R: LEFT and RIGHT
  • Excel in R: MATCH
  • Excel in R: CHOOSE
  • Excel in R: DATE
  • Excel in R: DAYS
  • Excel in R: FIND and FINDB
18. R for Data Science Lessons (Apr-Jun 2022)
  • Excel in R: INDEX
  • Excel in R: COUNT
  • Excel in R: AVERAGE
  • Excel in R: SUMIF and AVERAGEIF
  • Excel in R: COUNTIF
  • Excel in R: CONCATENATE
  • Excel in R: MAX and MIN
  • Excel in R: PROPER
  • Excel in R: AND
  • Excel in R: LEN
  • Excel in R: COUNTA
  • Excel in R: NETWORKDAYS
  • Excel in R: IFERROR
19. R for Data Science Lessons (Jul-Sep 2022)
  • Citation
  • Vectorize
  • Powerpoint from R
  • Infix operator
  • Kronecker
  • Flowcharting
  • Glue
  • Crayon
  • COVID-19
  • Apexcharter
  • Factorial
  • Download files
  • Choose
20. R for Data Science Lessons (Oct-Dec 2022)
  • Beta and gamma
  • as.Date()
  • as.POSIXlt()
  • as.POSIXct()
  • Lubridate
  • ISOdate()
  • system.timezone() and OlsonNames()
  • format()
  • difftime()
  • seq.Date()
  • weekdays(), months(), quarters(), Julian()
21. R for Data Science Lessons (Jan-Mar 2023)
  • Introduction to Plumber
  • Plumber request and response objects
  • getwd setwd
  • Use Visual Studio Code with R
  • Tibbles
  • Overview of dplyr
  • dplyr: mutate
  • dplyr: select
  • dplyr: filter
  • dplyr: slice and friends
  • dplyr: summarise
  • dplyr: arrange
  • dplyr: group_by
22. R for Data Science Lessons (Apr-Jun 2023)
  • dbplyr translates R to SQL
  • dplyr: pull
  • dplyr: joins
  • R7 OOP: Introduction
  • R7 OOP: Properties
  • R7 OOPS: Property getters and setters
  • R7 OOPS: Validators
  • R7 OOP: Class Inheritance
  • R7 OOP: Generics and Methods
  • Python with RStudio
  • Animating plots
  • Animating ggplot
  • Introduction to Quarto

Taught by

Mark Niemann-Ross

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