R for Data Science: Lunch Break Lessons

New This Week

• Flowcharting

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