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lynda R for Data Science: Lunchbreak Lessons

Video Introducing this tutorial

The five minutes you spend each week will provide you with a building block you can use in the next two hours at work. Review language basics, discover methods to improve existing R code, explore new and interesting features, and learn about useful development tools and libraries that will make your time programming with R that much more productive.
All series code samples can be downloaded at https://github.com/mnr/five-minutes-of-R.Note: Because this is an ongoing series, viewers will not receive a certificate of completion.
New This Week :
Use R on the Raspberry Pi
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
zip and tar
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
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 (April 2021- June 2021) Lessons :
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