Note: If chunks do not run, you may have to uncomment package installation or other lines

Introduction to R markdown

“Programs are meant to be read by humans and only incidentally for computers to execute.” ― Donald Knuth

R markdowns are programs that mix a markup language (i.e., markdown) with programming languages (e.g., R) to best communicate compared to having either one in isolation. Many markdown features are implemented such as bold, italics, bold and italics or hyperlinks such as the previous example. It is easily integrated withing RStudio the flagship integrated development environment (IDE) for R.

Setting up RStudio

Global options for RStudio

Many newcomers and advanced users alike can benefit from customizing their RStudio global options. For example, I personally like a dark dark mode theme such as Tomorrow Night 80. Many options under the Code menu can help you adhere to best practices, catch issues, or follow a standard coding style.

The .Rprofile in the HOME directory can be used to modify startup behavior

For example, my .Rprofile file has the following code

Sys.setenv(TZ = 'EST')
if (interactive()) {
  try(expr = fortunes::fortune(), silent = TRUE)
  }
cat("Welcome, Nosferican.\nLogged at: ", as.character(Sys.time()))

## Welcome, Nosferican.
## Logged at:  2023-07-06 09:20:05

which displays an R fortune cookie, my username and current time when I start a session. The fortune cookie is a random piece of R history/culture very useful to understand the philosophy behind the project.

The .Renviron file can be used to define variables accessible during your session

For example, rather than writing my database credentials and making those avaiable in the code I can specify these as environmental variables I can access without compromising these

db_userid = "[your computing ID]"
db_pwd = "[your database pwd]"

Setting up your environment (Housekeeping)

For the following lesson, we will be using various functionality available in R packages. The following code will make the namespace (e.g., functions) available for us to use.

The next block of code will provide all the functionality we will be using during this lesson

library(magrittr)

## Warning: package 'magrittr' was built under R version 4.1.2

## 
## Attaching package: 'magrittr'

## The following object is masked from 'package:purrr':
## 
##     set_names

## The following object is masked from 'package:tidyr':
## 
##     extract

library(stringr)
library(forcats)
library(lubridate)
library(ggplot2)

Atomic data types

R has six atomic data types:

logical
integer
numeric (alias for double precision)
complex
character
raw

Logical

x <- c(NA, FALSE, TRUE)
names(x = x) <- as.character(x = x)
x

##  <NA> FALSE  TRUE 
##    NA FALSE  TRUE

& Table

outer(X = x, Y = x, FUN = "&")

##        <NA> FALSE  TRUE
## <NA>     NA FALSE    NA
## FALSE FALSE FALSE FALSE
## TRUE     NA FALSE  TRUE

| Table

outer(X = x, Y = x, FUN = "|")

##       <NA> FALSE TRUE
## <NA>    NA    NA TRUE
## FALSE   NA FALSE TRUE
## TRUE  TRUE  TRUE TRUE

xor Table

outer(X = x, Y = x, FUN = "xor")

##       <NA> FALSE  TRUE
## <NA>    NA    NA    NA
## FALSE   NA FALSE  TRUE
## TRUE    NA  TRUE FALSE

Negation

!TRUE

## [1] FALSE

!FALSE

## [1] TRUE

Logical interpretation of integers/numeric

TRUE & 0 # (TRUE & (0 == 0))

## [1] FALSE

FALSE | -2 # (FALSE | (-2 == 0))

## [1] TRUE

Integer

x = 2L
y = 3L
+x # Positive sign

## [1] 2

-x # Negative sign

## [1] -2

abs(x = x)

## [1] 2

x + y

## [1] 5

x - y

## [1] -1

x * y

## [1] 6

x / y

## [1] 0.6666667

x^y

## [1] 8

sqrt(x = x)

## [1] 1.414214

x %% y # Modulus

## [1] 2

x %/% y # Integer division

## [1] 0

log(x = x)

## [1] 0.6931472

exp(x = x)

## [1] 7.389056

factorial(x = x)

## [1] 2

Numeric

x = 2.5
y = 3.2

+x # Positive sign

## [1] 2.5

-x # Negative sign

## [1] -2.5

abs(x = x)

## [1] 2.5

x + y

## [1] 5.7

x - y

## [1] -0.7

x * y

## [1] 8

x / y

## [1] 0.78125

x^y

## [1] 18.76757

sqrt(x = x)

## [1] 1.581139

x %% y # Modulus

## [1] 2.5

x %/% y # Integer division

## [1] 0

log(x = x) # Log (defaults to natual log)

## [1] 0.9162907

exp(x = x)

## [1] 12.18249

factorial(x = x)

## [1] 3.323351

round(x = x, digits = 2L)

## [1] 2.5

floor(x = x)

## [1] 2

ceiling(x = x)

## [1] 3

Complex

x = 2 + 1i
y = 3 + 1i

+x # Positive sign

## [1] 2+1i

-x # Negative sign

## [1] -2-1i

abs(x = x)

## [1] 2.236068

x + y

## [1] 5+2i

x - y

## [1] -1+0i

x * y

## [1] 5+5i

x / y

## [1] 0.7+0.1i

x^y

## [1] -4.113793+5.703463i

sqrt(x = x)

## [1] 1.455347+0.343561i

log(x = x) # Log (defaults to natual log)

## [1] 0.804719+0.4636476i

exp(x = x)

## [1] 3.992324+6.217676i

x == y

## [1] FALSE

is.complex(x = x)

## [1] TRUE

Re(z = x)

## [1] 2

Im(z = x)

## [1] 1

Mod(z = x)

## [1] 2.236068

Arg(z = x)

## [1] 0.4636476

Conj(z = x)

## [1] 2-1i

Character

x <- "\"R doesn't like emojis :(, Julia does.\" - Bayoán (史志鼎)"
str_detect(string = x, pattern = "Bayoán")

## [1] TRUE

str_detect(string = x, pattern = "Nosferican")

## [1] FALSE

str_extract(string = x, pattern = "(?<=\" - ).*")

## [1] "Bayoán (史志鼎)"

str_sub(string = x, start = 28L, end = 32L)

## [1] "Julia"

str_replace(string = x, pattern = "(?<=\" - ).*", "Me")

## [1] "\"R doesn't like emojis :(, Julia does.\" - Me"

str_remove(string = x, pattern = "e")

## [1] "\"R dosn't like emojis :(, Julia does.\" - Bayoán (史志鼎)"

str_replace_all(string = x, pattern = "e", replace = "E")

## [1] "\"R doEsn't likE Emojis :(, Julia doEs.\" - Bayoán (史志鼎)"

str_c("This a fine quote.", x, sep = "  ")

## [1] "This a fine quote.  \"R doesn't like emojis :(, Julia does.\" - Bayoán (史志鼎)"

Collections

Arrays

Arrays are collections of homogeneous data types. The most common types are the one dimensional array (vector) and the two dimensional array (matrix).

vector(mode = "logical", length = 2L)

## [1] FALSE FALSE

vector(mode = "character", length = 5L)

## [1] "" "" "" "" ""

vector(mode = "numeric", length = 3L)

## [1] 0 0 0

vector(mode = "integer", length = 4L)

## [1] 0 0 0 0

x <- 1:10
str(object = x)

##  int [1:10] 1 2 3 4 5 6 7 8 9 10

summary(object = x)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    1.00    3.25    5.50    5.50    7.75   10.00

table(origininal_object = x)

## origininal_object
##  1  2  3  4  5  6  7  8  9 10 
##  1  1  1  1  1  1  1  1  1  1

x[2:5] <- 1L
table(modified_object = x)

## modified_object
##  1  6  7  8  9 10 
##  5  1  1  1  1  1

x[11] <- NA
typeof(x)

## [1] "integer"

sort(x = x, decreasing = TRUE, na.last = TRUE) # default values TRUE and NA

##  [1] 10  9  8  7  6  1  1  1  1  1 NA

x[13] <- "A"
x

##  [1] "1"  "1"  "1"  "1"  "1"  "6"  "7"  "8"  "9"  "10" NA   NA   "A"

is.vector(x = x)

## [1] TRUE

Matrices

x <- matrix(data = 1:16,
            nrow = 4L,
            ncol = 4L,
            dimnames = list(LETTERS[1:4], letters[1:4]))
x + 2 * x

##    a  b  c  d
## A  3 15 27 39
## B  6 18 30 42
## C  9 21 33 45
## D 12 24 36 48

x %*% x

##     a   b   c   d
## A  90 202 314 426
## B 100 228 356 484
## C 110 254 398 542
## D 120 280 440 600

str(object = x)

##  int [1:4, 1:4] 1 2 3 4 5 6 7 8 9 10 ...
##  - attr(*, "dimnames")=List of 2
##   ..$ : chr [1:4] "A" "B" "C" "D"
##   ..$ : chr [1:4] "a" "b" "c" "d"

summary(object = x)

##        a              b              c               d        
##  Min.   :1.00   Min.   :5.00   Min.   : 9.00   Min.   :13.00  
##  1st Qu.:1.75   1st Qu.:5.75   1st Qu.: 9.75   1st Qu.:13.75  
##  Median :2.50   Median :6.50   Median :10.50   Median :14.50  
##  Mean   :2.50   Mean   :6.50   Mean   :10.50   Mean   :14.50  
##  3rd Qu.:3.25   3rd Qu.:7.25   3rd Qu.:11.25   3rd Qu.:15.25  
##  Max.   :4.00   Max.   :8.00   Max.   :12.00   Max.   :16.00

table(x)

## x
##  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 
##  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1

x[3, 2] <- NA
x

##   a  b  c  d
## A 1  5  9 13
## B 2  6 10 14
## C 3 NA 11 15
## D 4  8 12 16

Arrays

x <- array(data = 1:3, dim = c(2L, 4L, 3L))
x

## , , 1
## 
##      [,1] [,2] [,3] [,4]
## [1,]    1    3    2    1
## [2,]    2    1    3    2
## 
## , , 2
## 
##      [,1] [,2] [,3] [,4]
## [1,]    3    2    1    3
## [2,]    1    3    2    1
## 
## , , 3
## 
##      [,1] [,2] [,3] [,4]
## [1,]    2    1    3    2
## [2,]    3    2    1    3

str(object = x)

##  int [1:2, 1:4, 1:3] 1 2 3 1 2 3 1 2 3 1 ...

dim(x = x)

## [1] 2 4 3

Lists

x = list(x = 1:5, y = TRUE, z = c("A", "Z"))
str(object = x)

## List of 3
##  $ x: int [1:5] 1 2 3 4 5
##  $ y: logi TRUE
##  $ z: chr [1:2] "A" "Z"

x$z

## [1] "A" "Z"

x$A <- 23L
x

## $x
## [1] 1 2 3 4 5
## 
## $y
## [1] TRUE
## 
## $z
## [1] "A" "Z"
## 
## $A
## [1] 23

x[1L]

## $x
## [1] 1 2 3 4 5

x[[1L]]

## [1] 1 2 3 4 5

x[[4]] <- list(a = 3, b = 2)
x

## $x
## [1] 1 2 3 4 5
## 
## $y
## [1] TRUE
## 
## $z
## [1] "A" "Z"
## 
## $A
## $A$a
## [1] 3
## 
## $A$b
## [1] 2

x$A$b

## [1] 2

Structs

Date time objects are structs can wrap an atomic data element for special functionality

x <- now()
year(x = x)

## [1] 2023

month(x = x)

## [1] 7

day(x = x)

## [1] 6

hour(x = x)

## [1] 9

minute(x = x)

## [1] 20

seconds(x = 1)

## [1] "1S"

x %m+% months(x = 1L, abbreviate = TRUE)

## [1] "2023-08-06 09:20:05 EST"

Named vectors are an example of a struct with more than one atomic data type element

x <- c(a = 1, b = 2)
str(object = x)

##  Named num [1:2] 1 2
##  - attr(*, "names")= chr [1:2] "a" "b"

names(x = x)

## [1] "a" "b"

One last example includes categorical or factor variables

set.seed(seed = 0L)
x <- as_factor(x = sample(x = letters[1:5], size = 100L, replace = TRUE))
str(x)

##  Factor w/ 5 levels "a","d","b","e",..: 1 2 1 3 4 5 3 5 5 1 ...

x[10L]

## [1] a
## Levels: a d b e c

levels(x = x)

## [1] "a" "d" "b" "e" "c"

ggplot(mapping = aes(x = x)) +
  geom_bar() +
  labs(title = "Histogram",
       x = "Category",
       y = "Count") +
  theme(plot.title = element_text(hjust = 0.5))

“The 3 Ways of R” or Becoming a Better Code Googler (GoogleR?)

author: Aaron D. Schroeder date: 6/5/2020 autosize: true

The R Language - Multiple Approaches

Used many different ways, including

Procedural programming (PP)
- HOW MOST EVERYBODY STARTS, also known as inline programming takes a top-down approach. Writing a list of instructions step by step.
Object-oriented programming (OOP)
- encapsulating data and behavior into objects. An OOP application will use a collection of objects which knows how to perform certain actions and how to interact with other elements of the application.
Functional programming (FP)
- WHAT MOST PEOPLE GET TO AFTER PROCEDURAL, passing data from function to function to function to get a result. Functions are treated as data, meaning you can use them as parameters, return them, build functions from other functions, etc.

Like Javascript

Can be also be used as PP, OOP, or FP

‘Frameworks’ are created to make it easier

React
Vue.js
Ember.js
Meteor.js

And many more! BUT, A Single Framework can Lock You In!

PROBLEM! People are only learning how to do Javascript the “React” or “Vue.js” or … way - VERY LIMITING - ESPECIALLY FOR USING OTHER PEOPLE’S CODE!

R ‘Frameworks’

While not exactly “Frameworks”, R has the same issue in that different coding “approaches” have emerged

base
- championed purists who like to do things the old-fashioned way (reminds them of the good-ol-days before S was renamed to R)
- if you know what is going on “under the hood” you can write susinct and fast code, but if you don’t…
tidy (tibl, dplyr, stringr, many many more)
- championed by the ‘followers of the Wickham Way’, I’m no going to say it’s a cult, but…
- an “opionated” way to do functional programming that is easier to pick up than base
- get all data to tidy format, then process in an easy to follow chain
- way different than base and rather verbose
datatable
- championed by grumpy programmers who value speed and sussinctness most
- actually just a very fast data structure that can be used with tidy or anything else
- however, has it’s own syntax that can be significantly more susinct
hybrid
- combine the speed of data.table with the programming style of tidy
- more and more packages are appearing to make this possible

Need to be Bi/Tri Lingual!

If you are going to be a great R Code Googler (which you want to be!) you need to be able to at least read and understand what is going on in the code samples you find, regardless of the approach used!

Today’s Objectives

So, for today our objectives are to

Get an introduction to very simple versions of the different approaches to
- reading data into R
- susbsetting data (selecting & filtering)
- renaming columns
- piping
Send you off to the interactive DataCamp tutorials to learn more and practice
- Data Manipulation with dplyr
- Data Manipulation with data.table

df1 <- data.frame(a = seq(1,16,by=2), b = LETTERS[1:8], x=month.abb[1:8], y = sample(10:20,10000, replace = TRUE), z=letters[1:8])
data.table::fwrite(df1, "sample_small.csv")
df2 <- data.frame(a = seq(1,16,by=2), b = LETTERS[1:8], x=month.abb[1:8], y = sample(10:20,1000000, replace = TRUE), z=letters[1:8])
data.table::fwrite(df2, "sample_medium.csv")
df3 <- data.frame(a = seq(1,16,by=2), b = LETTERS[1:8], x=month.abb[1:8], y = sample(10:20,10000000, replace = TRUE), z=letters[1:8])
data.table::fwrite(df3, "sample_large.csv")

base

system.time(read.csv <- read.csv("sample_large.csv", stringsAsFactors =
FALSE))

##    user  system elapsed 
##   7.493   0.553   8.128

readr (need to assign to new data.frame)

library(readr)
system.time(read_csv <- read_csv("sample_large.csv", progress = FALSE))

## Rows: 10000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

##    user  system elapsed 
##   8.161   0.297   3.083

data.table

library(data.table)

## 
## Attaching package: 'data.table'

## The following objects are masked from 'package:lubridate':
## 
##     hour, isoweek, mday, minute, month, quarter, second, wday, week,
##     yday, year

## The following objects are masked from 'package:dplyr':
## 
##     between, first, last

## The following object is masked from 'package:purrr':
## 
##     transpose

system.time(fread <- fread("sample_large.csv"))

##    user  system elapsed 
##   1.033   0.064   1.109

more advanced data.table

fread("pigeon-racing.csv", drop = 4:11)

##      Pos              Breeder          Pigeon
##   1:   1        Texas Outlaws 19633-AU15-FOYS
##   2:   2       Junior Juanich   0402-AU15-JRL
##   3:   3    Jerry Allensworth  0404-AU15-VITA
##   4:   4          Alias-Alias  2013-AU15-ALIA
##   5:   5         Greg Glazier   5749-AU15-SLI
##  ---                                         
## 396: 396      Hutchins/Milner  2496-AU15-VITA
## 397: 397              Twin200  7799-AU15-VITA
## 398: 398     Mayberry Classic   5508-AU15-MAC
## 399: 399 Sierra Ranch Classic  0519-AU15-SIER
## 400: 400    Hi-Cal Connection  0798-AU15-HAWA

fread("pigeon-racing.csv", select = c(1, 2, 3))

##      Pos              Breeder          Pigeon
##   1:   1        Texas Outlaws 19633-AU15-FOYS
##   2:   2       Junior Juanich   0402-AU15-JRL
##   3:   3    Jerry Allensworth  0404-AU15-VITA
##   4:   4          Alias-Alias  2013-AU15-ALIA
##   5:   5         Greg Glazier   5749-AU15-SLI
##  ---                                         
## 396: 396      Hutchins/Milner  2496-AU15-VITA
## 397: 397              Twin200  7799-AU15-VITA
## 398: 398     Mayberry Classic   5508-AU15-MAC
## 399: 399 Sierra Ranch Classic  0519-AU15-SIER
## 400: 400    Hi-Cal Connection  0798-AU15-HAWA

fread("pigeon-racing.csv", drop = c("Name", "Arrival"))

##      Pos              Breeder          Pigeon Color Sex Ent   Speed  To Win
##   1:   1        Texas Outlaws 19633-AU15-FOYS  BCWF   H   1 172.155 0:00:00
##   2:   2       Junior Juanich   0402-AU15-JRL  SIWF   H   1 163.569 0:05:21
##   3:   3    Jerry Allensworth  0404-AU15-VITA    BB   H   1 163.442 0:05:27
##   4:   4          Alias-Alias  2013-AU15-ALIA  BBSP   H   1 163.392 0:05:28
##   5:   5         Greg Glazier   5749-AU15-SLI    BC   H   1 163.366 0:05:30
##  ---                                                                       
## 396: 396      Hutchins/Milner  2496-AU15-VITA    BB   H   5  90.901 1:31:23
## 397: 397              Twin200  7799-AU15-VITA   SIL   H   2  87.817 1:38:10
## 398: 398     Mayberry Classic   5508-AU15-MAC  BBSP   H   2  83.929 1:47:28
## 399: 399 Sierra Ranch Classic  0519-AU15-SIER    BC   H   6  78.286 2:02:34
## 400: 400    Hi-Cal Connection  0798-AU15-HAWA    BB   H   5  76.677 2:07:18
##      Eligible
##   1:      Yes
##   2:      Yes
##   3:      Yes
##   4:      Yes
##   5:      Yes
##  ---         
## 396:      Yes
## 397:      Yes
## 398:      Yes
## 399:      Yes
## 400:      Yes

fread("pigeon-racing.csv", select = c("Breeder", "Speed"))

##                   Breeder   Speed
##   1:        Texas Outlaws 172.155
##   2:       Junior Juanich 163.569
##   3:    Jerry Allensworth 163.442
##   4:          Alias-Alias 163.392
##   5:         Greg Glazier 163.366
##  ---                             
## 396:      Hutchins/Milner  90.901
## 397:              Twin200  87.817
## 398:     Mayberry Classic  83.929
## 399: Sierra Ranch Classic  78.286
## 400:    Hi-Cal Connection  76.677

A 4th Way!

#library(vroom)
#system.time(vroom <- vroom("sample_large.csv"))

library(microbenchmark)

## Warning: package 'microbenchmark' was built under R version 4.1.2

library(here)

## here() starts at /Users/joannaschroeder/Documents/R/intro-rmd-websites

#results_vroom <- microbenchmark(
#read.csv = read.csv(file = here("static", "data", "sim-data-large.csv")),
#read_csv = read_csv(file = here("static", "data", "sim-data-large.csv")),
#vroom = vroom::vroom(file = here("static", "data", "sim-data-large.csv"))
#)

results <- microbenchmark(
read.csv = read.csv(file = "sample_medium.csv", stringsAsFactors =
FALSE),
read_csv = read_csv(file = "sample_medium.csv", progress = FALSE),
fread = fread(file = "sample_medium.csv"),
vroom = vroom::vroom(file = "sample_medium.csv"),
times = 10
)

## Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Rows: 1000000 Columns: 5── Column specification ─────────────────────────────────────────────
## Delimiter: ","
## chr (3): b, x, z
## dbl (2): a, y
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

library(ggplot2)

autoplot(object = results) +
scale_y_log10() +
labs(y = "Time [milliseconds], logged")

## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.

A data frame, the basic tabular representation of data in R

n = c(2, 3, 5) 
s = c("aa", "bb", "cc") 
b = c(TRUE, FALSE, TRUE) 
df = data.frame(n, s, b)       # df is a data frame
df

##   n  s     b
## 1 2 aa  TRUE
## 2 3 bb FALSE
## 3 5 cc  TRUE

Create Sample Data Frame

df <- data.frame(column_1 = c(1, 2, 3),
                 column_2 = c("A", "B", "C"),
                 column_3 = c("D", "E", "F"),
                 stringsAsFactors = F)
df

##   column_1 column_2 column_3
## 1        1        A        D
## 2        2        B        E
## 3        3        C        F

pg <- fread("pigeon-racing.csv")

Subset Rows

base R

df[df$column_1 == 2,] # have to include df$ before column name and don't forget the comma!

##   column_1 column_2 column_3
## 2        2        B        E

df[df$column_1 == 2,]

##   column_1 column_2 column_3
## 2        2        B        E

dplyr

library(dplyr)
filter(df, column_1 == 2)

##   column_1 column_2 column_3
## 1        2        B        E

filter(df, column_1 == 2)

##   column_1 column_2 column_3
## 1        2        B        E

data.table

library(data.table)
setDT(df) # needs to be a data.table first
df[column_1 == 2]

##    column_1 column_2 column_3
## 1:        2        B        E

df[column_1 == 2]

##    column_1 column_2 column_3
## 1:        2        B        E

Subset Columns

base R

df[, c("column_2", "column_3")]

##    column_2 column_3
## 1:        A        D
## 2:        B        E
## 3:        C        F

dplyr

select(df, c("column_2", "column_3"))

##    column_2 column_3
## 1:        A        D
## 2:        B        E
## 3:        C        F

data.table

setDT(df) # needs to be a data.table first
df[, .(column_2, column_3)] # the dot . is a shortcut for list()

##    column_2 column_3
## 1:        A        D
## 2:        B        E
## 3:        C        F

df[, .(column_2, column_3)]

##    column_2 column_3
## 1:        A        D
## 2:        B        E
## 3:        C        F

# or just like a data.frame
df[, c("column_2", "column_3")]

##    column_2 column_3
## 1:        A        D
## 2:        B        E
## 3:        C        F

Subset Rows & Columns

base R

df[df$column_1 == 2, c("column_2", "column_3")]

##    column_2 column_3
## 1:        B        E

dplyr

library(dplyr)

# two steps using the magrittr "pipe"
df %>%
  filter(column_1 == 2) %>%
  select(c("column_2", "column_3")) # don't need to specifcy data.frame in second step

##    column_2 column_3
## 1:        B        E

data.table

setDT(df) # needs to be a data.table first

df[column_1 == 2, .(column_2, column_3)] # the dot . is a shortcut for list()

##    column_2 column_3
## 1:        B        E

# or just like a data.frame
df[df$column_1 == 2, c("column_2", "column_3")]

##    column_2 column_3
## 1:        B        E

renaming column base

df <- data.frame(column_1 = c(1, 2, 3), column_b = c("A", "B", "C"))
print(df)

##   column_1 column_b
## 1        1        A
## 2        2        B
## 3        3        C

names(df)[names(df) == 'column_b'] <- 'column_2'
print(df)

##   column_1 column_2
## 1        1        A
## 2        2        B
## 3        3        C

renaming column dplyr

library(dplyr)
df <- data.frame(column_1 = c(1, 2, 3), column_b = c("A", "B", "C"))
print(df)

##   column_1 column_b
## 1        1        A
## 2        2        B
## 3        3        C

df <- dplyr::rename(df, "column_2" = column_b)
print(df)

##   column_1 column_2
## 1        1        A
## 2        2        B
## 3        3        C

renaming column data.table

library(data.table)
df <- data.frame(column_1 = c(1, 2, 3), column_b = c("A", "B", "C"))
print(df)

##   column_1 column_b
## 1        1        A
## 2        2        B
## 3        3        C

setnames(df, "column_b", "column_2")
print(df)

##   column_1 column_2
## 1        1        A
## 2        2        B
## 3        3        C

library(data.table)
library(dplyr)
pg <- fread("pigeon-racing.csv")

aggregate(Ent ~ Breeder, pg, length)

##                    Breeder Ent
## 1                  4-Birds   4
## 2           7-11 Syndicate   2
## 3               A P C Loft  12
## 4              Alias-Alias  11
## 5              Alonso Loft   3
## 6           American Lofts   4
## 7              Andy Skwiat  10
## 8               B D P Loft   3
## 9         Baldwin & Tilson   7
## 10             Baysideboys   3
## 11             Bionic Loft   2
## 12         Braden/Olivieri   2
## 13         Bud & Orie Loft   2
## 14      Bynum Family Lofts   5
## 15           Captain Chuck  10
## 16          Centmeyer Loft   2
## 17   Charlie's Little Loft   3
## 18        Churn Creek Loft   3
## 19      Clear Springs Loft   3
## 20     Credeur Family Loft   2
## 21          Crestview Loft   4
## 22    Crowley's Ridge Loft   2
## 23      Cypress Hills Farm   2
## 24           Dal-Tex R P C   3
## 25             Dave Dudley   3
## 26            Dave Harrett   6
## 27            Debbie Ganus   6
## 28        Drama Queen Loft   3
## 29               Dunn Loft   1
## 30              E & E Loft   3
## 31           Emerson/Krass   5
## 32          Equalizer Loft   4
## 33             Family Loft  12
## 34      Fisher Family Loft   5
## 35            Flyhome Loft   2
## 36         Flying D Loft 2   3
## 37       Ganus Family Loft   6
## 38        Goshentown Lofts   4
## 39        Greek Connection   5
## 40            Greg Glazier   4
## 41       Hi-Cal Connection   5
## 42         Hutchins/Milner   5
## 43            Iv Aces Loft   2
## 44    J & M Partridge Loft   4
## 45                  Jb & D  13
## 46                  Jerdee   6
## 47       Jerry Allensworth   4
## 48           Jerry Johnson   2
## 49          Junior Juanich   6
## 50              Kiko Arana   4
## 51               King City   3
## 52             Kokomo Loft   2
## 53               Kwan Loft   4
## 54            Leyba's Loft   3
## 55       Little Reata Loft   6
## 56           Loizzi/Sikora   5
## 57           Lonestar Loft   4
## 58        Mayberry Classic   2
## 59       Mc Laughlin Lofts   4
## 60              Mike Belus   2
## 61           Miller Loft 2   1
## 62         Milner-Mckinsey   8
## 63              Mr. Dovely   1
## 64           N C Syndicate   6
## 65      Nanez Family Lofts   4
## 66         Non Pareil Loft   4
## 67             Oscar/Ralph   1
## 68                P J Loft   3
## 69            Protege Loft   4
## 70              Rayce Loft   4
## 71                  Redtex  12
## 72             Rick Barker   5
## 73 Sandstrom Brothers Loft   7
## 74      Shang N Dennis Yoh   5
## 75    Shawnie & Lenny Loft   4
## 76    Sierra Ranch Classic   6
## 77      Silver Dollar Loft   2
## 78         Skip's Janssens   5
## 79           Stelling Loft   4
## 80            Stenman Loft  10
## 81              T C R Loft   5
## 82        Terry Montgomery   2
## 83           Texas Outlaws   4
## 84         The Bailey Team   7
## 85     The Brand Syndicate   5
## 86               Tongol 11   3
## 87       Tony Family Lofts   3
## 88               Turk Loft   2
## 89                 Twin200   2
## 90          Woodsend/Perry   9

table(pg$Breeder)

## 
##                 4-Birds          7-11 Syndicate              A P C Loft 
##                       4                       2                      12 
##             Alias-Alias             Alonso Loft          American Lofts 
##                      11                       3                       4 
##             Andy Skwiat              B D P Loft        Baldwin & Tilson 
##                      10                       3                       7 
##             Baysideboys             Bionic Loft         Braden/Olivieri 
##                       3                       2                       2 
##         Bud & Orie Loft      Bynum Family Lofts           Captain Chuck 
##                       2                       5                      10 
##          Centmeyer Loft   Charlie's Little Loft        Churn Creek Loft 
##                       2                       3                       3 
##      Clear Springs Loft     Credeur Family Loft          Crestview Loft 
##                       3                       2                       4 
##    Crowley's Ridge Loft      Cypress Hills Farm           Dal-Tex R P C 
##                       2                       2                       3 
##             Dave Dudley            Dave Harrett            Debbie Ganus 
##                       3                       6                       6 
##        Drama Queen Loft               Dunn Loft              E & E Loft 
##                       3                       1                       3 
##           Emerson/Krass          Equalizer Loft             Family Loft 
##                       5                       4                      12 
##      Fisher Family Loft            Flyhome Loft         Flying D Loft 2 
##                       5                       2                       3 
##       Ganus Family Loft        Goshentown Lofts        Greek Connection 
##                       6                       4                       5 
##            Greg Glazier       Hi-Cal Connection         Hutchins/Milner 
##                       4                       5                       5 
##            Iv Aces Loft    J & M Partridge Loft                  Jb & D 
##                       2                       4                      13 
##                  Jerdee       Jerry Allensworth           Jerry Johnson 
##                       6                       4                       2 
##          Junior Juanich              Kiko Arana               King City 
##                       6                       4                       3 
##             Kokomo Loft               Kwan Loft            Leyba's Loft 
##                       2                       4                       3 
##       Little Reata Loft           Loizzi/Sikora           Lonestar Loft 
##                       6                       5                       4 
##        Mayberry Classic       Mc Laughlin Lofts              Mike Belus 
##                       2                       4                       2 
##           Miller Loft 2         Milner-Mckinsey              Mr. Dovely 
##                       1                       8                       1 
##           N C Syndicate      Nanez Family Lofts         Non Pareil Loft 
##                       6                       4                       4 
##             Oscar/Ralph                P J Loft            Protege Loft 
##                       1                       3                       4 
##              Rayce Loft                  Redtex             Rick Barker 
##                       4                      12                       5 
## Sandstrom Brothers Loft      Shang N Dennis Yoh    Shawnie & Lenny Loft 
##                       7                       5                       4 
##    Sierra Ranch Classic      Silver Dollar Loft         Skip's Janssens 
##                       6                       2                       5 
##           Stelling Loft            Stenman Loft              T C R Loft 
##                       4                      10                       5 
##        Terry Montgomery           Texas Outlaws         The Bailey Team 
##                       2                       4                       7 
##     The Brand Syndicate               Tongol 11       Tony Family Lofts 
##                       5                       3                       3 
##               Turk Loft                 Twin200          Woodsend/Perry 
##                       2                       2                       9

data.frame(table(pg$Breeder))

##                       Var1 Freq
## 1                  4-Birds    4
## 2           7-11 Syndicate    2
## 3               A P C Loft   12
## 4              Alias-Alias   11
## 5              Alonso Loft    3
## 6           American Lofts    4
## 7              Andy Skwiat   10
## 8               B D P Loft    3
## 9         Baldwin & Tilson    7
## 10             Baysideboys    3
## 11             Bionic Loft    2
## 12         Braden/Olivieri    2
## 13         Bud & Orie Loft    2
## 14      Bynum Family Lofts    5
## 15           Captain Chuck   10
## 16          Centmeyer Loft    2
## 17   Charlie's Little Loft    3
## 18        Churn Creek Loft    3
## 19      Clear Springs Loft    3
## 20     Credeur Family Loft    2
## 21          Crestview Loft    4
## 22    Crowley's Ridge Loft    2
## 23      Cypress Hills Farm    2
## 24           Dal-Tex R P C    3
## 25             Dave Dudley    3
## 26            Dave Harrett    6
## 27            Debbie Ganus    6
## 28        Drama Queen Loft    3
## 29               Dunn Loft    1
## 30              E & E Loft    3
## 31           Emerson/Krass    5
## 32          Equalizer Loft    4
## 33             Family Loft   12
## 34      Fisher Family Loft    5
## 35            Flyhome Loft    2
## 36         Flying D Loft 2    3
## 37       Ganus Family Loft    6
## 38        Goshentown Lofts    4
## 39        Greek Connection    5
## 40            Greg Glazier    4
## 41       Hi-Cal Connection    5
## 42         Hutchins/Milner    5
## 43            Iv Aces Loft    2
## 44    J & M Partridge Loft    4
## 45                  Jb & D   13
## 46                  Jerdee    6
## 47       Jerry Allensworth    4
## 48           Jerry Johnson    2
## 49          Junior Juanich    6
## 50              Kiko Arana    4
## 51               King City    3
## 52             Kokomo Loft    2
## 53               Kwan Loft    4
## 54            Leyba's Loft    3
## 55       Little Reata Loft    6
## 56           Loizzi/Sikora    5
## 57           Lonestar Loft    4
## 58        Mayberry Classic    2
## 59       Mc Laughlin Lofts    4
## 60              Mike Belus    2
## 61           Miller Loft 2    1
## 62         Milner-Mckinsey    8
## 63              Mr. Dovely    1
## 64           N C Syndicate    6
## 65      Nanez Family Lofts    4
## 66         Non Pareil Loft    4
## 67             Oscar/Ralph    1
## 68                P J Loft    3
## 69            Protege Loft    4
## 70              Rayce Loft    4
## 71                  Redtex   12
## 72             Rick Barker    5
## 73 Sandstrom Brothers Loft    7
## 74      Shang N Dennis Yoh    5
## 75    Shawnie & Lenny Loft    4
## 76    Sierra Ranch Classic    6
## 77      Silver Dollar Loft    2
## 78         Skip's Janssens    5
## 79           Stelling Loft    4
## 80            Stenman Loft   10
## 81              T C R Loft    5
## 82        Terry Montgomery    2
## 83           Texas Outlaws    4
## 84         The Bailey Team    7
## 85     The Brand Syndicate    5
## 86               Tongol 11    3
## 87       Tony Family Lofts    3
## 88               Turk Loft    2
## 89                 Twin200    2
## 90          Woodsend/Perry    9

count(pg, Breeder)

##                     Breeder  n
##  1:                 4-Birds  4
##  2:          7-11 Syndicate  2
##  3:              A P C Loft 12
##  4:             Alias-Alias 11
##  5:             Alonso Loft  3
##  6:          American Lofts  4
##  7:             Andy Skwiat 10
##  8:              B D P Loft  3
##  9:        Baldwin & Tilson  7
## 10:             Baysideboys  3
## 11:             Bionic Loft  2
## 12:         Braden/Olivieri  2
## 13:         Bud & Orie Loft  2
## 14:      Bynum Family Lofts  5
## 15:           Captain Chuck 10
## 16:          Centmeyer Loft  2
## 17:   Charlie's Little Loft  3
## 18:        Churn Creek Loft  3
## 19:      Clear Springs Loft  3
## 20:     Credeur Family Loft  2
## 21:          Crestview Loft  4
## 22:    Crowley's Ridge Loft  2
## 23:      Cypress Hills Farm  2
## 24:           Dal-Tex R P C  3
## 25:             Dave Dudley  3
## 26:            Dave Harrett  6
## 27:            Debbie Ganus  6
## 28:        Drama Queen Loft  3
## 29:               Dunn Loft  1
## 30:              E & E Loft  3
## 31:           Emerson/Krass  5
## 32:          Equalizer Loft  4
## 33:             Family Loft 12
## 34:      Fisher Family Loft  5
## 35:            Flyhome Loft  2
## 36:         Flying D Loft 2  3
## 37:       Ganus Family Loft  6
## 38:        Goshentown Lofts  4
## 39:        Greek Connection  5
## 40:            Greg Glazier  4
## 41:       Hi-Cal Connection  5
## 42:         Hutchins/Milner  5
## 43:            Iv Aces Loft  2
## 44:    J & M Partridge Loft  4
## 45:                  Jb & D 13
## 46:                  Jerdee  6
## 47:       Jerry Allensworth  4
## 48:           Jerry Johnson  2
## 49:          Junior Juanich  6
## 50:              Kiko Arana  4
## 51:               King City  3
## 52:             Kokomo Loft  2
## 53:               Kwan Loft  4
## 54:            Leyba's Loft  3
## 55:       Little Reata Loft  6
## 56:           Loizzi/Sikora  5
## 57:           Lonestar Loft  4
## 58:        Mayberry Classic  2
## 59:       Mc Laughlin Lofts  4
## 60:              Mike Belus  2
## 61:           Miller Loft 2  1
## 62:         Milner-Mckinsey  8
## 63:              Mr. Dovely  1
## 64:           N C Syndicate  6
## 65:      Nanez Family Lofts  4
## 66:         Non Pareil Loft  4
## 67:             Oscar/Ralph  1
## 68:                P J Loft  3
## 69:            Protege Loft  4
## 70:              Rayce Loft  4
## 71:                  Redtex 12
## 72:             Rick Barker  5
## 73: Sandstrom Brothers Loft  7
## 74:      Shang N Dennis Yoh  5
## 75:    Shawnie & Lenny Loft  4
## 76:    Sierra Ranch Classic  6
## 77:      Silver Dollar Loft  2
## 78:         Skip's Janssens  5
## 79:           Stelling Loft  4
## 80:            Stenman Loft 10
## 81:              T C R Loft  5
## 82:        Terry Montgomery  2
## 83:           Texas Outlaws  4
## 84:         The Bailey Team  7
## 85:     The Brand Syndicate  5
## 86:               Tongol 11  3
## 87:       Tony Family Lofts  3
## 88:               Turk Loft  2
## 89:                 Twin200  2
## 90:          Woodsend/Perry  9
##                     Breeder  n

#or with magrittr piping
pg %>% count(Breeder)

##                     Breeder  n
##  1:                 4-Birds  4
##  2:          7-11 Syndicate  2
##  3:              A P C Loft 12
##  4:             Alias-Alias 11
##  5:             Alonso Loft  3
##  6:          American Lofts  4
##  7:             Andy Skwiat 10
##  8:              B D P Loft  3
##  9:        Baldwin & Tilson  7
## 10:             Baysideboys  3
## 11:             Bionic Loft  2
## 12:         Braden/Olivieri  2
## 13:         Bud & Orie Loft  2
## 14:      Bynum Family Lofts  5
## 15:           Captain Chuck 10
## 16:          Centmeyer Loft  2
## 17:   Charlie's Little Loft  3
## 18:        Churn Creek Loft  3
## 19:      Clear Springs Loft  3
## 20:     Credeur Family Loft  2
## 21:          Crestview Loft  4
## 22:    Crowley's Ridge Loft  2
## 23:      Cypress Hills Farm  2
## 24:           Dal-Tex R P C  3
## 25:             Dave Dudley  3
## 26:            Dave Harrett  6
## 27:            Debbie Ganus  6
## 28:        Drama Queen Loft  3
## 29:               Dunn Loft  1
## 30:              E & E Loft  3
## 31:           Emerson/Krass  5
## 32:          Equalizer Loft  4
## 33:             Family Loft 12
## 34:      Fisher Family Loft  5
## 35:            Flyhome Loft  2
## 36:         Flying D Loft 2  3
## 37:       Ganus Family Loft  6
## 38:        Goshentown Lofts  4
## 39:        Greek Connection  5
## 40:            Greg Glazier  4
## 41:       Hi-Cal Connection  5
## 42:         Hutchins/Milner  5
## 43:            Iv Aces Loft  2
## 44:    J & M Partridge Loft  4
## 45:                  Jb & D 13
## 46:                  Jerdee  6
## 47:       Jerry Allensworth  4
## 48:           Jerry Johnson  2
## 49:          Junior Juanich  6
## 50:              Kiko Arana  4
## 51:               King City  3
## 52:             Kokomo Loft  2
## 53:               Kwan Loft  4
## 54:            Leyba's Loft  3
## 55:       Little Reata Loft  6
## 56:           Loizzi/Sikora  5
## 57:           Lonestar Loft  4
## 58:        Mayberry Classic  2
## 59:       Mc Laughlin Lofts  4
## 60:              Mike Belus  2
## 61:           Miller Loft 2  1
## 62:         Milner-Mckinsey  8
## 63:              Mr. Dovely  1
## 64:           N C Syndicate  6
## 65:      Nanez Family Lofts  4
## 66:         Non Pareil Loft  4
## 67:             Oscar/Ralph  1
## 68:                P J Loft  3
## 69:            Protege Loft  4
## 70:              Rayce Loft  4
## 71:                  Redtex 12
## 72:             Rick Barker  5
## 73: Sandstrom Brothers Loft  7
## 74:      Shang N Dennis Yoh  5
## 75:    Shawnie & Lenny Loft  4
## 76:    Sierra Ranch Classic  6
## 77:      Silver Dollar Loft  2
## 78:         Skip's Janssens  5
## 79:           Stelling Loft  4
## 80:            Stenman Loft 10
## 81:              T C R Loft  5
## 82:        Terry Montgomery  2
## 83:           Texas Outlaws  4
## 84:         The Bailey Team  7
## 85:     The Brand Syndicate  5
## 86:               Tongol 11  3
## 87:       Tony Family Lofts  3
## 88:               Turk Loft  2
## 89:                 Twin200  2
## 90:          Woodsend/Perry  9
##                     Breeder  n

#dt[filter, select, group]
pg[, .N, Breeder]

##                     Breeder  N
##  1:           Texas Outlaws  4
##  2:          Junior Juanich  6
##  3:       Jerry Allensworth  4
##  4:             Alias-Alias 11
##  5:            Greg Glazier  4
##  6:           Dal-Tex R P C  3
##  7:           N C Syndicate  6
##  8:        Baldwin & Tilson  7
##  9:                  Redtex 12
## 10:        Terry Montgomery  2
## 11:          Woodsend/Perry  9
## 12:          Crestview Loft  4
## 13:        Goshentown Lofts  4
## 14:            Flyhome Loft  2
## 15:         Skip's Janssens  5
## 16:         Bud & Orie Loft  2
## 17:         Milner-Mckinsey  8
## 18:    Shawnie & Lenny Loft  4
## 19:      Nanez Family Lofts  4
## 20:                  Jb & D 13
## 21:      Silver Dollar Loft  2
## 22:            Protege Loft  4
## 23:              Mike Belus  2
## 24:    Sierra Ranch Classic  6
## 25:              A P C Loft 12
## 26:        Churn Creek Loft  3
## 27: Sandstrom Brothers Loft  7
## 28:         Flying D Loft 2  3
## 29:      Clear Springs Loft  3
## 30:          Equalizer Loft  4
## 31:            Stenman Loft 10
## 32:    Crowley's Ridge Loft  2
## 33:            Dave Harrett  6
## 34:             Dave Dudley  3
## 35:       Mc Laughlin Lofts  4
## 36:       Little Reata Loft  6
## 37:           Emerson/Krass  5
## 38:         Non Pareil Loft  4
## 39:             Andy Skwiat 10
## 40:          American Lofts  4
## 41:             Alonso Loft  3
## 42:           Captain Chuck 10
## 43:      Shang N Dennis Yoh  5
## 44:    J & M Partridge Loft  4
## 45:              B D P Loft  3
## 46:              T C R Loft  5
## 47:             Family Loft 12
## 48:   Charlie's Little Loft  3
## 49:             Oscar/Ralph  1
## 50:         The Bailey Team  7
## 51:               Kwan Loft  4
## 52:       Ganus Family Loft  6
## 53:                 4-Birds  4
## 54:        Greek Connection  5
## 55:               Turk Loft  2
## 56:            Leyba's Loft  3
## 57:           Lonestar Loft  4
## 58:      Bynum Family Lofts  5
## 59:     The Brand Syndicate  5
## 60:             Kokomo Loft  2
## 61:           Loizzi/Sikora  5
## 62:              Rayce Loft  4
## 63:             Bionic Loft  2
## 64:            Iv Aces Loft  2
## 65:      Fisher Family Loft  5
## 66:     Credeur Family Loft  2
## 67:              Kiko Arana  4
## 68:             Rick Barker  5
## 69:            Debbie Ganus  6
## 70:                P J Loft  3
## 71:               King City  3
## 72:          Centmeyer Loft  2
## 73:       Hi-Cal Connection  5
## 74:           Stelling Loft  4
## 75:               Tongol 11  3
## 76:               Dunn Loft  1
## 77:          7-11 Syndicate  2
## 78:        Drama Queen Loft  3
## 79:         Hutchins/Milner  5
## 80:           Miller Loft 2  1
## 81:              Mr. Dovely  1
## 82:      Cypress Hills Farm  2
## 83:           Jerry Johnson  2
## 84:                 Twin200  2
## 85:             Baysideboys  3
## 86:        Mayberry Classic  2
## 87:       Tony Family Lofts  3
## 88:                  Jerdee  6
## 89:              E & E Loft  3
## 90:         Braden/Olivieri  2
##                     Breeder  N

pg[Color == "BBWF", .(Sex, Speed), .(Breeder)][, .N, .(Breeder)][order(-N)]

##                     Breeder N
##  1:              Mike Belus 2
##  2:             Andy Skwiat 2
##  3:       Ganus Family Loft 2
##  4:          American Lofts 2
##  5:             Family Loft 2
##  6:      Shang N Dennis Yoh 2
##  7:       Little Reata Loft 2
##  8:            Greg Glazier 1
##  9:         Milner-Mckinsey 1
## 10:      Nanez Family Lofts 1
## 11:    Sierra Ranch Classic 1
## 12:         Skip's Janssens 1
## 13:              A P C Loft 1
## 14:       Jerry Allensworth 1
## 15:            Leyba's Loft 1
## 16:             Alias-Alias 1
## 17:              Kiko Arana 1
## 18:              Rayce Loft 1
## 19:           Emerson/Krass 1
## 20:       Hi-Cal Connection 1
## 21:          Centmeyer Loft 1
## 22:          7-11 Syndicate 1
## 23:               Tongol 11 1
## 24:             Alonso Loft 1
## 25:            Debbie Ganus 1
## 26:                  Jerdee 1
## 27:         Hutchins/Milner 1
## 28: Sandstrom Brothers Loft 1
## 29:         Braden/Olivieri 1
##                     Breeder N

Nested Option:

library(dplyr)
library(data.table)

arrange(
  summarize(
    group_by(
      filter(mtcars, carb > 1),cyl), Avg_mpg = mean(mpg)), desc(Avg_mpg)
  )

## # A tibble: 3 × 2
##     cyl Avg_mpg
##   <dbl>   <dbl>
## 1     4    25.9
## 2     6    19.7
## 3     8    15.1

Multiple Object Option

a <- filter(mtcars, carb > 1) 
b <- group_by(a, cyl) 
c <- summarise(b, Avg_mpg = mean(mpg)) 
d <- arrange(c, desc(Avg_mpg)) 
print(d)

## # A tibble: 3 × 2
##     cyl Avg_mpg
##   <dbl>   <dbl>
## 1     4    25.9
## 2     6    19.7
## 3     8    15.1

%>% Option:

library(magrittr) 
library(dplyr) 
mtcars %>% 
  filter(carb > 1) %>% 
  group_by(cyl) %>% 
  summarise(Avg_mpg = mean(mpg)) %>% 
  arrange(desc(Avg_mpg))

## # A tibble: 3 × 2
##     cyl Avg_mpg
##   <dbl>   <dbl>
## 1     4    25.9
## 2     6    19.7
## 3     8    15.1

. is assumed first

mtcars %>% 
  filter(carb > 1) %>% 
  lm(mpg ~ cyl + hp, data = .) %>% 
  summary()

## 
## Call:
## lm(formula = mpg ~ cyl + hp, data = .)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4.6163 -1.4162 -0.1506  1.6181  5.2021 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 35.67647    2.28382  15.621 2.16e-13 ***
## cyl         -2.22014    0.52619  -4.219 0.000353 ***
## hp          -0.01414    0.01323  -1.069 0.296633    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.689 on 22 degrees of freedom
## Multiple R-squared:  0.7601, Adjusted R-squared:  0.7383 
## F-statistic: 34.85 on 2 and 22 DF,  p-value: 1.516e-07

data.table piping

set.seed(123)
dt <- data.table(a = sample(letters, 1e5, replace = TRUE),
                 b = abs(rnorm(1e5)))

dt

##         a         b
##      1: o 0.2854386
##      2: s 0.3810986
##      3: n 1.1975067
##      4: c 1.0806172
##      5: j 1.0456392
##     ---            
##  99996: y 1.8387322
##  99997: k 1.0059273
##  99998: n 0.5727827
##  99999: r 0.3695162
## 100000: f 0.4031301

one line

# adding columns in dt uses :=, $ will still work as well but not for piping
dt[, x := sqrt(b)][, y := b^2][, z := paste0(a , b)]

dt

##         a         b         x         y                  z
##      1: o 0.2854386 0.5342646 0.0814752 o0.285438610498582
##      2: s 0.3810986 0.6173319 0.1452362  s0.38109864857572
##      3: n 1.1975067 1.0943065 1.4340223  n1.19750670084312
##      4: c 1.0806172 1.0395274 1.1677335  c1.08061720585168
##      5: j 1.0456392 1.0225650 1.0933613  j1.04563918817768
##     ---                                                   
##  99996: y 1.8387322 1.3559986 3.3809363  y1.83873224053769
##  99997: k 1.0059273 1.0029593 1.0118897   k1.0059272754005
##  99998: n 0.5727827 0.7568241 0.3280800 n0.572782712020763
##  99999: r 0.3695162 0.6078785 0.1365422 r0.369516237085063
## 100000: f 0.4031301 0.6349253 0.1625139  f0.40313009749158

multiple lines - ewwwww

# multiline dt piping is hard to read
dt[, x := sqrt(b)][
  , y := b^2][
    , z := paste0(a , b)]

dt

##         a         b         x         y                  z
##      1: o 0.2854386 0.5342646 0.0814752 o0.285438610498582
##      2: s 0.3810986 0.6173319 0.1452362  s0.38109864857572
##      3: n 1.1975067 1.0943065 1.4340223  n1.19750670084312
##      4: c 1.0806172 1.0395274 1.1677335  c1.08061720585168
##      5: j 1.0456392 1.0225650 1.0933613  j1.04563918817768
##     ---                                                   
##  99996: y 1.8387322 1.3559986 3.3809363  y1.83873224053769
##  99997: k 1.0059273 1.0029593 1.0118897   k1.0059272754005
##  99998: n 0.5727827 0.7568241 0.3280800 n0.572782712020763
##  99999: r 0.3695162 0.6078785 0.1365422 r0.369516237085063
## 100000: f 0.4031301 0.6349253 0.1625139  f0.40313009749158

using magrittr pipes with data.table :-)

# Best of both worlds!
dt[, x := sqrt(b)] %>%
  .[, y := b^2] %>%
  .[, z := paste0(a , b)]

dt

##         a         b         x         y                  z
##      1: o 0.2854386 0.5342646 0.0814752 o0.285438610498582
##      2: s 0.3810986 0.6173319 0.1452362  s0.38109864857572
##      3: n 1.1975067 1.0943065 1.4340223  n1.19750670084312
##      4: c 1.0806172 1.0395274 1.1677335  c1.08061720585168
##      5: j 1.0456392 1.0225650 1.0933613  j1.04563918817768
##     ---                                                   
##  99996: y 1.8387322 1.3559986 3.3809363  y1.83873224053769
##  99997: k 1.0059273 1.0029593 1.0118897   k1.0059272754005
##  99998: n 0.5727827 0.7568241 0.3280800 n0.572782712020763
##  99999: r 0.3695162 0.6078785 0.1365422 r0.369516237085063
## 100000: f 0.4031301 0.6349253 0.1625139  f0.40313009749158

Introduction to R

José Bayoán Santiago Calderón and Aaron Schroeder

2019-06-06

Introduction to R markdown

Setting up RStudio

Setting up your environment (Housekeeping)

Atomic data types

Logical

Integer

Numeric

Complex

Character

Collections

Arrays

Matrices

Arrays

Lists

Structs

“The 3 Ways of R” or Becoming a Better Code Googler (GoogleR?)

The R Language - Multiple Approaches

Used many different ways, including

Like Javascript

Can be also be used as PP, OOP, or FP

‘Frameworks’ are created to make it easier

And many more! BUT, A Single Framework can Lock You In!

PROBLEM! People are only learning how to do Javascript the “React” or “Vue.js” or … way - VERY LIMITING - ESPECIALLY FOR USING OTHER PEOPLE’S CODE!

R ‘Frameworks’

While not exactly “Frameworks”, R has the same issue in that different coding “approaches” have emerged

Need to be Bi/Tri Lingual!

If you are going to be a great R Code Googler (which you want to be!) you need to be able to at least read and understand what is going on in the code samples you find, regardless of the approach used!

Today’s Objectives

So, for today our objectives are to

base

readr (need to assign to new data.frame)

data.table

more advanced data.table

A 4th Way!

A data frame, the basic tabular representation of data in R

Create Sample Data Frame

Subset Rows

base R

dplyr

data.table

Subset Columns

base R

dplyr

data.table

Subset Rows & Columns

base R

dplyr

data.table

renaming column base

renaming column dplyr

renaming column data.table

Nested Option:

Multiple Object Option

%>% Option:

. is assumed first

data.table piping

one line

multiple lines - ewwwww

using magrittr pipes with data.table :-)