# NOT functions, R tricks and a compilation of some simple quick plus often used codes to improve your R scripts

## Official website: https://quickcode.obi.obianom.com

### Package stats: https://rpkg.net/package/quickcode

``````# Install in R
install.packages("quickcode")``````

# 70+ great R functions to add to your scripts!

## ✅ Some Quick R Examples

``````#load libraries and print names along with versions

quickcode::libraryAll(
dplyr,
r2resize,
ggplot2
)

``````

``````#simple conversion between boolean types
#input type is "vector"
baba <- c(TRUE,"y","n","YES","yes",FALSE,"f","F","T","t")
as.boolean(baba,1) # return vector as Yes/No
as.boolean(baba,2) # return vector as TRUE/FALSE
as.boolean(baba,3) # return vector as 1/0
``````

``````#apply the yesNoBool to convert between boolean
#input type is "data.frame"
usedata <- data.frame(ID = number(32))
usedata #view the dataset

usedata\$yess = rep(c("yes","n","no","YES","No","NO","yES","Y"),4) #create a new column
usedata #view the modified dataset

#set all yess field as standardize boolean
yesNoBool(usedata,yess, type="bin") #set all as binary 1/0
yesNoBool(usedata,yess, type="log") #set all as logical TRUE/FALSE
``````

``````#initialize one or more variables

print(g) # Error: object 'g' not found

init(g,h,i,o)
print(g) # g = NULL
print(h) # h = NULL

init(r,y,u,b,value = 5)
print(r) # r = 5
print(b) # b = 5
print(z) # Error: object 'z' not found
``````

``````#add keys to a vector content for use in downstream processes

ver1 <- c("Test 1","Test 2","Test 3")

for(i in ver1){
message(sprintf("%s is the key for this %s", i\$key, i\$value))
}
``````

``````# Introducing the super variable
# store dataset that should not be altered
newSuperVar(mtdf, value = austres) # create a super variable
head(mtdf) # view it
mtdf.class # view the store class of the variable, it cannot be changed
# it means that when the super variable is edited, the new value MUST have the same class

# create and lock super variable by default
# extra security to prevent changing
newSuperVar(mtdf3, value = beaver1, lock = TRUE)
mtdf3.round(1) # round to 1 decimal places
mtdf3.signif(2) # round to 2 significant digits

# Task: create a new super variable to store numbers
# edit the numbers from various scopes
newSuperVar(edtvec, value = number(5))
edtvec # view content of the vector

# edtvec.set(letters) #ERROR: Cannot set to value with different class than initial value

edtvec.set(number(20)) # set to new numbers
edtvec # view output

for (pu in 1:8) {
print(edtvec) # view output within loop
edtvec.set(number(pu)) # set to new numbers within for loop
}

lc <- lapply(1:8, function(pu) {
print(edtvec) # view output within loop
edtvec.set(number(pu)) # set to new numbers within lapply loop
})

# see that the above changed the super variable easily.
# local variable will not be altered by the loop
# example
bim <- 198
lc <- lapply(1:8, function(j) {
print(bim)
bim <- j # will not alter the value of bim in next round
})
``````

``````
#check if the entry is not integer

not.integer(45) #returns TRUE
not.integer(45.) #returns TRUE
not.integer(45L) #returns FALSE

not.null(45L) #returns TRUE
not.null(h<-NULL) #returns FALSE

``````

``````
#clear R environment, set directory and load data
#note: the code below also automatically loads the quickcode library so that all other functions within package can be used easily

quickcode::refresh()
quickcode::clean()

#or combine with setwd and source and load

quickcode::clean(
setwd = "/wd/",
source = c(
"file.R",
"file2.R"
),
"data.RData",
"data2.RData"
)
)

``````

``````
#shorthand for not in vector

p1 <- 4
p2 <- c(1:10)

p1 %nin% p2

``````

``````
#add to a vector in one code

p1 <- c(6,7,8)
p2 <- c(1,2,3)

vector_push(p1,p2)

print(p1)

``````

``````
#add to a data frame in one code

p1 <- data.frame(ID=1:10,ID2=1:10)
p2 <- data.frame(ID=11:20,ID2=21:30)

data_push(p1,p2,"rows")

print(p1)
``````

``````
#remove from a vector in one code

p1 <- c(6,7,8,1,2,3)

vector_pop(p1)

print(p1)

``````

``````

#remove from a data frame in one code

p1 <- data.frame(ID=1:10,ID2=1:10,CD=11:20,BD=21:30)

data_pop(p1) #remove last row

print(p1)

data_pop(p1,5) #remove last 5 rows

print(p1)
``````

``````

#remove columns from a data frame in one code

p1 <- data.frame(ID=1:10,ID2=1:10,ID4=1:10,CD=11:20,BD=21:30)

data_pop(p1,which = "cols") #remove last column

print(p1)

data_pop(p1,2,which = "cols") #remove last 2 columns

print(p1)

data_pop(p1,1,which = "cols") #remove last 1 column and vectorise

print(p1)
``````