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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

R dependency: https://depends.rpkg.net/package/quickcode

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

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

70+ great R functions to add to your scripts!

Add one-line code in your R script to clear environment, clear console, set working directory and load files

Create a super variable with unique capability and wide scope

✅ 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")
add_key(ver1)

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)
head(mtdf3) # view
mtdf3.round(1) # round to 1 decimal places
head(mtdf3) # view
mtdf3.signif(2) # round to 2 significant digits
head(mtdf3) # view

# 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"
  ),
  load = c(
  "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)

And many more useful functions including list_shuffle, in.range …

By Obinna Obi Obianom, Creator of www.rpkg.net and www.shinyappstore.com

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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