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https://github.com/oobianom/quickcode

An R package made out of mine and Brice's scrapbook of much needed functions.
https://github.com/oobianom/quickcode

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An R package made out of mine and Brice's scrapbook of much needed functions.

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README 

        





# 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 



### Author R scholar profile: https://scholar.rpkg.net/aut/obinna+obianom 



```

# Install in R

install.packages("quickcode")

```



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



## Featured function 1

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

![](https://quickcode.obi.obianom.com/quickcode.png)



## Featured function 2

### Create a super variable with unique capability and wide scope

![](https://quickcode.obi.obianom.com/quickcode2.png)



## ✅ Some Quick R Examples



***



![](https://quickcode.obi.obianom.com/bionic_txt2.png)



***



```

# Use the nullish coalescing operator using  "or()" or "%or%"

ex.V1 <- 5

ex.V2 <- NA

ex.V3 <- NULL

ex.V4 <- ""

alternative <- 500



# Give an alternative result if the test is NULL NA or empty



or(ex.V1,alternative) # result will give 5 because ex.V1 is not NULL NA or empty



ex.V1 %or% alternative # result will give 5 because ex.V1 is not NULL NA or empty



ex.V2 %or% alternative # result will give 500 because ex.V2 is NA



ex.V3 %or% alternative # result will give 500 because ex.V3 is NULL



ex.V4 %or% alternative # result will give 500 because ex.V4 is empty



# Further chaining



ex.V2 %or% ex.V1 %or% alternative # result will be 5 because ex.V2 is NA but ex.V1 is 5



ex.V2 %or% ex.V3 %or% alternative # result will be 500 because ex.V2 is NA and ex.V3 is NULL



```



***



```

#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)



```



[![](https://quickcode.obi.obianom.com/writeit2.svg)](https://rpkg.net/package/quickcode)



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



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