# NOT functions, R tricks and a compilation of some miscellaneous codes to improve your R scripts ## Official website: https://quickcode.obi.obianom.com ; https://quickcode.rpkg.net ## NEW Function Documentation: https://quickcode.rpkg.net/reference/index2.html ### 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 ``` *** ![](https://quickcode.obi.obianom.com/trimfile.gif) ``` #Recommended to use "Addins" in RStudio #Function call: Remove Empty Lines from a File trim.file("path/to/your/file.txt") ``` *** ``` #Detect outliers in data by IQR and Zscore methods x <- c(1, 2, 3, 4, 100) detect_outlier(x, summary = TRUE) detect_outlier(z, method = "iqr", multiplier = 3) detect_outlier(y, method = "zscore", z_threshold = 2.5) ``` *** ``` #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

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