Create a variable that supersedes other variables and has various functionalities
Arguments
- variable
variable name for super variable
- value
value of the variable
- lock
lock variable to change
- editn
number of times the super variable may be set to a new value using .set().
- Set to NULL to allow unlimited value change
- Set to 0 to prevent editing the super variable
Note
What you should know about the functionality:
This function ensures that a variable is created and may not easily be altered.
It helps preserve the original variable by providing only limited access to the variable.
Creation of this super variable automatically attached some key functions to it,
such that the user is able to call the function like .set(), .rm().
Super variable value may be set from any scope using the .set() function, which
means that it is granted global variable features without being present within the
global environment of the current section.
The variable name of the super variable may
be overwritten in the local environment, but this would not alter the super variable.
It means that once the local variable is removed, the super variable remains available
for use.
Use cases:
- Preserve originality of variable within an R session. Avoid inadvertent deletion.
- Widely accessible from any scope e.g functions, lapply, loops, local environment etc
- Restricted mutability of variable using set function e.g varname.set()
- Variable with easy function calls by attaching '.'
- Variable with un-mutable class when changing its value
- Variable with restricted number of times it can be changed
Examples
# Task: create a super variable to
# store dataset that should not be altered
newSuperVar(mtdf, value = austres) # create a super variable
head(mtdf) # view it
#> [1] 13067.3 13130.5 13198.4 13254.2 13303.7 13353.9
mtdf.class # view the store class of the variable, it cannot be changed
#> [1] "ts"
# it means that when the super variable is edited, the new value MUST have the same class "ts"
# create and lock super variable by default
# extra security to prevent changing
newSuperVar(mtdf3, value = beaver1, lock = TRUE)
head(mtdf3) # view
#> day time temp activ
#> 1 346 840 36.33 0
#> 2 346 850 36.34 0
#> 3 346 900 36.35 0
#> 4 346 910 36.42 0
#> 5 346 920 36.55 0
#> 6 346 930 36.69 0
mtdf3.round(1) # round to 1 decimal places
head(mtdf3) # view
#> day time temp activ
#> 1 346 840 36.3 0
#> 2 346 850 36.3 0
#> 3 346 900 36.4 0
#> 4 346 910 36.4 0
#> 5 346 920 36.5 0
#> 6 346 930 36.7 0
mtdf3.signif(2) # round to 2 significant digits
head(mtdf3) # view
#> day time temp activ
#> 1 350 840 36 0
#> 2 350 850 36 0
#> 3 350 900 36 0
#> 4 350 910 36 0
#> 5 350 920 36 0
#> 6 350 930 37 0
# 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
#> [1] 989796930 920810920 699060670 501683940 651211721
# 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
#> [1] 122456571 877662456 242745245 268460318 57187700 483436664 879106300
#> [8] 185263354 729098265 57820740 317418108 991231294 163001476 431725693
#> [15] 55356427 890909582 511030826 586039434 764088705 265678445
for (pu in 1:8) {
print(edtvec) # view output within loop
edtvec.set(number(pu)) # set to new numbers within for loop
}
#> [1] 122456571 877662456 242745245 268460318 57187700 483436664 879106300
#> [8] 185263354 729098265 57820740 317418108 991231294 163001476 431725693
#> [15] 55356427 890909582 511030826 586039434 764088705 265678445
#> [1] 922044610
#> [1] 542750453 684796673
#> [1] 985971426 21730612 547744612
#> [1] 113177268 618165892 311652864 847668387
#> [1] 720177668 45533169 35399543 403824668 402159537
#> [1] 967187903 446602062 492371572 849516133 972632371 339960427
#> [1] 207482094 91025226 449917866 392054235 225694087 63416129 658798843
lc <- lapply(1:8, function(pu) {
print(edtvec) # view output within loop
edtvec.set(number(pu)) # set to new numbers within lapply loop
})
#> [1] 465200626 937148200 251387636 962507853 989139661 238239587 205783011
#> [8] 486979911
#> [1] 433634519
#> [1] 23538982 866274810
#> [1] 428422168 801913291 617613581
#> [1] 180622873 162176338 134378123 851868852
#> [1] 919463090 184563029 69547758 691353684 938521527
#> [1] 561368817 33680892 62541986 944709481 861278716 255574511
#> [1] 166432913 287912323 909114178 487720854 562149077 563715948 401457498
# 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
})
#> [1] 198
#> [1] 198
#> [1] 198
#> [1] 198
#> [1] 198
#> [1] 198
#> [1] 198
#> [1] 198
# Task: create and search data.frame
# create a new super variable with value as mtcars
# search if it contains the numeric value 21
newSuperVar(lon2, value = mtcars) # declares lon2
lon2 # view content of lon2
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
#> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
#> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
#> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
#> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
#> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
#> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
#> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
#> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
#> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
#> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
#> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
#> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
#> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
#> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
#> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
#> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
#> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
#> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
#> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
#> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
#> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
#> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
#> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
#> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
#> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
#> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
#> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
#> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
#> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2
lon2.contains("21.0") # WRONG - since df.col is not specific,
#> [1] FALSE
# only the first column is search for the character "21.0"
lon2.contains("21.0", df.col = "mpg") # WRONG - searches mpg column
#> [1] FALSE
# for the character "21.0"
lon2.contains(21.0, df.col = "mpg") # CORRECT - search mpg column for the
#> [1] TRUE
# numeric value 21.0
# remove lon2 as a super variable
exists("lon2") # before removal
#> [1] TRUE
lon2.rm()
exists("lon2") # after removal
#> [1] FALSE
# Task: create and search vector
# create a new super variable with value as 10 random numbers
# search if it contains the numeric value 72
newSuperVar(lon3, value = number(10, seed = 12)) # declares lon3
lon3 # view content of lon3
#> [1] 297914714 827278583 727320750 767861829 98239010 612880475 542204285
#> [8] 64057465 891652716 711531738
lon3.contains(72) # should give TRUE or false if the vector contains the value 45
#> [1] TRUE
lon3.contains(72, fixed = TRUE) # should give TRUE or false if the vector contains the value 45
#> [1] TRUE
# remove lon3 as a super variable
lon3.rm()
#Task: create a super variable that can only be edited 3 times
newSuperVar(man1, value = number(5), editn = 3)
man1 # view value
#> [1] 937871792 420263352 935543960 20459592 813607802
man1.set(number(10)) # change value first time
man1 # view value
#> [1] 570216551 572387564 832886781 578315298 380012494 977679002 404691028
#> [8] 563284928 655541844 620977293
man1.set(number(2)) # change value second time
man1 # view value
#> [1] 734810736 224065701
man1.set(number(1)) # change value third time
man1 # view value
#> [1] 248943356
man1.set(number(5)) # change value forth time,
# should not change because max change times exceeded
man1 # view value
#> [1] 248943356