HOXO-M - anonymous data analyst group in Japan

What is inconvenience of for loops in R? It is that results you get will be gone away. So we have created a package to store the results automatically. To do it, you only need to cast one line spell magic_for(). In this text, we tell you about how to use the magic.

1. Overview

for() is one of the most popular functions in R. As you know, it is used to create loops.

For example, let’s calculate squared values for 1 to 3.

for (i in 1:3) {
  squared <- i ^ 2
  print(squared)
}
#> [1] 1
#> [1] 4
#> [1] 9

It is very easy.

However, it becomes too much hassle to change such codes to store printed results. You must prepare some containers with correct length for storing results and change print() to assignment statements.

result <- vector("numeric", 3) # prepare a container
for (i in 1:3) {
  squared <- i ^ 2
  result[i] <- squared         # change to assignment
}
result
#> [1] 1 4 9

Moreover, you may want to store results as a data.frame with iteration numbers.

result <- data.frame(matrix(nrow = 3, ncol = 2))
colnames(result) <- c("i", "squared")
for (i in 1:3) {
  squared <- i ^ 2
  result[i, 1] <- i
  result[i, 2] <- squared
}
result
#>   i squared
#> 1 1       1
#> 2 2       4
#> 3 3       9

What a bother!

In such or more troublesome situations like that you have to store many variables, codes will grow more complex.

The magicfor package makes to resolve the problem being kept readability.

You just add two lines before for loops. First, load the library. Second, call magic_for(). Notice that the main for loop is kept intact.

library(magicfor)  # Load library
magic_for(print)   # Call magic_for()

for (i in 1:3) {
  squared <- i ^ 2
  print(squared)
}
#> The loop is magicalized with print().
#> [1] 1
#> [1] 4
#> [1] 9

magic_for() takes a function name, and reconstructs for() to remember values passed to the specified function in for loops. We call it magicalization. Once you call magic_for(), as you just exectute for() as usual, the result will be stored in memory automatically.

Here, let’s use magic_result_as_vector() to access the stored values.

magic_result_as_vector()  # Get the result
#> [1] 1 4 9

This is one of the functions to obtain results from magicalized for loops, and means to take out the results as a vector.

Even if the number of observed variables increases, you can do it the same way.

magic_for(silent = TRUE)

for (i in 1:3) {
  squared <- i ^ 2
  cubed <- i ^ 3
  put(squared, cubed)
}

magic_result_as_dataframe()
#>   i squared cubed
#> 1 1       1     1
#> 2 2       4     8
#> 3 3       9    27

put() is the default function to store values in magicalized for loops. It allows to take any number of variables and can display them.

2. Installation

You can install the magicfor package from CRAN.

install.packages("magicfor")

The source code for magicfor package is available on GitHub at

https://github.com/hoxo-m/magicfor.

3. Details

The magicfor package provides the functions as follows:

magic_for(): Magicalize for.
magic_free(): Cancel magicalization.
Get results:
- magic_result(): as a list.
- magic_result_as_vetor(): as a vector.
- magic_result_as_dataframe(): as a data.frame.
put(): Display values.

In the following, we assume that the library is loaded to use the functions.

library(magicfor)

3.1 Basics

The main function magic_for() magicalize for loops. Magicalize means to change the behavior of for() to store values outputted via target functions.

magic_for()

for (i in 1:3) {
  squared <- i ^ 2
  put(squared)
}
#> The loop is magicalized with put().
#> squared: 1
#> squared: 4
#> squared: 9

The default target function is put(). It displays input values, for example:

x <- 1
put(x)
#> x: 1

You can take out stored values using magic_result_**() when for loops have finished.

magic_result_as_vector()
#> [1] 1 4 9

3.2 `magic_for()`

magic_for() has several options.

Specify the first argument func, you can change target functions.

magic_for(cat)

for (i in 1:3) {
  squared <- i ^ 2
  cat(squared, " ")
}
#> The loop is magicalized with cat().
#> 1  4  9

If progress = TRUE, show progress bar.

magic_for(progress = TRUE)

for (i in 1:3) {
  squared <- i ^ 2
  put(squared)
}

#> |=================================================================| 100%

If you set test a number, the iteration is limited to that number of times.

magic_for(test = 2)

for (i in 1:100) {
  squared <- i ^ 2
  put(squared)
}
#> The loop is magicalized with put().
#> squared: 1
#> squared: 4

If silent = TRUE, target function will be not executed but only the values will be stored.

If temp = TRUE, the effect of magicalization will be lost after once execution of for loop.

magic_for(temp = TRUE)
is_magicalized()
#> [1] TRUE

for (i in 1:3) {
  squared <- i ^ 2
  put(squared)
}
#> The loop is temporary magicalized with put().
#> squared: 1
#> squared: 4
#> squared: 9

is_magicalized()
#> [1] FALSE

3.3 `magic_free()`

You can use magic_free() to cancel magicalization.

magic_for()
is_magicalized()
#> [1] TRUE

magic_free()
is_magicalized()
#> [1] FALSE

The function also clear the stored values.

magic_for(silent = TRUE)

for (i in 1:3) {
  squared <- i ^ 2
  put(squared)
}

magic_result_as_vector()
#> [1] 1 4 9

magic_free()
magic_result_as_vector()
#> NULL

3.4 `magic_result_**()`

You can use magic_result_**() to obtain results from magicalized for loops.

magic_for(silent = TRUE)

for (i in 1:3) {
  squared <- i ^ 2
  put(squared)
}

magic_result() returns results as a list.

magic_result()
#> $squared
#> $squared[[1]]
#> [1] 1
#> 
#> $squared[[2]]
#> [1] 4
#> 
#> $squared[[3]]
#> [1] 9

magic_result_as_vector() returns results as a vector.

magic_result_as_vector()
#> [1] 1 4 9

magic_result_as_dataframe() returns results as a data.frame.

magic_result_as_dataframe()
#>   i squared
#> 1 1       1
#> 2 2       4
#> 3 3       9

3.5 `put()`

put() displays input values with high flexibility.

x <- 2
y <- 3
put(x)
#> x: 2
put(x, y)
#> x: 2, y: 3
put(x, x ^ 2, x ^ 3)
#> x: 2, x^2: 4, x^3: 8
put(x, squared = x ^ 2, cubed = x ^ 3)
#> x: 2, squared: 4, cubed: 8

It is very useful for magicfor.

magic_for()

for (i in 1:3) {
  put(x = i, squared = i ^ 2, cubed = i ^ 3)
}
#> The loop is magicalized with put().
#> x: 1, squared: 1, cubed: 1
#> x: 2, squared: 4, cubed: 8
#> x: 3, squared: 9, cubed: 27

magic_result_as_dataframe(F)
#>   x squared cubed
#> 1 1       1     1
#> 2 2       4     8
#> 3 3       9    27

4. Miscellaneous

Whenever you put just variables in magicalized for loops, their values will be stored regardless of target functions.

magic_for()

for (i in 1:3) {
  squared <- i ^ 2
  squared
}
#> The loop is magicalized with put().

magic_result_as_vector()
#> [1] 1 4 9

When you write trarget functions inside of if statements without else, NA will be inserted to represent missing.

magic_for()

for (i in 1:3) {
  squared <- i ^ 2
  if(i == 3) put(squared)
}
#> The loop is magicalized with put().
#> squared: 9

magic_result_as_vector()
#> [1] NA NA  9

Target functions work only top level lines or inside of if statements in magicalized for loops. For example, it does not work inside nested for loops.

magic_for()

for (i in 1:2) {
  for (j in 1:2) {
    put(i, j, i * j)
  }
}
#> The loop is magicalized with put().
#> i: 1, j: 1, i*j: 1
#> i: 1, j: 2, i*j: 2
#> i: 2, j: 1, i*j: 2
#> i: 2, j: 2, i*j: 4

magic_result_as_vector()
#> list()

5. Bug Reports

https://github.com/hoxo-m/magicfor/issues

HOXO-M - anonymous data analyst group in Japan -

2016/12/24

New R Package magicfor - Magic Functions to Obtain Results from for Loops in R

1. Overview

2. Installation

3. Details

3.1 Basics

3.2 `magic_for()`

3.3 `magic_free()`

3.4 `magic_result_**()`

3.5 `put()`

4. Miscellaneous

5. Bug Reports

2016/12/24

New R Package magicfor - Magic Functions to Obtain Results from for Loops in R

1. Overview

2. Installation

3. Details

3.1 Basics

3.2 magic_for()

3.3 magic_free()

3.4 magic_result_**()

3.5 put()

4. Miscellaneous

5. Bug Reports

3.2 `magic_for()`

3.3 `magic_free()`

3.4 `magic_result_**()`

3.5 `put()`