Recode string into a binary matrix

Question

I would like to recode some strings into binary mode for codifing them into matrices, in R. Let's say I have the following strings in a data frame:

strings  code
ABC       1
BCA       2
CAB       1

After extracting them I have the following strings:

"ABC" "BCA" "CAB"

And I would like to implement the next transformation:

A = 100
B = 010
C = 001

So that transforming "ABC" into the next matrix

100
010
001

And so, "BCA" into:

010
001
100

And "CAB" into:

001
100
010

And, after this transformation, getting a vector for "ABC" that is:

100010001

which represents ABC, an so on.

Basically, what I want to do is defining an algorithm with binary dictionary for letters characters so that it converts each letter into a binary sequence using R.

I've tried some aproaches but could not get a nice function...

Any help?

zx8754 · Accepted Answer · 2017-11-02 11:42:55Z

2

Make a named vector, then split and match.

dictionary <- setNames(c("100", "010", "001"), LETTERS[1:3])

x <- c("ABC", "BCA", "CAB")

sapply(strsplit(x, ""), function(i)
  paste(dictionary[ i ], collapse = ""))

# [1] "100010001" "010001100" "001100010"

Or instead of creating custom dictionary, why not use real binary?

sapply(x, function(i)
  paste(rawToBits(charToRaw(i)), collapse = ""))

# ABC 
# "010000000000010000010000000001000101000000000100" 
# BCA 
# "000100000000010001010000000001000100000000000100" 
# CAB 
# "010100000000010001000000000001000001000000000100"

edited Nov 2, 2017 at 11:42

answered Nov 2, 2017 at 11:33

zx8754

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akrun · Accepted Answer · 2017-11-02 11:31:08Z

1

We could use a gsub. Create a key/value list ('lst'), Loop through the sequence of 'lst', use gsub to match the names of the 'lst', replace with the 'value' and assing it back to 'strings' column

lst <- list(A = '100', B = '010', C = '001')
for(i in seq_along(lst)) df1$strings <- gsub(names(lst)[[i]], lst[[i]], df1$strings)
df1
#    strings code
#1 100010001    1
#2 010001100    2
#3 001100010    1

answered Nov 2, 2017 at 11:31

akrun

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