How to count TRUE values in a logical vector

Question

In R  what is the most efficient idiomatic way to count the number of TRUE values in a logical vector  I can think of two ways   z  lt - sample c TRUE  FALSE   1000  rep   TRUE  sum z     1  498  table z   TRUE     TRUE     498    Which do you prefer  Is there anything even better

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Another option is to use summary function  It gives a summary of the Ts  Fs and NAs    gt  summary hival     Mode   FALSE    TRUE    NA s  logical    4367      53    2076   gt

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I ve just had a particular problem where I had to count the number of true statements from a logical vector and this worked best for me     length grep TRUE   gene rep matrix i 1 6   gt  1     gt  5   So This takes a subset of the gene rep matrix object  and applies a logical test  returning a logical vector  This vector is put as an argument to grep  which returns the locations of any TRUE entries  Length then calculates how many entries grep finds  thus giving the number of TRUE entries

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There s also a package called bit that is specifically designed for fast boolean operations  It s especially useful if you have large vectors or need to do many boolean operations   z  lt - sample c TRUE  FALSE   1e8  rep   TRUE   system time     sum z    0 170s     system time     bit  sum bit z    0 021s   10x improvement in speed

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which is good alternative  especially when you operate on matrices  check  which and notice the arr ind argument   But I suggest that you stick with sum  because of na rm argument that can handle NA s in logical vector  For instance     create dummy variable set seed 100  x  lt - round runif 100  0  1   x  lt - x    1   create NA s x seq 1  length x   7    lt - NA   If you type in sum x  you ll get NA as a result  but if you pass na rm   TRUE in sum function  you ll get the result that you want    gt  sum x   1  NA  gt  sum x  na rm TRUE   1  43   Is your question strictly theoretical  or you have some practical problem concerning logical vectors

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There are some problems when logical vector contains NA values  See for example   z  lt - c TRUE  FALSE  NA  sum z    gives you NA table z   TRUE     gives you 1 length z z    TRUE     f3lix answer  gives you 2  because NA indexing returns values    So I think the safest is to use na rm   TRUE   sum z  na rm   TRUE    best way to count TRUE values    which gives 1   I think that table solution is less efficient  look at the code of table function    Also  you should be careful with the  table  solution  in case there are no TRUE values in the logical vector  Suppose z  lt - c NA  FALSE  NA  or simply z  lt - c FALSE  FALSE   then table z   TRUE   gives you NA for both cases

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Another way is    gt  length z z  TRUE    1  498   While sum z   is nice and short  for me length z z  TRUE   is more self explaining  Though  I think with a simple task like this it does not really make a difference     If it is a large vector  you probably should go with the fastest solution  which is sum z   length z z  TRUE   is about 10x slower and table z  TRUE  is about 200x slower than sum z    Summing up  sum z  is the fastest to type and to execute

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Another option which hasn t been mentioned is to use which   length which z     Just to actually provide some context on the  which is faster question   it s always easiest just to test yourself   I made the vector much larger for comparison   z  lt - sample c TRUE FALSE  1000000 rep TRUE  system time sum z      user  system elapsed     0 03    0 00    0 03 system time length z z  TRUE       user  system elapsed     0 75    0 07    0 83  system time length which z       user  system elapsed     1 34    0 28    1 64  system time table z   TRUE       user  system elapsed    10 62    0 52   11 19    So clearly using sum is the best approach in this case   You may also want to check for NA values as Marek suggested   Just to add a note regarding NA values and the which function    gt  which c T  F  NA  NULL  T  F    1  1 4  gt  which  c T  F  NA  NULL  T  F    1  2 5   Note that which only checks for logical TRUE  so it essentially ignores non-logical values

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I ve been doing something similar a few weeks ago  Here s a possible solution  it s written from scratch  so it s kind of beta-release or something like that  I ll try to improve it by removing loops from code     The main idea is to write a function that will take 2  or 3  arguments  First one is a data frame which holds the data gathered from questionnaire  and the second one is a numeric vector with correct answers  this is only applicable for single choice questionnaire   Alternatively  you can add third argument that will return numeric vector with final score  or data frame with embedded score   fscore  lt - function x  sol  output    numeric         if  ncol x     length sol             stop  Number of items differs from length of correct answers          else           inc  lt - matrix ncol ncol x   nrow nrow x           for  i in 1 ncol x                 inc  i   lt - x  i     sol i                    if  output     numeric                 res  lt - rowSums inc            else if  output     data frame                 res  lt - data frame x  result   rowSums inc             else               stop  Type not supported                        return res      I ll try to do this in a more elegant manner with some  ply function  Notice that I didn t put na rm argument    Will do that    create dummy data frame - values from 1 to 5 set seed 100  d  lt - as data frame matrix round runif 200 1 5    10     create solution vector sol  lt - round runif 20  1  5     Now apply a function    gt  fscore d  sol    1  6 4 2 4 4 3 3 6 2 6   If you pass data frame argument  it will return modified data frame  I ll try to fix this one    Hope it helps

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