Counting the number of elements with the values of x in a vector

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闹比i
闹比i 2020-11-22 02:44

I have a vector of numbers:

numbers <- c(4,23,4,23,5,43,54,56,657,67,67,435,
         453,435,324,34,456,56,567,65,34,435)

How can I hav

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  • 2020-11-22 03:20

    You can just use table():

    > a <- table(numbers)
    > a
    numbers
      4   5  23  34  43  54  56  65  67 324 435 453 456 567 657 
      2   1   2   2   1   1   2   1   2   1   3   1   1   1   1 
    

    Then you can subset it:

    > a[names(a)==435]
    435 
      3
    

    Or convert it into a data.frame if you're more comfortable working with that:

    > as.data.frame(table(numbers))
       numbers Freq
    1        4    2
    2        5    1
    3       23    2
    4       34    2
    ...
    
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  • 2020-11-22 03:20

    You can change the number to whatever you wish in following line

    length(which(numbers == 4))
    
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  • 2020-11-22 03:22

    There is also count(numbers) from plyr package. Much more convenient than table in my opinion.

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  • 2020-11-22 03:22

    One more way i find convenient is:

    numbers <- c(4,23,4,23,5,43,54,56,657,67,67,435,453,435,324,34,456,56,567,65,34,435)
    (s<-summary (as.factor(numbers)))
    

    This converts the dataset to factor, and then summary() gives us the control totals (counts of the unique values).

    Output is:

    4   5  23  34  43  54  56  65  67 324 435 453 456 567 657 
    2   1   2   2   1   1   2   1   2   1   3   1   1   1   1 
    

    This can be stored as dataframe if preferred.

    as.data.frame(cbind(Number = names(s),Freq = s), stringsAsFactors=F, row.names = 1:length(s))

    here row.names has been used to rename row names. without using row.names, column names in s are used as row names in new dataframe

    Output is:

         Number Freq
    1       4    2
    2       5    1
    3      23    2
    4      34    2
    5      43    1
    6      54    1
    7      56    2
    8      65    1
    9      67    2
    10    324    1
    11    435    3
    12    453    1
    13    456    1
    14    567    1
    15    657    1
    
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  • 2020-11-22 03:25

    One option could be to use vec_count() function from the vctrs library:

    vec_count(numbers)
    
       key count
    1  435     3
    2   67     2
    3    4     2
    4   34     2
    5   56     2
    6   23     2
    7  456     1
    8   43     1
    9  453     1
    10   5     1
    11 657     1
    12 324     1
    13  54     1
    14 567     1
    15  65     1
    

    The default ordering puts the most frequent values at top. If looking for sorting according keys (a table()-like output):

    vec_count(numbers, sort = "key")
    
       key count
    1    4     2
    2    5     1
    3   23     2
    4   34     2
    5   43     1
    6   54     1
    7   56     2
    8   65     1
    9   67     2
    10 324     1
    11 435     3
    12 453     1
    13 456     1
    14 567     1
    15 657     1
    
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  • 2020-11-22 03:26
    numbers <- c(4,23,4,23,5,43,54,56,657,67,67,435 453,435,324,34,456,56,567,65,34,435)
    
    > length(grep(435, numbers))
    [1] 3
    
    
    > length(which(435 == numbers))
    [1] 3
    
    
    > require(plyr)
    > df = count(numbers)
    > df[df$x == 435, ] 
         x freq
    11 435    3
    
    
    > sum(435 == numbers)
    [1] 3
    
    
    > sum(grepl(435, numbers))
    [1] 3
    
    
    > sum(435 == numbers)
    [1] 3
    
    
    > tabulate(numbers)[435]
    [1] 3
    
    
    > table(numbers)['435']
    435 
      3 
    
    
    > length(subset(numbers, numbers=='435')) 
    [1] 3
    
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