I am having quite a tricky problem, which i just cannot seem to solve.
I have a large dataset (23277 rows, 151 columns). Each column has values from 0:100 (inclusive) representing probabilities assigned for events in the world.
As part of calculating the score for each individual, I need to count the occurrences of each of the values in the dataset.
I first tried apply, but I need to ignore NA's, and subset, so when i tried the following:
apply(ans.samp, 1, sum(ans.samp[ans==0]), na.rm=TRUE)
I got the error message: sum(ans.samp[ans == 0])' is not a function, character or symbol
I repeated this process with sapply, vapply, tapply and do.call to no avail.
Giving up on a vectorised solution, I wrote the following for loop.
RespCount <- function (x) { for (i in (1:nrow(x)))
{ res <- vector(mode="numeric", length=nrow(x))
ans.tmp <- x[i,]
res[i] <- length(ans.tmp[ans.tmp==0])
print(res)
}
return(res)
}
However, after i got this working, it returns only the total sum of O in the sample.
I would appreciate some help with this, as I am under some time pressure, and I would like to be able to solve these kinds of problems in R in the future.
Sample data included for reproducibility:
structure(list(X = 1:6, X100 = c(70L, NA, 80L, 0L, 40L, NA),
X10 = c(30L, NA, NA, NA, NA, NA), X1 = c(50L, NA, NA, NA,
NA, NA), X11 = c(50L, NA, NA, NA, NA, NA), X12 = c(30L, NA,
NA, NA, NA, NA), X13 = c(50L, NA, NA, NA, NA, NA), X14 = c(70L,
NA, NA, NA, NA, NA), X15 = c(60L, NA, NA, NA, NA, NA), X158 = c(30L,
NA, NA, NA, NA, NA), X159 = c(50L, NA, NA, NA, NA, NA), X160 = c(80L,
NA, NA, NA, NA, NA), X16 = c(50L, NA, NA, NA, NA, NA), X161 = c(40L,
NA, NA, NA, NA, NA), X162 = c(100L, NA, NA, NA, NA, NA),
X163 = c(50L, NA, NA, NA, NA, NA), X164 = c(0L, NA, NA, NA,
NA, NA), X165 = c(0L, NA, NA, NA, NA, NA), X166 = c(20L,
NA, NA, NA, NA, NA), X167 = c(0L, NA, NA, NA, NA, NA), X168 = c(30L,
NA, NA, NA, NA, NA), X169 = c(100L, NA, NA, NA, NA, NA),
X170 = c(30L, NA, NA, NA, NA, NA), X17 = c(40L, NA, NA, NA,
NA, NA), X171 = c(50L, NA, NA, NA, NA, NA), X172 = c(20L,
NA, NA, NA, NA, NA), X173 = c(30L, NA, NA, NA, NA, NA), X174 = c(20L,
NA, NA, NA, NA, NA), X175 = c(30L, NA, NA, NA, NA, NA), X176 = c(10L,
NA, NA, NA, NA, NA), X177 = c(70L, NA, NA, NA, NA, NA), X178 = c(40L,
NA, NA, NA, NA, NA), X179 = c(70L, NA, NA, NA, NA, NA), X180 = c(0L,
NA, NA, NA, NA, NA), X18 = c(30L, NA, NA, NA, NA, NA), X181 = c(100L,
NA, NA, NA, NA, NA), X182 = c(100L, NA, NA, NA, NA, NA),
X183 = c(20L, NA, NA, NA, NA, NA), X184 = c(80L, NA, NA,
NA, NA, NA), X185 = c(90L, NA, NA, NA, NA, NA), X186 = c(0L,
NA, NA, NA, NA, NA), X187 = c(10L, NA, NA, NA, NA, NA), X188 = c(100L,
NA, NA, NA, NA, NA), X189 = c(100L, NA, NA, NA, NA, NA),
X190 = c(0L, NA, NA, NA, NA, NA), X19 = c(100L, NA, NA, NA,
NA, NA), X191 = c(0L, NA, NA, NA, NA, NA), X192 = c(90L,
NA, NA, NA, NA, NA), X193 = c(50L, NA, NA, NA, NA, NA), X194 = c(100L,
NA, NA, NA, NA, NA), X195 = c(10L, NA, NA, NA, NA, NA), X196 = c(100L,
NA, NA, NA, NA, NA), X197 = c(20L, NA, NA, NA, NA, NA), X198 = c(40L,
NA, NA, NA, NA, NA), X199 = c(20L, NA, NA, NA, NA, NA), X200 = c(0L,
NA, NA, NA, NA, NA), X20 = c(0L, NA, NA, NA, NA, NA), X201 = c(0L,
NA, NA, NA, NA, NA), X202 = c(20L, NA, NA, NA, NA, NA), X203 = c(20L,
NA, NA, NA, NA, NA), X204 = c(80L, NA, NA, NA, NA, NA), X205 = c(0L,
NA, NA, NA, NA, NA), X206 = c(80L, NA, NA, NA, NA, NA), X207 = c(0L,
NA, NA, NA, NA, NA), X2 = c(10L, NA, NA, NA, NA, NA), X21 = c(0L,
NA, NA, NA, NA, NA), X22 = c(100L, NA, NA, NA, NA, NA), X23 = c(50L,
NA, NA, NA, NA, NA), X24 = c(50L, NA, NA, NA, NA, NA), X25 = c(70L,
NA, NA, NA, NA, NA), X26 = c(60L, NA, NA, NA, NA, NA), X27 = c(40L,
NA, NA, NA, NA, NA), X28 = c(20L, NA, NA, NA, NA, NA), X29 = c(0L,
NA, NA, NA, NA, NA), X30 = c(90L, NA, NA, NA, NA, NA), X3 = c(0L,
NA, NA, NA, NA, NA), X31 = c(50L, NA, NA, NA, NA, NA), X32 = c(50L,
NA, NA, NA, NA, NA), X33 = c(0L, NA, NA, NA, NA, NA), X34 = c(50L,
NA, NA, NA, NA, NA), X35 = c(90L, NA, NA, NA, NA, NA), X36 = c(50L,
NA, NA, NA, NA, NA), X37 = c(60L, NA, NA, NA, NA, NA), X38 = c(40L,
NA, NA, NA, NA, NA), X39 = c(50L, NA, NA, NA, NA, NA), X40 = c(0L,
NA, NA, NA, NA, NA), X4 = c(50L, NA, NA, NA, NA, NA), X41 = c(90L,
NA, NA, NA, NA, NA), X42 = c(80L, NA, NA, NA, NA, NA), X43 = c(50L,
NA, NA, NA, NA, NA), X44 = c(80L, NA, NA, NA, NA, NA), X45 = c(80L,
NA, NA, NA, NA, NA), X46 = c(0L, NA, NA, NA, NA, NA), X47 = c(80L,
NA, NA, NA, NA, NA), X48 = c(20L, NA, NA, NA, NA, NA), X49 = c(100L,
NA, NA, NA, NA, NA), X50 = c(0L, NA, NA, NA, NA, NA), X5 = c(0L,
NA, NA, NA, NA, NA), X51 = c(80L, 100L, 70L, 100L, 0L, 60L
), X52 = c(10L, 0L, 0L, 0L, 0L, 20L), X53 = c(40L, 40L, 70L,
20L, 90L, 50L), X54 = c(0L, 10L, 0L, 50L, 50L, 0L), X55 = c(20L,
80L, 90L, 80L, 30L, 0L), X56 = c(100L, 100L, 50L, 100L, 80L,
100L), X57 = c(60L, 0L, 100L, 70L, 100L, 80L), X58 = c(100L,
100L, 100L, 50L, 100L, 100L), X59 = c(80L, 50L, 80L, 0L,
30L, 50L), X60 = c(70L, 50L, 60L, 50L, 100L, 100L), X6 = c(100L,
NA, NA, NA, NA, NA), X61 = c(50L, 50L, 50L, 30L, 70L, 50L
), X62 = c(20L, 50L, 40L, 40L, 50L, 100L), X63 = c(50L, 0L,
100L, 10L, 50L, 100L), X64 = c(60L, 30L, 0L, 50L, 50L, 50L
), X65 = c(50L, 50L, 70L, 80L, 50L, 50L), X66 = c(70L, 40L,
10L, 90L, 60L, 50L), X67 = c(30L, 50L, 50L, 0L, 50L, 60L),
X68 = c(30L, 0L, 0L, 40L, 70L, 80L), X69 = c(30L, NA, 70L,
10L, 0L, 20L), X70 = c(80L, NA, 50L, 50L, 70L, 100L), X7 = c(100L,
NA, NA, NA, NA, NA), X71 = c(70L, NA, 50L, 100L, 100L, 100L
), X72 = c(60L, NA, 70L, 50L, 80L, 50L), X73 = c(80L, NA,
80L, 80L, 80L, NA), X74 = c(50L, NA, 50L, 0L, 50L, NA), X75 = c(30L,
NA, 70L, 10L, 80L, NA), X76 = c(70L, NA, 40L, 80L, 100L,
NA), X77 = c(80L, NA, 50L, 100L, 40L, NA), X78 = c(80L, NA,
0L, 0L, 0L, NA), X79 = c(80L, NA, 50L, 50L, 50L, NA), X80 = c(40L,
NA, 90L, 70L, 60L, NA), X8 = c(50L, NA, NA, NA, NA, NA),
X81 = c(70L, NA, 60L, 40L, 80L, NA), X82 = c(80L, NA, 100L,
60L, 60L, NA), X83 = c(30L, NA, 100L, 30L, 0L, NA), X84 = c(80L,
NA, 0L, 60L, 100L, NA), X85 = c(80L, NA, 50L, 40L, 30L, NA
), X86 = c(50L, NA, 90L, 50L, 50L, NA), X87 = c(80L, NA,
50L, 70L, 20L, NA), X88 = c(40L, NA, 70L, 30L, 90L, NA),
X89 = c(50L, NA, 50L, 80L, 80L, NA), X90 = c(90L, NA, 100L,
60L, 100L, NA), X91 = c(0L, NA, 0L, 0L, 0L, NA), X9 = c(100L,
NA, NA, NA, NA, NA), X92 = c(50L, NA, 70L, 90L, 80L, NA),
X93 = c(40L, NA, 50L, 50L, 50L, NA), X94 = c(40L, NA, 0L,
60L, 40L, NA), X95 = c(90L, NA, 100L, 40L, 50L, NA), X96 = c(50L,
NA, 50L, 50L, 50L, NA), X97 = c(60L, NA, 60L, 100L, 50L,
NA), X98 = c(40L, NA, 40L, 0L, 0L, NA), X99 = c(30L, NA,
0L, 50L, 70L, NA)), .Names = c("X", "X100", "X10", "X1",
"X11", "X12", "X13", "X14", "X15", "X158", "X159", "X160", "X16",
"X161", "X162", "X163", "X164", "X165", "X166", "X167", "X168",
"X169", "X170", "X17", "X171", "X172", "X173", "X174", "X175",
"X176", "X177", "X178", "X179", "X180", "X18", "X181", "X182",
"X183", "X184", "X185", "X186", "X187", "X188", "X189", "X190",
"X19", "X191", "X192", "X193", "X194", "X195", "X196", "X197",
"X198", "X199", "X200", "X20", "X201", "X202", "X203", "X204",
"X205", "X206", "X207", "X2", "X21", "X22", "X23", "X24", "X25",
"X26", "X27", "X28", "X29", "X30", "X3", "X31", "X32", "X33",
"X34", "X35", "X36", "X37", "X38", "X39", "X40", "X4", "X41",
"X42", "X43", "X44", "X45", "X46", "X47", "X48", "X49", "X50",
"X5", "X51", "X52", "X53", "X54", "X55", "X56", "X57", "X58",
"X59", "X60", "X6", "X61", "X62", "X63", "X64", "X65", "X66",
"X67", "X68", "X69", "X70", "X7", "X71", "X72", "X73", "X74",
"X75", "X76", "X77", "X78", "X79", "X80", "X8", "X81", "X82",
"X83", "X84", "X85", "X86", "X87", "X88", "X89", "X90", "X91",
"X9", "X92", "X93", "X94", "X95", "X96", "X97", "X98", "X99"), row.names = c(NA,
6L), class = "data.frame")
Any insight would be greatly appreciated.
From some attempts on the small dataset above, it appears that the number is being calculated for each row, but when i return the res object, it merely gives me the final value. How can I fix this?
To count the number of times a value occurs in a column of an R data frame, we can use table function for that particular column.
Method 2: Using sum() method in R The sum() method can be used to calculate the summation of the values appearing in the function argument. Here, we specify a logical expression as an argument of the sum() function which calculates the sum of values which are equivalent to the specified value.
In R, the easiest way to find the number of missing values per row is a two-step process. First, the is.na() function assesses all values in a data frame and returns TRUE if a value is missing. Then, the rowsSums() function counts the number of TRUE's (i.e., missing values) per row.
There're two ways to use the apply
family functions. Either you do
apply(mat, 1, sum, na.rm=TRUE)
if you want to apply the function sum()
to each row, passing additional parameters like na.rm=TRUE
. Or you can do
apply(mat, 1, foo)
where foo()
is a function of your own, defined externally, e.g.
foo <- function(x) sum(x==0, na.rm=TRUE)
Note that NA handling might also be dealt with a parameter of the function itself, with default value set to TRUE
, in the above definition, as in
foo2 <- function(x, no.na=TRUE) sum(x==0, na.rm=no.na)
and you can call it as apply(mat, 1, foo2, no.na=F)
although it doesn't really make sense with the sum()
function (unless you want to check if there're NA values, but in this case it's better to use is.na()
:-).
Finally, you can define your function directly inline as
apply(mat, 1, function(x) sum(x==0, na.rm=TRUE))
In your case, it gives me
> apply(mat, 1, function(x) sum(x==0, na.rm=TRUE))
1 2 3 4 5 6
22 4 9 8 7 2
which is equivalent to apply(ex, 1, foo)
.
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With