问题
Let's say I have a data frame with 10 numeric variables V1-V10 (columns) and multiple rows (cases).
What I would like R to do is: For each case, give me the number of occurrences of a certain value in a set of variables.
For example the number of occurrences of the numeric value 99 in that single row for V2, V3, V6, which obviously has a minimum of 0 (none of the three have the value 99) and a maximum of 3 (all of the three have the value 99).
I am really looking for an equivalent to the SPSS function COUNT: "COUNT creates a numeric variable that, for each case, counts the occurrences of the same value (or list of values) across a list of variables."
I thought about table() and library plyr's count(), but I cannot really figure it out. Vectorized computation preferred. Thanks a lot!
回答1:
Try
apply(df,MARGIN=1,table)
Where df is your data.frame. This will return a list of the same length of the amount of rows in your data.frame. Each item of the list corresponds to a row of the data.frame (in the same order), and it is a table where the content is the number of occurrences and the names are the corresponding values.
For instance:
df=data.frame(V1=c(10,20,10,20),V2=c(20,30,20,30),V3=c(20,10,20,10))
#create a data.frame containing some data
df #show the data.frame
V1 V2 V3
1 10 20 20
2 20 30 10
3 10 20 20
4 20 30 10
apply(df,MARGIN=1,table) #apply the function table on each row (MARGIN=1)
[[1]]
10 20
1 2
[[2]]
10 20 30
1 1 1
[[3]]
10 20
1 2
[[4]]
10 20 30
1 1 1
#desired result
回答2:
I think that there ought to be a simpler way to do this, but the best way that I can think of to get a table of counts is to loop (implicitly using sapply) over the unique values in the dataframe.
#Some example data
df <- data.frame(a=c(1,1,2,2,3,9),b=c(1,2,3,2,3,1))
df
# a b
#1 1 1
#2 1 2
#3 2 3
#4 2 2
#5 3 3
#6 9 1
levels=unique(do.call(c,df)) #all unique values in df
out <- sapply(levels,function(x)rowSums(df==x)) #count occurrences of x in each row
colnames(out) <- levels
out
# 1 2 3 9
#[1,] 2 0 0 0
#[2,] 1 1 0 0
#[3,] 0 1 1 0
#[4,] 0 2 0 0
#[5,] 0 0 2 0
#[6,] 1 0 0 1
回答3:
Here is another straightforward solution that comes closest to what the COUNT command in SPSS does — creating a new variable that, for each case (i.e., row) counts the occurrences of a given value or list of values across a list of variables.
#Let df be a data frame with four variables (V1-V4)
df <- data.frame(V1=c(1,1,2,1,NA),V2=c(1,NA,2,2,NA),
V3=c(1,2,2,1,NA), V4=c(NA, NA, 1,2, NA))
#This is how to compute a new variable counting occurences of value "1" in V1-V4.
df$count.1 <- apply(df, 1, function(x) length(which(x==1)))
The updated data frame contains the new variable count.1 exactly as the SPSS COUNT command would do.
> df
V1 V2 V3 V4 count.1
1 1 1 1 NA 3
2 1 NA 2 NA 1
3 2 2 2 1 1
4 1 2 1 2 2
5 NA NA NA NA 0
You can do the same to count how many time the value "2" occurs per row in V1-V4. Note that you need to select the columns (variables) in df to which the function is applied.
df$count.2 <- apply(df[1:4], 1, function(x) length(which(x==2)))
You can also apply a similar logic to count the number of missing values in V1-V4.
df$count.na <- apply(df[1:4], 1, function(x) sum(is.na(x)))
The final result should be exactly what you wanted:
> df
V1 V2 V3 V4 count.1 count.2 count.na
1 1 1 1 NA 3 0 1
2 1 NA 2 NA 1 1 2
3 2 2 2 1 1 3 0
4 1 2 1 2 2 2 0
5 NA NA NA NA 0 0 4
This solution can easily be generalized to a range of values. Suppose we want to count how many times a value of 1 or 2 occurs in V1-V4 per row:
df$count.1or2 <- apply(df[1:4], 1, function(x) sum(x %in% c(1,2)))
回答4:
If you need to count any particular word/letter in the row.
#Let df be a data frame with four variables (V1-V4)
df <- data.frame(V1=c(1,1,2,1,L),V2=c(1,L,2,2,L),
V3=c(1,2,2,1,L), V4=c(L, L, 1,2, L))
For counting number of L in each row just use
#This is how to compute a new variable counting occurences of "L" in V1-V4.
df$count.L <- apply(df, 1, function(x) length(which(x=="L")))
The result will appear like this
> df
V1 V2 V3 V4 count.L
1 1 1 1 L 1
2 1 L 2 L 2
3 2 2 2 1 0
4 1 2 1 2 0
回答5:
In my effort to find something similar to Count from SPSS in R is as follows:
`df <- data.frame(a=c(1,1,NA,2,3,9),b=c(1,2,3,2,NA,1))` #Dummy data with NAs
`df %>%
dplyr::mutate(count = rowSums( #this allows calculate sum across rows
dplyr::select(., #Slicing on .
dplyr::one_of( #within select use one_of by clarifying which columns your want
c('a','b'))), na.rm = T)) #once the columns are specified, that's all you need, na.rm is cherry on top
That's how the output looks like
> df
a b count
1 1 1 2
2 1 2 3
3 NA 3 3
4 2 2 4
5 3 NA 3
6 9 1 10
Hope it helps :-)
来源：https://stackoverflow.com/questions/24015557/count-occurrences-of-value-in-a-set-of-variables-in-r-per-row