This may seem like a very basic R question, but I'd appreciate an answer. I have a data frame in the form of:
col1 col2
a g
a h
a g
b i
b g
b h
c i
I want to transform it into counts, so the outcome would be like this. I've tried using table () function, but seem to only be able to get the count for one column.
a b c
g 2 1 0
h 1 1 0
i 0 1 1
How do I do it in R?
Use the length() function to count the number of elements returned by the which() function, as which function returns the elements that are repeated more than once. The length() function in R Language is used to get or set the length of a vector (list) or other objects.
There are multiple ways to get the count of the frequency of all unique values in an R vector. To count the number of times each element or value is present in a vector use either table(), tabulate(), count() from plyr package, or aggregate() function.
R base provides duplicated() and unique() functions to remove duplicates in an R DataFrame (data. frame), By using these two functions we can delete duplicate rows by considering all columns, single column, or selected columns.
I'm not really sure what you used, but table
works fine for me!
Here's a minimal reproducible example:
df <- structure(list(V1 = c("a", "a", "a", "b", "b", "b", "c"),
V2 = c("g", "h", "g", "i", "g", "h", "i")),
.Names = c("V1", "V2"), class = "data.frame",
row.names = c(NA, -7L))
table(df)
# V2
# V1 g h i
# a 2 1 0
# b 1 1 1
# c 0 0 1
Notes:
table(df[c(2, 1)])
(or table(df$V2, df$V1)
) to swap the rows and columns.as.data.frame.matrix(table(df))
to get a data.frame
as your output. (as.data.frame
will create a long data.frame
, not one in the same output format you desire).Using f
from @Ananda you can use dcast
library(reshape2)
> dcast(f, V1~V2)
Using V2 as value column: use value.var to override.
Aggregation function missing: defaulting to length
V1 g h i
1 a 2 1 0
2 b 1 1 1
3 c 0 0 1
However, I'm writing this only in case you may need something more than just table
(which for this case it's the simplest correct answer) in the future, like:
set.seed(1)
f$var <- rnorm(7)
> f
V1 V2 var
1 a g -0.6264538
2 a h 0.1836433
3 a g -0.8356286
4 b i 1.5952808
5 b g 0.3295078
6 b h -0.8204684
7 c i 0.4874291
> dcast(f, V1~V2, value.var="var", fun.aggregate=sum)
V1 g h i
1 a -1.4620824 0.1836433 0.0000000
2 b 0.3295078 -0.8204684 1.5952808
3 c 0.0000000 0.0000000 0.4874291
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