Have a data frame like this
other=data.frame(name=c("a","b","a","c","d"),result=c("Y","N","Y","Y","N"))
How can I use spread function in tidyr or other function to get the count of result Y or N as column header like this
name Y N
a 2 0
b 0 1
Thanks
These are a few ways of many to go about it:
1) With library dplyr
, you can simply group things and count into the format needed:
library(dplyr)
other %>% group_by(name) %>% summarise(N = sum(result == 'N'), Y = sum(result == 'Y'))
Source: local data frame [4 x 3]
name N Y
<fctr> <int> <int>
1 a 0 2
2 b 1 0
3 c 0 1
4 d 1 0
2) You can use a combination of table
and tidyr
spread as follows:
library(tidyr)
spread(as.data.frame(table(other)), result, Freq)
name N Y
1 a 0 2
2 b 1 0
3 c 0 1
4 d 1 0
3) You can use a combination of dplyr
and tidyr
to do as follows:
library(dplyr)
library(tidyr)
spread(count(other, name, result), result, n, fill = 0)
Source: local data frame [4 x 3]
Groups: name [4]
name N Y
<fctr> <dbl> <dbl>
1 a 0 2
2 b 1 0
3 c 0 1
4 d 1 0
Here is another option using dcast
from data.table
library(data.table)
dcast(setDT(other), name~result, length)
# name N Y
#1: a 0 2
#2: b 1 0
#3: c 0 1
#4: d 1 0
Although, table(other)
would be a compact option (from @mtoto's comments), for large datasets, it may be more efficient to use dcast
. Some benchmarks are given below
set.seed(24)
other1 <- data.frame(name = sample(letters, 1e6, replace=TRUE),
result = sample(c("Y", "N"), 1e6, replace=TRUE), stringsAsFactors=FALSE)
other2 <- copy(other1)
gopala1 <- function() other1 %>%
group_by(name) %>%
summarise(N = sum(result == 'N'), Y = sum(result == 'Y'))
gopala2 <- function() spread(as.data.frame(table(other1)), result, Freq)
gopala3 <- function() spread(count(other1, name, result), result, n, fill = 0)
akrun <- function() dcast(as.data.table(other2), name~result, length)
library(microbenchmark)
microbenchmark(gopala1(), gopala2(), gopala3(),
akrun(), unit='relative', times = 20L)
# expr min lq mean median uq max neval
# gopala1() 2.710561 2.331915 2.142183 2.325167 2.134399 1.513725 20
# gopala2() 2.859464 2.564126 2.531130 2.683804 2.720833 1.982760 20
# gopala3() 2.345062 2.076400 1.953136 2.027599 1.882079 1.947759 20
# akrun() 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 20
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