Reputation: 63
I am trying to do a frequency count by 2 variables. This is my data, in dataframe "api":
Name Grade
1 John Smith C
2 John Smith B
3 John Smith C
4 Jane Doe A
5 Jane Doe C
6 Lisa Brown B
I want this:
Name Grade Freq
1 John Smith C 2
2 John Smith B 1
3 John Smith C 2
4 Jane Doe A 1
5 Jane Doe C 1
6 Lisa Brown B 1
This is my code:
api_count<-count(api, c("Name", "Grade")
And I get this error message:
Error: Problem with `mutate()` input `..1`.
x Input `..1` can't be recycled to size 28328.
i Input `..1` is `c("Name", "Grade")`.
i Input `..1` must be size 28328 or 1, not 2.
Upvotes: 0
Views: 3575
Reputation: 887183
We can use add_count
library(dplyr)
df %>%
add_count(Name, Grade)
# Name Grade n
#1 John Smith C 2
#2 John Smith B 1
#3 John Smith C 2
#4 Jane Doe A 1
#5 Jane Doe C 1
#6 Lisa Brown B 1
df <- structure(list(Name = c("John Smith", "John Smith", "John Smith",
"Jane Doe", "Jane Doe", "Lisa Brown"), Grade = c("C", "B", "C",
"A", "C", "B")), class = "data.frame", row.names = c(NA, -6L))
Upvotes: 0
Reputation: 160447
I think @Duck's is the most direct approach (and preferred; and with this data, half the computation time), but here's an alternative in case it makes more sense: count
and then join
back with the original data:
df %>%
count(Name, Grade) %>%
left_join(df, ., by = c("Name", "Grade"))
# Name Grade n
# 1 John Smith C 2
# 2 John Smith B 1
# 3 John Smith C 2
# 4 Jane Doe A 1
# 5 Jane Doe C 1
# 6 Lisa Brown B 1
Upvotes: 0
Reputation: 124
I think your code is mostly correct, only some minor syntax issues:
api <- data.frame(Name = c(rep("John Smith",3), rep("Jane Doe", 2), "Lisa Brown"), Grade = c("C", "B", "C", "A", "C","B")))
api
Name Grade
1 John Smith C
2 John Smith B
3 John Smith C
4 Jane Doe A
5 Jane Doe C
6 Lisa Brown B
count(api, c("Name", "Grade"))
Name Grade freq
1 Jane Doe A 1
2 Jane Doe C 1
3 John Smith B 1
4 John Smith C 2
5 Lisa Brown B 1
Upvotes: 1
Reputation: 39595
I would suggest this tidyverse
approach:
library(tidyverse)
#Code
df %>% group_by(Name,Grade) %>% mutate(N=n())
Output:
# A tibble: 6 x 3
# Groups: Name, Grade [5]
Name Grade N
<chr> <chr> <int>
1 John Smith C 2
2 John Smith B 1
3 John Smith C 2
4 Jane Doe A 1
5 Jane Doe C 1
6 Lisa Brown B 1
Some data used:
#Data
df <- structure(list(Name = c("John Smith", "John Smith", "John Smith",
"Jane Doe", "Jane Doe", "Lisa Brown"), Grade = c("C", "B", "C",
"A", "C", "B")), class = "data.frame", row.names = c(NA, -6L))
Upvotes: 1