How to count by gender and unique id in R

Question

I'm trying to count the number of females, males and N/A in the column 'gender' in the data frame trips. However is is returning me just the number of rows instead.

library(dplyr)
count(trips, vars = "gender")
# A tibble: 1 × 2
#    vars      n
#   <chr>  <int>
#1 gender 286858


head(trips)

trip_id | start_time | stop_time | duration | bike_di | gender | birthyear
 1      | 10:00      | 11:00     |   3600   | BD-215  | Male   | 1960
 1      | 10:30      | 11:00     |   1800   | BD-715  | Female | 1960
 1      | 10:45      | 11:00     |    900   | BD-615  | Male   | 1960
 1      | 10:50      | 11:00     |    600   | BD-315  | Female | 1960

Please provide a reproducible example. Show what you have tried. http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example — Pierre Lapointe, Mar 26 '17 at 13:53
`vars` is not an argument in `count`. You need either `count(trips, gender)` or `count_(trips, vars = "gender")`. — Henrik, Mar 26 '17 at 14:59

score 1 · Answer 1 · edited Mar 26 '17 at 14:41

1

For the females type:

sum(trips$gender=='Female')

For the males type

sum(trips$gender=='male')

For the NA, is it only in the gender column or in the all columns? type:

colsums(is.na(trips))

and you will get number of NAs in each column.

Hopefully it helps.

edited Mar 26 '17 at 14:41

Pierre Lapointe

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answered Mar 26 '17 at 14:33

Rlearner

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score 0 · Accepted Answer · answered Mar 26 '17 at 14:51

Here's a dplyr solution. I added a line where gender is NA as you mentioned you also want to count them.

trips <- read.table(text="trip_id  start_time  stop_time  duration  bike_di  gender  birthyear
 1       10:00       11:00        3600    BD-215   Male    1960
 1       10:30       11:00        1800    BD-715   Female  1960
 1       10:45       11:00         900    BD-615   Male    1960
 1       10:45       11:00         900    BD-615   NA    1960
 1       10:50       11:00         600    BD-315   Female  1960",header=TRUE, stringsAsFactors=FALSE)

 trips %>%
 group_by(gender) %>%
 summarise(gender_count=n())

# A tibble: 3 x 2
  gender gender_count
   <chr>        <int>
1 Female            2
2   Male            2
3   <NA>            1

How to count by gender and unique id in R

2 Answers2