How can find the total number of males and females based on a number of another column ?

[Alisher]

#

[Alisher]

I want to know how to sum total number of males and females. Thank you in advance!

[williaml]

Hi, first of all, please provide reproducible examples, not screenshots.

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

Secondly, it would be good if you shared your code. What have you tried?

Thirdly, have a look at dplyr::count().

Count the observations in each group — count

[pieterjanvc]

Hi,

Welcome to the RStudio community!

I agree with @williaml that you should have a look at how to build a reprex to better share your data. But given this is your first time posting here, and the problem is relatively easy, I was able to quickly create some fake data and show a way to solve it

library(dplyr)

set.seed(1)
myData = data.frame(
  Gender = sample(c("Male", "Female"), 5, replace = T),
  Number = sample(1:20, 5)
)
myData
#>   Gender Number
#> 1   Male     11
#> 2 Female     14
#> 3   Male     18
#> 4   Male      1
#> 5 Female      5

myData %>% group_by(Gender) %>% 
  summarise(total = sum(Number), .groups = "drop")
#> # A tibble: 2 x 2
#>   Gender total
#>   <chr>  <int>
#> 1 Female    19
#> 2 Male      30

^{Created on 2021-11-22 by the reprex package (v2.0.1)}

Hope this helps,
PJ

[Alisher]

Thank you a lot! This helped a lot and I also found another way of solving this problem:

sum(Datt[Datt$Gender == "Male", "Number"])
sum(Datt[Datt$Gender == "Female", "Number"])

[pieterjanvc]

Hi,

You're welcome.
Yes the solution that you supplied in the last comment is how you can do this in base R, so not using the Tidyverse.

If you like to learn more about the Tidyverse (dplyr package in this case):

Tidyverse packages

PJ