Hello!
I am very new to R. How do I go about calculating the proportion of a response for a certain subset of a data set. For example, of those who are college graduates, how many are stem? So far I have something like this...
df = %>%
filter(education = "college_grad") %>%
filter(major = "stem") %>%
and I am not sure what to do after this.
Help will be appreciated,
xbechtel
See the gtsummary package
Scroll down
suppressPackageStartupMessages({library(dplyr)
library(gtsummary)})
trial %>% select(trt, age, grade) %>% tbl_summary()
|
Characteristic |
N = 2001 |
|---|---|
|
Chemotherapy Treatment |
|
|
Drug A |
98 (49%) |
|
Drug B |
102 (51%) |
|
Age |
47 (38, 57) |
|
Unknown |
11 |
|
Grade |
|
|
I |
68 (34%) |
|
II |
68 (34%) |
|
III |
64 (32%) |
|
1 Statistics presented: n (%); Median (IQR) |
Created on 2020-09-29 by the reprex package (v0.3.0.9001)
Hello!
Is there a way to do this just using the tidyverse package? Essential I was asked to use inline rcode to produce this proportion when describing the data set?
Begin with the usual analysis in term of f(x) = y
x is the data at hand, y is the subset desired, and f is the function, or composite function, to turn the one into the other.
The choice of f will depend on whether the count or a proportion is required.
The OP code is off to a false start by filtering down df to only college graduates in stem majors. This precludes any proportionality test. If only a count is needed all that's required is
suppressPackageStartupMessages({library(dplyr)})
# prefer dat or my_df over df, which is a built-in function name
# this avoids situation where `df` can be read as a closure
mtcars %>%
filter(cyl == 4 & carb == 2) %>%
summarise_all(~ sum(., trim = .2))
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> 1 155.6 24.2 699.8 522.2 25.05 14.588 113.82 5.2 4.2 26.2 12.2
Created on 2020-09-29 by the reprex package (v0.3.0.9001)
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