This is my data set summary:
trajectory context_face face
Min. : 1 Pass :404 Length:1204 Frown :230
1st Qu.: 76 Undecided:400 Class :character Scrunch : 62
Median :151 Allow :400 Mode :character Gasp : 87
Mean :151 Smile :394
3rd Qu.:226 Neutral :258
Max. :301 Pout : 25
Wide-opened eyes:148
I want to know the proportions (occurence) of specific faces (e.g., Frown, Scrunch) by each trajectory (Pass, Undecided, Allow). In other words, how many Frowns or Srunches were in each trajectory condition.
I tried function describeBy(df, df$trajectory) but it didn't work. Dataset is already in long form. I want to see something like this (values are random here):
Pass Undecided Allow
Frown 10 2 18
Scrunch 19 20 4
Gasp 23 18 14
Smile 19 11 6
Neutral
Pout
Wide-opened eyes
Which function should I use? Thank you very much. This is my first question I have no idea how to edit it, I hope you can still understand my point.
Here's a tidyverse approach
library(tidyverse)
df <- tibble(face = c('Frown','Scrunch','Gasp','Smile'),
Pass = c(10,19,23,19),
Undecided = c(2,20,18,11),
Allow = c(18,4,14,6))
df %>%
pivot_longer(cols = c(Pass, Undecided, Allow),
names_to = 'trajectory',
values_to = 'value') %>%
group_by(face, trajectory) %>%
summarize(occurence = sum(value)) %>%
ungroup() %>%
mutate(proportion = occurence/sum(occurence))
#> `summarise()` has grouped output by 'face'. You can override using the
#> `.groups` argument.
#> # A tibble: 12 × 4
#> face trajectory occurence proportion
#> <chr> <chr> <dbl> <dbl>
#> 1 Frown Allow 18 0.110
#> 2 Frown Pass 10 0.0610
#> 3 Frown Undecided 2 0.0122
#> 4 Gasp Allow 14 0.0854
#> 5 Gasp Pass 23 0.140
#> 6 Gasp Undecided 18 0.110
#> 7 Scrunch Allow 4 0.0244
#> 8 Scrunch Pass 19 0.116
#> 9 Scrunch Undecided 20 0.122
#> 10 Smile Allow 6 0.0366
#> 11 Smile Pass 19 0.116
#> 12 Smile Undecided 11 0.0671
Created on 2023-03-16 with reprex v2.0.2