Make bar graph that counts levels of different columns

Question

Hi I have a table with 1 category 'Pilar' with different topics eg Budget Schedule, scope, risk and ressources. each rows mentions green, yellow or red. I am completely stuck as I want a bar graph grouped per pillar so 1 seperate from 2 and 3 for each of the topics counting the times green occured, yellow and red. table

See worst drawn paint image, I hope this gives in idea of what i need. paint drawing of what I need

I tried working with aggerate but my brain couldn't figure it out. Next trying to a long format but as there are no numbers involved I think this cannot work either.

Thanks in advance as my brain is dead :D

This is what I tried:

projects_sum <-as.data.frame(projects_sum) projects_sum <- gather(projects_sum,measure,Budget:Ressources)

Error in ensym(): ! Can't convert to a symbol. Run rlang::last_trace() to see where the error occurred.

It's easier to help you if you include a simple [reproducible example](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) with sample input and desired output that can be used to test and verify possible solutions. Please [do not post code or data in images](https://meta.stackoverflow.com/q/285551/2372064) — MrFlick, Apr 21 '23 at 13:47
Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking. — Community, Apr 21 '23 at 21:39

score 0 · Accepted Answer · answered Apr 21 '23 at 15:25

My made up data:

structure(list(pillar = c("1", "1", "1", "1", "1", "1", "1", 
"1", "1", "1", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", 
"3", "3", "3", "3", "3", "3", "3", "3", "3", "3"), budget = c("red", 
"red", "red", "red", "red", "red", "green", "green", "red", "green", 
"red", "yellow", "red", "red", "yellow", "yellow", "red", "red", 
"yellow", "red", "green", "red", "red", "red", "red", "yellow", 
"red", "red", "red", "red"), schedule = c("red", "green", "red", 
"yellow", "red", "yellow", "yellow", "red", "red", "yellow", 
"yellow", "green", "red", "green", "red", "red", "yellow", "yellow", 
"red", "yellow", "green", "yellow", "red", "green", "yellow", 
"yellow", "green", "green", "green", "red"), scope = c("green", 
"red", "green", "red", "yellow", "green", "green", "green", "red", 
"red", "red", "yellow", "green", "red", "red", "red", "yellow", 
"yellow", "red", "red", "green", "red", "red", "green", "red", 
"red", "red", "green", "green", "red"), risk = c("yellow", "red", 
"green", "yellow", "yellow", "yellow", "green", "green", "green", 
"green", "green", "green", "red", "yellow", "yellow", "yellow", 
"green", "green", "red", "green", "red", "yellow", "yellow", 
"green", "yellow", "yellow", "red", "yellow", "green", "yellow"
), resources = c("red", "green", "green", "green", "yellow", 
"green", "green", "green", "red", "green", "green", "green", 
"green", "yellow", "green", "green", "yellow", "green", "green", 
"green", "red", "green", "green", "red", "green", "green", "red", 
"green", "yellow", "green")), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -30L))

This tidyverse approach first pivots to a longer data frame structure, then counts the occurrences of each color by pillar and variable. The complete step fills in empty combinations, to allow for empty columns in the plot.

library(tidyverse)


df %>%
  pivot_longer(-pillar) %>%
  count(pillar, name, value) %>%
  complete(pillar, name, value, fill = list(n = 0)) %>%
  ggplot(aes(name, n, fill = factor(value, levels = c('green','yellow','red')))) +
  geom_col(position = position_dodge2(0.7, preserve = 'single'), width = 0.6, ) +
  facet_wrap(~ pillar,
             labeller = label_both) +
  scale_fill_manual(values = c('green','yellow','red')) +
  labs(x = '', y = 'Count') +
  theme(legend.position = 'none')

^{Created on 2023-04-21 with reprex v2.0.2}

Make bar graph that counts levels of different columns

1 Answers1