CODEWITHSUNDEEP
rggplot2graphing
Alyssa C
Alyssa C

Reputation: 51

Binary column sums into percentage stacked bar chart in ggplot

I have tried everything to convert the bar chart I made here from COUNT on the y axis to PERCENT OF TOTAL (N=142) on the y axis, but can't seem to figure it out. I would like the x-axis to be the columns "Spatial_Management", "Landing_ban", and "Bycatch_rentention", and the y-axis to be percentage of policies that have a 1 value for this column. And the fill to be "Strength". I think I need to make a very simple edit my data beforehand, I have tried this below but it's not working.

EDIT: sample dataframe: 

    df<- data.frame(policy=c("Policy A", "Policy B", "Policy C", "Policy D", 
                     "Policy E","Policy F" ),
            Spatial_Management= c(0,1,1,0, 0,1),
            Landing_ban= c(0,1,1,0, 0,1),
            Bycatch_Retention= c(0,1,1,0, 0,1),
            Strength=c("M", "V", "M", "P", "P", "M"),
            stringsAsFactors=FALSE)

My current figure code is: 

df %>% 
  pivot_longer(Spatial_management:Bycatch_Retention) 
  filter(value==1) %>%
  ggplot(aes(x=factor(name, level=level_order), fill = factor(Strength)) +
                       y = (..count..)/sum(..count..)) +
 geom_bar()+
 stat_bin(geom = "text",
       aes(label = paste(round((..count..)/sum(..count..)*100), "%")),
       vjust = 5) +
 scale_y_continuous(labels = percent)

I know this is very simple, but would appreciate any help!!!

Upvotes: 2

Views: 605

Answers (1)

dc37
dc37

Reputation: 16178

Here, you need to reshape your dataframe into a longer format and then to count for the number of values divided by the number of policies (here it is equal to the number of rows of you dataframe):

library(tidyr)
library(dplyr)
library(ggplot2)
df %>% pivot_longer(-c(policy, Strength), names_to = "var", values_to = "val") %>%
  group_by(Strength, var) %>%
  summarise(Val = sum(val)/ nrow(df)) %>%
  ggplot(aes(x = var, y = Val, fill = Strength))+
  geom_col()+
  scale_y_continuous(labels = percent)

enter image description here

Upvotes: 2

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