I have the data.frame bellow, called 'subdata.frame'. Its a data from a rent bike company. There are users called 'member' who paid a annual subscribe, and the casuals riders. Further, we have the three type of bikes. The 'n' counts the total of rides in a certain period.

So, i'm trying to create two donut charts to show the proportion of each type of bike used within the member and casual groups. I'm using the 'facet_grid' (~member_casual) function. But first, its necessary to create new columns for the percentage and cumulative sums.

subdata.frame <- data.frame(subdata) %>%
                  group_by(member_casual) %>%
                    count(rideable_type) %>%
                      mutate(prop = n/sum(n)) %>%
                        mutate(ymax = cumsum(prop))

Resulting in the next table:

Using the geom_rect function, 'ymax' will set the top of each rectangle.

So, i assign the 'ymin', to set the bottom of each rectangle:

subdata.frame$ymin <- c(0, head(subdata.frame$ymax, n=-1))

So, i run the ggplot function:

ggplot(subdata.frame, aes(ymax=ymax, ymin=ymin, xmax=4, xmin=3, fill=rideable_type))  
  geom_rect()  
  scale_fill_brewer(palette=4)  
  facet_grid(~member_casual)  
  coord_polar(theta="y")  
  xlim(c(2, 4))  
  theme_void() 

Finnaly, i have the plot bellow. Note that the member donut chart is incomplete: plot error

CodePudding user response：

The issue is that using subdata.frame$ymin <- c(0, head(subdata.frame$ymax, n=-1)) to compute the ymin you did not take the grouping by member type into account.

First, to reproduce your issue:

library(ggplot2)

subdata.frame$ymin <- c(0, head(subdata.frame$ymax, n=-1))

ggplot(subdata.frame, aes(ymax=ymax, ymin=ymin, xmax=4, xmin=3, fill=rideable_type))  
  geom_rect()  
  scale_fill_brewer(palette=4)  
  facet_grid(~member_casual)  
  coord_polar(theta="y")  
  xlim(c(2, 4))  
  theme_void() 

To fix that you could use dplyr::lag as already suggested by @RuiBarradas and to group your data by member_casual when doing so:

library(dplyr)

subdata.frame <- subdata.frame %>%
  group_by(member_casual) %>%
  mutate(ymin = lag(ymax, default = 0))

ggplot(subdata.frame, aes(ymax=ymax, ymin=ymin, xmax=4, xmin=3, fill=rideable_type))  
  geom_rect()  
  scale_fill_brewer(palette=4)  
  facet_grid(~member_casual)  
  coord_polar(theta="y")  
  xlim(c(2, 4))  
  theme_void() 

DATA

subdata.frame <- data.frame(
  stringsAsFactors = FALSE,
     member_casual = c("casual", "casual", "casual", "member", "member"),
     rideable_type = c("classic_bike","docked_bike",
                       "electric_bike","classic_bike","electric_bike"),
                 n = c(68941L, 14503L, 20990L, 75455L, 17008L),
              prop = c(0.66, 0.139, 0.201, 0.816, 0.184),
              ymax = c(0.66, 0.799, 1, 0.816, 1)
)