Based on the code below I am trying to create a pyramid plot
. The Value
column is in percent so I added the %
sign to this column. And, now the code doesn't work.
Error: Discrete value supplied to continuous scale
The reason behind adding the %
sign is that this way it will also be in the x-axis labels.
How can I fix this such that the %
sign appears on the x-axis and the -
sign doesn't appear on x-axis as well?
Code data:
library(tidyverse)
# Data
pop = sstructure(list(age_group = c("< 5 years", "5 - 9", "10 - 14",
"15 - 19", "20 - 24", "25 - 29", "30 - 34", "35 - 44",
"45 - 54", "55 - 64", "65 - 74", "75 - 84", "85 "),
males = c(6, 6, 7, 6, 7, 7, 8, 17, 15, 11, 6, 3, 1), females = c(6,
5, 6, 6, 6, 7, 7, 16, 15, 12, 7, 4, 2)), row.names = c(NA,
-13L), spec = structure(list(cols = list(`AGE GROUP` = structure(list(), class = c("collector_character",
"collector")), MALES = structure(list(), class = c("collector_double",
"collector")), FEMALES = structure(list(), class = c("collector_double",
"collector"))), default = structure(list(), class = c("collector_guess",
"collector")), delim = ","), class = "col_spec"), problems = <pointer: 0x0000029a145331e0>, class = c("spec_tbl_df",
"tbl_df", "tbl", "data.frame"))
# Draw a pyramid plot
# Clean data
pop_df = pop %>% select(age_group,
males,
females) %>%
gather(key = Type, value = Value, -c(age_group))
# Make male values negative
pop_df$Value = ifelse(pop_df$Type == "males", -1*pop_df$Value, pop_df$Value)
# Add % sign to the Value column
pop_df$Value = paste0(pop_df$Value, "%")
# Plot
gg_pop = ggplot(pop_df, aes(x = age_group, y = Value, fill = Type))
geom_bar(data = subset(pop_df, Type == "females"), stat = "identity")
geom_bar(data = subset(pop_df, Type == "males"), stat = "identity")
scale_y_continuous(labels = abs)
ggtitle("Male vs Female Population Comparison")
labs(x = "Age group", y = "Percentage", fill = "Gender")
coord_flip()
# Interactive
ggplotly(gg_pop)
CodePudding user response:
Don't add %
to the column data, add it in the label.
ggplot(pop_df, aes(x = age_group, y = Value, fill = Type))
geom_bar(data = subset(pop_df, Type == "females"), stat = "identity")
geom_bar(data = subset(pop_df, Type == "males"), stat = "identity")
scale_y_continuous(labels = function(z) paste0(abs(z), "%")) # CHANGE
ggtitle("Male vs Female Population Comparison")
labs(x = "Age group", y = "Percentage", fill = "Gender")
coord_flip()