Plotly in R: How to draw stacked bar chart in a time-series data to show percentage composition?

Question

I have a dataframe that looks like this:

+------------+------+-------+
| Date       | Boys | Girls |
+------------+------+-------+
| 2020-01-01 | 53   | 78    |
+------------+------+-------+
| 2020-01-02 | 23   | 30    |
+------------+------+-------+
| 2020-01-03 | 45   | 20    |
+------------+------+-------+
| 2020-01-04 | 120  | 178   |
+------------+------+-------+
| 2020-01-05 | 57   | 58    |
+------------+------+-------+
| ...        | ...  | ...   |
+------------+------+-------+

I would like to draw a stacked bar chart across time, to show what percentage of the total is boys vs. what percentage of the total is girls.

It would looks something like this chart:

But the x axis would be dates.

I am drawing this using plotly (not ggplot2, since I would like it to be interactive) using R.

Thanks very much!

Answer 1

Try with ggplotly as it can be easier:

library(plotly)
library(ggplot2)
library(dplyr)
library(tidyr)
#Code 1
ggplotly(df %>% pivot_longer(-Date) %>%
  mutate(Date=as.Date(Date)) %>%
  ggplot(aes(x=Date,y=value,fill=name))+
  geom_bar(stat = 'identity')+
  labs(fill='Var'))
#Code 2
ggplotly(df %>% pivot_longer(-Date) %>%
           mutate(Date=as.Date(Date)) %>%
           ggplot(aes(x=Date,y=value,fill=name))+
           geom_bar(stat = 'identity',position = 'fill')+
           labs(fill='Var')+
           scale_y_continuous(labels = scales::percent))

Outputs:

Some data used:

#Data
df <- structure(list(Date = c("2020-01-01", "2020-01-02", "2020-01-03", 
"2020-01-04", "2020-01-05"), Boys = c(53L, 23L, 45L, 120L, 57L
), Girls = c(78L, 30L, 20L, 178L, 58L)), row.names = c(NA, -5L
), class = "data.frame")