Dygraphs in R: Plot Ribbon and mean line of different groups - r

Question

I recently started working dygraphs in R, and wanted to achieve a ribbon line plot with it.
Currently, I have the below ggplot which displays a ribbon (for data from multiple batches over time) and its median for two groups. Below is the code for it.
ggplot(df,
aes(x=variable, y=A, color=`[category]`, fill = `[category]`)) +
stat_summary(geom = "ribbon", alpha = 0.35) +
stat_summary(geom = "line", size = 0.9) +
theme_minimal()+ labs(x="TimeStamp")
I could add the median solid line on the dygraph, but I'm unable to add the ribbon to it. Below is the dygraph and my code for it.
df_Medians<- df%>%
group_by(variable,`[category]`) %>%
summarise(A = median(A[!is.na(A)]))
median <- cbind(as.ts(df_Medians$A))
dygraph(median) %>%
dyRangeSelector()
Is there anyway to plot something similar to the above ggplot on dygraphs? Thanks in advance.

Answer 1

See if the following serves your purpose:
ggplot code (for mean, replace median_se with mean_se in the stat_summary layers):
library(ggplot2)
ggplot(df,
aes(x=variable, y=A, color=category, fill = category)) +
stat_summary(geom = "ribbon", alpha = 0.35, fun.data = median_se) +
stat_summary(geom = "line", size = 0.9, fun.data = median_se) +
theme_minimal()
dygraph code (for mean, replace median_se with mean_se in the summarise step):
library(dplyr)
library(dygraph)
# calculate summary statistics for each category, & spread results out such that each row
# corresponds to one position on the x-axis
df_dygraph <- df %>%
group_by(variable, category) %>%
summarise(data = list(median_se(A))) %>%
ungroup() %>%
tidyr::unnest(data) %>%
mutate(category = as.integer(factor(category))) %>% # optional: standardizes the column
# names for summary stats
tidyr::pivot_wider(id_cols = variable, names_from = category,
values_from = c(ymin, y, ymax))
> head(df_dygraph)
# A tibble: 6 x 7
variable ymin_1 ymin_2 y_1 y_2 ymax_1 ymax_2
<int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 1 3817. 2712. 4560. 2918. 5304. 3125.
2 2 3848. 2712. 4564. 2918. 5279. 3125.
3 3 3847. 2826. 4564 2961 5281. 3096.
4 4 3722. 2827. 4331 2962. 4940. 3098.
5 5 3833. 2831. 4570. 2963 5306. 3095.
6 6 3835. 2831. 4572 2964 5309. 3097.
dygraph(df_dygraph, main = "Dygraph title") %>%
dySeries(c("ymin_1", "y_1", "ymax_1"), label = "Category 1") %>%
dySeries(c("ymin_2", "y_2", "ymax_2"), label = "Category 2") %>%
dyRangeSelector()
Code for median counterpart of mean_se:
median_se <- function(x) {
x <- na.omit(x)
se <- sqrt(var(x) / length(x))
med <- median(x)
ggplot2:::new_data_frame(list(y = med,
ymin = med - se,
ymax = med + se),
n = 1)
}
Sample data:
df <- diamonds %>%
select(price, cut) %>%
filter(cut %in% c("Fair", "Ideal")) %>%
group_by(cut) %>%
slice(1:1000) %>%
mutate(variable = rep(seq(1, 50), times = 20)) %>%
ungroup() %>%
rename(A = price, category = cut)