I have some time series data across multiple categories, where each category has a subset of a group of products and I want to plot them in a plotly subplot so each product line has the same color. How do I do this?
I have tried specifying a palette in the colors argument which did not work, and I also tried using an expand_grid
to "pad" each category with the missing products, but that also did not work. And finally I tried a combination of both approaches which still did not work.
Below is a toy dataset of the problem. As you can see in the legendgroup the lines for each category are coloured differently.
data <- expand_grid(Category = c(LETTERS[1:3]), Product = letters[1:5], date = seq.Date(as.Date("2020-01-01"), as.Date("2020-12-31"), by = 7)) %>%
mutate(y_value = rnorm(nrow(.), 50, 25)) %>%
filter(!paste0(Category, Product) %in% c("Ab","Bd","Ce","Ca"))
data %>%
group_by(Category) %>%
do(
plot = plot_ly(data = ., x=~date, y = ~ y_value, color = ~Product, legendgroup = ~ Product) %>%
add_lines(hoverinfo = "text", text = ~ paste0("Category: ", Category, "<br>", "Product: ", Product)) %>%
add_annotations(text = ~Category, x = 0.5,y = ~ max(y_value), xref = "paper",showarrow = FALSE)
) %>%
subplot(nrows = 3, shareX = TRUE, shareY = FALSE)
You could make use of a named vector of color vectors to assign colors to your products and passing it to the colors
argument of plot_ly
like so:
library(plotly)
library(tidyr)
data <- expand_grid(Category = c(LETTERS[1:3]), Product = letters[1:5], date = seq.Date(as.Date("2020-01-01"), as.Date("2020-12-31"), by = 7)) %>%
mutate(y_value = rnorm(nrow(.), 50, 25)) %>%
filter(!paste0(Category, Product) %in% c("Ab","Bd","Ce","Ca"))
colors <- c("a" = "blue", "b" = "red", c = "green", d = "orange", e = "purple")
data %>%
group_by(Category) %>%
do(
plot = plot_ly(data = ., x=~date, y = ~ y_value, color = ~Product, colors = colors, legendgroup = ~ Product) %>%
add_lines(hoverinfo = "text", text = ~ paste0("Category: ", Category, "<br>", "Product: ", Product)) %>%
add_annotations(text = ~Category, x = 0.5,y = ~ max(y_value), xref = "paper",showarrow = FALSE)
) %>%
subplot(nrows = 3, shareX = TRUE, shareY = FALSE)