Plotly dropdown menus (events) causes the values, legend, and colors to be redrawn incorrectly
I am trying to have a dropdown button within plotly that enables to use different columns of my dataframe for traces to be drawn. However, switching from the first trace to another, arbitrary values gets plotted (not sure what values plotly uses after the first change, but they don't match the dataframe values), the legend gets screwed up (colors are not unique anymore, labels are out of order, not all of the values are shown on the legend, etc.). You can see the plot in action at the link below on R-pubs.
https://rpubs.com/Mdoubledash/testplotlydropdown
What do I mean by not the right traces are drawn? Simply switching to A2 and going back to A1, you see that the plot looks different from the first render and there are duplicated colors/labels on the plot and the legend.
Here's the code I have used (see the reproducible data at the bottom). Here, I am adding 7 traces and then within the layout argument I assign these 7 traces to the dropdown button.
ex_df %>%
plot_ly(x = ~Date, color = ~Model) %>%
add_lines(y = ~`A1`) %>%
add_lines(y = ~`A2`, visible = F) %>%
add_lines(y = ~`A3`, visible = F) %>%
add_lines(y = ~`B1`, visible = F) %>%
add_lines(y = ~`B2`, visible = F) %>%
add_lines(y = ~`C1`, visible = F) %>%
add_lines(y = ~`C2`, visible = F) %>%
layout(
title = "Plotly Dropdown Menus",
xaxis = list(domain = c(1, 1)),
yaxis = list(title = "Value"),
updatemenus = list(
list(y = 10,
buttons = list(
list(method = "restyle",
args = list("visible", list(T, F, F, F, F, F, F)),
label = "A1"),
list(method = "restyle",
args = list("visible", list(F, T, F, F, F, F, F)),
label = "A2"),
list(method = "restyle",
args = list("visible", list(F, F, T, F, F, F, F)),
label = "A3"),
list(method = "restyle",
args = list("visible", list(F, F, F, T, F, F, F)),
label = "B1"),
list(method = "restyle",
args = list("visible", list(F, F, F, F, T, F, F)),
label = "B2"),
list(method = "restyle",
args = list("visible", list(F, F, F, F, F, T, F)),
label = "C1"),
list(method = "restyle",
args = list("visible", list(F, F, F, F, F, F, T)),
label = "C2")
)
)
)
)
The code runs fine, and looks OK with the first render.
Example Dataset:
#dput(ex_df)
ex_df <- structure(list(Model = c("M_0", "M_1", "M_2", "M_3", "M_4", "M_5",
"M_0", "M_1", "M_2", "M_3", "M_4", "M_5",
"M_0", "M_1", "M_2", "M_3", "M_4", "M_5"),
Date = structure(c(1630512000, 1630512000, 1630512000,
1630512000, 1630512000, 1630512000,
1630512900, 1630512900, 1630512900,
1630512900, 1630512900, 1630512900,
1630513800, 1630513800, 1630513800,
1630513800, 1630513800, 1630513800),
tzone = "", class = c("POSIXct", "POSIXt")),
A1 = c(4.3924, 2.77967, 3.23016, 3.23016, 4.3924, 4.3924,
4.45712, 2.8175, 3.27791, 3.27789, 4.45715, 4.43708,
4.87661, 3.10666, 3.61006, 3.61005, 4.8779, 4.79372),
A2 = c(0.19052, 0.19052, 0.19052, 0.19052, 0.19052, 0.19052,
0.43156, 0.43156, 0.43156, 0.43163, 0.43156, 0.43156,
0.6055, 0.6055, 0.6055, 0.60551, 0.6055, 0.6055),
A3 = c(NA, 4.33173, 3.88124, 3.88124, 2.719, 2.719,
NA, 4.33173, 3.96342, 3.9293, 2.719, 2.719,
NA, 4.34133, 2.46357, 4.12238, 2.719, 2.719),
B1 = c(13.03056, 11.41784, 11.86833, 11.86833, 13.03056,13.03056,
13.02643, 11.41376, 11.86428, 11.86428,13.02643, 13.02643,
13.01181, 11.3972, 11.84812, 11.84812, 13.01181, 13.01093),
B2 = c(15.90011, 18.61912, 14.73789, 18.61912, 18.6191, 18.6191,
20.56435, 21.78546, 20.17156, 21.78857, 21.78544, 21.78544,
18.05423, 19.96631, 17.51721, 19.96667, 19.96629, 19.96629),
C1 = c(116.84061, 116.84061, 120.72184, 116.84061, 116.84061, 116.84062,
35.50683, 35.50684, 36.85026, 35.56428, 35.50684, 35.50679,
162.67923, 162.67924, 168.46906, 162.67662, 162.67924, 162.67929),
C2 = c(106.3359, 106.3359, 106.33588, 106.33589, 106.3359, 106.33603,
-24.20234, -24.20234, -25.43058, -24.17748, -24.20234, -24.20229,
345.84013, 345.84011, 332.59987, 345.83915, 345.84011, 345.84026)),
class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -18L))
The reason you're not seeing what you expect is because of how Plotly handles your data. Typically, Plotly will make a separate trace for each color. You created 7 traces; you have 6 unique values in Model. You need around 42 T or F, but around doesn't work.
How many traces?
plt <- ex_df %>%
plot_ly(x = ~Date, color = ~Model) %>%
add_lines(y = ~A1) %>%
add_lines(y = ~A2, visible = F) %>%
add_lines(y = ~A3, visible = F) %>%
add_lines(y = ~B1, visible = F) %>%
add_lines(y = ~B2, visible = F) %>%
add_lines(y = ~C1, visible = F) %>%
add_lines(y = ~C2, visible = F)
plt <- plotly_build(plt)
length(plt$x$data)
# [1] 41
To determine which column doesn't have all colors, sometimes you can look at the name and legendgroup for the traces. However, when I looked, there were no legendgroup designations. The Model is the trace name.
You can look at this like so:
x <- invisible(lapply(1:length(plt$x$data),
function(i){
plt$x$data[[i]]$name
})) %>% unlist()
table(x)
# x
# M_0 M_1 M_2 M_3 M_4 M_5
# 6 7 7 7 7 7
I tried a few more things to determine which trace was missing a color.
funModeling::df_status(ex_df)
# A3 as has NA's; that's probably the one that's missing a color
ex_df[ , c(1, 5)] %>% na.omit() %>% select(Model) %>% unique()
# # A tibble: 5 × 1
# Model
# <chr>
# 1 M_1
# 2 M_2
# 3 M_3
# 4 M_4
# 5 M_5 # A3 is missing M_0
The layout, armed with the right info.
plt %>%
layout(
title = "Plotly Dropdown Menus",
xaxis = list(domain = c(1, 1)),
yaxis = list(title = "Value"),
updatemenus = list(
list(y = 10,
buttons = list(
list(method = "restyle",
args = list("visible", c(rep(T, 6), rep(F, 35))),
label = "A1"),
list(method = "restyle",
args = list("visible", c(rep(F, 6), rep(T, 6), rep(F, 29))),
label = "A2"),
list(method = "restyle",
args = list("visible", c(rep(F, 12), rep(T, 5), rep(F, 24))),
label = "A3"),
list(method = "restyle",
args = list("visible", c(rep(F, 17), rep(T, 6), rep(F, 18))),
label = "B1"),
list(method = "restyle",
args = list("visible", c(rep(F, 23), rep(T, 6), rep(F, 12))),
label = "B2"),
list(method = "restyle",
args = list("visible", c(rep(F, 33), rep(T, 6), rep(F, 6))),
label = "C1"),
list(method = "restyle",
args = list("visible", c(rep(F, 35), rep(T, 6))),
label = "C2")
) # end buttons list
)) # end updatemenus list
) # end layout
Looks good.
I ran another plot just to check.
ex_df %>%
plot_ly(x = ~Date, color = ~Model) %>%
add_lines(y = ~C2) %>%
layout(
title = "Plotly Dropdown Menus",
xaxis = list(domain = c(1, 1)),
yaxis = list(title = "Value"))
- How to get the selected tab's name of a Quarto Tabset Panel?
- Separting alphanumeric string using tidyr separate wider regex
- Convert JSON type scraped string to dataframe in R
- Testing private methods in R6 classes in R
- How can I align the tag with the displayed text?
- Date labels in the x axis are misaligned by one month
- How can I force a shiny app to switch colors after a specific time?
- pretty_breaks not working with geom_spatraster
- pretty_breaks does not working with geom_sf
- overwrite a facet panel with custom plot
- How to draw a shapefile with ggpolar
- Exported file from R using `haven` cannot be opened by SAS
- How to install libpng-dev on Mac
- Ignoring NAs while aggregating character vector
- Shinyselected row in a striped DT::datatable() disappears when style = "bootstrap5" and RowGroup extension is used
- ggplot2 secondary axis tidyeval
- parse dynamic case_when based on thresholds values
- dbWriteTable or dbAppendTable fail for date column when appending to DB2-table
- How can I use a loop in RMarkdown to programmatically plot figures and text on individual pages in a document?
- Conditional recursive formula in dplyr
- Current development in how to adjust individual x axis title using ggplot facet_wrap
- How to make a probability figure using a logistic regression?
- dplyr - Need to add the CSV filename after importing all files from a directory
- How to reorder a stacked bar chart in ggplot2?
- how can I render a quarto website to a single pdf
- Assign specific values to unique values in all dataframe columns in R
- Unable to install tidyverse package for r kernel in jupyter
- How to replace values in a matrix based on a conditional variable
- How can I make my enormous dataframe from wide to long in R?
- Group variable stacking when using geom_ridgeline_gradient()