Show data points in common (intersection) across levels in dropdown/checkbox filter R/plotly/crosstalk

Hi,

I have a scatter plot with a checkbox menu added via crosstalk’s bscols(). When I select, let’s say Animal_Biology, Bioinformatics_Computational_Biology, and Cell_Biology from the drop-down menu, I’d like the scatter plot to show ONLY the researchers (data points) that are involved in those three topics instead of everyone in all three research fields. Any ideas as per how can I achieve this? Thanks in advance and any help/suggestion is deeply appreciated.

Oscar.

shared_data <- indPlotlyMetadataLong %>% SharedData$new()

mcaPlot <- shared_data %>%
plot_ly(x = ~Dim.1 , y = ~Dim.2, alpha = 0.9, text = ~researcher,),
color = ~research_field,
marker = list(size = 11),
hoverinfo = “text”) %>%
add_markers() %>%
highlight(persistent = TRUE) %>%
hide_legend() %>%
layout(title = “MCA of CSB data”,
xaxis = list(title = “PC 1”, range = c(-1, 1.2)),
yaxis = list(title = “PC 2”, range = c(-1, 1.2)))

Add checkboxes to mcaPlot

bscols(widths = c(4, 8),
filter_checkbox(id = “research_field”, label = “Select a research field”,
sharedData = shared_data, group = ~research_field,
allLevels = TRUE, inline = FALSE, columns = 2),
mcaPlot)

Here is my indPlotlyMetadataLong data -used to create shared_data:

structure(list(Dim.1 = c(0.154663044922868, 0.039412348935979,
-0.238553016168864, -0.857636033313211, 0.136180995471785, -0.023405229926155,
0.309675654958752, 0.956678913668931, -0.402039082922732, -0.083222278467751,
0.154663044922868, 0.039412348935979, -0.238553016168864, -0.857636033313211,
0.136180995471785, -0.023405229926155, 0.309675654958752, 0.956678913668931,
-0.402039082922732, -0.083222278467751, 0.154663044922868, 0.039412348935979,
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0.309675654958752, 0.956678913668931, -0.402039082922732, -0.083222278467751,
0.154663044922868, 0.039412348935979, -0.238553016168864, -0.857636033313211,
0.136180995471785, -0.023405229926155, 0.309675654958752, 0.956678913668931,
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0.154663044922868, 0.039412348935979, -0.238553016168864, -0.857636033313211,
0.136180995471785, -0.023405229926155, 0.309675654958752, 0.956678913668931,
-0.402039082922732, -0.083222278467751, 0.154663044922868, 0.039412348935979,
-0.238553016168864, -0.857636033313211, 0.136180995471785, -0.023405229926155,
0.309675654958752, 0.956678913668931, -0.402039082922732, -0.083222278467751,
0.154663044922868, 0.039412348935979, -0.238553016168864, -0.857636033313211,
0.136180995471785, -0.023405229926155, 0.309675654958752, 0.956678913668931,
-0.402039082922732, -0.083222278467751, 0.154663044922868, 0.039412348935979,
-0.238553016168864, -0.857636033313211, 0.136180995471785, -0.023405229926155,
0.309675654958752, 0.956678913668931, -0.402039082922732, -0.083222278467751,
0.154663044922868, 0.039412348935979, -0.238553016168864, -0.857636033313211,
0.136180995471785, -0.023405229926155, 0.309675654958752, 0.956678913668931,
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-0.238553016168864, -0.857636033313211, 0.136180995471785, -0.023405229926155,
0.309675654958752, 0.956678913668931, -0.402039082922732, -0.083222278467751,
0.154663044922868, 0.039412348935979, -0.238553016168864, -0.857636033313211,
0.136180995471785, -0.023405229926155, 0.309675654958752, 0.956678913668931,
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0.309675654958752, 0.956678913668931, -0.402039082922732, -0.083222278467751,
0.154663044922868, 0.039412348935979, -0.238553016168864, -0.857636033313211,
0.136180995471785, -0.023405229926155, 0.309675654958752, 0.956678913668931,
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-0.238553016168864, -0.857636033313211, 0.136180995471785, -0.023405229926155,
0.309675654958752, 0.956678913668931, -0.402039082922732, -0.083222278467751
), Dim.2 = c(0.282285353128673, -0.111166763161315, -0.505836530845472,
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