app.R

library(shiny)library(bslib)library(dplyr)library(ggplot2)library(ggExtra)penguins_csv<-"https://raw.githubusercontent.com/jcheng5/simplepenguins.R/main/penguins.csv"df<- readr::read_csv(penguins_csv)# Find subset of columns that are suitable for scatter plotdf_num<- df|>select(where(is.numeric),-Year)ui<-page_sidebar(sidebar =sidebar(varSelectInput("xvar","X variable", df_num,selected ="Bill Length (mm)"),varSelectInput("yvar","Y variable", df_num,selected ="Bill Depth (mm)"),checkboxGroupInput("species","Filter by species",choices =unique(df$Species),selected =unique(df$Species)    ),hr(),# Add a horizontal rulecheckboxInput("by_species","Show species",TRUE),checkboxInput("show_margins","Show marginal plots",TRUE),checkboxInput("smooth","Add smoother"),  ),plotOutput("scatter"))server<-function(input, output, session) {  subsetted<-reactive({req(input$species)    df|>filter(Species%in% input$species)  })  output$scatter<-renderPlot({    p<-ggplot(subsetted(),aes(!!input$xvar,!!input$yvar))+list(theme(legend.position ="bottom"),if (input$by_species)aes(color = Species),geom_point(),if (input$smooth)geom_smooth()    )if (input$show_margins) {      margin_type<-if (input$by_species)"density"else"histogram"      p<- ggExtra::ggMarginal(p,type = margin_type,margins ="both",size =8,groupColour = input$by_species,groupFill = input$by_species)    }    p  },res =100)}shinyApp(ui, server)

app.py

from pathlibimport Pathimport pandasas pdimport seabornas snsfrom shinyimport App, Inputs, Outputs, Session, reactive, render, req, uisns.set_theme()# https://raw.githubusercontent.com/jcheng5/simplepenguins.R/main/penguins.csvdf= pd.read_csv(Path(__file__).parent/"penguins.csv", na_values="NA")numeric_cols= df.select_dtypes(include=["float64"]).columns.tolist()species= df["Species"].unique().tolist()species.sort()app_ui= ui.page_sidebar(    ui.sidebar(        ui.input_selectize("xvar","X variable", numeric_cols, selected="Bill Length (mm)"        ),        ui.input_selectize("yvar","Y variable", numeric_cols, selected="Bill Depth (mm)"        ),        ui.input_checkbox_group("species","Filter by species", species, selected=species        ),        ui.hr(),        ui.input_switch("by_species","Show species", value=True),        ui.input_switch("show_margins","Show marginal plots", value=True),    ),    ui.card(        ui.output_plot("scatter"),    ),)def server(input: Inputs, output: Outputs, session: Session):@reactive.Calcdef filtered_df()-> pd.DataFrame:"""Returns a Pandas data frame that includes only the desired rows"""# This calculation "req"uires that at least one species is selected        req(len(input.species())>0)# Filter the rows so we only include the desired speciesreturn df[df["Species"].isin(input.species())]@output@render.plotdef scatter():"""Generates a plot for Shiny to display to the user"""# The plotting function to use depends on whether margins are desired        plotfunc= sns.jointplotifinput.show_margins()else sns.scatterplot        plotfunc(            data=filtered_df(),            x=input.xvar(),            y=input.yvar(),            hue="Species"ifinput.by_species()elseNone,            hue_order=species,            legend=False,        )app= App(app_ui, server)