Easy web apps for data science without the compromises
No web development skills required
Here is a Shiny app
Shiny apps are easy to write. Let users interact with your data and your analysis, all with R or Python:
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(theme =bs_theme(bootswatch ="minty"),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$yvar))+list(theme(传说．position ="bottom"),if(input$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
frompathlibimportPathimportpandasaspdimportseabornassnsimportshiny.experimentalasxfromshinyimportApp, 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=x.ui.page_sidebar(x.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),),x.ui.output_plot("scatter"))defserver(input: Inputs, output: Outputs, session: Session):@reactive.Calcdeffiltered_df()->pd.DataFrame:"""Returns a Pandas data frame that includes only the desired rows"""# This calculation "req"uires that at least one species is selectedreq(len(input．species())>0)# Filter the rows so we only include the desired speciesreturndf[df["Species"].isin(input．species())]@output@render.plotdefscatter():"""Generates a plot for Shiny to display to the user"""# The plotting function to use depends on whether margins are desiredplotfunc=sns.jointplotifinput．show_margins()elsesns.scatterplotplotfunc(data=filtered_df(),x=input．xvar(),y=input．yvar(),hue="Species"ifinput．by_species()elseNone,hue_order=species,传说=False,)app=App(app_ui, server)Hosting and Deployment
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组织使用的:
