Plot the relationship between a continuous and a binary variable, with the distribution of the continuous variable conditional on the binary variable. It includes a logistic and spline fit. You can add more layers to the result using standard ggplot2 syntax.

logithistplot.R

# inspired by http://schamberlain.github.io/2012/01/logistic-regression-barplot-fig/
logithistplot <- function(data,breaks="Sturges",se=TRUE) {
    require(ggplot2);
    col_names=names(data)
    
    # get min and max axis values
    min_x <- min(data[,1])
    max_x <- max(data[,1])
    
    # get bin numbers
    hist_both <- hist(data[,1],plot=FALSE,breaks=breaks)
    hist0 <- hist(data[data[,2]==0,1],breaks=hist_both$breaks,plot=FALSE)
    hist1 <- hist(data[data[,2]==1,1],breaks=hist_both$breaks,plot=FALSE)
    max_count=max(c(hist0$counts,hist1$counts))
    
    # create plots
    a <- ggplot(data, aes_string(x = col_names[1], y = col_names[2])) +
      theme_bw(base_size=16) +
      geom_smooth(method = "gam", family = "binomial", se = se,
                  aes(colour='Spline',fill='Spline'), size=1.5,formula=y~s(x,bs="cr"))+ 
      geom_smooth(method = "glm", family = "binomial", se = se,
                  aes(colour='Logit',fill='Logit'), size=1.5) +
      guides(fill=FALSE)+
      labs(y = "Probability\n", x = paste0("\n",col_names[1]), colour="Method")
    
    y_range_orig=ggplot_build(a)$panel$ranges[[1]]$y.range
    y_range=y_range_orig
    if (y_range[1]<0) y_range[1]=0
    if (y_range[2]>1) y_range[2]=1
    min_y <- min(y_range[1])
    max_y <- max(y_range[2])
    
    # need blank bar up to y_min, bars for 0's, blank bars up to 1's, bars for 1's up to y_max
    hist_df=data.frame(mids=hist_both$mids,
                       counts_below=min_y,
                       counts0=hist0$counts/max_count*diff(y_range)/2,
                       counts_mid=diff(y_range)-hist_both$counts/max_count*diff(y_range)/2,
                       counts1=hist1$counts/max_count*diff(y_range)/2)
    hist.m=melt(hist_df,id=1)
    
    a <- ggplot(data, aes_string(x = col_names[1], y = col_names[2])) +
      theme_bw(base_size=16) +
      geom_bar(data=hist.m,aes(mids,value,fill=variable),stat="identity")+
      coord_cartesian(ylim=y_range_orig)+
      scale_fill_manual(values=c(NA,NA,"grey","grey","red","blue"))+
      geom_smooth(method = "gam", family = "binomial", se = se,
                  aes(colour='Spline',fill='Spline'), size=1.5,formula=y~s(x,bs="cr"))+ 
      geom_smooth(method = "glm", family = "binomial", se = se,
                  aes(colour='Logit',fill='Logit'), size=1.5) +
      guides(fill=FALSE)+
      labs(y = "Probability\n", x = paste0("\n",col_names[1]), colour="Method")
    (a)
  }
  # Examples
  # logithistplot(mtcars[,c("mpg","vs")],breaks=10,se=FALSE) + ggtitle("Cars Data")
  # logithistplot(movies[,c("rating","Action")])+labs(y="Probability of Being an Action Movie")

Thanks for the code,

it gives error.

logithistplot(mtcars[,c("mpg","vs")],breaks=10,se=FALSE) + ggtitle("Cars Data")
Warning: Ignoring unknown parameters: family
Warning: Ignoring unknown parameters: family
Error in if (y_range[1] < 0) y_range[1] = 0 : argument is of length zero