Visualization methods in R to examine correlation of labels against response Question
What are some good plotting methods in R for examining the relationship between a target variable and various explanatory variables? In particular, I'm looking for visualization techniques that scale to more variables than the traditional scatterplot matrix.
More details
The scatterplot matrix is a great tool for visualizing pairwise relationships between variables. For example, with the swiss dataset in R, we can easily plot a matrix of scatterplots.
library(datasets)
data(swiss)
plot(swiss[1:3])

which yields

I am interested in the case where I want to predict some response, say Fertility using some combination of explanatory variables. I want to closely examine how each explanatory variable correlates with Fertility. If I have many columns in my dataframe, using plot(swiss) becomes unwieldy.
For example, the following plot (generated following instructions here) shows pairwise correlations for all columns in a dataframe. If I could plot something like this but only showing correlations between Fertility and other columns, that would be useful.
library(datasets)
data(swiss)
plot(swiss[1:3])

library(devtools)
library(inspectdf)
library(tidyverse)
library(readr)

show_plot(inspect_cor(swiss))

which yields
Below are two functions using my favorite packages:

The first one shows a scatterplot of every column against the target column
The second one shows the correlation of every column with the target column, with confidence intervals (I found how to do that with ggplot here).

Code:
library(ggplot2)
library(reshape2)
library(plyr)

scatterplot &lt;- function(data, targetColumn='Fertility') {
  d&lt;-melt(data,id.vars = targetColumn)
#  ggplot(d, aes_string('value',targetColumn))+geom_point()+facet_grid(variable~.)
  ggplot(d, aes_string('value',targetColumn))+geom_point()+facet_wrap(variable~.)
}


corplotCI &lt;- function(data, targetColumn='Fertility', method='pearson') {
  d&lt;-ldply(colnames(data), function(col) {
    if (col != targetColumn) {
      r &lt;- cor.test(data[,col], data[,targetColumn],method=method)
      data.frame(variable=col,cor=r$estimate, lowerCI=r$conf.int[1],upperCI=r$conf.int[2])
    }
  })
  ggplot(d,aes(cor,variable))+geom_point(size=3)+geom_errorbarh(aes(xmin = lowerCI,xmax = upperCI),height=.5)+coord_cartesian(xlim=c(-1,1))
}

Usage:
scatterplot(swiss)

corplotCI(swiss)