plot show relationship between independent variable and dependent variable(Binary)
There is package named Boruta in R/Python. This is also called as predictor importance test. Used to pick the important variable.

Uses of this package:

Boruta is a feature selection algorithm. Precisely, it works as a wrapper algorithm around Random Forest. This package derive its name from a demon in Slavic mythology who dwelled in pine forests.

We know that feature selection is a crucial step in predictive modeling. This technique achieves supreme importance when a data set comprised of several variables is given for model building.

Boruta can be your algorithm of choice to deal with such data sets. Particularly when one is interested in understanding the mechanisms related to the variable of interest, rather than just building a black box predictive model with good prediction accuracy.

The outcome would be a box whisker plot with their importance with the target variable. You need not worry about categorical and continuous variables. you just need to cast them correctly before passing the data to the algorithm.

You can go through this Link for better understanding on the package and implementation of the same.

This is the sample plot:

Let me know if you need any additional information.