I have a data set with 2000 continuous predictor variables and a binary outcome variable. I would like a few easy ways to visualize this data. A box plot or histogram of all the variables seems that it would be too much. Are there any good ways of simultaneously visualizing the data?
High dimensional data visualization depends on your overall objective. If for example you want to see if the data is actually separable, you could consider looking at a dimentionality tool like PCA, LDA or non-linear tools MDS, kernelPCA ,local linear Embedding, Isomap (these tools will depend on what structure of the data you would like to preserve).
But If your concern is to see the relationships between the variables and/or their distribution with outliers, the best option is to use a pair-plot (scatter plot matrix) with subsets of the data, I admit this is a bit laborious.