Consider specifying a target variable when computing a summary

Currently all of the metrics computed are independent of a target variable or column, but if `lens.summarise` took the name of a column as the target variable, the output of some metrics could be more interpretable even if the target variable is not used in any kind of predictive modelling.

A good example of this could be PCA (see #14), which could plot the different categories of the target variables in different colours for 2D plots of the data transformed into the principal components. This would give a good idea of whether the target variable can be easily inferred from the available data.