as these discretization functions are especially useful for quantile and group analysis detecting and filtering outliers filtering or transforming outliers is largely matter of applying array operations consider dataframe with some normally distributed datain [ ]np random seed( in [ ]data dataframe(np random randn( )in [ ]data describe(out[ ] count mean - std min - - - - - max - - - - - - suppose you wanted to find values in one of the columns exceeding three in magnitudein [ ]col data[ in [ ]col[np abs(col out[ ] - - name to select all rows having value exceeding or - you can use the any method on boolean dataframein [ ]data[(np abs(data any( )out[ ] - - - - - - - - - - - - - - - - - - - - - - values can just as easily be set based on these criteria here is code to cap values outside the interval - to data transformation www it-ebooks info