views out[ ]views zscore minmax - - - - - the preceding output shows the min-max scaled values in the minmax column and as expectedthe maximum viewed video in row index has value of and the minimum viewed video in row index has value of you can also compute this mathematically using the following code (sample computation for the first rowin [ ](vw[ np min(vw)(np max(vwnp min(vw)out[ ] robust scaling the disadvantage of min-max scaling is that often the presence of outliers affects the scaled values for any feature robust scaling tries to use specific statistical measures to scale features without being affected by outliers mathematically this scaler can be represented as rs median iqr( , where we scale each value of feature by subtracting the median of and dividing the resultant by the iqr also known as the inter-quartile range of which is the range (differencebetween the first quartile ( th %ileand the third quartile ( th %ilethe following code performs robust scaling on our sample feature in [ ]rs robustscaler(views['robust'rs fit_transform(views[['views']]views out[ ]views zscore minmax robust - - - - - - - - the scaled values are depicted in the robust column and you can compare them with the scaled features in the other columns you can also compute the same using the mathematical equation we formulated for the robust scaler as depicted in the following snippet (for the first row index valuein [ ]quartiles np percentile(vw( )