How to transform some columns only with SimpleImputer or equivalent

Question

I am taking my first steps with scikit library and found myself in need of backfilling only some columns in my data frame.

I have read carefully the documentation but I still cannot figure out how to achieve this.

To make this more specific, let's say I have:

A = [[7,2,3],[4,np.nan,6],[10,5,np.nan]]

And that I would like to fill in the second column with the mean but not the third. How can I do this with SimpleImputer (or another helper class)?

An evolution from this, and the natural follow up questions is: how can I fill the second column with the mean and the last column with a constant (only for cells that had no values to begin with, obviously)?

Answer 1

There is no need to use the SimpleImputer.
DataFrame.fillna() can do the work as well

• For the second column, use

  column.fillna(column.mean(), inplace=True)

• For the third column, use

  column.fillna(constant, inplace=True)

Of course, you will need to replace column with your DataFrame's column you want to change and constant with your desired constant.

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Edit
Since the use of inplace is discouraged and will be deprecated, the syntax should be

column = column.fillna(column.mean())