To dear contributors: It's recommended to go through the comments in #10483 (e.g., #10483 (comment))

Newbie here! Can I work on this?

@gilbertoolimpio go ahead please

@qinhanmin2014 and @jnothman I need help, I'm a little confused, should I remove all mentions from the SimpleImputer axis only in the documentation? And besides, could you help me how could be the comment that the axis was removed?

In the code the axis often appears as axis = 0, should I change to None or delete these entries as well?

For example in the code below (in impute.py class SimpleImpute) should I remove these entries from the axis parameter or set None?

    def __init__(self, missing_values="NaN", strategy="mean",
                 axis=0, verbose=0, copy=True):
        self.missing_values = missing_values
        self.strategy = strategy
        self.axis = axis
        self.verbose = verbose
        self.copy = copy

tks! =)

Because this is not released code, it can be safely removed without breaking backwards compatibility. Just drop axis there. Don't worry about looking at the previous work and comments too much.

Yes, you need to remove from the documentation too, if necessary adjusting the wording to say imputation is done over each column.

In terms of adding a comment on axis being removed, we ultimately want to say something like "sklearn.preprocessing.Imputer has been renamed to sklearn.impute.SimpleImputer, and its axis parameter is no longer available. The deprecated Imputer will be removed in version 0.22." in doc/whats_new/v0.20.rst where the deprecation of Imputer is currently mentioned (but you can use your own words). A mention of axis disappearing is also appropriate in the deprecation warning at

We might also want to help users a bit more and say

Future (and default) behavior is equivalent to ``axis=0``
(impute along columns). Row-wise imputation can be performed with
FunctionTransformer (e.g.,
``FunctionTransformer(lambda X: Imputer().fit_transform(X.T).T)``).

in what's new.

First Time Contributor. Can I look into this issue?

@bhaveshpoddar94 Someone has taken the issue. See the above PR which refers to the issue.