Update row values where certain condition is met in pandas

Say I have the following dataframe:

table

What is the most efficient way to update the values of the columns feat and another_feat where the stream is number 2?

Is this it?

    for index, row in df.iterrows():
        if df1.loc[index,'stream'] == 2:
           # do something

UPDATE: What to do if I have more than a 100 columns? I don't want to explicitly name the columns that I want to update. I want to divide the value of each column by 2 (except for the stream column).

So to be clear what my goal is:

Dividing all values by 2 of all rows that have stream 2, but not changing the stream column

I think you can use loc if you need update two columns to same value:

    df1.loc[df1['stream'] == 2, ['feat','another_feat']] = 'aaaa'
    print df1
       stream        feat another_feat
    a       1  some_value   some_value
    b       2        aaaa         aaaa
    c       2        aaaa         aaaa
    d       3  some_value   some_value

If you need update separate, one option is use:

    df1.loc[df1['stream'] == 2, 'feat'] = 10
    print df1
       stream        feat another_feat
    a       1  some_value   some_value
    b       2          10   some_value
    c       2          10   some_value
    d       3  some_value   some_value

Another common option is use numpy.where:

    df1['feat'] = np.where(df1['stream'] == 2, 10,20)
    print df1
       stream  feat another_feat
    a       1    20   some_value
    b       2    10   some_value
    c       2    10   some_value
    d       3    20   some_value

EDIT: If you need divide all columns without stream where condition is True, use:

    print df1
       stream  feat  another_feat
    a       1     4             5
    b       2     4             5
    c       2     2             9
    d       3     1             7

    #filter columns all without stream
    cols = [col for col in df1.columns if col != 'stream']
    print cols
    ['feat', 'another_feat']

    df1.loc[df1['stream'] == 2, cols ] = df1 / 2
    print df1
       stream  feat  another_feat
    a       1   4.0           5.0
    b       2   2.0           2.5
    c       2   1.0           4.5
    d       3   1.0           7.0

From: stackoverflow.com/q/36909977