Pandas: Optimizing Some Python Code By Getting Rid Of DataFrame.apply()

the following code is produced using python 2.7 and pandas 0.9.1. I have a dataframe with two columns 'minor' and 'major'. I calculate the 'critical' value by taking the max absolu

Solution 1:

Random thoughts: to get the indices, you can use .idxmax instead of max, namely

>>> w = df[['minor','major']].abs().idxmax(axis=1)
>>> w
10    minor
20    major
30    minor
dtype: object

and then you could use lookup (there's probably something simpler, but I'm missing it right now):

>>> df.lookup(df.index, w)
array([ -6. ,   3. ,  19.2])

IOW:

>>> df['critic_vector'] = df[['minor','major']].abs().idxmax(axis=1)
>>> df['critic'] = abs(df.lookup(df.index, df.critic_vector))
>>> df
    major  minor critic_vector  critic
10    2.0   -6.0         minor     6.0
20    3.0   -2.3         major     3.0
30    7.4   19.2         minor    19.2

I'm not super-happy with the lookup line -- you could replace it with your original max call, of course -- but I think the idxmax approach isn't a bad one.