Creating a new column in Panda by using lambda function on two existing columns

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You can use function map and select by function np.where more info

print df
#     a     b
#0  aaa  rrrr
#1   bb     k
#2  ccc     e
#condition if condition is True then len column a else column b
df['c'] = np.where(df['a'].map(len) > df['b'].map(len), df['a'].map(len), df['b'].map(len))
print df
#     a     b  c
#0  aaa  rrrr  4
#1   bb     k  2
#2  ccc     e  3

Next solution is with function apply with parameter axis=1:

axis = 1 or ‘columns’: apply function to each row

df['c'] = df.apply(lambda x: max(len(x['a']), len(x['b'])), axis=1)

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