Creating a new column in Panda by using lambda function on two existing columns
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 bdf['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 3Next 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)