How to concat multiple Pandas DataFrame columns with different token separator?

Question

I am trying to concat multiple Pandas DataFrame columns with different tokens.

For example, my dataset looks like this :

dataframe = pd.DataFrame({'col_1' : ['aaa','bbb','ccc','ddd'], 
                          'col_2' : ['name_aaa','name_bbb','name_ccc','name_ddd'], 
                          'col_3' : ['job_aaa','job_bbb','job_ccc','job_ddd']})

I want to output something like this:

    features
0   aaa <0> name_aaa <1> job_aaa
1   bbb <0> name_bbb <1> job_bbb
2   ccc <0> name_ccc <1> job_ccc
3   ddd <0> name_ddd <1> job_ddd

Explanation :

concat each column with "<{}>" where {} will be increasing numbers.

What I've tried so far:

I don't want to modify original DataFrame so I created two new dataframe:

features_df = pd.DataFrame()
final_df    = pd.DataFrame()
for iters in range(len(dataframe.columns)):
    features_df[dataframe.columns[iters]] = dataframe[dataframe.columns[iters]] + ' ' + "<{}>".format(iters)
final_df['features'] = features_df[features_df.columns].agg(' '.join, axis=1)

There is an issue I am facing, It's adding <2> at last but I want output like above, also this is not panda's way to do this task, How I can make it more efficient?

Answer 1

from itertools import chain

dataframe['features'] = dataframe.apply(lambda x: ''.join([*chain.from_iterable((v, f' <{i}> ') for i, v in enumerate(x))][:-1]), axis=1)

print(dataframe)

Prints:

  col_1     col_2    col_3                      features
0   aaa  name_aaa  job_aaa  aaa <0> name_aaa <1> job_aaa
1   bbb  name_bbb  job_bbb  bbb <0> name_bbb <1> job_bbb
2   ccc  name_ccc  job_ccc  ccc <0> name_ccc <1> job_ccc
3   ddd  name_ddd  job_ddd  ddd <0> name_ddd <1> job_ddd