Join two pandas dataframes on timestamps

Question

I have two pandas dataframes, identical in columns. Each have a timestamp column. One dataframe has text data from user A and another dataframe has text data from user B. When user A is speaking, user B is not speaking, so the data never overlaps. I want to merge them together into one dataframe organized by timestamp.

 df_a start stop words 0 2.1 i know honey but what happened we got a job 3.7 6.4 no know but thats a different kind of help but 8.2 11.5 because people that are supposed to be 12.9 15.4 yeah but where else can you go to get one df_b start stop words 2.2 3.6 but he never said 6.5 8.2 but what? 11.6 12.8 i dont think thats true 15.5 19.2 anywhere i dont know desired_output start stop words 0 2.1 i know honey but what happened we got a job 2.2 3.6 but he never said 3.7 6.4 no know but thats a different kind of help but 6.5 8.2 but what? 8.2 11.5 because people that are supposed to be 11.6 12.8 i dont think thats true 12.9 15.4 yeah but where else can you go to get one 15.5 19.2 anywhere i dont know

Answer 1

这应该做：

df = df_a.append(df_b).sort_values(by=['start'])

Answer 2

I would use pd.concat given the operation feels more like concatenating rather than joining:

output = pd.concat([df_a,df_b]).sort_values(['start'])
print(output)
   start  stop                                           words
0    0.0   2.1     i know honey but what happened we got a job
0    2.2   3.6                               but he never said
1    3.7   6.4  no know but thats a different kind of help but
1    6.5   8.2                                       but what?
2    8.2  11.5          because people that are supposed to be
2   11.6  12.8                         i dont think thats true
3   12.9  15.4       yeah but where else can you go to get one
3   15.5  19.2                            anywhere i dont know