How to combine values in a row depending on value in another row in pandas

Question

I have a pandas dataframe with several columns (words, start time, stop time, speaker). I want to combine all values in the \'word\' column while the values in the \'speaker\' c

Answer 1

We'll use GroupBy.agg with a dict of aggfuncs:

(df.groupby('speaker', as_index=False, sort=False)
   .agg({'word': ' '.join, 'start': 'min', 'stop': 'max',}))

   speaker                word  start  stop
0        2  but that's alright   2.72  3.47
1        1       we'll have to   8.43  9.07

---

To group by consecutive occurrences, use the shifting cumsum trick, then use that as the second grouper along with "speaker":

gp1 = df['speaker'].ne(df['speaker'].shift()).cumsum()

(df.groupby(['speaker', gp1], as_index=False, sort=False)
   .agg({'word': ' '.join, 'start': 'min', 'stop': 'max',}))

   speaker                word  start   stop
0        2  but that's alright   2.72   3.47
1        1       we'll have to   8.43   9.07
2        2           okay sure   9.19  11.01
3        1               what?  11.02  12.00