temp = df.groupby(‘date’)[‘t’].cumsum().rename(‘t_cumulative’) df = df.merge(temp, on=’date_time’, how=’outer’) solved Calculate cumulative intraday measures that reset every day in pandas
You could run one apply() which will use for-loop to convert list to Series with headers – it can use enumerate to put correct number in headers. Because some rows have less participants so it puts NaN which you can later fill with empty strings. And next you can use join() to add all as … Read more
You can use groupby and join to create the expected output. One way is to create a column to_join from the columns Tri_gram_sents and Value, and then agg this column: df[‘to_join’] = df[‘Tri_gram_sents’] + ‘ ‘ + df[‘Value’].astype(str) ser_output = df.groupby(‘sentence’)[‘to_join’].agg(‘ ‘.join) Or you can do everything in one line without create the column with … Read more