Первый столбец извлечения по DataFrame.pop
, Series.str.split
, DataFrame.stack
для Series
и DataFrame.join
к оригиналу, затем удалите дубликаты по DataFrame.drop_duplicates
и агрегируйте по GroupBy.agg
с подсчетами и sum
:
s = (df.pop('text')
.str.split(expand=True)
.stack()
.reset_index(1, drop=True)
.rename('text'))
df1 = (df.join(s)
.reset_index(drop=True)
.drop_duplicates(['id','text'])
.groupby('text', sort=False)['c1']
.agg([('Totalcount','size'),('Points','sum')])
.reset_index()
.rename(columns={'text':'Word'}))
print (df1)
Word Totalcount Points
0 Hello 2 2
1 world 1 1
2 how 1 1
3 are 1 1
4 you 1 1
5 people 3 1
6 I 1 1
7 am 1 1
8 fine 1 1
9 Good 2 -2
10 Morning 1 -1
11 Evening 1 -1
РЕДАКТИРОВАТЬ:
Для повышения производительности используйте chain.from_iterable
с numpy.repeat
:
from itertools import chain
splitted = [x.split() for x in df['text']]
lens = [len(x) for x in splitted]
df = pd.DataFrame({
'Word' : list(chain.from_iterable(splitted)),
'id' : df['id'].values.repeat(lens),
'c1' : df['c1'].values.repeat(lens)
})
df1 = (df.drop_duplicates(['id','Word'])
.groupby('Word', sort=False)['c1']
.agg([('Totalcount','size'),('Points','sum')])
.reset_index())
print (df1)
Word Totalcount Points
0 Hello 2 2
1 world 1 1
2 how 1 1
3 are 1 1
4 you 1 1
5 people 3 1
6 I 1 1
7 am 1 1
8 fine 1 1
9 Good 2 -2
10 Morning 1 -1
11 Evening 1 -1