此问题是this的另一部分。所以我将其添加为新问题
如果我的数据框B类似于:
ID category words bucket_id
1 audi a4, a6 94
2 bugatti veyron, chiron 86
3 mercedez s-class, e-class 79
4 dslr canon, nikon 69
5 apple iphone,macbook,ipod 51
6 finance sales,loans,sales price 12
7 politics trump, election, votes 77
8 entertainment spiderman,thor, ironmen 88
9 music beiber, rihana,drake 14
........ ..............
......... .........
我想要映射的类别及其对应的列ID作为字典。像这样:-
{'id': 2, 'term': 'bugatti', 'bucket_id': 86}
{'id': 3, 'term': 'mercedez', 'bucket_id': 79}
{'id': 6, 'term': 'finance', 'bucket_id': 12}
{'id': 7, 'term': 'politics', 'bucket_id': 77}
{'id': 9, 'term': 'music', 'bucket_id': 14}
答案 0 :(得分:1)
编辑:
df = pd.DataFrame({'ID': [1, 2, 3],
'category': ['bugatti', 'entertainment', 'mercedez'],
'words': ['veyron,chiron', 'spiderman,thor,ironmen',
's-class,e-class,s-class'],
'bucket_id': [94, 86, 79]})
print (df)
ID category words bucket_id
0 1 bugatti veyron,chiron 94
1 2 entertainment spiderman,thor,ironmen 86
2 3 mercedez s-class,e-class,s-class 79
A = ['veyron','s-class','derman']
idx = [i for i, x in enumerate(df['words']) for y in x.split(',') if y in A]
print (idx)
[0, 2, 2]
L = (df.loc[idx, ['ID','category','bucket_id']]
.rename(columns={'category':'term'})
.to_dict(orient='r'))
print (L)
[{'ID': 1, 'term': 'bugatti', 'bucket_id': 94},
{'ID': 3, 'term': 'mercedez', 'bucket_id': 79},
{'ID': 3, 'term': 'mercedez', 'bucket_id': 79}]