这是我的数据框架
CATEGORY BRAND
0 Noodle Anak Mas
1 Noodle Anak Mas
2 Noodle Indomie
3 Noodle Indomie
4 Noodle Indomie
23 Noodle Indomie
24 Noodle Mi Telor Cap 3
25 Noodle Mi Telor Cap 3
26 Noodle Pop Mie
27 Noodle Pop Mie
...
我已经确保df类型是string,我的代码是
df = data[['CATEGORY', 'BRAND']].astype(str)
import collections, re
texts = df
bagsofwords = [ collections.Counter(re.findall(r'\w+', txt))
for txt in texts]
sumbags = sum(bagsofwords, collections.Counter())
当我打电话的时候
sumbags
输出为
Counter({'BRAND': 1, 'CATEGORY': 1})
我希望所有的数据都以sumbags的形式统计,除了标题,以使其清晰一些,比如
Counter({'Noodle': 10, 'Indomie': 4, 'Anak': 2, ....}) # because it is bag of words
我需要每一个字都算数
最佳答案
IIUIC,使用
选项1]numpyflatten
和split
In [2535]: collections.Counter([y for x in df.values.flatten() for y in x.split()])
Out[2535]:
Counter({'3': 2,
'Anak': 2,
'Cap': 2,
'Indomie': 4,
'Mas': 2,
'Mi': 2,
'Mie': 2,
'Noodle': 10,
'Pop': 2,
'Telor': 2})
选项2]
使用
value_counts()
In [2536]: pd.Series([y for x in df.values.flatten() for y in x.split()]).value_counts()
Out[2536]:
Noodle 10
Indomie 4
Mie 2
Pop 2
Anak 2
Mi 2
Cap 2
Telor 2
Mas 2
3 2
dtype: int64
选项3]
使用
stack
和value_counts
In [2582]: df.apply(lambda x: x.str.split(expand=True).stack()).stack().value_counts()
Out[2582]:
Noodle 10
Indomie 4
Mie 2
Pop 2
Anak 2
Mi 2
Cap 2
Telor 2
Mas 2
3 2
dtype: int64
细节
In [2516]: df
Out[2516]:
CATEGORY BRAND
0 Noodle Anak Mas
1 Noodle Anak Mas
2 Noodle Indomie
3 Noodle Indomie
4 Noodle Indomie
23 Noodle Indomie
24 Noodle Mi Telor Cap 3
25 Noodle Mi Telor Cap 3
26 Noodle Pop Mie
27 Noodle Pop Mie
关于python - 如何从 Pandas 数据框中创建一个单词包,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/46360435/