我有一个数据框,其中包含如下信息
>>> Results.Category[:5]
0 issue delivery wrong master account
1 data wrong master account batch
2 order delivery wrong data account
3 issue delivery wrong master account
4 delivery wrong master account batch
Name: Category, dtype: object
现在我要在“类别”列中保留唯一的单词 例如 : 在第一行中出现单词“ wrong”,我想从其余所有行中删除它,而仅在第一行中保留单词“ wrong” 在第二行中有“数据”一词,然后我想从其余所有行中删除它,而仅在第二行中保留“数据”一词
我发现,如果行中有重复项,我们可以使用下面的内容删除,但是我需要从列中删除重复的单词,有人可以在这里帮助我。
AFResults['FinalCategoryN'] = AFResults['FinalCategory'].apply(lambda x: remove_dup(x))
答案 0 :(得分:3)
似乎您想要类似的东西,
out = []
seen = set()
for c in df['Category']:
words = c.split()
out.append(' '.join([w for w in words if w not in seen]))
seen.update(words)
df['FinalCategoryN'] = out
df
Category FinalCategoryN
0 issue delivery wrong master account issue delivery wrong master account
1 data wrong master account batch data batch
2 order delivery wrong data account order
3 issue delivery wrong master account
4 delivery wrong master account batch
如果您不关心顺序,则可以使用set逻辑:
u = df['Category'].apply(str.split)
v = split.shift().map(lambda x: [] if x != x else x).cumsum().map(set)
(u.map(set) - v).str.join(' ')
0 account delivery issue master wrong
1 batch data
2 order
3
4
Name: Category, dtype: object
答案 1 :(得分:2)
在这种情况下,您首先需要split
,然后通过drop_duplicates
删除重复项
df.c.str.split(expand=True).stack().drop_duplicates().\
groupby(level=0).apply(','.join).reindex(df.index)
Out[206]:
0 issue,delivery,wrong,master,account
1 data,batch
2 order
3 NaN
4 NaN
dtype: object
答案 2 :(得分:1)
您无法向量化的内容,所以让我们忘了熊猫,然后使用Python set
:
total = set()
result = []
for line in AFResults['FinalCategory']:
line = set(line.split()).difference(total)
total = total.union(line)
result.append(' '.join(line))
您将获得以下列表:['wrong issue master delivery account', 'batch data', 'order', '', '']
您可以使用它来填充数据框列:
AFResults['FinalCategoryN'] = result
答案 3 :(得分:0)
将apply
与sorted
和set
以及str.join
和list.index
一起使用:
AFResults['FinalCategoryN'] = AFResults['FinalCategory'].apply(lambda x: ' '.join(sorted(set(x.split()), key=x.index)))