本文介绍了Pandas Dataframe 检查列值是否在列列表中的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一个数据框 df
:
data = {'id':[12,112],
'idlist':[[1,5,7,12,112],[5,7,12,111,113]]
}
df=pd.DataFrame.from_dict(data)
看起来像这样:
id idlist
0 12 [1, 5, 7, 12, 112]
1 112 [5, 7, 12, 111, 113]
我需要检查 id
是否在 idlist
中,然后选择或标记它.我尝试了以下变体并收到评论错误:
I need to check and see if id
is in the idlist
, and select or flag it. I have tried variations of the following and receive the commented error:
df=df.loc[df.id.isin(df.idlist),:] #TypeError: unhashable type: 'list'
df['flag']=df.where(df.idlist.isin(df.idlist),1,0) #TypeError: unhashable type: 'list'
一些可能的解决方案的其他方法是 .apply
在列表理解中?
Some possible other methods to a solution would be .apply
in a list comprehension?
我在这里寻找解决方案,要么选择 id
在 idlist
中的行,要么用 1 标记该行,其中 id
在 idlist
中.结果 df
应该是:
I am looking for a solution here that either selects the rows where id
is in idlist
, or flags the row with a 1 where id
is in idlist
. The resulting df
should be either:
id idlist
0 12 [1, 5, 7, 12, 112]
或:
flag id idlist
0 1 12 [1, 5, 7, 12, 112]
1 0 112 [5, 7, 12, 111, 113]
感谢您的帮助!
推荐答案
使用apply
:
df['flag'] = df.apply(lambda x: int(x['id'] in x['idlist']), axis=1)
print (df)
id idlist flag
0 12 [1, 5, 7, 12, 112] 1
1 112 [5, 7, 12, 111, 113] 0
类似:
df['flag'] = df.apply(lambda x: x['id'] in x['idlist'], axis=1).astype(int)
print (df)
id idlist flag
0 12 [1, 5, 7, 12, 112] 1
1 112 [5, 7, 12, 111, 113] 0
使用列表推导
:
df['flag'] = [int(x[0] in x[1]) for x in df[['id', 'idlist']].values.tolist()]
print (df)
id idlist flag
0 12 [1, 5, 7, 12, 112] 1
1 112 [5, 7, 12, 111, 113] 0
过滤解决方案:
Solutions for filtering:
df = df[df.apply(lambda x: x['id'] in x['idlist'], axis=1)]
print (df)
id idlist
0 12 [1, 5, 7, 12, 112]
df = df[[x[0] in x[1] for x in df[['id', 'idlist']].values.tolist()]]
print (df)
id idlist
0 12 [1, 5, 7, 12, 112]
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