Pandas：摆脱多索引
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Pandas: Get rid of multiindex
提问by ScientiaEtVeritas
After grouping and counting I'm trying to remove the multiindex like this:
分组和计数后，我试图删除这样的多索引：
df = df[['CID','FE', 'FID']].groupby(by=['CID','FE']).count()
.unstack().reset_index()
Printing the columns (df.colums) show that it is still a MultiIndex.
打印列 ( df.colums) 表明它仍然是一个 MultiIndex。
MultiIndex(levels=[['FID', 'CID'], [...]]
MultiIndex(levels=[['FID', 'CID'], [...]]
I can't access the column CIDvia df['CID']
我无法CID通过以下方式访问该列df['CID']
回答by jezrael
I think you need if is necessary convert MultiIndexto Index:
我认为如果有必要，您需要转换MultiIndex为Index：
df.columns = df.columns.map(''.join)
Or if need remove level use droplevel:
或者如果需要删除级别使用droplevel：
df.columns = df.columns.droplevel(0)
If need access to values is possible use xs:
如果需要访问值是可能的使用xs：
df = df.xs('CID', axis=1, level=1)
You can also check:
您还可以检查：
What is the difference between size and count in pandas?
EDIT:
编辑：
For remove MultiIndex is another solution select by ['FID'].
对于 remove MultiIndex 是另一个解决方案 select by ['FID']。
df = df.groupby(by=['CID','FE'])['FID'].count().unstack().reset_index()
Samples (also added rename_axisfor nicer output):
示例（还添加rename_axis了更好的输出）：
df = pd.DataFrame({'CID':[2,2,3],
'FE':[5,5,6],
'FID':[1,7,9]})
print (df)
CID FE FID
0 2 5 1
1 2 5 7
2 3 6 9
df = df.groupby(by=['CID','FE'])['FID']
.count()
.unstack()
.reset_index()
.rename_axis(None, axis=1)
print (df)
CID 5 6
0 2 2.0 NaN
1 3 NaN 1.0
回答by Allen
This should get rid of MultiIndex for CID and allow you to access it via df['CID']
这应该摆脱 CID 的 MultiIndex 并允许您通过 df['CID'] 访问它
df = df.rename(columns={('CID',''):'CID'})
