如何从具有多层头的Python数据帧中检索数据？

我有以下格式的CSV文件：

            Level1_head1    Level1_head2    Level1_head3
            Level2_head1    Level2_head2    Level2_head3 
ID
S0000001    someValue       someValue       someValue       
S0000002    someValue       someValue       someValue       
S0000003    someValue       someValue       someValue       
S0000004    someValue       someValue       someValue       
S0000005    someValue       someValue       someValue

请注意，

ID

上方的单元格是空的，

ID

右侧的单元格也是空的

我已将上述数据放入Python Dataframe对象

df

，并尝试从中提取列

ID

：

df = pd.read_csv("data.csv", header=[0,1], index_col=0)
date_series = df[0:]

但是，我得到了整个数据帧，而不是单个列。输出数据帧时，显示如下：

            Level2_head1    Level2_head2    Level2_head3 
ID
S0000001    someValue       someValue       someValue       
S0000002    someValue       someValue       someValue       
S0000003    someValue       someValue       someValue       
S0000004    someValue       someValue       someValue       
S0000005    someValue       someValue       someValue

我也试过：

date_series = df['ID']

及

然而，对于前者，我有一个键错误，

df

找不到值为'ID'的键。对于后者，我有一个错误，即

df

没有属性“ID”

---

我现在完全糊涂了。如何检索包含ID的第一列（ID）？

您不能使用

date\u series=df['ID']

，因为

ID

是

索引的
名称

但是使用get first column
index
到
Series
：

print df
         Level1_head1 Level1_head2 Level1_head3
         Level2_head1 Level2_head2 Level2_head3
ID                                             
S0000001    someValue    someValue    someValue
S0000002    someValue    someValue    someValue
S0000003    someValue    someValue    someValue
S0000004    someValue    someValue    someValue
S0000005    someValue    someValue    someValue

print df.index.name
ID

print df.index
Index([u'S0000001', u'S0000002', u'S0000003', u'S0000004', u'S0000005'], dtype='object', name=u'ID')

print df.index.to_series()
ID
S0000001    S0000001
S0000002    S0000002
S0000003    S0000003
S0000004    S0000004
S0000005    S0000005
Name: ID, dtype: object

#if you need reset index
print df.index.to_series().reset_index(drop=True)
0    S0000001
1    S0000002
2    S0000003
3    S0000004
4    S0000005
Name: ID, dtype: object

print pd.Series(df.index)
0    S0000001
1    S0000002
2    S0000003
3    S0000004
4    S0000005
Name: ID, dtype: object

或使用pd.Series的解决方案
：

print df
         Level1_head1 Level1_head2 Level1_head3
         Level2_head1 Level2_head2 Level2_head3
ID                                             
S0000001    someValue    someValue    someValue
S0000002    someValue    someValue    someValue
S0000003    someValue    someValue    someValue
S0000004    someValue    someValue    someValue
S0000005    someValue    someValue    someValue

print df.index.name
ID

print df.index
Index([u'S0000001', u'S0000002', u'S0000003', u'S0000004', u'S0000005'], dtype='object', name=u'ID')

print df.index.to_series()
ID
S0000001    S0000001
S0000002    S0000002
S0000003    S0000003
S0000004    S0000004
S0000005    S0000005
Name: ID, dtype: object

#if you need reset index
print df.index.to_series().reset_index(drop=True)
0    S0000001
1    S0000002
2    S0000003
3    S0000004
4    S0000005
Name: ID, dtype: object

print pd.Series(df.index)
0    S0000001
1    S0000002
2    S0000003
3    S0000004
4    S0000005
Name: ID, dtype: object

如果我的回答是有帮助的，别忘了，投赞成票。谢谢