另一个熊猫问题：
我有这个带有分层索引的表：
In [51]:
from pandas import DataFrame
f = DataFrame({'a': ['1','2','3'], 'b': ['2','3','4']})
f.columns = [['level1 item1', 'level1 item2'],['', 'level2 item2'], ['level3 item1', 'level3 item2']]
f
Out[51]:
level1 item1 level1 item2
level2 item2
level3 item1 level3 item2
0 1 2
1 2 3
2 3 4
碰巧选择level1 item1会产生以下错误：
In [58]: f['level1 item1']
AssertionError: Index length did not match values
不过，这似乎和关卡的数量有些关系。当我将级别数减少到只有两个时，就没有这样的错误：
from pandas import DataFrame
f = DataFrame({'a': ['1','2','3'], 'b': ['2','3','4']})
f.columns = [['level1 item1', 'level1 item2'],['', 'level1 item2']]
f
Out[59]:
level1 item1 level1 item2
level1 item2
0 1 2
1 2 3
2 3 4
相反，前面的 DataFrame 给出了预期的系列：
In [63]:
f['level1 item1']
Out[63]:
0 1
1 2
2 3
Name: level1 item1
用虚拟字符填充下面level1 item1的空白“修复”了这个问题，但这不是一个好的解决方案。
如何在不使用虚拟名称填充这些列的情况下解决此问题？
非常感谢！
原始示例：
该表是使用以下索引生成的：
index = [np.array(['Size and accumulated size of adjusted gross income', 'All returns', 'All returns', 'All returns', 'All returns', 'All returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns']),
np.array(['', 'Number of returns', 'Percent of total', 'Adjusted gross income less deficit', 'Adjusted gross income less deficit', 'Adjusted gross income less deficit', 'Number of returns', 'Percent of total', 'Adjusted gross income less deficit', 'Adjusted gross income less deficit', 'Taxable income', 'Taxable income', 'Taxable income', 'Income tax after credits', 'Income tax after credits', 'Income tax after credits', 'Total income tax', 'Total income tax', 'Total income tax', 'Total income tax', 'Total income tax']),
np.array(['', '', '', '', '', '', '', '','', '', 'Number of returns', 'Amount', 'Percent of total', 'Number of returns', 'Amount', 'Percent of total', 'Amount', 'Percent of', 'Percent of', 'Percent of', 'Average total income tax (dollars)']),
np.array(['', '', '', 'Amount', 'Percent of total', 'Average (dollars)', 'Average (dollars)', 'Average (dollars)', 'Amount', 'Percent of total', 'Percent of total', 'Percent of total', 'Percent of total', 'Percent of total', 'Percent of total', 'Percent of total', 'Percent of total', 'Total', 'Taxable income', 'Adjusted gross income less deficit', 'Adjusted gross income less deficit'])]
df.columns = index
这是 CSV 文件中某些数据的几乎完美副本，但您可以看到在“退货数量”、“占总收入的百分比”和“调整后的总收入减去赤字”下方存在差距。当我尝试选择退货数量时，该差距会产生此错误：
In [68]: df['Taxable returns']['Number of returns']
AssertionError: Index length did not match values
我不明白这个错误。所以一个很好的解释将不胜感激。无论如何，当我使用这个索引填补这个空白时（注意第三个 numpy 数组中的第一个元素）：
index = [np.array(['Size and accumulated size of adjusted gross income', 'All returns', 'All returns', 'All returns', 'All returns', 'All returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns', 'Taxable returns']),
np.array(['', 'Number of returns', 'Percent of total', 'Adjusted gross income less deficit', 'Adjusted gross income less deficit', 'Adjusted gross income less deficit', 'Number of returns', 'Percent of total', 'Adjusted gross income less deficit', 'Adjusted gross income less deficit', 'Taxable income', 'Taxable income', 'Taxable income', 'Income tax after credits', 'Income tax after credits', 'Income tax after credits', 'Total income tax', 'Total income tax', 'Total income tax', 'Total income tax', 'Total income tax']),
np.array(['1', '2', '3', '4', '5', '6', '7', '8','9', '10', 'Number of returns', 'Amount', 'Percent of total', 'Number of returns', 'Amount', 'Percent of total', 'Amount', 'Percent of', 'Percent of', 'Percent of', 'Average total income tax (dollars)']),
np.array(['', '', '', 'Amount', 'Percent of total', 'Average (dollars)', 'Average (dollars)', 'Average (dollars)', 'Amount', 'Percent of total', 'Percent of total', 'Percent of total', 'Percent of total', 'Percent of total', 'Percent of total', 'Percent of total', 'Percent of total', 'Total', 'Taxable income', 'Adjusted gross income less deficit', 'Adjusted gross income less deficit'])]
df.columns = index
我得到正确的结果：
In [71]: df['Taxable returns']['Number of returns']
Out[71]:
7
Average (dollars)
0 90,660,104
1 3,495
...