我想调整数据
我现在有这样的话：
Yan TNSeq Kato Eco-GeneOrth Essential
accA accA accA accA accA
accB accB accB accB accB
accC accC accC accC accC
accD accD accD accD accD
aceF acpP acpP alaS aceF
acpP acpS acpS argA acpP
acpS adk adk argB acpS
我想要的是：
Yan TNSeq Kato Eco-GeneOrth Essential
accA accA accA accA accA
accB accB accB accB accB
accC accC accC accC accC
accD accD accD accD accD
aceF NaN NaN Nan aceF
acpP NaN Nan acpP acpP
NaN acpS NaN NaN acpS
我尝试过reindex并排序，但没有运气
我很无能
基本上我想要的是将前4列与Essential列对齐或排序，以便行中的数据匹配。
答案 0 :(得分：1)
<强>更新
In [120]: df[df.apply(lambda x: x['Essential'] == x, axis=1)]
Out[120]:
Yan TNSeq Kato Eco-GeneOrth Essential
0 accA accA accA accA accA
1 accB accB accB accB accB
2 accC accC accC accC accC
3 accD accD accD accD accD
4 aceF NaN NaN NaN aceF
5 acpP NaN NaN NaN acpP
6 acpS NaN NaN NaN acpS
试试这个：
In [86]: df[df.apply(lambda x: x[0] == x, axis=1)]
Out[86]:
Yan TNSeq Kato Eco-GeneOrth Essential
0 accA accA accA accA accA
1 accB accB accB accB accB
2 accC accC accC accC accC
3 accD accD accD accD accD
4 aceF NaN NaN NaN aceF
5 acpP NaN NaN NaN acpP
6 acpS NaN NaN NaN acpS
数据：
In [87]: df
Out[87]:
Yan TNSeq Kato Eco-GeneOrth Essential
0 accA accA accA accA accA
1 accB accB accB accB accB
2 accC accC accC accC accC
3 accD accD accD accD accD
4 aceF acpP acpP alaS aceF
5 acpP acpS acpS argA acpP
6 acpS adk adk argB acpS
答案 1 :(得分：0)
IIUC使用eq并使用arg axis=0传递您的列，以针对该列创建整个df的布尔掩码：
In [49]:
df[df.eq(df['Essential'],axis=0)]
Out[49]:
Yan TNSeq Kato Eco-GeneOrth Essential
0 accA accA accA accA accA
1 accB accB accB accB accB
2 accC accC accC accC accC
3 accD accD accD accD accD
4 aceF NaN NaN NaN aceF
5 acpP NaN NaN NaN acpP
6 acpS NaN NaN NaN acpS