Pandas，如何将多列组合成一个数组列
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Pandas, how to combine multiple columns into an array column
提问by Gnefihz Deng
I need to put a combined column as the concat of all values of the row.
我需要将一个组合列作为该行所有值的连接。
Source:
来源：
pd.DataFrame(data={
'a' : [1,2,3],
'b' : [2,3,4]
})
Target:
目标：
pd.DataFrame(data={
'a' : [1,2,3],
'b' : [2,3,4],
'combine' : [[1,2],[2,3],[3,4]]
})
Current solution:
当前解决方案：
test['combine'] = test[['a','b']].apply(lambda x: pd.Series([x.values]), axis=1)
Issues: I actually have many columns, it seems taking too long to run. Is it a better way.
问题：我实际上有很多列，运行时间似乎太长了。有没有更好的办法。
回答by cs95
df
a b
0 1 2
1 2 3
2 3 4
If you want to add a column of lists as a single column, you'll need to call the .valuesattribute, convert it to a nested list, and assign it back -
如果要将一列列表添加为单个列，则需要调用该.values属性，将其转换为嵌套列表，然后将其分配回 -
df['combine'] = df.values.tolist()
Or,
或者，
df['combine'] = df[['a', 'b']].values.tolist()
df
a b combine
0 1 2 [1, 2]
1 2 3 [2, 3]
2 3 4 [3, 4]
Note that just assigning the .valuesresult directly does not work, as pandasspecial casesnumpy arrays, leading to undesirable outcomes -
请注意，仅.values直接分配结果是行不通的，因为numpy 数组的pandas特殊情况会导致不良结果 -
df['combine'] = df[['a', 'b']].values
ValueError: Wrong number of items passed 2, placement implies 1
A couple of notes -
一些注意事项 -
try not to use
apply/transformas much as possible. It is only a convenience function meant to hide the application of a loop, and is slow, offering no performance/vectorization benefits whatoseverkeeping columns of `objects offers no performance gains as far as pandas is concerned, so unless the goal is to display data, try to avoid it.
尽量不要使用
apply/transform。它只是一个方便的函数，旨在隐藏循环的应用程序，而且速度很慢，没有任何性能/矢量化优势就 Pandas 而言，保留 `objects 列不会带来性能提升，所以除非目标是显示数据，否则尽量避免它。
