如何将pandas dataframe列连接到可迭代列表？

Question

I'm working with a pandas dataframe with about 200 columns. 我正在使用大约200列的pandas数据帧。 Columns 31-73 look something like this: 第31-73列看起来像这样：

31   32   33
NaN  NaN  Z
X    NaN  Z
NaN  NaN  NaN
NaN  Y    Z

What I hope to return is a new column that looks (something) like this: 我希望返回的是一个看起来像这样的新列：

new_col
[Z]
[X,Z]
[]
[Y,Z]

I'm close, but not quite there. 我很亲密，但并不完全。 This code: 这段代码：

data['new_col'] = data.ix[:, 30:73].fillna('').apply(lambda row: ','.join(map(str, row)), axis=1)

returns this: 返回：

new_col
,,Z
,X,,Z
,,,
,,Y,Z

How can I exclude unnecessary delimiters from the new concatenated list? 如何从新的连接列表中排除不必要的分隔符？

Answer 1

You seem to have an errant value Nan which I'm assuming is NaN , anyway this should work: 你似乎有一个错误的价值Nan ，我假设是NaN ，无论如何这应该工作：

In [24]:
df.apply(lambda x: [','.join(x.dropna())], axis=1)

Out[24]:
0      [Z]
1    [X,Z]
2       []
3    [Y,Z]
dtype: object

So in your case: 所以在你的情况下：

data['new_col'] = data.apply(lambda x: [','.join(x.dropna())], axis=1)

should work. 应该管用。