将NaN移至其各自行的末尾 [英] Shift NaNs to the end of their respective rows

问题描述

我有一个DataFrame:

I have a DataFrame like :

     0    1    2
0  0.0  1.0  2.0
1  NaN  1.0  2.0
2  NaN  NaN  2.0

---

我想得到的是

---

What I want to get is

Out[116]: 
     0    1    2
0  0.0  1.0  2.0
1  1.0  2.0  NaN
2  2.0  NaN  NaN

---

这是我目前的做法.

---

This is my approach as of now.

df.apply(lambda x : (x[x.notnull()].values.tolist()+x[x.isnull()].values.tolist()),1)
Out[117]: 
     0    1    2
0  0.0  1.0  2.0
1  1.0  2.0  NaN
2  2.0  NaN  NaN

---

有没有有效的方法来实现这一目标? apply这是减慢速度的方法. 谢谢您的助手！:)

---

Is there any efficient way to achieve this ? apply Here is way to slow . Thank you for your assistant!:)

我的真实数据大小

df.shape
Out[117]: (54812040, 1522)

推荐答案

以下是使用 justify -

Here's a NumPy solution using justify -

In [455]: df
Out[455]: 
     0    1    2
0  0.0  1.0  2.0
1  NaN  1.0  2.0
2  NaN  NaN  2.0

In [456]: pd.DataFrame(justify(df.values, invalid_val=np.nan, axis=1, side='left'))
Out[456]: 
     0    1    2
0  0.0  1.0  2.0
1  1.0  2.0  NaN
2  2.0  NaN  NaN

如果要保存内存，请改回分配-

If you want to save memory, assign it back instead -

df[:] = justify(df.values, invalid_val=np.nan, axis=1, side='left')

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