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DS-1000 / 44 / I have a DataFrame like :

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Problem:
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

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

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

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

My real data size
df.shape
Out[117]: (54812040, 1522)

A:
<code>
import pandas as pd
import numpy as np

df = pd.DataFrame([[3,1,2],[np.nan,1,2],[np.nan,np.nan,2]],columns=['0','1','2'])
</code>
result = ... # put solution in this variable
BEGIN SOLUTION
<code>

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