Filling NaNs in a financial dataset

[larzz]

Yeah I did some additions. Do you think you can help if I upload that one?

Maybe,but not sure as it hard a task when DataFrame is 500 columns wide.
Than at least i or someone else can may take a look at look it.
If you could make the task wanted in smaller scale,it would be fine.
A example of this could be like this.

import pandas as pd

df = pd.read_clipboard()
'''
          A         B         C
0 -0.166919  0.979728 -0.632955
1 -0.297953 -0.912674 -1.365463
2 -0.120211 -0.540679 -0.680481
3       NaN -2.027325  1.533582
4       NaN       NaN  0.461821
5 -0.788073       NaN       NaN
6 -0.916080 -0.612343       NaN
7 -0.887858  1.033826       NaN
8  1.948430  1.025011 -2.982224
9  0.019698 -0.795876 -0.046431
'''

So here have DataFrame with some NaN values,an want to fill in with average values that columns has.

>>> df
          A         B         C
0 -0.166919  0.979728 -0.632955
1 -0.297953 -0.912674 -1.365463
2 -0.120211 -0.540679 -0.680481
3       NaN -2.027325  1.533582
4       NaN       NaN  0.461821
5 -0.788073       NaN       NaN
6 -0.916080 -0.612343       NaN
7 -0.887858  1.033826       NaN
8  1.948430  1.025011 -2.982224
9  0.019698 -0.795876 -0.046431
>>> df.mean()
A   -0.151121
B   -0.231291
C   -0.530307
dtype: float64
>>> df.fillna(df.mean())
          A         B         C
0 -0.166919  0.979728 -0.632955
1 -0.297953 -0.912674 -1.365463
2 -0.120211 -0.540679 -0.680481
3 -0.151121 -2.027325  1.533582
4 -0.151121 -0.231291  0.461821
5 -0.788073 -0.231291 -0.530307
6 -0.916080 -0.612343 -0.530307
7 -0.887858  1.033826 -0.530307
8  1.948430  1.025011 -2.982224
9  0.019698 -0.795876 -0.046431

I have a bigger file that isn't allowed to be uploaded through this site so I did it like this:

https://file.io/cNtj51B5Tswo

If it isn't allowed you can just remove it. This contains 1000 rows of the dataframe I am currently using. I understand that making the task on a smaller scale would be easier, but it shouldn't be that hard to upscale right?