Question has been posted before but the requirements were not properly conveyed. I have a csv file with more than 1000 columns:

A   B   C   D ....  X   Y   Z
1   0   0.5 5 ....  1   7   6
2   0   0.6 4 ....  0   7   6
3   0   0.7 3 ....  1   7   6
4   0   0.8 2 ....  0   7   6

Here X , Y and Z are the 999, 1000, 10001 column and A, B, C , D are the 1st,2nd,3rd and 4th. I need to reorder the columns in such a way that it gives me the following.

D   Y   Z   A   B   C   ....X
5   7   6   1   0   0.5 ....1
4   7   6   2   0   0.6 ....0
3   7   6   3   0   0.7 ....1
2   7   6   4   0   0.8 ....0

that is 4th column becomes the 1st, 1000 and 1001th column becomes 2nd and 3rd and the other columns are shifted right accordingly.

So the question is how to reorder your columns in a custom way.

For example you have the following DF and you want to reorder your columns in the following way (indices):

5, 3, rest...

DF

In [82]: df
Out[82]:A  B    C  D  E  F  G
0  1  0  0.5  5  1  7  6
1  2  0  0.6  4  0  7  6
2  3  0  0.7  3  1  7  6
3  4  0  0.8  2  0  7  6

columns

In [83]: cols = df.columns.tolist()In [84]: cols
Out[84]: ['A', 'B', 'C', 'D', 'E', 'F', 'G']

reordered:

In [88]: cols = [cols.pop(5)] + [cols.pop(3)] + colsIn [89]: cols
Out[89]: ['F', 'D', 'A', 'B', 'C', 'E', 'G']In [90]: df[cols]
Out[90]:F  D  A  B    C  E  G
0  7  5  1  0  0.5  1  6
1  7  4  2  0  0.6  0  6
2  7  3  3  0  0.7  1  6
3  7  2  4  0  0.8  0  6