apporach a huge matrix data: Python or R or MATLAB

[bio_informatics]

I have file which looks like:
*tab separated*

0 0.11692212 0.12066375 0.1096388
0.11692212 0 0.09939274 0.0684602
0.12066375 0.09939274 0 0.13651687
0.1096388 0.0684602 0.13651687 0

In essence it means:

A B C D
A 0 0.11692212 0.12066375 0.1096388
B 0.11692212 0 0.09939274 0.0684602
C 0.12066375 0.09939274 0 0.13651687
D 0.1096388 0.0684602 0.13651687 0

Value of A against A, value of A against B,
Value of B against A, and so on..
Where value for A against B is same as B against A, and further for other columns and row applies the same.

I have a file with 350X350 or 490X490 matrix numbers, which follow the exact same pattern as above.
How do I approach such set if I got to have say top 4 or top 10 values with their row and column number.

Should I proceed with Python [ I work in python] or any statistical tool? R or MATLAB?

I know this doesn't relate to Bioinformatics, or NGS, but approach sometimes means a lot.

[dpryan]

With such a small matrix it shouldn't much matter which language you use. With python you'd want to use numpy rather than the base functionality, but aside from that you shouldn't have issues in any of the languages. If you're most familiar with python then just use it.

[bio_informatics]

Hi,
Thank you for your reply. I put a sample matrix. I have matrix of more than 350x350, or 490X490.

[tomc]

As dpryan said those are small enough not to matter what you use, whatever is comfortable.
( and we did not mean the sample you posted
but the few hundred square matricies you mention)

If you have tens of thousands of those ~500^2 matricies to process maybe worry a bit more.

[bio_informatics]

@tomc-
Alright. Shall proceed with numpy then.