I have a large correlation matrix in a pandas python DataFrame: df (342, 342).

How do I take the mean, sd, etc. of all of the numbers in the upper triangle not including the 1's along the diagonal?

Thank you.

Another potential one line answer:

In [1]: corr
Out[1]:a         b         c         d         e
a  1.000000  0.022246  0.018614  0.022592  0.008520
b  0.022246  1.000000  0.033029  0.049714 -0.008243
c  0.018614  0.033029  1.000000 -0.016244  0.049010
d  0.022592  0.049714 -0.016244  1.000000 -0.015428
e  0.008520 -0.008243  0.049010 -0.015428  1.000000In [2]: corr.values[np.triu_indices_from(corr.values,1)].mean()
Out[2]: 0.016381

Edit: added performance metrics

Performance of my solution:

In [3]: %timeit corr.values[np.triu_indices_from(corr.values,1)].mean()
10000 loops, best of 3: 48.1 us per loop

Performance of Theodros Zelleke's one-line solution:

In [4]: %timeit corr.unstack().ix[zip(*np.triu_indices_from(corr, 1))].mean()
1000 loops, best of 3: 823 us per loop

Performance of DSM's solution:

In [5]: def method1(df):...:     df2 = df.copy()...:     df2.values[np.tril_indices_from(df2)] = np.nan...:     return df2.unstack().mean()...:In [5]: %timeit method1(corr)
1000 loops, best of 3: 242 us per loop