Fill matrix with transposed version
Here is one alternative way:
>>> m[np.triu_indices_from(m, k=1)] = m.T[np.triu_indices_from(m, k=1)]>>> marray([[ 1. , 0.5, 0.6, 0.5], [ 0.5, 1. , 0. , 0.4], [ 0.6, 0. , 1. , 0.3], [ 0.5, 0.4, 0.3, 1. ]])m[np.triu_indices_from(m, k=1)] returns the values above the diagonal of m and assigns them to the values values above the diagonal of the transpose of m.
With numpy.isnan():
>>> m[np.isnan(m)] = m.T[np.isnan(m)]>>> m a b c da 1.0 0.5 0.6 0.5b 0.5 1.0 0.0 0.4c 0.6 0.0 1.0 0.3d 0.5 0.4 0.3 1.0or better, with panda.isnull():
>>> m[pd.isnull(m)] = m.T[pd.isnull(m)]>>> m a b c da 1.0 0.5 0.6 0.5b 0.5 1.0 0.0 0.4c 0.6 0.0 1.0 0.3d 0.5 0.4 0.3 1.0which is finally equivalent to @DSM 's solution!