nanmean - np - np.mean - errror

[sparkz_alot]

Not sure if I understand, but the "mean" is nothing more than the sum of a list of numbers divided by the number of items in the list.  So for example, taking your column 1 numbers we can use something simple like:

col_1 = [-177.01262488, -486.95502974, -701.57667656, -739.68606132, 496.35283147]
total = 0.0

# Column 1 mean
for n in col_1:
    total += n
print("Total = ", total)
mean_1 = total / len(col_1)
print("Mean of column 1 = ", mean_1)

and end up with:

Output:
Total =  -1608.8775610300002

Mean of column 1 =  -321.77551220600003

The same could be done for column 2. Not as fancy as numpy, but it will at least give you something to compare outputs.