I have a train dataset traind
with the shape (60000,28,28)
.
I want to slice out all samples (60000)
which have a mean of 0.3
or bigger.
I tried this:
condition = (np.mean(traind[0:60000,:,:]) > 0.3)
subTraind = traind[condition]
but it throws me followed error:
IndexError: too many indices for array: array is 2-dimensional, but 3 were indexed
Is there a way to do a slicing with multiple index conditions?
np.mean
will compute the mean over the entire array by default. You want to compute mean along the last 2 axes only: