May-24-2018, 01:06 AM
Hi I'm trying to find a simple way to run through a large data set (2432094 lines). I'm currently writing a program that takes the first 480 lines (8 hours) and creates a new array. Then I shifting by 60 lines (one hour) for line 1 and then grabbing another 480 lines and create another array. I'd like to continue this for the whole data set.
Here's what I'm currently running:
n_window = n[:480,:]
n_window1 = n[540:1020,:]
n_window2 = n[1080:1560,:]
n_window3 = n[1620:2100,:]
n_window4 = n[2160:2640,:]
n_window5 = n[2700:3180,:]
n_window6 = n[3240:3720,:]
n_window7 = n[3780:4260,:]
n_window8 = n[4320:4800,:]
n_window9 = n[4860:5340,:]
n_window11 = n[5400:5880,:]
n_window12 = n[5940:6420,:]
n_window13 = n[6480:6960,:]
n_window14 = n[7020:7500,:]
n_window15 = n[7560:8040,:]
n_window16 = n[8100:8580,:]
n_window17 = n[8640:9120,:]
new_window = np.concatenate([n_window,n_window1, n_window2,n_window3,n_window4,n_window5,n_window6,n_window7,n_window8,n_window9,n_window11,n_window12,n_window13,n_window14,n_window15,n_window16,n_window17])
Can anyone help?
Here's what I'm currently running:
n_window = n[:480,:]
n_window1 = n[540:1020,:]
n_window2 = n[1080:1560,:]
n_window3 = n[1620:2100,:]
n_window4 = n[2160:2640,:]
n_window5 = n[2700:3180,:]
n_window6 = n[3240:3720,:]
n_window7 = n[3780:4260,:]
n_window8 = n[4320:4800,:]
n_window9 = n[4860:5340,:]
n_window11 = n[5400:5880,:]
n_window12 = n[5940:6420,:]
n_window13 = n[6480:6960,:]
n_window14 = n[7020:7500,:]
n_window15 = n[7560:8040,:]
n_window16 = n[8100:8580,:]
n_window17 = n[8640:9120,:]
new_window = np.concatenate([n_window,n_window1, n_window2,n_window3,n_window4,n_window5,n_window6,n_window7,n_window8,n_window9,n_window11,n_window12,n_window13,n_window14,n_window15,n_window16,n_window17])
Can anyone help?