#Access array element
import numpy as np
num = np.array([2, 4, 5, 7])

print(num[0]) #access the first element:2
print(num[2] + num[3]) #Summation: 12

#Access 2-D array
import numpy as np
num = np.array([[2, 3, 4], [5, 1, 6]])
print(num[1, 2]) #3rd element on 2nd row so 6

#Access 3-D array
import numpy as np
num = np.array([[[1, 2, 3], [4, 5, 6], [7, 8, 9]]])
print(num[0, 0, 1]) #2

#Negative indexing
import numpy as np
num = np.array([[2, 4, 1], [3, 5, 6]])
print(num[1, -1]) #6

[3, -2, -1, 0, 2, 4, 1]
at the first i take
pivot 1:
3 > 1, -2 < 1, -1 < 1, 0 < 1, 2 > 1, 4 > 1
then elements smaller that 1 are -2, -1, 0
elements greater than 1 are 3, 2, 4
and then [-2,-1,0] 1 [3, 2, 4]

now what i've to do is to arrange elements smaller than 1 as a pivot take 0
pivot 0: -2 < 0, -1 < 0 They're ordered
Know elements up to 1 are ordered:[-2, -1, 0, 1]
the next is to sort elements right of 1: those are [3, 2, 4]
as a pivot take 4:
3 < 4, 2 < 4 : [3, 2] 4 []
and know take 2 as a pivot: 3 > 2: then [] 2 [3]
combine the process right of 1: ->>[2, 3, 4] Done
now combine the elements left of 1: [-2, -1, 0, 1]

COMBINE ALL OF THEM: [-2, -1, 0, 1, 2, 3, 4] done
I understand in this way

""""
compare numbers with pivot
group them
sort left
sort right
combine

Average time: O(n log n)
""""

In this morning, I was designing the UI of project am working on it. So now let's continue to our learning. You know that we're discussing on numpy and we try to cover; why it's needed to learn numpy, numpy creating arrays, numpy array indexing. No worries I've pinned the text.

Hey guys am so sorry for my being late.
I was just working on some projet.🤗

Optimization algorithms,
Training ML models,
Scientific simulations,
Computer graphics &
Data science