python slice an array
a[start:stop] # items start through stop-1
a[start:] # items start through the rest of the array
a[:stop] # items from the beginning through stop-1
a[:] # a copy of the whole array
Example:
>>> a = [1, 2, 3, 4, 5, 6, 7, 8]
>>> a[1:4]
[2, 3, 4]is : and :: the same in python slice
a[-1] # last item in the array
a[-2:] # last two items in the array
a[:-2] # everything except the last two itemspython slice
# array[start:stop:step]
# start = include everything STARTING AT this idx (inclusive)
# stop = include everything BEFORE this idx (exclusive)
# step = (can be ommitted) difference between each idx in the sequence
arr = ['a', 'b', 'c', 'd', 'e']
arr[2:] => ['c', 'd', 'e']
arr[:4] => ['a', 'b', 'c', 'd']
arr[2:4] => ['c', 'd']
arr[0:5:2] => ['a', 'c', 'e']
arr[:] => makes copy of arrpython slice
a[start:stop] # items start through stop-1
a[start:] # items start through the rest of the array
a[:stop] # items from the beginning through stop-1
a[:] # a copy of the whole arraypython3 slice
# array[start:stop:step]
# start = include everything STARTING AT this idx (inclusive)
# stop = include everything BEFORE this idx (exclusive)
# step = (can be committed) difference between each idx in the sequence
arr = ['a', 'b', 'c', 'd', 'e']
arr[2:] => ['c', 'd', 'e']
arr[:4] => ['a', 'b', 'c', 'd']
arr[2:4] => ['c', 'd']
arr[0:5:2] => ['a', 'c', 'e']
arr[:] => makes copy of arrarray slicing python
#slicing arrays:
#generic sampling is done by
#arr[start:end] -> where start is the starting index and end is ending idx
>>> import numpy as np
>>> arr = np.array([1,2,3,4,5])
>>> print(arr[1:5]) #starting idx 1 to ending index 4
[2 3 4 5]#it will print from starting idx to ending idx-1
#if you leave the ending index blank it will print all
#from the starting index till end
>>> arr = np.array([2,6,1,7,5])
>>> print(arr[3:])
[7 5]
>>> print(arr[:3]) #if you leave the starting index blank it will print from 0 index to the ending idx-1
[2 6 1]
>>> print(arr[:])
[2 6 1 7 5]
#leaving both the index open will print the entire array.
##########STEP slicing########
#if you want to traverse by taking steps more than 1
#we use step slicing in that case
#syntax for step slicing is : arr[start:end:step]
>>> arr = np.array([2,6,1,7,5,10,43,21,100,29])
>>> print(arr[1:8:2])#we have taken steps of two
[ 6 7 10 21]Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
