I want to square even index values in numpy array and assign same in that array. I followed 2 approaches.
1 -
for i in range(len(arr)):
if i %2 == 0:
arr[i] = arr[i]**2
That is working.
2 -
arr[i] = arr[i]**2 for i in range(len(arr)) if i % 2 == 0
File "<ipython-input-149-30fc7ed25f1f>", line 1
arr[i] = arr[i]**2 for i in range(len(arr)) if i % 2 == 0
^
SyntaxError: invalid syntax
not working.
Is some syntax error?
This works with list compreension:
arr = [arr[i]**2 if i % 2 == 0 else arr[i] for i in range(len(arr))]
But you could also use the shorter:
arr[::2] = arr[::2]**2
arr[::2] = arr[::2]**2 is by far the best and mosty numpy-style solution of all solutions!I assume you are trying to do list comprehension, for which your syntax is slightly off, read up on the syntax of list comprehension.
It's syntax is similar to [exp1(item) if condition1 else exp2(item) for item in arr] .
The correct way to do it is as follows.
arr = [1,2,3,4,5,6]
arr = [arr[i]**2 if i % 2 == 0 else arr[i] for i in range(len(arr))]
print(arr)
#[1, 2, 9, 4, 25, 6]
What this is doing is running the for loop, checking the condition, and then picking either arr[i] or arr[i]**2, and then assigning the result to the list
Dont loop over numpy arrays you lose all the power of numpy.
Use these numpy functions to achieve the required result instead:
import numpy as np
arr = np.random.randint(0,10, size=(10,))
print(arr)
ans = np.where(np.arange(10) % 2 == 0, arr, arr**2)
print(ans)
output:
[ 1 9 1 1 0 6 5 2 1 5 ]
[ 1 81 1 1 0 36 5 4 1 25]
np.where selects the elements where the condition is true. Then outputs either the original array or the squared array.
Docs for np.where.