from numpy import *
arr1 = array([5,10,15,20,30])
arr2 = array([55,16,1,280,60])
arr3 = ([])
k =0
for num1 in arr1:
num3 = num1 + arr2[k]
arr3.append(num3)
k +=1
print(arr3)
What if arr1 or arr2 has more indexes? How can I fix this?
It's generally a bad idea to from package import * as you can override other packages in your namespace. Numpy has a built in solution to add two arrays together:
import numpy as np
arr1 = np.array([5,10,15,20,30])
arr2 = np.array([55,16,1,280,60])
arr1+arr2
array([ 60, 26, 16, 300, 90]) # 435 ns ± 5.89 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
Though, you need the two arrays to have the same length.
If you want to use some standard python functions (and not a for loop) you can use map and zip to handle to arrays that aren't the same length:
list(map(sum, zip(arr1,arr2)))
[60, 26, 16, 300, 90] # 4.45 µs ± 60.2 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
If you want to use a for loop you can do this:
new_list = []
for i in range(min(len(arr1), len(arr2))):
new_list.append(arr1[i]+arr2[i])
new_list
[60, 26, 16, 300, 90] # 2.71 µs ± 307 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
All of these assume you want to stop when you reach the end of the shortest list.
If the arrays are unequal in length, you first need to align the portions that are of the same length, perform your operation (e.g. addition), and then concatenate the remainder of the longer array (possibly applying another operation, but not in this case).
import numpy as np
arr1 = np.array([5,10,15,20,30])
arr2 = np.array([55,16,1,280,60, 70]) # Longer than arr1.
min_len = min(len(arr1), len(arr2))
longer_array = arr1 if len(arr1) > len(arr2) else arr2
partial_result = arr1[:min_len] + arr2[:min_len]
>>> np.concatenate((partial_result, longer_array[min_len:]))
array([ 60, 26, 16, 300, 90, 70])
Simply copy the largest array into new array , and replace each index of new array with addition of respective indexes of two arrays . So that index out of range and copying array of larger array into new can be avoided.
from numpy import *
arr1 = array([1, 2, 3, 4, 5 ])
arr2 = array([6, 7, 8, 9, 10, 11, 12])
arr3 = ([])
if len(arr1) == len(arr2): # Finding minimum length array
minLength = len(arr1)
pass
elif len(arr1) > len(arr2):
minLength = len(arr2)
arr3 = arr1.copy() # Copy max array into new array
else:
minLength = len(arr1)
arr3 = arr2.copy() # Copy max array into new array
for i in range(minLength):
arr3[i] = arr1[i] + arr2[i] # adding array and replacing in new array
print(arr3)
from numpy import *
arr1 = array([2, 6, 8, 9, 1])
arr2 = array([1, 2, 3, 4, 5])
list1 = [ ]
e = 0
for num1 in arr1:
list1.append(arr2[e] + num1)
e+=1
print(array(list1))
#import numpy methods
from numpy import *
#initialize two array
arr1 = array([2, 6, 8, 1, 3])
arr2 = array([1, 6, 2, 1, 5])
#declare an empty array
arr3=([])
#find length of first array
n=len(arr1)
#traverse using for loop
for i in range(0,n):
#append sum of both array in final array
arr3.append(arr1[i]+arr2[i])
#print final array
print(arr3)
from numpy import * is considered bad practise. Instead, use import numpy as np, like everyone else.
for this we need numpy package to be imported first,use this only when both the array are of the same length.
from numpy import*
arr1 = array([1,2,3,4,5])
arr2 = array([2,3,4,5,6])
for i in range(len(arr1)):
arr3 = arr1[i] + arr2[i]
print(arr3)
arr3 = arr1 + arr2for equal shape numpy arrays. If shapes differ the problem is ill defined.