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numpy.sum() in Python

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  • Last Updated : 03 Apr, 2020

numpy.sum(arr, axis, dtype, out) : This function returns the sum of array elements over the specified axis.

Parameters :
arr : input array.
axis : axis along which we want to calculate the sum value. Otherwise, it will consider arr to be flattened(works on all the axis). axis = 0 means along the column and axis = 1 means working along the row.
out : Different array in which we want to place the result. The array must have same dimensions as expected output. Default is None.
initial : [scalar, optional] Starting value of the sum.

Return : Sum of the array elements (a scalar value if axis is none) or array with sum values along the specified axis.

Code #1:




# Python Program illustrating 
# numpy.sum() method
import numpy as np 
       
# 1D array 
arr = [20, 2, .2, 10, 4]  
   
print("\nSum of arr : ", np.sum(arr)) 
   
print("Sum of arr(uint8) : ", np.sum(arr, dtype = np.uint8)) 
print("Sum of arr(float32) : ", np.sum(arr, dtype = np.float32))
   
print ("\nIs np.sum(arr).dtype == np.uint : "
       np.sum(arr).dtype == np.uint) 
  
print ("Is np.sum(arr).dtype == np.float : "
       np.sum(arr).dtype == np.float


Output:

Sum of arr :  36.2
Sum of arr(uint8) :  36
Sum of arr(float32) :  36.2

Is np.sum(arr).dtype == np.uint :  False
Is np.sum(arr).dtype == np.uint :  True

 
Code #2:




# Python Program illustrating 
# numpy.sum() method
import numpy as np 
       
# 2D array 
arr = [[14, 17, 12, 33, 44],   
       [15, 6, 27, 8, 19],  
       [23, 2, 54, 1, 4,]]  
   
print("\nSum of arr : ", np.sum(arr)) 
   
print("Sum of arr(uint8) : ", np.sum(arr, dtype = np.uint8)) 
print("Sum of arr(float32) : ", np.sum(arr, dtype = np.float32))
   
print ("\nIs np.sum(arr).dtype == np.uint : "
                 np.sum(arr).dtype == np.uint) 
  
print ("Is np.sum(arr).dtype == np.uint : "
              np.sum(arr).dtype == np.float


Output:

Sum of arr :  279
Sum of arr(uint8) :  23
Sum of arr(float32) :  279.0

Is np.sum(arr).dtype == np.uint :  False
Is np.sum(arr).dtype == np.uint :  False

 
Code #3:




# Python Program illustrating 
# numpy.sum() method 
       
import numpy as np 
       
# 2D array  
arr = [[14, 17, 12, 33, 44],   
       [15, 6, 27, 8, 19],  
       [23, 2, 54, 1, 4,]]  
   
print("\nSum of arr : ", np.sum(arr)) 
print("Sum of arr(axis = 0) : ", np.sum(arr, axis = 0)) 
print("Sum of arr(axis = 1) : ", np.sum(arr, axis = 1))
  
print("\nSum of arr (keepdimension is True): \n",
      np.sum(arr, axis = 1, keepdims = True))


Output:

Sum of arr :  279
Sum of arr(axis = 0) :  [52 25 93 42 67]
Sum of arr(axis = 1) :  [120  75  84]

Sum of arr (keepdimension is True): 
 [[120]
 [ 75]
 [ 84]]

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