Python: 2D Numpy Array (Matrix) - Finding Sum of Negative Numbers (Rows)

Question

I have a matrix (using numpy), user enters number of rows and columns. After going through some FOR loops, user enters elements, of course depending on what number of rows and columns did he/she has chosen.

Now I need to find a sum of negative elements for every row below row 7 and output this every row sum, right after the exact row. Here is my code (even though code for this last thing doesn't work)

import numpy as np
A = list()
n = int(input("How many rows: "))
m = int(input("How many columns: "))

for x in range(n):
    if n <= 0 or n>10:
         print("Out of range")
         break
    elif m <= 0 or m>10:
         print("Out of range")
         break
    else:
        for y in range(m):
             num = input("Element: ")
             A.append(int(num))

shape = np.reshape(A,(n,m))

for e in range(n < 7):
    if e < 0:
        print(sum(e))

print(shape)

If as a user, I will enter 3 rows and 3 columns, I can get something like this (I'll enter some numbers to explain what I need):

[-1, 2, -3]
[-4, 5, -6]
[-7, -8, 9]

I should get something like this:

[-1, 2, -3] Sum of Negative Elements In This Row (Till 7th) [-4]
[-4, 5, -6] Sum of Negative Elements In This Row (Till 7th) [-10]
[-7, -8, 9] Sum of Negative Elements In This Row (Till 7th) [-15]

Also please don't forget I need it only till row 7, even if it will have more rows, I am not interested in them.

wwii · Accepted Answer · 2017-11-06 22:55:52Z

a = np.random.random_integers(-1, 1, (10,3))
>>> a
array([[ 0,  0, -1],
       [ 1, -1, -1],
       [ 0,  1,  1],
       [-1,  0,  0],
       [ 1, -1,  0],
       [-1,  1,  1],
       [ 0,  1,  0],
       [ 1, -1,  0],
       [-1,  0,  1],
       [ 1, -1,  1]])
>>>

You can slice a numpy array in any of its dimensions. The first seven rows would be:

>>> a[:7,:]
array([[ 0,  0, -1],
       [ 1, -1, -1],
       [ 0,  1,  1],
       [-1,  0,  0],
       [ 1, -1,  0],
       [-1,  1,  1],
       [ 0,  1,  0]])
>>>

Iterating over the array produces rows which can be summed. Boolean indexing can be used to select items based on a condition:

>>> for row in a[:7,:]:
...     less_than_zero = row[row < 0]
...     sum_less_than = np.sum(less_than_zero)
...     print('row:{:<14}\tless than zero:{:<11}\tsum:{}'.format(row, less_than_zero, sum_less_than))


row:[ 0  0 -1]      less than zero:[-1]         sum:-1
row:[ 1 -1 -1]      less than zero:[-1 -1]      sum:-2
row:[0 1 1]         less than zero:[]           sum:0
row:[-1  0  0]      less than zero:[-1]         sum:-1
row:[ 1 -1  0]      less than zero:[-1]         sum:-1
row:[-1  1  1]      less than zero:[-1]         sum:-1
row:[0 1 0]         less than zero:[]           sum:0
>>>

bastelflp · Accepted Answer · 2017-11-06 22:50:07Z

0

Go through every row of your 2D array and select the negative values with row[row < 0] and calculate the sum of these values:

import numpy as np

a = np.array([[-1, 2, -3], [-4, 5, -6], [-7, -8, 9]])  # your array

for row in a:
    neg_sum = sum(row[row < 0])  # sum of negative values
    print('{} Sum of Negative Elements In This Row: {}'.format(row, neg_sum))

This prints:

[-1  2 -3] Sum of Negative Elements In This Row: -4
[-4  5 -6] Sum of Negative Elements In This Row: -10
[-7 -8  9] Sum of Negative Elements In This Row: -15

answered Nov 6, 2017 at 22:50

bastelflp

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4 Comments

Jemal Amshalal Over a year ago

Thank you very much, it is exactly what i needed.

Jemal Amshalal Over a year ago

One question, if i add [:7,:] to for row in a: it will cut down everything even if matrix is 8x8, how can i manage to show whole matrix, but calculate negative numbers till 7th ?

bastelflp Over a year ago

Keep the full row (for row in a) but include this into the neg_sum = ... line.

Jemal Amshalal Over a year ago

So i need to add [:7,:] not to( for row in a ) , but to ( neg_sum = line ) ? I really don't know where to add, it gives me error that dimension is 8 and i have till 7, but no result

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