Matrix: Sum of a column

Answered

Marc Schmidt

• November 11, 2020 07:54
• Edited

Hello everyone, 
I'm new to Python and could need your help. 

I would like to sum up a column in a matrix. 

My matrix is defined with pandas: 

cities = [1,2,3,4,5] 

seq = [[0, 3, 0, 5, 0], [1, 2, 3, 0, 0], [0, 1, 5, 0, 2], [0, 3, 1, 0, 0], [0, 9, 0, 1, 0]]
matrix = pd.DataFrame(seq, columns=cities, index=cities)
print(matrix, '\n')

which gives:

   1  2  3  4  5
1  0  3  0  5  0
2  1  2  3  0  0
3  0  1  5  0  2
4  0  3  1  0  0
5  0  9  0  1  0 

In the next step I have to formulate constrains for which I need the sum of row i  and/or column j. 

I tried it like this: 

column = (sum(matrix[i][:] for i in cities )) 
row    = (sum(matrix[:][i] for i in cities ))

Unfortunately, both give this result and sum up the rows but not the columns. 

1     8
2     6
3     8
4     4
5    10
dtype: int64

I found, that there is the following possibility, but I only want to sum up column i in my constraint and not all. 

matrix.sum(axis = 0) #columns
matrix.sum(axis = 1) #rows

Best regards

Marc 

0

• 

  Jaromił Najman

  Gurobi Staff

  • November 11, 2020 09:09
  • Edited

  Hi Marc,

  Your last attempt is correct.

  The code

  number = matrix.sum(axis=0)
  print(number)

  provides

  1 1
  2 18
  3 9
  4 6
  5 2
  dtype: int64

  , i.e., the sum of each column saved as a \(\texttt{pandas Series}\). You can access the value of the sum of the second column via

  print(number[2])

  which prints

  18

  The index of the columns is defined via your list \(\texttt{cities}\).
  It works the same for rows.

  Best regards,
  Jaromił

  0
• 

  Marc Schmidt

  • November 11, 2020 12:05

  

  

  

  Hi Jaromił, 

  thanks for the explanation and solution! It works :) 

   

  0

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