How to calculate the sum of all columns of a 2D numpy array efficiently

Question

Let s say I have the following 2D numpy array consisting of four rows and three columns    gt  gt  gt  a   numpy arange 12  reshape 4 3   gt  gt  gt  print a     0  1  2     3  4  5     6  7  8     9 10 11     What would be an efficient way to generate a 1D array that contains the sum of all columns  like  18  22  26    Can this be done without having the need to loop through all columns

User · Answer

Use the axis argument    gt  gt  numpy sum a  axis 0    array  18  22  26

User · Answer

a sum 0    should solve the problem  It is a 2d np array and you will get the sum of all column  axis 0 is the dimension that points downwards and axis 1 the one that points to the right

User · Answer

Use numpy sum  for your case  it is  sum   a sum axis 0

User · Answer

Then NumPy sum function takes an optional axis argument that specifies along which axis you would like the sum performed    gt  gt  gt  a   numpy arange 12  reshape 4 3   gt  gt  gt  a sum 0  array  18  22  26     Or  equivalently    gt  gt  gt  numpy sum a  0  array  18  22  26

User · Answer

Other alternatives for summing the columns are numpy einsum  ij- gt j   a   and numpy dot a T  numpy ones a shape 0     If the number of rows and columns is in the same order of magnitude  all of the possibilities are roughly equally fast   If there are only a few columns  however  both the einsum and the dot solution significantly outperform numpy s sum  note the log-scale     Code to reproduce the plots  import numpy import perfplot   def numpy sum a       return numpy sum a  axis 1    def einsum a       return numpy einsum  ij- gt i   a    def dot ones a       return numpy dot a  numpy ones a shape 1      perfplot save       quot out1 png quot         setup lambda n  numpy random rand n  n       setup lambda n  numpy random rand n  3       n range  2  k for k in range 15        kernels  numpy sum  einsum  dot ones       logx True      logy True      xlabel  len a

User · Answer

Check out the documentation for numpy sum  paying particular attention to the axis parameter  To sum over columns      gt  gt  gt  import numpy as np  gt  gt  gt  a   np arange 12  reshape 4 3   gt  gt  gt  a sum axis 0  array  18  22  26     Or  to sum over rows    gt  gt  gt  a sum axis 1  array   3  12  21  30     Other aggregate functions  like numpy mean  numpy cumsum and numpy std  e g   also take the axis parameter   From the Tentative Numpy Tutorial      Many unary operations  such as computing the sum of all the elements   in the array  are implemented as methods of the ndarray class   By   default  these operations apply to the array as though it were a list   of numbers  regardless of its shape  However  by specifying the axis   parameter you can apply an operation along the specified axis of an   array

[python] How to calculate the sum of all columns of a 2D numpy array (efficiently)

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