Loading an array into a matrix

[paul18fr]

Not sure to figure out exactly what you want to do, but I guess the following code may help you. Note that I think it's better to convert directly the list:

import numpy as np

List = [[3.3480644 , 2.6733143 , 2.3946035 , 1.651863  , 1.4944869  , 1.4064457 , 2.0166957 , 2.7554176 ], 
        [2.6761208 , 2.147566  , 1.2485328 , 0.6944433 , 0.87446946 , 1.1815729 , 1.879112  , 2.3758152 ]]

List2Array = np.asarray(List)       # convert a list into a Numpy array
print(f"List2Array={List2Array}\n")

r, c = np.shape(List2Array)         # r=number of rows and c=number of columns

# to add zeros in front
M1 = np.zeros((r, 1), dtype=np.float32)
InFront = np.hstack((M1, List2Array))
print(f"InFront={InFront}\n")

# to add zeros at the bottom
M2 = np.zeros((1, c), dtype=np.float32)
AtBottom = np.vstack((List2Array, M2))
print(f"AtBottom={AtBottom}\n")

# to sum the array per row
SumPerRow = np.sum(List2Array, axis=1)
print(f"SumPerRow={SumPerRow}\n")

# to sum the array per column
SumPercolumn = np.sum(List2Array, axis=0)
print(f"SumPercolumn={SumPercolumn}\n")

# to eventually sum all terms
SumAllTerms = np.sum(List2Array)
print(f"SumAllTerms={SumAllTerms}")

Output:
List2Array=[[3.3480644  2.6733143  2.3946035  1.651863   1.4944869  1.4064457
  2.0166957  2.7554176 ]
 [2.6761208  2.147566   1.2485328  0.6944433  0.87446946 1.1815729
  1.879112   2.3758152 ]]

InFront=[[0.         3.3480644  2.6733143  2.3946035  1.651863   1.4944869
  1.4064457  2.0166957  2.7554176 ]
 [0.         2.6761208  2.147566   1.2485328  0.6944433  0.87446946
  1.1815729  1.879112   2.3758152 ]]

AtBottom=[[3.3480644  2.6733143  2.3946035  1.651863   1.4944869  1.4064457
  2.0166957  2.7554176 ]
 [2.6761208  2.147566   1.2485328  0.6944433  0.87446946 1.1815729
  1.879112   2.3758152 ]
 [0.         0.         0.         0.         0.         0.
  0.         0.        ]]

SumPerRow=[17.7408911  13.07763246]

SumPercolumn=[6.0241852  4.8208803  3.6431363  2.3463063  2.36895636 2.5880186
 3.8958077  5.1312328 ]

SumAllTerms=30.81852356