Writing numbers into file python

Export it into a CSV file. Your use case is very simple and you should be able to do it using standard Python.

with open('output.csv', 'w') as f:
  for x, y in l:
    f.write("%s, %s\n" % (x, y))

Note: list is a reserved word in python and you should not be using it.

Use openpyxl to write .xslx files from Python:

import openpyxl

my_list = [(0.496, 12.49), (0.531, 12.40), (0.578, 12.18), (0.615, 
   11.96), (0.657, 11.75), (0.731, 11.28), (0.785, 10.85), (0.812, 
   10.61), (0.883, 9.92), (0.930, 9.40), (0.979, 8.77), (1.026, 
   8.10), (1.081, 7.23), (1.134, 6.33), (1.189, 5.39), (1.220, 
   4.85), (1.273, 3.92), (1.332, 2.91), (1.364, 2.55), (1.418, 
   2.16), (1.467, 1.65), (1.523, 1.17), (1.569, 0.82), (1.626, 
   0.47), (1.678, 0.21), (1.723, 0.01), (1.776, 0.19), (1.814, 
   0.28), (1.869, 0.36), (1.933, 0.36), (1.972, 0.31), (2.021, 
   0.18), (2.081, 0.13), (2.129, 0.46), (2.169, 0.79), (2.219, 
   1.24), (2.280, 1.84), (2.306, 2.11), (2.358, 2.67), (2.414, 
   3.37), (2.471, 4.05), (2.505, 4.51), (2.562, 5.22), (2.613, 
   5.84), (2.652, 6.31), (2.712, 7.01), (2.758, 7.52), (2.802, 
   7.99), (2.869, 8.63), (2.930, 9.16), (2.971, 9.57), (3.043, 
   10.35), (3.078, 10.69), (3.119, 11.00), (3.174, 11.26), (3.217, 
   11.40), (3.261, 11.53), (3.307, 11.55), (3.371, 11.51), (3.432, 
   11.40), (3.479, 11.26), (3.507, 11.20), (3.557, 11.00), (3.623, 
   10.55), (3.663, 10.28), (3.729, 9.79), (3.768, 9.57), (3.825, 
   9.24), (3.880, 8.85), (3.944, 8.41), (3.969, 8.04), (4.014, 
   7.55), (4.086, 6.67), (4.105, 6.37), (4.166, 5.50), (4.212, 
   4.88), (4.266, 4.20), (4.311, 3.69), (4.364, 3.06), (4.401, 
   2.65), (4.453, 2.09), (4.497, 1.68), (4.556, 1.18), (4.602, 
   0.85), (4.644, 0.57), (4.695, 0.29), (4.754, 0.04), (4.799, 
   0.11), (4.847, 0.17), (4.918, 0.11), (4.959, 0.04), (4.992, 
   0.19), (5.063, 0.64), (5.098, 0.90), (5.157, 1.40), (5.201, 
   1.79), (5.245, 2.20), (5.291, 2.65), (5.326, 3.00), (5.387, 
   3.65), (5.420, 4.02), (5.469, 4.62), (5.538, 5.44), (5.579, 
   5.96), (5.629, 6.57), (5.674, 7.14), (5.724, 7.73), (5.798, 
   8.60), (5.823, 8.88), (5.888, 9.62), (5.919, 9.94), (5.963, 
   10.41), (6.009, 10.85), (6.050, 11.22), (6.115, 11.71), (6.153, 
   11.99), (6.222, 12.39), (6.263, 12.61), (6.302, 12.77), (6.377, 
   12.99), (6.414, 13.03), (6.454, 13.02), (6.522, 12.89), (6.558, 
   12.74), (6.626, 12.41), (6.677, 12.05), (6.729, 11.64), (6.791, 
   11.00), (6.832, 10.58), (6.887, 9.92), (6.949, 9.13), (6.996, 
   8.48), (7.028, 8.09), (7.094, 7.13), (7.123, 6.70), (7.161, 
   6.16), (7.213, 5.35), (7.250, 4.81), (7.332, 3.61), (7.382, 
   2.93), (7.420, 2.45), (7.474, 1.88), (7.514, 1.40), (7.576, 
   0.71), (7.600, 0.50), (7.662, 0.12), (7.725, 0.16), (7.768, 
   0.26), (7.810, 0.30), (7.858, 0.26), (7.904, 0.18), (7.980, 
   0.10), (8.021, 0.29), (8.078, 0.65), (8.133, 1.06), (8.165, 
   1.33), (8.218, 1.83), (8.267, 2.31), (8.321, 2.87), (8.355, 
   3.27), (8.413, 3.91), (8.473, 4.61), (8.519, 5.22), (8.553, 
   5.65), (8.643, 6.74), (8.678, 7.23), (8.734, 7.94), (8.760, 
   8.27), (8.803, 8.81), (8.851, 9.35), (8.905, 9.94), (8.961, 
   10.45), (9.009, 10.92), (9.053, 11.34), (9.106, 11.75), (9.166, 
   12.14), (9.228, 12.48), (9.292, 12.71), (9.340, 12.86), (9.384, 
   13.01), (9.412, 13.05), (9.452, 13.03), (9.472, 13.00)]

book = openpyxl.Workbook()
sheet = book.active

for i, value in enumerate(my_list):
    sheet.cell(row=i+1, column=1).value = value[0]
    sheet.cell(row=i+1, column=2).value = value[1]    

book.save('test.xlsx')

When you have data like numbers or objects in memory, it's generally not correct to dump that data directly into disk, you'll want to serialize it.

The easiest way to serialize it is with print which automatically calls the "serialization" method __str__. The problem with this serialization method is that's not always easy to deserialize.

When you have a data structure, like the matrix you describe, you'll want a serialization method that will preserve the structure and allow to reconstruct it in memory. In this case you can use CSV (through the csv module), JSON (through the json module) or many others.

Use CSV.