I have to import a file, which for example contains 3 rows of numbers:
1 2 3 4
1 2 3
1 2 3 4 5 6
How can I store them into a numpy.ndarray M, so that for example M[0] gives a np.array containing the first row, i.e. [1,2,3,4]?
Thanks in advance.
How about this:
import numpy as np
with open('test_file.txt') as file:
arr = np.array(
[
np.array([float(num) for num in line.strip().split("\t")])
for line in file
]
)
print(arr)
and the array should look like the one below:
[array([1., 2., 3., 4.]) array([1., 2., 3.])
array([1., 2., 3., 4., 5., 6.])]
'13.8\t21.6\t28.9\t34.3\t38.2\t42\t44.6\t46.3\t47.4\t48.2\t47.4\t45.5\t\n', I put '\t' instead of " " in split(). But it gives me ValueError: could not convert string to float: ''. How can I fix it? Thanks.Same as Giorgios but with a np.array instead of a list for rows :
import numpy as np
with open('test_file.txt') as file:
arr = np.array(
[
np.array([float(num) for num in line.split(" ")])
for line in file
]
)
print(arr)
