Convert fixed-width, non-delimited float strings to comma separated values

I have the following string of float numbers:


As you can see, there are no spaces between the numbers in this string. I am trying to make them csv. Therefore, I would like them to look like:


Is there a way to do this in python?. I tried to read the file using numpy, for example:

>>> w=numpy.loadtxt('coord', dtype='float')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/lib/python2.7/dist-packages/numpy/lib/", line 856, in loadtxt
items = [conv(val) for (conv, val) in zip(converters, vals)]
ValueError: invalid literal for float():

but as there are no spaces, it is not possible. I also tried numpy.fromfile which seems to read the file, but the it shows this:

>>> w=numpy.fromfile('coord', dtype='float')
>>> w
array([  3.53728147e-057,   3.03226305e-100,   5.64351177e-038,
         3.70004839e-033,   1.24395502e-047,   3.37923148e-057,
         2.93531907e-086,   3.69971918e-057,   7.25394458e-043])

I would be very glad if somebody could shed some light in this problem.

Edited: The chosen answer works, but I would like to add that the solution proposed by @DSM is avery good as well:

np.genfromtxt("file.dat", delimiter=18) 


Looks like you’re stuck with fixed-width values instead of delimited. You’ll have to slice up the string based on the character widths.

>>> s = '0.621464022829E+00-.143866495639E-020.266573765475E-02-.582189744480E-07'
>>> [float(s[i:i+18]) for i in range(0, len(s), 18)]
[0.621464022829, -0.00143866495639, 0.00266573765475, -5.8218974448e-08]

To read from a csv you could do something like

with open('file.csv') as f:
    data = [[float(line[i:i+18]) for i in range(0, len(line), 18)] for line in f.readlines()]

You could then pass this to numpy if you want

w = numpy.array(data)

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