you can use the 'converters' keyword in numpy.loadtxt.
first define a function to convert a string in a float, that can handle
your 'N/A' entries:
def converter(x):
if x == 'N/A':
return numpy.nan
else:
return float(x)
then use:
>>> numpy.loadtxt('test.dat', converters={1
I am using loadtxt and I have missing values that are show up as N/A.
I get a,
ValueError: invalid literal for float(): N/A
Is there a way to ignore these?
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