Hi all, I originally posted this to the issue tracker (https://github.com/numpy/numpy/issues/5686), and am posting here as well at the request of charris. Currently, np.genfromtxt uses a numpy.lib._iotools.NameValidator which mangles field names by replacing spaces and stripping out certain non-alphanumeric characters etc.: import numpy as np from io import BytesIO s = 'name,name with spaces,2*(x-1)!\n1,2,3\n4,5,6' x = np.genfromtxt(BytesIO(s), delimiter=',', names=True) print(repr(x)) # array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], # dtype=[('name', '<f8'), ('name_with_spaces', '<f8'), ('2x1', '<f8')]) This behaviour has been the cause of some confusion in the past, e.g. http://stackoverflow.com/q/29097917/1461210, http://stackoverflow.com/q/16020137/1461210. Part of the issue is that it's currently not very well covered by the documentation for np.genfromtext - at best, it's alluded to in the descriptions for some of the keyword arguments ('deletechars', 'autostrip', 'replace_space' etc.). However, I think the more fundamental problem is that this behaviour seems to be inconsistent with the rules for naming the fields in structured arrays. In the example above, all of the original field names are perfectly legal: names = ['name', 'name with spaces', '2*(x-1)!'] types = ('f',) * 3 dtype = zip(names, types) x2 = np.empty(2, dtype=dtype) x2[:] = [(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)] print(repr(x2)) # array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], # dtype=[('name', '<f4'), ('name with spaces', '<f4'), ('2*(x-1)!', '<f4')]) print(x2['2*(x-1)!']) # [3. 6.] What is the rationale behind the use of NameValidator here? One possible reason would be to ensure that the field names would also be legal for an np.recarray. However, this doesn't make sense for several reasons: Firstly, the names above also seem to be legal field names for a recarray: xr = x2.view(np.recarray) print(repr(x2)) # rec.array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], # dtype=[('name', '<f4'), ('name with spaces', '<f4'), ('2*(x-1)!', '<f4')]) Obviously if the field names aren't valid Python identifiers then it won't be possible to access them via 'xr.fieldname' syntax, but dict-style indexing is still fine, e.g. xr['2*(x-1)!']. Also, if the goal of NameValidator were to ensure that the field names were always valid Python identifiers then it currently fails at this anyway, since in my first example, '2x1' is not a valid Python identifier. What is perhaps most confusing is the fact that np.genfromtxt will even mangle field names that you pass in directly via the 'names' keyword argument. Suppose you wanted to specify field names that NameValidator doesn't like. You might try something like this: print(repr(np.genfromtxt(BytesIO(s), delimiter=',', names=names, skip_header=1))) # array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], # dtype=[('name', '<f8'), ('name_with_spaces', '<f8'), ('2x1', '<f8')]) Or even this: print(repr(np.genfromtxt(BytesIO(s), delimiter=',', names=names, skip_header=1, deletechars=[], replace_space=False, excludelist=[], autostrip=False))) # array([(1.0, 2.0, 3.0), (4.0, 5.0, 6.0)], # dtype=[('name', '<f8'), ('name_with_spaces', '<f8'), ('2x1', '<f8')]) Still no luck! As far as I can tell, there is no option in np.genfromtxt that allows you to preserve field names that don't conform to NameValidator's seemingly arbitrary rules. What should be done about this? Personally, I think that either things like spaces and non-alphanumeric characters should be disallowed in structured array field names altogether (and my second example should raise an exception), or np.genfromtxt should leave field names alone by default. It would also be a good idea to raise a SyntaxWarning in a case where the user creates a recarray containing field names that are not valid Python identifiers (and are therefore incompatible with the dot indexing syntax). This is essentially what PyTables does for non-conforming HDF5 node names: https://github.com/PyTables/PyTables/blob/13047c897d28b7278cbeab732f12feadbf.... Any thoughts on this? Alistair