python - Numpy accessing column of genfromtxt array raises IndexError -

i'm reading tab separated files. want infer type of columns automatically , read members of first column.

however, type numpy outputs can vary lot, depending on input (single or multi-column) , on dtype parameter used.

here set of test cases

multi_col = "a\t1\t2\nb\t3\t4"  = np.genfromtxt(stringio(multi_col), delimiter="\t", skip_header=0,                   dtype=[('f0', '|s16'), ('f1', '<i8'), ('f2', '<i8')]) print_properties(a, 'a') print("first col a['f0'] = " + str(a['f0']) + '\n')  = np.genfromtxt(stringio(multi_col), delimiter="\t", skip_header=0, dtype=none) print_properties(a, 'a') print("first col a['f0'] = " + str(a['f0']) + '\n')  = np.genfromtxt(stringio(multi_col), delimiter="\t", skip_header=0, dtype=str) print_properties(a, 'a') print('first col a[:, 0] = ' + str(a[:, 0]) + '\n')  single_col = "a\nb"  b = np.genfromtxt(stringio(single_col), delimiter="\t", skip_header=0, dtype=[('f0', '|s16')]) print_properties(b, 'b') print("first col b['f0'] = " + str(b['f0']) + '\n')  b = np.genfromtxt(stringio(single_col), delimiter="\t", skip_header=0, dtype=none) print_properties(b, 'b') print('already column\n')  b = np.genfromtxt(stringio(single_col), delimiter="\t", skip_header=0, dtype=str) print_properties(b, 'b') print('already column\n')  single_val = "a\n"  c = np.genfromtxt(stringio(single_val), delimiter="\t", skip_header=0, dtype=str) print_properties(c, 'c') print('single value\n') 

i can't find way access first column in uniform way. different operators needed different cases.

if use col0 = a[:, 0] in first 2 cases, error

indexerror: many indices array 

on other side, if use col0 = a['f0'], gives error in third case

indexerror: integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`none`) , integer or boolean arrays valid indices 

is there uniform way access first column without typecasting?

here's solution "worked me".

def print_1st_col(arr):     # access first column according different structures numpy can output     if arr.dtype.fields not none:         print('structured array')         col = arr['f0']  # structured array     else:         if arr.ndim <= 1:             print('uniform 1d array')             col = arr  # direct access (single number or uniform 1d array)         else:             print('uniform multi-dimensional array')             col = arr[:, 0]  # uniform multi-dimensional array      print(str(col) + '\n')