numpy dtype anomaly

[bluefrog]

I've reduced the number of columns to 4, and still the error occurs if usecols is specified. If not, it succeeds in loading each column into an array. I've taken out the missing column, which is column 2 in the previous post.
I've also included a decode('ascii') on the byte string for the date, which is the 2nd column.

So without "usecols", it works fine, as follows:

import sys
import numpy as np
import os.path as op
from datetime import datetime, date, time
from io import StringIO

sample_data = StringIO(
"AAPL,28-01-2011,344.17,344.4\n\
AAPL,31-01-2011,335.8,340.04\n\
AAPL,01-02-2011,341.3,345.65\n\
AAPL,02-02-2011,344.45,345.25\n\
AAPL,03-02-2011,343.8,344.24\n\
AAPL,04-02-2011,343.61,346.7")

def usage():
    print("usage: {} {}".format(op.basename(sys.argv[0], 'filename')))

def get_weekday(date_str):
    return datetime.strptime(date_str.decode('ascii'), "%d-%m-%Y").date().weekday()

def load_arrays(data_file, *col_tuple):
    a1 = a2 = a3 = a4 = None

  #  rec_type = np.dtype([('stock_code', 'S4'), ('cob_date', 'S10'), ('close_price', 'f4')])
    try:
        a1, a2, a3, a4 = np.loadtxt(data_file, 
                                dtype={'names': ('stock_code','cob_date','high_price','low_price'),
                                       'formats': ('S4', 'S10', 'f4', 'f4')}, 
                                converters={1: get_weekday}, delimiter=',',
                                unpack=True)

    except IOError as e:
        usage() # failed to open file
    except Exception as e: print(e)

    return a1, a2, a3, a4

try:
    data_file = sample_data
    s, d, h, l = load_arrays(data_file)
except IndexError:
    usage()

print("Stock code array:\n{}".format(s))
print("\nClose of Business date array:\n{}".format(d))
print("\nHigh price array:\n{}".format(h))
print("\nLow price array:\n{}".format(l))

But when I want to only load say column 0 and 2, then I get

list index out of range

code appears as:

def load_arrays(data_file, *col_tuple):
    a1 = a2 = None

    try:
        a1, a2 = np.loadtxt(data_file, 
                                dtype={'names': ('stock_code','cob_date','high_price','low_price'),
                                       'formats': ('S4', 'S10', 'f4', 'f4')}, 
                                converters={1: get_weekday}, delimiter=',',
                                usecols=(0,2), unpack=True)

    except IOError as e:
        usage() # failed to open file
    except Exception as e: print(e)

    return a1, a2

try:
    data_file = sample_data
    s,  h= load_arrays(data_file)
except IndexError:
    usage()

The number of columns matches what is specified in dtype.