getting indices in numpy - python-3.x

Question

Can someone find out what is wrong with the code below?
import numpy as np
data = np.recfromcsv("data.txt", delimiter=" ", names=['name', 'types', 'value'])
indices = np.where((data.name == 'david') * data.types.startswith('height'))
mean_value = np.mean(data.value[indices])
I want to calculate mean of weight and height for david and mark as follows:
david>> mean(weight_2005 and weight_2012), mean (height_2005 and height_2012)
mark>> mean(weight_2005 and weight_2012), mean (height_2005 and height_2012)
From the text (data.txt) file:
david weight_2005 50
david weight_2012 60
david height_2005 150
david height_2012 160
mark weight_2005 90
mark weight_2012 85
mark height_2005 160
mark height_2012 170
I am using python 3.2 and numpy 1.8
The above code provides the type error as follows:
TypeError: startswith first arg must be bytes or a tuple of bytes, not numpy.str_

Answer 1

With Python3.2 and numpy 1.7, this line works
indices = np.where((data.name == b'david') * data.types.startswith(b'height'))
data displays as:
rec.array([(b'david', b'weight_2005', 50),...],
dtype=[('name', 'S5'), ('types', 'S11'), ('value', '<i4')])
type(data.name[0]) is <class 'bytes'>.
b'height' works in Python2.7 as well.
another option is to convert all the data to unicode (Python 3 strings)
dtype=[('name','U5'), ('types', 'U11'), ('value', '<i4')]
dataU=data.astype(dtype=dtype)
indices = np.where((dataU.name == 'david') * dataU.types.startswith('height'))
or
data = np.recfromtxt('data.txt', delimiter=" ",
names=['name', 'types', 'value'], dtype=dtype)
It looks like recfromcsv does not take a dtype, but recfromtxt does.