Python's csv module handles data row-wise, which is the usual way of looking at such data. You seem to want a column-wise approach. Here's one way of doing it.
Assuming your file is named myclone.csv and contains
workers,constant,age
w0,7.334,-1.406
w1,5.235,-4.936
w2,3.2225,-1.478
w3,0,0
this code should give you an idea or two:
>>> import csv
>>> f = open('myclone.csv', 'rb')
>>> reader = csv.reader(f)
>>> headers = next(reader, None)
>>> headers
['workers', 'constant', 'age']
>>> column = {}
>>> for h in headers:
... column[h] = []
...
>>> column
{'workers': [], 'constant': [], 'age': []}
>>> for row in reader:
... for h, v in zip(headers, row):
... column[h].append(v)
...
>>> column
{'workers': ['w0', 'w1', 'w2', 'w3'], 'constant': ['7.334', '5.235', '3.2225', '0'], 'age': ['-1.406', '-4.936', '-1.478', '0']}
>>> column['workers']
['w0', 'w1', 'w2', 'w3']
>>> column['constant']
['7.334', '5.235', '3.2225', '0']
>>> column['age']
['-1.406', '-4.936', '-1.478', '0']
>>>
To get your numeric values into floats, add this
converters = [str.strip] + [float] * (len(headers) - 1)
up front, and do this
for h, v, conv in zip(headers, row, converters):
column[h].append(conv(v))
for each row instead of the similar two lines above.