On 27 January 2016 at 23:00, Ek Esawi <[email protected]> wrote:
> Ops..here is the text file.; previously i copied and pasted from either
> Word or Excel.
>
>
> AA,BB,CC,DD,EE
> 1,A1,B1,11.2,11/20/2011
> 2,A2,B2,2.5,10/21/2011
> 3,A3,B3,13.67,9/21/2011
> 4,A4,B4,14.2,8/22/2011
> 5,A5,B5,20,7/23/2011
Finally! That's what I expect to see in a csv file. Do the first,
second and third columns just count up like that? I thought that you
were expecting some rows to have the same values in the second and
third columns.
I'm not sure that it's really worth using numpy for this. I'd just use
the csv module:
import csv
with open('test.csv') as csvfile:
reader = csv.reader(csvfile)
next(reader, None) # Ignore first line of file
for line in reader:
index, col2, col3, col4, date = line
col4 = float(col4) # Convert 4th column value to float
print([col2, col3, col4])
Running this I get:
$ python3 test.py
['A1', 'B1', 11.2]
['A2', 'B2', 2.5]
['A3', 'B3', 13.67]
['A4', 'B4', 14.2]
['A5', 'B5', 20.0]
--
Oscar
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