On 05/13/2015 07:24 PM, 20/20 Lab wrote:
I'm a beginner to python. Reading here and there. Written a couple of
short and simple programs to make life easier around the office.
Welcome to Python, and to this mailing list.
That being said, I'm not even sure what I need to ask for. I've never
worked with external data before.
I have a LARGE csv file that I need to process. 110+ columns, 72k
rows.
That's not very large at all.
I managed to write enough to reduce it to a few hundred rows, and
the five columns I'm interested in.
Now is were I have my problem:
myList = [ [123, "XXX", "Item", "Qty", "Noise"],
[72976, "YYY", "Item", "Qty", "Noise"],
[123, "XXX" "ItemTypo", "Qty", "Noise"] ]
It'd probably be useful to identify names for your columns, even if it's
just in a comment. Guessing from the paragraph below, I figure the
first two columns are "account" & "staff"
Basically, I need to check for rows with duplicate accounts row[0] and
staff (row[1]), and if so, remove that row, and add it's Qty to the
original row.
And which column is that supposed to be? Shouldn't there be a number
there, rather than a string?
I really dont have a clue how to go about this. The
number of rows change based on which run it is, so I couldnt even get
away with using hundreds of compare loops.
If someone could point me to some documentation on the functions I would
need, or a tutorial it would be a great help.
Is the order significant? Do you have to preserve the order that the
accounts appear? I'll assume not.
Have you studied dictionaries? Seems to me the way to handle the
problem is to read in a row, create a dictionary with key of (account,
staff), and data of the rest of the line.
Each time you read a row, you check if the key is already in the
dictionary. If not, add it. If it's already there, merge the data as
you say.
Then when you're done, turn the dict back into a list of lists.
--
DaveA
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