On 05/13/2015 04:24 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.
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. 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"] ]
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. 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.
You could try using a dictionary, combining when needed:
# untested
data = {}
for row in all_rows:
key = row[0], row[1]
if key in data:
item, qty, noise = data[key]
qty += row[3]
else:
item, qty, noise = row[2:]
data[key] = item, qty, noise
for (account, staff), (item, qty, noise) in data.items():
do_stuff_with(account, staff, item, qty, noise)
At the end, data should have what you want. It won't, however, be in
the same order, so hopefully that's not an issue for you.
--
~Ethan~
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