Op 09-01-17 om 07:58 schreef Deborah Swanson:
> Peter Otten wrote, on January 08, 2017 5:21 AM
>> Deborah Swanson wrote:
>>
>>> Peter Otten wrote, on January 08, 2017 3:01 AM
>>
>> Personally I would recommend against mixing data (an actual location)
> and
>> metadata (the column name,"Location"), but if you wish my code can be
>> adapted as follows:
>>
>> infile = open("dictreader_demo.csv")
>> rows = csv.reader(infile)
>> fieldnames = next(rows)
>> Record = namedtuple("Record", fieldnames)
>> records = [Record._make(fieldnames)]
>> records.extend(Record._make(row) for row in rows)
> Works like a charm. I stumbled a bit changing all my subscripted
> variables to namedtuples and rewriting the inevitable places my code
> that didn't work the same. But actually it was fun, especially deleting
> all the sections and variables I no longer needed. And it executes
> correctly now too - with recognizable fieldnames instead of my quirky
> 2-letter code subscripts. All in all a huge win!
>
> I do have two more questions.
>
> 1) I have a section that loops through the sorted data, compares two
> adjacent rows at a time, and marks one of them for deletion if the rows
> are identical.
>
> I'm using
>
> for i in range(len(records)-1):
> r1 = records[i]
> r2 = records[i+1]
> if r1.xx = r2.xx:
> .
> .
> and my question is whether there's a way to work with two adjacent rows
> without using subscripts?
for r1, r2 in zip(records[i], records[i+1]):
if r1.xx == r2.xx
.
.
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