Question

So I have already imported one XML-ish file with 3000 elements and parsed them into a CSV for output. But I also need to import a second CSV file with ‘keyword’,’latitude’,’longitude’ as columns and use it to add the GPS coordinates to additional columns on the first file.

Reading the python tutorial, it seems like {dictionary} is what I need, although I’ve read on here that tuples might be better. I don’t know.

But either way – I start with:

    floc = open('c:\python\kenya_location_lookup.csv','r')
    l = csv.DictReader(floc)
    for row in l: print row.keys()

The output look like:

{‘LATITUDE’: ‘-1.311467078’, ‘LONGITUDE’: ‘36.77352011’, ‘KEYWORD’: ‘Kianda’}
{‘LATITUDE’: ‘-1.315288401’, ‘LONGITUDE’: ‘36.77614331’, ‘KEYWORD’: ‘Soweto’}
{‘LATITUDE’: ‘-1.315446430425027’, ‘LONGITUDE’: ‘36.78170621395111’, ‘KEYWORD’: ‘Gatwekera’}
{‘LATITUDE’: ‘-1.3136151425171327’, ‘LONGITUDE’: ‘36.785863637924194’, ‘KEYWORD’: ‘Kisumu Ndogo’}

I’m a newbie (and not a programmer). Question is how do I use the keys to pluck out the corresponding row data and match it against words in the body of the element in the other set?

Answer 1

If you dump the DictReader into a list (data = [row for row in csv.DictReader(file)]), and you have unique keywords for each row, convert that list of dictionaries into a dictionary of dictionaries, using that keyword as the key.

>>> data = [row for row in csv.DictReader(open('C:\\my.csv'),
...                                       ('num','time','time2'))]
>>> len(data)  # lots of old data :P
1410
>>> data[1].keys()
['time2', 'num', 'time']
>>> keyeddata = {}
>>> for row in data[2:]:  # I have some junk rows
...     keyeddata[row['num']] = row
...
>>> keyeddata['32']
{'num': '32', 'time2': '8', 'time': '13269'}

Once you have the keyword pulled out, you can iterate through your other list, grab the keyword from it, and use it as the index for the lat/long list. Pull out the lat/long from that index and add it to the other list.