For example, my csv has columns as below:
ID, ID2, Date, Job No, Code
I need to write the columns back in the same order. The dict jumbles the order immediately, so I believe it's more of a problem with the reader.
For example, my csv has columns as below:
ID, ID2, Date, Job No, Code
I need to write the columns back in the same order. The dict jumbles the order immediately, so I believe it's more of a problem with the reader.
Python's dict
s do NOT maintain order.
However, the instance of csv.DictReader
that you're using (after you've read the first row!-) does have a .fieldnames
list of strings, which IS in order.
So,
for rowdict in myReader:
print ['%s:%s' % (f, rowdict[f]) for f in myReader.fieldnames]
will show you that the order is indeed maintained (in .fieldnames
of course, NEVER in the dict
-- that's intrinsically impossible in Python!-).
So, suppose you want to read a.csv
and write b.csv
with the same column order. Using plain reader and writer is too easy, so you want to use the Dict varieties instead;-). Well, one way is...:
import csv
a = open('a.csv', 'r')
b = open('b.csv', 'w')
ra = csv.DictReader(a)
wb = csv.DictWriter(b, None)
for d in ra:
if wb.fieldnames is None:
# initialize and write b's headers
dh = dict((h, h) for h in ra.fieldnames)
wb.fieldnames = ra.fieldnames
wb.writerow(dh)
wb.writerow(d)
b.close()
a.close()
assuming you have headers in a.csv
(otherewise you can't use a DictReader on it) and want just the same headers in b.csv
.