Reputation: 699
The issue is common, when I import a csv file and process it and finally output it, the order of column in the output csv file may be different from the original one,for instance:
dct={}
dct['a']=[1,2,3,4]
dct['b']=[5,6,7,8]
dct['c']=[9,10,11,12]
header = dct.keys()
rows=pd.DataFrame(dct).to_dict('records')
with open('outTest.csv', 'wb') as f:
f.write(','.join(header))
f.write('\n')
for data in rows:
f.write(",".join(str(data[h]) for h in header))
f.write('\n')
the original csv file is like:
a,c,b
1,9,5
2,10,6
3,11,7
4,12,8
while I'd like to fixed the order of the column like the output:
a,b,c
1,5,9
2,6,10
3,7,11
4,8,12
and the answers I found are mostly related to pandas
, I wonder if we can solve this in another way.
Any help is appreciated, thank you.
Upvotes: 0
Views: 627
Reputation: 140256
Instead of dct={}
just do this:
from collections import OrderedDict
dct = OrderedDict()
The keys will be ordered in the same order you define them.
Comparative test:
from collections import OrderedDict
dct = OrderedDict()
dct['a']=[1,2,3,4]
dct['b']=[5,6,7,8]
dct['c']=[9,10,11,12]
stddct = dict(dct) # create a standard dictionary
print(stddct.keys()) # "wrong" order
print(dct.keys()) # deterministic order
result:
['a', 'c', 'b']
['a', 'b', 'c']
Upvotes: 3