I\'m trying to write a nested dictionary to a .csv file. Here is is a simple example:
import csv
import itertools
fields = [ \'org\', \'2015\', \'2014\', \'
I think this could be an easier way:
import csv
fields = [ 'org', '2015', '2014', '2013' ]
dw = { 'orgname1': { '2015' : 2, '2014' : 1, '2013' : 1 },
'orgname2': { '2015' : 1, '2014' : 2, '2013' : 3 },
'orgname3': { '2015' : 1, '2014' : 3, '2013' : 1 }
}
with open("test_output.csv", "w") as csv_file:
csvwriter = csv.writer(csv_file)
csvwriter.writerow(['org', '2015', '2014', '2013'])
for org in dw:
csvwriter.writerow(org, dw[org]['2015'], dw[org]['2014'], dw[org]['2013'])
This looks like a job for DictWriter:
import csv
import itertools
import sys
fields = [ 'org', '2015', '2014', '2013' ]
dw = { 'orgname1': { '2015' : 2, '2014' : 1, '2013' : 1 },
'orgname2': { '2015' : 1, '2014' : 2, '2013' : 3 },
'orgname3': { '2015' : 1, '2014' : 3, '2013' : 1 }
}
w = csv.DictWriter( sys.stdout, fields )
for key,val in sorted(dw.items()):
row = {'org': key}
row.update(val)
w.writerow(row)
Using DictWriter there is no need in sorting the fields in advance, since w.writerow()
will assure the correct order. But it does make sense to sort the items themselves.
So putting together all the above suggestions and picking the best of each, i would come up with following code:
import csv
import itertools
def mergedict(a,b):
a.update(b)
return a
fields = [ 'org', '2015', '2014', '2013' ]
dw = { 'orgname1': { '2015' : 2, '2014' : 1, '2013' : 1 },
'orgname2': { '2015' : 1, '2014' : 2, '2013' : 3 },
'orgname3': { '2015' : 1, '2014' : 3, '2013' : 1 }
}
with open("test_output.csv", "wb") as f:
w = csv.DictWriter( f, fields )
w.writeheader()
for k,d in sorted(dw.items()):
w.writerow(mergedict({'org': k},d))
i added a tiny mergedict()
function that makes it a one liner further down.
Change:
w.writerow([key, [dw[key][year] for year in years]])
To:
w.writerow([key] + [dw[key][year] for year in years])
Otherwise, you try to write something like [orgname1, [2, 1, 1]]
to the csv, while you mean [orgname1, 2, 1, 1]
.
As Padraic mentioned, you may want to change years = dw.values()[0].keys()
to years = sorted(dw.values()[0].keys())
or years = fields[1:]
to avoid random behaviour.
Alternative implementation using DictWriter and with headers
import csv
import itertools
fields = [ 'org', '2015', '2014', '2013' ]
dw = { 'orgname1': { '2015' : 2, '2014' : 1, '2013' : 1 },
'orgname2': { '2015' : 1, '2014' : 2, '2013' : 3 },
'orgname3': { '2015' : 1, '2014' : 3, '2013' : 1 }
}
with open("test_output.csv", "wb") as f:
w = csv.DictWriter(f, fields)
w.writeheader()
for k in dw:
w.writerow({field: dw[k].get(field) or k for field in fields})
Output:
org,2015,2014,2013
orgname1,2,1,1
orgname3,1,3,1
orgname2,1,2,3