Python - Convert dictionary (having "list" as values) into csv file - python-2.7

Question

Trying to write below dictionary into csv file with desired output as mentioned below.
dict_data = {"1":["xyz"],
"2":["abc","def"],
"3":["zzz"]
}
desired output:
1,3,2
xyz,zzz,abc
def
Below code doesn't work as expected as it keeps both "abc" & "def" in same cell as shown below.
with open('k.csv','wb') as out_file:
writer = csv.writer(out_file,dialect = 'excel')
headers = [k for k in dict_data]
items = [dict_data[k] for k in dict_data]
writer.writerow(headers)
writer.writerow(items)
output:
1,3,2
xyz,zzz,abc,def

Answer 1

Here is the complete solution:
import csv
import os
class CsvfileWriter:
'''
Takes dictionary as input and writes items into a CSV file.
For ex:-
Input dictionary:
dict_data = {"1":["xyz"],"2":["abc","def"],"3":["zzz"]}
Output: (CSV file)
1,3,2
xyz,zzz,abc
,,def
'''
def __init__(self,dictInput,maxLength=0):
'''
Creates a instance with following variables.
dictInput & maxLength
dictInput -> dictionary having values(list) of same length
ex:-
dict_data = {"1":["xyz",""],"2":["abc","def"],"3":["zzz",""]}
maxLength -> length of the list
'''
self.dictInput = dictInput
self.maxLength = maxLength
#classmethod
def list_padding(cls,dictInput):
'''
converts input dictionary having list (as values) of varying lenghts into constant length.
Also returns class variables dictInput & maxLength
Note:
dictInput represents the dictionary after padding is applied.
maxLength represents the length of the list(values in dictionary) having maximum number of items.
Ex:-
input dictionary:
dict_data = {"1":["xyz"],"2":["abc","def"],"3":["zzz"]}
output dictionary:
dict_data = {"1":["xyz",""],"2":["abc","def"],"3":["zzz",""]}
'''
cls.dictInput = dictInput
listValues = dictInput.values()
listValues.sort(key = lambda i: len(i))
maxLength = len(listValues[-1])
for i in listValues:
while(len(i) < maxLength):
i.append('')
return cls(dictInput,maxLength)
def write_to_csv(self):
with open('sample_file.csv','wb') as out_file:
writer = csv.writer(out_file,dialect = 'excel')
headers = [k for k in self.dictInput]
items = [self.dictInput[k] for k in self.dictInput]
writer.writerow(headers)
c = 0
while (c < self.maxLength):
writer.writerow([i[c] for i in items])
c += 1
dict_data = {"1":["xyz"],"2":["abc","def"],"3":["zzz"]}
cf = CsvfileWriter.list_padding(dict_data)
cf.write_to_csv()

Answer 2

The following works in Python 2:
import csv
dict_data = {
"1":["xyz"],
"2":["abc","def"],
"3":["zzz"]
}
def transpose(cols):
return map(lambda *row: list(row), *cols)
with open('k.csv','w') as out_file:
writer = csv.writer(out_file,dialect = 'excel')
headers = dict_data.keys()
items = transpose(dict_data.values())
writer.writerow(headers)
writer.writerows(items)
I can't take credit for the transpose function, which I picked up from here. It turns a list of columns into a list of rows, automatically padding columns that are too short with None. Fortunately, the csv writer outputs blanks for None values, which is exactly what's needed.
(In Python 3, map behaves differently (no padding), so it would require some changes.)
Edit: A replacement transpose function that works for both Python 2 and 3 is:
def transpose(cols):
def mypop(l):
try:
return l.pop(0)
except IndexError:
return ''
while any(cols):
yield [mypop(l) for l in cols]