I am trying to write a nested dictionary into python. I have a dictionary like below:
{'09-04-2018' : {1: 11, 2: 5, 3: 1, 4: 1, 5: 0} , '10-04-2018' : {1: 5, 2: 1, 3: 1, 4: 1, 5: 0}}
and i wanted to write it something like:
count,09-04-2018,10-04-2018
1,11,5
2,5,1
3,1,1
4,1,1
5,0,0
The following produces the requested output:
data = {'09-04-2018' : {1: 11, 2: 5, 3: 1, 4: 1, 5: 0} , '10-04-2018' : {1: 5, 2: 1, 3: 1, 4: 1, 5: 0}}
rows = []
keys = sorted(data)
header = ['count'] + keys
counts = sorted(set(k for v in data.values() for k in v))
for count in counts:
l = [count]
for key in keys:
l.append(data[key].get(count))
rows.append(l)
print header
print rows
import csv
with open('output.csv', 'w') as csvfile:
writer = csv.writer(csvfile)
writer.writerow(header)
writer.writerows(rows)
This builds up the rows before writing them it is possible to write them directly rather than appending them to the list and writing the contents of the list.
produces this output:
count,09-04-2018,10-04-2018
1,11,5
2,5,1
3,1,1
4,1,1
5,0,0
If you are open to using a 3rd party library, you can use pandas:
import pandas as pd
d = {'09-04-2018' : {1: 11, 2: 5, 3: 1, 4: 1, 5: 0},
'10-04-2018' : {1: 5, 2: 1, 3: 1, 4: 1, 5: 0}}
# create dataframe from dictionary
df = pd.DataFrame.from_dict(d).reset_index().rename(columns={'index': 'count'})
# write dataframe to csv file
df.to_csv('file.csv', index=False)
print(df)
# count 09-04-2018 10-04-2018
# 0 1 11 5
# 1 2 5 1
# 2 3 1 1
# 3 4 1 1
# 4 5 0 0
You can shorten your code by using zip:
import csv
d = {'09-04-2018' : {1: 11, 2: 5, 3: 1, 4: 1, 5: 0} , '10-04-2018' : {1: 5, 2: 1, 3: 1, 4: 1, 5: 0}}
with open('filename.csv', 'w') as f:
write = csv.writer(f)
full_rows = [i for h in [zip(*b.items()) for _, b in sorted(d.items(), key=lambda x:map(int, x[0].split('-')))] for i in h]
write.writerows([['counts']+[a for a, _ in sorted(d.items(), key=lambda x:map(int, x[0].split('-')))]]+list(zip(*[full_rows[0]]+full_rows[1::2])))
Output:
counts,09-04-2018,10-04-2018
1,11,5
2,5,1
3,1,1
4,1,1
5,0,0
