Write Python dictionary to CSV where where keys= columns, values = rows

Question

I have a list of dictionaries that I want to be able to open in Excel, formatted correctly. This is what I have so far, using csv:

list_of_dicts = [{'hello': 'goodbye'}, {'yes': 'no'}]
out_path= "/docs/outfile.txt"
out_file = open(ipath, 'wb')

writer = csv.writer(ofile, dialect = 'excel')

for items in list_of_dicts:
    for k,v in items.items():
        writer.writerow([k,v])

Obviously, when I open the output in Excel, it's formatted like this:

key  value
key  value

What I want is this:

key   key   key

value value value

I can't figure out how to do this, so help would be appreciated. Also, I want the column names to be the dictionary keys, in stead of the default 'A, B, C' etc. Sorry if this is stupid.

Thanks

Answer 1

The csv module has a DictWriter class for this, which is covered quite nicely in another SO answer. The critical point is that you need to know all your column headings when you instantiate the DictWriter. You could construct the list of field names from your list_of_dicts, if so your code becomes

list_of_dicts = [{'hello': 'goodbye'}, {'yes': 'no'}]
out_path= "/docs/outfile.txt"
out_file = open(out_path, 'wb')

fieldnames = sorted(list(set(k for d in list_of_dicts for k in d)))
writer = csv.DictWriter(out_file, fieldnames=fieldnames, dialect='excel')

writer.writeheader() # Assumes Python >= 2.7
for row in list_of_dicts:
    writer.writerow(row)
out_file.close()

The way I've constructed fieldnames scans the entire list_of_dicts, so it will slow down as the size increases. You should instead construct fieldnames directly from the source of your data e.g. if the source of your data is also a csv file you can use a DictReader and use fieldnames = reader.fieldnames.

You can also replace the for loop with a single call to writer.writerows(list_of_dicts) and use a with block to handle file closure, in which case your code would become

list_of_dicts = [{'hello': 'goodbye'}, {'yes': 'no'}]
out_path= "/docs/outfile.txt"

fieldnames = sorted(list(set(k for d in list_of_dicts for k in d)))

with open(out_path, 'wb') as out_file:
    writer = csv.DictWriter(out_file, fieldnames=fieldnames, dialect='excel')
    writer.writeheader()
    writer.writerows(list_of_dicts)