通过Node从CSV创建JSON

Question

I have a CSV of all the states/counties in the US. I'd like to turn this into JSON in the following format:

Alabma: [
  {
    "county_name":"Alabama -- Statewide",
    "fips":1000,
    "fips2":"'01000'",
  },

But the python I'm writing for this produces the following

 State: [{
    "county_name":"Baldwin County",
    "fips":1003,
    "fips2":"'01003'",
    "state_name":" Alabama"
  },

I think I need just a little direction and I can figure this out. Thanks for your help! Here's my python:

import csv
import json
output = { 'state':[] }
with open('county_state.csv', 'rU') as csv_file:
    for state_name in csv.DictReader(csv_file):
        output['state'].append({
            'fips': state_name['fips2'],
            'county': state_name['county_name']

        })

print json.dumps(output)

Some example rows from the CSV file:

county_name fips    fips2   state_name
Autauga County  01001   '01001'  Alabama
Baldwin County  01003   '01003'  Alabama
Barbour County  01005   '01005'  Alabama
Putnam County   12107   '12107'  Florida
St. Johns County    12109   '12109'  Florida
St. Lucie County    12111   '12111'  Florida
Santa Rosa County   12113   '12113'  Florida
Emmet County    19063   '19063'  Iowa
Fayette County  19065   '19065'  Iowa
Floyd County    19067   '19067'  Iowa
Franklin County 19069   '19069'  Iowa
Fremont County  19071   '19071'  Iowa
Greene County   19073   '19073'  Iowa
Grundy County   19075   '19075'  Iowa
Guthrie County  19077   '19077'  Iowa
Hamilton County 19079   '19079'  Iowa
Hancock County  19081   '19081'  Iowa

Answer 1

Your data seems to have mixed delimiters, if you could uniform it to tabs, for example, this should be the solution.

dictreader = DictReader(csvdata, delimiter='\t', quoting=QUOTE_NONE)

output = {}

for state in dictreader:
    if not output.get(state['state_name']):
        output[state['state_name']] = []
    output[state['state_name']].append({'county_name': state['county_name'], 'fips': state['fips'], 'fips2': state['fips2'], 'state_name': state['state_name']})

Answer 2

I think your input CSV file is likely delimited by tabs, not spaces. If that's the case, then this seems to produce JSON in the format you say you want:

from collections import defaultdict, OrderedDict
import csv
import json

output = defaultdict(list)
with open('county_state.csv', 'rb') as csv_file:
    reader = csv.DictReader(csv_file, delimiter='\t')
    for row in reader:
        output[row['state_name']].append(
            OrderedDict((
                (fieldname, row[fieldname]) for fieldname in reader.fieldnames
                                                if fieldname != 'state_name')))

# sort the output by state (optional)
output = OrderedDict(((state, counties) for state, counties in
                                            sorted(output.iteritems())))
print json.dumps(output, indent=2)

Output:

{
  "Alabama": [
    {
      "county_name": "Autauga County",
      "fips": "01001",
      "fips2": "'01001'"
    },
    {
      "county_name": "Baldwin County",
      "fips": "01003",
      "fips2": "'01003'"
    },
    {
      "county_name": "Barbour County",
      "fips": "01005",
      "fips2": "'01005'"
    }
  ],
  "Florida": [
    {
      "county_name": "Putnam County",
      "fips": "12107",
      "fips2": "'12107'"
    },
    {
      "county_name": "St. Johns County",
      "fips": "12109",
      "fips2": "'12109'"
    },
    {
      "county_name": "St. Lucie County",
      "fips": "12111",
      "fips2": "'12111'"
    },
    {
      "county_name": "Santa Rosa County",
      "fips": "12113",
      "fips2": "'12113'"
    }
  ],
  "Iowa": [
    {
      "county_name": "Emmet County",
      "fips": "19063",
      "fips2": "'19063'"
    },
    {
      "county_name": "Fayette County",
      "fips": "19065",
      "fips2": "'19065'"
    },
    {
      "county_name": "Floyd County",
      "fips": "19067",
      "fips2": "'19067'"
    },
    {
      "county_name": "Franklin County",
      "fips": "19069",
      "fips2": "'19069'"
    },
    {
      "county_name": "Fremont County",
      "fips": "19071",
      "fips2": "'19071'"
    },
    {
      "county_name": "Greene County",
      "fips": "19073",
      "fips2": "'19073'"
    },
    {
      "county_name": "Grundy County",
      "fips": "19075",
      "fips2": "'19075'"
    },
    {
      "county_name": "Guthrie County",
      "fips": "19077",
      "fips2": "'19077'"
    },
    {
      "county_name": "Hamilton County",
      "fips": "19079",
      "fips2": "'19079'"
    },
    {
      "county_name": "Hancock County",
      "fips": "19081",
      "fips2": "'19081'"
    }
  ]
}