CODEWITHSUNDEEP
pythonjsondictionary
Shelly875
Shelly875

Reputation: 91

How to count a value with JSON based on another value in the JSON file

I have a JSON file made up of an array which contains dictionaries, each dictionary is an opinion of a buyer on a specific garage. I want to find out how many occurrence of each car's type I have in each garage, it looks like this:

[
  {"garage": "mike_gar", "reliability": 6, "car_type": "ford", "time": "16:10:36"},
  {"garage": "bill_gar", "reliability": 5,"car_type": "kia", "time": "4:37:22"},
  {"garage": "alison_gar", "reliability": 1, "car_type": "kia", "time": "11:25:40"},
  {"garage": "alison_gar", "reliability": 10, "car_type": "mazda", "time": "2:18:42"},
  {"garage": "mike_gar", "reliability": 3, "car_type": "mazda", "time": "12:14:20"},
  {"garage": "mike_gar", "reliability": 2, "car_type": "ford", "time": "2:08:27"}
]

Assuming we already read from the JSON file to a variable g_arr. I'v tried to use reduce() to count the occurrence , but failed to succeed.

output example: {"garage" : "mike_gar", "types":{"ford" : 2, "mazda": 1}}

Upvotes: 1

Views: 102

Answers (3)

Mykola Zotko
Mykola Zotko

Reputation: 17794

Pandas package is great for working with a such data. You can easily convert your list into a Pandas dataframe.

import pandas as pd

df = pd.DataFrame(g_arr)
print(df)

Prints:

  car_type      garage  reliability      time
0     ford    mike_gar            6  16:10:36
1      kia    bill_gar            5   4:37:22
2      kia  alison_gar            1  11:25:40
3    mazda  alison_gar           10   2:18:42
4    mazda    mike_gar            3  12:14:20
5     ford    mike_gar            2   2:08:27

Than you can use the .groupby() method to group your data and the .size() method to get row counts per group.

print(df.groupby(['garage', 'car_type']).size())

Prints:

garage      car_type
alison_gar  kia         1
            mazda       1
bill_gar    kia         1
mike_gar    ford        2
            mazda       1
dtype: int64

Upvotes: 1

ggorlen
ggorlen

Reputation: 56865

Here's a solution based on reduction. First, I test whether the garage exists in the accumulation dictionary, and if not, create it. Then, I check whether the car type exists in the garage dictionary, and if not, I create it. Finally, I increment the car type.

res = {}

for d in garages:
    if d["garage"] not in res:
        res[d["garage"]] = {"garage": d["garage"], "types": {}}

    if d["car_type"] not in res[d["garage"]]["types"]:
        res[d["garage"]]["types"][d["car_type"]] = 0

    res[d["garage"]]["types"][d["car_type"]] += 1

Output:

{
  'mike_gar': {'garage': 'mike_gar', 'types': {'ford': 2, 'mazda': 1}},
  'bill_gar': {'garage': 'bill_gar', 'types': {'kia': 1}}, 
  'alison_gar': {'garage': 'alison_gar', 'types': {'kia': 1, 'mazda': 1}}
}

Try it!

If you'd like your result in an array, use res.values().

Upvotes: 1

Walid Da.
Walid Da.

Reputation: 948

You can simply parse your data and do the count as the following:

garages = []
cars = []
output = []

for element in data:
    if element['garage'] not in garages: garages.append(element['garage'])
    if element['car_type'] not in cars: cars.append(element['car_type'])

for type in garages:
    current = {}
    current['types'] = {}
    current['garage'] = type
    for element in data:
        if element['car_type'] not in current['types']:
            current['types'][element['car_type']]=0

        if current['garage'] == element['garage']:
            for car_type in cars:
                if element['car_type'] == car_type:
                    current['types'][element['car_type']]+=1
    output.append(current)

print output

the output of executing the above is:

[{'garage': 'mike_gar', 'types': {'mazda': 1, 'kia': 0, 'ford': 2}}, {'garage': 'bill_gar', 'types': {'mazda': 0, 'kia': 1, 'ford': 0}}, {'garage': 'alison_gar', 'types': {'mazda': 1, 'kia': 1, 'ford': 0}}]

Upvotes: 1

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