extracts data from json to CSV

I'm working with opensea response file json, try to get info about nft

json file https://paste.pythondiscord.com/yazaxipiwe full json file https://cdn.discordapp.com/attachments/303906514266226689/1028843885906116658/opensea.json

im getting problems with extracting traits data, traits have daynamic data like some have null traits data and some have 4 to 8 traits data

how to extract like this traits

name    link    traits_type(eye)    traits_type(fur)    traits_type(mouth)
APE 0   https://lh3.google.com  3d eye  red open-mouth 
APE1    https://lh3.google.com  brown   robot   moster
APE2    https://lh3.google.com  white   green   big teeth 
APE3    https://lh3.google.com  monster eye brown   sharp teeth

CSV link

code

file = json.load(open('opensea.json'))
name.append(file['name'])
link.append(file['image_url'])

but how do get traits data?

Solution

It may need to use for-loop to convert it to dictionary with {type:value}

data = {}
for item in file['traits']: 
    key = item['trait_type']
    value = item['value'] 

    data[key] = value

    print(key, value)

and later you can create row (using .get() you can set default value when item doesn't exist)

row = [
     file['name'], 
     file['image_url'], 
     data.get('Eye', ''), 
     data.get('Fur', ''), 
     data.get('Mouth', '')
]

and add to list

all_rows.append(row)

and later convert all to DataFrame

df = pd.DataFrame(all_rows, columns=['name', 'link', 'traits_type(eye)', 'traits_type(fur)', 'traits_type(mouth)']

import json
import pandas as pd

file = json.load(open('opensea.json'))

print(file.keys())

all_rows = []

for asset in file['assets']:
    data = {}
    for item in asset['traits']: 
        key = item['trait_type']
        value = item['value'] 

        data[key] = value

        #print(key, value)
        
    row = [
        asset['name'],
        asset['image_url'],
        data.get('Fur', ''),
        data.get('Eyes', ''),
        data.get('Mouth', '')
    ]
    all_rows.append(row)
    
for item in all_rows:
    print(item)

df = pd.DataFrame(all_rows, columns=['name', 'url', 'fur', 'eyes', 'mouth'])
print(df[['name', 'fur', 'eyes', 'mouth']])

Result:

    name           fur         eyes                     mouth
0   None         Robot       X Eyes                Discomfort
1   None         Robot   Blue Beams                      Grin
2   None         Robot           3d           Bored Cigarette
3   None       Cheetah        Bored                Tongue Out
4   None  Golden Brown       Closed                 Phoneme L
5   None         Brown       X Eyes               Dumbfounded
6   None         Cream        Crazy                     Bored
7   None  Golden Brown        Angry                     Bored
8   None        Zombie        Robot                     Bored
9   None         Brown       Sleepy                Small Grin
10  None           Dmt     Eyepatch                     Bored
11  None    Dark Brown    Bloodshot  Bored Unshaven Cigarette
# ...