json - 使用 python 将嵌套的 Json 转换为 CSV，每行具有唯一的第一列

Question

我看过很多 youtube 视频并查看了几个论坛，但是，我无法找到我的问题的答案，因为也许我的数据结构很奇怪，而且我是一个新手 python 用户，所以这对我来说会很复杂。

我有一个看起来像这样的“data.json”文件：

以前几行数据为例：

{
    "570": {
        "appid": 570,
        "name": "Dota 2",
        "developer": "Valve",
        "publisher": "Valve",
        "score_rank": 65,
        "positive": 848043,
        "negative": 136246,
        "userscore": 86,
        "owners": "100,000,000 .. 200,000,000",
        "average_forever": 29576,
        "average_2weeks": 1541,
        "median_forever": 523,
        "median_2weeks": 823,
        "price": "0",
        "initialprice": "0",
        "discount": "0"
    },
    "578080": {
        "appid": 578080,
        "name": "PLAYERUNKNOWN'S BATTLEGROUNDS",
        "developer": "PUBG Corporation",
        "publisher": "PUBG Corporation",
        "score_rank": 10,
        "positive": 481531,
        "negative": 468448,
        "userscore": 49,
        "owners": "50,000,000 .. 100,000,000",
        "average_forever": 19962,
        "average_2weeks": 762,
        "median_forever": 10055,
        "median_2weeks": 271,
        "price": "2999",
        "initialprice": "2999",
        "discount": "0"
    }
}

我已经尝试过这些事情（审查隐私的位置链接）：

1.

    import json, csv
    infile = open("C:\Users\....\data.json", "r")
    outfile = open("C:\Users\....\bar.csv", "w")
    writer = csv.writer(outfile)
    for row in json.loads(infile.read()):
    writer.write(row)

2. import sys
   import pandas as pd
   from pandas import DataFrame
   import json
   
   
   data=r'C:\Users\....\data.json'
   print ("This is json data input", data)
   
   /* Reads and converts json to dict.
   def js_r(data):
      with open(data, encoding='utf-8') as f_in:
          return(json.load(f_in))
   
   if __name__ == "__main__":
       my_dic_data = js_r(data)
       print("This is my dictionary", my_dic_data)
   keys= my_dic_data.keys()
   print ("The original dict keys",keys)
   /* You assign a new dictionary key- SO_users, and make     dictionary comprehension = { your_key: old_dict[your_key] for `enter code here`your_key in your_keys }
   dict_you_want={'my_items':my_dic_data[0]for key in keys}
   
   print ("These are the keys to dict_you_want",dict_you_want.keys())
   
   
   print ("This is the dictionary of SO_users", dict_you_want)
   df=pd.DataFrame(dict_you_want)
   print ("df:", df)
   /*When .apply(pd.Series) method on items column is applied,     the dictionaries in items column will be used as column headings
   df2=df['my_items'].apply(pd.Series)
   print ("df2",df2)
   df3=pd.concat([df2.drop(['user'],axis=1),df2['user'].apply(pd.Series)],axis=1)
   /*df3=df2['user'].apply(pd.Series)
   
   print ("df3",df3)
   

以上链接均无效，它们会产生错误。我想做的是我想要：

1. 打开数据.json

2. 从 json 中读取以下列并将它们放入 data.csv（与 data.json 相同的位置）：“appid”、“name”、“developer”、“publisher”、“score_rank”、“positive”、“negative”、 “userscore”、“owners”、“average_forever”、“average_2weeks”、“median_forever”、“median_2weeks”、“price”、“initialprice”、“discount”

3. 排除第一列，它基本上是每一行的唯一标识符，并且所有上述子属性在每个唯一标识中重复。

你能指导我完成这个吗？

标签： jsonpython-3.xcsv

Answer 1

你可以这样做：

import json, csv

data = json.load(open('data.json', 'r'))

with open('data.csv', 'w', newline='', encoding='utf-8') as csvfile:
    fieldnames = [...] # whatever fields in whatever order you want
    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)

    writer.writeheader()
    for appid, appinfo in data.items():
        writer.writerow(appinfo)