数据的前几行为例：

Question

我看了很多youtube视频，并看了几个论坛，但是，我找不到问题的答案，因为也许我的数据结构很奇怪，而且我是python新手，所以这对我来说很复杂。

我有一个看起来像这样的“ data.json”文件：

数据的前几行为例：

{
    "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"
    }
}

我已经尝试过这些操作（出于隐私目的，审查了位置链接）：

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)

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)

以上任何链接均无法产生错误。我想做的是我想要的：

打开data.json
从json读取以下列，并将其放入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” ”，“价格”，“初始价格”，“折扣”
不包括第一列，该列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都重复。

您能指导我完成这个吗？

Answer 1

您可以这样做：

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)

使用python将嵌套的Json转换为CSV，并且每行都有唯一的第一列

数据的前几行为例：

我已经尝试过这些操作（出于隐私目的，审查了位置链接）：

1 个答案: