python - Python 中迭代两个键

Question

我期待在这里迭代我的两个 key (型号和经销商)并将其记录在 csv 中。也许因为我是 py 的新手，或者是我习惯使用 sql 的方式，所以我不太明白循环两个键并获取数据的想法。目前我正在做一个基本循环来提取数据，任何关于如何解决这个问题的见解都会非常有帮助

我的代码:

for x in data['models']:
   for y in data['models'][x]:
       fetch={'brand': x, 'model':y}
       resul.append(fetch)

for a in data['dealers']:
   for b in data['dealers'][a]:
       fetch={'brand': a, 'dealer':b}

我的输入:

data={ 
 "models" : 
       {
          "ford" : [ "ranger","mustang","ecosport","ikon"],
        "nissan" : ["gt","terrano"],
        "tesla" : ["cyber truck","model x","model s","model s2"],
        "honda" : ["civic", "accord"]
        },
    
 "dealers":
        {
         "tesla": [ "california", "newyork", "ohio"],
         "ford" : ["new jersey","hongkong","beijing","delhi","telaviv","ottawa"],
         "gm" : ["new york","washington dc"],
         "nissan" : ["dubai","saudi arabia"]
         }
}

输出:

| brand | models | dealers|
|-------|--------|---------|
|ford   | ranger | new jery|
|ford   | mustang| hongkong |
|ford   | ecosport| beijing |
|ford   | ikon    | delhi|
|ford   |         | telaviv |
|ford   |         | ottawa |
|nissan | gt      | dubai |
|nissan | terrano | saudi arabia|
|tesla  |cyber truck| california|
|tesla  | model x   | newyork   |
|tesla  | model s   | ohio      |
|tesla  | model s2  |           |
|honda  | civic     |           |
|honda  | accord    |           |
|gm     | new york  |           |
|gm     | washington dc|        |

Answer 1

由于您已使用 pandas 标记了问题，因此这是一种可能的方法，它显着涉及大量 pandas 操作，包括 stack、爆炸并使用unstack reshape

df = pd.DataFrame(data).stack().explode().to_frame()
df = df.set_index(df.groupby(level=[0, 1]).cumcount(), append=True)[0]\
       .unstack(level=1).droplevel(1).rename_axis('brand').reset_index()

---

print(df)

     brand        dealers       models
0     ford     new jersey       ranger
1     ford       hongkong      mustang
2     ford        beijing     ecosport
3     ford          delhi         ikon
4     ford        telaviv          NaN
5     ford         ottawa          NaN
6       gm       new york          NaN
7       gm  washington dc          NaN
8    honda            NaN        civic
9    honda            NaN       accord
10  nissan          dubai           gt
11  nissan   saudi arabia      terrano
12   tesla     california  cyber truck
13   tesla        newyork      model x
14   tesla           ohio      model s
15   tesla            NaN     model s2