在熊猫数据框中存储字典

Question

我想将字典存储到数据框

dictionary_example={1234:{'choice':0,'choice_set':{0:{'A':100,'B':200,'C':300},1:{'A':200,'B':300,'C':300},2:{'A':500,'B':300,'C':300}}},
   234:{'choice':1,'choice_set':0:{'A':100,'B':400},1:{'A':100,'B':300,'C':1000}},
   1876:{'choice':2,'choice_set':0:{'A': 100,'B':400,'C':300},1:{'A':100,'B':300,'C':1000},2:{'A':600,'B':200,'C':100}}
  }

将它们放入

id choice  0_A  0_B  0_C  1_A  1_B  1_C  2_A  2_B  2_C  
1234  0     100  200 300  200  300  300  500  300  300
234  1      100  400  -   100  300  1000  -    -    -
1876  2     100  400  300  100  300  1000 600 200 100

Answer 1

我认为以下内容非常接近，核心思想只是将这些词典转换为json并依靠pandas.read_json来解析它们。

dictionary_example={
        "1234":{'choice':0,'choice_set':{0:{'A':100,'B':200,'C':300},1:{'A':200,'B':300,'C':300},2:{'A':500,'B':300,'C':300}}},
       "234":{'choice':1,'choice_set':{0:{'A':100,'B':400},1:{'A':100,'B':300,'C':1000}}},
       "1876":{'choice':2,'choice_set':{0:{'A': 100,'B':400,'C':300},1:{'A':100,'B':300,'C':1000},2:{'A':600,'B':200,'C':100}}}

    }

df = pd.read_json(json.dumps(dictionary_example)).T


def to_s(r):
    return pd.read_json(json.dumps(r)).unstack()

flattened_choice_set = df["choice_set"].apply(to_s)

flattened_choice_set.columns = ['_'.join((str(col[0]), col[1])) for col in flattened_choice_set.columns] 

result = pd.merge(df, flattened_choice_set, 
         left_index=True, right_index=True).drop("choice_set", axis=1)

result