将字典的嵌套列表展平到Pandas Dataframe中

Question

我正在阅读下面的json结构

{"response":
    {"GDUEACWF":
        {"2018-06-01":
            [{"groupwide_market":"Developed Markets",
            "weights":0.8794132316432903},
            {"groupwide_market":"Developed Markets",
            "weights":0.8794132316432903}],
        "2018-06-02":
            [{"groupwide_market":"Developed Markets",  
            "weights":0.8794132316432903},
            {"groupwide_market":"Developed Markets",
            "weights":0.8794132316432903}]}}}

，然后尝试将其展平为以下格式的Pandas数据框。

|data_date  |groupwide_market  |weights
|2018-06-01 |Developed Markets |0.08794132316432903

我试图通过使用以下代码遍历每对k，v对中的每个列表来做到这一点。它确实可以工作，但是它也非常慢。 10万行数据需要30多分钟才能生成。

df = pd.DataFrame()
#concatenating each line of the list within each dict cell
for k1,v1 in data['response'][mnemonic].items():
    for ele in v1:
        df_temp = pd.concat({k2: pd.Series(v2) for k2, v2 in ele.items()}).transpose()
        df_temp['data_date'] = k1
        df = df.append(df_temp,ignore_index=True)
df.columns = [x[0] for x in df.columns]

我可以知道是否有更有效的方法吗？尝试阅读json_normalize的文档和示例，但无法弄清楚在这种情况下是否适用。

提前谢谢！

Answer 1

假设字典为data，我们可以进行如下操作：

import pandas as pd
pd.DataFrame([(date, *nodes.values()) for info in data["response"].values()
              for date, values in info.items() for nodes in values],
              columns=["date", "market", "weight"])

使用给定的响应作为输入，输出如下：