Question

我正在使用CSV文件，其中一些数据以嵌套的JSON格式保存。

示例数据集（当我将CSV文件加载到Pandas中时）： - 我需要将数据（M）类别中的值转换为单独的列。目前，它们已保存为列表

    deviceId (S)    timestamp (S)   data (M)
0   3377    1523128290722   { "deviceId" : { "N" : "3377" }, "device...
1   736 1523128294737   { "deviceId" : { "N" : "736" }, "deviceI...
2   4963    1523128290731   { "deviceId" : { "N" : "4963" }, "device...

列数据（M）中的数据是嵌套列表

user_dict = df['data (M)']

[In] type([user_dict]) is list
[Out] True

以下是我尝试过的一些代码示例：

user_dict = df['data (M)']


pd.DataFrame.from_dict({(i,j): user_dict[i][j] 
                           for i in user_dict.keys() 
                           for j in user_dict[i].keys()},
                       orient='index')


AttributeError: 'str' object has no attribute 'keys'

-

user_dict = df['data (M)']
df2 = pd.DataFrame(user_dict[1:],columns=data[0])


TypeError: Index(...) must be called with a collection of some kind, '{' was passed

最终我想要一个看起来像这样的Pandas DataFrame：

deviceId (S)    timestamp (S)   temperature (N)                  (N) Humidity (N)
0   3377    1523128290722   { "Temperature" : { "N" : "24.2424" }, { "Humdity" : { "N" : "24.2424" }
1   736 1523128294737   { "Temperature" : { "N" : "24.466" }, { "Humdity" : { "N" : "24.2424" }
2   4963    1523128290731   { "Temperature" : { "N" : "26.4534" }, { "Humdity" : { "N" : "24.2424" }

将嵌套JSON值的CSV转换为Pandas

0 个答案: