python - 从字典列表创建 Pandas 数据框，字典键作为列

Question

不确定标题是否足够解释。

我有一个字典列表，我想从中创建一个数据框。为简单起见，列表是:

list=[]

DIC1={'value': 69.0, 'time': 10, 'from': 'Mexico', 'signal_name': 'Part1'}
DIC2={'value': 65.0, 'time': 10, 'from': 'Mexico', 'signal_name': 'Part2'}
DIC3={'value': 60.0, 'time': 11, 'from': 'Mexico', 'signal_name': 'Part1'}
DIC4={'value': 67.0, 'time': 10, 'from': 'Mexico', 'signal_name': 'Part3'}
DIC5={'value': 69.0, 'time': 11, 'from': 'Mexico', 'signal_name': 'Part2'}
DIC6={'value': 70.0, 'time': 12, 'from': 'Mexico', 'signal_name': 'Part1'}
DIC7={'value': 68.0, 'time': 12, 'from': 'Mexico', 'signal_name': 'Part2'}
DIC8={'value': 71.0, 'time': 11, 'from': 'Mexico', 'signal_name': 'Part3'}
DIC9={'value': 50.0, 'time': 12, 'from': 'Mexico', 'signal_name': 'Part3'}

list=[DIC1,DIC2,DIC3,DIC4,DIC5,DIC6,DIC7,DIC8,DIC9]
#Convert to Dataframe
df=pd.DataFrame(list) 

如果我像上面的例子一样简单地将字典列表转换为数据框，我会得到一个像这样的数据框:

    from    signal_name time    value
0   Mexico  Part1       10      69.0
1   Mexico  Part2       10      65.0
2   Mexico  Part1       11      60.0
3   Mexico  Part3       10      67.0
4   Mexico  Part2       11      69.0
5   Mexico  Part1       12      70.0
6   Mexico  Part2       12      68.0
7   Mexico  Part3       11      71.0
8   Mexico  Part3       12      50.0

但我正在尝试获取过滤表，我猜是一种数据透视表？像这样的东西:

    time    from    part1(value)    part2(value)    part3(value)
0   10      Mexico      69.0            65.0            67.0
1   11      Mexico      60.0            69.0            71.0
2   12      Mexico      70.0            68.0            50.0

这可能吗？

Answer 1

借助数据透视表

df.pivot_table(index=['from','time'],columns=['signal_name'],values=['value']).reset_index()

输出:

               from time value            signal_name              Part1 Part2 Part30            Mexico   10  69.0  65.0  67.01            Mexico   11  60.0  69.0  71.02            Mexico   12  70.0  68.0  50.0

If you dont want value as separate header then pass values parameter as a string i.e

df.pivot_table(index=['from','time'],columns=['signal_name'],values='value').reset_index()

signal_name    from  time  Part1  Part2  Part30            Mexico    10   69.0   65.0   67.01            Mexico    11   60.0   69.0   71.02            Mexico    12   70.0   68.0   50.0