3 Arrays (X,Y,Z) 到 2 轴 (X,Y) 和网格 (Z)

Question

I repeating the same step on several results from my data. I am looking to convert my arrays into a lookup table:

import pandas as pd


x = np.array(
    [
        1.0,1.0,1.0,1.0,1.0,2.0,2.0,2.0,2.0,2.0,3.0,3.0,3.0,3.0,3.0,4.0,4.0,4.0,4.0,4.0,5.0,5.0,5.0,5.0,5.0
    ]
)
y = np.array(
    [
        10.0,20.0,30.0,40.0,50.0,10.0,20.0,30.0,40.0,50.0,10.0,20.0,30.0,40.0,50.0,10.0,20.0,30.0,40.0,50.0,10.0,20.0,30.0,40.0,50.0
    ]
)
z = np.random.rand(25)

data = {"x": x, "y": y, "z": z}
print(data)

Results in:

      x     y         z
0   1.0  10.0  0.822260
1   1.0  20.0  0.521899
2   1.0  30.0  0.064821
3   1.0  40.0  0.853616
4   1.0  50.0  0.944020
5   2.0  10.0  0.055000
6   2.0  20.0  0.328647
7   2.0  30.0  0.949762
8   2.0  40.0  0.904646
9   2.0  50.0  0.927425
10  3.0  10.0  0.738802
11  3.0  20.0  0.508795
12  3.0  30.0  0.246913
13  3.0  40.0  0.810238
14  3.0  50.0  0.340421
15  4.0  10.0  0.274144
16  4.0  20.0  0.738095
17  4.0  30.0  0.255514
18  4.0  40.0  0.784286
19  4.0  50.0  0.114887
20  5.0  10.0  0.443540
21  5.0  20.0  0.691474
22  5.0  30.0  0.311146
23  5.0  40.0  0.557778
24  5.0  50.0  0.670089

I would like to format / shape it in a way so I get the following:

    1           2           3           4           5
10  0.82226     0.055       0.738802    0.274144    0.44354
20  0.521899    0.328647    0.508795    0.738095    0.691474
30  0.064821    0.949762    0.246913    0.255514    0.311146
40  0.853616    0.904646    0.810238    0.784286    0.557778
50  0.94402     0.927425    0.340421    0.114887    0.670089

One way guess I could it is doing a for loop and looking at the unique values, but I was wondering if there is a better/obvious way to do this.

Answer 1

Today I learned what a pivot table is..

Using the pandas module:

df = pd.Dataframe{data}
print(df.pivot(index="y", columns="x", values="z"))