[SPARK-40590][TEST] Fix ps.read_parquet when pandas_metadata is True

[itholic]

What changes were proposed in this pull request?

This PR proposes to fix the ps.read_parquet test since the pd.to_parquet is broken when the index is MultiIndex from pandas 1.5.0.

We leverage the pd.to_parquet in the test, so the test failed with pandas 1.5.0 as below (MultiIndex is not respected):

DataFrame shape mismatch
[left]:  (20, 5)
[right]: (20, 4)

Left:
    i32  i64     f  bhello     index
0     0    0   0.0      yo  0.617492
1     1    1   1.0  people  0.823826
2     2    2   2.0  people  0.443275
3     0    3   3.0   hello  0.639776
4     1    4   4.0      yo  0.393410
5     2    0   5.0      yo  0.898860
6     0    1   6.0  people  0.725236
7     1    2   7.0      yo  0.933009
8     2    3   8.0      yo  0.663381
9     0    4   9.0   hello  0.471077
10    1    0  10.0   hello  0.562182
11    2    1  11.0  people  0.734902
12    0    2  12.0      yo  0.956519
13    1    3  13.0   hello  0.860517
14    2    4  14.0  people  0.012749
15    0    0  15.0  people  0.561815
16    1    1  16.0  people  0.389130
17    2    2  17.0   hello  0.930301
18    0    3  18.0   hello  0.835025
19    1    4  19.0      yo  0.212191
i32         int32
i64         int64
f         float64
bhello     object
index     float64
dtype: object

Right:
             i32  i64     f  bhello
   index                           
0  0.617492    0    0   0.0      yo
1  0.823826    1    1   1.0  people
2  0.443275    2    2   2.0  people
3  0.639776    0    3   3.0   hello
4  0.393410    1    4   4.0      yo
5  0.898860    2    0   5.0      yo
6  0.725236    0    1   6.0  people
7  0.933009    1    2   7.0      yo
8  0.663381    2    3   8.0      yo
9  0.471077    0    4   9.0   hello
10 0.562182    1    0  10.0   hello
11 0.734902    2    1  11.0  people
12 0.956519    0    2  12.0      yo
13 0.860517    1    3  13.0   hello
14 0.012749    2    4  14.0  people
15 0.561815    0    0  15.0  people
16 0.389130    1    1  16.0  people
17 0.930301    2    2  17.0   hello
18 0.835025    0    3  18.0   hello
19 0.212191    1    4  19.0      yo
i32         int32
i64         int64
f         float64
bhello     object
dtype: object

Why are the changes needed?

We should make the all test passing with pandas 1.5.0.

Does this PR introduce any user-facing change?

No.

How was this patch tested?

Manually test with pandas 1.5.0.

[itholic]

Here is the related discussion with pandas community in the pandas repo, and confirmed as regression.

[itholic]

cc @HyukjinKwon Can you take a look when you find some time? The comment is resolved

[HyukjinKwon]

Merged to master.