Is there a way to do an `intersect()` of a dataframe with itself without symmetric duplicates? about pyranges HOT 3 CLOSED

gr=pr.from_dict( {'Start':[1,2,10, 14], 'End':[4,5, 20, 18], 'Chromosome':['chr1']*4, 'Strand':['+']*4})
gr
+-----------+-----------+--------------+--------------+
|     Start |       End | Chromosome   | Strand       |
|   (int32) |   (int32) | (category)   | (category)   |
|-----------+-----------+--------------+--------------|
|         1 |         4 | chr1         | +            |
|         2 |         5 | chr1         | +            |
|        10 |        20 | chr1         | +            |
|        14 |        18 | chr1         | +            |
+-----------+-----------+--------------+--------------+
Stranded PyRanges object has 4 rows and 4 columns from 1 chromosomes.
For printing, the PyRanges was sorted on Chromosome and Strand.

jgr._temp =[ '_'.join(sorted( map(str, [i, ib]))) for i, ib in zip( jgr.ID, jgr.ID_b) ]
jgr
+-----------+-----------+--------------+--------------+-----------+-----------+-----------+--------------+-----------+------------+
|     Start |       End | Chromosome   | Strand       |        ID |   Start_b |     End_b | Strand_b     |      ID_b |      _temp |
|   (int32) |   (int32) | (category)   | (category)   |   (int64) |   (int32) |   (int32) | (category)   |   (int64) |   (object) |
|-----------+-----------+--------------+--------------+-----------+-----------+-----------+--------------+-----------+------------|
|         1 |         4 | chr1         | +            |         0 |         2 |         5 | +            |         1 |        0_1 |
|         2 |         5 | chr1         | +            |         1 |         1 |         4 | +            |         0 |        0_1 |
|        10 |        20 | chr1         | +            |         2 |        14 |        18 | +            |         3 |        2_3 |
|        14 |        18 | chr1         | +            |         3 |        10 |        20 | +            |         2 |        2_3 |
+-----------+-----------+--------------+--------------+-----------+-----------+-----------+--------------+-----------+------------+
Stranded PyRanges object has 4 rows and 10 columns from 1 chromosomes.
For printing, the PyRanges was sorted on Chromosome and Strand.

final_gr=pr.PyRanges( jgr.df.groupby('_temp').first() )
final_gr
+-----------+-----------+--------------+--------------+-----------+-----------+-----------+--------------+-----------+
|     Start |       End | Chromosome   | Strand       |        ID |   Start_b |     End_b | Strand_b     |      ID_b |
|   (int32) |   (int32) | (category)   | (category)   |   (int64) |   (int32) |   (int32) | (category)   |   (int64) |
|-----------+-----------+--------------+--------------+-----------+-----------+-----------+--------------+-----------|
|         1 |         4 | chr1         | +            |         0 |         2 |         5 | +            |         1 |
|        10 |        20 | chr1         | +            |         2 |        14 |        18 | +            |         3 |
+-----------+-----------+--------------+--------------+-----------+-----------+-----------+--------------+-----------+
Stranded PyRanges object has 2 rows and 9 columns from 1 chromosomes.
For printing, the PyRanges was sorted on Chromosome and Strand.