As one of the comments pointed out, you can use pyranges.join function.
Let's make up some data:
import numpy as np, pyranges as pr, pandas as pd
f1 = pr.from_dict({'Chromosome': ['chr1', 'chr1', 'chr1'], 'Start': [3, 8, 5],
'End': [6, 9, 7], 'Name': ['interval1', 'interval3', 'interval2']})
f2 = pr.from_dict({'Chromosome': ['chr1', 'chr1'], 'Start': [1, 6],
'End': [2, 7], 'Name': ['a', 'b']})
print(f1)
+--------------+-----------+-----------+------------+
| Chromosome | Start | End | Name |
| (category) | (int32) | (int32) | (object) |
|--------------+-----------+-----------+------------|
| chr1 | 3 | 6 | interval1 |
| chr1 | 8 | 9 | interval3 |
| chr1 | 5 | 7 | interval2 |
+--------------+-----------+-----------+------------+
Unstranded PyRanges object has 3 rows and 4 columns from 1 chromosomes.
For printing, the PyRanges was sorted on Chromosome.
print(f2)
+--------------+-----------+-----------+------------+
| Chromosome | Start | End | Name |
| (category) | (int32) | (int32) | (object) |
|--------------+-----------+-----------+------------|
| chr1 | 1 | 2 | a |
| chr1 | 6 | 7 | b |
+--------------+-----------+-----------+------------+
Unstranded PyRanges object has 2 rows and 4 columns from 1 chromosomes.
For printing, the PyRanges was sorted on Chromosome.
The join method will return a table whose rows correspond to overlapping ranges in f1 and f2. In the returned object, the column names of f1 are preserved, while those of f2 that are also present in f1 have a suffix added (by default, "_b"):
f1.join(f2)
+--------------+-----------+-----------+------------+-----------+-----------+------------+
| Chromosome | Start | End | Name | Start_b | End_b | Name_b |
| (category) | (int32) | (int32) | (object) | (int32) | (int32) | (object) |
|--------------+-----------+-----------+------------+-----------+-----------+------------|
| chr1 | 5 | 7 | interval2 | 6 | 7 | b |
+--------------+-----------+-----------+------------+-----------+-----------+------------+
Unstranded PyRanges object has 1 rows and 7 columns from 1 chromosomes.
For printing, the PyRanges was sorted on Chromosome.
For the overlapping intervals, all the information that was present in f1 and f2 is now available in the object return by join.
Note: by default, join will only return the overlapping intervals. If you also want rows in f1 with no overlap in f2, or those in f2 with no overlap in f1, you can use how='left' or how='right' respectively:
f1.join(f2, how='left')
+--------------+-----------+-----------+------------+-----------+-----------+------------+
| Chromosome | Start | End | Name | Start_b | End_b | Name_b |
| (category) | (int64) | (int64) | (object) | (int64) | (int64) | (object) |
|--------------+-----------+-----------+------------+-----------+-----------+------------|
| chr1 | 5 | 7 | interval2 | 6 | 7 | b |
| chr1 | 3 | 6 | interval1 | -1 | -1 | -1 |
| chr1 | 8 | 9 | interval3 | -1 | -1 | -1 |
+--------------+-----------+-----------+------------+-----------+-----------+------------+
Unstranded PyRanges object has 3 rows and 7 columns from 1 chromosomes.
For printing, the PyRanges was sorted on Chromosome.
Now, you claim to want the indices of the overlapping rows. Thing is, because of its underlying implementation (dictionary of dataframes, one per chromosome), AFAIK you shouldn't be relying on row indices for any task in PyRanges. You can't use them to get certain rows, for example. To all effects, the indices of the dataframes underlying a pyranges object are inaccessible and unmodifiable.
If you really need to, you may simulate the behaviour of indices by creating numerical columns and using them to subset certain rows:
f1.index1=np.arange( len(f1) )
f2.index2=np.arange( len(f2) )
jf=f1.join(f2)
# make f1 a dataframe, get rows which have an overlap in f2
f1[ f1.index1.isin( jf.index1.unique() ) ]
+--------------+-----------+-----------+------------+-----------+
| Chromosome | Start | End | Name | index1 |
| (category) | (int32) | (int32) | (object) | (int64) |
|--------------+-----------+-----------+------------+-----------|
| chr1 | 5 | 7 | interval2 | 2 |
+--------------+-----------+-----------+------------+-----------+
Unstranded PyRanges object has 1 rows and 5 columns from 1 chromosomes.
For printing, the PyRanges was sorted on Chromosome.
