Description: Fix for Pandas 2.0
Bug-Debian: https://bugs.debian.org/1044064
Author: Andreas Tille <tille@debian.org>
Last-Update: 2024-02-18

--- a/tests/test_binary.py
+++ b/tests/test_binary.py
@@ -346,7 +346,7 @@ def test_nearest(gr, gr2, nearest_how, o
     bedtools_df.Distance = bedtools_df.Distance.abs()
 
     bedtools_df = bedtools_df[bedtools_df.Chromosome2 != "."]
-    bedtools_df = bedtools_df.drop("Chromosome2", 1)
+    bedtools_df = bedtools_df.drop("Chromosome2", axis=1)
 
     result = gr.nearest(
         gr2, strandedness=strandedness, overlap=overlap, how=nearest_how)
@@ -541,7 +541,7 @@ def test_k_nearest(gr, gr2, nearest_how,
     bedtools_df.Distance = bedtools_df.Distance.abs()
 
     bedtools_df = bedtools_df[bedtools_df.Chromosome2 != "."]
-    bedtools_df = bedtools_df.drop("Chromosome2", 1)
+    bedtools_df = bedtools_df.drop("Chromosome2", axis=1)
 
     # cannot test with k > 1 because bedtools algo has different syntax
     # cannot test keep_duplicates "all" or None/False properly, as the semantics is different for bedtools
--- a/pyranges/pyranges.py
+++ b/pyranges/pyranges.py
@@ -2500,7 +2500,7 @@ class PyRanges():
 
         result = pr.PyRanges(new_result)
 
-        if not result.__IX__.is_monotonic:
+        if not result.__IX__.is_monotonic_increasing:
             result = result.sort("__IX__")
 
         result = result.drop(like="__IX__|__k__")
--- a/tests/test_unary.py
+++ b/tests/test_unary.py
@@ -120,9 +120,8 @@ def test_cluster(gr, strand):
             StringIO(result),
             sep="\t",
             header=None,
-            squeeze=True,
             names="Chromosome Start End Name Score Strand Cluster".split(),
-            dtype={"Chromosome": "category"})
+            dtype={"Chromosome": "category"}).squeeze('columns')
 
     print("bedtools_df\n", bedtools_df)
 
@@ -252,9 +251,8 @@ def test_windows(gr):
             StringIO(result),
             sep="\t",
             header=None,
-            squeeze=True,
             names="Chromosome Start End".split(),
-            dtype={"Chromosome": "category"})
+            dtype={"Chromosome": "category"}).squeeze('columns')
 
     print("bedtools_df\n", bedtools_df)