Resolve FutureWarnigns from pandas 1.5.0

pyscal/utils/monotonicity.py

@@ -89,7 +89,7 @@ def modify_dframe_monotonicity(
     # Prepare and check columns:
     for col in monotonicity:
         if dframe[col].dtype != np.float64:
-            dframe.loc[:, col] = dframe[col].astype(float)
+            dframe[col] = dframe[col].astype(float)
 
         # Bail on clearly erroneous data:
         check_almost_monotone(dframe[col], digits, monotonicity[col]["sign"])

pyscal/utils/testing.py

@@ -129,16 +129,16 @@ def check_table(dframe: pd.DataFrame) -> None:
     if "SW" in dframe and "SG" not in dframe:
         # (avoiding GasWater tables, where sw is an auxiliary column)
         assert len(dframe["SW"].unique()) == len(dframe)
-        assert dframe["SW"].is_monotonic
+        assert dframe["SW"].is_monotonic_increasing
         assert (dframe["SW"] >= 0.0).all()
-        assert dframe["SWN"].is_monotonic
+        assert dframe["SWN"].is_monotonic_increasing
         assert dframe["SON"].is_monotonic_decreasing
-        assert dframe["SWNPC"].is_monotonic
+        assert dframe["SWNPC"].is_monotonic_increasing
     if "SG" in dframe:
         assert len(dframe["SG"].unique()) == len(dframe)
-        assert dframe["SG"].is_monotonic
+        assert dframe["SG"].is_monotonic_increasing
         assert (dframe["SG"] >= 0.0).all()
-        assert dframe["SGN"].is_monotonic
+        assert dframe["SGN"].is_monotonic_increasing
         assert dframe["SON"].is_monotonic_decreasing
     if "KROW" in dframe:
         assert series_decreasing(dframe["KROW"])

tests/test_slgof.py

@@ -14,7 +14,7 @@ def check_table(dframe):
     """Check sanity of important columns"""
     assert not dframe.empty
     assert not dframe.isnull().values.any()
-    assert dframe["SL"].is_monotonic
+    assert dframe["SL"].is_monotonic_increasing
     assert (dframe["SL"] >= 0.0).all()
     assert (dframe["SL"] <= 1.0).all()
     # Increasing, but not monotonically for slgof