avoid pandas futurewarning for grouping with get_group() (#407)

* fix #407
* Update pandas syntax to avoid FutureWarnings:
   FutureWarning: When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.
* Update CHANGES

CHANGES

@@ -12,13 +12,14 @@ The rules for this file:
   * accompany each entry with github issue/PR number (Issue #xyz)
   * release numbers follow "Semantic Versioning" https://semver.org
 
-09/19/2024 orbeckst
+09/19/2024 orbeckst, jaclark5
 
   * 2.4.1
 
 Fixes
   - [doc] tutorial: use alchemlyb.concat (PR #399)
-
+  - Resolve pandas FutureWarnings in bar_.py and mbar_.py (issue #408 PR #407)
+
 
 09/17/2024 jaclark5, orbeckst
 
@@ -32,6 +33,7 @@ Enhancements
 Changes
   - modernize build system: replaced setup.py,cfg with pyproject.toml (#385)
 
+
 08/24/2024 xiki-tempula
 
   * 2.3.2

src/alchemlyb/estimators/bar_.py

@@ -97,7 +97,11 @@ def fit(self, u_nk):
         # group u_nk by lambda states
         groups = u_nk.groupby(level=u_nk.index.names[1:])
         N_k = [
-            (len(groups.get_group(i)) if i in groups.groups else 0)
+            (
+                len(groups.get_group(i if isinstance(i, tuple) else (i,)))
+                if i in groups.groups
+                else 0
+            )
             for i in u_nk.columns
         ]
 
@@ -119,12 +123,21 @@ def fit(self, u_nk):
                 continue
 
             # get us from lambda step k
-            uk = groups.get_group(self._states_[k])
+            uk = groups.get_group(
+                self._states_[k]
+                if isinstance(self._states_[k], tuple)
+                else (self._states_[k],)
+            )
             # get w_F
             w_f = uk.iloc[:, k + 1] - uk.iloc[:, k]
 
             # get us from lambda step k+1
-            uk1 = groups.get_group(self._states_[k + 1])
+            uk1 = groups.get_group(
+                self._states_[k + 1]
+                if isinstance(self._states_[k + 1], tuple)
+                else (self._states_[k + 1],)
+            )
+
             # get w_R
             w_r = uk1.iloc[:, k] - uk1.iloc[:, k + 1]
 

src/alchemlyb/estimators/mbar_.py

@@ -127,7 +127,11 @@ def fit(self, u_nk):
 
         groups = u_nk.groupby(level=u_nk.index.names[1:])
         N_k = [
-            (len(groups.get_group(i)) if i in groups.groups else 0)
+            (
+                len(groups.get_group(i if isinstance(i, tuple) else (i,)))
+                if i in groups.groups
+                else 0
+            )
             for i in u_nk.columns
         ]
         self._states_ = u_nk.columns.values.tolist()