Fixed incorrect test codes.

.github/workflows/python-package-conda.yml

@@ -14,10 +14,10 @@ jobs:
 
     steps:
     - uses: actions/checkout@v2
-    - name: Set up Python 3.8
+    - name: Set up Python 3.9
       uses: actions/setup-python@v2
       with:
-        python-version: 3.8
+        python-version: 3.9
     - name: Add conda to system path
       run: |
         # $CONDA is an environment variable pointing to the root of the miniconda directory
@@ -27,7 +27,9 @@ jobs:
         conda env update --file environment.yml --name base
     - name: Test with pytest
       run: |
+        conda update conda -y -q
         conda config --add channels conda-forge
+        conda update conda -y -q
         conda install scikit-learn=1.0.2 pandas=1.3.5  -y -q
         conda install tensorflow joblib pytest -y -q
         conda install imageio scikit-image -y -q

mlxtend/frequent_patterns/tests/test_fpbase.py

@@ -104,12 +104,12 @@ def test_with_dataframe(df):
         test_with_dataframe(sdf)
 
     def test_sparsedataframe_notzero_column(self):
-        dfs = self.df.astype(pd.SparseDtype("int", np.nan))
+        dfs = self.df.astype(pd.SparseDtype("int", 0))
 
         dfs.columns = [i for i in range(len(dfs.columns))]
         self.fpalgo(dfs)
 
-        dfs = self.df.astype(pd.SparseDtype("int", np.nan))
+        dfs = self.df.astype(pd.SparseDtype("int", 0))
 
         dfs.columns = [i + 1 for i in range(len(dfs.columns))]
         assert_raises(
@@ -334,5 +334,10 @@ def compare_dataframes(df1, df2):
     rows1 = sorted(zip(itemsets1, df1["support"]))
     rows2 = sorted(zip(itemsets2, df2["support"]))
 
-    for r1, r2 in zip(rows1, rows2):
-        assert_array_equal(r1, r2)
+    for row1, row2 in zip(rows1, rows2):
+        if row1[0] != row2[0]:
+            msg = f"Expected different frequent itemsets\nx:{row1[0]}\ny:{row2[0]}"
+            raise AssertionError(msg)
+        elif row1[1] != row2[1]:
+            msg = f"Expected different support\nx:{row1[1]}\ny:{row2[1]}"
+            raise AssertionError(msg)

mlxtend/frequent_patterns/tests/test_hmine.py

@@ -13,6 +13,7 @@
     FPTestEx1All,
     FPTestEx2All,
     FPTestEx3All,
+    compare_dataframes,
 )
 
 from mlxtend.frequent_patterns import apriori, fpgrowth, hmine
@@ -176,23 +177,9 @@ def test_compare_correct(self):
         for algo in algorithms.keys():
             self.setUp()
             res_df = algo(self.df, min_support=0.6)
-            compare_df(res_df, expect)
+            compare_dataframes(res_df, expect)
             algorithms[algo] = res_df
 
-        compare_df(algorithms[hmine], algorithms[fpgrowth])
-        compare_df(algorithms[hmine], algorithms[apriori])
-        compare_df(algorithms[fpgrowth], algorithms[apriori])
-
-
-def compare_df(df1, df2):
-    itemsets1 = [sorted(list(i)) for i in df1["itemsets"]]
-    itemsets2 = [sorted(list(i)) for i in df2["itemsets"]]
-    rows1 = sorted(zip(itemsets1, df1["support"]))
-    rows2 = sorted(zip(itemsets2, df2["support"]))
-    for row1, row2 in zip(rows1, rows2):
-        if row1[0] != row2[0]:
-            msg = f"Expected different frequent itemsets\nx:{row1[0]}\ny:{row2[0]}"
-            raise AssertionError(msg)
-        elif row1[1] != row2[1]:
-            msg = f"Expected different support\nx:{row1[1]}\ny:{row2[1]}"
-            raise AssertionError(msg)
+        compare_dataframes(algorithms[hmine], algorithms[fpgrowth])
+        compare_dataframes(algorithms[hmine], algorithms[apriori])
+        compare_dataframes(algorithms[fpgrowth], algorithms[apriori])