Fix np.nan, add windows CI workflow

.github/workflows/ci_windows.yaml

@@ -0,0 +1,42 @@
+name: CI
+
+on:
+  push:
+    branches: ["main", "master"]
+  pull_request:
+    branches: ["main", "master"]
+
+jobs:
+  build:
+    strategy:
+      matrix:
+        platform: [windows-latest]
+        python-version: ["3.10"]
+
+    runs-on: ${{ matrix.platform }}
+
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: false
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - uses: actions/cache@v4
+        with:
+          path: ${{ env.pythonLocation }}
+          key: ${{ env.pythonLocation }}-${{ hashFiles('setup.py') }}-${{ hashFiles('docs/requirements.txt') }}
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade --upgrade-strategy eager pip
+          pip install -r requirements.txt
+
+      - name: Test with unittest
+        env:
+          HED_GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          python -m unittest

hed/tools/analysis/annotation_util.py

@@ -199,7 +199,7 @@ def series_to_factor(series):
         series (Series) - Series to be converted to a list.
 
     Returns:
-        list - contains 0's and 1's, empty, 'n/a' and np.NAN are converted to 0.
+        list - contains 0's and 1's, empty, 'n/a' and np.nan are converted to 0.
     """
     replaced = series.replace('n/a', False)
     filled = replaced.fillna(False)
@@ -273,7 +273,7 @@ def to_factor(data, column=None):
         column (str): Optional column name if DataFrame (otherwise column 0).
 
     Returns:
-        list - contains 0's and 1's, empty, 'n/a' and np.NAN are converted to 0.
+        list - contains 0's and 1's, empty, 'n/a' and np.nan are converted to 0.
     """
     if isinstance(data, Series):
         series = data

hed/tools/remodeling/dispatcher.py

@@ -219,7 +219,7 @@ def post_proc_data(df):
             df (DataFrame): The DataFrame to be processed.
 
         Returns:
-            DataFrame: DataFrame with the 'np.NAN replaced by 'n/a'.
+            DataFrame: DataFrame with the 'np.nan replaced by 'n/a'.
         """
 
         dtypes = df.dtypes.to_dict()

hed/tools/remodeling/operations/remap_columns_op.py

@@ -134,7 +134,7 @@ def do_op(self, dispatcher, df, name, sidecar=None):
         """
         df1 = df.copy()
         df1[self.source_columns] = df1[self.source_columns].replace(
-            np.NaN, 'n/a')
+            np.nan, 'n/a')
         for column in self.integer_sources:
             int_mask = df1[column] != 'n/a'
             df1.loc[int_mask, column] = df1.loc[int_mask, column].astype(int)

tests/tools/analysis/test_annotation_util.py

@@ -300,13 +300,13 @@ def test_to_factor(self):
             factor1 = annotation_util.to_factor(series1)
             self.assertEqual(len(series1), len(factor1))
             self.assertEqual(sum(factor1), len(factor1))
-            series2 = Series(['a', '', None, np.NAN, 'n/a'])
+            series2 = Series(['a', '', None, np.nan, 'n/a'])
             factor2 = annotation_util.to_factor(series2)
             self.assertEqual(len(series2), len(factor2))
             self.assertEqual(sum(factor2), 1)
             data = {
                 'Name': ['Alice', '', 'n/a', 1.0],  # Contains a space
-                'Age': [25, np.NaN, 35, 0]
+                'Age': [25, np.nan, 35, 0]
             }
             df = DataFrame(data)
             factor3 = annotation_util.to_factor(df, column='Name')
@@ -321,7 +321,7 @@ def test_series_to_factor(self):
         factor1 = annotation_util.series_to_factor(series1)
         self.assertEqual(len(series1), len(factor1))
         self.assertEqual(sum(factor1), len(factor1))
-        series2 = Series(['a', '', None, np.NAN, 'n/a'])
+        series2 = Series(['a', '', None, np.nan, 'n/a'])
         factor2 = annotation_util.series_to_factor(series2)
         self.assertEqual(len(series2), len(factor2))
         self.assertEqual(sum(factor2), 1)
@@ -465,13 +465,13 @@ def test_to_factor(self):
         factor1 = annotation_util.to_factor(series1)
         self.assertEqual(len(series1), len(factor1))
         self.assertEqual(sum(factor1), len(factor1))
-        series2 = Series(['a', '', None, np.NAN, 'n/a'])
+        series2 = Series(['a', '', None, np.nan, 'n/a'])
         factor2 = annotation_util.to_factor(series2)
         self.assertEqual(len(series2), len(factor2))
         self.assertEqual(sum(factor2), 1)
         data = {
             'Name': ['Alice', '', 'n/a', 1.0],  # Contains a space
-            'Age': [25, np.NaN, 35, 0]
+            'Age': [25, np.nan, 35, 0]
         }
         df = DataFrame(data)
         factor3 = annotation_util.to_factor(df, column='Name')