Fixed handling of numpy.datetime64 objects in DataPointCollection.

Author: hcpchris

highcharts_core/options/series/data/collections.py

@@ -1,3 +1,4 @@
+import datetime
 from typing import Optional, List
 from collections import UserDict
 
@@ -273,7 +274,18 @@ def __setattr__(self, name, value):
                     try:
                         setattr(data_points[index], name, value[index])
                     except validator_errors.CannotCoerceError:
-                        if isinstance(value[index], str) and ',' in value[index]:
+                        if 'datetime64' in value[index].__class__.__name__:
+                            try:
+                                coerced_value = value[index].astype(datetime.datetime)
+                                IS_DATETIME = True
+                            except (ValueError, TypeError):
+                                IS_DATETIME = False
+                        else:
+                            IS_DATETIME = False
+                            
+                        if IS_DATETIME:
+                            setattr(data_points[index], name, coerced_value)
+                        elif isinstance(value[index], str) and ',' in value[index]:
                             coerced_value = value[index].replace(',', '')
                             setattr(data_points[index], name, coerced_value)
                         elif checkers.is_numeric(value[index]) or (

tests/options/series/test_area.py

@@ -3116,6 +3116,31 @@ def test_LineSeries_from_csv(input_files, filename, property_map, kwargs, expect
                                    **kwargs)
 
 
+def test_Bugfix118_LineSeries_from_pandas_with_datetime():
+    import datetime as dt
+    try:
+        import pandas as pd
+        HAS_PANDAS = True
+    except ImportError:
+        HAS_PANDAS = False
+
+    if HAS_PANDAS:
+        # Generate timestamps for the first 5 days of October 2023
+        start_date = dt.datetime(2023, 10, 1)
+        end_date = dt.datetime(2023, 10, 5)
+        date_range = [start_date + dt.timedelta(days=i) for i in range(5)]
+
+        # Create a list of values
+        values = [10, 20, 30, 40, 50]
+
+        # Create a DataFrame
+        df = pd.DataFrame({'Timestamp': date_range, 'Value': values})
+        my_series = cls5.from_pandas(df, property_map={"x": "Timestamp", "y": "Value"})
+
+        assert my_series is not None
+        assert isinstance(my_series, cls5)
+
+
 #### NEXT CLASS
 
 @pytest.mark.parametrize('kwargs, error', STANDARD_PARAMS)