Allow get_df on all data_types

strax/context.py

@@ -1910,15 +1910,8 @@ def get_df(
 
         """
         df = self.get_array(run_id, targets, save=save, max_workers=max_workers, **kwargs)
-        try:
-            return pd.DataFrame.from_records(df)
-        except Exception as e:
-            if "Data must be 1-dimensional" in str(e):
-                raise ValueError(
-                    f"Cannot load '{targets}' as a dataframe because it has "
-                    "array fields. Please use get_array."
-                )
-            raise
+
+        return strax.convert_structured_array_to_df(df)
 
     def get_zarr(
         self,

strax/utils.py

@@ -813,3 +813,25 @@ def convert_tuple_to_list(init_func_input):
     else:
         # if not a container, return. i.e. int, float, bytes, str etc.
         return func_input
+
+
+@export
+def convert_structured_array_to_df(structured_array):
+    """Convert a structured numpy array to a pandas DataFrame.
+
+    Parameters:
+    structured_array (numpy.ndarray): The structured array to be converted.
+    Returns:
+    pandas.DataFrame: The converted DataFrame.
+
+    """
+
+    data_dict = {}
+    for name in structured_array.dtype.names:
+        col = structured_array[name]
+        if col.ndim > 1:
+            # Convert n-dimensional columns to lists of ndarrays
+            data_dict[name] = [np.array(row) for row in col]
+        else:
+            data_dict[name] = col
+    return pd.DataFrame(data_dict)

tests/test_core.py

@@ -32,6 +32,23 @@ def test_core(allow_multiprocess, max_workers, processor):
     assert bla.dtype == strax.peak_dtype()
 
 
+@processing_conditions
+def test_core_df(allow_multiprocess, max_workers, processor):
+    """Test that get_df works with N-dimensional data."""
+    mystrax = strax.Context(
+        storage=[],
+        register=[Records, Peaks],
+        processors=[processor],
+        allow_multiprocess=allow_multiprocess,
+        use_per_run_defaults=True,
+    )
+
+    df = mystrax.get_df(run_id=run_id, targets="peaks", max_workers=max_workers)
+    p = mystrax.get_single_plugin(run_id, "records")
+    assert len(df.loc[0, "data"]) == 200
+    assert len(df) == p.config["recs_per_chunk"] * p.config["n_chunks"]
+
+
 def test_post_office_state():
     mystrax = strax.Context(
         storage=[],