diff --git a/EventStream/data/dataset_polars.py b/EventStream/data/dataset_polars.py
index ed93790c..a7f03e42 100644
--- a/EventStream/data/dataset_polars.py
+++ b/EventStream/data/dataset_polars.py
@@ -690,6 +690,7 @@ def _agg_by_time(self):
         )
 
     def _update_subject_event_properties(self):
+        self.subject_id_dtype = self.events_df.schema["subject_id"]
         if self.events_df is not None:
             logger.debug("Collecting event types")
             self.event_types = (
@@ -700,6 +701,9 @@ def _update_subject_event_properties(self):
             )
 
             n_events = self.events_df.group_by("subject_id").agg(pl.len().alias("count"))
+            # here we cast to str to avoid issues with the subject_id column being various other types as we
+            # will eventually JSON serialize it.
+            n_events = n_events.with_columns(pl.col("subject_id").cast(pl.Utf8))
             self.n_events_per_subject = {
                 subject_id: count for subject_id, count in zip(n_events["subject_id"], n_events["count"])
             }
@@ -707,9 +711,8 @@ def _update_subject_event_properties(self):
 
         if self.subjects_df is not None:
             logger.debug("Collecting subject event counts")
-            subjects_with_no_events = (
-                set(self.subjects_df.get_column("subject_id").to_list()) - self.subject_ids
-            )
+            subjects_df_subjects = self.subjects_df.select(pl.col("subject_id").cast(pl.Utf8))
+            subjects_with_no_events = set(subjects_df_subjects["subject_id"].to_list()) - self.subject_ids
             for sid in subjects_with_no_events:
                 self.n_events_per_subject[sid] = 0
             self.subject_ids.update(subjects_with_no_events)
@@ -725,7 +728,18 @@ def _filter_col_inclusion(cls, df: DF_T, col_inclusion_targets: dict[str, bool |
                     filter_exprs.append(pl.col(col).is_null())
                 case _:
                     try:
-                        incl_list = pl.Series(list(incl_targets), dtype=df.schema[col])
+                        logger.debug(
+                            f"Converting inclusion targets of type {type(list(incl_targets)[0])} for "
+                            f"{col} to {df.schema[col]}"
+                        )
+                        if isinstance(list(incl_targets)[0], str):
+                            incl_list = pl.Series(list(incl_targets), dtype=pl.Utf8)
+                        else:
+                            incl_list = pl.Series(list(incl_targets), dtype=df.schema[col])
+
+                        incl_list = incl_list.cast(df.schema[col])
+
+                        logger.debug(f"Converted to Series of type {incl_list.dtype}")
                     except TypeError as e:
                         incl_targets_by_type = defaultdict(list)
                         for t in incl_targets: