diff --git a/aligned/active_learning/job.py b/aligned/active_learning/job.py
index 9bbd781..e0cd027 100644
--- a/aligned/active_learning/job.py
+++ b/aligned/active_learning/job.py
@@ -21,12 +21,12 @@ class ActiveLearningJob(RetrivalJob):
     selection: ActiveLearningSelection
     write_policy: ActiveLearningWritePolicy
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         if not self.model.predictions_view.classification_targets:
             logger.info('Found no target. Therefore, no data will be written to an active learning dataset.')
-            return await self.job.to_polars()
+            return await self.job.to_lazy_polars()
 
-        data = await self.job.to_polars()
+        data = await self.job.to_lazy_polars()
         active_learning_set = self.selection.select(self.model, data, self.metric)
         await self.write_policy.write(active_learning_set, self.model)
         return data
diff --git a/aligned/compiler/model.py b/aligned/compiler/model.py
index 4e549cd..94e4939 100644
--- a/aligned/compiler/model.py
+++ b/aligned/compiler/model.py
@@ -4,6 +4,7 @@
 import logging
 from dataclasses import dataclass, field
 from typing import Any, Callable, Type, TypeVar, Generic, TYPE_CHECKING
+from datetime import timedelta
 
 from uuid import uuid4
 
@@ -54,6 +55,9 @@ class ModelMetadata:
     prediction_stream: StreamDataSource | None = field(default=None)
     application_source: BatchDataSource | None = field(default=None)
 
+    acceptable_freshness: timedelta | None = field(default=None)
+    unacceptable_freshness: timedelta | None = field(default=None)
+
     exposed_at_url: str | None = field(default=None)
 
     dataset_store: DatasetStore | None = field(default=None)
@@ -171,6 +175,8 @@ def model_contract(
     application_source: BatchDataSource | None = None,
     dataset_store: DatasetStore | StorageFileReference | None = None,
     exposed_at_url: str | None = None,
+    acceptable_freshness: timedelta | None = None,
+    unacceptable_freshness: timedelta | None = None,
 ) -> Callable[[Type[T]], ModelContractWrapper[T]]:
     def decorator(cls: Type[T]) -> ModelContractWrapper[T]:
 
@@ -190,6 +196,8 @@ def decorator(cls: Type[T]) -> ModelContractWrapper[T]:
             application_source=application_source,
             dataset_store=resolve_dataset_store(dataset_store) if dataset_store else None,
             exposed_at_url=exposed_at_url,
+            acceptable_freshness=acceptable_freshness,
+            unacceptable_freshness=unacceptable_freshness,
         )
         return ModelContractWrapper(metadata, cls)
 
@@ -225,6 +233,8 @@ class MyModel(ModelContract):
         classification_targets=set(),
         regression_targets=set(),
         recommendation_targets=set(),
+        acceptable_freshness=metadata.acceptable_freshness,
+        unacceptable_freshness=metadata.unacceptable_freshness,
     )
     probability_features: dict[str, set[TargetProbability]] = {}
 
diff --git a/aligned/data_file.py b/aligned/data_file.py
index 264dd81..0f9b547 100644
--- a/aligned/data_file.py
+++ b/aligned/data_file.py
@@ -27,9 +27,12 @@ async def read_pandas(self) -> pd.DataFrame:
     async def to_pandas(self) -> pd.DataFrame:
         return await self.read_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         raise NotImplementedError()
 
+    async def to_polars(self) -> pl.DataFrame:
+        return (await self.to_lazy_polars()).collect()
+
     async def write_polars(self, df: pl.LazyFrame) -> None:
         raise NotImplementedError()
 
diff --git a/aligned/feature_store.py b/aligned/feature_store.py
index c645810..07a539f 100644
--- a/aligned/feature_store.py
+++ b/aligned/feature_store.py
@@ -676,9 +676,9 @@ async def insert_into(
             import polars as pl
 
             columns = write_request.all_returned_columns
-            new_df = (await values.to_polars()).select(columns)
+            new_df = (await values.to_lazy_polars()).select(columns)
             try:
-                existing_df = await source.to_polars()
+                existing_df = await source.to_lazy_polars()
                 write_df = pl.concat([new_df, existing_df.select(columns)], how='vertical_relaxed')
             except UnableToFindFileException:
                 write_df = new_df
@@ -710,10 +710,10 @@ async def upsert_into(
         if isinstance(source, WritableFeatureSource):
             await source.upsert(values, [write_request])
         elif isinstance(source, DataFileReference):
-            new_df = (await values.to_polars()).select(write_request.all_returned_columns)
+            new_df = (await values.to_lazy_polars()).select(write_request.all_returned_columns)
             entities = list(write_request.entity_names)
             try:
-                existing_df = await source.to_polars()
+                existing_df = await source.to_lazy_polars()
                 write_df = upsert_on_column(entities, new_df, existing_df)
             except UnableToFindFileException:
                 write_df = new_df
diff --git a/aligned/feature_view/combined_view.py b/aligned/feature_view/combined_view.py
index eb7fd63..a18ab93 100644
--- a/aligned/feature_view/combined_view.py
+++ b/aligned/feature_view/combined_view.py
@@ -67,7 +67,7 @@ class SomeView:
         return store.feature_view(self.metadata.name)
 
     async def process(self, data: dict[str, list[Any]]) -> list[dict]:
-        df = await self.query().process_input(data).to_polars()
+        df = await self.query().process_input(data).to_lazy_polars()
         return df.collect().to_dicts()
 
 
diff --git a/aligned/feature_view/feature_view.py b/aligned/feature_view/feature_view.py
index 016baab..234e42f 100644
--- a/aligned/feature_view/feature_view.py
+++ b/aligned/feature_view/feature_view.py
@@ -5,6 +5,7 @@
 import polars as pl
 import pandas as pd
 
+from datetime import timedelta
 from abc import ABC, abstractproperty
 from dataclasses import dataclass, field
 from typing import TYPE_CHECKING, Any, TypeVar, Generic, Type, Callable
@@ -58,6 +59,8 @@ class FeatureViewMetadata:
     materialized_source: BatchDataSource | None = field(default=None)
     contacts: list[str] | None = field(default=None)
     tags: dict[str, str] = field(default_factory=dict)
+    acceptable_freshness: timedelta | None = field(default=None)
+    unacceptable_freshness: timedelta | None = field(default=None)
 
     @staticmethod
     def from_compiled(view: CompiledFeatureView) -> FeatureViewMetadata:
@@ -69,6 +72,8 @@ def from_compiled(view: CompiledFeatureView) -> FeatureViewMetadata:
             stream_source=view.stream_data_source,
             application_source=view.application_source,
             materialized_source=view.materialized_source,
+            acceptable_freshness=view.acceptable_freshness,
+            unacceptable_freshness=view.unacceptable_freshness,
         )
 
 
@@ -94,6 +99,8 @@ def feature_view(
     materialized_source: BatchDataSource | None = None,
     contacts: list[str] | None = None,
     tags: dict[str, str] | None = None,
+    acceptable_freshness: timedelta | None = None,
+    unacceptable_freshness: timedelta | None = None,
 ) -> Callable[[Type[T]], FeatureViewWrapper[T]]:
     def decorator(cls: Type[T]) -> FeatureViewWrapper[T]:
 
@@ -106,6 +113,8 @@ def decorator(cls: Type[T]) -> FeatureViewWrapper[T]:
             materialized_source=materialized_source,
             contacts=contacts,
             tags=tags or {},
+            acceptable_freshness=acceptable_freshness,
+            unacceptable_freshness=unacceptable_freshness,
         )
         return FeatureViewWrapper(metadata, cls())
 
@@ -296,7 +305,7 @@ def process_input(self, data: ConvertableToRetrivalJob) -> RetrivalJob:
         return self.query().process_input(data)
 
     async def process(self, data: ConvertableToRetrivalJob) -> list[dict]:
-        df = await self.query().process_input(data).to_polars()
+        df = await self.query().process_input(data).to_lazy_polars()
         return df.collect().to_dicts()
 
     async def freshness_in_source(self, source: BatchDataSource) -> datetime | None:
@@ -471,6 +480,8 @@ def compile_with_metadata(feature_view: Any, metadata: FeatureViewMetadata) -> C
             stream_data_source=metadata.stream_source,
             application_source=metadata.application_source,
             materialized_source=metadata.materialized_source,
+            acceptable_freshness=metadata.acceptable_freshness,
+            unacceptable_freshness=metadata.unacceptable_freshness,
             indexes=[],
         )
         aggregations: list[FeatureFactory] = []
@@ -626,7 +637,7 @@ class SomeView(FeatureView):
 
     @classmethod
     async def process(cls, data: dict[str, list[Any]]) -> list[dict]:
-        df = await cls.query().process_input(data).to_polars()
+        df = await cls.query().process_input(data).to_lazy_polars()
         return df.collect().to_dicts()
 
     @staticmethod
@@ -684,7 +695,7 @@ class MyView:
 @feature_view(
     name="{view_name}",
     description="some description",
-    source={batch_source_code}
+    source={batch_source_code},
     stream_source=None,
 )
 class MyView:
diff --git a/aligned/feature_view/tests/test_joined_source.py b/aligned/feature_view/tests/test_joined_source.py
index b23bd31..ad36ddd 100644
--- a/aligned/feature_view/tests/test_joined_source.py
+++ b/aligned/feature_view/tests/test_joined_source.py
@@ -78,10 +78,10 @@ async def test_join_different_types_polars() -> None:
     )
 
     new_data = left_data.join(right_data, 'inner', left_on='some_id', right_on='some_id')
-    result = await new_data.to_polars()
+    result = await new_data.to_lazy_polars()
 
     joined = result.collect().sort('some_id', descending=False)
-    assert joined.frame_equal(expected_df.select(joined.columns))
+    assert joined.equals(expected_df.select(joined.columns))
 
 
 @pytest.mark.asyncio
@@ -111,13 +111,13 @@ async def test_join_different_join_keys() -> None:
 
     new_data = left_data.join(right_data, 'inner', left_on='some_id', right_on='other_id')
 
-    result = await new_data.to_polars()
+    result = await new_data.to_lazy_polars()
     req_result = new_data.request_result
 
     joined = result.collect().sort('some_id', descending=False)
 
-    assert joined.frame_equal(expected_df.select(joined.columns))
-    assert joined.select(req_result.entity_columns).frame_equal(expected_df.select(['some_id']))
+    assert joined.equals(expected_df.select(joined.columns))
+    assert joined.select(req_result.entity_columns).equals(expected_df.select(['some_id']))
 
 
 @pytest.mark.asyncio
@@ -136,10 +136,10 @@ async def test_unique_entities() -> None:
         },
     )
 
-    result = await data.unique_on(['some_id'], sort_key='feature').to_polars()
+    result = await data.unique_on(['some_id'], sort_key='feature').to_lazy_polars()
     sorted = result.sort('some_id').select(['some_id', 'feature']).collect()
 
-    assert sorted.frame_equal(expected_df)
+    assert sorted.equals(expected_df)
 
 
 @pytest.mark.asyncio
diff --git a/aligned/jobs/tests/test_combined_job.py b/aligned/jobs/tests/test_combined_job.py
index 981a30e..3d70b37 100644
--- a/aligned/jobs/tests/test_combined_job.py
+++ b/aligned/jobs/tests/test_combined_job.py
@@ -27,7 +27,7 @@ async def test_combined_polars(
     job = CombineFactualJob(
         jobs=[retrival_job, retrival_job_with_timestamp], combined_requests=[combined_retrival_request]
     )
-    data = (await job.to_polars()).collect()
+    data = (await job.to_lazy_polars()).collect()
 
     assert set(data.columns) == {'id', 'a', 'b', 'c', 'd', 'created_at', 'c+d', 'a+c+d'}
     assert data.shape[0] == 5
diff --git a/aligned/jobs/tests/test_derived_job.py b/aligned/jobs/tests/test_derived_job.py
index f86ef39..c889a83 100644
--- a/aligned/jobs/tests/test_derived_job.py
+++ b/aligned/jobs/tests/test_derived_job.py
@@ -128,7 +128,7 @@ def feature_store() -> FeatureStore:
 @pytest.mark.asyncio
 async def test_aggregate_over_derived() -> None:
 
-    data = await IncomeAgg.query().all().to_polars()
+    data = await IncomeAgg.query().all().to_lazy_polars()
 
     df = data.collect()
 
@@ -142,7 +142,7 @@ async def test_aggregate_over_derived_fact() -> None:
 
     data = await store.features_for(
         entities={'user_id': ['a', 'b']}, features=['income_agg:total_amount']
-    ).to_polars()
+    ).to_lazy_polars()
 
     df = data.collect()
 
diff --git a/aligned/local/job.py b/aligned/local/job.py
index f534081..d93d451 100644
--- a/aligned/local/job.py
+++ b/aligned/local/job.py
@@ -35,7 +35,7 @@ def request_result(self) -> RequestResult:
     async def to_pandas(self) -> pd.DataFrame:
         return self.df.collect().to_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         return self.df
 
 
@@ -217,10 +217,10 @@ async def file_transform_polars(self, df: pl.LazyFrame) -> pl.LazyFrame:
             return df
 
     async def to_pandas(self) -> pd.DataFrame:
-        return (await self.to_polars()).collect().to_pandas()
+        return (await self.to_lazy_polars()).collect().to_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
-        file = await self.source.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        file = await self.source.to_lazy_polars()
         return await self.file_transform_polars(file)
 
 
@@ -292,8 +292,8 @@ async def to_pandas(self) -> pd.DataFrame:
         file = await self.source.read_pandas()
         return self.file_transformations(file)
 
-    async def to_polars(self) -> pl.LazyFrame:
-        file = await self.source.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        file = await self.source.to_lazy_polars()
         return self.file_transform_polars(file)
 
 
@@ -369,7 +369,7 @@ async def file_transformations(self, df: pl.LazyFrame) -> pl.LazyFrame:
         for request in self.requests:
             all_features.update(request.all_required_features)
 
-        result = await self.facts.to_polars()
+        result = await self.facts.to_lazy_polars()
         event_timestamp_col = 'aligned_event_timestamp'
 
         event_timestamp_entity_columns = [
@@ -489,10 +489,10 @@ async def file_transformations(self, df: pl.LazyFrame) -> pl.LazyFrame:
         return result.select([pl.exclude('row_id')])
 
     async def to_pandas(self) -> pd.DataFrame:
-        return (await self.to_polars()).collect().to_pandas()
+        return (await self.to_lazy_polars()).collect().to_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
-        return await self.file_transformations(await self.source.to_polars())
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        return await self.file_transformations(await self.source.to_lazy_polars())
 
     def log_each_job(self) -> RetrivalJob:
         from aligned.retrival_job import LogJob
diff --git a/aligned/local/tests/test_jobs.py b/aligned/local/tests/test_jobs.py
index ba5034c..f75d5bc 100644
--- a/aligned/local/tests/test_jobs.py
+++ b/aligned/local/tests/test_jobs.py
@@ -32,7 +32,7 @@ async def test_file_full_job_polars(retrival_request_without_derived: RetrivalRe
         }
     )
     job = FileFullJob(source=LiteralReference(frame), request=retrival_request_without_derived)
-    data = (await job.to_polars()).collect()
+    data = (await job.to_lazy_polars()).collect()
 
     assert set(data.columns) == {'id', 'a', 'b'}
     assert data.shape[0] == 5
@@ -45,3 +45,4 @@ async def test_write_and_read_feature_store(titanic_feature_store_scd: FeatureSt
     await source.write(definition.to_json().encode('utf-8'))
     store = await source.feature_store()
     assert store is not None
+    assert store.model('titanic').model.predictions_view.acceptable_freshness is not None
diff --git a/aligned/psql/jobs.py b/aligned/psql/jobs.py
index 4155f68..1134b07 100644
--- a/aligned/psql/jobs.py
+++ b/aligned/psql/jobs.py
@@ -127,10 +127,10 @@ def will_load_list_feature(self) -> bool:
         return False
 
     async def to_pandas(self) -> pd.DataFrame:
-        df = await self.to_polars()
+        df = await self.to_lazy_polars()
         return df.collect().to_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         try:
             return pl.read_database(self.query, self.config.url).lazy()
         except Exception as e:
@@ -264,9 +264,9 @@ async def to_pandas(self) -> pd.DataFrame:
         job = await self.psql_job()
         return await job.to_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         job = await self.psql_job()
-        return await job.to_polars()
+        return await job.to_lazy_polars()
 
     async def psql_job(self) -> PostgreSqlJob:
         if isinstance(self.facts, PostgreSqlJob):
@@ -492,7 +492,7 @@ def aggregated_values_from_request(self, request: RetrivalRequest) -> list[Table
         return fetches
 
     async def build_request(self) -> str:
-        facts = await self.facts.to_polars()
+        facts = await self.facts.to_lazy_polars()
         return self.build_request_from_facts(facts)
 
     def build_request_from_facts(self, facts: pl.LazyFrame) -> str:
diff --git a/aligned/redis/job.py b/aligned/redis/job.py
index 1422995..592523d 100644
--- a/aligned/redis/job.py
+++ b/aligned/redis/job.py
@@ -25,16 +25,16 @@ def retrival_requests(self) -> list[RetrivalRequest]:
         return self.requests
 
     async def to_pandas(self) -> pd.DataFrame:
-        return (await self.to_polars()).collect().to_pandas()
+        return (await self.to_lazy_polars()).collect().to_pandas()
 
     def describe(self) -> str:
         features_to_load = [list(request.all_feature_names) for request in self.requests]
         return f'Loading features from Redis using HMGET {features_to_load}'
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         redis = self.config.redis()
 
-        result_df = (await self.facts.to_polars()).collect()
+        result_df = (await self.facts.to_lazy_polars()).collect()
 
         for request in self.requests:
             redis_combine_id = 'redis_combine_entity_id'
diff --git a/aligned/redis/tests/test_redis_job.py b/aligned/redis/tests/test_redis_job.py
index 0862e41..54966f2 100644
--- a/aligned/redis/tests/test_redis_job.py
+++ b/aligned/redis/tests/test_redis_job.py
@@ -149,6 +149,6 @@ async def test_write_job(mocker, retrival_request: RetrivalRequest) -> None:  #
     await source.insert(insert_facts, [retrival_request])
 
     job = FactualRedisJob(RedisConfig.localhost(), requests=[retrival_request], facts=facts)
-    data = await job.to_polars()
+    data = await job.to_lazy_polars()
 
-    assert data.collect().select('x').to_series().series_equal(pl.Series('x', [1, 2, 3, None]))
+    assert data.collect().select('x').to_series().equals(pl.Series('x', [1, 2, 3, None]))
diff --git a/aligned/redshift/jobs.py b/aligned/redshift/jobs.py
index e0d9398..11d49d9 100644
--- a/aligned/redshift/jobs.py
+++ b/aligned/redshift/jobs.py
@@ -63,9 +63,9 @@ async def to_pandas(self) -> pd.DataFrame:
         job = await self.psql_job()
         return await job.to_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         job = await self.psql_job()
-        return await job.to_polars()
+        return await job.to_lazy_polars()
 
     async def psql_job(self) -> PostgreSqlJob:
         if isinstance(self.facts, PostgreSqlJob):
diff --git a/aligned/redshift/sql_job.py b/aligned/redshift/sql_job.py
index c3413ea..005b816 100644
--- a/aligned/redshift/sql_job.py
+++ b/aligned/redshift/sql_job.py
@@ -72,7 +72,7 @@ def select_table(table: TableFetch) -> str:
     from_table = 'FROM '
 
     columns = [col.sql_select for col in table.columns]
-    select = f'SELECT {",".join(columns)}'
+    select = f'SELECT {', '.join(columns)}'
 
     if table.conditions:
         wheres = 'WHERE ' + ' AND '.join(table.conditions)
@@ -169,10 +169,10 @@ def retrival_requests(self) -> list[RetrivalRequest]:
         return self.requests
 
     async def to_pandas(self) -> pd.DataFrame:
-        df = await self.to_polars()
+        df = await self.to_lazy_polars()
         return df.collect().to_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         try:
             return pl.read_sql(self.query, self.config.url).lazy()
         except Exception as e:
diff --git a/aligned/retrival_job.py b/aligned/retrival_job.py
index 9a17ad0..5401643 100644
--- a/aligned/retrival_job.py
+++ b/aligned/retrival_job.py
@@ -253,9 +253,11 @@ async def update_metadata() -> None:
             await data_store.store_train_test_validate(test_metadata)
 
         return TrainTestValidateJob(
-            train_job=self.train_job.on_load(update_metadata).cached_at(train_source),
-            test_job=self.test_job.on_load(update_metadata).cached_at(test_source),
-            validate_job=self.validate_job.on_load(update_metadata).cached_at(validate_source),
+            train_job=self.train_job.cached_at(train_source).on_load(update_metadata).cached_at(train_source),
+            test_job=self.test_job.cached_at(test_source).on_load(update_metadata).cached_at(test_source),
+            validate_job=self.validate_job.cached_at(validate_source)
+            .on_load(update_metadata)
+            .cached_at(validate_source),
             target_columns=self.target_columns,
         )
 
@@ -283,8 +285,8 @@ async def to_pandas(self) -> SupervisedDataSet[pd.DataFrame]:
             data, entities, features, self.target_columns, self.job.request_result.event_timestamp
         )
 
-    async def to_polars(self) -> SupervisedDataSet[pl.LazyFrame]:
-        data = await self.job.to_polars()
+    async def to_lazy_polars(self) -> SupervisedDataSet[pl.LazyFrame]:
+        data = await self.job.to_lazy_polars()
         if self.should_filter_out_null_targets:
             data = data.drop_nulls([column for column in self.target_columns])
 
@@ -375,7 +377,7 @@ class SupervisedTrainJob:
     train_size: float
 
     async def to_pandas(self) -> TrainTestSet[pd.DataFrame]:
-        core_data = await self.job.to_polars()
+        core_data = await self.job.to_lazy_polars()
         data = core_data.data.collect()
         data = data.to_pandas()
 
@@ -393,7 +395,7 @@ async def to_pandas(self) -> TrainTestSet[pd.DataFrame]:
     async def to_polars(self) -> TrainTestSet[pl.DataFrame]:
         # Use the pandas method, as the split is not created for polars yet
         # A but unsure if I should use the same index concept for polars
-        core_data = await self.job.to_polars()
+        core_data = await self.job.to_lazy_polars()
 
         data = core_data.data.collect()
 
@@ -470,9 +472,12 @@ async def to_pandas(self) -> pd.DataFrame:
         raise NotImplementedError(f'For {type(self)}')
 
     @abstractmethod
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         raise NotImplementedError(f'For {type(self)}')
 
+    async def to_polars(self) -> pl.DataFrame:
+        return await (await self.to_lazy_polars()).collect_async()
+
     def describe(self) -> str:
         if isinstance(self, ModificationJob):
             return f'{self.job.describe()} -> {self.__class__.__name__}'
@@ -734,7 +739,7 @@ async def write_to_source(self, source: WritableFeatureSource | DataFileReferenc
         from aligned.sources.local import DataFileReference
 
         if isinstance(source, DataFileReference):
-            await source.write_polars(await self.to_polars())
+            await source.write_polars(await self.to_lazy_polars())
         else:
             await source.insert(self, self.retrival_requests)
 
@@ -757,12 +762,12 @@ class CustomPolarsJob(RetrivalJob, ModificationJob):
     job: RetrivalJob
     polars_method: Callable[[pl.LazyFrame], pl.LazyFrame]
 
-    async def to_polars(self) -> pl.LazyFrame:
-        df = await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        df = await self.job.to_lazy_polars()
         return self.polars_method(df)
 
     async def to_pandas(self) -> pd.DataFrame:
-        df = await self.job.to_polars()
+        df = await self.job.to_lazy_polars()
         return df.collect().to_pandas()
 
 
@@ -778,8 +783,8 @@ class SubsetJob(RetrivalJob, ModificationJob):
     def fraction(self) -> float:
         return self.end_ratio - self.start_ratio
 
-    async def to_polars(self) -> pl.LazyFrame:
-        data = (await self.job.to_polars()).collect()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        data = (await self.job.to_lazy_polars()).collect()
         return subset_polars(data, self.start_ratio, self.end_ratio, self.sort_column).lazy()
 
     async def to_pandas(self) -> pd.DataFrame:
@@ -799,8 +804,8 @@ async def to_pandas(self) -> pd.DataFrame:
         await self.on_load()
         return data
 
-    async def to_polars(self) -> pl.LazyFrame:
-        data = (await self.job.to_polars()).collect()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        data = (await self.job.to_lazy_polars()).collect()
         await self.on_load()
         return data.lazy()
 
@@ -815,12 +820,12 @@ class EncodeDatesJob(RetrivalJob, ModificationJob):
     formatter: DateFormatter
     columns: list[str]
 
-    async def to_polars(self) -> pl.LazyFrame:
-        data = await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        data = await self.job.to_lazy_polars()
         return data.with_columns([self.formatter.encode_polars(column) for column in self.columns])
 
     async def to_pandas(self) -> pd.DataFrame:
-        return (await self.to_polars()).collect().to_pandas()
+        return (await self.to_lazy_polars()).collect().to_pandas()
 
 
 @dataclass
@@ -829,11 +834,11 @@ class InMemoryCacheJob(RetrivalJob, ModificationJob):
     job: RetrivalJob
     cached_data: pl.DataFrame | None = None
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         if self.cached_data is not None:
             return self.cached_data.lazy()
 
-        data = (await self.job.to_polars()).collect()
+        data = (await self.job.to_lazy_polars()).collect()
         self.cached_data = data
         return data.lazy()
 
@@ -860,10 +865,10 @@ def request_result(self) -> RequestResult:
     def retrival_requests(self) -> list[RetrivalRequest]:
         return [self.agg_request]
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         from aligned.local.job import aggregate
 
-        core_frame = await self.job.to_polars()
+        core_frame = await self.job.to_lazy_polars()
 
         existing_cols = set(core_frame.columns)
         agg_features = {agg.name for agg in self.agg_request.aggregated_features}
@@ -877,7 +882,7 @@ async def to_polars(self) -> pl.LazyFrame:
             return await aggregate(self.agg_request, core_frame)
 
     async def to_pandas(self) -> pd.DataFrame:
-        return (await self.to_polars()).collect().to_pandas()
+        return (await self.to_lazy_polars()).collect().to_pandas()
 
     def describe(self) -> str:
         return f'Aggregating over {self.job.describe()}'
@@ -905,9 +910,9 @@ def request_result(self) -> RequestResult:
     def retrival_requests(self) -> list[RetrivalRequest]:
         return RetrivalRequest.combine(self.left_job.retrival_requests + self.right_job.retrival_requests)
 
-    async def to_polars(self) -> pl.LazyFrame:
-        left = await self.left_job.to_polars()
-        right = await self.right_job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        left = await self.left_job.to_lazy_polars()
+        right = await self.right_job.to_lazy_polars()
 
         return left.with_columns(
             pl.col(self.left_event_timestamp).dt.cast_time_unit(self.timestamp_unit),
@@ -931,7 +936,7 @@ def log_each_job(self) -> RetrivalJob:
         return LogJob(sub_log)
 
     async def to_pandas(self) -> pd.DataFrame:
-        return (await self.to_polars()).collect().to_pandas()
+        return (await self.to_lazy_polars()).collect().to_pandas()
 
     def describe(self) -> str:
         return (
@@ -969,9 +974,9 @@ def request_result(self) -> RequestResult:
     def retrival_requests(self) -> list[RetrivalRequest]:
         return RetrivalRequest.combine(self.left_job.retrival_requests + self.right_job.retrival_requests)
 
-    async def to_polars(self) -> pl.LazyFrame:
-        left = await self.left_job.to_polars()
-        right = await self.right_job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        left = await self.left_job.to_lazy_polars()
+        right = await self.right_job.to_lazy_polars()
 
         return_request = self.left_job.request_result
 
@@ -1027,8 +1032,8 @@ class FilteredJob(RetrivalJob, ModificationJob):
     job: RetrivalJob
     condition: DerivedFeature | Feature | str
 
-    async def to_polars(self) -> pl.LazyFrame:
-        df = await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        df = await self.job.to_lazy_polars()
 
         if isinstance(self.condition, str):
             col = pl.col(self.condition)
@@ -1078,8 +1083,8 @@ async def to_pandas(self) -> pd.DataFrame:
         df = await self.job.to_pandas()
         return df.rename(self.mappings)
 
-    async def to_polars(self) -> pl.LazyFrame:
-        df = await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        df = await self.job.to_lazy_polars()
         return df.rename(self.mappings)
 
 
@@ -1092,8 +1097,8 @@ class DropDuplicateEntities(RetrivalJob, ModificationJob):
     def entity_columns(self) -> list[str]:
         return self.job.request_result.entity_columns
 
-    async def to_polars(self) -> pl.LazyFrame:
-        df = await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        df = await self.job.to_lazy_polars()
         return df.unique(subset=self.entity_columns)
 
     async def to_pandas(self) -> pd.DataFrame:
@@ -1118,8 +1123,8 @@ def retrival_requests(self) -> list[RetrivalRequest]:
     async def to_pandas(self) -> pd.DataFrame:
         raise NotImplementedError()
 
-    async def to_polars(self) -> pl.LazyFrame:
-        data = await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        data = await self.job.to_lazy_polars()
 
         update_jobs = []
         for index in self.indexes:
@@ -1155,7 +1160,7 @@ def retrival_requests(self) -> list[RetrivalRequest]:
     async def to_pandas(self) -> pd.DataFrame:
         return pd.DataFrame(self.data)
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         return pl.DataFrame(self.data).lazy()
 
     def describe(self) -> str:
@@ -1191,13 +1196,13 @@ async def to_pandas(self) -> pd.DataFrame:
         logging.debug(df)
         return df
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         if logger.level == 0:
             logging.basicConfig(level=logging.DEBUG)
         job_name = self.retrival_requests[0].name
         logging.debug(f'Starting to run {type(self.job).__name__} - {job_name}')
         try:
-            df = await self.job.to_polars()
+            df = await self.job.to_lazy_polars()
         except Exception as error:
             logging.debug(f'Failed in job: {type(self.job).__name__} - {job_name}')
             raise error
@@ -1237,9 +1242,9 @@ async def to_pandas(self) -> pd.DataFrame:
             list(DropInvalidJob.features_to_validate(self.retrival_requests)), await self.job.to_pandas()
         )
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         return self.validator.validate_polars(
-            list(DropInvalidJob.features_to_validate(self.retrival_requests)), await self.job.to_polars()
+            list(DropInvalidJob.features_to_validate(self.retrival_requests)), await self.job.to_lazy_polars()
         )
 
     def with_subfeatures(self) -> RetrivalJob:
@@ -1328,8 +1333,8 @@ async def compute_derived_features_pandas(self, df: pd.DataFrame) -> pd.DataFram
     async def to_pandas(self) -> pd.DataFrame:
         return await self.compute_derived_features_pandas(await self.job.to_pandas())
 
-    async def to_polars(self) -> pl.LazyFrame:
-        return await self.compute_derived_features_polars(await self.job.to_polars())
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        return await self.compute_derived_features_polars(await self.job.to_lazy_polars())
 
     def remove_derived_features(self) -> RetrivalJob:
         return self.job.remove_derived_features()
@@ -1343,10 +1348,10 @@ class UniqueRowsJob(RetrivalJob, ModificationJob):
     sort_key: str | None = field(default=None)
 
     async def to_pandas(self) -> pd.DataFrame:
-        return (await self.to_polars()).collect().to_pandas()
+        return (await self.to_lazy_polars()).collect().to_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
-        data = await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        data = await self.job.to_lazy_polars()
 
         if self.sort_key:
             data = data.sort(self.sort_key, descending=True)
@@ -1368,8 +1373,8 @@ async def to_pandas(self) -> pd.DataFrame:
 
         return data
 
-    async def to_polars(self) -> pl.LazyFrame:
-        data = await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        data = await self.job.to_lazy_polars()
 
         for request in self.retrival_requests:
             if request.entity_names - set(data.columns):
@@ -1401,8 +1406,8 @@ async def to_pandas(self) -> pd.DataFrame:
                 data[feature] = None
         return data
 
-    async def to_polars(self) -> pl.LazyFrame:
-        data = await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        data = await self.job.to_lazy_polars()
         for request in self.retrival_requests:
 
             missing = request.all_required_feature_names - set(data.columns)
@@ -1453,7 +1458,7 @@ async def data_windows(self, window: AggregateOver, data: pl.DataFrame, now: dat
             raise ValueError('Condition is not supported for stream aggregation, yet')
 
         try:
-            window_data = (await checkpoint.to_polars()).collect()
+            window_data = (await checkpoint.to_lazy_polars()).collect()
 
             if filter_expr is not None:
                 new_data = pl.concat(
@@ -1477,8 +1482,8 @@ async def data_windows(self, window: AggregateOver, data: pl.DataFrame, now: dat
     async def to_pandas(self) -> pd.DataFrame:
         raise NotImplementedError()
 
-    async def to_polars(self) -> pl.LazyFrame:
-        data = (await self.job.to_polars()).collect()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        data = (await self.job.to_lazy_polars()).collect()
 
         # This is used as a dummy frame, as the pl abstraction is not good enough
         lazy_df = pl.DataFrame({}).lazy()
@@ -1530,7 +1535,7 @@ async def to_polars(self) -> AsyncIterator[pl.LazyFrame]:
 
         needed_requests = self.job.retrival_requests
         without_derived = self.job.remove_derived_features()
-        raw_files = (await without_derived.to_polars()).collect()
+        raw_files = (await without_derived.to_lazy_polars()).collect()
         features_to_include = self.job.request_result.features.union(self.job.request_result.entities)
         features_to_include_names = {feature.name for feature in features_to_include}
 
@@ -1546,7 +1551,7 @@ async def to_polars(self) -> AsyncIterator[pl.LazyFrame]:
                 .select_columns(features_to_include_names)
             )
 
-            chunked_df = await chunked_job.to_polars()
+            chunked_df = await chunked_job.to_lazy_polars()
             yield chunked_df
 
     async def to_pandas(self) -> AsyncIterator[pd.DataFrame]:
@@ -1586,8 +1591,8 @@ async def to_pandas(self) -> pd.DataFrame:
             .to_pandas()
         )
 
-    async def to_polars(self) -> pl.LazyFrame:
-        return await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        return await self.job.to_lazy_polars()
 
     def cached_at(self, location: DataFileReference | str) -> RetrivalJob:
         return self
@@ -1621,18 +1626,18 @@ async def to_pandas(self) -> pd.DataFrame:
             await self.location.write_pandas(df)
         return df
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         try:
             logger.debug('Trying to read cache file')
-            df = await self.location.to_polars()
+            df = await self.location.to_lazy_polars()
         except UnableToFindFileException:
             logger.debug('Unable to load file, so fetching from source')
-            df = await self.job.to_polars()
+            df = await self.job.to_lazy_polars()
             logger.debug('Writing result to cache')
             await self.location.write_polars(df)
         except FileNotFoundError:
             logger.debug('Unable to load file, so fetching from source')
-            df = await self.job.to_polars()
+            df = await self.job.to_lazy_polars()
             logger.debug('Writing result to cache')
             await self.location.write_polars(df)
         return df
@@ -1684,8 +1689,8 @@ def retrival_requests(self) -> list[RetrivalRequest]:
     async def to_pandas(self) -> pd.DataFrame:
         return await self.job.to_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
-        return await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        return await self.job.to_lazy_polars()
 
 
 @dataclass
@@ -1707,9 +1712,9 @@ async def to_pandas(self) -> pd.DataFrame:
             self.time_metric.observe(elapsed)
         return df
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         start_time = timeit.default_timer()
-        df = await self.job.to_polars()
+        df = await self.job.to_lazy_polars()
         concrete = df.collect()
         elapsed = timeit.default_timer() - start_time
         logger.debug(f'Computed records in {elapsed} seconds')
@@ -1778,8 +1783,8 @@ async def to_pandas(self) -> pd.DataFrame:
                 df[feature.name] = pd.to_datetime(df[feature.name], infer_datetime_format=True, utc=True)
         return df
 
-    async def to_polars(self) -> pl.LazyFrame:
-        df = await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        df = await self.job.to_lazy_polars()
         org_schema = dict(df.schema)
         for request in self.requests:
             features_to_check = request.all_required_features
@@ -1915,9 +1920,9 @@ async def combine_polars_data(self, df: pl.LazyFrame) -> pl.LazyFrame:
         return df
 
     async def to_pandas(self) -> pd.DataFrame:
-        return (await self.to_polars()).collect().to_pandas()
+        return (await self.to_lazy_polars()).collect().to_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         if not self.jobs:
             raise ValueError(
                 'Have no jobs to fetch. This is probably an internal error.\n'
@@ -1925,7 +1930,7 @@ async def to_polars(self) -> pl.LazyFrame:
                 'Or maybe even submit a PR'
             )
 
-        dfs: list[pl.LazyFrame] = await asyncio.gather(*[job.to_polars() for job in self.jobs])
+        dfs: list[pl.LazyFrame] = await asyncio.gather(*[job.to_lazy_polars() for job in self.jobs])
         results = [job.request_result for job in self.jobs]
 
         joined_entities = set(results[0].entity_columns)
@@ -1989,8 +1994,8 @@ async def to_pandas(self) -> pd.DataFrame:
         else:
             return df
 
-    async def to_polars(self) -> pl.LazyFrame:
-        df = await self.job.to_polars()
+    async def to_lazy_polars(self) -> pl.LazyFrame:
+        df = await self.job.to_lazy_polars()
         if self.include_features:
             total_list = list({ent.name for ent in self.request_result.entities}.union(self.include_features))
             return df.select(total_list)
@@ -2037,10 +2042,10 @@ async def to_pandas(self) -> pd.DataFrame:
         await asyncio.gather(*[trigger.check_pandas(df, self.request_result) for trigger in self.triggers])
         return df
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         import asyncio
 
-        df = await self.job.to_polars()
+        df = await self.job.to_lazy_polars()
         await asyncio.gather(*[trigger.check_polars(df, self.request_result) for trigger in self.triggers])
         return df
 
diff --git a/aligned/schemas/feature_view.py b/aligned/schemas/feature_view.py
index 0d48687..0b00db5 100644
--- a/aligned/schemas/feature_view.py
+++ b/aligned/schemas/feature_view.py
@@ -2,7 +2,7 @@
 
 from typing import TYPE_CHECKING
 
-from datetime import datetime
+from datetime import datetime, timedelta
 from dataclasses import dataclass, field
 
 
@@ -18,7 +18,6 @@
 if TYPE_CHECKING:
     from aligned.retrival_job import RetrivalJob
 
-
 @dataclass
 class CompiledFeatureView(Codable):
     name: str
@@ -36,6 +35,9 @@ class CompiledFeatureView(Codable):
     application_source: BatchDataSource | None = field(default=None)
     materialized_source: BatchDataSource | None = field(default=None)
 
+    acceptable_freshness: timedelta | None = field(default=None)
+    unacceptable_freshness: timedelta | None = field(default=None)
+
     event_triggers: set[EventTrigger] | None = field(default=None)
 
     contacts: list[str] | None = field(default=None)
diff --git a/aligned/schemas/model.py b/aligned/schemas/model.py
index 6246e02..42c1e2b 100644
--- a/aligned/schemas/model.py
+++ b/aligned/schemas/model.py
@@ -1,5 +1,6 @@
 import logging
 from dataclasses import dataclass, field
+from datetime import timedelta
 
 from aligned.request.retrival_request import FeatureRequest, RetrivalRequest
 from aligned.schemas.codable import Codable
@@ -59,6 +60,9 @@ class PredictionsView(Codable):
     classification_targets: set[ClassificationTarget] | None = field(default=None)
     recommendation_targets: set[RecommendationTarget] | None = field(default=None)
 
+    acceptable_freshness: timedelta | None = field(default=None)
+    unacceptable_freshness: timedelta | None = field(default=None)
+
     @property
     def full_schema(self) -> set[Feature]:
 
diff --git a/aligned/schemas/transformation.py b/aligned/schemas/transformation.py
index d9039e6..47f78a0 100644
--- a/aligned/schemas/transformation.py
+++ b/aligned/schemas/transformation.py
@@ -117,7 +117,7 @@ async def run_transformation_test_polars(cls) -> None:
 
             expected = test.output_polars
             if test.transformation.dtype == FeatureType.bool():
-                is_correct = output.series_equal(test.output_polars.alias(alias))
+                is_correct = output.equals(test.output_polars.alias(alias))
                 assert is_correct, (
                     f'Output for {cls.__name__} is not correct.,'
                     f'\nGot: {output},\nexpected: {test.output_polars}'
diff --git a/aligned/server.py b/aligned/server.py
index 9c38550..da06fbf 100644
--- a/aligned/server.py
+++ b/aligned/server.py
@@ -159,7 +159,7 @@ async def get_model(entity_values: dict) -> str:
                     for value in entity_values['event_timestamp']
                 ]
 
-            df = await feature_store.model(name).features_for(entity_values).to_polars()
+            df = await feature_store.model(name).features_for(entity_values).to_lazy_polars()
             pandas_df = df.collect().to_pandas()
             orient = 'values'
             body = ','.join(
@@ -233,7 +233,9 @@ async def root() -> RedirectResponse:
         async def features(payload: APIFeatureRequest) -> dict:
             import json
 
-            df = await feature_store.features_for(payload.entities, features=payload.features).to_polars()
+            df = await feature_store.features_for(
+                payload.entities, features=payload.features
+            ).to_lazy_polars()
             json_data = json.dumps(df.collect().to_dict(as_series=False))
             return Response(content=json_data, media_type='application/json')
 
diff --git a/aligned/source_validation.py b/aligned/source_validation.py
index cd43b3e..b5b0cfc 100644
--- a/aligned/source_validation.py
+++ b/aligned/source_validation.py
@@ -25,7 +25,7 @@ async def validate_sources_in(views: list[SourceRequest]) -> dict[FeatureLocatio
 
     for view in views:
         try:
-            _ = (await view.source.all_data(view.request, limit=1).to_polars()).collect()
+            _ = (await view.source.all_data(view.request, limit=1).to_lazy_polars()).collect()
             results[view.location] = True
         except Exception:
             results[view.location] = False
diff --git a/aligned/sources/local.py b/aligned/sources/local.py
index d3545f7..d7dc7ef 100644
--- a/aligned/sources/local.py
+++ b/aligned/sources/local.py
@@ -62,7 +62,7 @@ async def as_repo_definition(self) -> RepoDefinition:
 
 async def data_file_freshness(reference: DataFileReference, column_name: str) -> datetime | None:
     try:
-        file = await reference.to_polars()
+        file = await reference.to_lazy_polars()
         if isinstance(reference, ColumnFeatureMappable):
             source_column = reference.feature_identifier_for([column_name])[0]
         else:
@@ -121,7 +121,7 @@ async def read_pandas(self) -> pd.DataFrame:
         except HTTPStatusError:
             raise UnableToFindFileException(self.path)
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
 
         if self.path.startswith('http'):
             from io import BytesIO
@@ -203,7 +203,7 @@ def multi_source_features_for(
         )
 
     async def schema(self) -> dict[str, FeatureFactory]:
-        df = await self.to_polars()
+        df = await self.to_lazy_polars()
         return {name: FeatureType.from_polars(pl_type).feature_factory for name, pl_type in df.schema.items()}
 
     async def feature_view_code(self, view_name: str) -> str:
@@ -268,7 +268,7 @@ async def write_pandas(self, df: pd.DataFrame) -> None:
             index=self.config.should_write_index,
         )
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
 
         if not do_file_exist(self.path):
             raise UnableToFindFileException(self.path)
@@ -348,12 +348,12 @@ def __hash__(self) -> int:
         return hash(self.job_group_key())
 
     async def read_pandas(self) -> pd.DataFrame:
-        return (await self.to_polars()).collect().to_pandas()
+        return (await self.to_lazy_polars()).collect().to_pandas()
 
     async def write_pandas(self, df: pd.DataFrame) -> None:
         await self.write_polars(pl.from_pandas(df).lazy())
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         if not do_file_exist(self.path):
             raise UnableToFindFileException(self.path)
 
@@ -389,7 +389,7 @@ async def insert(self, job: RetrivalJob, requests: list[RetrivalRequest]) -> Non
 
         request = requests[0]
 
-        data = await job.to_polars()
+        data = await job.to_lazy_polars()
         data.select(request.all_returned_columns).collect().write_delta(self.path, mode='append')
 
     async def upsert(self, job: RetrivalJob, requests: list[RetrivalRequest]) -> None:
@@ -398,8 +398,8 @@ async def upsert(self, job: RetrivalJob, requests: list[RetrivalRequest]) -> Non
 
         request = requests[0]
 
-        new_data = await job.to_polars()
-        existing = await self.to_polars()
+        new_data = await job.to_lazy_polars()
+        existing = await self.to_lazy_polars()
 
         upsert_on_column(list(request.entity_names), new_data, existing).collect().write_delta(
             self.path, mode='overwrite'
@@ -546,5 +546,5 @@ def job_group_key(self) -> str:
     async def read_pandas(self) -> pd.DataFrame:
         return self.file.collect().to_pandas()
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         return self.file
diff --git a/aligned/sources/psql.py b/aligned/sources/psql.py
index 214e0d9..df6b1a6 100644
--- a/aligned/sources/psql.py
+++ b/aligned/sources/psql.py
@@ -175,7 +175,7 @@ async def insert(self, job: RetrivalJob, requests: list[RetrivalRequest]) -> Non
 
         request = requests[0]
 
-        data = await job.to_polars()
+        data = await job.to_lazy_polars()
         data.select(request.all_returned_columns).collect().write_database(
             self.table, connection=self.config.url, if_exists='append'
         )
diff --git a/aligned/sources/redis.py b/aligned/sources/redis.py
index f50f2a6..3df23e4 100644
--- a/aligned/sources/redis.py
+++ b/aligned/sources/redis.py
@@ -173,7 +173,7 @@ def features_for(self, facts: RetrivalJob, request: FeatureRequest) -> RetrivalJ
     async def insert(self, job: RetrivalJob, requests: list[RetrivalRequest]) -> None:
 
         redis = self.config.redis()
-        data = await job.to_polars()
+        data = await job.to_lazy_polars()
 
         async with redis.pipeline(transaction=True) as pipe:
 
@@ -274,7 +274,7 @@ def make_redis_friendly(self, data: pl.LazyFrame, features: set[Feature]) -> pl.
 
     async def write_to_stream(self, job: RetrivalJob) -> None:
         redis = self.config.redis()
-        df = await job.to_polars()
+        df = await job.to_lazy_polars()
 
         df = self.make_redis_friendly(df, job.request_result.features.union(job.request_result.entities))
         values = df.collect()
diff --git a/aligned/sources/s3.py b/aligned/sources/s3.py
index 6607491..ba079f3 100644
--- a/aligned/sources/s3.py
+++ b/aligned/sources/s3.py
@@ -189,7 +189,7 @@ async def read_pandas(self) -> pd.DataFrame:
         except HTTPStatusError:
             raise UnableToFindFileException()
 
-    async def to_polars(self) -> pl.LazyFrame:
+    async def to_lazy_polars(self) -> pl.LazyFrame:
         try:
             data = await self.storage.read(self.path)
             buffer = BytesIO(data)
diff --git a/aligned/sources/tests/test_parquet.py b/aligned/sources/tests/test_parquet.py
index 852f303..84b6af9 100644
--- a/aligned/sources/tests/test_parquet.py
+++ b/aligned/sources/tests/test_parquet.py
@@ -26,9 +26,9 @@ async def test_read_parquet(point_in_time_data_test: DataTest) -> None:
         )
         store.add_feature_view(view)
 
-        stored = await store.feature_view(view.metadata.name).all().to_polars()
+        stored = await store.feature_view(view.metadata.name).all().to_lazy_polars()
         df = stored.select(source.data.columns).collect()
-        assert df.frame_equal(source.data)
+        assert df.equals(source.data)
 
 
 @pytest.mark.asyncio
@@ -55,7 +55,7 @@ async def test_parquest(point_in_time_data_test: DataTest) -> None:
         point_in_time_data_test.feature_reference,
         event_timestamp_column='event_timestamp',
     )
-    data = (await job.to_polars()).collect()
+    data = (await job.to_lazy_polars()).collect()
 
     expected = point_in_time_data_test.expected_output
 
@@ -63,7 +63,7 @@ async def test_parquest(point_in_time_data_test: DataTest) -> None:
     assert set(expected.columns) == set(data.columns), f'Expected: {expected.columns}\nGot: {data.columns}'
 
     ordered_columns = data.select(expected.columns)
-    assert ordered_columns.frame_equal(expected), f'Expected: {expected}\nGot: {ordered_columns}'
+    assert ordered_columns.equals(expected), f'Expected: {expected}\nGot: {ordered_columns}'
 
 
 @pytest.mark.asyncio
@@ -91,7 +91,7 @@ async def test_parquet_without_event_timestamp(
         point_in_time_data_test_wituout_event_timestamp.entities,
         point_in_time_data_test_wituout_event_timestamp.feature_reference,
     )
-    data = (await job.to_polars()).collect()
+    data = (await job.to_lazy_polars()).collect()
 
     expected = point_in_time_data_test_wituout_event_timestamp.expected_output
 
@@ -99,4 +99,4 @@ async def test_parquet_without_event_timestamp(
     assert set(expected.columns) == set(data.columns), f'Expected: {expected.columns}\nGot: {data.columns}'
 
     ordered_columns = data.select(expected.columns)
-    assert ordered_columns.frame_equal(expected), f'Expected: {expected}\nGot: {ordered_columns}'
+    assert ordered_columns.equals(expected), f'Expected: {expected}\nGot: {ordered_columns}'
diff --git a/aligned/sources/tests/test_psql.py b/aligned/sources/tests/test_psql.py
index 8ba5d94..df89ed1 100644
--- a/aligned/sources/tests/test_psql.py
+++ b/aligned/sources/tests/test_psql.py
@@ -43,7 +43,7 @@ async def test_postgresql(point_in_time_data_test: DataTest, psql: PostgreSQLCon
         point_in_time_data_test.feature_reference,
         event_timestamp_column='event_timestamp',
     )
-    data = (await job.to_polars()).collect()
+    data = (await job.to_lazy_polars()).collect()
 
     expected = point_in_time_data_test.expected_output
 
@@ -51,7 +51,7 @@ async def test_postgresql(point_in_time_data_test: DataTest, psql: PostgreSQLCon
     assert set(expected.columns) == set(data.columns), f'Expected: {expected.columns}\nGot: {data.columns}'
 
     ordered_columns = data.select(expected.columns)
-    assert ordered_columns.frame_equal(expected), f'Expected: {expected}\nGot: {ordered_columns}'
+    assert ordered_columns.equals(expected), f'Expected: {expected}\nGot: {ordered_columns}'
 
 
 @pytest.mark.skipif(
@@ -69,7 +69,7 @@ async def test_postgresql_write(titanic_feature_store: FeatureStore, psql: Postg
     store = titanic_feature_store.model('titanic').using_source(source)
     await store.insert_predictions(data)
 
-    stored_data = await psql.fetch('SELECT * FROM titanic').to_polars()
+    stored_data = await psql.fetch('SELECT * FROM titanic').to_lazy_polars()
     assert_frame_equal(
         pl.DataFrame(data),
         stored_data.collect(),
@@ -78,7 +78,7 @@ async def test_postgresql_write(titanic_feature_store: FeatureStore, psql: Postg
         check_dtype=False,
     )
 
-    preds = await store.predictions_for({'passenger_id': [1, 3, 2, 4]}).to_polars()
+    preds = await store.predictions_for({'passenger_id': [1, 3, 2, 4]}).to_lazy_polars()
     assert_frame_equal(
         pl.DataFrame(data),
         preds.collect(),
@@ -116,7 +116,7 @@ async def test_postgresql_without_event(
         point_in_time_data_test_wituout_event_timestamp.entities,
         point_in_time_data_test_wituout_event_timestamp.feature_reference,
     )
-    data = (await job.to_polars()).collect()
+    data = (await job.to_lazy_polars()).collect()
 
     expected = point_in_time_data_test_wituout_event_timestamp.expected_output
 
@@ -124,4 +124,4 @@ async def test_postgresql_without_event(
     assert set(expected.columns) == set(data.columns), f'Expected: {expected.columns}\nGot: {data.columns}'
 
     ordered_columns = data.select(expected.columns)
-    assert ordered_columns.frame_equal(expected), f'Expected: {expected}\nGot: {ordered_columns}'
+    assert ordered_columns.equals(expected), f'Expected: {expected}\nGot: {ordered_columns}'
diff --git a/aligned/split_strategy.py b/aligned/split_strategy.py
index a0c1852..9c41473 100644
--- a/aligned/split_strategy.py
+++ b/aligned/split_strategy.py
@@ -47,29 +47,29 @@ def sorted_features(self) -> list[str]:
     def train(self) -> DatasetType:
         if isinstance(self.data, pl.DataFrame):
             return self.data[self.train_index.to_list(), :]
-        return self.data.iloc[self.train_index]
+        return self.data.iloc[self.train_index]  # type: ignore
 
     @property
     def train_input(self) -> DatasetType:
-        return self.train[self.sorted_features]
+        return self.train[self.sorted_features]  # type: ignore
 
     @property
     def train_target(self) -> DatasetType:
-        return self.train[list(self.target_columns)]
+        return self.train[list(self.target_columns)]  # type: ignore
 
     @property
     def test(self) -> DatasetType:
         if isinstance(self.data, pl.DataFrame):
             return self.data[self.test_index.to_list(), :]
-        return self.data.iloc[self.test_index]
+        return self.data.iloc[self.test_index]  # type: ignore
 
     @property
     def test_input(self) -> DatasetType:
-        return self.test[self.sorted_features]
+        return self.test[self.sorted_features]  # type: ignore
 
     @property
     def test_target(self) -> DatasetType:
-        return self.test[list(self.target_columns)]
+        return self.test[list(self.target_columns)]  # type: ignore
 
 
 class SupervisedDataSet(Generic[DatasetType]):
@@ -102,19 +102,19 @@ def __init__(
     def entities(self) -> DatasetType:
         if isinstance(self.data, (pl.LazyFrame, pl.DataFrame)):
             return self.data.select(list(self.entity_columns))
-        return self.data[list(self.entity_columns)]
+        return self.data[list(self.entity_columns)]  # type: ignore
 
     @property
     def input(self) -> DatasetType:
         if isinstance(self.data, (pl.LazyFrame, pl.DataFrame)):
             return self.data.select(self.sorted_features)
-        return self.data[self.sorted_features]
+        return self.data[self.sorted_features]  # type: ignore
 
     @property
     def labels(self) -> DatasetType:
         if isinstance(self.data, (pl.LazyFrame, pl.DataFrame)):
             return self.data.select(list(self.target_columns))
-        return self.data[list(self.target_columns)]
+        return self.data[list(self.target_columns)]  # type: ignore
 
 
 class TrainTestValidateSet(Generic[DatasetType]):
@@ -158,22 +158,22 @@ def sorted_features(self) -> list[str]:
     def input(self) -> DatasetType:
         if isinstance(self.data, pl.LazyFrame):
             return self.data.select(self.sorted_features)
-        return self.data[self.sorted_features]
+        return self.data[self.sorted_features]  # type: ignore
 
     @property
     def labels(self) -> DatasetType:
         if isinstance(self.data, pl.LazyFrame):
             return self.data.select(sorted(self.target_columns))
-        return self.data[sorted(self.target_columns)]
+        return self.data[sorted(self.target_columns)]  # type: ignore
 
     @property
     def train(self) -> SupervisedDataSet[DatasetType]:
         if isinstance(self.data, pl.DataFrame):
             data = self.data[self.train_index.to_list(), :]
         else:
-            data = self.data.iloc[self.train_index]
+            data = self.data.iloc[self.train_index]  # type: ignore
 
-        return SupervisedDataSet(
+        return SupervisedDataSet(  # type: ignore
             data,
             self.entity_columns,
             self.feature_columns,
@@ -195,9 +195,9 @@ def test(self) -> SupervisedDataSet[DatasetType]:
         if isinstance(self.data, pl.DataFrame):
             data = self.data[self.test_index.to_list(), :]
         else:
-            data = self.data.iloc[self.test_index]
+            data = self.data.iloc[self.test_index]  # type: ignore
 
-        return SupervisedDataSet(
+        return SupervisedDataSet(  # type: ignore
             data,
             set(self.entity_columns),
             set(self.feature_columns),
@@ -218,8 +218,8 @@ def validate(self) -> SupervisedDataSet[DatasetType]:
         if isinstance(self.data, pl.DataFrame):
             data = self.data[self.validate_index.to_list(), :]
         else:
-            data = self.data.iloc[self.validate_index]
-        return SupervisedDataSet(
+            data = self.data.iloc[self.validate_index]  # type: ignore
+        return SupervisedDataSet(  # type: ignore
             data,
             self.entity_columns,
             set(self.feature_columns),
@@ -311,7 +311,7 @@ def split(data: DataFrame, start_ratio: float, end_ratio: float) -> DataFrame:
                 [develop, split(sub_group, self.train_size_percentage + self.test_size_percentage, 1)], axis=0
             )
 
-        return SplitDataSet(
+        return SplitDataSet(  # type: ignore
             train_input=train.drop(columns=[target_column]),
             train_target=train[target_column],
             develop_input=develop.drop(columns=[target_column]),
diff --git a/aligned/tests/test_model_target.py b/aligned/tests/test_model_target.py
index 4ccf122..17bbe47 100644
--- a/aligned/tests/test_model_target.py
+++ b/aligned/tests/test_model_target.py
@@ -56,15 +56,15 @@ async def test_titanic_model_with_targets_and_scd(titanic_feature_store_scd: Fea
         await titanic_feature_store_scd.model('titanic')
         .with_labels()
         .features_for(entities.to_dict(as_series=False), event_timestamp_column='event_timestamp')
-        .to_polars()
+        .to_lazy_polars()
     )
 
     input_df = dataset.input.collect()
     target_df = dataset.labels.collect()
 
-    assert target_df['survived'].series_equal(expected_data['survived'])
-    assert input_df['is_male'].series_equal(expected_data['is_male'])
-    assert input_df['age'].series_equal(expected_data['age'])
+    assert target_df['survived'].equals(expected_data['survived'])
+    assert input_df['is_male'].equals(expected_data['is_male'])
+    assert input_df['age'].equals(expected_data['age'])
 
 
 @pytest.mark.asyncio
@@ -125,7 +125,7 @@ class TestModel:
     await store.insert_into(FeatureLocation.model('test_model'), {'id': [1, 2, 3], 'a': [10, 14, 20]})
 
     stored_data = pl.read_parquet(path).select(expected_frame.columns)
-    assert stored_data.frame_equal(expected_frame)
+    assert stored_data.equals(expected_frame)
 
 
 @pytest.mark.asyncio
@@ -157,4 +157,4 @@ class TestModel:
 
     columns = set(stored_data.columns).difference(expected_frame.columns)
     assert len(columns) == 0
-    assert stored_data.select(expected_frame.columns).frame_equal(expected_frame)
+    assert stored_data.select(expected_frame.columns).equals(expected_frame)
diff --git a/aligned/tests/test_transformations.py b/aligned/tests/test_transformations.py
index d2894fb..9819b3b 100644
--- a/aligned/tests/test_transformations.py
+++ b/aligned/tests/test_transformations.py
@@ -112,10 +112,12 @@ class TestAgg:
     org_values_job = TestAgg.query().using_source(TestAgg.metadata.source).all()  # type: ignore
     await org_values_job.write_to_source(materialized_source)
 
-    values = await org_values_job.to_polars()
-    df = await TestAgg.query().all().to_polars()  # type: ignore
+    values = await org_values_job.to_lazy_polars()
+    descrete_values = await org_values_job.to_polars()
+    df = await TestAgg.query().all().to_lazy_polars()  # type: ignore
 
-    assert df.sort('dob_ssn').collect().frame_equal(values.sort('dob_ssn').select(df.columns).collect())
+    assert df.sort('dob_ssn').collect().equals(values.sort('dob_ssn').select(df.columns).collect())
+    assert descrete_values.sort('dob_ssn').equals(values.sort('dob_ssn').select(descrete_values.columns).collect())
 
 
 @pytest.mark.asyncio
diff --git a/aligned/worker.py b/aligned/worker.py
index 7a098d0..03b5dcd 100644
--- a/aligned/worker.py
+++ b/aligned/worker.py
@@ -248,7 +248,7 @@ async def process_predictions(
             active_learning_config.selection,
             active_learning_config.write_policy,
         )
-        _ = await job.to_polars()
+        _ = await job.to_lazy_polars()
 
         logger.debug(
             f'Processing {len(records)} predictions in {timeit.default_timer() - start_time} seconds'
diff --git a/conftest.py b/conftest.py
index 4126732..7b22d34 100644
--- a/conftest.py
+++ b/conftest.py
@@ -1,4 +1,5 @@
 from dataclasses import dataclass
+from datetime import timedelta
 from math import ceil, floor
 
 import polars as pl
@@ -632,6 +633,8 @@ def titanic_model_scd(titanic_feature_view_scd: FeatureView) -> ModelContractWra
         'titanic',
         description='A model predicting if a passenger will survive',
         features=[features.age, features.sibsp, features.has_siblings, features.is_male],  # type: ignore
+        acceptable_freshness=timedelta(days=1),
+        unacceptable_freshness=timedelta(days=2),
     )
     class Titanic:
 
diff --git a/setup.cfg b/setup.cfg
index 5a556ea..5833453 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -6,7 +6,7 @@ inline-quotes = 'double'
 # W503 line break before binary operator - not Black/PEP8 compatible
 # SIM106 handle error cases first
 # TC002 Move third-party import into a type-checking block (not compatible with pydantic)
-ignore = E203, W503, SIM106, TC002, SIM110, TC001
+ignore = E203, W503, SIM106, TC002, SIM110, TC001, E231, E201, E202, E241
 enable-extensions = TC, TC1
 pytest-mark-no-parentheses=true
 pytest-fixture-no-parentheses=true
diff --git a/test_data/credit_history_mater.parquet b/test_data/credit_history_mater.parquet
index 02e451b..af9c9a5 100644
Binary files a/test_data/credit_history_mater.parquet and b/test_data/credit_history_mater.parquet differ
diff --git a/test_data/feature-store.json b/test_data/feature-store.json
index b05e14b..72064a8 100644
--- a/test_data/feature-store.json
+++ b/test_data/feature-store.json
@@ -1 +1 @@
-{"metadata": {"created_at": "2024-02-03T20:34:56.568052", "name": "feature_store_location.py", "repo_url": null, "github_url": null}, "feature_views": [{"name": "titanic_parquet", "tags": {}, "source": {"mapping_keys": {}, "type_name": "parquet", "path": "test_data/titanic.parquet", "config": {"engine": "auto", "compression": "snappy", "should_write_index": false}}, "entities": [{"name": "passenger_id", "dtype": {"name": "int32"}, "description": null, "tags": null, "constraints": null}], "features": [{"name": "age", "dtype": {"name": "float"}, "description": "A float as some have decimals", "tags": null, "constraints": [{"name": "lower_bound_inc", "value": 0.0}, {"name": "upper_bound_inc", "value": 100.0}]}, {"name": "cabin", "dtype": {"name": "string"}, "description": null, "tags": null, "constraints": null}, {"name": "sibsp", "dtype": {"name": "int32"}, "description": "Number of siblings on titanic", "tags": null, "constraints": [{"name": "lower_bound_inc", "value": 0.0}, {"name": "upper_bound_inc", "value": 20.0}]}, {"name": "survived", "dtype": {"name": "bool"}, "description": "If the passenger survived", "tags": null, "constraints": null}, {"name": "sex", "dtype": {"name": "string"}, "description": null, "tags": null, "constraints": [{"name": "in_domain", "values": ["male", "female"]}]}, {"name": "name", "dtype": {"name": "string"}, "description": null, "tags": null, "constraints": null}], "derived_features": [{"name": "is_male", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "sex", "location": {"name": "titanic_parquet", "location": "feature_view"}, "dtype": {"name": "string"}}], "transformation": {"name": "equals", "dtype": {"name": "bool"}, "key": "sex", "value": {"name": "string", "value": "male"}}, "depth": 1}, {"name": "is_mr", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "name", "location": {"name": "titanic_parquet", "location": "feature_view"}, "dtype": {"name": "string"}}], "transformation": {"name": "contains", "dtype": {"name": "bool"}, "key": "name", "value": "Mr."}, "depth": 1}, {"name": "has_siblings", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "sibsp", "location": {"name": "titanic_parquet", "location": "feature_view"}, "dtype": {"name": "int32"}}], "transformation": {"name": "not-equals", "dtype": {"name": "bool"}, "key": "sibsp", "value": {"name": "int", "value": 0}}, "depth": 1}, {"name": "is_female", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "sex", "location": {"name": "titanic_parquet", "location": "feature_view"}, "dtype": {"name": "string"}}], "transformation": {"name": "equals", "dtype": {"name": "bool"}, "key": "sex", "value": {"name": "string", "value": "female"}}, "depth": 1}], "description": "Some features from the titanic dataset", "aggregated_features": [], "event_timestamp": null, "stream_data_source": null, "application_source": null, "materialized_source": null, "event_triggers": null, "contacts": null, "indexes": []}, {"name": "titanic", "tags": {}, "source": {"mapping_keys": {"PassengerId": "passenger_id", "Age": "age", "Sex": "sex", "Survived": "survived", "SibSp": "sibsp", "UpdatedAt": "updated_at"}, "type_name": "csv", "path": "test_data/titanic_scd_data.csv", "csv_config": {"seperator": ",", "compression": "infer", "should_write_index": false}, "formatter": {"date_format": "yyyy-MM-ddTHH:mm:ssZ", "time_unit": null, "time_zone": null, "name": "string_form"}}, "entities": [{"name": "passenger_id", "dtype": {"name": "int32"}, "description": null, "tags": null, "constraints": null}], "features": [{"name": "age", "dtype": {"name": "float"}, "description": "A float as some have decimals", "tags": null, "constraints": [{"name": "lower_bound_inc", "value": 0.0}, {"name": "upper_bound_inc", "value": 100.0}]}, 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\ No newline at end of file
diff --git a/test_data/test_model.parquet b/test_data/test_model.parquet
index 78c31e3..537db00 100644
Binary files a/test_data/test_model.parquet and b/test_data/test_model.parquet differ
diff --git a/test_data/titanic-sets.json b/test_data/titanic-sets.json
index 32c55a9..4f0c23f 100644
--- a/test_data/titanic-sets.json
+++ b/test_data/titanic-sets.json
@@ -1 +1 @@
-{"raw_data": [], "train_test": [], "train_test_validation": [{"id": "titanic_test", "name": null, "request_result": {"entities": [{"name": "passenger_id", "dtype": {"name": "int32"}, "description": null, "tags": null, "constraints": null}], "features": [{"name": "is_mr", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "name", "location": {"name": "titanic", "location": "feature_view"}, "dtype": {"name": "string"}}], "transformation": {"name": "contains", "dtype": {"name": "bool"}, "key": "name", "value": "Mr."}, "depth": 1}, {"name": "age", "dtype": {"name": "float"}, "description": "A float as some have decimals", "tags": null, "constraints": [{"name": "lower_bound_inc", "value": 0.0}, {"name": "upper_bound_inc", "value": 100.0}]}, {"name": "cabin", "dtype": {"name": "string"}, "description": null, "tags": null, "constraints": [{"name": "optional"}]}, {"name": "is_female", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "sex", "location": {"name": "titanic", "location": "feature_view"}, "dtype": {"name": "string"}}], "transformation": {"name": "equals", "dtype": {"name": "bool"}, "key": "sex", "value": {"name": "string", "value": "female"}}, "depth": 1}, {"name": "sibsp", "dtype": {"name": "int32"}, "description": "Number of siblings on titanic", "tags": null, "constraints": [{"name": "lower_bound_inc", "value": 0.0}, {"name": "upper_bound_inc", "value": 20.0}, {"name": "optional"}]}, {"name": "is_male", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "sex", "location": {"name": "titanic", "location": "feature_view"}, "dtype": {"name": "string"}}], "transformation": {"name": "equals", "dtype": {"name": "bool"}, "key": "sex", "value": {"name": "string", "value": "male"}}, "depth": 1}, {"name": "survived", "dtype": {"name": "bool"}, "description": "If the passenger survived", "tags": null, "constraints": null}, {"name": "has_siblings", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "sibsp", "location": {"name": "titanic", "location": "feature_view"}, "dtype": {"name": "int32"}}], "transformation": {"name": "not-equals", "dtype": {"name": "bool"}, "key": "sibsp", "value": {"name": "int", "value": 0}}, "depth": 1}, {"name": "sex", "dtype": {"name": "string"}, "description": null, "tags": null, "constraints": [{"name": "in_domain", "values": ["male", "female"]}, {"name": "optional"}]}, {"name": "name", "dtype": {"name": "string"}, "description": null, "tags": null, "constraints": [{"name": "optional"}]}], "event_timestamp": null}, "train_dataset": {"mapping_keys": {}, "type_name": "csv", "path": "test_data/titanic-train.csv", "csv_config": {"seperator": ",", "compression": "infer", "should_write_index": false}, "formatter": {"date_format": "yyyy-MM-ddTHH:mm:ssZ", "time_unit": null, "time_zone": null, "name": "string_form"}}, "test_dataset": {"mapping_keys": {}, "type_name": "csv", "path": "test_data/titanic-test.csv", "csv_config": {"seperator": ",", "compression": "infer", "should_write_index": false}, "formatter": {"date_format": "yyyy-MM-ddTHH:mm:ssZ", "time_unit": null, "time_zone": null, "name": "string_form"}}, "validation_dataset": {"mapping_keys": {}, "type_name": "csv", "path": "test_data/titanic-validate.csv", "csv_config": {"seperator": ",", "compression": "infer", "should_write_index": false}, "formatter": {"date_format": "yyyy-MM-ddTHH:mm:ssZ", "time_unit": null, "time_zone": null, "name": "string_form"}}, "train_size_fraction": 0.6, "test_size_fraction": 0.20000000000000007, "validate_size_fraction": 0.19999999999999996, "target": ["survived"], "description": null, "tags": null}], "active_learning": []}
+{"raw_data": [], "train_test": [], "train_test_validation": [{"id": "titanic_test", "name": null, "request_result": {"entities": [{"name": "passenger_id", "dtype": {"name": "int32"}, "description": null, "tags": null, "constraints": null}], "features": [{"name": "age", "dtype": {"name": "float"}, "description": "A float as some have decimals", "tags": null, "constraints": [{"name": "upper_bound_inc", "value": 100.0}, {"name": "lower_bound_inc", "value": 0.0}]}, {"name": "sex", "dtype": {"name": "string"}, "description": null, "tags": null, "constraints": [{"name": "in_domain", "values": ["male", "female"]}, {"name": "optional"}]}, {"name": "name", "dtype": {"name": "string"}, "description": null, "tags": null, "constraints": [{"name": "optional"}]}, {"name": "is_mr", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "name", "location": {"name": "titanic", "location": "feature_view"}, "dtype": {"name": "string"}}], "transformation": {"name": "contains", "dtype": {"name": "bool"}, "key": "name", "value": "Mr."}, "depth": 1}, {"name": "cabin", "dtype": {"name": "string"}, "description": null, "tags": null, "constraints": [{"name": "optional"}]}, {"name": "sibsp", "dtype": {"name": "int32"}, "description": "Number of siblings on titanic", "tags": null, "constraints": [{"name": "upper_bound_inc", "value": 20.0}, {"name": "lower_bound_inc", "value": 0.0}, {"name": "optional"}]}, {"name": "has_siblings", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "sibsp", "location": {"name": "titanic", "location": "feature_view"}, "dtype": {"name": "int32"}}], "transformation": {"name": "not-equals", "dtype": {"name": "bool"}, "key": "sibsp", "value": {"name": "int", "value": 0}}, "depth": 1}, {"name": "survived", "dtype": {"name": "bool"}, "description": "If the passenger survived", "tags": null, "constraints": null}, {"name": "is_female", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "sex", "location": {"name": "titanic", "location": "feature_view"}, "dtype": {"name": "string"}}], "transformation": {"name": "equals", "dtype": {"name": "bool"}, "key": "sex", "value": {"name": "string", "value": "female"}}, "depth": 1}, {"name": "is_male", "dtype": {"name": "bool"}, "description": null, "tags": null, "constraints": null, "depending_on": [{"name": "sex", "location": {"name": "titanic", "location": "feature_view"}, "dtype": {"name": "string"}}], "transformation": {"name": "equals", "dtype": {"name": "bool"}, "key": "sex", "value": {"name": "string", "value": "male"}}, "depth": 1}], "event_timestamp": null}, "train_dataset": {"mapping_keys": {}, "type_name": "csv", "path": "test_data/titanic-train.csv", "csv_config": {"seperator": ",", "compression": "infer", "should_write_index": false}, "formatter": {"date_format": "yyyy-MM-ddTHH:mm:ssZ", "time_unit": null, "time_zone": null, "name": "string_form"}}, "test_dataset": {"mapping_keys": {}, "type_name": "csv", "path": "test_data/titanic-test.csv", "csv_config": {"seperator": ",", "compression": "infer", "should_write_index": false}, "formatter": {"date_format": "yyyy-MM-ddTHH:mm:ssZ", "time_unit": null, "time_zone": null, "name": "string_form"}}, "validation_dataset": {"mapping_keys": {}, "type_name": "csv", "path": "test_data/titanic-validate.csv", "csv_config": {"seperator": ",", "compression": "infer", "should_write_index": false}, "formatter": {"date_format": "yyyy-MM-ddTHH:mm:ssZ", "time_unit": null, "time_zone": null, "name": "string_form"}}, "train_size_fraction": 0.6, "test_size_fraction": 0.20000000000000007, "validate_size_fraction": 0.19999999999999996, "target": ["survived"], "description": null, "tags": null}], "active_learning": []}
\ No newline at end of file
diff --git a/test_data/titanic-test.csv b/test_data/titanic-test.csv
index 741ec4d..d7321c4 100644
--- a/test_data/titanic-test.csv
+++ b/test_data/titanic-test.csv
@@ -1,21 +1,21 @@
-is_mr,passenger_id,age,cabin,is_female,sibsp,is_male,survived,has_siblings,sex,name
-True,61,22.0,,False,0,True,False,False,male,"Sirayanian, Mr. Orsen"
-False,62,38.0,B28,True,0,False,True,False,female,"Icard, Miss. Amelie"
-True,63,45.0,C83,False,1,True,False,True,male,"Harris, Mr. Henry Birkhardt"
-False,64,4.0,,False,3,True,False,True,male,"Skoog, Master. Harald"
-True,65,,,False,0,True,False,False,male,"Stewart, Mr. Albert A"
-False,66,,,False,1,True,True,True,male,"Moubarek, Master. Gerios"
-True,67,29.0,F33,True,0,False,True,False,female,"Nye, Mrs. (Elizabeth Ramell)"
-True,68,19.0,,False,0,True,False,False,male,"Crease, Mr. Ernest James"
-False,69,17.0,,True,4,False,True,True,female,"Andersson, Miss. Erna Alexandra"
-True,70,26.0,,False,2,True,False,True,male,"Kink, Mr. Vincenz"
-True,71,32.0,,False,0,True,False,False,male,"Jenkin, Mr. Stephen Curnow"
-False,72,16.0,,True,5,False,False,True,female,"Goodwin, Miss. Lillian Amy"
-True,73,21.0,,False,0,True,False,False,male,"Hood, Mr. Ambrose Jr"
-True,74,26.0,,False,1,True,False,True,male,"Chronopoulos, Mr. Apostolos"
-True,75,32.0,,False,0,True,True,False,male,"Bing, Mr. Lee"
-True,76,25.0,F G73,False,0,True,False,False,male,"Moen, Mr. Sigurd Hansen"
-True,77,,,False,0,True,False,False,male,"Staneff, Mr. Ivan"
-True,78,,,False,0,True,False,False,male,"Moutal, Mr. Rahamin Haim"
-False,79,0.83,,False,0,True,True,False,male,"Caldwell, Master. Alden Gates"
-False,80,30.0,,True,0,False,True,False,female,"Dowdell, Miss. Elizabeth"
+age,sex,name,is_mr,passenger_id,is_female,cabin,sibsp,has_siblings,survived,is_male
+22.0,male,"Sirayanian, Mr. Orsen",True,61,False,,0,False,False,True
+38.0,female,"Icard, Miss. Amelie",False,62,True,B28,0,False,True,False
+45.0,male,"Harris, Mr. Henry Birkhardt",True,63,False,C83,1,True,False,True
+4.0,male,"Skoog, Master. Harald",False,64,False,,3,True,False,True
+,male,"Stewart, Mr. Albert A",True,65,False,,0,False,False,True
+,male,"Moubarek, Master. Gerios",False,66,False,,1,True,True,True
+29.0,female,"Nye, Mrs. (Elizabeth Ramell)",True,67,True,F33,0,False,True,False
+19.0,male,"Crease, Mr. Ernest James",True,68,False,,0,False,False,True
+17.0,female,"Andersson, Miss. Erna Alexandra",False,69,True,,4,True,True,False
+26.0,male,"Kink, Mr. Vincenz",True,70,False,,2,True,False,True
+32.0,male,"Jenkin, Mr. Stephen Curnow",True,71,False,,0,False,False,True
+16.0,female,"Goodwin, Miss. Lillian Amy",False,72,True,,5,True,False,False
+21.0,male,"Hood, Mr. Ambrose Jr",True,73,False,,0,False,False,True
+26.0,male,"Chronopoulos, Mr. Apostolos",True,74,False,,1,True,False,True
+32.0,male,"Bing, Mr. Lee",True,75,False,,0,False,True,True
+25.0,male,"Moen, Mr. Sigurd Hansen",True,76,False,F G73,0,False,False,True
+,male,"Staneff, Mr. Ivan",True,77,False,,0,False,False,True
+,male,"Moutal, Mr. Rahamin Haim",True,78,False,,0,False,False,True
+0.83,male,"Caldwell, Master. Alden Gates",False,79,False,,0,False,True,True
+30.0,female,"Dowdell, Miss. Elizabeth",False,80,True,,0,False,True,False
diff --git a/test_data/titanic-train.csv b/test_data/titanic-train.csv
index 925bdb7..04997e7 100644
--- a/test_data/titanic-train.csv
+++ b/test_data/titanic-train.csv
@@ -1,61 +1,61 @@
-is_mr,passenger_id,age,cabin,is_female,sibsp,is_male,survived,has_siblings,sex,name
-True,1,22.0,,False,1,True,False,True,male,"Braund, Mr. Owen Harris"
-True,2,38.0,C85,True,1,False,True,True,female,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)"
-False,3,26.0,,True,0,False,True,False,female,"Heikkinen, Miss. Laina"
-True,4,35.0,C123,True,1,False,True,True,female,"Futrelle, Mrs. Jacques Heath (Lily May Peel)"
-True,5,35.0,,False,0,True,False,False,male,"Allen, Mr. William Henry"
-True,6,,,False,0,True,False,False,male,"Moran, Mr. James"
-True,7,54.0,E46,False,0,False,False,False,other,"McCarthy, Mr. Timothy J"
-False,8,2.0,,False,3,True,False,True,male,"Palsson, Master. Gosta Leonard"
-True,9,27.0,,True,0,False,True,False,female,"Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)"
-True,10,14.0,,True,1,False,True,True,female,"Nasser, Mrs. Nicholas (Adele Achem)"
-False,11,4.0,G6,True,1,False,True,True,female,"Sandstrom, Miss. Marguerite Rut"
-False,12,58.0,C103,True,0,False,True,False,female,"Bonnell, Miss. Elizabeth"
-True,13,20.0,,False,0,True,False,False,male,"Saundercock, Mr. William Henry"
-True,14,39.0,,False,1,True,False,True,male,"Andersson, Mr. Anders Johan"
-False,15,14.0,,True,0,False,False,False,female,"Vestrom, Miss. Hulda Amanda Adolfina"
-True,16,55.0,,True,0,False,True,False,female,"Hewlett, Mrs. (Mary D Kingcome) "
-False,17,2.0,,False,4,True,False,True,male,"Rice, Master. Eugene"
-True,18,,,False,0,True,True,False,male,"Williams, Mr. Charles Eugene"
-True,19,31.0,,True,1,False,False,True,female,"Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)"
-True,20,,,True,0,False,True,False,female,"Masselmani, Mrs. Fatima"
-True,21,35.0,,False,0,True,False,False,male,"Fynney, Mr. Joseph J"
-True,22,34.0,D56,False,0,True,True,False,male,"Beesley, Mr. Lawrence"
-False,23,15.0,,True,0,False,True,False,female,"McGowan, Miss. Anna ""Annie"""
-True,24,28.0,A6,False,0,True,True,False,male,"Sloper, Mr. William Thompson"
-False,25,8.0,,True,3,False,False,True,female,"Palsson, Miss. Torborg Danira"
-True,26,38.0,,True,1,False,True,True,female,"Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)"
-True,27,,,False,0,True,False,False,male,"Emir, Mr. Farred Chehab"
-True,28,19.0,C23 C25 C27,False,3,True,False,True,male,"Fortune, Mr. Charles Alexander"
-False,29,,,True,0,False,True,False,female,"O'Dwyer, Miss. Ellen ""Nellie"""
-True,30,,,False,0,True,False,False,male,"Todoroff, Mr. Lalio"
-False,31,40.0,,False,0,True,False,False,male,"Uruchurtu, Don. Manuel E"
-True,32,,B78,True,1,False,True,True,female,"Spencer, Mrs. William Augustus (Marie Eugenie)"
-False,33,,,True,0,False,True,False,female,"Glynn, Miss. Mary Agatha"
-True,34,66.0,,False,0,True,False,False,male,"Wheadon, Mr. Edward H"
-True,35,28.0,,False,1,True,False,True,male,"Meyer, Mr. Edgar Joseph"
-True,36,42.0,,False,1,True,False,True,male,"Holverson, Mr. Alexander Oskar"
-True,37,,,False,0,True,True,False,male,"Mamee, Mr. Hanna"
-True,38,21.0,,False,0,True,False,False,male,"Cann, Mr. Ernest Charles"
-False,39,18.0,,True,2,False,False,True,female,"Vander Planke, Miss. Augusta Maria"
-False,40,14.0,,True,1,False,True,True,female,"Nicola-Yarred, Miss. Jamila"
-True,41,40.0,,True,1,False,False,True,female,"Ahlin, Mrs. Johan (Johanna Persdotter Larsson)"
-True,42,27.0,,True,1,False,False,True,female,"Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott)"
-True,43,,,False,0,True,False,False,male,"Kraeff, Mr. Theodor"
-False,44,3.0,,True,1,False,True,True,female,"Laroche, Miss. Simonne Marie Anne Andree"
-False,45,19.0,,True,0,False,True,False,female,"Devaney, Miss. Margaret Delia"
-True,46,,,False,0,True,False,False,male,"Rogers, Mr. William John"
-True,47,,,False,1,True,False,True,male,"Lennon, Mr. Denis"
-False,48,,,True,0,False,True,False,female,"O'Driscoll, Miss. Bridget"
-True,49,,,False,2,True,False,True,male,"Samaan, Mr. Youssef"
-True,50,18.0,,True,1,False,False,True,female,"Arnold-Franchi, Mrs. Josef (Josefine Franchi)"
-False,51,7.0,,False,4,True,False,True,male,"Panula, Master. Juha Niilo"
-True,52,21.0,,False,0,True,False,False,male,"Nosworthy, Mr. Richard Cater"
-True,53,49.0,D33,True,1,False,True,True,female,"Harper, Mrs. Henry Sleeper (Myna Haxtun)"
-True,54,29.0,,True,1,False,True,True,female,"Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson)"
-True,55,65.0,B30,False,0,True,False,False,male,"Ostby, Mr. Engelhart Cornelius"
-True,56,,C52,False,0,True,True,False,male,"Woolner, Mr. Hugh"
-False,57,21.0,,True,0,False,True,False,female,"Rugg, Miss. Emily"
-True,58,28.5,,False,0,True,False,False,male,"Novel, Mr. Mansouer"
-False,59,5.0,,True,1,False,True,True,female,"West, Miss. Constance Mirium"
-False,60,11.0,,False,5,True,False,True,male,"Goodwin, Master. William Frederick"
+age,sex,name,is_mr,passenger_id,is_female,cabin,sibsp,has_siblings,survived,is_male
+22.0,male,"Braund, Mr. Owen Harris",True,1,False,,1,True,False,True
+38.0,female,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",True,2,True,C85,1,True,True,False
+26.0,female,"Heikkinen, Miss. Laina",False,3,True,,0,False,True,False
+35.0,female,"Futrelle, Mrs. Jacques Heath (Lily May Peel)",True,4,True,C123,1,True,True,False
+35.0,male,"Allen, Mr. William Henry",True,5,False,,0,False,False,True
+,male,"Moran, Mr. James",True,6,False,,0,False,False,True
+54.0,other,"McCarthy, Mr. Timothy J",True,7,False,E46,0,False,False,False
+2.0,male,"Palsson, Master. Gosta Leonard",False,8,False,,3,True,False,True
+27.0,female,"Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)",True,9,True,,0,False,True,False
+14.0,female,"Nasser, Mrs. Nicholas (Adele Achem)",True,10,True,,1,True,True,False
+4.0,female,"Sandstrom, Miss. Marguerite Rut",False,11,True,G6,1,True,True,False
+58.0,female,"Bonnell, Miss. Elizabeth",False,12,True,C103,0,False,True,False
+20.0,male,"Saundercock, Mr. William Henry",True,13,False,,0,False,False,True
+39.0,male,"Andersson, Mr. Anders Johan",True,14,False,,1,True,False,True
+14.0,female,"Vestrom, Miss. Hulda Amanda Adolfina",False,15,True,,0,False,False,False
+55.0,female,"Hewlett, Mrs. (Mary D Kingcome) ",True,16,True,,0,False,True,False
+2.0,male,"Rice, Master. Eugene",False,17,False,,4,True,False,True
+,male,"Williams, Mr. Charles Eugene",True,18,False,,0,False,True,True
+31.0,female,"Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)",True,19,True,,1,True,False,False
+,female,"Masselmani, Mrs. Fatima",True,20,True,,0,False,True,False
+35.0,male,"Fynney, Mr. Joseph J",True,21,False,,0,False,False,True
+34.0,male,"Beesley, Mr. Lawrence",True,22,False,D56,0,False,True,True
+15.0,female,"McGowan, Miss. Anna ""Annie""",False,23,True,,0,False,True,False
+28.0,male,"Sloper, Mr. William Thompson",True,24,False,A6,0,False,True,True
+8.0,female,"Palsson, Miss. Torborg Danira",False,25,True,,3,True,False,False
+38.0,female,"Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)",True,26,True,,1,True,True,False
+,male,"Emir, Mr. Farred Chehab",True,27,False,,0,False,False,True
+19.0,male,"Fortune, Mr. Charles Alexander",True,28,False,C23 C25 C27,3,True,False,True
+,female,"O'Dwyer, Miss. Ellen ""Nellie""",False,29,True,,0,False,True,False
+,male,"Todoroff, Mr. Lalio",True,30,False,,0,False,False,True
+40.0,male,"Uruchurtu, Don. Manuel E",False,31,False,,0,False,False,True
+,female,"Spencer, Mrs. William Augustus (Marie Eugenie)",True,32,True,B78,1,True,True,False
+,female,"Glynn, Miss. Mary Agatha",False,33,True,,0,False,True,False
+66.0,male,"Wheadon, Mr. Edward H",True,34,False,,0,False,False,True
+28.0,male,"Meyer, Mr. Edgar Joseph",True,35,False,,1,True,False,True
+42.0,male,"Holverson, Mr. Alexander Oskar",True,36,False,,1,True,False,True
+,male,"Mamee, Mr. Hanna",True,37,False,,0,False,True,True
+21.0,male,"Cann, Mr. Ernest Charles",True,38,False,,0,False,False,True
+18.0,female,"Vander Planke, Miss. Augusta Maria",False,39,True,,2,True,False,False
+14.0,female,"Nicola-Yarred, Miss. Jamila",False,40,True,,1,True,True,False
+40.0,female,"Ahlin, Mrs. Johan (Johanna Persdotter Larsson)",True,41,True,,1,True,False,False
+27.0,female,"Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott)",True,42,True,,1,True,False,False
+,male,"Kraeff, Mr. Theodor",True,43,False,,0,False,False,True
+3.0,female,"Laroche, Miss. Simonne Marie Anne Andree",False,44,True,,1,True,True,False
+19.0,female,"Devaney, Miss. Margaret Delia",False,45,True,,0,False,True,False
+,male,"Rogers, Mr. William John",True,46,False,,0,False,False,True
+,male,"Lennon, Mr. Denis",True,47,False,,1,True,False,True
+,female,"O'Driscoll, Miss. Bridget",False,48,True,,0,False,True,False
+,male,"Samaan, Mr. Youssef",True,49,False,,2,True,False,True
+18.0,female,"Arnold-Franchi, Mrs. Josef (Josefine Franchi)",True,50,True,,1,True,False,False
+7.0,male,"Panula, Master. Juha Niilo",False,51,False,,4,True,False,True
+21.0,male,"Nosworthy, Mr. Richard Cater",True,52,False,,0,False,False,True
+49.0,female,"Harper, Mrs. Henry Sleeper (Myna Haxtun)",True,53,True,D33,1,True,True,False
+29.0,female,"Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson)",True,54,True,,1,True,True,False
+65.0,male,"Ostby, Mr. Engelhart Cornelius",True,55,False,B30,0,False,False,True
+,male,"Woolner, Mr. Hugh",True,56,False,C52,0,False,True,True
+21.0,female,"Rugg, Miss. Emily",False,57,True,,0,False,True,False
+28.5,male,"Novel, Mr. Mansouer",True,58,False,,0,False,False,True
+5.0,female,"West, Miss. Constance Mirium",False,59,True,,1,True,True,False
+11.0,male,"Goodwin, Master. William Frederick",False,60,False,,5,True,False,True
diff --git a/test_data/titanic-validate.csv b/test_data/titanic-validate.csv
index eea2faf..ebcb646 100644
--- a/test_data/titanic-validate.csv
+++ b/test_data/titanic-validate.csv
@@ -1,21 +1,21 @@
-is_mr,passenger_id,age,cabin,is_female,sibsp,is_male,survived,has_siblings,sex,name
-True,81,22.0,,False,0,True,False,False,male,"Waelens, Mr. Achille"
-True,82,29.0,,False,0,True,True,False,male,"Sheerlinck, Mr. Jan Baptist"
-False,83,,,True,0,False,True,False,female,"McDermott, Miss. Brigdet Delia"
-True,84,28.0,,False,0,True,False,False,male,"Carrau, Mr. Francisco M"
-False,85,17.0,,True,0,False,True,False,female,"Ilett, Miss. Bertha"
-True,86,33.0,,True,3,False,True,True,female,"Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson)"
-True,87,16.0,,False,1,True,False,True,male,"Ford, Mr. William Neal"
-True,88,,,False,0,True,False,False,male,"Slocovski, Mr. Selman Francis"
-False,89,23.0,C23 C25 C27,True,3,False,True,True,female,"Fortune, Miss. Mabel Helen"
-True,90,24.0,,False,0,True,False,False,male,"Celotti, Mr. Francesco"
-True,91,29.0,,False,0,True,False,False,male,"Christmann, Mr. Emil"
-True,92,20.0,,False,0,True,False,False,male,"Andreasson, Mr. Paul Edvin"
-True,93,46.0,E31,False,1,True,False,True,male,"Chaffee, Mr. Herbert Fuller"
-True,94,26.0,,False,1,True,False,True,male,"Dean, Mr. Bertram Frank"
-True,95,59.0,,False,0,True,False,False,male,"Coxon, Mr. Daniel"
-True,96,,,False,0,True,False,False,male,"Shorney, Mr. Charles Joseph"
-True,97,71.0,A5,False,0,True,False,False,male,"Goldschmidt, Mr. George B"
-True,98,23.0,D10 D12,False,0,True,True,False,male,"Greenfield, Mr. William Bertram"
-True,99,34.0,,True,0,False,True,False,female,"Doling, Mrs. John T (Ada Julia Bone)"
-True,100,34.0,,False,1,True,False,True,male,"Kantor, Mr. Sinai"
+age,sex,name,is_mr,passenger_id,is_female,cabin,sibsp,has_siblings,survived,is_male
+22.0,male,"Waelens, Mr. Achille",True,81,False,,0,False,False,True
+29.0,male,"Sheerlinck, Mr. Jan Baptist",True,82,False,,0,False,True,True
+,female,"McDermott, Miss. Brigdet Delia",False,83,True,,0,False,True,False
+28.0,male,"Carrau, Mr. Francisco M",True,84,False,,0,False,False,True
+17.0,female,"Ilett, Miss. Bertha",False,85,True,,0,False,True,False
+33.0,female,"Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson)",True,86,True,,3,True,True,False
+16.0,male,"Ford, Mr. William Neal",True,87,False,,1,True,False,True
+,male,"Slocovski, Mr. Selman Francis",True,88,False,,0,False,False,True
+23.0,female,"Fortune, Miss. Mabel Helen",False,89,True,C23 C25 C27,3,True,True,False
+24.0,male,"Celotti, Mr. Francesco",True,90,False,,0,False,False,True
+29.0,male,"Christmann, Mr. Emil",True,91,False,,0,False,False,True
+20.0,male,"Andreasson, Mr. Paul Edvin",True,92,False,,0,False,False,True
+46.0,male,"Chaffee, Mr. Herbert Fuller",True,93,False,E31,1,True,False,True
+26.0,male,"Dean, Mr. Bertram Frank",True,94,False,,1,True,False,True
+59.0,male,"Coxon, Mr. Daniel",True,95,False,,0,False,False,True
+,male,"Shorney, Mr. Charles Joseph",True,96,False,,0,False,False,True
+71.0,male,"Goldschmidt, Mr. George B",True,97,False,A5,0,False,False,True
+23.0,male,"Greenfield, Mr. William Bertram",True,98,False,D10 D12,0,False,True,True
+34.0,female,"Doling, Mrs. John T (Ada Julia Bone)",True,99,True,,0,False,True,False
+34.0,male,"Kantor, Mr. Sinai",True,100,False,,1,True,False,True