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docs: Fix the documentation to run the tutorial Validating historical features with Great Expectations #3540

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Apr 3, 2023
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docs: Fix the documentation to run the tutorial Validating historical features with Great Expectations #3540

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20 changes: 10 additions & 10 deletions docs/tutorials/validating-historical-features.md
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Original file line number Diff line number Diff line change
Expand Up @@ -136,8 +136,8 @@ taxi_entity = Entity(name='taxi', join_keys=['taxi_id'])
```python
trips_stats_fv = BatchFeatureView(
name='trip_stats',
entities=['taxi'],
features=[
entities=[taxi_entity],
schema=[
Field(name="total_miles_travelled", dtype=Float64),
Field(name="total_trip_seconds", dtype=Float64),
Field(name="total_earned", dtype=Float64),
Expand All @@ -154,17 +154,17 @@ trips_stats_fv = BatchFeatureView(

```python
@on_demand_feature_view(
schema=[
Field("avg_fare", Float64),
Field("avg_speed", Float64),
Field("avg_trip_seconds", Float64),
Field("earned_per_hour", Float64),
],
sources=[
trips_stats_fv,
],
schema=[
Field(name="avg_fare", dtype=Float64),
Field(name="avg_speed", dtype=Float64),
Field(name="avg_trip_seconds", dtype=Float64),
Field(name="earned_per_hour", dtype=Float64),
]
)
def on_demand_stats(inp):
def on_demand_stats(inp: pd.DataFrame) -> pd.DataFrame:
out = pd.DataFrame()
out["avg_fare"] = inp["total_earned"] / inp["trip_count"]
out["avg_speed"] = 3600 * inp["total_miles_travelled"] / inp["total_trip_seconds"]
Expand Down Expand Up @@ -647,7 +647,7 @@ Now we can create validation reference from dataset and profiler function:


```python
validation_reference = ds.as_reference(profiler=stats_profiler)
validation_reference = ds.as_reference(name="validation_reference_dataset", profiler=stats_profiler)
```

and test it against our existing retrieval job
Expand Down