semantic-link-functions-meteostat

FabricDataFrames dynamically expose semantic functions based on logic defined by each function. For example, the is_holiday function shows up in the autocomplete suggestions when you're working on a FabricDataFrame containing both a datetime column and a country column.

Each semantic function uses information about the data types, metadata (such as Power BI data categories), and the data in a FabricDataFrame or FabricSeries to determine its relevance to the particular data on which you're working.

Semantic functions are automatically discovered when annotated with the @semantic_function decorator. You can think of semantic functions as being similar to C# extension methods applied to the popular DataFrame concept.

from sempy.fabric import FabricDataFrame

df = FabricDataFrame({
        "lat": [40.7128, 47.8095, 47.8095, 47.8095],
        "long": [-74.0060, 13.0550, 13.0550, 13.0550],
        "date": ["2023-01-06", "2023-01-06", "2023-01-07", "2023-01-10"]
    },
    column_metadata={"lat": {"data_category": "Latitude"}, "long": {"data_category": "Longitude"}},
)

df["date"] = pd.to_datetime(df["date"])

df_weather = df.add_weather_meteostat("lat", "long", "date")