Transform Decorator


transform decorators are applied to the main functions that perform tabular data transformations in Morph's Python cells. This decorator is used to ensure that the function returns a pandas.DataFrame object.


  • None.

Return value:

  • The decorator wraps the input function and ensures that the result of its execution is a pandas.DataFrame instance before returning it.

Usage example:

from morphdb_utils.annotations import transform
def main(data: Dict[str, pd.DataFrame]):
    df = data["sheet_cell"]
    # Extract only data that contains 'Annual Average'
    df = df[df['Name'] == "Nitrogen dioxide (NO2)"]
    df = df[df['Time Period'].str.contains("Annual Average")]
    # Select necessary columns and rename them
    df = df[['Time Period', 'Data Value', 'Geo Place Name']]
    df.columns = ['Year', 'NO2_Concentration', 'Location']
    # Extract year from 'Year' column which contains 'Annual Average YYYY'
    df['Year'] = df['Year'].str.extract(r'(\d{4})').astype(int)
    # Filter data to include only 'Manhattan'
    df = df[df['Location'] == "Manhattan"]
    # Sort the data by year in ascending order
    df = df.sort_values(by='Year', ascending=True)
    return df