ELT in Action
Feeling pretty good about running ETL processes? Well, it's time to give ELT pipelines a try. Like before, the extract(), load(), and transform() functions have been defined for you; all you'll have to worry about is running these functions. Good luck!
Diese Übung ist Teil des Kurses
ETL und ELT in Python
Anleitung zur Übung
- Use the appropriate ETL function to extract data from the
raw_data.csvfile. - Load the
raw_dataDataFrame into theraw_datatable in a data warehouse. - Call the
transform()function to transform the data in theraw_datasource table.
Interaktive Übung zum Anfassen
Probieren Sie diese Übung aus, indem Sie diesen Beispielcode ausführen.
# Extract data from the raw_data.csv file
raw_data = ____(file_name="____.csv")
# Load the extracted_data to the raw_data table
load(data_frame=____, table_name="____")
# Transform data in the raw_data table
____(
source_table="____",
target_table="cleaned_data"
)