Running an ETL Pipeline
Ready to run your first ETL pipeline? Let's get to it!
Here, the functions extract(), transform(), and load() have been defined for you. To run this data ETL pipeline, you're going to execute each of these functions. If you're curious, take a peek at what the extract() function looks like.
def extract(file_name):
print(f"Extracting data from {file_name}")
return pd.read_csv(file_name)
Questo esercizio fa parte del corso
ETL and ELT in Python
Istruzioni dell'esercizio
- Use the
extract()function to extract data from theraw_data.csvfile. - Transform the
extracted_dataDataFrame using thetransform()function. - Finally, load the
transformed_dataDataFrame to thecleaned_dataSQL table.
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# Extract data from the raw_data.csv file
extracted_data = ____(file_name="raw_data.csv")
# Transform the extracted_data
transformed_data = transform(data_frame=____)
# Load the transformed_data to cleaned_data.csv
____(data_frame=transformed_data, target_table="cleaned_data")