Question 233 of 307
Single answerYou are preparing data that your machine learning team will use to train a model using BigQueryML. They want to predict the price per square foot of real estate. The training data has a column for the price and a column for the number of square feet. Another feature column called ‘feature1’ contains null values due to missing data. You want to replace the nulls with zeros to keep more data points. Which query should you use?
✓ASELECT * EXCEPT(feature1),
IFNULL(feature1, 0) AS feature1_cleaned
FROM training_data;
IFNULL(feature1, 0) AS feature1_cleaned
FROM training_data;
BSELECT * EXCEPT(price, square_feet),
price/square_feet AS price_per_sqft
FROM training_data
WHERE feature1 IS NOT NULL;
price/square_feet AS price_per_sqft
FROM training_data
WHERE feature1 IS NOT NULL;
CSELECT * EXCEPT(price, square_feet, feature1),
price/square_feet AS price_per_sqft,
IFNULL(feature1, 0) AS feature1_cleaned
FROM training_data;
price/square_feet AS price_per_sqft,
IFNULL(feature1, 0) AS feature1_cleaned
FROM training_data;
DSELECT *
FROM training_data
WHERE feature1 IS NOT NULL;
FROM training_data
WHERE feature1 IS NOT NULL;
✓
Correct Answer: A
SELECT * EXCEPT(feature1),<br> IFNULL(feature1, 0) AS feature1_cleaned<br> FROM training_data;
▥
Explanation
The correct answer is highlighted above. Review the wording carefully, then use the next question to continue building your understanding of Google certification topics.