Number filtering
But what if we want to choose a car with small mileage, let it be less than 5000 miles. We need to set the condition to a numeric column.
This also can be done with WHERE
statement. For example,
123SELECT * FROM audi_cars WHERE mileage < 5000
Comparison operators you also can use for numeric columns:
<
- less than<=
- less-equal>=
- greater-equal ->
- greater=
- equal<>
- not equal.
Now let's try to find the cheapest car in this dataset.
Swipe to start coding
From the audi_cars
dataset extract cars with price
less than 10 000.
Lösung
Danke für Ihr Feedback!
single
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Awesome!
Completion rate improved to 2.63Awesome!
Completion rate improved to 2.63
Number filtering
But what if we want to choose a car with small mileage, let it be less than 5000 miles. We need to set the condition to a numeric column.
This also can be done with WHERE
statement. For example,
123SELECT * FROM audi_cars WHERE mileage < 5000
Comparison operators you also can use for numeric columns:
<
- less than<=
- less-equal>=
- greater-equal ->
- greater=
- equal<>
- not equal.
Now let's try to find the cheapest car in this dataset.
Swipe to start coding
From the audi_cars
dataset extract cars with price
less than 10 000.
Lösung
Danke für Ihr Feedback!
single
Awesome!
Completion rate improved to 2.63
Number filtering
Swipe um das Menü anzuzeigen
But what if we want to choose a car with small mileage, let it be less than 5000 miles. We need to set the condition to a numeric column.
This also can be done with WHERE
statement. For example,
123SELECT * FROM audi_cars WHERE mileage < 5000
Comparison operators you also can use for numeric columns:
<
- less than<=
- less-equal>=
- greater-equal ->
- greater=
- equal<>
- not equal.
Now let's try to find the cheapest car in this dataset.
Swipe to start coding
From the audi_cars
dataset extract cars with price
less than 10 000.
Lösung
Danke für Ihr Feedback!