Course Content

SQL Basics

1. Selecting

The very first meet with the database SELECTing certain columns LIMITing results Unique values from column Unique values from multiple columns How many?How many unique?Aliases Tables aliases

2. Filtering

Word filtering Number filtering Combining conditions Filtering by numeric interval Multiple filtering on one column LIKE filtering NOT like this!

3. Aggregating

MINimal and MAXimal values SUMming values Mean values ROUNDing

4. Sorting

Sorting by one column Sorting in DESCending order The cheapest car Sorting by multiple columns

5. Grouping

What is grouping?More aggregate statistics!Grouping by multiple columns The cheapest combination HAVING some conditions Least consuming cars Filtering group size

6. Practicing

Challenge: Unique combinations Challenge: Average Q-series cars price Challenge: The cheapest new A-series cars Challenge: Relation between engine size and fuel consumption Challenge: Mileage and manufacture year - is there relation?Challenge: Average price for each model and year Challenge: The most expensive transmission + engine size combinations

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,


              123
            
SELECT *
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.

Task

From the audi_cars dataset extract cars with price less than 10 000.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 2. Chapter 2

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,


              123
            
SELECT *
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.

Task

From the audi_cars dataset extract cars with price less than 10 000.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 2. Chapter 2

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,


              123
            
SELECT *
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.

Task

From the audi_cars dataset extract cars with price less than 10 000.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

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,


              123
            
SELECT *
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.

Task

From the audi_cars dataset extract cars with price less than 10 000.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 2. Chapter 2

Switch to desktop for real-world practiceContinue from where you are using one of the options below