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SQL Basics
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Contenido del Curso

SQL Basics

SQL Basics

1. Selecting
The very first meet with the databaseSELECTing certain columnsLIMITing resultsUnique values from columnUnique values from multiple columnsHow many?How many unique?AliasesTables aliases
2. Filtering
Word filteringNumber filteringCombining conditionsFiltering by numeric intervalMultiple filtering on one columnLIKE filteringNOT like this!
3. Aggregating
MINimal and MAXimal valuesSUMming valuesMean valuesROUNDing
4. Sorting
Sorting by one columnSorting in DESCending orderThe cheapest carSorting by multiple columns
5. Grouping
What is grouping?More aggregate statistics!Grouping by multiple columnsThe cheapest combinationHAVING some conditionsLeast consuming carsFiltering group size
6. Practicing
Challenge: Unique combinationsChallenge: Average Q-series cars priceChallenge: The cheapest new A-series carsChallenge: Relation between engine size and fuel consumptionChallenge: Mileage and manufacture year - is there relation?Challenge: Average price for each model and yearChallenge: The most expensive transmission + engine size combinations

bookFiltering group size

Sometimes in real life, you can meet the situation where you have significant differences between two characteristics. For example, the average rate for one item is 5, and for another is 4.6. Without any further analysis looks like that the first item is better, but what if the first item received 2 rates and the second more than a thousand? We need to be ready to this effect.

For example, let's calculate the average price for each model having at least 10 cars in each group.


              
1234

            
SELECT model, AVG(price)
FROM audi_cars
GROUP BY model
HAVING COUNT(*) > 10
copy

To calculate the number of observations in each group you can use the known COUNT(*) statement.

Tarea

From audi_cars calculate the average price for each engine size (enginesize column). Take into account only groups containing at least 7 observations and sort the resulting table by average price in ascending order.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 5. Capítulo 7
toggle bottom row

bookFiltering group size

Sometimes in real life, you can meet the situation where you have significant differences between two characteristics. For example, the average rate for one item is 5, and for another is 4.6. Without any further analysis looks like that the first item is better, but what if the first item received 2 rates and the second more than a thousand? We need to be ready to this effect.

For example, let's calculate the average price for each model having at least 10 cars in each group.


              
1234

            
SELECT model, AVG(price)
FROM audi_cars
GROUP BY model
HAVING COUNT(*) > 10
copy

To calculate the number of observations in each group you can use the known COUNT(*) statement.

Tarea

From audi_cars calculate the average price for each engine size (enginesize column). Take into account only groups containing at least 7 observations and sort the resulting table by average price in ascending order.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sección 5. Capítulo 7
toggle bottom row

bookFiltering group size

Sometimes in real life, you can meet the situation where you have significant differences between two characteristics. For example, the average rate for one item is 5, and for another is 4.6. Without any further analysis looks like that the first item is better, but what if the first item received 2 rates and the second more than a thousand? We need to be ready to this effect.

For example, let's calculate the average price for each model having at least 10 cars in each group.


              
1234

            
SELECT model, AVG(price)
FROM audi_cars
GROUP BY model
HAVING COUNT(*) > 10
copy

To calculate the number of observations in each group you can use the known COUNT(*) statement.

Tarea

From audi_cars calculate the average price for each engine size (enginesize column). Take into account only groups containing at least 7 observations and sort the resulting table by average price in ascending order.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
¿Todo estuvo claro?

¿Cómo podemos mejorarlo?

¡Gracias por tus comentarios!

Sometimes in real life, you can meet the situation where you have significant differences between two characteristics. For example, the average rate for one item is 5, and for another is 4.6. Without any further analysis looks like that the first item is better, but what if the first item received 2 rates and the second more than a thousand? We need to be ready to this effect.

For example, let's calculate the average price for each model having at least 10 cars in each group.


              
1234

            
SELECT model, AVG(price)
FROM audi_cars
GROUP BY model
HAVING COUNT(*) > 10
copy

To calculate the number of observations in each group you can use the known COUNT(*) statement.

Tarea

From audi_cars calculate the average price for each engine size (enginesize column). Take into account only groups containing at least 7 observations and sort the resulting table by average price in ascending order.

Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
Sección 5. Capítulo 7
Switch to desktopCambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones
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