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Filtering group size | Grouping
SQL Basics
course content

Contenido del Curso

SQL Basics

SQL Basics

1. Selecting
2. Filtering
3. Aggregating
4. Sorting
5. Grouping
6. Practicing

Filtering 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.

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.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Sección 5. Capítulo 7
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Filtering 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.

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.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

Sección 5. Capítulo 7
toggle bottom row

Filtering 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.

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.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

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.

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