Group By Month Example

SELECT MONTH(date_column) AS month, COUNT(*) AS count
FROM date_month_year_table
GROUP BY MONTH(date_column);

Output:

Group by month

Explanation: This MySQL query utilizes the `MONTH()` function to extract the month component from the “date_column” in the “date_month_year_table” and counts the occurrences for each unique month. The result is presented with two columns: “month,” representing the numeric month value, and “count,” indicating the frequency of records for each specific month.

This query showcases the application of the `GROUP BY` clause in MySQL for aggregating and analyzing data based on the month component of date values within the specified table.

How to Group by Month and Year in MySQL?

GROUP BY clause is an essential feature for data analysis. It enables users to aggregate information based on specific criteria. To group records based on day, month, and year, we can use DAY(), MONTH(), and YEAR() functions respectively.

In this article, we will look at how to use MySQL’s GROUP BY clause to organize data based on the DAY, MONTH, and YEAR components of date data. We will start by creating a database and a table and populate it with the sample data. Then, we will use the three methods of GROUP BY: GROUP BY DAY(), GROUP BY MONTH (), and GROUP BY YEAR ().

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Demo MySQL Database

In this tutorial, we will learn how to group data based on day, month, and year. Let’s create a sample table, on which we will use the MySQL queries to group by day, month, and Year....

Group by Day Example

SELECT DAY(date_column) AS day, COUNT(*) AS countFROM date_month_year_tableGROUP BY DAY(date_column);...

Group By Month Example

SELECT MONTH(date_column) AS month, COUNT(*) AS countFROM date_month_year_tableGROUP BY MONTH(date_column);...

Group By Year Example

SELECT YEAR(date_column) AS year, COUNT(*) AS countFROM date_month_year_tableGROUP BY YEAR(date_column);...

Conclusion

Using DATE(), MONTH() and YEAR() functions with GROUP BY clause allows to group data based on date, month and year respectively. This is very useful for tasks like trend analysis and reporting, enhancing precision and efficiency in aggregating information....

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