7/22/2023 0 Comments Mysql count number with percentageLike we do in MS Excel we can display sum of all columns and the sum of all total subject marks by using UNION. LEAST(social,science,math) as min FROM student_sum idĭisplaying sum of all columns at last row We can list starting from highest mark to lowest mark by using Order By Query.įrom student_sum GROUP BY id ORDER BY Total DESC Displaying highest & lowest mark in all subjects of each student SELECT id,name,GREATEST(social,science,math) as max, Listing all columns along with aggregate functions like sum(), max() using over() with partition → Displaying from Highest to lowest SELECT id,name,class, social, math, science, Note that id is unique value column in our table. Now we will try to display all marks and sum of them for each student by using group by. Query to display percentage value using 2 decimal places.įORMAT((( social + science + math)/(95*3) * 100),2) AS percentageįROM `student_sum` Sum of the row data of each record The above percentage data is having four decimal places, we can format these numbers by using ROUND Sql command. ![]() (( social + science + math)/(95*3) * 100) AS percentage SELECT id, name, class,( social + science + math) as Total, SELECT name, (( social + science + math)/(95*3) * 100) AS percentageįROM `student_sum` Displaying Total Mark with Percentageīoth total mark and percentage we can display like this So to get the percentage mark of each student we have to multiply 95 with 3 ( for three subjects ) and then divide that from the total and multiply with 100 here is the query. Let us assume the full mark in each subject is 95. We can add various other sql commands like where clause etc. SELECT sum(social + math + science ) as total So the sum is to be collected in all three columns. Now we will try to get sum of marks of all students in all subjects. Monitoring PostgreSQL with Navicat Monitor 3.Related Tutorial MySQL SUM MySQL Max MySQL Min MySQL AvgĪs you can see the above sum is sum of marks of each student.Trace Queries on your PostgreSQL Instances with Navicat Monitor 3.Viewing PostgreSQL Instance Details in Navicat Monitor 3.A Quick Guide to Naming Conventions in SQL - Part 2.A Quick Guide to Naming Conventions in SQL - Part 3.Selecting Distinct Values From a Relational Database.Implement Audit Trail Logging Using Triggers.Multi-Version Concurrency Control in PostgreSQL.A Guide to MySQL Foreign Key Constraints. ![]() Next week, we’ll obtain row counts from multiple tables and views. It distinguishes between a NULL representing the set of all values in a super-aggregate row (produced by a ROLLUP) from a NULL in a regular row. The “Total:” was produced using the SQL GROUPING() function, which was added in MySQL 8.0.1. ![]() You can also stack counts vertically using GROUP BY: +-+-+-+ BONUS! Grouping and Including a Grand Total This SELECT statement would yield the following: Here's one option using a separate COUNT DISTINCT for each column:ĬOUNT(DISTINCT CASE WHEN gender = 'male' THEN tel END) male_count,ĬOUNT(DISTINCT CASE WHEN gender = 'female' THEN tel END) female_count It is possible for the same 'tel' to appear multiple times, but that tel’s gender should only be counted one time. The person is identified by their telephone ('tel') number. Say that we wanted to build a query that told us how many distinct women and men there are in the table. Here’s a table that contains several users’ telephone numbers and sex (limited to two for simplicity): +-+-+ Conditional Counts using ExpressionsĪs mentioned above, COUNT() function parameters are not limited to column names function return values and expressions such as IF/CASE statements are also fair game. ![]() Invoking COUNT(*) will return the number of all rows (4) while a COUNT DISTINCT on the last_name will count each row with a duplicated last name as one, so that we get a total of 3: SELECT COUNT(*), COUNT(DISTINCT last_name) FROM clients Say that we had the following table of clients: Its syntax is: COUNT(DISTINCT expr,)Īs with the regular COUNT() function, the expr parameters above can be any given expression, including specific columns, all columns (*), function return values, or expression such as IF/CASE statements. Hence, the inclusion of the DISTINCT keyword eliminates duplicate rows from the count. The COUNT(DISTINCT) function returns the number of rows with unique non-NULL values. In today’s follow-up, we’ll use the COUNT() function in more sophisticated ways to tally unique values as well as those which satisfy a condition. In last week’s Getting Row Counts in MySQL blog we employed the native COUNT() function’s different variations to tally the number of rows within one MySQL table.
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