In SQL Server, the APPROX_PERCENTILE_DISC() function calculates and returns an approximate percentile based on a discrete distribution of the column values.
We pass the desired percentile to the function when we call it.
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An Overview of the APPROX_PERCENTILE_CONT() Function in SQL Server
In SQL Server, the APPROX_PERCENTILE_CONT() function calculates and returns an approximate percentile based on a continuous distribution of the column value. This is an interpolated value from the set of values in a group based on percentile value and sort specification.
Understanding the AVG() Function in SQL Server
Like most other RDBMSs, SQL Server has an AVG() function that returns the average of the values in a group.
Below are examples that demonstrate how the AVG() function works in SQL Server.
An Introduction to the MEDIAN() Function in SQL
Some relational database management systems (RDBMSs) have a MEDIAN() function that calculates the median value within a range of values.
It returns the middle value or an interpolated value that would be the middle value once the values are sorted.
The SQL MEDIAN() function typically operates on numeric expressions, but depending on the RDBMS, may also operate on other data types, such as datetime expressions.
Depending on the RDBMS, the MEDIAN() function can be used as a window function, as an aggregate function, or as both.
Understanding the MODE() Function in SQL
Some SQL relational database management systems (RDBMSs) have a MODE() function that returns the most frequently occurring value from all row values in a column.
The mode is the value that appears most frequently in a data set.
Continue readingIntroduction to the PERCENTILE_DISC() Function in SQL
Some SQL databases have a PERCENTILE_DISC() function that calculates a percentile based on a discrete distribution of a range of column values.
We specify the percentile to use when we call the function.
Depending on the DBMS, PERCENTILE_DISC() can be used as a window function, as an aggregate function, or as both.
The PERCENTILE_DISC() function always returns a value from the underlying data. This is in contrast to the PERCENTILE_CONT() function, which can interpolate between adjacent values to return a value that’s not in the underlying data.
Overview of the PERCENTILE_CONT() Function in SQL
Some relational database management systems (RDBMSs) have a PERCENTILE_CONT() function that calculates a percentile based on a continuous distribution across a range of column values.
We specify the percentile to use when we call the function.
Depending on the RDBMS, PERCENTILE_CONT() can be used as a window function or an aggregate function, or as both.
How to Fix Error “function mode() does not exist” in PostgreSQL
If you’re getting an error that reads “function mode() does not exist” in PostgreSQL, it could be that you’re using the wrong syntax with this function.
The mode() function requires a WITHIN GROUP clause, and we can get the above error if we remove that clause.
In this case, we can fix the error by adding a valid WITHIN GROUP clause.
Overview of the MODE() Function in PostgreSQL
PostgreSQL has an ordered-set aggregate function called mode() that allows us to get the mode from a given column.
The mode is the most frequently occurring value.
Null values are ignored, so if null occurs the most, the mode() function will return the second most common value.
Create a Running Total in SQL
We can use SQL to create a running total of a given column. By this I mean, we can create a column that calculates the cumulative sum of a given column.
The running total/cumulative sum is the sum of all rows up until the current row. The result is that the sum increases (or decreases in the case of negative values) with each row returned in the result set. Each row’s value is added to the cumulative amount from all prior rows, so for any given row, we get the total sum for all rows up to that point – the “running total”.
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