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# Statistical computed column functions¶

This section provides syntax and examples for the statistical computed column functions you can use with the Data Prep Compute tool. To use a statistics function, you must store the value as a numeric data type. Numeric data types can be identiﬁed by the numeric data type icon in the header row. If the value is not stored as a numeric data type, convert the value to numeric format using the VALUE function.

## AVERAGE¶

Calculates the value equal to the sum of a list of numbers divided by the number of items in the list.

Syntax

`AVERAGE(VALUE_1, [VALUE_2, ...])`

• `VALUE_1` is the ﬁrst value.
• `VALUE_2`, ... [optional] are the additional values.

Example

`AVERAGE(@Column_A@, @Column_B@, @Column_C@)` Notes on use

The `VALUE` you provide must be a numeric value, a column that contains numeric values, or a function that returns a numeric value.

## MAX¶

Returns the greatest (maximum) value from a set of values.

Syntax

`MAX(VALUE_1, [VALUE_2, ...])`

• `VALUE_1` is the ﬁrst value.
• `VALUE_2``, ...` [optional] are the additional values.

Example

`MAX(@Column_A@, @Column_B@, @Column_C@)` Notes on use

The `VALUE` you provide must be a numeric value, a column that contains numeric values, or a function that returns a numeric value.

## MEDIAN¶

Returns the number that exists in the middle of a range of numbers ordered from lowest to highest value.

Syntax

`MEDIAN(VALUE_1, [VALUE_2, ...])`

• `VALUE_1` is the ﬁrst value.
• `VALUE_2, ...` [optional] are the additional values.

Example

`MEDIAN(@colum_A@, @colum_B@, @colum_C@, @colum_C@, @colum_E@)` Notes on use

The `VALUE` you provide must be a numeric value, a column that contains numeric values, or a function that returns a numeric value.

In a range with an even set of numbers, the median is the center number, half the numbers are to the right of the value returned and half of the numbers are to the left of the value returned. Where there is no single number in the middle of the range), MEDIAN calculates the average on the two numbers on either side of the mid-point.

Note

MEDIAN is diﬀerent than AVERAGE. AVERAGE is an arithmetic mean—calculated by adding up a set of numbers and then dividing by the number of values in the set. MEDIAN takes the value at the center of the range. In those number ranges that exhibit a balance in the distribution of values within the collection, the MEDIAN and AVERAGE calculations may coincide; in skewed distributions, the values will be diﬀerent.

## MIN¶

Returns the smallest (minimum) value from a set of values.

Syntax

`MIN(VALUE_1, [VALUE_2, ...])`

• `VALUE_1` is the ﬁrst value.
• `VALUE_2, ...` [optional] are the additional values.

Example

`MIN(@Column_A@, @Column_B@, @Column_C@)` Notes on use

The `VALUE` you provide must be a numeric value, a column that contains numeric values, or a function that returns a numeric value.

## MODE¶

Returns the value that occurs most frequently in a set of numbers.

Syntax

`MODE(VALUE_1, VALUE_2, [VALUE_3, ...])`

• `VALUE_1` is the ﬁrst value.
• `VALUE_2` is the second value.
• `VALUE_3, ...` [optional] are the additional values.

Example

`MODE(@Column_A@, @Column_B@, @Column_C@)` Notes on use

The VALUE you provide must be a numeric value, a column that contains numeric values, or a function that returns a numeric value.

If multiple numbers have an equal occurrence count greater than one, the value returned is the number (of those that are equal in frequency) that appears ﬁrst in the set (reading from left to right). If no number appears more than once, the function returns an error.

The most common problem related to `MODE` is when the provided set of numbers has no duplicates. At least one number must appear two or more times for the function to successfully evaluate. If the minimum number of arguments (two) are used, then each argument must evaluate to the same number or an error will occur. As you might expect, larger sets of numbers with a more limited variation will reduce the chance of `MODE` returning an error.

## STDEV¶

Estimates the standard deviation, how much variation from the average, that exists within a sample set of data.

Syntax

`STDEV(VALUE_1, [VALUE_2, ...])`

• `VALUE_1` is the ﬁrst value.
• `VALUE_2, ...` [optional] are the additional values.

Example

`STDEV(@Column_A@, @Column_B@, @Column_C@)` Notes on use

The `VALUE` you provide must be a numeric value, a column that contains numeric values, or a function that returns a numeric value.

The standard deviation for data is the square root of its variance. If the set under analysis represents all data points (referred to as a population), use `STDEVP` instead.

## STDEVP¶

Estimates the standard deviation, how much variation from the average, that exists within the entire set (population) of data.

Syntax

`STDEVP(VALUE_1, [VALUE_2, ...])`

• `VALUE_1` is the ﬁrst value.
• `VALUE_2, ...` [optional] are the additional values.

Example

`STDEVP(@Column_A@, @Column_B@, @Column_C@)` Notes on use

The `VALUE` you provide must be a numeric value, a column that contains numeric values, or a function that returns a numeric value.

If the set under analysis represents only a sample of the data points, use `STDEV` instead.

## VAR¶

Estimates how much dispersion exists (how much the values are spread out) within a samples set of data.

Syntax

`VAR(VALUE_1, [VALUE_2, ...])`

• `VALUE_1` is the ﬁrst value.
• `VALUE_2, ...` [optional] are the additional values.

Example

`VAR(@Column_A@, @Column_B@, @Column_C@)` Notes on use

The `VALUE` you provide must be a numeric value, a column that contains numeric values, or a function that returns a numeric value.

If the set under analysis represents all data points (referred to as a population), use `VARP` instead.

## VARP¶

Estimates how much dispersion exists (how much the values are spread out) within the entire set (population) of data.

Syntax

`VARP(VALUE_1, [VALUE_2, ...])`

• `VALUE_1` is the ﬁrst value.
• `VALUE_2, ...` [optional] are the additional values.

Example

`VARP(@Column_A@, @Column_B@, @Column_C@)` Notes on use

The `VALUE` you provide must be a numeric value, a column that contains numeric values, or a function that returns a numeric value.

If the set under analysis represents only a sample of data points, use `VAR` instead.

Updated April 12, 2022