pulumi-gcp-kotlin/com.pulumi.gcp.dataplex.kotlin.outputs/DatascanDataProfileResultProfileFieldProfileIntegerProfile

DatascanDataProfileResultProfileFieldProfileIntegerProfile

data class DatascanDataProfileResultProfileFieldProfileIntegerProfile(val average: Int? = null, val max: String? = null, val min: String? = null, val quartiles: String? = null, val standardDeviation: Int? = null)

Constructors

constructor(average: Int? = null, max: String? = null, min: String? = null, quartiles: String? = null, standardDeviation: Int? = null)

Types

Companion

object Companion

Properties

average

val average: Int? = null

Average of non-null values in the scanned data. NaN, if the field has a NaN.

max

val max: String? = null

Maximum of non-null values in the scanned data. NaN, if the field has a NaN.

min

val min: String? = null

Minimum of non-null values in the scanned data. NaN, if the field has a NaN.

quartiles

val quartiles: String? = null

A quartile divides the number of data points into four parts, or quarters, of more-or-less equal size. Three main quartiles used are: The first quartile (Q1) splits off the lowest 25% of data from the highest 75%. It is also known as the lower or 25th empirical quartile, as 25% of the data is below this point. The second quartile (Q2) is the median of a data set. So, 50% of the data lies below this point. The third quartile (Q3) splits off the highest 25% of data from the lowest 75%. It is known as the upper or 75th empirical quartile, as 75% of the data lies below this point. Here, the quartiles is provided as an ordered list of quartile values for the scanned data, occurring in order Q1, median, Q3.

standardDeviation

val standardDeviation: Int? = null

Standard deviation of non-null values in the scanned data. NaN, if the field has a NaN.