Interface DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfoOrBuilder (1.47.0)

Version 1.47.0

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public static interface DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfoOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

getAverage()

public abstract double getAverage()

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

double average = 1;

Returns
Type	Description
double	The average.

getMax()

public abstract long getMax()

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

int64 max = 5;

Returns
Type	Description
long	The max.

getMin()

public abstract long getMin()

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

int64 min = 4;

Returns
Type	Description
long	The min.

getQuartiles(int index)

public abstract long getQuartiles(int index)

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 approximate quartile values for the scanned data, occurring in order Q1, median, Q3.

repeated int64 quartiles = 6;

Parameter
Name	Description
index	int The index of the element to return.

Returns
Type	Description
long	The quartiles at the given index.

getQuartilesCount()

public abstract int getQuartilesCount()

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 approximate quartile values for the scanned data, occurring in order Q1, median, Q3.

repeated int64 quartiles = 6;

Returns
Type	Description
int	The count of quartiles.

getQuartilesList()

public abstract List<Long> getQuartilesList()

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 approximate quartile values for the scanned data, occurring in order Q1, median, Q3.

repeated int64 quartiles = 6;

Returns
Type	Description
List<Long>	A list containing the quartiles.

getStandardDeviation()

public abstract double getStandardDeviation()

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

double standard_deviation = 3;

Returns
Type	Description
double	The standardDeviation.