Interface DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfoOrBuilder (1.7.0)

Version 1.7.0

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

Implements

MessageOrBuilder

Methods

getAverage()

public abstract double getAverage()

The average of non-null values of integer field in the sampled data. Return NaN, if the field has a NaN. Optional if zero non-null rows.

double average = 1;

Returns

Type	Description
double	The average.

getMax()

public abstract long getMax()

The maximum value of an integer field in the sampled data. Return NaN, if the field has a NaN. Optional if zero non-null rows.

int64 max = 5;

Returns

Type	Description
long	The max.

getMin()

public abstract long getMin()

The minimum value of an integer field in the sampled data. Return NaN, if the field has a NaN. Optional if zero non-null rows.

int64 min = 4;

Returns

Type	Description
long	The min.

getQuartiles(int index)

public abstract long getQuartiles(int index)

A quartile divide 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. So, here the quartiles is provided as an ordered list of quartile values, 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 divide 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. So, here the quartiles is provided as an ordered list of quartile values, 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 divide 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. So, here the quartiles is provided as an ordered list of quartile values, 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()

The standard deviation of non-null of integer field in the sampled data. Return NaN, if the field has a NaN. Optional if zero non-null rows.

double standard_deviation = 3;

Returns

Type	Description
double	The standardDeviation.