public static interface DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfoOrBuilder extends MessageOrBuilder
Implements
MessageOrBuilderMethods
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;
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;
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;
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;
Name | Description |
index | int The index of the element to return. |
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;
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;
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;
Type | Description |
double | The standardDeviation. |