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

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;

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;

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;

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;

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;

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;

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;