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.
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.
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.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-07 UTC."],[],[],null,["# Interface DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfoOrBuilder (0.16.0)\n\nVersion latestkeyboard_arrow_down\n\n- [0.16.0 (latest)](/java/docs/reference/google-cloudevent-types/latest/com.google.events.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfoOrBuilder)\n- [0.15.0](/java/docs/reference/google-cloudevent-types/0.15.0/com.google.events.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfoOrBuilder)\n- [0.14.1](/java/docs/reference/google-cloudevent-types/0.14.1/com.google.events.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfoOrBuilder) \n\n public static interface DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfoOrBuilder extends MessageOrBuilder\n\nImplements\n----------\n\n[MessageOrBuilder](https://cloud.google.com/java/docs/reference/protobuf/latest/com.google.protobuf.MessageOrBuilder.html)\n\nMethods\n-------\n\n### getAverage()\n\n public abstract double getAverage()\n\nAverage of non-null values in the scanned data. NaN, if the field\nhas a NaN.\n\n`double average = 1;`\n\n### getMax()\n\n public abstract double getMax()\n\nMaximum of non-null values in the scanned data. NaN, if the field\nhas a NaN.\n\n`double max = 5;`\n\n### getMin()\n\n public abstract double getMin()\n\nMinimum of non-null values in the scanned data. NaN, if the field\nhas a NaN.\n\n`double min = 4;`\n\n### getQuartiles(int index)\n\n public abstract double getQuartiles(int index)\n\nA quartile divides the number of data points into four parts, or\nquarters, of more-or-less equal size. Three main quartiles used\nare: The first quartile (Q1) splits off the lowest 25% of data from\nthe highest 75%. It is also known as the lower or 25th empirical\nquartile, as 25% of the data is below this point. The second\nquartile (Q2) is the median of a data set. So, 50% of the data lies\nbelow this point. The third quartile (Q3) splits off the highest\n25% of data from the lowest 75%. It is known as the upper or 75th\nempirical quartile, as 75% of the data lies below this point.\nHere, the quartiles is provided as an ordered list of quartile\nvalues for the scanned data, occurring in order Q1, median, Q3.\n\n`repeated double quartiles = 6;`\n\n### getQuartilesCount()\n\n public abstract int getQuartilesCount()\n\nA quartile divides the number of data points into four parts, or\nquarters, of more-or-less equal size. Three main quartiles used\nare: The first quartile (Q1) splits off the lowest 25% of data from\nthe highest 75%. It is also known as the lower or 25th empirical\nquartile, as 25% of the data is below this point. The second\nquartile (Q2) is the median of a data set. So, 50% of the data lies\nbelow this point. The third quartile (Q3) splits off the highest\n25% of data from the lowest 75%. It is known as the upper or 75th\nempirical quartile, as 75% of the data lies below this point.\nHere, the quartiles is provided as an ordered list of quartile\nvalues for the scanned data, occurring in order Q1, median, Q3.\n\n`repeated double quartiles = 6;`\n\n### getQuartilesList()\n\n public abstract List\u003cDouble\u003e getQuartilesList()\n\nA quartile divides the number of data points into four parts, or\nquarters, of more-or-less equal size. Three main quartiles used\nare: The first quartile (Q1) splits off the lowest 25% of data from\nthe highest 75%. It is also known as the lower or 25th empirical\nquartile, as 25% of the data is below this point. The second\nquartile (Q2) is the median of a data set. So, 50% of the data lies\nbelow this point. The third quartile (Q3) splits off the highest\n25% of data from the lowest 75%. It is known as the upper or 75th\nempirical quartile, as 75% of the data lies below this point.\nHere, the quartiles is provided as an ordered list of quartile\nvalues for the scanned data, occurring in order Q1, median, Q3.\n\n`repeated double quartiles = 6;`\n\n### getStandardDeviation()\n\n public abstract double getStandardDeviation()\n\nStandard deviation of non-null values in the scanned data. NaN, if\nthe field has a NaN.\n\n`double standard_deviation = 3;`"]]
