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RANK_ANLS

  • Last update:  2024-08-16
  • Concept

    Syntax

    RANK_ANLS(X_AGG(Array),Range,Order)

    Indicators are ranked across rows   based on fields added to horizontal/vertical axes or row/column dimensions.

    Parameter 1

    SUM_AGG(Array)

    The first parameter is the indicator to be ranked, which must be an aggregation function or aggregation indicator.

    An aggregation indicator refers to the result obtained by using an aggregation function.

    Parameter 2

    Range

    The second parameter Range is used to set the calculation range. You can set Range to 0 (ranking all rows) or 1 (ranking all rows within each group).

    Parameter 3

    Order

    The third parameter Order specifies the ranking rule. You can set Order to asc (ascending) or desc (descending).

    Notes

    The value of the third parameter is case-insensitive, which can also be DESC or ASC.

    Example

    RANK_ANLS(SUM_AGG(Total Amount),0,"asc"): When you drag the Contract Type field into the horizontal axis, the function groups and aggregates the total amount by contract type, and ranks the total amount in the ascending order across all contract types.

    You can download the sample data Contract Fact Table.xlsx.

    Rank the total amount, for example, rank the total amount of each contract type in the ascending order.

    Ranking the Total Amount by Contract Type

    Add a calculation field named Ranking by the formula RANK_ANLS(SUM_AGG(Total Amount),0,"asc"), as shown in the following figure.

    RANK_ANLS-排名 图1.png

    For details about how to write functions, see Function Calculation Format.

    Drag Contract Type, Total Amount, and Ranking into the analysis area, and select Ascend from the drop-down list of the Total Amount field, as shown in the following figure.

    RANK_ANLS-排名 图2.png

    Effect Display

    The total amount is ranked by contract type in the ascending order, as shown in the following figure.

    RANK_ANLS-排名 图3.png

    Further Learning

    Attachment List


    Theme: Advanced Data Analyis
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