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dax-mastery掌握达克斯

Agent Skill

dax-mastery 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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423

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33

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148
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:dax-mastery(掌握达克斯)
来源仓库:https://github.com/josiahsiegel/claude-plugin-marketplace
仓库路径:skills/dax-mastery
安装命令:
npx skills add https://github.com/josiahsiegel/claude-plugin-marketplace --skill dax-mastery
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/josiahsiegel/claude-plugin-marketplace --skill dax-mastery

简介

dax-mastery 提供 Power BI 专属 DAX 表达式语言完整参考。

  • 涵盖行上下文、筛选上下文、CALCULATE 函数与时间智能等核心概念。
  • 包含迭代器函数、表格运算与性能调优策略,适用于复杂度量值开发。
  • 支持 RLS 过滤器与安全角色配置指导,强化数据治理实践。
  • 学习时应结合实际数据集练习,避免仅记忆语法而忽略语义理解。

SKILL.md

DAX (Data Analysis Expressions) Mastery

Overview

Complete DAX reference covering evaluation contexts, CALCULATE, time intelligence, iterators, table functions, performance optimization, and advanced patterns. DAX is the formula language for Power BI measures, calculated columns, calculated tables, and RLS filters.

Evaluation Contexts

Row Context

  • Created by: Calculated columns, iterators (SUMX, FILTER, AVERAGEX, etc.), row-by-row evaluation
  • Each row in the table has its own row context
  • Access columns directly: Sales[Amount]
  • Nested iterators create nested row contexts

Filter Context

  • Created by: Slicers, visual filters, page filters, report filters, CALCULATE arguments
  • Determines which rows are visible to aggregation functions
  • Does NOT provide row-level access (cannot use Sales[Amount] directly in a measure without aggregation)

Context Transition

  • CALCULATE converts row context into filter context
  • Happens when a measure is referenced inside an iterator
  • Each row's column values become filter arguments
// Context transition example:
Sales Amount = SUM(Sales[Amount])

// Inside SUMX, each row triggers context transition:
Weighted Amount =
SUMX(
    Products,
    Products[Weight] * [Sales Amount]  // [Sales Amount] triggers CALCULATE internally
)

CALCULATE - The Most Important Function

CALCULATE(<expression>, <filter1>, <filter2>, ...)

Filter argument types:

TypeExampleBehavior
Boolean (table filter)Products[Color] = "Red"Adds filter, keeps existing context
Table expressionFILTER(ALL(Products), Products[Price] > 100)Replaces filter on affected columns
REMOVEFILTERSREMOVEFILTERS(Products[Color])Removes existing filter on column
ALLALL(Products)Removes all filters on table
KEEPFILTERSKEEPFILTERS(Products[Color] = "Red")Intersects with existing filter
USERELATIONSHIPUSERELATIONSHIP(Sales[ShipDate], Date[Date])Activates inactive relationship
CROSSFILTERCROSSFILTER(Sales[ProductID], Products[ID], Both)Changes cross-filter direction

Critical rules:

  • Boolean filters are syntactic sugar for FILTER(ALL(column), condition)
  • Boolean filters REPLACE the existing filter on that column
  • Use KEEPFILTERS to ADD to (intersect with) existing filters
  • CALCULATE modifiers (ALL, REMOVEFILTERS) execute BEFORE filter arguments

Time Intelligence Quick Reference

Prerequisite: A proper Date table marked as a date table with a continuous date column.

FunctionPurposeExample
TOTALYTDYear-to-dateTOTALYTD([Sales], Date[Date])
TOTALMTDMonth-to-dateTOTALMTD([Sales], Date[Date])
TOTALQTDQuarter-to-dateTOTALQTD([Sales], Date[Date])
SAMEPERIODLASTYEARSame period, prior yearCALCULATE([Sales], SAMEPERIODLASTYEAR(Date[Date]))
DATEADDShift by intervalCALCULATE([Sales], DATEADD(Date[Date], -1, MONTH))
PARALLELPERIODEntire shifted periodCALCULATE([Sales], PARALLELPERIOD(Date[Date], -1, QUARTER))
DATESYTDDate table filtered to YTDCALCULATE([Sales], DATESYTD(Date[Date]))
DATESBETWEENDate rangeCALCULATE([Sales], DATESBETWEEN(Date[Date], start, end))
PREVIOUSMONTHEntire previous monthCALCULATE([Sales], PREVIOUSMONTH(Date[Date]))
PREVIOUSYEAREntire previous yearCALCULATE([Sales], PREVIOUSYEAR(Date[Date]))

Common time intelligence patterns:

// Year-over-Year Growth %
YoY Growth % =
VAR CurrentSales = [Total Sales]
VAR PriorYearSales = CALCULATE([Total Sales], SAMEPERIODLASTYEAR(Date[Date]))
RETURN
    DIVIDE(CurrentSales - PriorYearSales, PriorYearSales)

// Rolling 12-Month Total
Rolling 12M =
CALCULATE(
    [Total Sales],
    DATESINPERIOD(Date[Date], MAX(Date[Date]), -12, MONTH)
)

// Moving Average (3 months)
3M Moving Avg =
AVERAGEX(
    DATESINPERIOD(Date[Date], MAX(Date[Date]), -3, MONTH),
    CALCULATE([Total Sales])
)

Variables (VAR/RETURN)

Always use variables for readability and performance:

Profit Margin % =
VAR TotalRevenue = SUM(Sales[Revenue])
VAR TotalCost = SUM(Sales[Cost])
VAR Profit = TotalRevenue - TotalCost
RETURN
    DIVIDE(Profit, TotalRevenue)

Rules:

  • Variables are evaluated once (performance benefit when reused)
  • Variables capture filter context at the point of definition
  • Variables can hold scalar values or tables
  • Use meaningful names (not x, temp)

Iterator Functions

Iterators scan a table row by row, creating row context:

FunctionPurpose
SUMXSum of expression evaluated per row
AVERAGEXAverage of expression per row
MINX / MAXXMin/Max of expression per row
COUNTXCount of non-blank expression results
RANKXRank based on expression
FILTERReturns table rows matching condition
ADDCOLUMNSAdds calculated columns to table
SELECTCOLUMNSReturns table with selected/calculated columns
GENERATECross-join with row context
// Weighted average price
Weighted Avg Price =
SUMX(
    Sales,
    Sales[Quantity] * RELATED(Products[UnitPrice])
) / SUM(Sales[Quantity])

Calculation Groups

Reduce measure sprawl by defining reusable calculation patterns:

// Instead of creating YTD, PY, YoY for EVERY measure:
// Create ONE calculation group with items:
// - Current: SELECTEDMEASURE()
// - YTD: CALCULATE(SELECTEDMEASURE(), DATESYTD(Date[Date]))
// - PY: CALCULATE(SELECTEDMEASURE(), SAMEPERIODLASTYEAR(Date[Date]))
// - YoY%: VAR Curr = SELECTEDMEASURE()
//         VAR PY = CALCULATE(SELECTEDMEASURE(), SAMEPERIODLASTYEAR(Date[Date]))
//         RETURN DIVIDE(Curr - PY, PY)

Create via Tabular Editor, TMDL view in Desktop, or TOM/.NET SDK.

Field Parameters

Enable users to dynamically switch dimensions or measures in visuals:

// Created via Modeling tab > New parameter > Fields
// Generates a calculated table:
Parameter =
{
    ("Revenue", NAMEOF(Sales[Total Revenue]), 0),
    ("Profit", NAMEOF(Sales[Total Profit]), 1),
    ("Units", NAMEOF(Sales[Total Units]), 2)
}

User-Defined Functions (September 2025 Preview)

The most significant DAX language update since variables (2015). Define reusable parameterized functions:

// Define a UDF in DAX query view or model
DEFINE
FUNCTION AddTax = (amount : NUMERIC) => amount * 1.1

// Nest UDFs
FUNCTION AddTaxAndDiscount = (amount : NUMERIC, discount : NUMERIC) =>
    AddTax(amount - discount)

EVALUATE { AddTaxAndDiscount(100, 20) }  // Returns 88

Parameter types: NUMERIC, Scalar, Table, AnyVal, AnyRef, CalendarRef, ColumnRef, MeasureRef, TableRef

Parameter modes: val (eager evaluation) or expr (lazy/context-sensitive)

Usage: Once defined and saved to the model, call UDFs from measures, calculated columns, visual calculations, and other UDFs.

Enable: File > Options > Preview features > DAX user-defined functions

Window Functions (WINDOW, INDEX, OFFSET)

DAX window functions for row-relative and range calculations:

// Running total using WINDOW
Running Total =
CALCULATE(
    [Total Sales],
    WINDOW(1, ABS, 0, REL, ALLSELECTED(Date[Month]),
        ORDERBY(Date[MonthNumber], ASC))
)

// Previous row value using OFFSET
Previous Month Sales =
CALCULATE(
    [Total Sales],
    OFFSET(-1, ALLSELECTED(Date[Month]),
        ORDERBY(Date[MonthNumber], ASC))
)

// Nth row using INDEX
First Month Sales =
CALCULATE(
    [Total Sales],
    INDEX(1, ALLSELECTED(Date[Month]),
        ORDERBY(Date[MonthNumber], ASC))
)

Key clauses:

  • ORDERBY -- sort order within the window
  • PARTITIONBY -- subset of rows (the "window" partition)
  • MATCHBY -- identify the current row in ambiguous contexts

Visual Calculations (2024-2026)

Calculations scoped to the visual matrix, not the data model:

FunctionPurpose
FIRSTValue from first row of axis
LASTValue from last row of axis
PREVIOUSValue from previous row
NEXTValue from next row
LOOKUPValue with filter (June 2025)
LOOKUPWITHTOTALSValue with filter, respects totals (June 2025)

Visual calculations are defined per-visual and do not affect the semantic model.

Calendar-Based Time Intelligence (September 2025 Preview)

Define custom calendars (fiscal, retail, 13-month, lunar) with 8 new week-based functions:

FunctionPurpose
TOTALWTDWeek-to-date running total
CLOSINGBALANCEWEEKClosing balance for the week
OPENINGBALANCEWEEKOpening balance for the week
STARTOFWEEKFirst date of current week
ENDOFWEEKLast date of current week
NEXTWEEKTable of dates for next week
PREVIOUSWEEKTable of dates for previous week
DATESWTDWeek-to-date date filter

Enable: File > Options > Preview features > Enhanced DAX Time Intelligence

Dynamic Format Strings

Apply context-dependent formatting without converting to text (GA in Desktop and Report Server Jan 2025+):

// Dynamic format string for currency
Total Sales =
SUM(Sales[Amount])

// Format string expression (set in measure properties):
// = IF(SELECTEDVALUE(Currency[Code]) = "EUR", "€#,##0.00", "$#,##0.00")

Advantage over FORMAT(): Keeps numeric data type, enabling correct chart rendering and sorting.

TABLEOF and NAMEOF (February 2026)

Reference model objects that auto-adapt to renames:

// NAMEOF returns the name of a column/measure/calendar as text
NAMEOF(Sales[Amount])  // Returns "Amount"

// TABLEOF returns a reference to the table of a column/measure
TABLEOF(Sales[Amount])  // Returns reference to Sales table

Useful inside UDFs for safer, rename-proof code.

Common Anti-Patterns

Anti-PatternProblemFix
FILTER(table,...) as CALCULATE argFull table scan, no engine optimizationUse boolean filter: column = value
Nested CALCULATEConfusing context overridesUse single CALCULATE with multiple filters
SUMX over entire table for simple sumUnnecessary iteratorUse SUM() for simple column aggregation
FORMAT() in measures for sortingReturns text, cannot sort numericallyUse separate sort column
Calculated columns for aggregationStored per row, wastes memoryUse measures instead
COUNTROWS(FILTER(table,...))Slower than CALCULATE(COUNTROWS(table), filter)Use CALCULATE with filter
Copy-pasting DAX across measuresHard to maintain, error-proneUse UDFs (preview) to define reusable logic
FORMAT() for conditional displayReturns text, breaks sorting/chartsUse dynamic format strings instead
Overusing EARLIER()Confusing, legacy patternUse VAR to capture outer context
Ignoring MATCHBY in window functionsAmbiguous row identityAlways specify MATCHBY when partition has duplicates

Additional Resources

Reference Files

  • references/dax-function-categories.md -- Complete function reference organized by category including INFO functions, window functions, and 2025-2026 additions
  • references/dax-patterns-advanced.md -- Advanced patterns: virtual relationships, dynamic segmentation, parent-child hierarchies, basket analysis

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Codex

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按下载量换算13

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