jkpieterse

cpreg1 = LAMBDA(temp, press,
    LET(
        tau, 1386 / temp,
        pi, 0.1 * press / 16.53,
        -0.001 * rgas_water * tau ^ 2 * gammatautaureg1(tau, pi)
    )
);

cpreg2 = LAMBDA(temp, press,
    LET(

ncalm

/*
OUTLIERS

These lambda functions allow us to quickly apply the standard deviation test to a series of transformed variables

Included in this file:

OUTLIER.THRESHOLDS - for calculating outlier thresholds using a standard deviation test

inputs:

ExcelRobot

/*
Name: Unpivot Table (UNPIVOT)
Description: Given a table range with headers and array of header names, unpivots the 
   specified columns in place, optionally removing any blank entries.
Written By: Excel Robot (@ExcelRobot)
Category: Array
*/
UNPIVOT=LAMBDA(table,[columns_to_unpivot],[attribute_name],[value_name],[remove_blanks], LET(
   _ColumnsToUnpivot, IF(
      ISOMITTED(columns_to_unpivot),

DrKarinaAdcock

// video explaining all these formulas: https://youtu.be/yO8zX_Ivcug

// see video: https://youtu.be/P8knGhzV7uk
ListTable = LAMBDA(array,
        LET(one,TAKE(array,,1),two,TAKE(array,,-1),
        list,UNIQUE(one),
        HSTACK(list,BYROW(list,LAMBDA(x,TEXTJOIN(", ",TRUE,FILTER(two,one=x)))))));
	
// see video: https://youtu.be/lli7MTilTB8
repeatXtimes = LAMBDA(array,num_repeat,

CHatmaker

/*  FUNCTION NAME:  CrtIdxλ
    DESCRIPTION:*/  /**Creates an array of indexes that can be used with INDEX() can combine  
                        all rows in all tables as would a database 'Natrual Join' or 'Cross Join.'*/
/*                  This was developed for multidimensional modeling. A key to multidimensional modeling
                    is the ability to combine all instances of all dimensions, and then access each 
                    dimension's value. A dimension is a category of things like:
                        Customers, Products, Regions, Months, etc.
                        
                    When faced with the situation where each dimension has a piece of information needed
                    for a particular calculation such as:

halbuki

/* ROOTS OF FUNCTIONS */
BISEC = LAMBDA(f, lbound, ubound, [prec],
    LET(
        c, (lbound + ubound) / 2,
        fl, f(lbound), fu, f(ubound), fc, f(c),
        IF(
            ABS(fc) < MAX(prec, 1E-15),
            c,
            IF(
                SIGN(fl) = SIGN(fc),

halbuki

/* USE NAMESPACE "List" */

Accumulate = LAMBDA(_list, _seed, _accumulator, REDUCE(_seed, _list, _accumulator));

AllTrue = LAMBDA(_list, AND(_list));

AnyTrue = LAMBDA(_list, OR(_list));

Average = LAMBDA(_list, AVERAGE(_list));

halbuki

/* USE NAMESPACE "Table" */

Item = LAMBDA(_table, _index,
    MAKEARRAY(
        2,
        COLUMNS(_table),
        LAMBDA(ir, ic, CHOOSE(ir, INDEX(_table, 1, ic), INDEX(_table, _index + 1, ic)))
    )
);

halbuki

/* USE NAMESPACE "Record" */

Field = LAMBDA(_record, _field,
    LET(
        fieldnames, Record.FieldNames(_record),
        fieldcol, List.PositionOf(fieldnames, _field),
        INDEX(_record, 2, fieldcol)
    )
);

ExcelRobot

/*
Name:  Mandelbrot Set (Mandelbrot)
Description:  Generates a Mandelbrot set based on given assumptions that can be used with conditional formatting to view the visual representation.
Parameters:
   xleft - Left X value
   xright - Right X value
   ytop - Top Y value
   ybottom - Bottom Y value
   size - number of columns/rows in square output range
   iterations - number of iterations