cellname()

Read(28) Label: excel cell name, row, column,

Description:

Return an Excel cell name according to specific row and column.

Syntax:

cellname(r,c)

Note:

The function finds the name of an Excel cell through row parameter r and column parameter c.

Parameters:

r

The rth row in an Excel sheet, which is an integer greater than 0

c

The cth column in an Excel sheet, which is an integer greater than 0

Return value:

A string

Example:

cellname(1,1)

Result: A1

cellname(4,3)

Result: C4

cellname(124,198)

Result: GP124

cgroups()

Here’s how to use cgroups() function.

T. cgroups(Fi,…;y:Gi,…;w)

Description:

Perform grouping and aggregation over a pre-summarized data cube.

Syntax:

T.cgroups(Fi,…;y:Gi,…;w)

Note:

For a grouping & aggregation operation over entity table T, the function automatically searches for and queries an eligible cube. It will first query a cube where the grouping field is in a more front position; if there isn’t such a cube, query the whole entity table. Parameter Fi is the grouping condition, parameter Gi is the result of calculating the aggregate function y, and parameter w is the filtering condition.

Parameters:

T

Entity table/cluster table

Fi

Grouping field

y

Aggregate function

Gi

Field names in result set

w

Filtering condition

Options:

@m(...;n)

Enable parallel processing; use default value when parameter n is absent (the default is the max number of parallel tasks set in Tool-Option

Return value:

A table sequence

Example:

 

 

A

 

 

1

=file("D://test/orders.ctx").create()

Open composite table file orders.ctx:

 

 

2

=A1.cgroups(OCount;count(OAmount):COUNT)

 

3

=A1.cgroups(OCount;count(OAmount):COUNT;OAmount<=3000)

Add filtering condition to A2

 

4

=A1.cgroups@m(OCount;count(OAmount):COUNT;OAmount<=3000;)

Parallel processing, as the number of parallel tasks is absent, use the default value

 

5

=A1.cgroups@m(OCount;count(OAmount):COUNT;OAmount<=3000;4)

Parallel processing with the number of parallel tasks being 4   

6

=file("emp.ctx":[1],["192.168.0.104:8282"])

Open cluster file emp.ctx

 

7

=A6.open()

Return a cluster table

 

8

=A7.cgroups(DEPT;count(EID):COUNT)

Perform grouping & aggregation over a pre-summarized data cube of a cluster table