dateinterval()

Read(43) Label: dateinterval,

Here are how to use dateinterval() functions.

A.dateinterval()

Description:

The external library function generates multiple date difference variables for a datetime sequence/table sequence variable.

Syntax:

A.dateinterval(T)

During modeling, generate multiple date difference variables for a sequence of datetime variables and return a binary sequence where the first bit is a table sequence made up of all the derivative variables and the second bit is generation process records Rec; the derivative variables automatically perform subsequent pre-processing

A.dateinterval@r(Rec)

During scoring, generate a table sequence consisting of multiple date difference variables according to sequence A of datetime variables and generation process records Rec

Parameters:

A

A sequence, which is a datetime variable

T

The target variable value used to perform potential data smoothing

Rec

A sequence of generation process records

Options:

@bnie

Each option specifies a target type, and options are mutual-exclusive; automatically judge the type when no option is used; the order of priorities of the options is binary, numeric, integer and enumerated

Return value:

A sequence/table sequence

Example:

 

A

 

1

=T("D: //catering_sale.csv").run(date1=date(date1,"yyyy/MM/dd"),date2=date(date2,"yyyy/MM/dd"))

 

2

=[A1.(date1),A1.(date2)]

A sequence of datetime variables

3

=A1.(sales)

The target variable

4

=A2.dateinterval@n(A3)

A4(1) A table sequence of derivative variables

A4(2) Generation process records Rec

@n specifies the target variable as numeric

5

=A2.dateinterval@r(A4(2))

Generate date difference variables for A2 according to A4’s generation process records Rec

 

P.dateinterval()

Description:

The external library function generates multiple date difference variables for a datetime table sequence/record sequence variable.

Syntax:

P.dateinterval(cns, T)

During modeling, generate multiple date difference variables for sequence cns of datetime variables and return a binary sequence where the first bit is a table sequence made up of all the derivative variables and the second bit is generation process records Rec; the derivative variables automatically perform subsequent pre-processing

P.dateinterval@r(cns, Rec)

During scoring, generate a table sequence consisting of multiple date difference variables according to sequence cns of datetime variables and generation process records Rec

Parameters:

P

A table sequence/record sequence

cns

A sequence of names of columns ( or column numbers starting from 1) of a record sequence

T

A sequence of target variable values used to perform potential data smoothing

Rec

A sequence of generation process records

Options:

@bnie

Each option specifies a target type, and options are mutual-exclusive; automatically judge the type when no option is used; the order of priorities of the options is binary, numeric, integer and enumerated

Return value:

A sequence/table sequence

Example:

 

A

 

1

=T("D: //catering_sale.csv").run(date1=date(date1,"yyyy/MM/dd"),date2=date(date2,"yyyy/MM/dd"))

 

2

=A1.(sales)

 

3

=A1.dateinterval@n(["date1","date2"],A2)

Generate difference between “date1” and “date2”, and perform smoothing according to target variable A2

A3(1) A table sequence of derivative variables

A3(2) Generation process records Rec

4

=A1.dateinterval@r(["date1","date2"],A3(2))

Generate multiple difference variables between “date1” and “date2” according to A3’s generation process records Rec