Sort Transform

注意

Transforms are a part of the underlying language, which is not directly accessible to users. This content is maintained for reference purposes only. For more information on the user-accessible equivalent to transforms, see Transformation Reference.

Sorts the dataset based on one or more columns in ascending or descending order. You can also sort based on the order of rows when the dataset was created.

Limitations:

注意

This transform is intended primarily for use in the Transformer page. Sort order may not be preserved in the output files.

If you generate a new sample after a sort transform has been applied, the sort order is not retained. You can re-apply the sort step, although the following limitations still apply.
Sort order is not preserved on output when the output is a multi-part file.

Basic Usage

sort order:LastName

Output: Dataset is sorted in alphabetically ascending order based on the values in the LastName column, assuming that the values are strings.

Syntax and Parameters

sort order:column_ref

Token	Required?	Data Type	Description
sort	Y	transform	Name of the transform
order	Y	string	Name of column or columns by which to sort

For more information on syntax standards, see Language Documentation Syntax Notes.

order

Identifies the column or set of columns by which the dataset is sorted.

Multiple column names can be separated by commas.
Ranges of columns cannot be specified.

The order can be reversed by adding a negative sign in front of the column name:

Transformation Name	`Sort rows`
Parameter: Sort by	-ProductName

Multi-column sorts: You can also specify multi-column sorts. The following example sorts first by the inverse order of ProductName and within that sort, rows are sorted by ProductColor:

Transformation Name	`Sort rows`
Parameter: Sort by	-ProductName,ProductColor

Sort by original row numbers: As an input value, this parameter also accepts the SOURCEROWNUMBER function, which performs the sort according to the original order of rows when the dataset was created.

Transformation Name	`Sort rows`
Parameter: Sort by	$sourcerownumber

See SOURCEROWNUMBER Function.

Usage Notes:

Required?	Data Type
Yes	String (column name)

Data is sorted based on the data type of the source:

Data Type of Source	Sort Order
Integer	Numerical
Decimal	Numerical
Datetime	Numerical
All others	String

Examples

提示

For additional examples, see Common Tasks.

Example - sort methods

Source:

The column without a name identifies the original row numbers. In the data grid, this information is available when you hover over the black dot to the left of a row of data.

	CustId	FirstName	LastName	City	State	LastOrder
1	1001	Skip	Jones	San Francisco	CA	25
2	1002	Adam	Allen	Oakland	CA	1099
3	1003	David	Wiggins	Oakland	MI	125.25
4	1004	Amanda	Green	Detroit	MI	452.5
5	1005	Colonel	Mustard	Los Angeles	CA	950
6	1006	Pauline	Hall	Saginaw	MI	432.22
7	1007	Sarah	Miller	Cheyenne	WY	724.22
8	1008	Teddy	Smith	Juneau	AK	852.11
9	1009	Joelle	Higgins	Sacramento	CA	100

Transformation:

First, you might want to clean up the number formatting in the lastOrder column. The following formats the values to always include two digits after the decimal point:

Transformation Name	`Edit column with formula`
Parameter: Columns	LastOrder
Parameter: Formula	numformat(LastOrder, '####.00')

Now, you're interested in the highest value for your customers' most recent orders. You can apply the following sort:

Transformation Name	`Sort rows`
Parameter: Sort by	-LastOrder

Rows are sorted by the LastOrder column in descending order (largest to smallest):

	CustId	FirstName	LastName	City	State	LastOrder
2	1002	Adam	Allen	Oakland	CA	1099.00
5	1005	Colonel	Mustard	Los Angeles	CA	950.00
8	1008	Teddy	Smith	Juneau	AK	852.11
7	1007	Sarah	Miller	Cheyenne	WY	724.22
4	1004	Amanda	Green	Detroit	MI	452.50
6	1006	Pauline	Hall	Saginaw	MI	432.22
3	1003	David	Wiggins	Oakland	MI	125.25
9	1009	Joelle	Higgins	Sacramento	CA	100.00
1	1001	Skip	Jones	San Francisco	CA	25.00

The above row numbers represent the original order of the rows.Now, you want to get your data geographically organized by sorting by city and state. You can perform multi-column sorts such as the following, which sorts first by State and then by City columns:

Transformation Name	`Sort rows`
Parameter: Sort by	State,City

In the generated output, the data is first sorted by the State value. Each set of rows within the same State value is also sorted by the City value.

	CustId	FirstName	LastName	City	State	LastOrder
8	1008	Teddy	Smith	Juneau	AK	852.11
5	1005	Colonel	Mustard	Los Angeles	CA	950.00
2	1002	Adam	Allen	Oakland	CA	1099.00
9	1009	Joelle	Higgins	Sacramento	CA	100.00
1	1001	Skip	Jones	San Francisco	CA	25.00
4	1004	Amanda	Green	Detroit	MI	452.50
3	1003	David	Wiggins	Oakland	MI	125.25
6	1006	Pauline	Hall	Saginaw	MI	432.22
7	1007	Sarah	Miller	Cheyenne	WY	724.22

Example - Sort by original row numbers

This example illustrates how you can rename columns based on the contents of specified rows.

Source:

You have imported the following racer data on heat times from a CSV file. When loaded in the Transformer page, it looks like the following:

(rowId)	column2	column3	column4	column5
1	Racer	Heat 1	Heat 2	Heat 3
2	Racer X	37.22	38.22	37.61
3	Racer Y	41.33	DQ	38.04
4	Racer Z	39.27	39.04	38.85

In the above, the (rowId) column references the row numbers displayed in the data grid; it is not part of the dataset. This information is available when you hover over the black dot on the left side of the screen.

Transformation:

You have examined the best performance in each heat according to the sample. You then notice that the data contains headers, but you forget how it was originally sorted. The data now looks like the following:

(rowId)	column2	column3	column4	column5
1	Racer Y	41.33	DQ	38.04
2	Racer	Heat 1	Heat 2	Heat 3
3	Racer X	37.22	38.22	37.61
4	Racer Z	39.27	39.04	38.85

You can use the following transformation to use the third row as your header for each column:

Transformation Name	`Rename column with row(s)`
Parameter: Option	Use row(s) as column names
Parameter: Type	Use a single row to name columns
Parameter: Row number	3

Results:

After you have applied the above transformation, your data should look like the following:

(rowId)	Racer	Heat_1	Heat_2	Heat_3
3	Racer Y	41.33	DQ	38.04
2	Racer X	37.22	38.22	37.61
4	Racer Z	39.27	39.04	38.85

本节内容如下: