Fold multiple columns by pattern

This processor takes values from multiple columns and transforms them to one line per column, like the Fold multiple columns processor. It selects the columns to fold using a pattern, and if the pattern has a capture group, the captured portion of the column name is used instead of the full column name.

It is a variant of Fold multiple columns, where the columns to fold are specified by a pattern instead of a list.

The processor only creates lines for non-empty columns.

For example, using “tag_(.*)” as column to fold pattern :

name	n_connection	tag_1	tag_2	tag_3
Florian	16570	bigdata	python	puns

becomes

name	n_connection	tag	rank
Florian	16570	bigdata	1
Florian	16570	python	2
Florian	16570	puns	3

With capture groups

Another example: with the following dataset representing quarterly scores:

person	age	Q1_score	Q2_score	Q3_score
John	24	3	4	6
Sidney	31		6	9
Bill	33	1		4

Applying the “Fold multiple columns by pattern” processor with a pattern “.*_score” will generate the following result:

person	age	quarter	score
John	24	Q1_score	3
John	24	Q2_score	4
John	24	Q3_score	6
Sidney	31	Q2_score	6
Sidney	31	Q3_score	9
Bill	33	Q1_score	1
Bill	33	Q3_score	4

When the pattern contains a capture group, the captured portion of the folded column’s name is used. On the same dataset, using the pattern “(.*)_score” would produce:

person	age	quarter	score
John	24	Q1	3
John	24	Q2	4
John	24	Q3	6
Sidney	31	Q2	6
Sidney	31	Q3	9
Bill	33	Q1	1
Bill	33	Q3	4

For more details on reshaping, please see Reshaping.

Smart Pattern

You can get help from Smart Pattern to write your regular expression. Click on ‘Find with Smart Pattern’.

In the ‘Smart Pattern’ window, you can highlight the portion of the column name that you wish to use. To use a pattern in the processor, select it and click on ‘OK’.