Enrichment reference

This reference documentation explains how to use enrichments to tailor data to your needs.

The list of available enrichments is the following.

Enrichment category	Enrichment name	Description
Add fields	add_moving_average	Add a new field to the data extract with moving averages.
Add fields	addfield	Add a new field to the data extract with a specific value in each row.
Add fields	addfieldusingcontextx	Add a new field to the data extract with values calculated using data from the current, previous and next rows.
Add fields	addfieldx	Add a new field to the data extract with values calculated using a Python expression.
Add fields	addrownumbers	Add a new field to the data extract with row numbers.
Convert fields	aggregate	Convert existing fields in the data extract by performing calculations on selected values.
Convert fields	anonymise	Convert existing fields in the data extract by anonymizing the values in the selected fields.
Add fields	append	Add fields to the data extract from another datastream or subtable.
Map/Order	applyschema	Rename fields according to Data Mapping.
Import data	avro	Load data from an Apache AVRO file.
Select/Cut fields	cache	Cache the current state of the data table.
Add fields	capture	Add new fields to the data extract by capturing parts of the values from an existing field.
Select/Cut fields	collect	Populate a value table using values from a certain column in a data extract.
Select/Cut fields	conflicts	Find rows that share common values in a selected column but also contain non-identical values in at least one other column.
Convert fields	convert	Convert the values in a column of a data extract.
Convert fields	convertall	Convert all the values in a data extract.
Convert fields	convertallx	Convert all the values in a data extract using a Python expression.
Convert fields	convertdates	Convert dates to Python datetime.
Convert fields	convertduration	Convert duration data into ISO 8601 format.
Convert fields	convertnumbers	Convert numerical characters to numbers.
Convert fields	convertpacked	Convert keys and values within a dictionary into a new format.
Convert fields	convertunix	Convert a UNIX timestamp into an easy-to-read datetime format.
Convert fields	convertx	Use a Python expression to convert values in a selected column.
Import data	csv	Parse a csv file.
Convert fields	currency	Convert monetary values from one currency to another.
Select/Cut fields	cut	Keep columns from a data extract.
Select/Cut fields	cutout	Remove columns from a data extract.
Select/Cut fields	cutoutre	Find columns to remove from a data extract using a regular expression.
Select/Cut fields	cutre	Find columns to keep in a data extract using a regular expression.
Select/Cut fields	delta	Compare data extracts, and return unique rows into a new data extract.
Select/Cut fields	distinct	Find the number of distinct rows in a data extract.
Process files	dump	Save a copy of the data extract into a given file format.
Select/Cut fields	duplicates	Find and return the duplicated rows in a data extract.
Import data	excel	Load data from a specific sheet of an Excel file.
Notifications	expectheader	Check if the header contains the expected field names, and raise an error if issues are found.
Add fields	extendmissing	Check if certain columns exist in the data extract, and add them if they are missing from the data extract.
Map/Order	fieldmap	Update your data extract table by mapping existing values into new or existing columns.
Map/Order	filldown	Fill empty fields in the data extract using values in the row above.
Map/Order	fillright	Fill empty fields in the data extract using values in the column to the left of an empty column.
Add fields	filltimegaps	Add rows to a data extract containing missing dates in a date range.
Import data	fixencoding	Decode or encode a data extract.
Import data	fwf	Load data with a fixed width from a text file.
Convert fields	hash	Encrypt selected columns in a data extract.
Select/Cut fields	head	Return a set number of rows from the top of the data extract.
Notifications	if	Perform an action on a data extract if a condition is false.
Add fields	increment	Sort a data extract and add a new column containing a difference in values.
Add fields	join	Join data extracts from multiple datastreams into a single data extract.
Import data	json	Load data from a JSON file.
Notifications	mailto	Send a copy of a data extract by email.
Map/Order	map	Use a mapping table to create new values based on existing values in a data extract.
Map/Order	map_workspace	Send data to a workspace in Explore & Present.
Convert fields	melt	Reshape a table by transposing fields into data.
Map/Order	mergecolumn	Combine fields from different columns into a single column. The combined values are stored in a JSON-style dictionary.
Map/Order	mergeheader	Combine a defined number of rows into the table header.
Map/Order	mergesort	Combine data from a sorted data extract with another sorted data extract from a different datastream.
Import data	messy	Load messy files to parse the data using media type.
Meta operations	metaaddfield	Add a column to the data extract containing selected data from the metaheader.
Map/Order	movefield	Move a column to a new position in the data extract.
Add fields	namingconvention	Add new fields to the data extract by using parts of the values from an existing field. This is a simplified version of the capture instruction.
Import data	ndjson	Load data from a NDJSON (newline delimited JSON) formatted file.
Import data	parquet	Load data from a Parquet file.
Map/Order	preamble	Add new header rows and row values to the data extract.
Map/Order	pushheader	Add a new header to the data extract.
Convert fields	recast	Transpose distinct data values into the data extract header. This is the opposite of the melt instruction.
Import data	recode	Detects the encoding of data and re-encodes to a given encoding type.
Map/Order	rename	Rename columns in a data extract.
Map/Order	reorder	Reorder columns in a data extract.
Add fields	resolveurl	Add a new column to the data extract containing a resolved URL.
Select/Cut fields	search	Search for certain values in a data extract and keep the rows containing the values.
Select/Cut fields	select	Select rows in data extract to keep using a python expression.
Select/Cut fields	selecteq	Select and keep rows in a data extract if they contain values that are an exact match to a given value. This search is not case sensitive.
Select/Cut fields	selectfalse	Select and keep rows in a data extract that contain empty fields in a chosen column.
Select/Cut fields	selectgt	Select rows in a data extract to keep if a value is greater than a given limit.
Select/Cut fields	selectin	Select and keep rows in a data extract if they contain values that are an exact match to a given value. This search is case sensitive.
Select/Cut fields	selectinvt	Select rows in a data extract to keep if they match values in a value table.
Select/Cut fields	selectlt	Select rows in a data extract to keep if a value is less than a given limit.
Select/Cut fields	selectne	Select rows in a data extract that contain a value that does not match a given value.
Select/Cut fields	selectnone	Select and keep rows in a data extract if they contain empty values in a certain column.
Select/Cut fields	selectnotin	Select rows in data extract to keep if they do not exactly match a given value.
Select/Cut fields	selectnotnone	Remove rows from a data extract if they contain empty values in a certain column.
Select/Cut fields	selecttrue	Select and keep rows in a data extract if they contain any value.
Meta operations	set_meta	Add values to the metadata of a data extract.
Meta operations	set_tags	Add custom tags to your data extract.
Map/Order	setheader	Rename the column in your data extract.
Select/Cut fields	skip	Remove a number of rows from the start of a data extract.
Select/Cut fields	skipmeta	Download data directly from Adverity without a header in the file.
Select/Cut fields	skipuntil	Remove rows from a data extract until a given value is found.
Map/Order	sort	Sort data in a data extract.
Process files	split	Split a data extract into multiple extracts.
Add fields	splitfield	Split values into new columns using a regular expression.
Import data	spss	Load data from an SPSS file.
Add fields	sumup	Add a running total to your data extract.
Select/Cut fields	tail	Return a set number of rows from the bottom of a data extract.
Import data	text	Load data from a text file.
Convert fields	timecast	Split a date range across multiple rows in a data extract.
Convert fields	translate	Translate values in your data extract from one language to another.
Map/Order	transpose	Swap the positions of rows and columns in a data extract.
Select/Cut fields	trimheader	Remove leading or trailing whitespace from headers.
Check values	unique	Keep only the unique rows in a data extract.
Add fields	unpack	Separate values contained in lists into columns in a data extract.
Add fields	unpackdict	Separate values contained in dictionaries into columns in a data extract.
Add fields	unpacklist	Separate values contained in lists into rows in a data extract.
Check values	verifyunique	Check if the rows in a data extract are unique.
Import data	xlsx	Load data from an XLSX file.
Import data	xml	Load data from an XML file.
Import data	zipload	Load data from a ZIP file.