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Mapping rules and conditions
Jakub Dziuba avatar
Written by Jakub Dziuba
Updated over 2 weeks ago

RULES

General

Choose Data:

  • Description: Select the value to be included in this field by specifying a field from the import or a custom static value.

  • Example: Rename the "product_id" column to "product_id".

Leave Empty:

  • Description: Leaves cells blank.

  • Example: Leaving blank cells for missing product information.

Text

Join Values:

  • Description: Combines two or more values into one.

  • Example: Joining the "first_name" and "last_name" columns into "full_name".

Add Prefix:

  • Description: Adds a specified prefix to each value in the column.

  • Example: Adding the prefix "SKU-" to each value in the "product_code" column, e.g., "12345" -> "SKU-12345".

Add Suffix:

  • Description: Adds a specified suffix to each value in the column.

  • Example: Adding the suffix "-PL" to each value in the "country_code" column, e.g., "PL" -> "PL-PL".

Replace Single Value:

  • Description: Replaces one specific value with another value.

  • Example: Replacing the value "out_of_stock" with "unavailable" in the status column.

Replace Multiple Values:

  • Description: Replaces multiple values with other values.

  • Example: Replacing "yes" and "no" with "true" and "false" in the "available" column.

Remove Single Value:

  • Description: Removes one specific value from the column.

  • Example: Removing the value "N/A" from the "discount" column.

Remove Multiple Values:

  • Description: Removes multiple specified values from the column.

  • Example: Removing the values "unknown", "N/A", and "null" from the "supplier" column.

Remove Duplicates:

  • Description: Removes duplicate values.

  • Example: Removing duplicate product entries in a product catalog.

Recapitalize:

  • Description: Changes the capitalization of text (e.g., to uppercase).

  • Example: Changing "laptop" to "Laptop" in the "product_name" column.


Numeric

Recalculate Value:

  • Description: Recalculates values according to new rules.

  • Example: Converting the gross price to the net price in the "price" column.

Calculate Percentage Margin:

  • Description: Calculates the percentage margin.

  • Example: Calculating the percentage margin from the "selling_price" and "cost_price" columns.

Calculate Percentage Markup:

  • Description: Calculates the percentage markup.

  • Example: Calculating the percentage markup based on "cost_price" and "selling_price."

Round Value:

  • Description: Rounds numbers to a specified number of decimal places.

  • Example: Rounding price values in the "price" column to two decimal places.


Convert type

Convert to Text:

  • Description: Converts an array of values into a single string.

  • Example: Converting a list of categories ["electronics", "gadgets"] to "electronics, gadgets".

Pick from Array:

  • Description: Allows you to select a single value from an array.


Look Up

Extract Text From:

  • Description: Extracts specific data from a field.

  • Example: Extracting the zip code from the address in the "address" column.

Lookup in Table:

  • Description: comprehensive description and tutorial here


Data agregation

Segmentation:

  • Description: Divides a dataset into a specified number of equal groups. When using it, you also need to select the field in "Order by," which specifies the field by which the division is made. In "Tiles name," provide the names of the individual intervals (as many intervals will be created as there are names provided). In "Order direction," choose Descending or Ascending, depending on whether you want to divide and assign names in descending or ascending order.

  • Example: Dividing products into 3 groups (high, mid, low) based on the value in the ga4_item_netto_revenue field in descending order.

Rank Values:

  • Description: Assigns a rank to each row (each product) in the dataset, taking into account the specified criterion given in the "Order By" field and the "Order direction" - Descending or Ascending, depending on whether you want to assign the rank in descending or ascending order.

  • Example: Ranking products in descending order based on the value in the gads_clicks field.

Ranking products in descending order based on the value in the gads_clicks field.

Sum + Date Range:

  • Description: comprehensive description and tutorial here

CONDITIONS

is equal to

  • Description: Checks if a value is equal to a specified value.

  • Example: Checking if the order status is "shipped".


is not equal to

  • Description: Checks if a value is not equal to a specified value.

  • Example: Checking if the product category is not "outlet".


contains

  • Description: Checks if a value contains a specified string.

  • Example: Checking if the product description contains the word "premium".


does not contain

  • Description: Checks if a value does not contain a specified string.

  • Example: Checking if the product review does not contain the word "bad".


is blank

  • Description: Checks if a value is blank.

  • Example: Checking if the "discount_code" field is blank.


is not blank

  • Description: Checks if a value is not blank.

  • Example: Checking if the "email" field is not blank.


starts with

  • Description: Checks if a value starts with a specified string.

  • Example: Checking if the product code starts with "ABC".


does not start with

  • Description: Checks if a value does not start with a specified string.

  • Example: Checking if the category name does not start with "old".


ends with

  • Description: Checks if a value ends with a specified string.

  • Example: Checking if an email address ends with "@gmail.com".


does not end with

  • Description: Checks if a value does not end with a specified string.

  • Example: Checking if a phone number does not end with "000".


is greater than

  • Description: Checks if a value is greater than a specified value.

  • Example: Checking if the product price is greater than 100 PLN.


is greater or equal to

  • Description: Checks if a value is greater than or equal to a specified value.

  • Example: Checking if the stock quantity is greater than or equal to 10 units.


is less than

  • Description: Checks if a value is less than a specified value.

  • Example: Checking if the delivery time is less than 5 days.


is less or equal to

  • Description: Checks if a value is less than or equal to a specified value.

  • Example: Checking if the number of returns is less than or equal to 2.


is between

  • Description: Checks if a value is between two specified values.

  • Example: Checking if the order date is between January 1 and December 31.


is not between

  • Description: Checks if a value is not between two specified values.

  • Example: Checking if the customer's age is not between 18 and 25 years.


is longer than

  • Description: Checks if the length of a value is greater than a specified length.

  • Example: Checking if the product description is longer than 100 characters.


is shorter than

  • Description: Checks if the length of a value is shorter than a specified length.

  • Example: Checking if the category name is shorter than 50 characters.


matches regex

  • Description: Checks if a value matches a specified regular expression.

  • Example: Checking if the phone number matches the pattern "^\d{3}-\d{3}-\d{4}$".


does not match regex

  • Description: Checks if a value does not match a specified regular expression.

  • Example: Checking if the postal code does not match the pattern "^\d{2}-\d{3}$".


is in list

  • Description: Checks if a value is on a specified list of values.

  • Example: Checking if the country code is on the list of EU codes.


is not in list

  • Description: Checks if a value is not on a specified list of values.

  • Example: Checking if the product category is not on the list of discontinued categories.


is in list (regexp)

  • Description: Checks if a value matches any regular expression from a list.

  • Example: Checking if an email address matches one of many regular expression patterns.


is not in list (regexp)

  • Description: Checks if a value does not match any regular expression from a list.

  • Example: Checking if a URL does not match any forbidden regular expression patterns.

Data filtering categories:

Some conditions can only be used for filtering numeric data, while others are only for textual data. Here's the breakdown:


Conditions for filtering textual data:

is equal to

is not equal to
contains
does not contain
is blank
is not blank
starts with
does not start with
ends with
does not end with
is longer than
is shorter than
matches regex
does not match regex


Conditions for filtering numeric data:


is equal to
is not equal to
is greater than
is greater or equal to
is less than
is less or equal to
is between
is not between


Some conditions, like "is equal to" and "is not equal to", can be used for both textual and numeric data.

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