Transforms

  • Aggregate Transform

    Overview The Aggregate Transform performs summary calculations across a set of values in a column, as grouped by the values in another column. Usage The following table explains how to use parameters with the Aggregate transform: Parameter Modifier Usage Function Formula consisting of columns in your dataset, functions, or conditional statements Required. Use this …

  • Countpattern Transform

    OverviewThe Countpattern transform counts the number of times a specified pattern occurs in a record. This transform creates a new column that contains an integer value. UsageThe following table explains how to use parameters with the Countpattern transform: Parameter Modifier Usage Column Argument: Column in your dataset. Required. Use …

  • Deduplicate Transform

    Overview The Deduplicate transform removes exact duplicate records from a dataset. The Deduplicate transform only removes rows where the following condition is true:For any two or more rows, the values in every column are the same. UsageThe Deduplicate transform is case-sensitive. You cannot modify the Deduplicate transform with any parameters. Use the following general format for the Deduplica…

  • Delete Transform

    Overview The Delete transform removes rows from a dataset. Rows must satisfy a conditional statement in order to be removed from the dataset. Usage The following table explains how to use parameters with the Delete transform: Parameter Modifier Usage Condition Formula consiting of functions or conditional statements. The condition that rows need to satisfy in order…

  • Derive Transform

    OverviewThe Derive Transform creates a new column in your dataset that contains the result of a specified formula. UsageThe following table explains how to use parameters with the Derive transform: Parameter Modifier Usage Formula Formula consisting of columns in your dataset, functions, or conditional statements Required. Use this parameter to …

  • Drop Transform

    Overview The Drop transform removes columns from a dataset. When Trifacta executes the Drop transform, the specified column(s) and all records in that column(s) are removed from the dataset. You can trigger a drop transform by: Clicking on one column header Clicking on multiple column headers Selecting columns from the Columns View UsageThe following table explains how to use paramete…

  • Extract Transform

    Overview The Extract transform extracts data that follows a specified pattern from a given column and creates a new column(s) containing that data. The original column remains unchanged. Usage The following table explains how to use parameters with the Extract transform: Parameter Modifier Usage Column Argument: Column in your dataset. Re…

  • Extractkv Transform

    Overview The Extractkv transform extracts key-value pairs from a source column and creates a new column containing those key-value pairs formatted as a map. The source column must have a data type of string. The data in the resulting column will conform to the following format:{“key1”:”value1”,”key2”:”value2”…}  Usage The following table explains how to use parameters with…

  • Extractlist Transform

    Overview The Extractlist transform extracts occurrences of a specified pattern from a source column and creates a new column containing an array of those pattern occurrences. The source column can have any data type. Usage The following table explains how to use parameters with the Extractlist transform: Parameter Modifier Usage Column Argument: Co…

  • Flatten Transform

    Overview The Flatten transform takes an array as the input and generates a new row for each value in the array. Flattening a column effects the entire dataset. keywords: flatten, convert, rows, columns, transform …

  • Header Transform

    Overview The Header transform converts the data in a specified row of a dataset into column headers. Usage The Header transform can by modified by specifying the Row Number. Trifacta defaults the row number to the first row. keywords: header, column names…

  • Join Transform

    Overview The Join transform allows you to enrich your data by combining common information between two datasets. Steps The first step is selecting the dataset you would like to join with   Next, edit the columns that are used as the join keys. Optional: you can choose to ignore case, special characters, and white space After specifying the join conditions, you can modify the join type The …

  • Keep Transform

    Overview The Keep transform retains only those rows in a dataset that satisfy a given conditional statement. You can use the Keep transform to filter your dataset. Usage The following table explains how to use parameters with the Keep transform: Parameter Modifier Usage Condition Argument: Conditional statement. Required. Use the row param…

  • Merge Transform

    Overview The Merge transform concatenates the values contained in two or more columns and creates a new column containing the resulting merged value. The Merge transform can also concatenate a string value with a values from a column in your dataset. Usage The following table explains how to use parameters with the Merge transform: Parameter Modifier Usage Colu…

  • Move Transform

    Overview The Move Transform allows the user to move columns anywhere in the dataset. Usage The following table explains how to use parameters with the Move Transform: Parameter Modifier Usage Column Column in your dataset Required. Use this parameter to select the column that you wish to move.  After Column in your dataset Required (if Before not sel…

  • Nest Transform

    Overview The Nest transform receives a list of columns as an input and creates a new column containing a map of key-value pairs or an array of values generated from the source column name and data. The original columns are retained in the dataset. The output column contains a map formatted as follows:{“key1”:”value1”,”key2”:”value2”…} or an array formatted as follows: ["val…

  • Pivot Transform

    Overview The pivot transform converts unique values in a column or columns into their own distinct column. The rows for each column contain summary calculations specified in the Functions box. Initiating from Builder: Initiating from column menu: Usage The following table explains how to use parameters with the Pivot transform: Parameter Modifier Usage Column …

  • Rename Transform

    Overview The Rename transform changes the name of a column. Usage The following table explains how to use parameters with the Rename transform: Parameter Modifier Usage Column Argument: Column in your dataset. Required. Use this parameter to select the column that you want to rename. The column parameter only accepts a single column…

  • Replace Transform

    Overview The Replace transform identifies occurrences of a specified pattern within a column, and replaces each occurrence of that pattern with a new value. Usage The following table explains how to use parameters with the Replace transform: Parameter Modifier Usage Column Argument: Column in your dataset. Required. Use this parameter …

  • Set Transform

    Overview The Set transform computes a supplied formula and then overwrites the values in a column with the result of that formula. Usage The following table explains how to use parameters with the Set transform: Parameter Modifier Usage Columns Argument:Column(s) in your dataset Required. Use this parameter to specify the column in your dataset that you want…

  • Settype Transform

    Overview The Settype Transform sets the data type of the specified column or columns. The valid and invalid values in the data quality bar computed based on the data type of that column. Usage The following table explains how to use parameters with the settype transform: Parameter Modifier Usage Column String literal specifies the column or columns where you want …

  • Sort Transform

    Overview The Sort Transform sorts the data in your dataset by the specified criteria. Usage The following table explains how to use parameters with the sort transform: Parameter Modifier Usage Sort by Column in your dataset or SOURCEROWNUMBER() when available specifies the column(s) or criteria you want to sort your dataset by. Trifacta defaults to sort descending, …

  • Split Transform

    Overview The Split transform creates new columns by splitting an existing column around a specified value or pattern. The new columns contain data located to the left and right of the pattern used to create the split. The original column is dropped. Usage The following table explains how to use parameters with the Split transform: Parameter Modifier Usage Colu…

  • Union Transform

    Overview The Union Transform allows you to append data from one dataset to another. Steps The first step is selecting the dataset you would like to append: Next, you can check the relationship between the column matches and manually add or change the columns: keywords: Union, transform, recipe, keys, flow, tools…

  • Unnest Transform

    Overview The Unnest transform expands the contents of an array or a map and creates new columns in your dataset for each element of the array or map. For maps, unnest takes each key-value pair and creates a new column with the key as the column header and the values as the columns rows. Usage The following table explains how to use parameters with the Unnest transform: Parameter M…

  • Unpivot Transform

    Overview The Unpivot transform reshapes a dataset by converting columns into row values.  You can initiate the an unpivot by clicking on the columns you would like to unpivot and find the suggestion card which converts columns into rows:   Or by selecting columns in the Columns View and selecting the action to Unpivot:  Or by working you way through builder and specifying the columns you…

  • Valuestocols Transform

    Overview The Valuestocols transform identifies unique values in a source column, creates a new column for each unique value, and places an indicator in the new column for each row where that unique value is present in the source column. By default, Trifacta enters “1” in the new column when the unique value is present in the source column. Trifacta leaves the new column empty when the unique …

  • Window Transform

    OverviewThe Window transform performs calculations on a set of rows in a dataset that are related to the current row. You can use the following window functions as part of the Window transform:prevnextsession You can use the Window transform when records in a dataset are related, or when records in a dataset are time-oriented and analysis needs to be performed over a given period of time. Usag…

  • FAQ: Trifacta Wrangle Language Overview

    The Trifacta Wrangle language is a data transformation language that you can use to design operations that Trifacta will perform on your data. Interacting with a dataset through predictive transformation also produces a series of transformation steps in the Wrangle language. • Basics • Transforms • Functions • Aggregate Functions • Comparison Functions •…

  • FAQ: Aggregate Functions

    Aggregate functions perform calculations on sets of values instead of on single values.The following table provides a brief description of the aggregate functions that you can use in Trifacta. You can click on the name of each aggregate function for a more detailed explanation of that function. Function Description Syntax …

  • FAQ: Date Functions

    Date functions allow you to perform operations on date/time values in Trifacta.The following table provides a brief description of the date functions that you can use in Trifacta. You can click on the name of each date function for a more detailed explanation of that function. Function Description Syntax …

  • FAQ: Logic Functions

    Logic functions perform Boolean operations on user-defined conditional statements and return true or false.The following table provides a brief explanation of the logic functions that you can use in Trifacta. You can click on the name of each function for a more detailed explanation of that function. Function Description Syntax…

  • FAQ: Math Functions

    Math functions allow you to perform mathematical operations on numeric values in Trifacta.The following table provides a brief explanation of the math functions that you can use in Trifacta. You can click on the name of each function for a more detailed explanation of that function. Function Description Syntax …

  • FAQ: Nested Functions

    Nested functions allow you to perform operations on columns that contain array-type data.The following table provides a brief explanation of the nested functions that you can use in Trifacta. You can click on the name of each function for a more detailed explanation of that function. Function Description Syntax …

  • FAQ: String Functions

    String functions allow you to perform operations on string values in your dataset. The following table provides a brief explanation of the string functions that you can use in Trifacta. You can click on the name of each function for a more detailed explanation of that function. Function Description Syntax …

  • FAQ: Type Functions

    Type functions allow you to identify sets of records in your dataset where the values in a given column conform to a specified data type or contain null data.The following table provides a brief description of the type functions that you can use in Trifacta. You can click on the name of each type function for a more detailed explanation of that function. Function Description Format …

  • FAQ: Window Functions

    Window functions perform calculations on sets of related values. The following table provides a brief description of the window functions that you can use in Trifacta. You can click on the name of each window function for a more detailed explanation of that function. Function Description Syntax …

  • FAQ: What is a Transform?

    Transforms in Trifacta are the commands used to manipulate data. When you write a wrangle script in Trifacta, the first element in each line of the script is the Transform. For example, the following line of Wrangle script executes the "derive" transform:derive value: mean(price)You can use the following Transforms when working in Trifacta:aggregatecountpatterndeduplicatedeletederivedro…

  • FAQ: Which parameters can I use to modify a transform?

    All transforms written in Wrangle conform to the following format:<transform> <parameter>: <function and/or argument>Each transform can be modified by one or more parameters. Each combination of transform and parameter can execute a specific set of functions on arguments. The following table shows the relationships between transforms, parameters, and functions in Trifacta: Transf…

  • FAQ: What is a function?

    Functions in Trifacta define computations that will be performed on data in one or more columns in a dataset. Trifacta includes functions in the following categories: Aggregate functions.Logic functions.Comparison functions.Math functions.Date functions.String functions.Nested functions.Type functions.Window functions.Special functions.Functions are not executable, and you can not invoke a funct…