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Transformation Examples

This section contains examples that demonstrate how Wrangle transformations and functions can quickly transform your data.

Note

These examples appear in other pages, including language reference documentation. See Wrangle Language.

Transformation Examples

Item

Description

EXAMPLE - ARRAYINDEXOF and ARRAYRIGHTINDEXOF Functions

This example illustrates how to convert the index value of an array for a specified value searching from left to right and right to left by using ARRAYINDEXOF and ARRAYRIGTHINDEXOF functions.

EXAMPLE - ARRAYLEN and ARRAYELEMENTAT Functions

This example illustrates how to return n-based number of elements in an array.

EXAMPLE - ARRAYSLICE and ARRAYMERGEELEMENTS Functions

This example illustrates how to generate an Array that is a slice of an another Array, based on index numbers. The elements of this Array can then be merged into a String value.

EXAMPLE - ARRAYSTOMAP Function

This example illustrates how to use the ARRAYSTOMAP and KEYS functions to convert values in Array or Object data type of key-value pairs.

EXAMPLE - Base64 Encoding Functions

This example demonstrates how to convert an input string to a base64-encoded value and back to ASCII text strings.

EXAMPLE - Case Functions

This example demonstrates functions that can be used to change the case of String values.

EXAMPLE - Comparison Functions1

This example illustrates the comparison functions in Designer Cloud Powered by Trifacta Enterprise Edition.

EXAMPLE - Comparison Functions2

This example demonstrates functions for comparing the relative values of two functions.

EXAMPLE - Comparison Functions Equal

This example demonstrates comparison functions.

EXAMPLE - Conditional Calculations Functions

This example illustrates how to use the conditional calculation functions.

EXAMPLE - COUNT Functions

This example demonstrates how to count the number of values and non-null values within a group.

EXAMPLE - COUNTIF Functions

This example demonstrates how to count the number of values within a group, based on a specified conditional test.

EXAMPLE - Countpattern Transform

This example demonstrates how to count the number of occurrences of text patterns in a column.

EXAMPLE - DATE and TIME Functions

This example provides an overview on various date and time functions.

EXAMPLE - Date Difference Functions

This example demonstrates how to calculate the number of days between two input dates.

EXAMPLE - DATEDIF Function

This example illustrates how to calculate the number of days that have elapsed between the order date and today.

EXAMPLE - Date Functions

This example illustrates to how to use date-related functions to derive specific values for a Datetime column type.

EXAMPLE - Date Functions - Min Max and Mode

This example shows how you can apply statistical functions on Datetime columns.

EXAMPLE - DATEIF Functions

This example illustrates how you can apply conditionals to calculate minimum, maximum, and most common date values.

EXAMPLE - Day of Functions

This example illustrates how you can apply functions to derive day-of-week values out of a column of Datetime type.

EXAMPLE - DEGREES and RADIANS Functions

This example illustrates to convert values from one unit of measure to the other.

EXAMPLE - Delete and Keep Transforms

This examples illustrates how you can keep and delete rows from your dataset.

EXAMPLE - Domain Functions

This examples illustrates how you can extract component parts of a URL using specialized functions for the URL data type.

EXAMPLE - Double Metaphone Functions

This example illustrates how to use double metaphone functions to generate phonetic spellings in Designer Cloud Powered by Trifacta Enterprise Edition.

EXAMPLE - Exponentional Functions

This example demonstrates the exponential functions.

EXAMPLE - Extractkv and Unnest Transforms

This example shows how you can unpack data nested in an Object into separate columns.

EXAMPLE - Extractlist Transform

This example illustrates how to extract values from a column.

EXAMPLE - Extract Values

In this example, you extract one or more values from a source column and assemble them in an Array column.

EXAMPLE - Flatten an Array

This section describes how to flatten the values in an Array into separate rows in your dataset.

EXAMPLE - Flatten and Unnest Transforms

This example illustrates you to use the flatten and unnest transforms.

EXAMPLE - Flatten and Valuestocols Transforms

This example shows how you can break out a column of nested values into separate rows and columns of data.

EXAMPLE - IF Data Type Validation Functions

This example illustrates how to use the IF* functions for data type validation.

EXAMPLE - IPTOINT Function

This examples illustrates how you can convert IP addresses to numeric values for purposes of comparison and sorting.

EXAMPLE - KTHLARGESTDATE Functions

This example illustrates how you can apply conditionals to calculate minimum, maximum, and most common date values.

EXAMPLE - KTHLARGEST Function

This example explores how you can use aggregation functions to calculate rank of values in a column.

EXAMPLE - KTHLARGESTIF Function

This example illustrates how to use the conditional ranking functions.

EXAMPLE - LIST and UNIQUE Function

This example demonstrates you to extract values from one column of an array into a new column.

EXAMPLE - LISTIF Functions

This example illustrates you to identify and list all values within a group that meet a specified condition.

EXAMPLE - LIST Math Functions

This example describes how to generate random array (list) data and then to apply statistical functions specifically created for arrays.

EXAMPLE - Logical Functions

This example demonstrate the AND, OR, and NOT logical functions.

EXAMPLE - Nest and Unnest JSON Records

This example illustrates how you can use unnesting and nesting transformations to reshape your JSON data.

EXAMPLE - Nest Columns into Arrays

This section provides simple examples of nesting columns into Arrays by extracting values from a column or nesting one or more columns into an Array column.

EXAMPLE - Nest Columns into Objects

This section provides a simple example of nesting columns into a new column of Object data type.

EXAMPLE - Nested Functions

This example illustrates how to use the nested functions.

EXAMPLE - Nest JSON Records

This section illustrates a simple example of how to nest tabular data into JSON records.

EXAMPLE - NEXT Function

This example covers how to use the NEXT function to create windows of data from the current row and subsequent (next) rows in the dataset. You can then apply rolling computations across these windows of data.

EXAMPLE - NOW and TODAY Functions

This example illustrates you to generate the date and time values for the current date and timestamp in the specified time zone.

EXAMPLE - Numeric Functions

This example demonstrates how to use numeric functions to perform computations in your recipe steps.

EXAMPLE - Percentile Functions

This example illustrates you to apply percentile functions.

EXAMPLE - POW and SQRT Functions

In this example, you learn how to compute exponentials and square roots on your numeric data.

EXAMPLE - PREV Function

This example describes how you can use the PREV function to analyze data that is available in a window in rows before the current one.

EXAMPLE - Quote Parameter

This example demonstrates how to use quote parameter for more sophisticated splitting of columns of data using the split transform.

EXAMPLE - RANDBETWEEN and PI Functions

This example illustrates how you can apply functions to generate random numeric data in your dataset.

EXAMPLE - RANK Functions

This example demonstrates you to generate a ranked order of values.

EXAMPLE - Replacement Transforms

This example illustrates the different uses of the replacement transformations to replace or extract cell data.

EXAMPLE - Rolling Date Functions

This example describes how to use rolling functions for Datetime values.

EXAMPLE - Rolling Functions

This example describes how to use rolling computational functions.

EXAMPLE - Rolling Functions 2

This example describes how to use rolling statistical functions.

EXAMPLE - ROLLINGKTHLARGEST Functions

This example describes how to use rolling kthlargest functions for calculating ranking of values within a defined window of rows.

EXAMPLE - Rounding Functions

This example demonstrates how the rounding functions work together.

EXAMPLE - Change data type transformation

This example illustrates how to clean up data by changing its data type to String, manipulating it using String functions, and then retyping the data to its proper data type.

EXAMPLE - Rename columns with rows

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

EXAMPLE - Splitting with Different Delimiter Types

This example shows how you can split data from a single column into multiple columns using delimiters.

EXAMPLE - STARTSWITH and ENDSWITH Functions

This example demonstrates functions that can be used to evaluate the beginning and end of values of any type using patterns.

EXAMPLE - Statistical Functions

This example illustrates how you can apply statistical functions to your dataset. Calculations include average (mean), max, min, standard deviation, and variance.

EXAMPLE - Statistical Functions Sample Method

This example shows some of the statistical functions that use the sample method of computation.

EXAMPLE - String Cleanup Functions

This example demonstrates functions that can be used to clean up strings.

EXAMPLE - String Comparison Functions

This example demonstrates functions that can be used to compare two sets of strings.

EXAMPLE - SUMIF and COUNTDISTINCTIF Functions

This example illustrates how you can use conditional calculation functions.

EXAMPLE - SUMIF Function

This example can be used to sum the values in a column based on a condition and organized by group.

EXAMPLE - Time Zone Conversion Functions

This example shows how you can use functions to convert Datetime values to different time zones.

EXAMPLE - Trigonometry Arc Functions

This example illustrates how to apply the inverse trigonometric (Arc) functions to your transformations.

EXAMPLE - Trigonometry Functions

This example illustrates how to apply basic trigonometric functions to your transformations.

EXAMPLE - Trigonometry Hyperbolic Arc Functions

This example illustrates how to apply inverse (arc) hyperbolic functions to your transformations.

EXAMPLE - Trigonometry Hyperbolic Functions

This example illustrates how to apply hyperbolic trigonometric functions to your transformations. All of the functions take inputs in radians.

EXAMPLE - Two-Column Statistical Functions

This example illustrates statistical functions that can be applied across two columns of values.

EXAMPLE - Type Functions

This example illustrates how various type checking functions can be applied to your data.

EXAMPLE - Type Parsing Functions

This example shows how to use parsing functions for evaluating input values against the function-specific data type.

EXAMPLE - UNICODE Function

In this example, you can see how the CHAR function can be used to convert numeric index values to Unicode characters, and the UNICODE function can be used to convert characters back to numeric values.

EXAMPLE - Unixtime Functions

This example illustrates how you can use functions to manipulate Unix time values in a column of Datetime type.

EXAMPLE - Unnest an Array

This section describes how to unnest the values in an Array into separate columns in your dataset.

EXAMPLE - Unnest JSON Records

You can unnest a set of JSON records into new columns of tabular data for easier manipulation within the application.

EXAMPLE - Extract Keys From Objects

You can extract the keys from an Object column into an Array of String values.

EXAMPLE - Extract Object Values

This simple example demonstrates how to extract nested values from Object elements into a separate column.

EXAMPLE - Filtering Strings into Objects

You can create nested objects by filtering strings. In this example, column headers and column values are nested into a single entity in a new column of Object data type.