Page tree

Trifacta Dataprep



Contents:

If you licensed Dataprep by Trifacta before Oct. 14, 2020, you are using the Dataprep by Trifacta Legacy product edition. On October 14, 2022, this product edition will be decommissioned by Google and will be no longer available for use. Current customers of this product edition are encouraged to transition to one of the product editions hosted by Trifacta. See Product Editions.

   


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

ItemDescription
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 Dataprep by Trifacta®.
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  Dataprep by Trifacta®.
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 - 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 ANDOR, and NOT logical functions.
EXAMPLE - Nested Functions This example illustrates how to use the nested functions.
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 - 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 - 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 - Nest JSON Records This section illustrates a simple example of how to nest tabular data into JSON records.
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.

This page has no comments.