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The following operations can be performed with the Shape Tool:

Each are discussed below.

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deduplicate
deduplicate
Deduplicate

The Deduplicate function searches your data for rows that match each other exactly, and condenses them into a single row, removing duplicate entries from your data.

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Fuzzy deduplication finds matching rows using a fuzzy algorithm. This means similar values, that are not exact matches, are grouped together and deduplicated. For example:
 

To enable this Beta feature, contact Paxata System Administrator and request that Fuzzy Deduplication be enabled.


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groupby
groupby
Group By

This function allows for the user to utilize a number of different aggregate functions (listed below) on any of the existing columns within the dataset. When the Group By button is selected, a pane will appear above the dataset which allows the user to specify which columns to include in the Group By process, which column they wish to perform an aggregate function on, which aggregate function to use, as well as specify the name of the new aggregate column being created. The data will display a preview of the selections made by the user, highlighted in blue, so that you can see how it will affect the data. It is important to remember that only those columns included in the "Columns (Aggregates)" field will remain in your data following the Group By function. Those columns included will be used when identifying duplicate rows for grouping.

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These operations are called aggregate because they find matching rows in the dataset and then combine them into one row. A matching row is defined as one that, excluding the reference column, share the same values in a column-by-column examination. The reference column is excluded from the column-by-column examination because its value are submitted to the aggregate function in order to produce the reference column value in the single-row result.

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transpose
transpose
Transpose

Transpose is the simplest of the Shape functions, essentially allowing you to switch your rows and columns (imagine rotating your data 90 degrees).

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Once you are satisified with the options you have chosen for the Transpose process, clicking the "Save" button in the upper-right hand corner of the screen will finalize and commit the process to your project.

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pivot
pivot
Pivot

Pivot is similar to transpose in that it allows you to rearrange your column headers into row headers; but, it also allows you to perform aggregate functions on a selected column to be displayed as the body of data within your pivot table. Unlike the Transpose function, multiple headings can be chosen as column headers.

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Remember to pay attention to the data displayed below the Shaping window, as it will show a preview of the Pivot table you are generating based on your selected options. Once you are satisfied with the setup of your Pivot table, clicking the "Save" button in the upper-right hand corner of the screen will finalize and commit the action to your project.


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depivot
depivot
Depivot

The Depivot function is a very powerful function that allows you to take your data and stack columns into two columns (one column containing the Column headers that the original data came from, a second column containing the value from that column). While a very powerful feature, for users who have never used a function like Depivot, it can be tough to understand exactly what is happening during the Depivot process.

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