Reshape Your Data With Ease

In this article, we are going to give some love to two tools that are often overlooked, the “Arrange“ and the “Make Columns“ tools.

🥑 Snack Pairing: Guacamole and Tortilla Chips

Just like guacamole adds that extra flavor to tortilla chips, the Arrange and Make Columns tools help you refine and spice up your data workflow. Fresh, customizable, and always a good choice for adding that extra punch to your Alteryx designs.

What Are the Arrange & Make Columns Tools?

In the Alteryx universe, organizing and reshaping data efficiently can be just as important as getting the data in the first place. Two essential tools that allow you to do this seamlessly are the Arrange and Make Columns tools. These tools might not always be in the spotlight, but they’re incredibly powerful when it comes to structuring your datasets just the way you need them.

Let’s dive into what each of these tools can do, when to use them, and how they stack up against their Excel counterparts.

The Arrange Tool: Rebuilding Your Data Structure

The Arrange tool is like a reconstruction tool for your data. If you’ve ever used the Transpose tool in Alteryx and needed to clean up the resulting data, the Arrange tool is the next step. It helps you reshape your data into a more usable format by allowing you to define which fields should form the columns and which should stay as values.

When to Use the Arrange Tool:

• After using the Transpose tool to pivot data, you can use Arrange to convert those rows back into a proper structure.

• If you want to build matrices or multi-dimensional tables from data that was unstructured.

• Rebuilding the layout of your data after some cleaning or transformation work.

Key Features:

• Group By: Allows you to group the data by specific fields, useful for keeping your data organized when you have categorical data.

• Header Field: Lets you specify which fields should act as headers (i.e., column names).

• Data Field: Defines the fields that will hold the actual data for the newly structured table.

• Easily handle missing data by filling or excluding based on your needs.

Excel Comparison:

The closest Excel tool to the Arrange tool would be a pivot table, but with more limitations. Excel pivot tables can be tricky when you need to unpivot or transpose data and then restore it. Alteryx’s Arrange tool does this fluidly, giving you more flexibility and control over how your data is reshaped.

The Make Columns Tool: Creating Columns On-the-Fly

The Make Columns tool is all about automation. It allows you to generate a fixed number of columns based on a specified number or field. This is particularly useful when you're working with data that requires a dynamic and flexible number of output columns, such as feature engineering in machine learning or preparing reports that require a set number of fields.

When to Use the Make Columns Tool:

• If you need to create multiple columns from a single field, for instance, separating data into distinct columns.

• When preparing datasets for machine learning models or analytics workflows where the number of features (columns) varies.

• If you have a dataset that contains delimited data in a single column and need to break that down into multiple columns for analysis.

Key Features:

• Specify Number of Columns: You can set how many columns to generate.

• Custom Field Names: The tool automatically creates columns with a base name like “Column_1”, “Column_2”, etc. You can also set the name dynamically.

• Delimiter: If you need to split data from a delimited string, this tool comes in handy to quickly split it into multiple columns.

Excel Comparison:

There isn’t a direct Excel counterpart for the Make Columns tool. You might be able to replicate similar functionality using text-to-columns or Excel formulas (e.g., SPLIT), but these methods are cumbersome and lack the flexibility of Alteryx’s dedicated tool.

How Do These Tools Work Together?

Imagine you’ve unpivoted your data using

, and now you need to clean it up. This is where the Arrange tool comes into play, reshaping your data back into a format that makes sense for analysis or reporting. Next, if you want to generate new columns or create a set number of output fields from a single field, you can use the Make Columns tool.

Both tools complement each other when working with complex datasets. For instance, if you need to organize raw transactional data into a multi-dimensional table and then split that table into separate columns based on categories or metrics, these tools can easily handle that workflow.

Best Practices for Using Arrange & Make Columns

• Handle Missing Data Carefully: When using the Arrange tool, always be mindful of how missing data is treated. Make sure to fill or exclude missing values where necessary to avoid misalignment in your data structure.

• Limit the Number of Columns: When using the Make Columns tool, it’s easy to generate too many columns. Always ensure that the number of columns you’re creating is reasonable for your analysis, as having too many columns can create unnecessary complexity.

• Naming Conventions: Make sure to give your newly generated columns meaningful names. This makes it easier to track and analyze your data later on.

• Testing and Validation: After using both tools, always validate that your reshaped or newly created columns match the expected data type and structure. This helps avoid errors down the road.

A Quick Comparison at a Glance

Conclusion: Reshaping Your Data Has Never Been Easier

The Arrange and Make Columns tools are simple but powerful ways to manipulate and reshape your data in Alteryx. Whether you’re rebuilding a table layout after a transpose operation or dynamically creating a set number of output columns, these tools give you the flexibility and control needed to optimize your workflows.

Happy snacking and analyzing!