Getting Started with dbtplyr

To use dbtplyr in your data models, you’ll utilize macros to define how you want to select and manipulate your data. Here’s a quick guide on how to get this set up.

Installation

Ensure you have dbt installed in your environment. You can install dbtplyr directly from your dbt project by adding it to your packages.yml file:

packages:
  - package: emilyriederer/dbtplyr
    version: [">=0.1.0"]

Using dbtplyr Macros

Here’s where the magic begins. Let’s say you have a dataset called mydata, and you want to perform different operations on columns based on their prefixes – for example, summing columns that start with ‘N’ and averaging those that start with ‘IND’ in the dataset mydata. This can be efficiently achieved using dbtplyr:

% set cols = dbtplyr.get_column_names(ref(mydata))
% set cols_n = dbtplyr.starts_with('N', cols)
% set cols_ind = dbtplyr.starts_with('IND', cols)

select
  dbtplyr.across(cols_n, sum(var) as var_tot),
  dbtplyr.across(cols_ind, mean(var) as var_avg)
from ref(mydata)

Analogy: Building Your Ideal Salad

Imagine you’re at a salad bar. You have various ingredients labeled with different tags – ‘Leafy’, ‘Veggie’, ‘Protein’, etc. Instead of picking each ingredient by hand, you tell the chef:

• “I want all the ‘Leafy’ ingredients in one bowl and all the ‘Protein’ ingredients in another.”

This is akin to how dbtplyr allows you to select columns based on their naming conventions. With a few instructions (macros), you can have your data neatly organized without the hassle of picking through everything manually!

Troubleshooting Tips

If you encounter issues when implementing dbtplyr, consider these troubleshooting ideas:

• Ensure that you have correctly set the column names in your reference. The macro dbtplyr.get_column_names(ref(mydata)) must point to an existing dataset.
• Check for typos or mismatched prefixes in starts_with() macros. It’s easy to overlook small details!
• If no columns match your conditions, consider using the final_comma parameter to handle empty matches gracefully.