Solving Conditional Join Issues with the janitor Package in Python

Learn how to successfully perform a conditional join using the `janitor` package in Python, and resolve compatibility issues with older pandas versions.
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Using Conditional Join with the janitor Package in Python

When working with data in Python, particularly in analytics and data manipulation, it is common to need to join datasets based on specific conditions. This article will explore how to achieve this using the conditional_join function from the janitor package and address a common issue faced when using it with the latest versions of pandas.

The Problem at Hand

In our case, a user is trying to perform a lookup to retrieve factor values based on three conditions from a lookup table and a dataset. The lookup table contains several fields including State_Cd, Deductible, Revenue_1, Revenue_2, and Factor. The dataset includes policy information that corresponds to specific states and deductibles, and it also includes revenue figures.

The Lookup Table

Here’s how the lookup table looks:

State_CdDeductibleRevenue_1Revenue_2FactorTX0-99999999249999990.15TX025000000990000000.25TX1000-99999999249999990.20TX100025000000990000000.30CA0-99999999249999990.11CA025000000990000000.15CA1000-99999999249999990.13CA100025000000990000000.45The Dataset

The user's dataset corresponds to this structure:

PolicyStateDeductibleRevenueACA01500000BTX100030000000CTX01000000The goal is to retrieve the Factor value that meets these conditions:

The State must match the State_Cd.

The Deductible should be equal.

The Revenue should fall between Revenue_1 and Revenue_2.

The Attempted Solution

The user attempted to use the conditional_join method like this:

[[See Video to Reveal this Text or Code Snippet]]

Encountered Error

However, instead of obtaining the desired output, an error occurred:

[[See Video to Reveal this Text or Code Snippet]]

The Solution

Upon investigating the issue, the error appeared mainly due to the compatibility of the janitor package with the installed version of pandas. The solution is to revert to an earlier version of pandas.

Steps to Fix

To resolve this issue, you need to uninstall the current version of pandas and install an earlier version. Follow these steps:

Open your command line interface (CLI).

Run the command to install an older version of pandas, for example version 1.4:

[[See Video to Reveal this Text or Code Snippet]]

After the installation, rerun your conditional join code.

Expected Output

After applying the above solution, the expected output should now look like this:

PolicyStateDeductibleRevenueFactorACA015000000.11BTX1000300000000.30CTX010000000.15Conclusion

Using conditional_join from the janitor package can greatly simplify your data operations in Python. However, be mindful of package compatibility issues, particularly with pandas. By following the outlined solution, you should be able to achieve your desired data results without hindrance.

If you face similar issues, remember to check your package versions and ensure compatibility. Happy coding!