Typescript Function in Palantir: Update Values in DataFrame Columns Without Data Loss

Learn how to implement a `Typescript` function in Palantir to manipulate DataFrame columns effectively by updating values and changing irrelevant information to null while preserving the integrity of your data.
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Understanding the Problem: Updating Values in DataFrame Columns

When working with large datasets, particularly in Palantir's Foundry environment, you may encounter situations where you need to update specific values in a DataFrame. One common requirement is to remove a value from a column and ensure that values in other related columns are set to null. This can be pivotal when maintaining data accuracy for downstream analytics or reporting.

For instance, consider a scenario where you have a DataFrame consisting of multiple entities with columns such as ID, level, responsible, and description. If you decide to remove an entry from the 'level' column, you also want the corresponding 'responsible' and 'description' fields to reflect this change appropriately — by turning them into null values.

In this guide, we will guide you through the process of implementing a Typescript function to achieve this result in an effective manner.

Example DataFrame Structure

Let's use the following example to illustrate our point:

IDlevelresponsibledescriptionA12level2NG34JeanSheetB15level5NG90ElisBellowC67level4NG64MatireClampH65level3NG45LouisCubicalJ90level0NG08MarieBlechExpected Outcome

When we remove the 'level' for ID B15 and ID H65, we expect the table to result in:

IDlevelresponsibledescriptionA12level2NG34JeanSheetB15No valuenullnullC67level4NG64MatireClampH65No valuenullnullJ90level0NG08MarieBlechSolution: Implementing the Typescript Function

Step 1: Function Declaration

To address this requirement, we can define a function that modifies these properties accordingly. Here is a proposed implementation:

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

Step 2: Explanation of the Code Changes

Loop through the objectPart array: The function iterates through the provided array that contains existing object properties.

Check for matching ID: For each object, it checks whether the ID matches the one that needs to be updated.

Create updated object properties: Instead of overwriting the entire entity with fewer columns, you redefine the necessary fields. By setting responsible and description to null, you keep these columns effectively empty to indicate the relationship loss.

Step 3: Executing Changes

Within this function, it’s necessary to appropriately handle the modification to the data structure. Ensure that after creating the updated object, you save or apply these changes as per your system’s method for persisting updates.

Conclusion

Updating values in a DataFrame can seem daunting, but with a well-structured Typescript function, you can do it seamlessly in Palantir Foundry. By implementing the example provided in this blog, you can easily manipulate your DataFrames, ensuring that when an entry is removed from one column, the related columns are set to null, maintaining the integrity of your data.

In summary, remember:

Always check for the ID match before applying changes.

Ensure the correct setting of attributes based on your use case.

Persist changes in accordance with your Palantir framework.

Armed with this knowledge, you can enhance your data manipulation strategies effectively!