Скачать или смотреть How to Implement Auto Mapping with Python for Excel IDs

Learn how to effectively perform `auto mapping` of IDs between two Excel sheets using Python with example code and steps for a seamless data processing experience.
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Solving ID Mismatches Between Excel Tables with Python

In today's data-driven world, managing and cleaning data efficiently is a necessity, especially when it comes to working with large datasets. If you've ever faced the challenge of mismatched IDs between two datasets, you'll understand how tedious it can be to reconcile them. This post will guide you through a step-by-step approach to automatically map IDs between two Excel sheets using Python, particularly when the IDs are not formatted consistently.

The Problem: Mismatched IDs

Say you have two Excel sheets that are connected via an ID column. Unfortunately, due to inconsistent formatting, IDs in the two tables may not match as expected. For example:

Table A has AA00-123-334

Table B contains AA-00123-334, A00-123-334, and other variations

In this scenario, the task is to perform automatic mapping of these IDs while ensuring that other relevant data within the rows is also considered.

The Steps Required

To address this, we will need to follow these steps:

Remove letters from the ID in Table B.

Delete dashes from the ID in Table B, making it a continuous number.

Format the ID back by adding a dash after every three digits from the right.

Search in Table A for the newly formatted ID.

Match the year of birth in both tables and update Table B with the corresponding ID from Table A if there is a match.

The Solution using Python

We can employ the powerful pandas library and regular expressions to achieve this efficiently. Below is how we can implement this:

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

Output Explanation

After running the code above, the output will show the formatted IDs in Table B and the corresponding mapped IDs from Table A.

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

Column expected_id now contains the matched IDs from Table A, compared based on the cleaned IDs and year of birth.

Conclusion

By utilizing efficient data manipulation techniques in Python, especially with pandas, we can automate the mapping of IDs from differing formats. This not only saves time but also reduces the likelihood of human error in the matching process. With these steps, your datasets can be cleansed and merged seamlessly, making your data analysis tasks much more straightforward.

Whether you're dealing with thousands of entries or a handful, this approach will streamline your workflow and enhance your productivity. Happy coding!