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Filtering out null values

You've removed duplicate rows. The next step is to filter out any rows with null (empty) values in the transaction date column. Rows without a transaction date are likely not real transaction events and may have been generated in error.

You'll be using Python to carry out these data transformation tasks. Use CleanerBot3000 to understand why it's important to filter out the null values in the dataset and which Pandas function you need to utilize.

Ensure that CleanerBot3000 has applied this function and provided you with an updated view of your dataset!

What is the correct Pandas function to filter out null (empty) values?

This exercise is part of the course

Cleaning Data with Generative AI

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