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We'll start with another dirty application-log dataset, clean it with Pandas, and then send the cleaned records to an AI model for an evaluation of what is happening in the application.

For this example, instead of starting with CSV, we'll start with application-log data stored as JSON.

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We'll start with another dirty customer dataset, clean it with Pandas, save the results for both people and software, and then send the cleaned records to an AI model for an evaluation of the data.

For this example, we'll work entirely from the Linux terminal using Python and Pandas. We'll start with a simple CSV file containing customer names, cities, and ages.

In our last example, Python and Pandas turned messy temperature readings into clean CSV and JSON files. This time we'll take the idea one step further.