Apache Spark 3 for Data Engineering and Analytics with Python - Challenge Part 2 - Get the City and State

The video tutorial demonstrates how to extract city and state information from a purchase address using PySpark's split function. It covers creating a markdown heading, importing necessary functions, and manipulating dataframes to add new columns for city and state. The tutorial emphasizes avoiding user-defined functions by leveraging built-in PySpark capabilities, and it concludes with a demonstration of the final dataframe containing the extracted information.

What is the purpose of extracting the city and state from the purchase address?

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What are the three components of the purchase address mentioned in the text?

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How does the process of converting the purchase address into a list help in data analysis?

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Describe how the split function is used to separate the components of the purchase address.

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Explain how to retrieve the city from the list created by splitting the purchase address.

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What steps are taken to extract the state from the purchase address?

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What is the final outcome after adding the city and state as new columns to the dataframe?

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