Data Science and Machine Learning (Theory and Projects) A to Z - Pandas for Data Manipulation and Understanding: Pandas

The video tutorial introduces the rolling function in pandas, explaining its use for window operations on data frames. It demonstrates how to apply the rolling function with different window sizes and aggregates, and how to handle NaN values. Advanced techniques, such as using Gaussian windows for data smoothing, are also covered. The tutorial includes practical examples using both dummy and real datasets, highlighting the versatility and efficiency of the rolling function in data analysis.

What are some different types of window functions mentioned in the text?

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How can you avoid NaN values when using the rolling function?

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What is the significance of the minimum property in the rolling function?

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