Mastering Pandas: 100 Examples for .apply(lambda) in Different Scenarios

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I. Overview of apply(lambda):

The apply(lambda) function in pandas is a versatile and powerful tool that is used for applying a function along the axis of a DataFrame or Series. It is a fundamental part of data manipulation and analysis in pandas. Here's an overview of the apply(lambda) function and why you might want to use it:

DataFrame.apply(func, axis=0, raw=False, result_type=None, args=(), **kwds)

• func: The function to apply to each column or row. apply() and lambda are often used together.
• It is not limited to using lambda functions; you can pass any function to apply(), whether it's a built-in function, a user-defined function, or a lambda function.
• axis: Specifies whether the function should be applied along columns (axis=0) or rows (axis=1).
• raw: If True, the function receives the data as a NumPy array. If False (default), the function receives a Series for each column or row.
• result_type: Specifies the type of the result. It can be 'expand', 'reduce', or 'broadcast'.
• args: Additional positional arguments passed to the function.

Working Principle: