Challenge 2: Array Manipulation
NumPy offers a comprehensive set of tools for modifying and reshaping arrays. The key benefits include:
Diverse Capabilities: From reshaping to splitting, NumPy offers a wide range of functions to modify arrays as per requirements.
In-place Operations: Many NumPy functions can perform modifications in-place, meaning without creating a copy of the array, ensuring efficient memory usage.
Intuitive Syntax: Array manipulations often have a very readable and straightforward syntax, making the code self-explanatory.
The ability to seamlessly manipulate arrays is a cornerstone of many numerical and data science tasks, making these functions indispensable.
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Manipulate arrays to change their shape and get desired elements.
- Extract the diagonal elements.
- Retrieve the elements in the second row.
- Extract the 2nd and 3rd rows and change their shape to (5, 2).
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