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Numpy Beginner's Guide (Update)

Numpy Beginner's Guide (Update)

By : Ivan Idris
2 (1)
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Numpy Beginner's Guide (Update)

Numpy Beginner's Guide (Update)

2 (1)
By: Ivan Idris

Overview of this book

This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources.
Table of Contents (16 chapters)
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14
C. NumPy Functions' References
15
Index

Fancy indexing

The at() method was added in NumPy 1.8. This method allows fancy indexing in-place. Fancy indexing is indexing that does not involve integers or slices, which is normal indexing. In-place means that the array we operate on will be modified.

The signature for the at() method is ufunc.at(a, indices[, b]). The indices array specifies the elements to operate on. We need the b array only for universal functions with two operands. The following Time for action section gives examples of the at() method.

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