What is broadcasting in NumPy?
An example of an AI chatbot conversation about broadcasting in NumPy.
What is broadcasting in NumPy?
Broadcasting in NumPy allows arrays of different shapes to be used together in arithmetic operations.
Can you give me an example of broadcasting?
Sure! If you have a 1D array of shape (3,) and a 2D array of shape (3, 4), NumPy will automatically expand the 1D array to match the shape of the 2D array.
How does NumPy handle different shapes during broadcasting?
NumPy compares the shapes from the trailing dimensions and expands them as needed, following specific rules.
What are the rules for broadcasting in NumPy?
The main rules are: 1) If dimensions are equal, they are compatible. 2) If one dimension is 1, it can be stretched. 3) If dimensions differ and neither is 1, an error occurs.
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