# How to add 'n' to each element, indexed by a second vector, using NumPy?

Hey, I encountered a code snippet titled “Adding ‘n’ to each element indexed by a second vector” utilizing NumPy functions. Seeking an explanation for this code or clarification on the described phenomenon using alternative code.

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Hello @safiaa.02, here is an explanation for the code you attached:

• The code creates a NumPy array `X` of length 10, filled with ones, using the `np.ones()` function and an array `Y` of 20 random integers between 0 and 9 (inclusive) using the `np.random.randint()` function.

• Then, the code uses the `np.bincount()` function to count the occurrences of each index in `Y`. and the `minlength` argument is specified that ensures that the length of the output of `np.bincount()` is the same as the length of `X`.

• Finally, the code adds the counts obtained from `np.bincount()` to the corresponding indices in `X` using the `+=` operator. This means that the counts are added to the original value of `X` rather than replacing it.

In summary, the code creates two NumPy arrays `X` and `Y`, counts the number of occurrences of each index in `Y` using `np.bincount()`, and then adds these counts to the corresponding indices in `X`. This is a way to incrementally count the occurrences of each index in `Y` in the array `X`.

You might ask why this code is useful. Well, this code can count the occurrences of elements in a dataset and create a histogram of the results. It is often used in data analysis, visualization, and machine learning applications to gain insights into data distribution.

I hope this helped!

For simplicity, you can use this simple code snippet using NumPy where I create two arrays, `Z` and `I`. The aim is to increment values in `Z` at specific indices based on the elements in array `I`. I’m including the `np.add.at()` function to add a given value (`n`) to the elements in `Z` at the indices specified in `I`. It’s worth noting that this function handles duplicates correctly. The resulting array `Z` reflects the incremented values at the specified indices.

Note that output will vary each time you run the code due to the randomness.