Hey, I had work assigned to me in school which to basically write a code that was splitting a dataset into equal-sized subsets based on some indexing variable and then computing the mean of each subset. I had a hard time interpreting the logic for this, can anyone please provide me with a solution for this?

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Hello @safiaa.02, I have provided a solution below which splits a random dataset of 100 entries into groups based on unique random indexes and then calculates the mean for each group.

- The code generates an array of
`100`

random numbers between`0`

and`1`

, which serves as our sample dataset. It also generates an array of`100`

random integers between`0`

and`9`

to be used as an indexing variable. - Next, the unique values in
`S`

and their corresponding indices are found using`np.unique()`

. An array of zeros with the same length as the number of unique values in`S`

is created to store the mean of`D`

values for each unique value. - The code then loops over each unique value in
`S`

and calculates the mean of the`D`

values that correspond to the current unique value in`S`

. This is done using boolean indexing to select the`D`

values with the same index as the current unique value.