I have a collection like : List<List<Object>> firstListI want to group together a similar list of pattern : List<List<Object>> secondList but grouped by indexes.
I am familiar with the concept of "vectorization", and how pandas employs vectorized techniques to speed up computation. Vectorized functions broadcast operations over the entire series or DataFrame to achieve speedups much greater than conventionally iterating over the data.
For A=[1,2,3]I would like to getB=['r1','t1','r2','t2','r3','t3']I know it is easy to get ['r1','r2','r3'] by
Let's say I have a "rectangular grid" made of nested arrays, like this:I am trying to iterate across its columns, so the result will be like 'a0', 'b0', 'c0', 'd0', 'a1'... etc.
Rust's for loops are a bit different than those in C-style languages. I am trying to figure out if I can achieve the same result below in a similar fashion in Rust. Note the condition where the i^2 < n.
I've written a basic script in Python3 that calculates the Collatz Conjecture. It takes a positive integer as an input and returns the number the steps until the sequence drops down to 1.
I'm doing a C# exercise to create an operation that takes a collection, performs a function on each object in the collection, and returns a collection of modified objects.
I would like to get an answer pointing out the reasons why the following idea described below on a very simple example is commonly considered bad and know its weaknesses.