I have a DataFrame, df. n is a column denoting the number of groups in the x column. x is a column containing the comma-separated groups.

## How can I change the location of columns without using pandas

I have a matrix as shown below;And here's my code block:If a column full of A's, I want to move that column to the most right side, but my code moves all A's to right. This is my output:

## Transform binary vector to binary matrix

I have a binary vector that holds information on whether or not some event happened for some observation:

## Deprecation status of the numpy matrix class

What is the status of the matrix class in numpy? I keep being told that I should use the ndarray class instead. Is it worth/safe using the matrix class in new code I write? I don't understand why I should use ndarrays instead.

## Numpy: Efficient way to convert indices of a square matrix to its upper triangular indices

Question: given a tuple of index, return its order in upper triangular indices. Here is an example:Suppose we have a square matrix A of shape (3, 3).

## Diagonal snake filling array

Python 3.7. I'm trying to fill multidimensional array (n*m size) in diagonal-snake pattern:I have a function for n x n size and it works fine for it. But for n x m size it returns:

## Find equal rows between two Matlab matrices

I have a matrix index in Matlab with size GxN and a matrix A with size MxN. Let me provide an example before presenting my question.

## Create matrix row-index which increments when rowsum > 100, and following row

I have a matrix:I want to add a column with rows index. This index will starts at 1 and repeats the same index, until it arrived to a row where the rowsums is > 100 to move to the next value.

## How to calculate the sum of “submatrix” entries with numpy/pandas?

I have the following 8x8 matrix in Python, which I have represented as either an 8-by-8 numpy array, or a pandas DataFrame:

## Select entries of matrix based on given locations

I have following matrix (MxN where M ≤ N):From each row, I want to select following column entries respectively (one per row):