I have an array consisting of two values a and b. (In my case these are strings). The array, in the physical interpretation, is periodic, so if N is the length of the array arr, then arr[n+N]=arr[n]. How do I roll the array such that it has the form [a, a, ..., a, b, ..., b, b] i.e. sorted or grouped into two parts within the context of the definition of array (physically it will remain the same because I will roll the physical quantity in the same way too, of which this array is a label)?

This could be a bug, or could be something I don’t understand about when numpy decides to convert the types of the objects in an “object” array.

This could be a bug, or could be something I don’t understand about when numpy decides to convert the types of the objects in an “object” array.

I have a (5, 5) 2D numpy array:

I am new python (and to coding in general) so apologies if this question isn’t the most descriptive.
I am trying to compare a string value of company names in a dataframe to a series of company names in a numpy array. If the company name in the dataframe matches any of the names in the numpy array, I want it to return 1. Otherwise I want it to return zero.

I have a 2D numpy array which I wrap around its both axes: x & y:

Let’s say I have a 2d matrix that with shape (6, 4), that represents values at coordinates

Supposed I have a numpy array [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16], How do I take 4 elements every 8 elements). Here is the expected result:

I know that in numpy, I can use numpy.take to get the subarray at a particular axis value instead of using fancy indexing.

I know that in numpy, I can use numpy.take to get the subarray at a particular axis value instead of using fancy indexing.