I have the following arrays: And I need to run each array through the following if-else statement: How can I do this without writing an if-else statement for each array? It’s manageable for now, but I plan to have 25 of these arrays, and I feel like there’s a better way. Answer Put all of your votes into a list
Tag: arrays
How do I find the highest float from a list?
I have made a program that gets a movie you pick from a list and tells you its directors and rating it also tells you if a movie is the highest-rated. I want the program to do the same thing it is doing but instead of just checking if the title is 5 stars, it checks if the rating is
Creating 3d Tensor Array from 2d Array (Python)
I have two numpy arrays (4×4 each). I would like to concatenate them to a tensor of (4x4x2) in which the first ‘sheet’ is the first array, second ‘sheet’ is the second array, etc. However, when I try np.stack the output of d[1] is not showing the correct values of the first matrix. Answer If you do np.dstack((x, y)), which
How to change 12 random 0 to 1 in python Matrix
My program is suppose to change 12 zeros on random positions to 1 in python 6×6 matrix. This is my code. So my matrix is going to look like this at the beggining So I randomly chose an array and the element in chosen array. The problem is that different number of zeros is changed every time. Not 12 like
Trying to run a test to see how many children it takes to have one of each sex but the array is not working properly?
I am running some code for a class and I have no clue what to do, I submitted the assignment but it’s not helpful if I don’t know what to do in the end. Here is the code that I am running to try and track these tests. The idea is to see how many children it takes before you
How do you slice a cross section in pandas or numpy?
I have the following data frame which can be copy/pasted and made to a data frame with: df = pd.read_clipboard() I would like to take a cross section from it, I want something like say: [1, 4, 9, 1, 10, 6, 4, 0, 4, 6, 10, 1, 9, 4, 1]) which is index df.loc[1, 0], df.loc[2, 1], df.loc[3, 2], df.loc[4,
How to length the last dimension of a numpy array and fill it up with another array?
I have a numpy array of shape (5, 4, 3) and another numpy array of shape (4,) and what I want to do is expand the last dimension of the first array (5, 4, 3) -> (5, 4, 4) and then broadcast the other array with shape (4,) such that it fills up the new array cells respectively. Example: becomes
Fastest way to create a square nxn matrix from 1d array in numpy
Suppose the following numpy array: I want to know the fastest way to generate the following operation: (1) How to efficiently create matrix “result” (because n >> 0 can be very large) ? (2) Does this matrix have a particular name ? Answer This is a bit faster: cursory benchmarks, nothing scientific. (timeit 100 times with arr):
how to split a numpy array into subarrays based on values of one colums
I have a big numpy array and want to split it. I have read this solution but it could not help me. The target column can have several values but I know based on which one I want to split it. In my simplified example the target column is the third one and I want to split it based on
Connecting to random points in a 2d numpy array based on distance
I have a 2d numpy array and select a random coordinate position (say 10×10 array and start at position 2,3). I want to randomly connect to 40% of the other points in the 2d array effectively generating a list of tuples [(x1, y1), (x2, y2) …] where the list is 40% of the other coordinates. An additional constraint, however, is