I have a numpy array with columns that are in blocks. I want to transpose the blocks. It's conceptually simple, and I guess one can do it simply, but I dont kno
I implemented it but it prints all. print(ta.STOCHRSI(df["close"], 14, 5, 3, 0)[-1]) 2022-04-20 17:00:00 NaN 2022-04-20 18:00:00 NaN 2022-04-
I have an xarray.Dataset with two 1D variables sun_azimuth and sun_elevation with multiple timesteps along the time dimension: import xarray as xr import numpy
I'm trying to "paste" the values contained in the 1D array dataslice (1x8) into the 2D array values_matrix (9x9), following the position indices contained in th
My question is how to convert a vector on pandas data frame into tensors. The data frame has a resume column which has a vector representations of each resume d
Please I need someone to explain the function of excluded argument in Numpy vectorize function in a simple way.
I've seen the data types in the NumPy package of Python, but I found the description of the data type 'intp' a bit confusing. Its description is like: intp: Int
I'm currently working to diagonalize a 5000x5000 Hermitian matrix, and I find that when I use Julia's eigen function in the LinearAlgebra module, which produces
I want to rank the rows of a 2D matrix lexicographically (in descending order) such that they are ranked: first by the left-most column, then second left-most c
I'm trying to plot a stellar orbit in a given potential. First, I initialize the position and velocity, and derive the acceleration from the position according
am trying to predict the exact solution for the mathieu's equation y"+(lambda - 2qcos(2x))y = 0. I have been able to get five eigenvalues for the equation using
I'm using scikit-learn TfldfVectorizer to produce the TF-IDF matrix #Import TfIdfVectorizer from scikit-learn from sklearn.feature_extraction.text import TfidfV
I have data in which values are ranging from small negative values to positive 1000. Since the minimum and maximum differ by large scales, I first set locator a
I'm trying to use finite differences to solve the diffusion equation in 3D. I think I'm having problems with the main loop. In particular the discrete equation
I'm having a hard time exporting my blender model to glTF 2.0 format (for godot): (I still can export it to default .dae format) So, I tried installing numpy f
Given a tensor b, and I would like to extract N elements in each row that satisfy a specific condition. For example, suppose a is a matrix that indicates whethe
I would like to expand a list of arrays into a single array, so for example: a = [array([1,2,3]), array([4,5,6]), array([7,8,9,])] To become: a = [array([1,2,3
I was using the CVXPY library in Python, trying to solve a particular optimization problem. import cvxpy as cp import numpy as np from scipy.stats import norm
Let's say that I have a data stream where single data point is retrieved at a time: import numpy as np def next_data_point(): """ Mock a data stream. Da
New to python, so if this impossible sorry for time wasting.. I would like to get the full data set that is printed in console into to the csv when written out.