Assume that I have two arrays A and B, where both A and B are m x n. My goal is now, for each row of A and B, to find where I should insert the elements of row i of A in the corresponding row of B. That is, I wish to apply np.digitize or np.searchsorted to each row of A and B.
For one off string searches, is it faster to simply use str.find/rfind than to use re.match/search?
I’m curious as to why it’s so much faster to multiply than to take powers in python (though from what I’ve read this may well be true in many other languages too). For example it’s much faster to do
I am currently running the following code based on Chapter 12.5 of the Python Cookbook:
Q: How to speed this up?
Example Problem As a simple example, consider the numpy array arr as defined below: import numpy as np arr = np.array([[5, np.nan, np.nan, 7, 2], [3, np.nan, 1, 8, np.nan], [4, 9, 6, np.nan, np.nan]]) where arr looks like this in console output: array([[ 5., nan, nan, 7., 2.], [ 3., nan, 1., 8., nan], … Read more
I have a problem to parse 1000’s of text files(around 3000 lines in each file of ~400KB size ) in a folder. I did read them using readlines,
Suppose I have an if statement with a return. From the efficiency perspective, should I use
This PEP adds a new statement “with” to the Python language to make it possible to factor out standard uses of try/finally statements.