Advertisements I would like to multiply all items in an array with each other and to get a df with the first column being a1a1, a1a2, a1a3…, the second column a2a1, a2*a2 etc. and I’d like a vectorized solution. What I have so far is half-vectorized, I don’t know how to get rid of the… Read More Vectorized solution for multiplying each element of array with each element
Advertisements I’d like to vectorize my code and tried df[‘results’] = coord.loc[df[‘a’],’x_coord’] * coord.loc[df[‘b’],’y_coord’] but it returns the error "ValueError: cannot reindex on an axis with duplicate labels" because df[‘a] and df[‘b’] both contain duplicate values. These cannot be removed because they are the whole point (the df contains coordinates, therefore there are pairs like… Read More Vectorization of indexing into df rows
Advertisements Suppose we have a pandas dataframe: import pandas as pd data = pd.DataFrame({‘columnNM’: [‘Jerry’, ‘Bob’, ‘Phil’, ‘Bill’, ‘Mickey’, ‘Pigpen’, ‘Robert’], ‘columnNM2’: [‘John’, ‘Tom’, ‘Donna’, ‘Keith’, ‘Brent’, ‘Vince’, ‘Bruce’]}) Also suppose we have an open file we are writing to, something opened using: file = open(‘myPathExample’, ‘w’) I want to perform comparison operations, control flow… Read More Vectorized alternative for itertuples using file.write()
Advertisements What’s the fastest way to cycle through and repeat names in one dataframe when updating certain rows in a second dataframe? Thank you for your help. I’ve spent many days on this and am getting nowhere. Rows with Rules 4,5,6,10,11,12 should cycle through and repeat names in the Names Dataframe. This is the dataframe… Read More How to cycle through values in Pandas Dataframe?
Advertisements I have a pandas dataframe and I am trying to estimate a new timeseries V(t) based on the values of an existing timeseries B(t). I have written a minimal reproducible example to generate a sample dataframe as follows: import pandas as pd import numpy as np lenb = 5000 lenv = 200 l =… Read More Vectorized calculation of new timeseries in pandas dataframe
Advertisements I have a little bit code which I’ll have to vectorizate it to make it faster. I’m not very attached into python and thinking that the for loop is not so efficient. Is there any way to reduce the time? import numpy as np import time start = time.time() N = 10000000 #9 seconds… Read More Vectorization a code to make it faster than this
Advertisements I have np.ndarray A of shape (N, M, D). I’d like to create np.ndarray B of shape (N, M, D, D) such that for every pair of fixed indices n, m along axes 0 and 1 B[n, m] = np.eye(A[n, m]) I understand how to solve this problem using cycles, yet I’d like to… Read More Expand a dimension of 3-dimensional array into a diagonal matrix with vectorized computations
Advertisements I have a dataframe which looks like this: Market Date Begin Date Settlement 0 2016-01-01 2016-01-01 26.1935 1 2016-01-01 2016-02-01 24.1071 2 2016-01-01 2016-03-01 21.0591 3 2016-01-01 2016-04-01 20.7348 4 2016-01-01 2016-05-01 20.2072 … … … … 265198 2022-09-21 2031-04-01 65.1300 265199 2022-09-21 2031-05-01 65.1300 265200 2022-09-21 2031-06-01 65.1300 265201 2022-09-21 2031-07-01 65.1300 265202… Read More Vectorized way of checking a date column's calendar sequence
Advertisements I have two dataframe. The first dataframe have only one column: email, the first dataframe is a complete list of email. The second dataframe is a dataframe with three column: email, subscribe_or_unsubscribe, date. The second dataframe is a history of user subcribing or unsubscribing from the email system. The second dataframe is sorted by… Read More Vectorization assign the newest value based on datetime
Advertisements I’m trying to vectorise the following a = np.array([1,2]) b = np.array([[5,5],[5,5]]) target = 0 for _ in a: target = target + _ * b The above yields a 2×2 matrix where all entries are 15. How can I achieve this through vectorisation? I’ve been trying to cast a to be two 2×2… Read More Vectorising a sum of scalar multiplied by a matrix, where the scaler is an element of a list