Questions tagged [elementwise-operations]
204 questions
2
votes
1 answer
Element-wise division between two dataframes with tickers and Date index
I have two dataframes with Date as index,
df1 as follows:
ticker AAPL AMD BIDU GOOGL IXIC MSFT
Date
2011-06-29 0.017664 0.024379 0.029592 …
Lazer
- 45
- 6
2
votes
3 answers
How to map a states table to life table in numpy?
The problem and what I expect.
I have a table h which indicates the H-bond states, where 1 for existing H-bond, 0 for no H-bond exist. Colums are for different object, rows are for different time step.
0, 0, 1, 1, 0, 0
0, 0, 1, 1, 0, 0
1, 0, 1, 1,…
Jack Huang
- 31
- 4
2
votes
1 answer
Logical AND operation across multiple lists
I have a dictionary that looks something like:
d= {'GAAP':[True,True],'L1':[True,False],'L2':[True,True]}
I would like to perform a logical AND operation across each of the values in the dictionary and return a LIST of True/False values. Something…
Number Logic
- 852
- 1
- 9
- 19
2
votes
1 answer
Custom algorithm to deal with negative values within a DataFrame
To start, I have a DataFrame that looks like the following:
df = pd.DataFrame({'a': [25, 22, -2, 16, 10], 'b': [-5, 18, -2, 25, 48], 'c': [34, -12, 7, 8, 22],
'd': [10, 8, -2, -4, 12]})
Goal: Eliminate all zeroes using a specific script or…
Jeff Coldplume
- 343
- 1
- 13
2
votes
3 answers
How to efficiently multiply every element in a 2-dimensional array by a 1-dimensional array in Numpy?
I would like to efficiently multiply every element in a 2D array with a 1D array using numpy, so that a 3D array is returned.
Basically, the code should do something like:
import numpy as np
#create dummy…
Cpt Fishpan
- 23
- 5
2
votes
6 answers
Concatenate two lists elementwise to an n x n matrix
I have two lists with strings which I want to concatenate elementwise into a n x n matrix. I have tried the below code but this only gives me n x 1 list.
row = ['a','b','c']
col = ['a','b','c']
matrix = map(''.join, zip(row,col))
The expected…
Anders
- 89
- 9
2
votes
1 answer
Numpy elementwise multiplication (unexpected integer overflow)
I'm using Python 3.7 and numpy 1.15.2 and have encountered a behavior in elementwise multiplication that I don't understand. The following is intuitive to me:
import numpy as np
a = np.array([[30000,4000]])
b =…
Irene Palnau
- 43
- 7
2
votes
1 answer
How to get Mean & Std of multiple numpy saved arrays using element-wise operation
I have a folder with 1000 numpy compressed files (npz) representing the results of a data simulation. Each file has two arrays a and b, with same dimension, shape, data type. What I want as a final output is the element-wise mean and standard…
renan-brso
- 149
- 3
- 11
2
votes
2 answers
Multiply each element of a vector by each element of another vector
I have two very big column vectors, A and B, of size ax1 and bx1, respectively. I want to construct a vector C of size (b*a)x1 by computing A(i)*B(j) for each i and j. To illustrate what I…
TEX
- 2,249
- 20
- 43
2
votes
2 answers
Element-wise maximum with key
is there a more efficient way to perform element-wise maximum with key?
import numpy as np
a = np.array([-2, 2, 4, 0])
b = np.array([-3,-5, 2, 0])
c = np.array([ 1, 1, 1, 1])
mxs = np.empty((4,))
for i in range(4):
mxs[i] = max([a[i], b[i],…
Low Yield Bond
- 327
- 5
- 10
2
votes
1 answer
2d array compare to 1d array returns 2d array
I am trying to compare a 1D array element-wise to a 2D array, and returns the elements of the 2D array which fulfils the condition in a 2D array form without using a for loop. Preferably using numpy or quicker method.
a = range(1,10)
Tna =…
Kingvader Wong
- 75
- 1
- 9
2
votes
2 answers
Element-wise mutiplication .* of vectors gives matrix in Matlab
Given two vectors
a = 1:3;
b = 2:4;
it's well known that the element-wise mutiplication a.*b produces
[ 2 6 12 ]
Calling that result c, we have c(i) = a(i)*b(i)
But I don't understand how a.*b', b'.*a and b'*a all produce
[ 2 4 6
3 …
wsdzbm
- 3,096
- 3
- 25
- 28
2
votes
2 answers
Python: how to get element-wise standard deviation of multiple arrays in a dataframe
I have a rather big dataframe (df) containing arrays and NaN in each cell, the first 3 rows look like this:
df:
A B C
X [4, 8, 1, 1, 9] NaN [8, 2, 8, 4, 9]
Y [4, 3, 4, 1, 5] [1, 2, 6,…
Svenno Nito
- 635
- 1
- 6
- 22
2
votes
2 answers
Comparing arrays and adding to different elements?
z = np.array([1, 2, 3, 4])
x = np.array([4, 2, 3, 5])
n = 1
I want to compare these two arrays element wise and I want to add n to only those elements of z that are different to those of x.
Answer should be:
z = [2, 2, 3, 5]
Charles B
- 95
- 3
- 14
2
votes
1 answer
Pandas multiply DataFrames with element-wise match of index and column
I have two pandas DataFrames, with one of them having index and columns that are subsets of the other. For example:
DF1 =
date a b c
20170101 1.0 2.2 3
20170102 2.1 5.2 -3.0
20170103 4.2 1.8 10.0
...
20170331 9.8 …
Zhang18
- 4,800
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- 67