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Tag: numpy

Select multiple ranges of columns in Pandas DataFrame

I have to read several files some in Excel format and some in CSV format. Some of the files have hundreds of columns. Is there a way to select several ranges of columns without specifying all the column names or positions? For example something like selecting columns 1 -10, 15, 17 and 50-100: I need to know how to do

Skip every nth index of numpy array

In order to do K-fold validation I would like to use slice a numpy array such that a view of the original array is made but with every nth element removed. For example: If n = 4 then the result would be Note: the numpy requirement is due to this being used for a machine learning assignment where the dependencies

Numpy Array Conditional Operation Mask?

Suppose you have an array: a = [ 0,1,0] [-1,2,1] [3,-4,2] And lets say you add 20 to everything b = [ 20, 21, 20] [ 19, 22, 21] [ 23, 16, 22] Now lets say I want to add the resulting b to the original array a but only in cases where a < 0 i.e at the index

Understanding scipy deconvolve

I’m trying to understand scipy.signal.deconvolve. From the mathematical point of view a convolution is just the multiplication in fourier space so I would expect that for two functions f and g: Deconvolve(Convolve(f,g) , g) == f In numpy/scipy this is either not the case or I’m missing an important point. Although there are some questions related to deconvolve on SO

Error while reading image using cv2.imread() in Django views.py

I am trying to apply image processing on an image which i’m loading through cv2.imread() in Django’s views.py file, but i’m getting an AttributeError everytime. Following is the hierarchy views.py through which i’m trying to read temp321.jpg : Error which i’m getting: What am i doing wrong? Answer This error indicates that a is None. With a being the result

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