I want to change first column to int in dnarray [[ 1. 6.218 2.974 0. ] [ 2. 32.881 8.66 0. ] [ 3. 38.94 35.843 0. ] [ 4. 8.52 35.679 0. ] [ 5. 52.902 49.538 0. ]] float64 int32 float64 I tried to use deepcopy, but no success. Any help will be good, I didn’t find any
Tag: numpy
Working with 2 arrays to populate a third one in numpy
I am trying to work with two arrays in a certain way in python. Lets say now I have a target array C = [2, 7, 15, 25, 40]. I want to find a output value (say Y) for each element in C (say x) with conditions: If x < A[0] then Y = B[0] If A[i] < x <
how to perform a backwards correlation/convolution in python
I am trying to perform a backwards correlation (at least that’s what I think it’s called) on 2 matrices to get a resultant matrix. Note: backwards convolution works too, because I’m applying this to a CNN. I have the following two matrices: vals: w0: I essentially want to apply a sliding window, except in this case all the values of
Map pandas dataframe columns to an array
I have a dataframe like this: And an array like: The first element will be for family_id=0 and column “choice_0” = 52 The second element will be for family_id=1 and column “choice_2” = 82 The third element will be for family_id=2 and column “choice_4” = 27 And I will like to get: The logic will be: For family_id =0 The
Pandas: Remove Column Based on Threshold Criteria
I have to solve this problem: Objective: Drops columns most of whose rows missing Inputs: 1. Dataframe df: Pandas dataframe 2. threshold: Determines which columns will be dropped. If threshold is .9, the columns with 90% missing value will be dropped Outputs: 1. Dataframe df with dropped columns (if no columns are dropped, you will return the same dataframe) Excel
Drop rows that contains the data between specific dates
The file contains data by date and time: All I want I want drop rows that contains between these dates and includes the start and end dates: Any Idea? Answer Sample: Use boolean indexing for filter by condition with chain by | for bitwise OR: Or filter by Series.between and invert mask by ~:
Finding the minimum of the N numpy matrices?
I want to find the minimum of N numpy matrices elementwise (but with a twist, read till the end). To show, I create 3 numpy matrices as follows: I except my output d to be: I also need to retain the information from where does the each element in the d matrix is coming from. So if I label a,
Find all coordinates of black / grey pixels in image using python
I’m trying to find a way to read any any .png, .jpg or .tiff, and return the coordinates of all black or grey pixels in that image. I’m thinking of having a certain threshold grey color, and writing out the coordinates of every pixel that is darker than that. I’m not sure how to manage the aspect of reading the
How to create a Python convolution kernel?
I’m trying to create a convolution kernel, and the middle is going to be 1.5. Unfortunately I keep running in to ideas on how to do that. I’m trying to create something similar to this Answer Since OpenCV uses Numpy to display images, you can simply create a convolution kernel using Numpy. Here’s the kernel. Note the type is <class
Is there a fast way to shuffle numpy image in segments?
I want to write a function that can take small images and return a permutation of them, block-wise. Basically I want to turn this: Into this: There was an excellent answer in Is there a function in Python that shuffle data by data blocks? that helped me write a solution. However for ~50,000 28×28 images this takes a long time