I have a 3D numpy array and I want to add a 2D np array of 0’s to the front of it. I want to add another array B so that: I’ve tried np.append(B,A) but it returns a 2D array. Answer You can do it using numpy.vstack and by reshaping your array. For instance: By the way, you can create
Tag: numpy
Python Numpy; difference between colon and ellipsis indexing
I have been experimenting with Numpy array indexing using both colon and ellipsis. However, I cannot understand the results that I am getting. Below is the example code: Answer The original is (2,2) With :, it becomes (2,1,2). The new axis added after the first dimension. With … the shape is (2,2,1), the new shape is added last.
Matplotlib histogram where bins are defined range of FLOATS and colored by it?
I do RMSF analysis and as a results I have list of floats (0.1, 0.3, etc.) and I would like to do a histogram where are bins of defined ranges of the floats. Then I want to have each range of float with corresponding color. I tried to do it with analogies of this script: I know that there is
Python – Convert Array of Float audio data to wav file
I have audio data recorded from microphone like this : (ndarray of float) This is my code: But when I play the audio it become broken, nothing but just noise… how to convert it into .wav audio file? Answer you need to use pack your data first using struct replace your waveFile.writeframeswith this and maybe also convert your data to
Creating a tumbling windows in python
Just wondering if there is a way to construct a tumbling window in python. So for example if I have list/ndarray , listA = [3,2,5,9,4,6,3,8,7,9]. Then how could I find the maximum of the first 3 items (3,2,5) -> 5, and then the next 3 items (9,4,6) -> 9 and so on… Sort of like breaking it up to sections
Manipulating 2D matrix using numpy boolean indexing takes a long time
I’ve generated a huge amount of random data like so: which is a 100,000 by 1000 matrix(!) I’m generating new matrix where for each row, each column is true if the mean of all the columns beforehand (minus the expectancy of bernoulli RV with p=0.25) is greater than equal some epsilon. like so: After doing so I’m generating a 1-d
Delete values over the diagonal in a matrix with python
I have the next problem with a matrix in python and numpy given this matrix i want to obtain this: I was trying with np.diag() but doesnt works Thanks! Answer Use np.tril(a) to extract the lower triangular matrix. Refer this : https://docs.scipy.org/doc/numpy/reference/generated/numpy.tril.html
How to remove NaN on CSV?
I have a .csv file of a table consisting of 12 col and 30k rows. One of the col is ‘mentions’, some of the data are empty (NaN). I am trying to remove all the rows where mentions = NaN. I don’t want to fill it with new data. I just wanna remove those rows so they wont be part
Taking the min value of N last days
I have this data frame: I want to show the min value of n last days (say, n = 4), using Date column, excluding the value of current day. A similar solution has provided by jezrael. (That one calculates the mean, and not min.) Expected result: Answer Use similar solution like @Chris with custom lambda function in GroupBy.apply and last
Efficiently compare running total for month to total for month
I have a dataframe (df). It contains predicted daily data from a model, up until the end of 2020. As each day passes in the year, actual and id data is added to the row. There are multiple names for each day I want to add an additional column named payout. The payout should be 0 unless the sum of