How to remove rows from numpy array if certain number of an element is present-CodePudding

I have a 2d numpy array that contains some numbers like:

data = 
[[1.1, 1.2, 1.3, 1.4],
[2.1, 2.2, 2.3, -1.0],
[-1.0, 3.2, 3.3, -1.0],
[-1.0, -1.0. -1.0, -1.0]]

I want to remove every row that contains the value -1.0 2 or more times, so I'm left with

data = 
[[1.1, 1.2, 1.3, 1.4],
[2.1, 2.2, 2.3, -1.0]]

I found this question which looks like it's very close to what I'm trying to do, but I can't quite figure out how I can rewrite that to fit my use case.

CodePudding user response：

You can easily do it with this piece of code:

new_data = data[(data == -1).sum(axis=1) < 2]

Result:

>>> new_data
array([[ 1.1,  1.2,  1.3,  1.4],
       [ 2.1,  2.2,  2.3, -1. ]])

CodePudding user response：

def remove_rows(data, threshold):
    mask = np.array([np.sum(row == -1) < threshold for row in data])
    return data[mask]

This function will return a new array with no rows having -1's more than or equal to the threshold

You need to pass in a Numpy array for it to work.