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Getting error: ufunc 'subtract' did not contain a loop with signature matching types dtype('<U32') dtype('<U32') dtype('<U32')

I'm getting the error I stated in the title on my machine learning project. I'm following a guide on the internet . here's the parts that I'm getting the error:

def euclideanDistance(instance1, instance2, length):
    distance = 0
    for x in range(length):
        distance += pow((instance1[x] - instance2[x]), 2)
    return math.sqrt(distance)
def getNeighbors(trainingSet, testInstance, k):
    distances = []
    length = len(testInstance)-1
    for x in range(len(trainingSet)):
        dist = euclideanDistance(testInstance, trainingSet[x], length)
        distances.append((trainingSet[x], dist))
    distances.sort(key=operator.itemgetter(1))
    neighbors = []
    for x in range(k):
        neighbors.append(distances[x][0])
    return neighbors
neighbors = getNeighbors(training_feature_list, test_feature_list, 3)
print(neighbors)
I've looked around the internet about this question and noticed that many people asked this before but as I understand, the problem emerges from trying to use ufunc on different types of variables. But my training_feature_list and test_feature_list are similar. 
train set goes like [['5.1' '0.2']['4.9' '0.2']...(30 rows) 
test set goes like [['4.8' '0.2']['5.4' '0.4']...(20 rows).
I'd be so glad if anyone could briefly explain why this problem emerges (because I probably didn't understand it well) and how to fix it.
thanks in advance
If your lists really look like [['5.1' '0.2']['4.9' '0.2']... , then the error is probably caused by the fact that you are trying to subtract one string from another as '5.1' is a string, while 5.1 (which you prbably want) is a floating point number.
If that is not the case than another possible cause for the error (although I would expect a different one) is that you are passing lists instead of numpy arrays, which you should preferably do for calculations, as you can not just subtract one list from another.
                I'm pretty sure that they're both numpy arrays so it shouldn't be second case. how do I make sure that I handle my numpy arrays as floats instead of strings if it's the case 1? (because as I know default data type is float on numpy)
– Emre Unsal
                Feb 20, 2019 at 15:10
                I found it, yes you were right from the beginning. I was handling my arrays as strings because when I first created them, they had their labels in each row so it probably got created as string array. using x.astype saved me.
– Emre Unsal
                Feb 20, 2019 at 15:21
                Case one is just because of how you wrote the example of your lists, if they come out of some numpy calculation, then they should already be floats.
– trikPu
                Feb 20, 2019 at 15:22
        
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