ValueError: setting an array element with a sequence. on data read from csv

Let's start from the beginning:

1. You seem to want to iterate through every line of your file to create an array. The iteration should be over range(0, len(data)), not range(0, len(data) - 1): the last element of the range is exclusive, so you are currently skipping the last line. In fact, you can write simply range(len(data)), or what is even more Pythonic, do

   for y in data:
       y = y[1:41]
   

2. Based on what comes later, you want the 40 elements of y starting with the second element. In that case y[1:41] is correct (you don't need the trailing :1). If you didn't mean to skip the first element, use y[0:40], or more Pythonically y[:40]. Remember that the indexing is zero-based and the stop index is exclusive.

3. Each element of your y list is not a number. It is a string, which you read from a file. Normally, you could convert it to a list of numbers using

   y = [float(x) for x in y]
   

   OR

   y = list(map(float, y))
   

   Your code is instead creating a nested list for each element, splitting it by its digits. Is this really what you intend? It certainly does not seem that way from the rest of the question.

4. create2Darray seems to expect a list of 4n numbers, and break it into a 2D list of size n-by-4. If you want to keep using pure Python at this point, you can shorten the code using range:

   def create2Darray(arr):
       return [arr[i:i + 4] for i in range(0, len(arr), 4)]
   

5. The result of the 2D operation is appended to a 3D list with label_data.append(y). Currently, because of the digit splitting, label_data is a 4D list with a ragged 4th dimension. It is pretty inefficient to append a list that way. You would do much better to have a small function containing the statements in the body of your for loop, and use that in a list comprehension.
6. Finally, you convert your 4D array (which should probably be 3D), into a numpy array. This operation fails because your numbers don't all have the same number of digits. Once you fix step #3, the error will go away. There still remains the question of why you want dtype=np.float when you explicitly converted everything to an int, but that is for you to figure out.
7. Don't forget to add a return value to getTrainingData!

TL;DR

The simplest thing you can really do though, is to do all the transformations after you convert the file to a 2D numpy array. Your program could be rewritten as

with open('data_more.csv', newline='') as file:
    reader = csv.reader(file)
    data = [float(x) for x in line[1:] for line in reader]
data = np.array(data).reshape(data.shape[0], -1, 4)

With a copy-n-paste from your link:

In [367]: txt="""frame_video_02_0.jpg,126,37,147,112,100,41,126,116,79,34,96,92,
     ...: 68,31,77,88,1
     ...: """
In [368]: txt=txt.splitlines()
In [369]: data =np.genfromtxt(txt, delimiter=',')

data is a 2d array of floats:

In [370]: data.shape
Out[370]: (3, 401)
In [371]: data[0,:10]
Out[371]: array([ nan, 126.,  37., 147., 112., 100.,  41., 126., 116.,  79.])

The first column is nan, because it's a text that can't be made into a float. I could remove it with data = data[:, 1:]

I can load the file names separately:

In [373]: labels = np.genfromtxt(txt, delimiter=',', usecols=[0],dtype=None,encoding=None)
In [374]: labels
Out[374]: 
array(['frame_video_02_0.jpg', 'frame_video_02_50.jpg',
       'frame_video_02_100.jpg'], dtype='<U22')

I haven't tried debug your code, though with a file like this, reading the numbers into a Python list of lists shouldn't be hard.