Numpy is a python package that allows you to create a numpy array and perform mathematical calculations. While using the Numpy package you may use some functions that are not defined in the numpy and it encounters attributeError. In this tutorial, you will learn how to solve the AttributeError numpy.ndarray object has no attribute remove in a very simple way.
The main cause for getting this error is that you must be using the wrong function. The remove() function is not provided by the numpy python package. It is used by the list.
If you use dir(numpy_array) then you will see all the functions and attribute provide by the numpy array. Clearly remove() function is not present here.
dir(numpy_array)Output
['T', '__abs__', '__add__', '__and__', '__array__', '__array_finalize__', '__array_function__', '__array_interface__', '__array_prepare__', '__array_priority__', '__array_struct__', '__array_ufunc__', '__array_wrap__', '__bool__', '__class__', '__complex__', '__contains__', '__copy__', '__deepcopy__', '__delattr__', '__delitem__', '__dir__', '__divmod__', '__doc__', '__eq__', '__float__', '__floordiv__', '__format__', '__ge__', '__getattribute__', '__getitem__', '__gt__', '__hash__', '__iadd__', '__iand__', '__ifloordiv__', '__ilshift__', '__imatmul__', '__imod__', '__imul__', '__index__', '__init__', '__init_subclass__', '__int__', '__invert__', '__ior__', '__ipow__', '__irshift__', '__isub__', '__iter__', '__itruediv__', '__ixor__', '__le__', '__len__', '__lshift__', '__lt__', '__matmul__', '__mod__', '__mul__', '__ne__', '__neg__', '__new__', '__or__', '__pos__', '__pow__', '__radd__', '__rand__', '__rdivmod__', '__reduce__', '__reduce_ex__', '__repr__', '__rfloordiv__', '__rlshift__', '__rmatmul__', '__rmod__', '__rmul__', '__ror__', '__rpow__', '__rrshift__', '__rshift__', '__rsub__', '__rtruediv__', '__rxor__', '__setattr__', '__setitem__', '__setstate__', '__sizeof__', '__str__', '__sub__', '__subclasshook__', '__truediv__', '__xor__', 'all', 'any', 'argmax', 'argmin', 'argpartition', 'argsort', 'astype', 'base', 'byteswap', 'choose', 'clip', 'compress', 'conj', 'conjugate', 'copy', 'ctypes', 'cumprod', 'cumsum', 'data', 'diagonal', 'dot', 'dtype', 'dump', 'dumps', 'fill', 'flags', 'flat', 'flatten', 'getfield', 'imag', 'item', 'itemset', 'itemsize', 'max', 'mean', 'min', 'nbytes', 'ndim', 'newbyteorder', 'nonzero', 'partition', 'prod', 'ptp', 'put', 'ravel', 'real', 'repeat', 'reshape', 'resize', 'round', 'searchsorted', 'setfield', 'setflags', 'shape', 'size', 'sort', 'squeeze', 'std', 'strides', 'sum', 'swapaxes', 'take', 'tobytes', 'tofile', 'tolist', 'tostring', 'trace', 'transpose', 'var', 'view']
You will get the numpy.ndarray object has no attribute remove error when you will run the below lines of code.
import numpy as np
numpy_array = np.array([10,20,30,40,50])
numpy_array.remove(10)Output
The solution to this attributeError is very simple. You don’t have to use the remove() function on the numpy array. This function is used on the list. However, if you want to use it then first convert the numpy array to a list and then use the remove() function. Lastly, you can again convert the list back to numpy array.
Execute the below lines of code
import numpy as np
numpy_array = np.array([10,20,30,40,50])
array_to_list= numpy_array.tolist()
array_to_list.remove(10)
final_numpy_array = np.asarray(array_to_list)
final_numpy_arrayOutput
You can see you are not getting any AttributeError when you run the above lines of code.
Mose of cases coders gets attributeerror when they apply a function that is not in the packages. This attributeError is also the same case. If you are getting the numpy.ndarray object has no attribute remove error then the above solution will solve this.
I hope you have liked this tutorial. If you are still getting this error or want to add more solutions to it then you can contact us for more help.