TypeError: Field elements must be 2- or 3-tuples, got 1

# TypeError: Field elements must be 2- or 3-tuples, got 1

The NumPy error "TypeError: Field elements must be 2- or 3-tuples, got 1" occurs when you try to create a two-dimensional NumPy array incorrectly.

To solve the error, pass a two-dimensional array to the numpy.array() method.

Here is an example of how the error occurs.

main.py

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import numpy as np

# ⛔️ TypeError: Field elements must be 2- or 3-tuples, got '1'
arr = np.array([2, 4, 6], [1, 3, 5])

typeerror field elements must be 2 or 3 tuples got

We tried to create a two-dimensional NumPy array incorrectly which caused the error.

Notice that we passed 2 arrays as separate arguments to the numpy.array method.

To solve the error, use two sets of square brackets.

main.py

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import numpy as np

arr = np.array([[2, 4, 6], [1, 3, 5]])

# [[2 4 6]
#  [1 3 5]]
print(arr)

create two dimensional numpy array correctly

The code for this article is available on GitHub

We passed a single, two-dimensional list to the numpy.array() method to create a NumPy array.

We start with a set of square brackets and then specify the rows using sublists.

Make sure that the sublists contain the same number of elements, otherwise, you would get the Creating ndarray from ragged nested sequences is deprecated warning.

You can also pass a tuple containing the sublists as the first argument to numpy.array().

main.py

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import numpy as np

arr = np.array(([2, 4, 6], [1, 3, 5]))

# [[2 4 6]
#  [1 3 5]]
print(arr)

However, make sure to pass the collection of sublists as a single argument by wrapping them in curly braces [] or parentheses ().

If you want to create a one-dimensional array, pass a flat list to the numpy.array() method.

main.py

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import numpy as np


arr = np.array([1, 3, 5, 7, 9, 11])

print(arr)  # 👉️ [ 1  3  5  7  9 11]

creating a one dimensional numpy array

The code for this article is available on GitHub

The first argument the numpy.array method takes is an array-like object.

The argument can be:

an array
any object that exposes the array interface
an object whose __array__ method returns an array
any nested sequence

If the supplied value is a scalar, a 0-dimensional array containing the value is returned.

main.py

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import numpy as np

arr = np.array(123)

print(arr) # 👉️ 123
print(type(arr)) # 👉️ <class 'numpy.ndarray'>

The second argument the numpy.array() method takes is the dtype (data type).

main.py

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import numpy as np

arr = np.array([[1, 2, 3], [4, 5, 6]], dtype=float)

# [[1. 2. 3.]
#  [4. 5. 6.]]
print(arr)

print(arr.dtype)  # 👉️ float64

specify dtype argument explicitly

The code for this article is available on GitHub

The dtype argument represents the desired data type for the array.

If the argument isn't supplied, NumPy tries to use a default dtype that can represent the given values.

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TypeError: Field elements must be 2- or 3-tuples, got 1

# TypeError: Field elements must be 2- or 3-tuples, got 1

# Additional Resources

Borislav Hadzhiev