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

Borislav Hadzhiev

Last updated: Apr 11, 2024

Reading timeยท3 min

**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

`import numpy as np # โ๏ธ TypeError: Field elements must be 2- or 3-tuples, got '1' arr = np.array([2, 4, 6], [1, 3, 5])`

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

`import numpy as np arr = np.array([[2, 4, 6], [1, 3, 5]]) # [[2 4 6] # [1 3 5]] print(arr)`

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

`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

`import numpy as np arr = np.array([1, 3, 5, 7, 9, 11]) print(arr) # ๐๏ธ [ 1 3 5 7 9 11]`

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

`import numpy as np arr = np.array(123) print(arr) # ๐๏ธ 123 print(type(arr)) # ๐๏ธ <class 'numpy.ndarray'>`

The second argument the `numpy.array()`

method takes is the
dtype (data
type).

main.py

`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) # ๐๏ธ float64`

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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