Typeerror unsupported format string passed to numpy.ndarray.__format__

Typeerror: unsupported format string passed to numpy.ndarray.__format__

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Did you encounter Typeerror: unsupported format string passed to numpy.ndarray.__format?

Well, this error is not uncommon when working on developing a program.

In this guide, you will know what this error means, its causes, and solutions to fix this error quickly.

Let’s start!

What is typeerror: unsupported format string passed to numpy.ndarray._format__?

The Typeerror: unsupported format string passed to numpy.ndarray.__format occurs when we format the numpy array using the unsupported format string.

The format string could be any string that specifies how to format the data in an array.

This error can happen for a few reasons:

  • Incorrect format string
  • Invalid array type
  • Incompatible array shapes

How this error unsupported format string passed to numpy.ndarray.__format occur?

Here’s an example of code that can raise the “TypeError: unsupported format string passed to numpy.ndarray.format”

import numpy as np

arr = np.array([1, 2, 3])
print(f"My array is: {arr:03.2f}")

How to fix typeerror: unsupported format string passed to numpy.ndarray.__format

Here’s how to fix this error with some example code:

Step 1: Identify the issue

The first step to fix the error is to identify the exact format string that is causing the error.

For instance, you might have something like this:

import numpy as np

arr = np.array([1, 2, 3])
print(f"My array is: {arr:03.2f}")

In this example code, we’re trying to format the NumPy array using a floating-point format specifier with two decimal places…

Even though the array contains integers.

This will raise the “unsupported format string” error.

Step 2: Choose a compatible format specifier

To fix this error, you need to choose a format specifier that is compatible with the data type of the array.

For instance, if the array contains integers…

You can use the “d” format specifier for integers:

import numpy as np

arr = np.array([1, 2, 3])
print(f"My array is: {arr:d}")

In this example, we’re using the “d” format specifier for integers, which is compatible with the data type of the NumPy array.

Step 3: Test and adjust as needed

Once you’ve chosen a compatible format specifier, test your code to make sure it’s working as expected.

If you still encounter errors, make sure to adjust your format specifier as needed until you get the desired output.

Here’s a modified example of the previous code that uses the compatible format specifier and should run without errors:

import numpy as np

arr = np.array([1, 2, 3])
print(f"My array is: {arr:d}")

Output:

My array is: [1 2 3]

By following these steps, you should be able to fix the “unsupported format string” error in your NumPy code.

Conclusion

In conclusion, the Typeerror: unsupported format string passed to numpy.ndarray.format error can be resolved by identifying issues, choosing compatible format specifiers, and testing and adjusting as needed.

We hope that this guide has helped you resolve this error and get back to coding.

If you are finding solutions to some errors you might encounter we also have Typeerror: nonetype object is not callable.

Thank you for reading!