NumPy float types: a demonstration of precision

The different NumPy float types allow us to store floats in different precision, dependent on the number of bits we allow the float to use. The larger the number of allowed bits, the more precision our array’s elements will have. E.g., np.float16 will use 16 bits (two bytes), while np.float64 takes up 64 bits (8 bytes).

Increased precision comes at the expense of memory and performance. Still, the rule of thumb is to err on the safe side and use np.float64 by default unless you have a good reason to use something else. E.g., if you can spare some precision and performance and memory usage are of the essence, use something smaller.

Edit and run this Python 3 example code

This code is editable and runnable. You can run "NumPy float types: a demonstration of precision" by pressing the run button. It will be executed in our backend and the result (stdout and stderr) is displayed in addition tabs.

Share this crumb (NumPy float types: a demonstration of precision) with your friends and colleagues to help them learn more about Python 3 programming.

Twitter, Facebook, LinkedIn

On Twitter, Facebook, and LinkedIn, simply paste the URL in your post and watch the magic unfold.

IFRAME

If you want to embed the crumb in an iframe, use the following code:

oEmbed (WordPress)

We support oEmbed, but most sites use allowlisting. On WordPress, oEmbed is supported out of the box, but see the note below.

If you plan to use crumb.sh heavily on Wordpress, you can use the following PHP code to allowlist our site and unlock all the functionalities of our crumbs:
wp_oembed_add_provider( 'https://crumb.sh/*', 'https://crumb.sh/oembed/' );

Embed.ly

Embed.ly is a service that allows you to embed content from other sites. We will request to be added to the list of trusted sites once we're out of beta.

NumPy float types: a demonstration of precision (Python 3 )