Review of Views and Copies

Review of Views and Copies#

The last reading on views and copies covered a lot, so here’s a brief summary of the key takeaways:

  • When an array is subset using simple indexing (i.e., by passing an index or range of indices denoted with a :), the result is just a reference to the original array’s data. This is called a view.

  • Because the view created through simple indexing is sharing data with the original array, changes to one will also impact the other.

  • While we often only refer to the newly created array as a “view,” the relationship between the original array and the view is symmetric, meaning changes to either may impact the other (if the change impacts an entry that is shared).

  • When you create a subset using fancy indexing or Boolean subsetting with a logical test, numpy will create a copy, not a view.

  • A view can be converted into a copy with .copy().

  • Creating a view is much faster than creating a copy; with that said, for most sizes of datasets you will encounter in life, both are exceedingly fast.