Arrays in Python give you a huge amount of flexibility for storing, organizing, and accessing data. This is crucial, not least because of Python’s popularity for use in data science.

These days a printer — especially one at home — is likely to spray ink out of nozzles. It is getting harder to find home laser printers, and earlier printer technologies such as dot mat… ...

It is possible to use generic Python objects as the dtype for a NumPy array, but if you do this, you’ll get no better performance with NumPy than you would with Python generally.