<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>numpy on Tom Roth</title><link>https://tomroth.dev/tags/numpy/</link><description>Recent content in numpy on Tom Roth</description><generator>Hugo -- gohugo.io</generator><language>en</language><lastBuildDate>Sun, 25 Jun 2017 00:00:00 +0000</lastBuildDate><atom:link href="https://tomroth.dev/tags/numpy/index.xml" rel="self" type="application/rss+xml"/><item><title>44 Numpy Functions</title><link>https://tomroth.dev/numpy/</link><pubDate>Sun, 25 Jun 2017 00:00:00 +0000</pubDate><guid>https://tomroth.dev/numpy/</guid><description>Have you heard about the Python package numpy? Probably.
But maybe you&amp;rsquo;re looking for an easy reference of useful numpy functions. Maybe that&amp;rsquo;s why you&amp;rsquo;re here. Well, you&amp;rsquo;re in luck!
Get started by opening up a editor. First, we&amp;rsquo;ll import the numpy package: import numpy as np.
Now cast your eye over these functions. In no particular order:
np.__version__ | Return the version of numpy you have loaded. np.shape(x) | return the shape of an array x.</description></item></channel></rss>