This post shows you how to use arrays in Python and why this data structure is so useful. A foundational skill for data science, coding, and more!

Consider the following Python code that generates a three-dimensional array. This array has 1,000 elements. Imagine that this array is a cube as shown blow. np.random.seed (7) a = np.random.randn (10, ...

Arrays are super useful. If you want even more details about python and arrays - this is a very useful site from Cornell. My python-foo will probably never catch up with The Virtuosi.

Im guessing this is built into the language, but I can't seem to find anything on it, and I'm just trying to get it done, so here I am to ask. Have a nested array that my function is returning ...

NumPy is known for being fast, but could it go even faster? Here’s how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users a wickedly fast library for working with ...

Let's imagine I have an array called thing. Before I start writing the code that will work on the array, I probably want to do the following: The good news is that python and numpy give you powerful ...

Given a binary array, find the maximum number of consecutive 1s in this array. ## Python Booleans as Numbers: Booleans are considered a numeric type in Python. All numbers except '0' are True and '0' ...