# NumPy Review (Optional)

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Happy Pythoning!

One of the many dependencies of `matplotlib` is called `numpy`, which is short for “numerical Python.” It’s a very popular library used for scientific computing.

`numpy` provides objects that can represent more complex data than the built-in data types in Python can. It also provides efficient yet advanced mathematical operations you can perform on this data.

In this course, you’ll use `numpy` mostly to generate pseudorandom numbers, which you’ll then store in multidimensional arrays.

Anonymous

I think you meant np.column_stack((a,b))

Austin Cepalia RP Team

That’s correct. I’ll have this video updated shortly

Thanks very much Austin, your tutorial is helpful to many, perticualary to those who are very confused because of too much of different tools in python for doing the same thing. The zen of python syas “There should be one– and preferably only one –obvious way to do it.” , if that is so why there are so many packages for doing the same stuff, example: matplotlib (the oop version, and the non oop version), altaire, bokeh, ggplot, seaboarn, pandas plot, plotly and so on…, I mean I was very confused until I find this tutorial and the other one in realpython which tells how matplotlib also exists in stateless and stateful versions, Really it saved me. But I wonder why, there are so many libraries for doing the same thing, its just really frustating and not one of them is easy to learn. I am really thankful that you made this tutorial.

Austin Cepalia RP Team

@Pradeep Kumar thanks for the kind words, I’m glad the course was useful to you. You’re absolutely right about the zen of Python. I’m not entirely sure if this is the best answer to your question, but if I had to guess I would say that there exit so many libraries, frameworks, and packages because the “best” way of doing something for one person might not be the best way of doing it for someone else. It’s like asking why there are so many different cars; they all get you from place A to place B, but some are faster on road, some can carry a heavy load, and some just look fancy! It’s a matter of personal preference. Likewise, the different plotting libraries accomplish basically the same thing but in radically different ways. They also have different features and capabilities.