Pip Installing and Importing Numpy

Quick reference

• 00:05 Okay, so we've got the main tools that we need installed.
• 00:08 We've got our Git Bash terminal, we've got our Jupyter Notebook set up, and
• 00:11 of course, we installed Python.
• 00:13 Now it's time to switch gears and install the first main data analysis tool that
• 00:18 we're going to use, and that is NumPy.
• 00:20 NumPy stands for numerical Python.
• 00:22 We'll talk about what it is, and how to use it in the next video.
• 00:26 In this video, we just want to install it and get it ready.
• 00:28 So, up until now we've downloaded things from websites like Python and
• 00:33 from the Git Bash terminal.
• 00:34 From now on, we're going to install things from the terminal like we did in the last
• 00:38 video with the Jupyter Notebooks.
• 00:39 And, NumPy is the first and the main one of those that we're going to use.
• 00:41 Now, I will say before we get started,
• 00:44 that NumPy is going to do a lot of the heavy lifting of our data analysis.
• 00:48 It's not something that's incredibly interesting.
• 00:51 It works kind of behind the scenes to move data around.
• 00:54 And we'll talk about all this in the next video, but first we need to install it.
• 00:58 So let's head back over to our terminal.
• 01:00 And you'll see that our Jupyter Notebook is running.
• 01:03 So let's hit the Ctrl and the C key at the same time on our keyboard, and
• 01:08 you can see it's shutting down.
• 01:09 And so our Jupyter Notebook has been turned off.
• 01:11 And it's kind of interesting to see if we head back over to our web browser, you see
• 01:15 we get this error, connection has failed, and our notebook doesn't work anymore.
• 01:19 And that's because it has to keep running in the terminal in order for
• 01:22 the Jupyter Notebook to work.
• 01:24 And we just turned it off in the terminal, so
• 01:25 it's turned off in the web browser as well.
• 01:28 So that's kind of interesting.
• 01:29 So I can go ahead and clear the screen if I want.
• 01:32 Now let's pip install NumPy.
• 01:34 And to do that, we just type in pip install.
• 01:37 And PIP, if you're not familiar, just stands for
• 01:39 the Python Installation Program, PIP.
• 01:41 And all it does is it installs Python modules and
• 01:44 tools that we're going to need for Python.
• 01:47 So pip install numpy.
• 01:49 And that's just NumPy, Numerical Python.
• 01:53 And when we do, it's collecting numpy, installing,
• 01:58 and should just take a couple of seconds, and boom we're done.
• 02:02 Now we can confirm that, if we want, by typing pip freeze.
• 02:06 And, remember, when we install Jupyter Notebooks, we install all of this stuff.
• 02:09 So we're going to have to kind of come through here and look.
• 02:11 And it should be In alphabetical order.
• 02:13 So just come down to the end section, and
• 02:16 then we see numpy 1.18.1 has been installed.
• 02:20 Now, if that's a different version by the time you watch this, no big deal,
• 02:23 just as long as it's the latest version, and
• 02:25 we can assume that it was the latest version because pip install always
• 02:29 installs the latest version unless you specify some other version to install.
• 02:32 So we can go ahead and clear the screen now.
• 02:35 And now we need to run our Jupyter Notebook one more time.
• 02:38 So I'm just hitting the up arrow key on my keyboard to sort of cycle through previous
• 02:42 commands that we've just done.
• 02:44 And we can come back to our Jupyter Notebook command, and I can hit Enter, and
• 02:48 boom that fires back up.
• 02:50 And you can see our screen has come back up.
• 02:53 I'm just going to come back over to this one, and hit Reload here.
• 02:57 And you'll notice this URL, I didn't really mention this in the last video,
• 03:00 but this is where we're going to be working from now on.
• 03:02 On this localhost:888/notebooks/ whatever the name of our notebook is.
• 03:09 And remember, we called ours data.
• 03:11 And 888 is just a port number that Jupyter Notebooks runs on.
• 03:16 And we don't really care what that means, it's just sort of interesting to note.
• 03:19 And then, in the future, to use our Jupyter Notebooks, we just run that
• 03:23 command that we just did in the terminal, and this jumps up, it fires up for us.
• 03:27 Or we could just open a web browser ourselves, manually, and type this in,
• 03:31 and that would work as well.
• 03:32 So, okay, let me get rid of some of this stuff here and
• 03:38 sort of start over with a fresh notebook.
• 03:41 So we've got a bunch of blank cells here.
• 03:43 Now we've installed NumPy.
• 03:45 But from now on, if we want to actually use NumPy,
• 03:49 we need to specify that right up here in our Jupyter Notebook.
• 03:53 And it doesn't have to be on the very top line like this, but
• 03:56 I like to put it there just because it's nice and clean that way.
• 03:59 But on any cell, really, you can put this command in.
• 04:03 And the command is import numpy as np, and then Shift Enter to run that.
• 04:10 And now we're good to go.
• 04:11 Now we can use NumPy in our Jupyter Notebook, as long as this
• 04:16 notebook is open, if we open a different notebook, we'll have to import this again.
• 04:20 But as long as we're using this data notebook that we created,
• 04:23 we can use NumPy.
• 04:24 And, like I said,
• 04:25 we're going to talk about in the next video exactly how to use this.
• 04:28 But the reason why we put this as np, so
• 04:32 that we can create a NumPy instance just by, from now on, calling np.
• 04:37 So we can go np., something, and we can do it.
• 04:42 You could name this anything you want up here.
• 04:44 You don't have to call this np.
• 04:46 You could call it jp, right?
• 04:49 You could call it hello, right?
• 04:51 But the convention is to call it np, is short for NumPy.
• 04:54 And it also makes it easier to retype it in, from time to time,
• 04:58 as we run NumPy functions and things going forward.
• 05:02 So that's all there is to installing NumPy.
• 05:04 Now we can use NumPy.
• 05:05 In the next video, I'll tell you sort of what NumPy is, how to use it,
• 05:09 why it's important, and we'll start actually doing some data analysis stuff,
• 05:13 and that'll be coming up in the next video.

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