Name: 相関表の可視化 - PythonとPandasによるデータ分析 p.4 (Visualizing Correlation Table - Data Analysis with Python and Pandas p.4)
Uploaded: 2021-01-14T12:27:44.000Z
Duration: 20 min 39 s
Description: VoiceTubeの動画で発音を聞きながら英語表現を覚えよう！学べる英語：

未来進行形

And welcome to part four of the data science and in data analysis with python and pandas tutorial Siri's in this video, we're gonna be continuing off of the last video where we got our basic correlation table.

And what we want to do in this video is focus on visualizing that correlation table and some of the other things things that are gonna come along with doing that.

So to begin, let's just get basically where we were so important.

Pandas as PT important numb pie as np and at least two star P don't read C S V and we could do data sets men wage dot C s V and then we want to do, like that act min wage in that loop.

I think it would be this loop here, right?

This one I don't want to Ah, yeah, that was all just confirmation of what was the problem.

Copy that says from the previous tutorial.

Um and then we want to set the min wage core here.

Eso this big yet this becomes our min wage core.

Terminal command prompt Pip, install Matt, plot live.

But if you've been following the Siri's you've already done that would be a hard syriza jumpin randomly.

So I'm gonna assume everybody's cut the things we've installed.

So for so first of all, with map hot lib, we just We're just gonna do import Matt, Matt plot lib dot Pipe lot as p l t.

And then we can do peel tea dot matt show and we're just gonna mat show that data frame.

We probably have to call P l t a show in here.

Unfortunately, as you'll find with is the case with Matt plot lib all the time.

You really are gonna likely need to do a lot of customization.

So if you want to come into your groups, I don't even know how to navigate my own side.

Dave is coming here, and you can learn all this stuff about customizing, Matt.

Uh, I'm not gonna spend too much time on that, but we are going to do at least some customization here just to make this work because I feel like one.

Well, right out of the gate, I would think.

We could say labels equals and then just duelist comprehension.

So see, foresee, in men Wage corps, I see the issue there anyway, columns and then fix this.

And then let's just do like, the 1st 2 letters, so that would be like the first.

Okay, so So this will be like, you know, if it's Alabama, a Michigan m I, and so on.

So we could do something really basic like that.

And then let's fix some of the other things Eso fig equals peel tea dot figure, and then figs size will be.

So if you want to start customizing Matt Pot lib, you have to kind of even pull it out even further.

So first of all we've pulled, we stopped you.

Well, in this case, we actually didn't do like dot values or anything.

We just passed the entire data frame, and it works, so well, that's great.

Uh, but then if you want to start modifying things, you can't modify a p l t.

Well, to have an axes, you have to have a subplot to have a supply you need to figure So So we have our figure.

So we're gonna say axes, Eagles fig dot ad subplot.

And in here, I'm going to pass 111 What this means is, this is a one by one.

All the subplots on the figure are in a one by one grid, and this is number one.

Um, so this just means there's gonna be one graph now, Uh, what we want to do is a ex dot matt show, and we want a mat show men wage core.

But then we also want to change the sea map.

That's that's Ah, color map and the sea map we want to use.

Here's p lt dot CME CME dot uh, red, yellow, green.

Ah, we We could just go ahead and just do this real quick and boom.

And, um, but our ticks aren't really labeled yet, so that's the next thing we want to do.

So the next thing we want to say is a ex dot set underscore, er ah, set underscored Why tick labels And we want to pass labels.

And then we'll do the exact same thing here.

And we we probably want to do that before the show.

So we have the labels here, but we don't have all of them so mad.

Plot live is kind of truncating them because it doesn't want to put too many labels on axes, Make it hard to read.

If these were numbers, then this would be probably descriptive enough for us, but they're not numbers, and it's not.

So what we need to do is tell Matt Pot Lid.

So the next thing we were we can do here is we can actually just tell Matt Pot lib, show all of the labels and the way that we could do as a x dot set, underscore and the ex ticks.

And then we use numb pied up range, and that will be for the len of labels labels.

And we'll do the exact same thing for wife X y boom.

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相関表の可視化 - PythonとPandasによるデータ分析 p.4 (Visualizing Correlation Table - Data Analysis with Python and Pandas p.4)

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