Placeholder Image

字幕表 動画を再生する

  • Okay, we covered the matrix arithmetic, which means the time has come to talk about some more data science oriented operations.

  • Cool.

  • I'm almost certain that if you have our studio open as you're going through the lessons, you will a grasp everything a lot better.

  • But that's a given and be Have The Matrix Don't Matt Data we created in the previous lesson loaded.

  • If you have started a new session and don't have the script from last time saved, I have entered the code.

  • We used this comment so few free to recreate the Matrix because that's what we'll be using in this lesson.

  • All right, so I have my matrix of us and worldwide box office.

  • Gross sings for the Matrix movie franchise, and I want to learn how much in total all three movies made at the box office, both around the world and in the U.

  • S.

  • On Lee.

  • Luckily, there is the simplest command in our that lets me do that.

  • It's called cold sums, and it returns to some for each calm in your data structure.

  • The only argument you need to pass is your data like this There these organisms of all values in Age of the Do Columns notice that the S for sums is capitalized.

  • Remember that our is case sensitive language.

  • If you don't use the proper capitalizations or won't know what you wanted to do, right, as you can probably guess, if there is a co sums, there will probably also be a row Sums function, just as it was with the call names and bro names and our bind and See Bint.

  • And there is Let's Try it out, even though it isn't too useful in our particular situation because one of our columns contains the worldwide box office figures and the other contains the US Cross, which is part of the worldwide statistic.

  • Nonetheless.

  • Now we have the total US and worldwide grosses for each movie in the trilogy.

  • Fantastic.

  • What if I wanted to know how much, on average, the movies made in the U.

  • S.

  • And across the globe?

  • Well, I can use the coal means function.

  • It works exactly like Qassams, but gives us the means.

  • Further columns in our data structure like this again be mindful of the capital M because our is case sensitive awesome.

  • We can also do row means and that will give us the averages for each row in the Matrix.

  • And there it is.

  • We can now find out the sums and the means for columns and Robin, a matrix that is super super useful when working with larger data, and you want to get a quick feel for what it has in store for you.

  • Often it will be useful to save this sums and averages.

  • You compute a separate rows and columns and add them to your data searcher.

  • Can you guess?

  • One way to do that, I'll give you a couple of seconds.

  • Of course, you can save each output as a vector and then simply bind what you need to displayed in The Matrix with our bind and see bind.

  • Let's try it out.

  • I will go back up and save the costumes and co means results into Victor's called Total and Average, and I will create a new matrix called matrix dot pre lim with our bind and stick the two new vectors to the bottom of my data.

  • And there you have it a nice and needs little matrix that tells a numbering from story.

  • Excellent.

  • Okay, let's rock it up here.

  • But before we go, I have one final question.

  • The blue pill are the red pill.

  • You take the blue pill, the story ends.

  • You wake up in your bed and believe whatever you want to believe.

  • You take the red pill, you stay in our Lent and I will show you how deep the rabbit hole goes.

  • Form or videos like this one, please subscribe.

Okay, we covered the matrix arithmetic, which means the time has come to talk about some more data science oriented operations.


動画の操作 ここで「動画」の調整と「字幕」の表示を設定することができます

B1 中級

データサイエンスと統計学。Rでの行列演算 (Data Science & Statistics: Matrix operations in R)

  • 3 0
    林宜悉 に公開 2021 年 01 月 14 日