Скачать с ютуб How to easily load, analyse and graph data in R в хорошем качестве

How to easily load, analyse and graph data in R

In this video I show you how to do load and analyze data in R. Then I show you how to build quick visuals and gain quick insights. For this analysis we will use a really interesting data set - sample set of YouTube channel data. I show you how to do several graphs really fast with ggplot based on this data. And then you'll see the relationship between the age of the account, the number of videos and the number of subscribers and/or total views. You'll also see how I use snippets of code. Once you have these snippets like I show you here all you have to do is load in your data set, look at the data or read the column names in with COLNAMES(), replace the x and y coordinates or columns and maybe add an extra measure for extra differentiation by color. Then you just highlight the piece of code you want hold on your control button and enter to run it. I do all of my coding for R inside of RStudio as the debugging capabilities and multiple screens just make it so much better than using straight R. Once you've found some data sets that means something to you or that you find interesting and started using GG plot a little bit you will find this both interesting and very rewarding as your data now takes on new visuals and you will be able to spot trends and insights much faster. Also, what's really neat is you just need to create a document with all your snippets of code in it, then when you need them its a simple look up under ggplot, Dplyer, etc. It'll make coding much easier, faster and more enjoyable. I hope you found this video interesting and informational. The data once visualized with ggplot shows exactly what we would expect - channels with more videos get more views and more subscribers. As the channels get more recent they have fewer subscribers and fewer views but not always. And the vast majority of channels have probably 200 or less videos. The bulk of the views are made up by the top 1% of channels maybe. I will let you make your own insights on this data. Thank you for watching. Please subscribe , like and and share so you will get notified of all my other great videos I have coming out! Thanks again and God bless!