1
00:00:06,830 --> 00:00:11,760
So, before we can plot something which just need to have a little bit of data

2
00:00:11,760 --> 00:00:14,160
that's very easy to create.

3
00:00:14,160 --> 00:00:18,130
That is a rnorm function which samples from a normal distribution.

4
00:00:18,130 --> 00:00:24,590
So by default we have mean zero and standard deviation one so let's sample hundred points here.

5
00:00:24,600 --> 00:00:29,630
And let's do the same for y.

6
00:00:29,630 --> 00:00:41,560
and actually increase the standard deviation a bit.

7
00:00:41,560 --> 00:00:47,530
And now we create a data frame and it’s data.frame and you say just (x,y).

8
00:00:47,530 --> 00:00:51,960
If you now view this data frame we see here

9
00:00:51,960 --> 00:00:54,130
that you have the two columns

10
00:00:54,130 --> 00:00:56,290
And you see here the numbers are a bit higher

11
00:00:56,300 --> 00:00:59,830
because the standard deviation is higher.

12
00:00:59,830 --> 00:01:01,160
And now we can plot it.

13
00:01:01,160 --> 00:01:10,090
So we have to import a library (ggplot2).

14
00:01:10,100 --> 00:01:17,130
And then we can actually plot it so we say ggplot

15
00:01:17,130 --> 00:01:21,130
plus parameters of course the data frame

16
00:01:21,130 --> 00:01:29,330
And I won't go into detail here

17
00:01:29,330 --> 00:01:32,360
because ggplot is relatively complex

18
00:01:32,360 --> 00:01:36,360
but a very, very powerful library.

19
00:01:36,360 --> 00:01:46,590
We are basically saying here that we want to draw points.

20
00:01:46,600 --> 00:01:53,100
So you see here that on the x-axis and the y-axis

21
00:01:53,100 --> 00:01:55,100
we are just plotting those points.

22
00:01:55,100 --> 00:02:00,160
Okay, now let's actually plot something more nicely.

23
00:02:00,160 --> 00:02:05,730
So there is a data frame build into R which is called mtcars.

24
00:02:05,730 --> 00:02:11,090
And it has different types of cars, and their properties.

25
00:02:11,100 --> 00:02:14,630
So it's a nice data set to play with.

26
00:02:14,630 --> 00:02:18,760
And as I said ggplot2 is relatively complex

27
00:02:18,760 --> 00:02:22,760
so I'm just copy-pasting the code

28
00:02:22,760 --> 00:02:26,760
for plotting something really nicely.

29
00:02:26,760 --> 00:02:37,390
So this is basically the weight of the car over the mileage.

30
00:02:37,400 --> 00:02:41,400
And you see here the more heavy the car gets,

31
00:02:41,400 --> 00:02:43,130
the less is the mileage.

32
00:02:43,130 --> 00:02:47,030
And in addition to that you are also drawing

33
00:02:47,030 --> 00:02:51,990
a regression line and also a confidence interval or a standard deviation.

34
00:02:52,000 --> 00:02:55,760
So that's pretty cool with only two lines of code

35
00:02:55,760 --> 00:02:59,760
You can create plots which you find

36
00:02:59,760 --> 00:03:03,730
in the best (scientific) publications because the best publishers

37
00:03:03,730 --> 00:03:08,860
often use R and ggplot2 for creating that plot.

38
00:03:08,860 --> 00:03:10,160
Okay, I hope this helps.

39
00:03:10,160 --> 00:03:11,530
If you have any further questions,

40
00:03:11,530 --> 00:03:14,660
please let me know in the Comments section below.

41
00:03:14,660 --> 00:03:17,030
And have a nice day. Bye!