1
00:00:04,500 --> 00:00:08,280
So we just made this
plot in ggplot2.

2
00:00:08,280 --> 00:00:10,070
When we compare it
back to the pie graph,

3
00:00:10,070 --> 00:00:14,050
the first thing I notice is that
now all the data is visible.

4
00:00:14,050 --> 00:00:15,840
We haven't lost
the small regions

5
00:00:15,840 --> 00:00:17,840
and we can read out
the exact share that

6
00:00:17,840 --> 00:00:20,940
comes from Africa, Oceania,
and the unknown or stateless

7
00:00:20,940 --> 00:00:23,400
column.

8
00:00:23,400 --> 00:00:26,660
I believe it is also easier
to compare the relative sizes

9
00:00:26,660 --> 00:00:29,530
of each region
because they're all

10
00:00:29,530 --> 00:00:31,520
put side by side
on a similar scale.

11
00:00:31,520 --> 00:00:33,150
There's no tricks,
or three dimensions,

12
00:00:33,150 --> 00:00:37,350
or colors to create
a perception issue.

13
00:00:37,350 --> 00:00:39,520
But, I will say that
something to consider

14
00:00:39,520 --> 00:00:43,020
is, for some people
and some applications,

15
00:00:43,020 --> 00:00:46,190
being not as visually
exciting is a negative.

16
00:00:46,190 --> 00:00:49,620
This plot, while very
readable and correct,

17
00:00:49,620 --> 00:00:51,620
is certainly a little bit dull.

18
00:00:51,620 --> 00:00:54,000
In some applications, this is
an important consideration.

19
00:00:56,790 --> 00:00:59,220
Now, wouldn't it be
interesting if we

20
00:00:59,220 --> 00:01:02,130
could plot this
data on a world map?

21
00:01:02,130 --> 00:01:04,000
It would be possible,
but a bit tedious

22
00:01:04,000 --> 00:01:05,950
to create because
we need to determine

23
00:01:05,950 --> 00:01:09,000
which country lies
in which region.

24
00:01:09,000 --> 00:01:11,530
Shading all countries in
a region of the same color

25
00:01:11,530 --> 00:01:13,560
might be misleading though.

26
00:01:13,560 --> 00:01:16,039
For example, countries
in Latin America

27
00:01:16,039 --> 00:01:19,440
will send students at
different rates, naturally.

28
00:01:19,440 --> 00:01:21,270
But, if we color them
all the same color,

29
00:01:21,270 --> 00:01:24,810
it kind of gives a
false impression.

30
00:01:24,810 --> 00:01:26,600
As it turns out, we
actually have access

31
00:01:26,600 --> 00:01:28,780
to per country data.

32
00:01:28,780 --> 00:01:30,560
So we will plot
that on a world map

33
00:01:30,560 --> 00:01:33,300
instead and see if it is an
effective way of communicating

34
00:01:33,300 --> 00:01:36,100
where students come from to MIT.