Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated:
1
00:00:05,560 --> 00:00:06,880
Welcome to this section.
2
00:00:07,240 --> 00:00:11,680
In this section, we're going to now move into looking at our graphical views of our data.
3
00:00:11,770 --> 00:00:16,059
So, so far, we've been looking at tables and we've been looking at text views of the data.
4
00:00:16,329 --> 00:00:20,350
With graphical views, we're able to actually be able to see the patterns within the data.
5
00:00:20,350 --> 00:00:24,880
So we get a different visual representation of the data and being able to understand it.
6
00:00:25,300 --> 00:00:27,170
We're going to start with the clustered column graph.
7
00:00:27,170 --> 00:00:28,300
We're going to see the common bar.
8
00:00:28,300 --> 00:00:32,830
Graphs are really great when we want to understand how big something is or how small something is,
9
00:00:33,220 --> 00:00:35,290
how much bigger one thing is than the other.
10
00:00:35,470 --> 00:00:39,700
So we're going to start with the clustered column, and then we're going to move into the 100% and the
11
00:00:39,700 --> 00:00:40,840
stacked column graph.
12
00:00:40,840 --> 00:00:45,700
And what we're going to see is the ability to be able to see how one item contributes to the other.
13
00:00:45,700 --> 00:00:49,370
So we're going to be able to see how these items are contributing to the total.
14
00:00:49,390 --> 00:00:51,900
Then we're going to move across to our trend graphs.
15
00:00:51,910 --> 00:00:56,530
So with our trend graphs, we've got a few graphs that we can be looking at, can look at our line graph
16
00:00:56,530 --> 00:00:57,700
or area graph.
17
00:00:57,850 --> 00:01:02,110
So our line graph gives us a representation of how data changes over time.
18
00:01:02,110 --> 00:01:04,629
And this is basically our trends that we're looking for.
19
00:01:04,780 --> 00:01:09,190
So line graphs are also great when you want to understand forecasting how the things move out into the
20
00:01:09,190 --> 00:01:11,050
future, we're going to see that area.
21
00:01:11,050 --> 00:01:15,670
Graphs give us very similar view to what line graphs do, but they're coloring in the area before.
22
00:01:15,670 --> 00:01:18,910
So they give us an ability to understand how big or how small something is.
23
00:01:19,240 --> 00:01:23,860
Then I'm going to look at a your visualization for the ribbon graph, which actually gives us the view
24
00:01:23,860 --> 00:01:25,930
of being able to see how items are ranked.
25
00:01:25,930 --> 00:01:30,900
So you can see which item is biggest by following how it is ranked throughout the graph.
26
00:01:30,910 --> 00:01:33,010
But you'll see in the lesson how we do this.
27
00:01:33,010 --> 00:01:35,140
Then we're going to look at some additional graphs.
28
00:01:35,140 --> 00:01:40,510
When we look at our pie graph, look at a tree graph, and these will give you different visual representations.
29
00:01:40,630 --> 00:01:44,440
Also going to be looking at a scatterplot and the bubble plot which could allow us to be able to see
30
00:01:44,440 --> 00:01:46,120
correlations between data.
31
00:01:46,210 --> 00:01:50,650
And we're going to be looking at the decomposition tree, which allows us to see how the components
32
00:01:50,650 --> 00:01:52,540
of an item make something up.
33
00:01:53,050 --> 00:01:56,410
But yet again, let's jump into the lessons and I will see you there.
3553
Can't find what you're looking for?
Get subtitles in any language from opensubtitles.com, and translate them here.