So for this section, we're going to be talking about data visualization, making charts, diagrams, figures, out of data. They say that a picture's worth 1000 words and the truth is that if you can display your data and your information using figures and charts, you can show a reader, or you can engage in a client, or a professor during a presentation if you will, in a very quick and efficient way. So we're going to be going through a couple of different ways to visualize your data. Here I've downloaded some information from the Federal Reserve Economic Database from the St. Louis Fed, and what we have here is a real gross domestic product from 2000 all the way through 2016. So we're going to be doing a couple of different charts using this data. First, we're going to do a scatter plot using the data and I'll show you how to display this information, and then we can include lines. I'm going to highlight the information here. This is the real GDP growth from the preceding quarters here, and I'm going to insert into a scatter plot, okay, and then I'm going to push this into its own sheet on Excel sheet. Okay. So when you look at it like this, it's very difficult to gauge any kind of information about what's happening with real GDP, right. It's a very messy chart. All right, I wouldn't recommend using a scatter plot for these data. But I wanted to show you how you can display the data, and then I also wanted to show you one of the pitfalls of just sort of grabbing Excel, highlighting data, and just making charts, is that sometimes we forget that we're supposed to be telling a story, and some charts, or some figures, some different diagrams, tell story more efficiently than others. Here, if you were to put this information into a report, it would in fact show the percent change in real GDP from the previous period, but your reader would have a difficult time understanding the trends here. Let's go back to these data here and I'm going to create a bar chart using just some of the data. So I'm going to highlight the information from 2004 through 2016, and I'm going to insert a bar chart here. Again, I'm going to move this to its own area, a new sheet here. Okay. Now, these data are displayed with a bar chart that include the dates on the x axis, okay. If I include a title here, which is the percentage change in real GDP from previous quarter. So now this is easier for your reader to identify what's going on. The height of the bar corresponds to some percentage change on the y axis, and the x axis identifies different periods, and so we have the year, and the month, the day, displayed on the x-axis. Now, your reader can see or if you're doing a presentation, they can see the trend of what's going on with the real GDP from the previous quarter. Now, of course when you looking at this information, it's much easier in this format to see where the significant changes are occurring right. If I insert a shape just to highlight what's going on here, you'll notice that look this whole area right here, identifies decreases, like the percentage change from the previous quarter is negative. So real GDP is decreasing, and it wouldn't be surprising to identify that this is the period of our last economic recession. This is one of the valuable tools that we have in data visualization, is that we can grab data and we can explain the data using a figure, and tell a very compelling story in a very short amount of time, picture is worth 1000 words. All right. Well, we saw here in this first chart, same information is that, the data don't really speak. They don't really tell the whole story. In this second chart here, the data are arranged using a bar chart and your reader can then identify what's going on. If you include this circle or if you just then tell the story, look these are the periods where you're real GDP is falling from the previous quarter, now you have a much more compelling chart. This is a bar chart very easy to do in Excel. Let's go over a couple more different charts and figures, maybe look at some times when using a scatter plot or using a line graph would be more appropriate. All right. For this section, let's talk about a different type of a chart, a line chart. Here, I've downloaded the real GDP but it's not a change. It's just the real GDP in billions of chained 2009 dollars. Again, I got this information from the Federal Reserve Economic Database at the St. Louis Fed. We're going to highlight the data from 2000 to 2016 again, and in this situation, I'm going to highlight this scatter plot first and show you what's going on here. Then what we're going to do is, we're going to add a line, okay. Here's the scatter plot as you can see it. If I add a line looks like this. I'm going to move this to a different part on the Excel spreadsheet here. Now in this situation, a line chart is more appropriate, okay. Here, I've got the real GDP instead of a percentage changes. This is just the real GDP, okay. Now, the real GDP with this line chart shows the trend of the value of all final goods and services in the United States Economy from 2000 all the way through 2016. Now, with this kind of a chart, you can actually show the movement of this variable, real GDP over time and what we have here is we can see in this portion from 2008 through 2010, we have as big deep in real GDP before it starts coming back again. Again, this area right here is consistent with the last economic recession. A line chart, a trend in this situation displays the information and tells a very compelling story. So then you can ask your reader or during a presentation, look at this trend of information, identify where the information, where this trend is changing, where it has an uptake, where it has a down take, and then translate those changes in the chart to the big historical changes that we know about. All right. This is where the economic recession occurred, here's where the economy had a downturn, here's where the economy started coming back again. Okay. This is an incredibly effective chart if you do it the right way. Let's look at a couple of different kinds of charts using some different kind of data. All right. Here I have the data for the Cavs, the 2016 season. I have the name of the pitcher, and the total number of wins that each of those pitcher had for the 2016 season. What I want to do is, I'm going to create two charts. I'm going to create a bar chart, but I'm also going to create a pie chart. For my bar chart, I can highlight the name of the player and the number of wins, and I can insert my bar chart here. I'm going to move this over to a new sheet, and here we can see very clearly. This is the pitcher's name on the x-axis, the number of wins on the y axis, the height of the bar represents the number of wins for each pitcher. This is a very compelling chart, it's appropriate to use with these data, it tells a very nice story. But you might want to use a pie chart to identify what portion of the total wins each pitcher was responsible for. In this case, we're going to do is, I'm going to copy the name of the player over one column. I'm also going to create a new column called percentage of wins. Now for this column, I'm going to take the number of wins for each pitcher and divide it by a 103. Now, this gives me a percentage here. Right. Now, you might get a number 0.17 and you'll have to turn it into a percentage. Now, with this percentage what I can do is I can scroll down which will copy this percentage for this calculation for each one of these pitchers, and when I copy it down, I have Arrieta getting 17 percent of the wins, I have Lester getting 18.4 percent of the wins, Hammel getting 14.6 percent of the wins, and what have you. Now, what I can do is I can highlight both of these sets of information, the pitcher and the percentage of wins, and insert now a pie chart. Now, what I want to do here is I'm going to move this again to a new sheet here, and what we can do is we can then add labels, add information about each of these sort of elements of the pi, each of the slice of the pie. At this point, we know this is Arrieta, we know that we've got Hendricks, and we have Luster and what have you right. But we might want to add some different labels. Here, I've added the label and this is now the percentage of the wins that each of these pitchers has here, okay. We can change where the labels are, format the data labels, so that maybe we can have the outside right. Here's outside right, this best fit, it shows some of the data inside, some of the data outside, inside center like this makes it a chart a little bit larger. But then puts the percentage of wins for each of the pictures inside the chart itself. Again, one of the things that I've seen over and over again with both MBA students, undergrads, people presenting information, is that, I'm grabbing information and making a chart as relatively simple. Arranging the charter, ranging the figure in such a way that you actually are telling a very compelling story, you're telling it efficiently, allowing your reader or whoever you're doing a presentation to basically take in the information, decipher it, and evaluate what the information means. If you're trying to show off a couple different performers, then a pie chart might be an effective way of identifying who has, what type of sales, or what percentage of the total sales are responsible for, you might do a pie chart for the total number of sales for each month. So January is responsible for this month's sales or June is responsible for this. What percentage of your company's sales? In this case, showing off the percentage of the wins for each of your pictures, there's a lot of data here and it can be messy. So you might have to decide, do I want to show it in terms of their percentage of the wins? Do I want to show the number of wins in a bar charts? So there are different charts that you can use and you'll have to identify which of the charts gives you the best story, and really allows whoever you're presenting the information to, to pick up the story quickly and identify the trend that is taking place.