Last time we looked at bar charts, as a way to compare different categories. This time, we'll look at line graphs. To build a line graph, we plot a set of points and we connect each of the points with the line segment. In line graphs, time is often, but not always, the horizontal axis in the graph. What are the line graphs good for? They're good for showing trends or other relationships. In the other relationship category, this is a line graph of water's boiling point compared to altitude above sea level. And this strikes close to home for me, because I live in Colorado Springs, which is about 6,000 feet above sea level. And so water actually boils at a significantly lower temperature. It's right around 201 degrees here. Instead of 212 degrees, which means that cooking, boiling spaghetti for example, the water isn't as hot, even though it's boiling, so it's not going to get any hotter. So it takes longer to cook pasta, and rice, and I know you're deeply concerned about those concerns for me, but this is actually about the line graph. Right that this shows a relationship between altitude and water's boiling point. This line graph actually uses time as the horizontal axis, and the vertical axis is about parking spaces and number of staff. So it's counting things up, so this is at a particular location. As you can see from 2003 to 2004, the parking spaces dropped to about half of what they were while the number of staff kept increasing over time. And then there's this big jump from 2006 to 2007 in staff parking spots. Though of course, you can obviously see that there are still not enough. Now, one of the things that line graphs can't show us is, in fact, we don't know why the number of staff parking days jumped from 2006 to 2007. It could have been that staff were starting to fight with the people who provide parking or whatever. It's unclear, what the actual cause and effect is from a line graph. So, we can't, in general, make assumptions about cause and effect from line graphs but we can see trend. And we can, in fact, if there are a couple of lines included in the line graph, we can actually see perhaps some relationships between the different items that we're graphing. This next one is, again, about commuting. And we can see a number of different things. The total automobiles, the purple line, increased from 1960 up until just around 2000 and then it has been decreasing a little bit at a time. But we can also see this trend it would appear from the data that 1980 was the first year that the census included questions about driving alone versus carpooling. But you can see pretty clearly that, except for the slight dip from 2010 to 2013, in the drove alone, the blue line, there's been a steady increase of people driving alone. And on the green line, the carpool line down below, we can see that there has pretty much been a steady decrease in the number of people who carpool from year to year across this particular set of time that's provided in the data. In this lecture, we learned that line graphs can help us see trends or other relationships in our dataset.