 In this video we're going to talk about dictionaries and data frames. So far we've really focused on importing data frames and getting help reading those data frames into Python. But another common data type that you'll come across is called a dictionary and they function in some ways similar to data frames, but in other ways are very different. So this video will just serve to introduce you to the data frame structure as well as demonstrate how to convert from a dictionary to data frame. So with that, let's go ahead and get started. All right, so here I'm just going to create an example of a data frame and so our dictionary. So the dictionary format looks like this. So we're going to give it a name, a variable name, and there are keys and their values and your key you can think of as being a column header, and the value is what goes below that column. So here, we'll just create a dictionary that we call data. And we open it up with curly brackets, and we give it our first key. And so we'll just say name. And here we give it a column, a colon, and then square brackets to say that now we're entering our values. And so here we just enter some names. So we say Amy, Bob, Claire, and Daisy. So this is our first key and value set to enter another one. We say comma, I'm going to enter down to keep the screen wide enough, but you can always do this in a single line. And let's say now we want to give their birthdays. And we'll keep these as strings so we can say that we'll say Amy was born. September 3, 1991. Bob. 21. 1988. Claire. Maybe she has the same birthday, but a different year. And Daisy. So this is our second key and value. And if we add a third one, we'll get their ages. And here we're going to add numbers so we're not going to put them in quotes. And we're just going to say, you know, these aren't their real ages but 303334 and 89. So there's not much directly related here, but just to show how you can have these numbers. And so if we do that and run it, we're connecting up there initializing, but then once it's run, we can come over to our variables. And we can see that we've got type dictionary, unlike the data frames that we've seen before. We can print the dictionary by just printing the name data. And we can see that the way it prints is a lot like the way that we wrote it so it's not as table like as the data frames that we have seen before. That's why a lot of times you'll want to convert your dictionary into a data frame. And so we can create a new variable data underscore DF, and the command is, before I do that, we want to make sure we import working with pandas. And so the command is PD dot data frame underscore or parentheses, the dictionary name. So we can run this check over on our variable thing and now we've got a data frame type as well, we can continue and print that data frame. And here we can see that it looks a lot nicer it looks more like the table we would expect, compared to the dictionary over here. And then one of the benefits of working with data frames is it becomes a lot easier to print and extract certain values, and we'll get into that more in a later video, but for now to show you some demonstration, if you wanted to print the name column, we do data underscore DF name in quotes. We can see that it's just printed all of our names. And then we can also do the same thing with age, for example. And here it's printed those ages. So this is just an example of how you can create dictionaries but also how you can convert them into data frames.