Geographical Plotting with Python Part 5 - Improving the plots

Key Takeaways

what is going on everybody welcome to another Matt plot lid slash basemap slash geographical plotting within Python where we left off we were plotting some dots on this blue United States here we got a Houston Boulder going on red Houston green Boulder cool stuff so anyway well what I was talking about last time was you know what if you want to customize the plot itself a little bit well there's a few things you can do right out of the gate one you can change the size so we can do like marker size equals 20 for this one and then let's make this one's marker can't do anything we can do marker size equals 15 okay so we can save that we can run that and now you can see that you got a big Houston dot and pretty big boulder but not as big as the Houston dot that's cool but let's do let's take this just as a really quick example and then do like 28 right I assume those will run over each other so let's run this real quick yeah and what if this one is a green actually and we'll plot that so what shows up here is just whoever got plotted last right so that's maybe not necessarily what you want right because you could have in theory dots run over each other and you would lose some some of your data possibly if that was an issue but again the size of the dot obviously it's not changing so like when we zoom in to just that spot that's not our problem anymore right but let's say it is it's becoming an issue for you or you do want them to run over a little bit like if you let them run over a little bit it kind of helps the transition of color so for example what we can do is throw an alpha here which kind of makes things see-through so we can say alpha point five and then we'll just apply this to both to all of these actually hey I'll run that and maybe I was a too much of an alpha but you get the idea now they're actually kind of clear so when they do overlap each other it's not such a big deal so finally the last thing I'm going to show you guys is you know how you would actually expand this because you always want to be able to expand you could instead have a flat equal and array lon equal an array and or actually and Python these are actually lists but anyway you can do that and actually well here's what we'll do we'll get rid of this this yes and we'll do that and then like lat two on two equals and actually I will just get rid of these brackets there's not really too much need for them it's not going to make this list too long so and stay well we could say is that is like thirty thirty one thirty four thirty three thirty thirty two so only that this one longitude sorry for the Skype message use thirty you arrows I 94 let's say negative one oh three negative 110 negative 107 negative that wasn't a negative 111 and negative 150 okay now then we're going to basically the same thing here I'm just going to copy and paste these variables switch them up we'll make these off a couple these forty this one's a 33 this one's going to be a 31 this won't be a 30 this one will be a 113 100 here 102 here and a 112 there okay now I will do that lawn that's fine and then this will be too too should work just so you can kind of get an idea how you would build like an array and then you could plot that stuff up like that right just to kind of give you an idea you can build arrays basically and have different varied data you've got green data and red data so to speak so you comply like you know employee versus unemployed you could plot wages you could plot all kinds of stuff or you could plus sentiment that's a great idea anyway that's going to conclude my basic geo plotting tutorials hopefully you guys have enjoyed and have some cool uses for that if you do happen to make something cool like me there I wouldn't mind seeing what you guys make with these geo plotting tutorials there's something else you guys would like to see feel free to let me know sometimes I'm able to just kind of add on to the series so if there's something that you request and I can do it pretty quickly or easily or whatever I'll just do it in in some cases I might have left something out so anyway hopefully that was helpful to you guys as always thanks for watching thanks for supporting subscriptions and until next time