Using Census Data in ArcGIS Pro

how's it going everybody it's uh me again with another arcgis tutorial today i want to talk about census data and how to actually get all of the useful data provided by the census bureau to display properly on the map i just did this in some work for a client and there's a lot of steps to it and then looking around on the internet you know a lot of people seem to have this question so i thought i'd make a video so the census bureau if you just look up census tiger data you'll get a lot of it and i got a lot of it so we're going to look at wisconsin here for a little bit and let's say that we want to make a map here a little choropleth map that shows um let me get this out of my way that shows you know percent just tracked which ones have the most housing in there so when we downloaded all the data from the census bureau we got this one shape file and a bunch of tables so we know we're going to want this was constant data we're going to get the tracked metadata and you'll see why here in a second just so i can make a point now we're also going to want these housing characteristics so let's go ahead and open all of those up it's going to take just a second now you see that we have all of the census tracts inside of wisconsin on the map and if we click them it's going to give us some of the census data but not everything that we want so we see it's got the fid the state fit county fip the geoid the name and then it's got some data in here this bravo 14002 you know e m numbers these end up corresponding to education data which isn't exactly what we're looking for here so we can kind of ignore that and realize that we need to join the data that we want to it so we know we want these housing characteristics so let's explore that data a little bit if we open this up it's going to take a minute because there's a lot of data in here there's thousands and thousands and thousands of tracks and then even probably 15 20 times more of that in metadata okay so we're in the housing data but all we have are these data codes what what are these bravo two five zero zero one echo one what what is that what are all of these well this tracked metadata is what's actually gonna tell us what these are so if we open this up we'll see all these different things and you can see there's 53 992 categories of data in here but you know we just want the housing data so one thing you can do is you could you know select by attribute and look for things to talk about housing or we could if you kind of know what field it is you're already looking for that's really easy to find as well so i know for example based on my experience working with this problem just recently i know exactly what it is we're looking for so i'll show you we're looking where the short name starts with sorry it begins with bravo two five zero zero one e and we click apply and you'll see it down here it'll say one selected and we view that selection and we have total housing units that's going to show us how many houses or housing units are in each of these census tracks so that's great that's exactly what we're looking for is this here so if we go back into our housing characteristics we can we see that that's this first one right here that's exactly what we need okay great so how do we get that joined with the map well the first thing is we don't want to have to deal with all this metadata every single time we do a you know any sort of modification to the data that's going to be very intensive so what we can do is we can export just the object id geoid and this field from here which is actually this one here and then we can get that ready to be joined so if we right click on this and we say data export table it's going to ask us a bunch of stuff you know where do we want to put it we're going to save it the geodatabase i've already started up for this example and these are the input rows that it's coming from yeah and our output name will be uh we're in wisconsin so we'll call it wisconsin wisconsin housing okay and now we only want those certain fields we want the geo id we know we want this this echo1 but we don't anything else so if we click the first one come all the way to the bottom let's make this a little bit bigger we come all the way to the bottom here we can shift click on this and click the x and it's actually going to delete everything else out of there that we don't want which is going to save us lots of lots of time um i think using that we still have 53 000 some odd bits of metadata and now we just have this one that we care about and we click ok and now it's going to output for us down here in the standalone table section a new one called wisconsin housing that we created okay so let's explore that data great that's exactly what we wanted to see so now we want to be able to join this wisconsin housing into our tracked data that we have up here so what we can do is we can do a couple of different things here one the first thing we could do is we could actually export these features and only keep uh and not keep any of that 1400 series data that we had so let's go ahead and do that because we don't we don't care about any of that at all so we'll come into here we'll scroll way to the end we'll make this window bigger so we can see the end and we can click it and we can get rid of that so that'll be even that much faster because now i don't have to deal with any of that so um we've got some good stuff in here but it's all just like the basic stuff no extra data we don't care about and we click ok a parameter is missing yep and that would be excited name it wisconsin tracts okay so that's going to dump all this into a new feature class which is just fine we can turn this one off to verify that it worked and yep that's wisconsin wisconsin looks kind of funny when it puts all the water i guess it is still wisconsin's water in there weird shape okay so we have our wisconsin housing data and we have our wisconsin tracks let's look at this and we know we're going to join these fields together and we're probably going to use this geoid field so you'll see here we have a geoid we go to wisconsin housing we have a geo id but we see that there's something in front of it if you notice this 14 000 us that's not in front of any of our geo ids here but it is in front of our geoid data so we'll use the geoid in the housing or sorry we'll use the gid from housing to match with the geoid data from the wisconsin tracks so we're going to do is we're going to right click on the tracks we're going to have a join so we click add join okay our input field from the tracts right was this geoid data that we talked about and then our field in the join table name oh i have the wrong one selected we go to wisconsin housing and now we're going to use just this geoid so these two features are the same so it knows how to put them together and we click ok so now if we click on any of these census tracts we'll see that this data has now updated where it used to have all of that other other data we weren't concerned with right here in our bravo two five zero zero one echo one it shows us there's 1 750 housing units there so to just take this for one final step let's just see where the most housing units are we come down into our symbology we don't want a single symbol we're going to do graduated colors based on the field id of bravo 2501 lego one and we'll just do five groups and there we are so in this tutorial we we showed you how to join census data into the actual shape file they give you something that they don't do by default i think it's just because if they had all of that data in in one shape file you know people like us that just want to worry about housing now have to deal with you know the hundreds of thousands of different census uh categories or breakdowns so this gives us that more flexibility and then we also just went ahead and turned it into a choropleth map just to show that we could and that it kind of makes sense so anyways i hope you enjoyed this tutorial census data can kind of be a beast to wrangle but once you've worked with it enough you start remembering some of the more common metadata tags like the the bravo two five whatevers and things like that so just keep working with the data and i hope you found this tutorial useful and i hope it saved you a lot of time if you liked it click the like if you wanted to be privy to some more arcgis tutorials you know go ahead and click that subscribe button maybe the bell if you want a notification and i'll see you in the next one

Channel: Tyler White

Views: 551

Keywords: esri, arcgis, pro, arcmap, census data, table join, TIGER

Id: quYkRi8d7ic

Length: 8min 51sec (531 seconds)

Published: Sat Dec 05 2020