The first step was to take the centroids file and join in to a shapefile of the worlds countries based on a common ID field, in this case FIPS country codes. QGIS doesn’t support table joins directly, but you can accomplish this with a good plugin called fTools, which includes a lot of additional and useful features. The instructions for getting fTools up and running are available on the fTools website; the installation doesn’t require you to download any files, you just handle everything through the QGIS plugin manager (if you have trouble seeing the plugin manager or getting fTools to appear, check to make sure that you have python installed on your machine). Once fTools is up and running, you’ll see a Tools dropdown menu next to your other menus – drop it down, select data management tools and join attribute tables. You’ll get a dialog box asking which shapefile and field you want to join and which shapefile or table you want to join to it. The plugin only supports joins from other shapefiles and dbf tables, so you have to save the save the country centroids text file as a dbf before you do the join (you can do this in Calc or a pre-2007 version of Excel). These aren’t dynamic joins; fTools will create a new shapefile with the table fields attached.
Once the join is complete, you can add the new shapefile with the new fields, click on the layer, and navigate to the labels tab. Hit the checkbox to turn the labels on, select the field that contains the label in the dropdown box at the top, then select data defined position from the menu below. You’ll see a new series of dropdowns on the right, and you can select your longitude column for the X coordinate and latitude column for the Y coordinate. Hit OK, and voila! You’ll have labels that are centered in the middle of each country.
Of course, the label placement will not be perfect in every case. There will be label overlap in areas with small countries, areas with many countries clustered together, and with countries that have long names. The scale and size of the font will also be a factor, and placing the country name in the center is not always ideal for small island nations. However, you can easily change the label placement by going into an edit mode and changing the coordinates in the attribute table to get optimal placement. You can mouse over the map and use the coordinate information that’s displayed beside the scale in the lower right-hand corner of the window to determine which coordinates are most optimal for a given situation. If you produce several maps at the same area and scale, you can use the same settings over and over again. You can also globally change the placement of all the labels using some of the other label options, such as placing all labels above or to the top-right of the centroid.
Now in order for all of this to work, the coordinates in the country centroid file must be in the same coordinate system as the shapefile. Since the country centroid file uses basic latitude and longitude, I was able to do this with a shapefile that was in the basic WGS 84 geographic coordinate system. If you’re using a different geographic coordinate system or a projected coordinate system, you’ll have to convert the coordinates in the centroid file to match that system. I haven’t delved into this too deeply yet, but there are a number of free tools that you can download that should do this – one of them is called GEOTRANS, and it’s available for free download from the NGA. It can handle batch transformations of coordinate data stored in text files, and supports conversions to several different geographic and projected systems.
]]>I downloaded most of the data from the NGA’s GeoNames Server (GNS). I blogged about the GNS awhile back, pointing out that you could query this gazetteer for individual places or you could download files that have all the features for each country in the world. While it took some time to figure out, you can actually take a middle road and query the database for specific categories of features that you can download. I used the text-based search and the links on the left side of the screen actually open different input boxes that you can use to query or exclude data. I managed to query top-level administrative units (countries) and to exclude most variant country names. After I downloaded the file, I still had to go in and do some clean-up, and I had to go back and get countries I missed by hand – these were mostly dependencies and territories that were excluded based on the search I did (Greenland, French Guiana, Netherlands Antilles, and a number of others).
Then I realized that the GNS excludes the United States and all of its territories. So, I went over to the USGS Geographic Names Information Service (GNIS) and grabbed the data for the US territories. The GNIS is simpler to navigate and you can download records pretty easily. They didn’t have a record for the United States as a whole, so I had to go over to the Census Bureau to get coordinates for the US centroid.
I brought all of these records into one file and placed it on the resources page for download, along with some metadata to describe it. Why would you want to use this stuff? You can use if for basic distance calculations, or as a annotated label field for label placement in GIS. More about that in my next post.
I also updated the country code cross-reference file that I took from the CIA World Factbook. You can use this as a bridge table to relate tables that use different identifiers. So if you wanted to join the fips-based centroid file to an iso-based shapefile of countries, you can join the centroids to the bridge first based on fips, and then that new table to the shapefile based on iso.
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While there is a lot of free GIS data out there, one of the black holes is business data. Specifically, if you want to plot all of the businesses in one industry or all of the branches or locations of one company, where do you get the data? I’ve found that, if you need a comprehensive resource, this is one of those datasets that you have to pay for.
At our library we subscribe to a great business directory called ReferenceUSA, which is produced by company called InfoUSA. Their directories of American and Canadian businesses are extremely comprehensive and cover every business large an small. They also have an international directory that has mid-size to large businesses. You can generate lists of businesses using several criteria and filters.
For places, you can specify the entire country, states, counties, places, or ZIP codes. You can get generate lists based on company names, keywords, or NAICS codes to grab all of the businesses in one industry. Once you have your list, you can click on each individual business to get a detailed profile. For GIS purposes, you’ll want to use the download option. Depending on your subscription, you’ll be able to download only a certain number of records at a time (we can get 25 records per download). Just download as a csv file, save, open in a spreadsheet, then start downloading subsequent batches and start copying and pasting records in a master file.
When you go to download, you’ll be prompted to choose basic, detailed, or custom. Basic isn’t going to cut it, as it’s missing the key fields – latitude and longitude coordinates. Choose the detailed option to get all of the fields. The custom option has some bugs – you’ll get lat and long without decimal places and some of the data for fields will be missing. Once you have all of the detailed records, you can delete a lot of the unecessary fields. You’ll want to, as many of the field headings are not database friendly – many are long and contain spaces, which will cause problems when you go to import the table into GIS. So be sure to delete any that you don’t need and fix the ones you do need.
Once you have your table ready, add it to your favorite GIS program. In ArcGIS you can use the Add XY Table feature to plot the points and turn them into a shapefile. Remember to specify the X coordinate as your longitude field and the Y coordinate as latitude, and define your geographic coordinate system as WGS 84. Once you plot them, right click on the feature in the Table of Contents and export them out as a shapefile so you have a permanent layer (see my previous XY post for more details). You can map the businesses as regular old points, or make some graduated symbols based on some of the attributes, like sales or total employees (ReferenceUSA doesn’t provide the exact data, but identifies a range, i.e. 1 to 10 employees, 11 to 25, etc).
Most of the open source alternatives also have a tool or plugin that allow you to plot XY data. Of course, the data does include address fields if you wanted to geocode your points rather than plot XY (but plotting XY is a million times easier and doesn’t require downloading huge street network files).
The good news here is that if you’re not affiliated with a university, you can probably get access to this db from a large public library, as many will have a subscription to a business directory as a matter of course. If they don’t have RefUSA they may have an alternative like the D and B Million Dollar Database. It’s another business directory that allows you to download XY data for businesses, but it is not nearly as comprehensive.
]]>I was working on a project this week that involved manipulating data tables, so I thought I’d share a couple tips here. A number of months ago I wrote a post about manipulating FIPS codes and text-based ID fields. But what if you have to manipulate numeric fields? Adding decimal places, zeros, etc? The answer is – math!
In one field, I had a population figure from the 1970 Census that had been rounded to the hundreds place, so it was listed like this:
Bronx   14718
I wanted to make this a little more explicit by adding the appropriate zeros, so in Excel (or Calc if you prefer) I created a formula to multiply this by 100 =(c2*100) to get the full number with zeros:
Bronx   1471800
I also had fields with latitude and longitude coordinates in decimal degrees, but they lacked decimal points. The longitude field also lacked the minus sign, which means if we plotted the points they would end up in Asia instead of North America (longitude east of the dateline and west of the prime meridian is notated as negative in decimal degrees, as is latitude south of the equator). I knew from the metadata that each coordinate pair was precise to four decimal places, and I knew all of my points were in North America. So I created a formula where I took the latitude and divided by ten thousand =(c3/10000) and took the longitude, divided by ten thousand and multiplied by -1 =((c4/10000)*-1). Here’s the before and after:
Bronx   408492   738800
Bronx   40.8492   -73.8800
Some of this may seem pretty obvious, but if you’re used to working with text-based ID fields all of the time (like I am), it’s easy to forget that all you need is simple math to fix number fields.
The last step I took was to check for null values. A few of my data points had 0,0 listed for lat and long, because coordinate data was missing for those particular places. The problem is that 0 IS a value! If we plotted this data, these points would show up where the equator and prime meridian meet below western Africa. You have to represent “no data” as a blank value or null, and not as a zero. I fixed those, plotted, and was good to go.
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