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Get Started with GIS Mapping . Part 2 of 2, December 2009 Madhu Lakshmanan. Agenda. Data Preparation – planning , geocoding , aggregating , data formatting ... Mapping aggregate data with AFF Mapper Using data sets from the AFF website Using your own datasets in Excel

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get started with gis mapping

Get Started with GIS Mapping

Part 2 of 2, December 2009

Madhu Lakshmanan

  • Data Preparation – planning, geocoding, aggregating, data formatting ...
  • Mapping aggregate data with AFF Mapper
    • Using data sets from the AFF website
    • Using your own datasets in Excel
  • Mapping aggregate data with Earthplot
  • Recap
  • To-Do
  • Resources
  • Homework
data preparation planning
Data Preparation - Planning
  • Having some idea of what you want to achieve with your map
  • What data do you have already?
  • What data do you need to acquire?
  • If you have to convert your data, what conversion tools do you need?
  • What maps can you reuse?
  • Data origin, metadata, processing
  • Discuss with other users, colleagues, peers
data preparation geocoding
Data Preparation - Geocoding
  • Can geocode at different address levels like state, county, zipcode, complete address, etc.
  • Multiple ways, differences in accuracy, daily limits, one time activity
  • Using
  • Using KMLGeocoder on desktop
  • Zip data with lat/long for each state
data preparation aggregate
Data Preparation - Aggregate
  • Useful to graph case address data at a higher level like zipcode/county/state
  • Using Excel to do sorting/subtotals
  • Using the aggregate geocoded data in tools like Earthplot
  • Certain tools need your data to be either in number format or don’t care. Knowing which can help in troubleshooting

Data Preparation - Formatting

mapping your case data points
Mapping your case data - points
  • Directly enter addresses into GE one by one. (can import bulk if using Pro version)
  • Use a tool like KMLGeocode to take your Excel address data and convert to KML directly – no identifying info needed other than address data. Limit is 5000 a day.
  • GE shows a map with a scatter plot of your case data. A screenshot of this will not reveal any specific address information to a viewer but sharing kml will do that.
mapping your case data aggregate
Mapping your case data - aggregate
  • Useful to denote differences in numbers at an aggregate level such as zip code on top of other layers
  • Need to have your data prepped as aggregates and geocoded beforehand.
  • Earthplot is a simple tool that creates such graphs for GE. (GE-Graph is one other more complex tool.)
  • AFF Mapper also requires your data to be aggregated but does not require geocoding. It creates the shaded graduated maps and not graphs
aff mapper using datasets from american factfinder
AFF Mapper – Using datasets from American Factfinder
  • Created to make maps using census boundary files and American Fact Finder data
  • Rule-based, but simple to follow
  • Find a shapefile from is a one time task for a particular geography, so make sure to extract, rename and save the file safely.
  • Extract to a folder on your computer that you can find. There will be multiple files in the folder.
aff mapper basic
AFF Mapper – Basic
  • Go to the American Fact Finder website for datasets.
  • In the left panel, choose Data Sets and a survey/census
  • Choose the option to create a custom table
  • Select a geographic type and subtypes if applicable.
  • Follow the prompts to select a table from the list
  • Filter by data elements (these will be the columns in your final excel file)
  • Sometimes you can further filter the results to restrict the number of rows
  • View the table before downloading.
  • In the toolbar above the table, you have an option to print/download. Choose download, choose to save as an Excel file with the descriptive field names and save. Extract the zip file to a well named folder.
aff mapper basic16
AFF Mapper – Basic
  • Start up the AFF Mapper
  • Click on Input file and choose your shapefile that you had downloaded from the TIGER site earlier.
  • Once that loads up, select XLS from the Join File Type and click on Join Table. Browse to your Factfinder downloaded xls file and select it.
  • It usually detects the common fields from the two files, but you might just want to see that it has done it right.
  • Then click Join Tables. You should see the two tables merge together.
  • Select the field that you want to be a label on your map
  • Click Render. Another box opens and you can choose your field to be mapped (only after choosing the distribution type) and set the mapping options. Set colors etc and say ok.
  • You return to the original screen, where you specify your output filename and click Go. This will create a KML file for you. You can then open it in GE.

The variable list appears only if you choose one of the distribution methods that allows for multiple values (Quantile, Equal Interval, Standard Deviations, Jenks Natural Breaks)

  • Choose a variable from the drop down list (pick one that is an estimate and not one that is a “margin of error”. There are both types in the Excel file we downloaded. i.e. for each estimate, they also give you the margin or error in the next column).
  • If you would like to normalize (divide by) another value such as the total population in that county or the total area or something to make the playing field level, then choose that variable in the “Normalize By” box.
  • Note that these are sampled and not like census, so you may find entire geographic areas that are empty if you choose a very restrictive variable.
aff mapper for your data
AFF Mapper – for your data
  • Earlier we saw how AFF Mapper can be used to map census (publicly available) datasets onto base shapes, but we can also use it to map our own data as long as it is put in a form that the program understands.
aff mapper data format
AFF Mapper – Data format
  • Your data needs to be in aggregate form, in Excel, aggregated to the level that you want to categorize on. e.g. if you want to see county-wise color graduated map, then your data should be aggregated to the county level
  • The columns that contain this level should be in both the base shapefile and your data file. e.g. your data file should contain the county code/name if that was your aggregation level.
  • The top row of your file can be the column headings. In the second row, you can have descriptive headings for your data. It is very IMPORTANT to use a colon ‘:’ in the 2nd row heading for those columns that are to be treated as NUMERIC, otherwise you will not be able to map those columns. E.g. you can call a column Case : Total
aff mapper example
AFF Mapper – Example
  • An Excel file with Michigan County-wise data aggregates is chosen. The 2nd row headings are created making sure that the numeric data field/s have colons in the 2nd row headings.

First Row Headings

Second Row Headings

Note the colon :

aff mapper example23
AFF Mapper – Example
  • A Michigan County level shapefile from the Census TIGER/Line was downloaded to serve as the base layer for the data.
  • Start AFF Mapper and use the county map of Michigan as the Input shape.
  • Then, under ‘Select Join FileType’, select XLS file and in the Join File box, browse for your previously created Excel file with the county aggregated data.
aff mapper example24
AFF Mapper – Example
  • Once that is loaded, set the Shape Join Field and the Table Join Field to be the same data, i.e. the level to which the data is aggregated, in this case County.
  • The names of the columns might be different, but all that matters is that they contain the same type of data.
  • In this example, we might set the Shape Join Field to CNTY|DFP and the Table Join Field (which is our data) to CCODE.
  • Alternatively, we could also use Name and CNAME but a code is usually more efficient than a name because of spellings etc.
aff mapper example25
AFF Mapper – Example
  • Hit Join tables and you should see the tables merge into one. Scroll to the right to see if your data is reflected in the table.
aff mapper example26
AFF Mapper – Example
  • Choose the County Name to be the Label Field and hit Render.
  • You will be able to choose a classification scheme – note that I have chosen Jenks Natural Breaks in this example.
  • Then pick the variable to be mapped – data, select the number of classes and colors and click OK
aff mapper example27
AFF Mapper – Example
  • Click on Output KML and enter a name for the output file. Then Click Go and wait for the “Finished” message.
  • You can then open Google Earth and open this file and see the result.
  • Earthplot requires data such as: the column that has been aggregated upon (e.g. zipcode), the actual aggregated values (e.g. counts), its latitude and longitude (the latitude and longitude of an area is usually created using its centroid) and any other data you might want to show in the description.
  • In Earthplot, you will see 2 tabs, a Data tab and an Options Tab.
  • Copy your Excel aggregate geocoded data and in Earthplot, in the Data tab, go to Edit->Paste and you will see your data appear in the same way that it appeared in Excel.
  • Go to the Options tab and set various options. In this example, we use a Graduated sizes type of map with one variable.
  • Set the columns to the correct items, i.e. longitude in column D, latitude in Column C etc. Make sure you have them right by looking at your data tab again. The variable column is the one in which the Count is stored.
  • Select the shape to be ‘circle’ for this example and Set the minimum and maximum sizes of your circle to be 0.05 and 0.3 to start with. You can keep tweaking these sizes and perhaps even the Ignore values box as you see your graph being created. Also set the color for your circles.
  • Click on Plot to GE icon in the toolbar and you should see your circles appear on the map. Tweaking the sizes, colors, and perhaps setting a number in the ignore box will help create the graph you want.
  • Once you have the graph you like, go to Earthplot and in the menu, choose Export to KML and give it a name and save. This way you will have a saved copy of your KML file.
to do
  • Assemble a set of tools for mapping
  • Begin a library of base files and data files for mapping on your computer/server
  • Find sources of data for your region – many local governmental entities and health related organizations are good sources.
  • Think about what sort of maps and visualizations work best for each purpose
  • Discuss maps and mapping practices with peers.
lsntap gis resources
LSNTAP GIS Resources
  • Several <5 min screencasts with how-tos of specific tasks we saw in the training series available at:
  • GIS mailing list being restarted – do sign up and discuss mapping at
  • GIS Resources section on updated
  • Email your questions to Madhu or to the GIS listserv or if you need to you can set up a G2M with Madhu. Email
  • Create maps for your area of interest using the tools discussed today.