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https://github.com/utdata/texas-schools

We've taken a schools directory from the Texas Education Agency and geocoded all the results. This is a project of the UT School of Journalism Data Visualization class.
https://github.com/utdata/texas-schools

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We've taken a schools directory from the Texas Education Agency and geocoded all the results. This is a project of the UT School of Journalism Data Visualization class.

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README 

        
Texas schools geocoding project

===============================



This is a class project by:



    Univeristy of Texas at Austin

    School of Journalism

    Data Visualization

    Spring 2015

    Instructor: Christian McDonald



We created a geocoded data set of all 9354 schools in Texas that can be merged with other data files from the [Texas Education Agency](http://tea.texas.gov/Reports_and_Data/) for easy mapping. The files are available for free use.



The work was completed in April 2015.



## Update July 2017

- TEA has a file of these lat/longs that is probably a better source at this time: http://schoolsdata2-tea-texas.opendata.arcgis.com/, click on "Schools", then Download Spreadsheet.

- And Common Core has all schools in the US: https://nces.ed.gov/ccd/pubschuniv.asp



## How to use this file



You can use the Download Zip button to just download all the files, or do a [Save As on this file](https://raw.githubusercontent.com/utdata/texas-schools/master/texas-schools-geocoded.csv) to get just the finished geocoded list, called `texas-schools-geocoded.csv`. It is 9354 rows of data. Feel free to fork this repo, update or improve the list and submit a pull request.



There are three sets of addresses in the file: The district, the school mailing address and the school site address. The `Latitude` and `Longitude` fields are keyed to the `SchoolSiteStreetAddress`.



The magic comes with the `SchoolNumber` field, which is a unique ID that matches other school-level data by the [Texas Education Agency](http://tea.texas.gov/Reports_and_Data/). You can database queries and data visualization tools to join data sets on that `SchoolNumber` to map accountability ratings and performance reports.



## Caveats



Things to know if you are using this data:



* Latitudes and Longitudes can only be as good as the address they start from. This will be particularly true for alternative schools, which can be ambiguous.

* Manually-found locations are based off Google Maps, and subject to any errors there. In many cases, the manual locations were verified through Street View photos.

* In some cases we just couldn't find the school. Those have blank Lat/Longs.

* The `CountyName` and `CountyNumber` fields are tied to the district, not the school, which is not always the same county as `SchoolSiteStreetAddress`. This is especially true with private schools.



## Files list



* `texas-schools-geocoded.csv` is a comma separated values file of geocoded schools.

* `schoolsraw.csv` is the origial file the project started from. It is called School and District File with Site Address, and was downloaded from the [Texas Education Agency AskTED](http://mansfield.tea.state.tx.us/tea.askted.web/Forms/Home.aspx) on 3/14/2015.

* `csv_splitter` is a python script used to split the raw file into pieces so each student in the class could have a batch of files to geocode. Someone might find that useful some day.



## GeocodeQualityType



If a geocoding result was not AddressRangeInterpolation or ExactParcelCentroidPoint, the location was manually checked, and the GeocodeQualityType field changed to Manual. Other fields from the geocoding process have been removed for clarity.



## How we geocoded



We used [Texas A&M Geoservices](http://geoservices.tamu.edu/) to batch geocode the files. It is a wonderful service that not only provides latitudes and longitudes for addresses, but gives a quality index of how the points were found. This is essential to be sure that an address was found at street point instead of a city or zip code centroid. Their service is free for up to 2500 addresses a month, or something like that. Check with them ... they are good people.



[Geo-stuff provided by Texas A&M University GeoServices](http://geoservices.tamu.edu/)



The students followed [this guide](https://docs.google.com/document/d/16_reBIxOvRJvfiuTN5bdGpFFq0JH39pmE5kCOv8xaCM/edit?usp=sharing) for the work. I checked and merged the individual files into a single data set.



## Corrections



If you have any corrections to offer, send them to [email protected].



## Contributors



The following students from the University of Texas at Austin School of Journalism, Spring 2015 Data Visualization course contributed to this project:



* LUQMAN ADENIYI

* JOSEPH BAUCUM

* NICOLE COBLER

* TAYLOR ELLIS

* LAUREN FLORENCE

* TRACY FRYDBERG

* DANIEL GOODWIN

* SEBASTIAN HERRERA

* GABRIEL MACIAS

* WESLEY MARTIN

* RENEE MORENO

* ALEXIS SCHRUBBE

* PHILLIP TRACY

* BRYAN WINTER

* MANZHI WU



Also contributing:



* CHRISTIAN MCDONALD

* ANDRE MONTEIRO

* EDWARD TIMMS



Many thanks to all who helped. Enjoy.