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Abundant testing data have existed for decades. Today we have the tools to access and consume these data like never before. Use the search bar to see how your neighborhood schools are performing. See which neighborhoods enjoy schools with high graduation rates and where more resources are needed. Included are reading and math breakdowns for the 2009-2010 school year, as well indication of how scores have changed since the previous year. For a deeper dive click through on each school to see performance in reading and math for the last three school years, as well as district averages for the 2009-2010.

Visualizing the dynamic geography of testing data not only empowers individual choices about where to send their children, but enables policymakers and researcher to see trends in how schools are performing only visible on a map.

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font: 13px/20px 'Helvetica Neue', Helvetica, Arial, sans-serif;
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border: 1px solid #8C8C8C;
border: 1px solid rgba(0, 0, 0, .45);
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border: 1px solid rgba(0, 0, 0, .45);
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border: 1px solid rgba(0, 0, 0, .45);
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Converting to SQLite

Importing the spatially-explicit tables (TMsch.csv and TMlea.csv, in the form of simple lat/long coordinates) into QGIS via the'Add Delimited Text Layer' plugin, allows for a first look at the data. Selecting 'Save layer as vector file..' from the Layers menu. In the dialog box, select the following parameters:

Format: SQLite
Encoding: UTF-8
CRS: Google Mercator EPSG:900913

Import the non-spatial .csv tables into SQLite database files using a database inspector like Base or from the command line using SQL for SQLite. Be sure to import all six tables into one database.