Lab Notes

Each group investigated four plazas in Granada,  most groups collected information manually,  all this data must be converted into a single .csv file for grasshopper to reference.

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STEP01_MY MAP

the first step of this assignment is involves gathering LAT+LONG coordinates for the data points location in the plazas. this can be done in google MY MAP tool.

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01. create a NEW MAP + set a NEW LAYER

02. locate your first plaza in Granada

03. at top of page add new MARKER to location of the first data point on the plaza

04. Continue process, work in an ORGANIZED fashion (I would recommend going clockwise, starting at the north most point of each plaza, dividing each plaza into a separate layer could help in data management)

STEP02_EXPORTScreen Shot 2015-07-09 at 11.03.47 PM

05.  click on three dots to the right of “add layer + share”, select export to KML

06. check box “Export to a .KML file instead of .KMZ (does not include custom icons).”

STEP03_CONVERT TO CSV

01. Navigate to downloads folder and rename KML file extension to XML file.

  • You may need to turn on file extensions via the view tab >  (windows 8& 10) or Tools > folder options > view >  uncheck hide extension for known file types. (windows 7)

02. Open a blank Excel file and import XML file.

  • Data > From Other Sources > From XML Data Source

03. You need to seperate LAT and LONG from same column. Select column with latitude and longitude data and choose, Data > Text to Columns

  • Choose separate text to columns via comma

04. COPY LAT+LONG coordinate information in column B and C (Column A should be the point number)

05. INPUT manually gathered data in columns D, E, F, ect (remember to do this systematically,  data must mach corresponding points.)  additionally remember to maintain correct data conversion-  NULL SET : -1, no ZEROS, categorical information should be converted to numbers not text.

06. SAVE file as .csv

07. SAVE new CSV file in GOOGLE SHEETS to share with group

08. Set path in GRASSHOPPER to link this CSV data set

 

CHEERS- a well constructed, organized data set will provide a solid foundation on which to build.