@@ -0,0 +1,1072 @@
+parse(df) :%0A    latDict, lonDict = dict(), dict()%0A%0A    # identify extreme most latitude and longitude coordinate pairs in each state%0A    # save coordinate pair of most extreme points for autozoom%0A    for count in range(0,len(usStates%5B'features'%5D)) :%0A        if geo%5B'key'%5D in %5Bcode for code in statePctChange%5B'code'%5D%5D :%0A            for coords in geo%5B'key'%5D%5B'coordinates'%5D%5B0%5D :%0A                # collect lat, lon data in either geoJSON format%0A                # lat, lon data will either be in list (coords) or a list of lists (pairs) %0A                try :%0A                    latDict%5Bcoords%5B1%5D%5D = coords%0A                    lonDict%5Bcoords%5B0%5D%5D = coords%0A                except :%0A                    for pair in coords :%0A                        latDict%5Bpair%5B1%5D%5D = pair%0A                        lonDict%5Bpair%5B0%5D%5D = pair%0A%0A    bounds = %5Blist(reversed(l)) for l in %5BlatDict%5Bmax(%5Bkey for key in latDict.keys()%5D)%5D, latDict%5Bmin(%5Bkey for key in latDict.keys()%5D)%5D,%0A        lonDict%5Bmax(%5Bkey for key in lonDict.keys()%5D)%5D, lonDict%5Bmin(%5Bkey for key in lonDict.keys()%5D)%5D%5D%5D%0A%0A    return bounds%0A

Create parse.py