1

I'm trying to test if a point is inside a polygon using this example:

https://stackoverflow.com/questions/20776205/point-in-polygon-with-geojson-in-python

However, my output says that none of the points is inside any of the polygons. Since the points are defined on the map of NYC, and my polygons define community districts of NYC, this doesn't make sense.

This is my full code:

import urllib2, json, csv
import numpy

from shapely.geometry import shape, Point

def readJson(url):
    """
    Returns a json file specified in @url.
    """
    response = urllib2.urlopen(url)
    return json.loads(response.read())


def readCSV(url):
    """
    Returns a csv file specified in @url.
    """
    response = urllib2.urlopen(url)
    return csv.DictReader(response, delimiter=',')  


def getRegions():
    """
    Returns a dictionary formed by the id of a region and its coordinates.
    """
    dict = {}
    # (longitude, latitude)
    url = "https://nycdatastables.s3.amazonaws.com/2013-08-19T18:22:23.125Z/community-districts-polygon.geojson"
    data = readJson(url)
    for district in data['features']:
        dict[district['id']] = district['geometry']

    return dict


def getPOIs():
    """
    Returns a list of tuples of POIs lat/long coordinates.
    """
    urls = ["https://nycdatastables.s3.amazonaws.com/2013-06-04T18:02:56.019Z/museums-and-galleries-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-12-16T21:49:55.716Z/nyc-parking-facilities-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-06-20T16:06:05.136Z/mapped-in-ny-companies-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-06-11T18:59:27.269Z/nyc-public-school-locations-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-07-29T15:49:03.498Z/nyc-private-school-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-07-01T16:25:00.297Z/nyc-special-education-school-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-06-05T14:35:56.387Z/basic-description-of-colleges-and-universities-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-06-05T20:25:17.301Z/operating-sidewalk-cafes-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-06-04T14:40:48.764Z/community-health-centers-results.csv",
            "http://data.nycprepared.org/ar/dataset/dycd-after-school-programs-housing/resource/d2306a8f-59d1-4cb0-b527-ba44ca8eec3a",
            "http://data.nycprepared.org/ar/dataset/dycd-after-school-programs-family-support-programs-for-seniors/resource/493f52a4-0a49-4f5f-8937-78e69fb77852",
            "https://nycdatastables.s3.amazonaws.com/2013-07-02T15:29:20.692Z/agency-service-center-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-06-13T18:39:44.536Z/nyc-2012-farmers-market-list-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-10-18T21:14:52.348Z/nyc-grocery-stores-final.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-06-18T14:29:37.626Z/subway-entrances-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-06-04T17:58:59.335Z/map-of-monuments-results.csv",
            "https://nycdatastables.s3.amazonaws.com/2013-06-18T20:17:34.010Z/nyc-landmarks-results.csv"]

    POIs = []       

    for url in urls:
        csv = readCSV(url)  
        print url
        for line in csv:
            latitude = line.get('latitude', None)
            longitude = line.get('longitude', None)
            if latitude is not None and longitude is not None:
                POIs.append((float(longitude), float(latitude))) 

    return POIs



def POIsInRegion(regions, POIs):
    """
    Returns a dictionary formed by the id of a region and the number of POIs that falls in
    this region.
    """
    dict = {}

    for key, value in regions.iteritems():
        dict[key] = 0   
        polygon = shape(value)
#       print value
        for p in POIs:
            point = Point(p[0], p[1])
#           print point
            if polygon.contains(point):
                print True, point
                dict[key] += 1

    return dict



if __name__ == '__main__':

    # Geographical Features
    regions_bbox = getRegions()
    regions_number = len(regions_bbox)
    print "Regions: ", regions_number

    print "Reading POIs..."
    POIs = getPOIs()
    print "Done Reading ", len(POIs), " POIs"

    print "Calculating POIs per Region"
    POIsPerRegion = POIsInRegion(regions_bbox, POIs)
    print POIsPerRegion

All data are valid and obtained at http://nycprepared.org.

Example:

First polygon (related to this data -- map can be view):

{u'type': u'Polygon', u'coordinates': [[[-74.01115034338935, 40.725777216880076], [-74.01081238260726, 40.72578980255575], [-73.99931241700145, 40.71755024177738], [-74.0005783921612, 40.71557090292421], [-74.0004546306596, 40.71436504759887], [-74.0009317433238, 40.71326325304528], [-74.00086781464309, 40.71156815886214], [-74.00050986097233, 40.710984270453366], [-74.0014714023208, 40.70974655432324], [-73.99919451174895, 40.70794737635146], [-74.00118685262828, 40.70685982577175], [-74.00098276757775, 40.706416712992926], [-74.00140666691954, 40.70617938802063], [-74.0005829704798, 40.70543393364888], [-74.00143661245443, 40.70487217770522], [-74.00206142563805, 40.70541700463557], [-74.00256965059467, 40.70552357952349], [-74.00268512768794, 40.70544924811865], [-74.00197070463986, 40.704737867482024], [-74.00217184875859, 40.70460659646367], [-74.00243071075865, 40.70467785800434], [-74.00238670806719, 40.70479566367446], [-74.00332307270787, 40.70562859522005], [-74.00363187169326, 40.70542980675174], [-74.00287843069457, 40.70483135798975], [-74.00297246475286, 40.70476649143739], [-74.00364446183866, 40.7054216846388], [-74.00438344417225, 40.70511325985482], [-74.00426687037428, 40.70501166020203], [-74.00459003883672, 40.70478775294501], [-74.00349632042324, 40.7037967692677], [-74.0037198704304, 40.703654481944646], [-74.00480628900745, 40.70464206905116], [-74.00518805133365, 40.70442053569055], [-74.00492580564406, 40.70421180838463], [-74.00521160900402, 40.704405532235306], [-74.00535027224755, 40.70431007996152], [-74.00415742154165, 40.70323163208721], [-74.004272587521, 40.703015666411474], [-74.00559242609006, 40.70408256373161], [-74.00601862790923, 40.703873152890765], [-74.00614010577931, 40.70397866027174], [-74.00659591913875, 40.70368590245182], [-74.00530412596078, 40.70255986563303], [-74.00549427805095, 40.70243138095038], [-74.00553546138175, 40.70264552110683], [-74.00567522315887, 40.702584071694936], [-74.00678502257081, 40.70356812690006], [-74.00930907655481, 40.70195460302253], [-74.00869964313567, 40.70113986754221], [-74.00775549150639, 40.70154800167179], [-74.00759136204219, 40.70132808104811], [-74.00853611510774, 40.70091969574503], [-74.008349275591, 40.70066934838819], [-74.00862036163862, 40.700552163210666], [-74.00960052263287, 40.701865481917835], [-74.01116664217923, 40.70147720220825], [-74.01109588602678, 40.70127499934884], [-74.01128983905524, 40.701249982244235], [-74.01079959311005, 40.70020721300695], [-74.01115033556837, 40.70089840010092], [-74.01135836291354, 40.70085195863632], [-74.01133409344382, 40.70056835368232], [-74.0115029114371, 40.70081505897418], [-74.01172926817475, 40.70077011805966], [-74.01163147918649, 40.7004582182481], [-74.01185378549589, 40.700738921450146], [-74.01208668214691, 40.700681308739156], [-74.01185672623029, 40.70010710340832], [-74.01196196116918, 40.70003754559543], [-74.01239160032284, 40.700620528094], [-74.01259392327509, 40.70057083347241], [-74.01261382087364, 40.70010826581106], [-74.01290881859993, 40.7005236116934], [-74.01310747847371, 40.700507452180624], [-74.01301189331895, 40.69981825663114], [-74.01311303826294, 40.69977416488007], [-74.01327349549122, 40.70049687022768], [-74.01348560832739, 40.700478222908394], [-74.01353285084137, 40.70010816142314], [-74.01367479248758, 40.70012582145088], [-74.01353047796475, 40.70031110034644], [-74.01355826959487, 40.70093987083052], [-74.01395152690475, 40.70099098246003], [-74.01422063261519, 40.700111490863044], [-74.01415238853336, 40.70057786578343], [-74.01428920741134, 40.70064414476502], [-74.01467120058032, 40.700210400694424], [-74.01432384363017, 40.700661304127095], [-74.01464323168875, 40.70081730432518], [-74.01509832270125, 40.700334265523416], [-74.01467365628476, 40.70083460852581], [-74.01502113661678, 40.70099250401337], [-74.015142318121, 40.70084289235424], [-74.01714508062658, 40.70270534997615], [-74.01764797572895, 40.70349459987939], [-74.01757035706059, 40.70418388098645], [-74.01779454520279, 40.704234897096185], [-74.01781758697946, 40.703937922496536], [-74.01795474048662, 40.70397578560846], [-74.01784441106724, 40.704242039937895], [-74.01844770243773, 40.704162168231505], [-74.01866830771891, 40.704435239616195], [-74.01748086152573, 40.70466748769614], [-74.01811296129115, 40.70455372748716], [-74.01888746649365, 40.70472914883734], [-74.0193425462446, 40.706093672024494], [-74.01912275963412, 40.706975814337405], [-74.01863058372699, 40.707139715269264], [-74.01884889814508, 40.706970312350194], [-74.01853513269668, 40.706918322014054], [-74.01819029325691, 40.7078216261098], [-74.01885500911966, 40.708047534447395], [-74.01777014254503, 40.712834574789106], [-74.01780037822344, 40.71234512415862], [-74.01662424491339, 40.71215731899518], [-74.01661840078305, 40.71275615002965], [-74.0163200662758, 40.713407982478245], [-74.01754443334657, 40.71361122266423], [-74.01772496219294, 40.7130701816227], [-74.01671018605823, 40.71862417605797], [-74.01321322719193, 40.71831571989575], [-74.0129144874633, 40.7197082932253], [-74.01344694049585, 40.71978201978623], [-74.01338906903445, 40.72004260727319], [-74.01452415856502, 40.720187397445684], [-74.01452279056075, 40.72053205032773], [-74.01296558526825, 40.720328675587126], [-74.01286909138038, 40.720833752211675], [-74.0132393733702, 40.720887986728066], [-74.01308010145637, 40.72154580719522], [-74.01253875807262, 40.72150317657635], [-74.01165326569942, 40.725871761851344], [-74.01516324118423, 40.72631971193678], [-74.01517084085862, 40.726579390657555], [-74.01145763103551, 40.72615568926202], [-74.01115034338935, 40.725777216880076]]]}

First points (related to this data -- map can be view):

POINT (-74.01375579499995 40.70381655000006)
POINT (-74.06303178799993 40.61512117100006)
POINT (-73.94729768499991 40.83385383400008)
POINT (-73.97810302099992 40.76162530600004)
POINT (-74.03968483799991 40.69905659600005)
POINT (-73.97364816499993 40.78082656700008)
POINT (-74.00701187899995 40.72352692500004)
POINT (-73.96597045099992 40.76882456300007)
POINT (-73.99963036799994 40.72112778300004)
POINT (-73.96428395699991 40.76983411600008)
POINT (-73.94654590499994 40.83358261600006)
POINT (-73.80557949899992 40.87177865100006)
POINT (-73.82489046299992 40.76288666600004)
POINT (-73.8797487409999 40.87823677400007)
POINT (-73.91975017699991 40.83103011300005)
POINT (-73.94401601399994 40.67450733000004)
POINT (-73.99240540399995 40.69480330800008)
POINT (-73.96358506799993 40.67108354500004)
POINT (-74.00731553399993 40.74789793400004)
POINT (-73.97727392099995 40.78587125400009)
POINT (-73.99883836099991 40.72074980300005)
POINT (-73.93173408699994 40.86492396800008)
POINT (-73.97985598399993 40.57526357600005)
POINT (-73.95778161999993 40.78432607400003)
POINT (-73.97304190099993 40.76210730600008)
POINT (-73.94649318099994 40.83330244300004)
POINT (-74.00613537699991 40.74789526000006)
POINT (-73.9873186399999 40.75750141900005)
POINT (-74.00290417199994 40.72245152200009)
POINT (-73.92383914699991 40.86713125400007)
POINT (-73.99272306099994 40.72496003700007)
POINT (-73.9513676009999 40.79309925400008)
POINT (-74.04132161699994 40.69820788700008)
POINT (-74.01133926299991 40.70339960900009)
POINT (-73.96708040599992 40.77105498700007)
POINT (-74.07387774199992 40.61516555800006)
POINT (-73.96174203899994 40.77916597400008)
POINT (-73.94306846199993 40.77611378300008)
POINT (-73.91397962899993 40.85874750300007)
POINT (-74.03231077699991 40.60900900100006)
POINT (-73.94682282199994 40.83345248000006)
POINT (-73.89098784299995 40.87835819800006)
POINT (-74.01808694199991 40.67557226800005)
POINT (-73.98383672499995 40.75602148500008)

Result:

Calculating POIs per Region
True POINT (-73.99386877199993 40.73798709800008)
0: 0, 1: 0, 2: 0, 3: 0, 4: 0, 5: 0, 6: 0, 7: 0, 8: 0, 9: 0, 10: 0, 11: 0, 12: 0, 13: 0, 14: 0, 15: 0, 16: 0, 17: 0, 18: 0, 19: 0, 20: 0, 21: 0, 22: 0, 23: 0, 24: 0, 25: 0, 26: 0, 27: 0, 28: 0, 29: 0, 30: 0, 31: 0, 32: 0, 33: 0, 34: 0, 35: 0, 36: 0, 37: 0, 38: 0, 39: 0, 40: 0, 41: 0, 42: 0, 43: 0, 44: 0, 45: 0, 46: 0, 47: 0, 48: 0, 49: 0, 50: 0, 51: 0, 52: 0, 53: 0, 54: 0, 55: 0, 56: 0, 57: 0, 58: 0, 59: 0, 60: 0, 61: 0, 62: 0, 63: 0, 64: 0, 65: 0, 66: 0, 67: 0, 68: 0, 69: 0, 70: 0, 71: 0, 72: 0, 73: 0, 74: 0, 75: 0, 76: 0, 77: 0, 78: 0, 79: 0, 80: 0, 81: 0, 82: 0, 83: 0, 84: 0, 85: 0, 86: 0, 87: 0, 88: 0, 89: 0, 90: 0, 91: 0, 92: 0, 93: 0, 94: 0, 95: 0, 96: 0, 97: 1, 98: 0, 99: 0, 100: 0, 101: 0, 102: 0, 103: 0, 104: 0, 105: 0, 106: 0, 107: 0, 108: 0, 109: 0, 110: 0, 111: 0, 112: 0, 113: 0, 114: 0, 115: 0, 116: 0, 117: 0, 118: 0, 119: 0, 120: 0, 121: 0, 122: 0, 123: 0, 124: 0, 125: 0, 126: 0, 127: 0, 128: 0, 129: 0, 130: 0, 131: 0, 132: 0, 133: 0, 134: 0, 135: 0, 136: 0, 137: 0, 138: 0, 139: 0, 140: 0, 141: 0, 142: 0, 143: 0, 144: 0, 145: 0, 146: 0, 147: 0, 148: 0}

ONE SINGLE TRUE printed. It doesn't make sense.

For instance, this point, from the first .csv:

enter image description here

Is clearly inside this polygon:

enter image description here

And it's not printed as `True!

I don't know what I'm missing.

  • 2
    In your function POIsInRegion, try to insert a print True in block if polygon.contains(point): and comment both print value and print point. You will see it prints True. Your error is not in shapely but in your dict manipulation IMO – ThomasG77 Dec 15 '15 at 1:37
  • For perfs, you should look at gis.stackexchange.com/questions/102933/… and snorf.net/blog/2014/05/12/using-rtree-spatial-indexing-with-ogr because your solution is highly inefficient (don't take it personal, it's just if you want to speedup things ;) ) – ThomasG77 Dec 15 '15 at 1:41
  • Weird, I can't see just one 'True', @ThomasG77. Which doesn't make sense. I'll check these references, but I have to solve the basic first. :S – pceccon Dec 15 '15 at 15:05
2

Shapely manual says "All operations are performed in the x-y plane."

in def getPOIs change

POIs.append((float(latitude), float(longitude))) 

to

POIs.append((float(longitude), float(latitude))) 

Here's the code that works; commented out all but one csv

import urllib2, json, csv
import numpy

from shapely.geometry import shape, Point


def readJson(url):
    """
    Returns a json file specified in @url.
    """
    response = urllib2.urlopen(url)
    return json.loads(response.read())

def readCSV(url):
    """
    Returns a csv file specified in @url.
    """
    response = urllib2.urlopen(url)
    return csv.DictReader(response, delimiter=',')


def getRegions():
    """
    Returns a dictionary formed by the id of a region and its coordinates.
    """
    dict = {}

    url = "https://nycdatastables.s3.amazonaws.com/2013-08-19T18:22:23.125Z/community-districts-polygon.geojson"
    data = readJson(url)
    for district in data['features']:
        dict[district['id']] = district['geometry']

    return dict


def getPOIs():
    """
    Returns a list of tuples of POIs lat/long coordinates.
    """
    urls = [
        "https://nycdatastables.s3.amazonaws.com/2013-06-04T18:02:56.019Z/museums-and-galleries-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-12-16T21:49:55.716Z/nyc-parking-facilities-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-06-20T16:06:05.136Z/mapped-in-ny-companies-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-06-11T18:59:27.269Z/nyc-public-school-locations-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-07-29T15:49:03.498Z/nyc-private-school-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-07-01T16:25:00.297Z/nyc-special-education-school-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-06-05T14:35:56.387Z/basic-description-of-colleges-and-universities-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-06-05T20:25:17.301Z/operating-sidewalk-cafes-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-06-04T14:40:48.764Z/community-health-centers-results.csv",
        #     "http://data.nycprepared.org/ar/dataset/dycd-after-school-programs-housing/resource/d2306a8f-59d1-4cb0-b527-ba44ca8eec3a",
        #     "http://data.nycprepared.org/ar/dataset/dycd-after-school-programs-family-support-programs-for-seniors/resource/493f52a4-0a49-4f5f-8937-78e69fb77852",
        #     "https://nycdatastables.s3.amazonaws.com/2013-07-02T15:29:20.692Z/agency-service-center-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-06-13T18:39:44.536Z/nyc-2012-farmers-market-list-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-10-18T21:14:52.348Z/nyc-grocery-stores-final.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-06-18T14:29:37.626Z/subway-entrances-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-06-04T17:58:59.335Z/map-of-monuments-results.csv",
        #     "https://nycdatastables.s3.amazonaws.com/2013-06-18T20:17:34.010Z/nyc-landmarks-results.csv"
            ]

    POIs = []

    for url in urls:
        csv = readCSV(url)
        print url
        for line in csv:
            latitude = line.get('latitude', None)
            longitude = line.get('longitude', None)
            if latitude is not None and longitude is not None:
                POIs.append((float(longitude), float(latitude)))
                # POIs.append((float(latitude), float(longitude)))
    return POIs


def POIsInRegion(regions, POIs):
    """
    Returns a dictionary formed by the id of a region and the number of POIs that falls in
    this region.
    """
    dict = {}

    for key, value in regions.iteritems():
        dict[key] = 0
        polygon = shape(value)
        for p in POIs:
            point = Point(p[0], p[1])
            # print point.wkt
            if polygon.contains(point):
                dict[key] += 1

    return dict


if __name__ == '__main__':
    # Geographical Features
    regions_bbox = getRegions()
    regions_number = len(regions_bbox)
    print "Regions: ", regions_number

    print "Reading POIs..."
    POIs = getPOIs()
    print len(POIs)
    print "Done Reading POIs"

    print "Calculating POIs per Region"
    POIsPerRegion = POIsInRegion(regions_bbox, POIs)
    for k,v in POIsPerRegion.iteritems():
        print k,v

Reversed the order in getPOIs function and tweaked the dict at the end.

Here's my result

{0: 9, 1: 0, 2: 2, 3: 0, 4: 4, 5: 0, 6: 0, 7: 0, 8: 13, 9: 0, 10: 3, 11: 0, 12: 0, 13: 0, 14: 1, 15: 0, 16: 0, 17: 0, 18: 0, 19: 0, 20: 0, 21: 0, 22: 0, 23: 0, 24: 0, 25: 0, 26: 0, 27: 0, 28: 0, 29: 0, 30: 0, 31: 0, 32: 0, 33: 0, 34: 0, 35: 0, 36: 0, 37: 0, 38: 0, 39: 0, 40: 0, 41: 0, 42: 2, 43: 0, 44: 0, 45: 0, 46: 0, 47: 0, 48: 0, 49: 0, 50: 0, 51: 0, 52: 0, 53: 0, 54: 0, 55: 0, 56: 0, 57: 0, 58: 0, 59: 0, 60: 0, 61: 0, 62: 0, 63: 0, 64: 0, 65: 0, 66: 0, 67: 0, 68: 0, 69: 0, 70: 0, 71: 0, 72: 0, 73: 0, 74: 0, 75: 6, 76: 0, 77: 0, 78: 1, 79: 0, 80: 0, 81: 0, 82: 0, 83: 0, 84: 2, 85: 0, 86: 0, 87: 0, 88: 0, 89: 0, 90: 0, 91: 0, 92: 0, 93: 1, 94: 0, 95: 1, 96: 1, 97: 11, 98: 1, 99: 0, 100: 1, 101: 0, 102: 3, 103: 0, 104: 3, 105: 21, 106: 0, 107: 2, 108: 1, 109: 0, 110: 3, 111: 1, 112: 0, 113: 0, 114: 0, 115: 0, 116: 0, 117: 0, 118: 1, 119: 0, 120: 0, 121: 6, 122: 0, 123: 0, 124: 2, 125: 0, 126: 2, 127: 1, 128: 2, 129: 1, 130: 0, 131: 0, 132: 0, 133: 1, 134: 8, 135: 1, 136: 0, 137: 2, 138: 1, 139: 4, 140: 3, 141: 0, 142: 0, 143: 0, 144: 0, 145: 0, 146: 0, 147: 0, 148: 0}
  • I did this... No success either, @nickves. – pceccon Dec 15 '15 at 0:29
  • 1
    It works; give it time its highly inefficient. I had to look through the debugger to verify the results. verify it for only museums-and-galleries-results before trying to do a 16MB csv – nickves Dec 15 '15 at 1:30
  • I don't know what's happening. I put a print statement inside the if and I can see just one True, which doesn't make sense. – pceccon Dec 15 '15 at 15:09
  • Thank you, @nickves. I can see that yours work. I don't know what's the difference, I'll make a diff here because I can't see the difference! Oo – pceccon Dec 15 '15 at 15:39
  • I definitely can't see any difference but thank you. – pceccon Dec 15 '15 at 15:47
2

I believe your issue is due to your coordinates having switched lat/long values. Your first coordinate POINT (-74.01375579499995 40.70381655000006) is actually in Antarctica and not NYC, by switching the values, you get in NYC (see pictures below). So, when the script is run to find the point within the NYC boundaries, that is why it is not found.

Antarctica

NYC

EDIT: For clarity, have added a picture to represent the changes of what I entered into Google Maps to the coordinates displayed.

Coordinates

  • Hi, @MaryBeth, I did this because I was getting the same result using lat/long. I'll change that. But should I change this in the shape too? Because there the first values are negative ~-74 and the other one positive. If so, how do I do that? So this seems a little bit inconsistent. Thank you. (: – pceccon Dec 14 '15 at 21:48
  • I found this, which is interesting: gis.stackexchange.com/questions/54065/… I'm not very familiar with GeoJSON, so this confusion between formats is new to me--but do you receive an error when you try to run? I'll look more at the logic later this evening and see if anything stands out. – MaryBeth Dec 14 '15 at 21:59
  • No, no error at all, it just doesn't work because it's not correct. – pceccon Dec 14 '15 at 22:00
  • I though that if I changed the points to be in longitude/latitude it would work, but it doesn't. – pceccon Dec 14 '15 at 22:08
  • google maps gets coords in latitude/longitude. – nickves Dec 14 '15 at 22:20

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