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Shapefiles use dBase databases, which do not support null values. Any null values in numeric fields are stored as 0 and strings as a blank space (regardless of software). If you want true null value support, you need storage format that is null capable (such as a file geodatabase). Alternatively, you can import the records that do have coordinates and ...


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1) The easiest solution is to use the processing module in the QGIS Python console: import processing processing.runalg("qgis:joinattributesbylocation","BKMapPLUTO.shp","DCP_nyc_freshzoning.shp","['intersects']",0,"sum,mean,min,max,median",0,'result.shp') 2) Without a GIS, you can use Fiona (read and write shapefiles as Python dictionaries) and Shapely ...


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You have to change the layer style from single symbol to categorized or graduated. See this tutorial for further details: http://qgis.spatialthoughts.com/2012/02/tutorial-styling-vector-data-in-qgis.html


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It sounds like you have a DEM and you want to augment the accuracy of that DEM with some elevation data you collected as points. That's totally possible but the process probably isn't as linear as you would like it to be. That is - you can't (to my knowledge) update the values of raster cells from vector points directly. You have to go through the process ...


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Depend what means 'many holes', but if it's not hundreds/thousands you can always use Auto Complete polygon tool. All you have to do is start edit session, select the tool, draw the line across a hole and merge created polygons to required polygon. It is better than digitising and Trace but still semi manual… see screenshots: Select Auto complete tool and ...


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I'm not sure exactly what you need. Do you need a shapefile for the New Delhi, India boundary or a shapefile that includes each town's boundaries? I quickly found the New Delhi, India administrative boundary in OpenStreetMap and the extracted it with a query in overpass-turbo.eu. If you need boundaries for the individual towns I altered the query and ...


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Apparently the ESRI Shape format doesn't support SmallInt and Integer. Shape does not support small integer (16bit) or integer (32bit) data types. Instead, it supports a number(x,y) data type. The equivalent data types are: smallint (16bit): number(6,0) integer (32bit): number(11,0) FME Shape Reader/Writer documentation So the answer ...


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This sort of problem is what the topology tool was made for: Create a topology for this layer using the "No Gaps" rule Validate the topology Add it the TOC Use the fix topology tool to Create Features. You can do this one by one or all at once.


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I would edit the polygon layer. trace the missing polygon boundary. merge the selected polygon and the newly created one. screenshots edit Trace create a new feature using the autocomplete polygon tool. @ChrisL is correct... You can simply draw a line crossing one of the edges (justone single segment from one existing polygon into the ...


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Given the extreme apparent age of the data, it seems unlikely that the original data was WGS84. Just plotting it shows an 0.13 degree shift from even 1:15m coastline (ArcGIS 10.0 Data & Maps "country.sdc\country"): If you do update the coastline data, you'd likely need to identify all other geometry data and update them as well.


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I think you should have a look at cshapes it... "provides historical maps of state boundaries and capitals in the post-World War II period". You can download a shapefile and query the data using the fields containing the year to evaluate how country shapes have changed over time. I found this website by first looking on the PennLibraries website.


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For future references, here is the solution I have came to after following the advices above. import shapefile as shp import matplotlib.pyplot as plt sf = shp.Reader("test.shp") plt.figure() for shape in sf.shapeRecords(): x = [i[0] for i in shape.shape.points[:]] y = [i[1] for i in shape.shape.points[:]] plt.plot(x,y) plt.show() The ...


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If your polygons do not overlap the map properly, you have a Coordinate Reference System (CRS) issue. If your map provider is Google Maps, the CRS is WGS84. Thus, you need to change the CRS of your SpatialPolygonDataFrame. library(sp) library(rgdal) proj4string(FieldsMap) # Gives the CRS of the data FieldsMap=spTransform(FieldsMap,CRS("+proj=longlat ...


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I've also worked with another company out of Ontario called AGSI. Their database has FSA and LDU boundaries along with address points.



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