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Mads Bahrami

SHP file data extraction

Mads Bahrami, Wolfram Research Inc

Posted 15 days ago

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This is a short essay where I showed how to get SHP data as dataset in WL. I thought it might be useful for other users, too.

An example of .shp file

data=Import["http://exampledata.wolfram.com/usamap.zip","Data"];

In[]:=

Dimensions

data//Dimensions

In[]:=

{2,4}

Out[]=

Looking at keys:

data〚1〛//Association//Keys

{LayerName,Geometry,Labels,LabeledData}

Out[]=

Looking at layer names:

Lookup["LayerName"]@data

In[]:=

{railroads,states}

Out[]=

Looking at labels:

Lookup["Labels"]@data

In[]:=

{{FNODE_,TNODE_,LENGTH,RAILRDL020,RROWNER1,RROWNER2,RROWNER3,MARK1,MARK2,MARK3},{AREA,PERIMETER,STATESP020,STATE,STATE_FIPS,ORDER_ADM,MONTH_ADM,DAY_ADM,YEAR_ADM}}

Out[]=

Looking at labelled data:

Lookup["LabeledData"]@data

In[]:=

{{FNODE_{7,8,10,8,14,12,15,15,18,19,14,22,23,25,24,26,27,25,30,33,29,35,37,37,37,37,38,34,41,34,44,43,17,31,

⋯8490⋯

,6432,4034,6434,6435,4606,6436,4711,6437,4747,6439,5015,6440,5364,6441,6442,4994,6443,5164,6444,6445,6446,6447,6448,5669,6449,5583,6450,5749,6451,5934,6452,6453,6106,6454},

⋯9⋯

⋯1⋯

}

large output

show less

show all

set size limit...

Out[]=

Note labeled data of railroads and states are note the same:

Length/@Lookup["LabeledData"]@data

In[]:=

{10,9}

Out[]=

Create and association of list of association:

assoc=AssociationThread[Lookup["LayerName"]@data,#]&@Apply[Association,Transpose/@Apply[Thread[#1#2]&,Lookup["LabeledData"][data],{2}],{2}];

In[]:=

Create and association of list of association:

geometry=First/@(Map[<|"Geometry"#|>&,Lookup[{"Geometry"}]@data,{3}]//AssociationThread[Lookup["LayerName"]@data,#]&);

In[]:=

Join two associations and generate dataset for railroads:

Join@@@Transpose[Lookup["railroads"][{assoc,geometry}]]//Dataset

In[]:=

FNODE_	TNODE_	LENGTH	RAILRDL020	RROWNER1	RROWNER2	RROWNER3	MARK1	MARK2	MARK3
7	8	0.245668	6	Bangor and Aroostook Railroad Company			BAR
8	9	0.321561	7	Bangor and Aroostook Railroad Company			BAR
10	11	0.148595	8	Burlington Northern and Santa Fe Railway Company			BNSF
8	12	0.463799	9	Bangor and Aroostook Railroad Company			BAR
14	13	0.962944	10	Burlington Northern and Santa Fe Railway Company			BNSF
12	15	0.590369	11	Bangor and Aroostook Railroad Company			BAR
15	16	0.323529	12	Bangor and Aroostook Railroad Company			BAR
15	17	0.350001	13	Bangor and Aroostook Railroad Company			BAR
18	17	0.0822385	14	Bangor and Aroostook Railroad Company			BAR
19	20	0.113505	15	Burlington Northern and Santa Fe Railway Company			BNSF
14	20	0.483141	16	Burlington Northern and Santa Fe Railway Company			BNSF
22	21	0.450157	17	Burlington Northern and Santa Fe Railway Company			BNSF
23	24	0.0593752	18	Burlington Northern and Santa Fe Railway Company			BNSF
25	23	0.0702975	19	Burlington Northern and Santa Fe Railway Company			BNSF
24	25	0.045303	20	Burlington Northern and Santa Fe Railway Company			BNSF
26	27	0.760763	21	Burlington Northern and Santa Fe Railway Company			BNSF
27	28	0.557414	22	Burlington Northern and Santa Fe Railway Company			BNSF
25	29	0.114372	23	Burlington Northern and Santa Fe Railway Company			BNSF
30	31	1.05735	24	Canadian American Railroad Company	New Brunswick Southern Railway Company, Limited		CDAC	NBSR
33	32	0.531375	25	Union Pacific Railroad Company			UP
rows 1–20 of 8558 columns 1–10 of 11

Data not in notebook; Store now »

Out[]=

Join two associations and generate dataset for states:

Join@@@Transpose[Lookup["states"][{assoc,geometry}]]//Dataset

In[]:=

AREA	PERIMETER	STATESP020	STATE	STATE_FIPS	ORDER_ADM	MONTH_ADM	DAY_ADM	YEAR_ADM	Geometry
25.537	32.498	1262.0	Minnesota	27	32	May	11.0	1858.0	…
0.874	36.371	1263.0	Washington	53	42	November	11.0	1889.0	…
0.002	0.181	1264.0	Washington	53	42	November	11.0	1889.0	…
20.663	43.424	1265.0	Washington	53	42	November	11.0	1889.0	…
45.093	35.4	1266.0	Montana	30	41	November	8.0	1889.0	…
24.457	29.687	1267.0	Idaho	16	43	July	3.0	1890.0	…
21.843	23.227	1268.0	North Dakota	38	39	November	2.0	1889.0	…
0.0	0.065	1269.0	Washington	53	42	November	11.0	1889.0	…
0.0	0.098	1270.0	Washington	53	42	November	11.0	1889.0	…
0.0	0.124	1271.0	Washington	53	42	November	11.0	1889.0	…
0.0	0.049	1272.0	Washington	53	42	November	11.0	1889.0	…
0.003	0.366	1273.0	Washington	53	42	November	11.0	1889.0	…
0.001	0.207	1274.0	Washington	53	42	November	11.0	1889.0	…
0.001	0.145	1275.0	Washington	53	42	November	11.0	1889.0	…
0.018	1.269	1276.0	Washington	53	42	November	11.0	1889.0	…
0.0	0.033	1277.0	Washington	53	42	November	11.0	1889.0	…
0.001	0.259	1278.0	Washington	53	42	November	11.0	1889.0	…
0.0	0.068	1279.0	Washington	53	42	November	11.0	1889.0	…
0.0	0.049	1280.0	Washington	53	42	November	11.0	1889.0	…
0.0	0.124	1281.0	Washington	53