describe_index¶

In [ ]:

describe_index(name: str = "", 
               list_polygons: bool = False,)

Retrieves information on an index that contains a set of polygons. If you do not pass any parameters, the function returns all defined indexes.

Parameters¶

Name	Type	Optional	Description
name	str	✓	Index name.
list_polygons	bool	✓	Boolean that specifies whether to list the polygons in the index. If set to True, the function will return a vDataFrame instead of a tablesample.

Returns¶

tablesample : An object containing the result. For more information, see utilities.tablesample.

Example¶

In [30]:

from verticapy.geo import *

# Describes all indexes
describe_index()

Out[30]:

	Abc name Varchar(4096)
1	world_polygon
2	world_counties

Rows: 1-2 | Column: name | Type: Varchar(4096)

In [31]:

# Describing a specific index
describe_index("world_polygon")

Out[31]:

	Abc type Varchar(20)	123 polygons Integer	123 SRID Integer	123 min_x Float	123 min_y Float	123 max_x Float	123 max_y Float
1	GEOMETRY	177	0	-180.0	-90.0	180.0	83.64513

Rows: 1-1 | Columns: 7

In [32]:

# Describing all the geometries of a specific index
describe_index("world_polygon",
               list_polygons = True)

Out[32]:

	123 gid Int	Abc state Varchar(20)	🌎 Geometry(13167)
1	140	INDEXED
2	2931	INDEXED
3	4050	INDEXED
4	57713	INDEXED
5	265100	INDEXED
6	279070	INDEXED
7	282814	INDEXED
8	329988	INDEXED
9	339747	INDEXED
10	360346	INDEXED
11	443593	INDEXED
12	591919	INDEXED
13	594130	INDEXED
14	603253	INDEXED
15	642550	INDEXED
16	647581	INDEXED
17	737718	INDEXED
18	758288	INDEXED
19	778358	INDEXED
20	865267	INDEXED
21	920938	INDEXED
22	1218208	INDEXED
23	1221549	INDEXED
24	1251581	INDEXED
25	1291358	INDEXED
26	1467152	INDEXED
27	1772255	INDEXED
28	1792338	INDEXED
29	1895250	INDEXED
30	1944643	INDEXED
31	1958042	INDEXED
32	1972126	INDEXED
33	2051363	INDEXED
34	2103721	INDEXED
35	2214858	INDEXED
36	2314307	INDEXED
37	2484780	INDEXED
38	2823859	INDEXED
39	2875422	INDEXED
40	2990561	INDEXED
41	3045191	INDEXED
42	3047987	INDEXED
43	3068243	INDEXED
44	3351827	INDEXED
45	3360148	INDEXED
46	3424386	INDEXED
47	3474121	INDEXED
48	3500000	INDEXED
49	3753142	INDEXED
50	3758571	INDEXED
51	3856181	INDEXED
52	4292095	INDEXED
53	4510327	INDEXED
54	4543126	INDEXED
55	4689021	INDEXED
56	4926330	INDEXED
57	4930258	INDEXED
58	4954674	INDEXED
59	5011102	INDEXED
60	5320045	INDEXED
61	5351277	INDEXED
62	5445829	INDEXED
63	5491218	INDEXED
64	5605948	INDEXED
65	5625118	INDEXED
66	5789122	INDEXED
67	5918919	INDEXED
68	6025951	INDEXED
69	6072475	INDEXED
70	6163195	INDEXED
71	6172011	INDEXED
72	6229794	INDEXED
73	6653210	INDEXED
74	6909701	INDEXED
75	6943739	INDEXED
76	7101510	INDEXED
77	7111024	INDEXED
78	7126706	INDEXED
79	7531386	INDEXED
80	7965055	INDEXED
81	8236303	INDEXED
82	8299706	INDEXED
83	8468555	INDEXED
84	8754413	INDEXED
85	9038741	INDEXED
86	9549747	INDEXED
87	9850845	INDEXED
88	9960487	INDEXED
89	9961396	INDEXED
90	10248069	INDEXED
91	10646714	INDEXED
92	10674723	INDEXED
93	10734247	INDEXED
94	10768477	INDEXED
95	10839514	INDEXED
96	11038805	INDEXED
97	11138234	INDEXED
98	11147407	INDEXED
99	11403800	INDEXED
100	11466756	INDEXED

Rows: 1-100 | Columns: 3