ERDDAP > tabledap > Subset

Dataset Title:	Glider - gs_484-20150220T2015
Institution:	OOI Coastal & Global Scale Nodes (CGSN)   (Dataset ID: gs_484_20150220t2015)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Data Access Form | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 6)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

trajectory	= (ANY) gs_484-20150220T2015	1 option: gs_484-20150220T2015
wmo_id	= (ANY) 3801516	1 option: 3801516
profile_id	= (ANY)	1 option:
time	= (ANY) 2015-02-21T00:24:59Z 2015-02-21T02:39:49Z 2015-02-21T04:51:35Z 2015-02-21T07:07:25Z 2015-02-21T09:57:26Z 2015-02-21T14:20:29Z	6 options
latitude	= (ANY) -54.49257137682748 -54.483399019591644 -54.47081298976504 -54.45420269541815 -54.44284144804027 -54.426934561015  degrees_north	6 options
longitude	= (ANY) -89.3241129311059 -89.30486521196973 -89.29276000383602 -89.27314527711104 -89.24572388092766 -89.23122257938675  degrees_east	6 options
lat_uv	= (ANY) -54.492455 -54.48340166666667 -54.47457918092621 -54.45883985988824 -54.44526616707926 -54.432254856615465  degrees_north	6 options
lon_uv	= (ANY) -89.32397 -89.30485500000002 -89.29828288497411 -89.27937182121617 -89.25315460599174 -89.23472690858877  degrees_east	6 options
time_uv	= (ANY) 2015-02-21T00:59:19Z 2015-02-21T03:11:18Z 2015-02-21T05:25:28Z 2015-02-21T07:42:59Z 2015-02-21T10:52:53Z 2015-02-21T14:20:17Z	6 options
u	= (ANY) 0.0338398 0.0654302 0.0693294 0.0881846 0.0928437  m s-1	6 options
v	= (ANY) -0.0303618 -0.0149639 -0.0145659 -0.00611342 0.00876983  m s-1	6 options

View:      Map of Distinct Data      Distinct Data Counts     Distinct Data  0 10 100 1000 10000 100000      Related Data Counts     Related Data  0 10 100 1000 10000 100000

 

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Map of Distinct Data   (Refine the map and/or download the image)
Optional: Click on the map to select the closest data.

 

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Distinct Data Counts

To view the counts of distinct combinations of the variables listed above,
check View : Distinct Data Counts above and select a value for one of the variables above.
 

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Distinct Data   (Metadata)    (Refine the data subset and/or download the data)  

trajectory	wmo_id	profile_id	time	latitude	longitude	lat_uv	lon_uv	time_uv	u	v
			UTC	degrees_north	degrees_east	degrees_north	degrees_east	UTC	m s-1	m s-1
gs_484-20150220T2015	3801516		2015-02-21T00:24:59Z	-54.426934561015	-89.23122257938675	-54.432254856615465	-89.23472690858877	2015-02-21T00:59:19Z	0.0693294	0.00876983
gs_484-20150220T2015	3801516		2015-02-21T02:39:49Z	-54.44284144804027	-89.24572388092766	-54.44526616707926	-89.25315460599174	2015-02-21T03:11:18Z	0.0338398	-0.00611342
gs_484-20150220T2015	3801516		2015-02-21T04:51:35Z	-54.45420269541815	-89.27314527711104	-54.45883985988824	-89.27937182121617	2015-02-21T05:25:28Z	0.0654302	-0.0303618
gs_484-20150220T2015	3801516		2015-02-21T07:07:25Z	-54.47081298976504	-89.29276000383602	-54.47457918092621	-89.29828288497411	2015-02-21T07:42:59Z	0.0928437	-0.0145659
gs_484-20150220T2015	3801516		2015-02-21T09:57:26Z	-54.483399019591644	-89.30486521196973	-54.48340166666667	-89.30485500000002	2015-02-21T10:52:53Z	0.0881846	-0.0149639
gs_484-20150220T2015	3801516		2015-02-21T14:20:29Z	-54.49257137682748	-89.3241129311059	-54.492455	-89.32397	2015-02-21T14:20:17Z

In total, there are 6 rows of distinct combinations of the variables listed above. All of the rows are shown above.
To change the maximum number of rows displayed, change View : Distinct Data above.
 

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Related Data Counts

To view the related data counts,
check View : Related Data Counts above and select a value for one of the variables above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.
 

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Related Data   (Metadata)    (Refine the data subset and/or download the data)

To view the related data, change View : Related Data above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.

 

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