ERDDAP > tabledap > Subset

Dataset Title:	Sverdrup-20170902T1930
Institution:	TAMU_GERG   (Dataset ID: Sverdrup-20170902T1930)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Data Access Form | Files | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 26)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

wmo_id	= (ANY) 4801924	1 option: 4801924
trajectory	= (ANY) Sverdrup_20170902T193013Z	1 option: Sverdrup_20170902T193013Z
profile_id	= (ANY) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26	26 options
time	= (ANY) 2017-09-02T19:33:56Z 2017-09-02T21:10:43Z 2017-09-03T00:19:49Z 2017-09-03T04:39:29Z 2017-09-03T08:55:53Z 2017-09-03T13:13:41Z 2017-09-03T17:34:20Z 2017-09-03T21:33:47Z 2017-09-04T01:53:35Z 2017-09-04T05:54:45Z 2017-09-04T10:11:09Z 2017-09-04T14:11:43Z 2017-09-04T18:21:02Z 2017-09-04T22:20:32Z 2017-09-05T02:32:47Z 2017-09-05T06:31:15Z 2017-09-05T11:10:02Z 2017-09-05T15:09:52Z 2017-09-05T18:31:34Z 2017-09-05T20:59:58Z 2017-09-06T01:00:00Z 2017-09-06T04:24:18Z 2017-09-06T06:53:37Z 2017-09-06T10:54:56Z 2017-09-06T15:16:19Z 2017-09-06T19:16:41Z	26 options
latitude	= (ANY) 27.894321598662177 27.915637472386035 27.94535257775833 27.978999359651752 27.9948777797105 27.997942843570986 28.00030355006702 28.00904105018205 28.02342391487715 28.040955052868853 28.05179378538405 28.059296222489003 28.071243213058906 28.08728642320669 28.09679618905042 28.10581776020586 28.112506155110506 28.11628548596122 28.12891788138281 28.14502691085047 28.166875680749655 28.192117342190645 28.21454111523623 28.22519568013776 28.229890518598644 28.23431217147738  degrees_north	26 options
longitude	= (ANY) -86.7920466438191 -86.78105417951065 -86.75471258313198 -86.72224232083141 -86.69471777012285 -86.67233627438429 -86.65837174498168 -86.63417254665899 -86.60780168329347 -86.58013051425922 -86.54995608880388 -86.51964261429544 -86.4944094153118 -86.4689682689694 -86.44037372297787 -86.40544337439027 -86.36734817539062 -86.32850041213813 -86.30683656797686 -86.30339246682485 -86.30021255415804 -86.26012884435104 -86.18796675646345 -86.18602544522231 -86.17531378474992 -86.14091963965672  degrees_east	26 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)  

wmo_id	trajectory	profile_id	time	latitude	longitude
			UTC	degrees_north	degrees_east
4801924	Sverdrup_20170902T193013Z	1	2017-09-02T19:33:56Z	28.23431217147738	-86.7920466438191
4801924	Sverdrup_20170902T193013Z	2	2017-09-02T21:10:43Z	28.229890518598644	-86.78105417951065
4801924	Sverdrup_20170902T193013Z	3	2017-09-03T00:19:49Z	28.22519568013776	-86.75471258313198
4801924	Sverdrup_20170902T193013Z	4	2017-09-03T04:39:29Z	28.21454111523623	-86.72224232083141
4801924	Sverdrup_20170902T193013Z	5	2017-09-03T08:55:53Z	28.192117342190645	-86.69471777012285
4801924	Sverdrup_20170902T193013Z	6	2017-09-03T13:13:41Z	28.166875680749655	-86.67233627438429
4801924	Sverdrup_20170902T193013Z	7	2017-09-03T17:34:20Z	28.14502691085047	-86.65837174498168
4801924	Sverdrup_20170902T193013Z	8	2017-09-03T21:33:47Z	28.12891788138281	-86.63417254665899
4801924	Sverdrup_20170902T193013Z	9	2017-09-04T01:53:35Z	28.11628548596122	-86.60780168329347
4801924	Sverdrup_20170902T193013Z	10	2017-09-04T05:54:45Z	28.112506155110506	-86.58013051425922
4801924	Sverdrup_20170902T193013Z	11	2017-09-04T10:11:09Z	28.10581776020586	-86.54995608880388
4801924	Sverdrup_20170902T193013Z	12	2017-09-04T14:11:43Z	28.09679618905042	-86.51964261429544
4801924	Sverdrup_20170902T193013Z	13	2017-09-04T18:21:02Z	28.08728642320669	-86.4944094153118
4801924	Sverdrup_20170902T193013Z	14	2017-09-04T22:20:32Z	28.071243213058906	-86.4689682689694
4801924	Sverdrup_20170902T193013Z	15	2017-09-05T02:32:47Z	28.059296222489003	-86.44037372297787
4801924	Sverdrup_20170902T193013Z	16	2017-09-05T06:31:15Z	28.05179378538405	-86.40544337439027
4801924	Sverdrup_20170902T193013Z	17	2017-09-05T11:10:02Z	28.040955052868853	-86.36734817539062
4801924	Sverdrup_20170902T193013Z	18	2017-09-05T15:09:52Z	28.02342391487715	-86.32850041213813
4801924	Sverdrup_20170902T193013Z	19	2017-09-05T18:31:34Z	28.00904105018205	-86.30021255415804
4801924	Sverdrup_20170902T193013Z	20	2017-09-05T20:59:58Z	28.00030355006702	-86.30339246682485
4801924	Sverdrup_20170902T193013Z	21	2017-09-06T01:00:00Z	27.997942843570986	-86.30683656797686
4801924	Sverdrup_20170902T193013Z	22	2017-09-06T04:24:18Z	27.9948777797105	-86.26012884435104
4801924	Sverdrup_20170902T193013Z	23	2017-09-06T06:53:37Z	27.978999359651752	-86.18796675646345
4801924	Sverdrup_20170902T193013Z	24	2017-09-06T10:54:56Z	27.94535257775833	-86.18602544522231
4801924	Sverdrup_20170902T193013Z	25	2017-09-06T15:16:19Z	27.915637472386035	-86.17531378474992
4801924	Sverdrup_20170902T193013Z	26	2017-09-06T19:16:41Z	27.894321598662177	-86.14091963965672

In total, there are 26 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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