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Dataset Title:	"Deepwater CTD - d94i155.bdo.nc - 26.14N, -96.33W - 1994-00-06"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94i155_bdo)
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: 12)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

depth	= (ANY) 0.0 18.0 34.0 43.0 46.0 57.0 70.0 80.0 90.0 100.0 166.0 228.0  m	12 options
temperature	= (ANY) 12.350000381469727 14.276800155639648 18.27829933166504 18.655500411987305 18.990999221801758 19.234699249267578 19.971599578857422 20.417499542236328 20.586700439453125 21.666900634765625 27.085899353027344 27.804899215698242  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 35.57270050048828 35.866600036621094 36.232200622558594 36.26060104370117 36.376800537109375 36.40570068359375 36.41279983520508 36.41400146484375 36.41999816894531 36.425899505615234 36.429100036621094 36.432098388671875  PSU	12 options
oxygen	= (ANY) 2.569999933242798 2.740000009536743 2.7699999809265137 2.7799999713897705 2.7899999618530273 2.940000057220459 3.559999942779541 3.690000057220459 3.940000057220459 4.679999828338623 4.690000057220459 4.739999771118164  milliliters per liter	12 options
nitrite	= (ANY) 0.029999999329447746 0.05000000074505806 0.07000000029802322 0.07999999821186066 0.09000000357627869 0.11999999731779099 0.12999999523162842 0.41999998688697815 0.5099999904632568 0.550000011920929 0.75  micromols	11 options
nitrate	= (ANY) 0.05000000074505806 0.09000000357627869 0.14000000059604645 1.7000000476837158 4.03000020980835 4.21999979019165 9.229999542236328 11.279999732971191 12.100000381469727 12.819999694824219 19.450000762939453 23.360000610351562  micromols	12 options
phosphate	= (ANY) 0.0 0.019999999552965164 0.10999999940395355 0.2199999988079071 0.4399999976158142 0.550000011920929 0.5799999833106995 0.6399999856948853 1.0499999523162842 1.350000023841858  micromols	10 options
silicate	= (ANY) 0.029999999329447746 0.4699999988079071 0.5199999809265137 0.7799999713897705 1.0800000429153442 1.2599999904632568 2.5799999237060547 3.5 3.6700000762939453 3.8499999046325684 6.96999979019165 10.359999656677246  micromols	12 options
salinity2	= (ANY) 35.57400131225586 35.8650016784668 36.229000091552734 36.25699996948242 36.374000549316406 36.409000396728516 36.41699981689453 36.41899871826172 36.42399978637695 36.43600082397461  PSU	10 options
qualityFlag	= (ANY) 0.0 1.0	2 options

View:      Map of All Related 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 All Related Data   (Refine the map and/or download the image)

To view the map, check View : Map of All 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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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)  

depth	temperature	salinity	oxygen	nitrite	nitrate	phosphate	silicate	salinity2	qualityFlag
m	degree_C (potential temperature from ctd)	PSU	milliliters per liter	micromols	micromols	micromols	micromols	PSU
0.0	27.804899215698242	36.232200622558594	4.679999828338623	0.07000000029802322	0.05000000074505806	0.0	0.5199999809265137	36.229000091552734	0.0
18.0	27.085899353027344	36.26060104370117	4.739999771118164	0.029999999329447746	0.09000000357627869	0.0	0.4699999988079071	36.25699996948242	0.0
34.0	21.666900634765625	36.376800537109375	4.690000057220459	0.05000000074505806	0.14000000059604645	0.019999999552965164	0.029999999329447746	36.374000549316406	0.0
43.0	20.586700439453125	36.41400146484375	3.940000057220459	0.550000011920929	1.7000000476837158	0.10999999940395355	0.7799999713897705	36.409000396728516	0.0
46.0	20.417499542236328	36.425899505615234	3.690000057220459	0.5099999904632568	4.03000020980835	0.2199999988079071	1.2599999904632568	36.42399978637695	0.0
57.0	19.971599578857422	36.41999816894531	3.559999942779541	0.75	4.21999979019165	0.2199999988079071	1.0800000429153442	36.41899871826172	0.0
70.0	19.234699249267578	36.41279983520508	2.940000057220459	0.41999998688697815	9.229999542236328	0.4399999976158142	2.5799999237060547	36.41699981689453	0.0
80.0	18.990999221801758	36.429100036621094	2.7899999618530273	0.11999999731779099	11.279999732971191	0.550000011920929	3.5	36.43600082397461	0.0
90.0	18.655500411987305	36.432098388671875	2.7799999713897705	0.07999999821186066	12.100000381469727	0.5799999833106995	3.6700000762939453	36.43600082397461	0.0
100.0	18.27829933166504	36.40570068359375	2.7699999809265137	0.09000000357627869	12.819999694824219	0.6399999856948853	3.8499999046325684	36.409000396728516	0.0
166.0	14.276800155639648	35.866600036621094	2.740000009536743	0.09000000357627869	19.450000762939453	1.0499999523162842	6.96999979019165	35.8650016784668	0.0
228.0	12.350000381469727	35.57270050048828	2.569999933242798	0.12999999523162842	23.360000610351562	1.350000023841858	10.359999656677246	35.57400131225586	1.0

In total, there are 12 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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