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Dataset Title:	"Deepwater CTD - d94j014.bdo.nc - 27.97N, -91.32W - 1994-11-03"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94j014_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 19.0 33.0 49.0 57.0 68.0 89.0 114.0 134.0 169.0 209.0 263.0  m	12 options
temperature	= (ANY) 14.125699996948242 14.665300369262695 15.57509994506836 16.19700050354004 16.993600845336914 18.900400161743164 21.001699447631836 22.677099227905273 24.273700714111328 25.878299713134766 25.929399490356445 25.92959976196289  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 35.831199645996094 35.91529846191406 35.962501525878906 35.962799072265625 35.98429870605469 36.057098388671875 36.15060043334961 36.263301849365234 36.3202018737793 36.39670181274414 36.45119857788086 36.46760177612305  PSU	12 options
oxygen	= (ANY) 2.9700000286102295 3.0199999809265137 3.059999942779541 3.0799999237060547 3.0999999046325684 3.1600000858306885 4.059999942779541 4.409999847412109 4.670000076293945 4.690000057220459 4.71999979019165  milliliters per liter	11 options
nitrite	= (ANY) 0.0 0.009999999776482582 0.029999999329447746 0.03999999910593033 0.10000000149011612 0.14000000059604645  micromols	6 options
nitrate	= (ANY) 0.05999999865889549 0.07999999821186066 0.10999999940395355 0.15000000596046448 0.20000000298023224 2.309999942779541 9.930000305175781 13.09000015258789 13.680000305175781 15.239999771118164 17.290000915527344 18.639999389648438  micromols	12 options
phosphate	= (ANY) 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.05000000074505806 0.11999999731779099 0.5099999904632568 0.6800000071525574 0.7699999809265137 0.8199999928474426 0.8999999761581421 1.0299999713897705  micromols	11 options
silicate	= (ANY) 0.5400000214576721 0.5699999928474426 0.5899999737739563 0.6399999856948853 0.9800000190734863 1.4700000286102295 2.819999933242798 3.7200000286102295 4.659999847412109 5.110000133514404 6.010000228881836 6.679999828338623  micromols	12 options
salinity2	= (ANY) 35.834999084472656 35.92399978637695 35.96699905395508 35.96900177001953 35.987998962402344 36.071998596191406 36.154998779296875 36.25 36.30500030517578 36.402000427246094 36.45600128173828 36.46799850463867  PSU	12 options
qualityFlag	= (ANY) 0.0	1 option: 0.0

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	25.929399490356445	35.962799072265625	4.670000076293945	0.0	0.20000000298023224	0.019999999552965164	0.6399999856948853	35.96699905395508	0.0
19.0	25.92959976196289	35.962501525878906	4.690000057220459	0.009999999776482582	0.15000000596046448	0.009999999776482582	0.5899999737739563	35.96900177001953	0.0
33.0	25.878299713134766	35.98429870605469	4.690000057220459	0.0	0.10999999940395355	0.009999999776482582	0.5400000214576721	35.987998962402344	0.0
49.0	24.273700714111328	36.3202018737793	4.71999979019165	0.009999999776482582	0.05999999865889549	0.029999999329447746	0.9800000190734863	36.30500030517578	0.0
57.0	22.677099227905273	36.39670181274414	4.409999847412109	0.10000000149011612	0.07999999821186066	0.05000000074505806	1.4700000286102295	36.402000427246094	0.0
68.0	21.001699447631836	36.46760177612305	4.059999942779541	0.14000000059604645	2.309999942779541	0.11999999731779099	0.5699999928474426	36.46799850463867	0.0
89.0	18.900400161743164	36.45119857788086	3.1600000858306885	0.029999999329447746	9.930000305175781	0.5099999904632568	2.819999933242798	36.45600128173828	0.0
114.0	16.993600845336914	36.263301849365234	3.0999999046325684	0.029999999329447746	13.09000015258789	0.6800000071525574	3.7200000286102295	36.25	0.0
134.0	16.19700050354004	36.15060043334961	3.059999942779541	0.03999999910593033	13.680000305175781	0.7699999809265137	4.659999847412109	36.154998779296875	0.0
169.0	15.57509994506836	36.057098388671875	3.0799999237060547	0.029999999329447746	15.239999771118164	0.8199999928474426	5.110000133514404	36.071998596191406	0.0
209.0	14.665300369262695	35.91529846191406	3.0199999809265137	0.029999999329447746	17.290000915527344	0.8999999761581421	6.010000228881836	35.92399978637695	0.0
263.0	14.125699996948242	35.831199645996094	2.9700000286102295	0.029999999329447746	18.639999389648438	1.0299999713897705	6.679999828338623	35.834999084472656	0.0

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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