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Dataset Title:	"Deepwater CTD - d94h163.bdo.nc - 27.54N, -95.91W - 1994-05-06"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94h163_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) 1.0 19.0 30.0 37.0 47.0 54.0 64.0 75.0 108.0 151.0 243.0 267.0  m	12 options
temperature	= (ANY) 13.718700408935547 14.30370044708252 17.02680015563965 18.762300491333008 19.552600860595703 19.884899139404297 20.12579917907715 20.644399642944336 20.66819953918457 20.91119956970215 20.983299255371094 24.959299087524414  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 32.531898498535156 35.128501892089844 35.777198791503906 35.84120178222656 35.86650085449219 35.96730041503906 36.117801666259766 36.1260986328125 36.24689865112305 36.27040100097656 36.32789993286133 36.458099365234375  PSU	12 options
oxygen	= (ANY) 2.690000057220459 2.7200000286102295 2.880000114440918 2.9800000190734863 3.6700000762939453 3.759999990463257 4.550000190734863 4.940000057220459 5.0 5.070000171661377 5.119999885559082  milliliters per liter	11 options
nitrite	= (ANY) 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.07999999821186066 0.10000000149011612 0.14000000059604645 0.20999999344348907  micromols	7 options
nitrate	= (ANY) 0.009999999776482582 0.019999999552965164 0.03999999910593033 0.33000001311302185 1.649999976158142 4.650000095367432 6.449999809265137 11.010000228881836 14.390000343322754 19.3700008392334 19.81999969482422  micromols	11 options
phosphate	= (ANY) 0.019999999552965164 0.029999999329447746 0.05000000074505806 0.09000000357627869 0.23999999463558197 0.33000001311302185 0.5699999928474426 0.7599999904632568 1.1100000143051147 1.190000057220459  micromols	10 options
silicate	= (ANY) 3.3299999237060547 3.930000066757202 4.019999980926514 4.309999942779541 4.559999942779541 4.670000076293945 5.539999961853027 6.289999961853027 7.639999866485596 9.260000228881836 12.569999694824219 13.710000038146973  micromols	12 options
salinity2	= (ANY) 32.54199981689453 35.2130012512207 35.78200149536133 35.84600067138672 35.86600112915039 35.944000244140625 36.108001708984375 36.143001556396484 36.27299880981445 36.30099868774414 36.32400131225586 36.46099853515625  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
1.0	24.959299087524414	32.531898498535156	5.070000171661377	0.029999999329447746	0.019999999552965164	0.019999999552965164	3.3299999237060547	32.54199981689453	0.0
19.0	20.66819953918457	35.128501892089844	5.119999885559082	0.029999999329447746	0.009999999776482582	0.029999999329447746	4.559999942779541	35.2130012512207	0.0
30.0	20.983299255371094	35.84120178222656	5.0	0.029999999329447746	0.009999999776482582	0.05000000074505806	4.309999942779541	35.84600067138672	0.0
37.0	20.91119956970215	35.96730041503906	5.0	0.029999999329447746	0.03999999910593033	0.029999999329447746	4.019999980926514	35.944000244140625	0.0
47.0	20.644399642944336	36.117801666259766	4.940000057220459	0.10000000149011612	0.33000001311302185	0.029999999329447746	3.930000066757202	36.108001708984375	0.0
54.0	20.12579917907715	36.1260986328125	4.550000190734863	0.20999999344348907	1.649999976158142	0.09000000357627869	4.670000076293945	36.143001556396484	0.0
64.0	19.884899139404297	36.24689865112305	3.759999990463257	0.14000000059604645	4.650000095367432	0.23999999463558197	5.539999961853027	36.30099868774414	0.0
75.0	19.552600860595703	36.32789993286133	3.6700000762939453	0.07999999821186066	6.449999809265137	0.33000001311302185	6.289999961853027	36.32400131225586	0.0
108.0	18.762300491333008	36.458099365234375	2.9800000190734863	0.05000000074505806	11.010000228881836	0.5699999928474426	7.639999866485596	36.46099853515625	0.0
151.0	17.02680015563965	36.27040100097656	2.880000114440918	0.03999999910593033	14.390000343322754	0.7599999904632568	9.260000228881836	36.27299880981445	0.0
243.0	14.30370044708252	35.86650085449219	2.690000057220459	0.03999999910593033	19.3700008392334	1.1100000143051147	12.569999694824219	35.86600112915039	0.0
267.0	13.718700408935547	35.777198791503906	2.7200000286102295	0.05000000074505806	19.81999969482422	1.190000057220459	13.710000038146973	35.78200149536133	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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