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Dataset Title:	"Deepwater CTD - d93f201.bdo.nc - 26.53N, -96.33W - 1993-00-06"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93f201_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 6.0 14.0 29.0 48.0 68.0 86.0 98.0 126.0 178.0 198.0 264.0  m	12 options
temperature	= (ANY) 12.19320011138916 15.633899688720703 16.58989906311035 18.880800247192383 21.179000854492188 22.210899353027344 22.8218994140625 24.128700256347656 27.86709976196289 29.089500427246094 29.568300247192383 29.65220069885254  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 35.345001220703125 35.43069839477539 35.55580139160156 35.7401008605957 36.07830047607422 36.07929992675781 36.211299896240234 36.2755012512207 36.30379867553711 36.34579849243164 36.38059997558594 36.48460006713867  PSU	12 options
oxygen	= (ANY) 2.630000114440918 2.809999942779541 2.819999933242798 3.009999990463257 3.7899999618530273 4.440000057220459 4.539999961853027 4.559999942779541 4.650000095367432 4.809999942779541 4.96999979019165 5.059999942779541  milliliters per liter	12 options
nitrite	= (ANY) 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.05999999865889549 0.07000000029802322 0.07999999821186066  micromols	7 options
nitrate	= (ANY) 0.10999999940395355 0.11999999731779099 0.800000011920929 3.9000000953674316 10.630000114440918 15.010000228881836 16.729999542236328 22.940000534057617  micromols	8 options
phosphate	= (ANY) 0.09000000357627869 0.10999999940395355 0.12999999523162842 0.14000000059604645 0.1599999964237213 0.23999999463558197 0.5799999833106995 0.8100000023841858 0.9399999976158142 1.309999942779541  micromols	10 options
silicate	= (ANY) 2.2200000286102295 2.2300000190734863 2.6700000762939453 2.700000047683716 2.9700000286102295 3.3399999141693115 3.359999895095825 3.5999999046325684 4.420000076293945 6.570000171661377 6.96999979019165 11.859999656677246  micromols	12 options
salinity2	= (ANY) 35.34600067138672 35.428001403808594 35.57400131225586 35.81800079345703 36.07099914550781 36.071998596191406 36.20600128173828 36.275001525878906 36.31100082397461 36.35900115966797 36.395999908447266 36.49100112915039  PSU	12 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	29.65220069885254	35.345001220703125	4.559999942779541	0.029999999329447746	0.11999999731779099	0.1599999964237213	3.5999999046325684	35.34600067138672	0.0
6.0	29.568300247192383	35.43069839477539	4.539999961853027	0.029999999329447746	0.11999999731779099	0.14000000059604645	3.359999895095825	35.428001403808594	0.0
14.0	29.089500427246094	35.7401008605957	4.650000095367432	0.019999999552965164	0.11999999731779099	0.12999999523162842	3.3399999141693115	35.81800079345703	0.0
29.0	27.86709976196289	36.07929992675781	4.96999979019165	0.019999999552965164	0.11999999731779099	0.10999999940395355	2.700000047683716	36.071998596191406	0.0
48.0	24.128700256347656	36.30379867553711	5.059999942779541	0.019999999552965164	0.11999999731779099	0.10999999940395355	2.2300000190734863	36.31100082397461	0.0
68.0	22.8218994140625	36.2755012512207	4.809999942779541	0.019999999552965164	0.10999999940395355	0.09000000357627869	2.2200000286102295	36.275001525878906	0.0
86.0	22.210899353027344	36.34579849243164	4.440000057220459	0.05999999865889549	0.800000011920929	0.10999999940395355	2.6700000762939453	36.35900115966797	0.0
98.0	21.179000854492188	36.38059997558594	3.7899999618530273	0.07999999821186066	3.9000000953674316	0.23999999463558197	2.9700000286102295	36.395999908447266	0.0
126.0	18.880800247192383	36.48460006713867	3.009999990463257	0.05000000074505806	10.630000114440918	0.5799999833106995	4.420000076293945	36.49100112915039	0.0
178.0	16.58989906311035	36.211299896240234	2.819999933242798	0.07000000029802322	15.010000228881836	0.8100000023841858	6.570000171661377	36.20600128173828	0.0
198.0	15.633899688720703	36.07830047607422	2.809999942779541	0.029999999329447746	16.729999542236328	0.9399999976158142	6.96999979019165	36.07099914550781	0.0
264.0	12.19320011138916	35.55580139160156	2.630000114440918	0.03999999910593033	22.940000534057617	1.309999942779541	11.859999656677246	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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