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Dataset Title:	"Deepwater CTD - d93e207.bdo.nc - 27.65N, -95.71W - 1993-05-10"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93e207_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) 2.0 9.0 23.0 48.0 68.0 88.0 98.0 108.0 127.0 146.0 198.0 237.0  m	12 options
temperature	= (ANY) 15.038000106811523 16.610599517822266 19.814800262451172 20.740100860595703 21.949499130249023 22.06369972229004 22.26930046081543 22.751800537109375 23.16950035095215 24.247499465942383 24.28350067138672 24.577199935913086  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 33.72850036621094 35.98680114746094 36.067298889160156 36.1515998840332 36.207298278808594 36.212398529052734 36.216400146484375 36.27280044555664 36.28020095825195 36.38840103149414 36.49959945678711 36.62670135498047  PSU	12 options
oxygen	= (ANY) 2.450000047683716 2.609999895095825 2.9200000762939453 3.2100000381469727 3.8399999141693115 4.130000114440918 4.199999809265137 4.429999828338623 4.449999809265137 4.550000190734863 4.619999885559082 4.650000095367432  milliliters per liter	12 options
nitrite	= (ANY) 0.0 0.05999999865889549 0.07000000029802322 0.07999999821186066 0.09000000357627869 0.10999999940395355 0.18000000715255737  micromols	7 options
nitrate	= (ANY) 0.0 0.029999999329447746 0.10999999940395355 0.11999999731779099 0.17000000178813934 0.3100000023841858 0.47999998927116394 2.4700000286102295 6.21999979019165 8.920000076293945 15.989999771118164 18.1299991607666  micromols	12 options
phosphate	= (ANY) 0.05000000074505806 0.07000000029802322 0.07999999821186066 0.18000000715255737 0.36000001430511475 0.47999998927116394 0.8799999952316284 0.8999999761581421  micromols	8 options
silicate	= (ANY) 1.6699999570846558 1.6799999475479126 1.7100000381469727 1.7899999618530273 1.909999966621399 2.1600000858306885 2.2200000286102295 2.9200000762939453 3.1500000953674316 3.4600000381469727 5.909999847412109 7.489999771118164  micromols	12 options
salinity2	= (ANY) 33.8390007019043 36.03200149536133 36.069000244140625 36.17599868774414 36.20800018310547 36.20899963378906 36.249000549316406 36.277000427246094 36.279998779296875 36.409000396728516 36.500999450683594 36.63100051879883  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
2.0	24.577199935913086	33.72850036621094	4.429999828338623	0.05999999865889549	0.47999998927116394	0.07000000029802322	3.4600000381469727	33.8390007019043	0.0
9.0	24.28350067138672	36.067298889160156	4.449999809265137	0.05999999865889549	0.17000000178813934	0.07999999821186066	2.2200000286102295	36.069000244140625	0.0
23.0	24.247499465942383	36.1515998840332	4.650000095367432	0.07000000029802322	0.11999999731779099	0.07000000029802322	1.909999966621399	36.17599868774414	0.0
48.0	23.16950035095215	36.28020095825195	4.550000190734863	0.07999999821186066	0.029999999329447746	0.07000000029802322	1.6799999475479126	36.279998779296875	0.0
68.0	22.751800537109375	36.27280044555664	4.619999885559082	0.07999999821186066	0.0	0.07000000029802322	1.6699999570846558	36.277000427246094	0.0
88.0	22.26930046081543	36.207298278808594	4.199999809265137	0.0	0.10999999940395355	0.05000000074505806	1.7100000381469727	36.20800018310547	0.0
98.0	22.06369972229004	36.216400146484375	4.130000114440918	0.18000000715255737	0.3100000023841858	0.07000000029802322	1.7899999618530273	36.249000549316406	0.0
108.0	21.949499130249023	36.38840103149414	3.8399999141693115	0.10999999940395355	2.4700000286102295	0.18000000715255737	2.1600000858306885	36.409000396728516	0.0
127.0	20.740100860595703	36.49959945678711	3.2100000381469727	0.09000000357627869	6.21999979019165	0.36000001430511475	2.9200000762939453	36.500999450683594	0.0
146.0	19.814800262451172	36.62670135498047	2.9200000762939453	0.07999999821186066	8.920000076293945	0.47999998927116394	3.1500000953674316	36.63100051879883	0.0
198.0	16.610599517822266	36.212398529052734	2.609999895095825	0.07000000029802322	15.989999771118164	0.8799999952316284	5.909999847412109	36.20899963378906	0.0
237.0	15.038000106811523	35.98680114746094	2.450000047683716	0.07999999821186066	18.1299991607666	0.8999999761581421	7.489999771118164	36.03200149536133	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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