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Dataset Title:	"Deepwater CTD - d94i020.bdo.nc - 27.86N, -90.5W - 1994-07-29"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94i020_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 13.0 29.0 48.0 64.0 75.0 95.0 137.0 205.0 274.0 385.0 652.0  m	12 options
temperature	= (ANY) 6.375400066375732 9.586700439453125 11.836899757385254 14.264800071716309 16.874300003051758 19.132699966430664 20.30120086669922 21.11079978942871 23.132200241088867 27.073699951171875 29.081600189208984 29.423500061035156  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 28.162399291992188 32.76570129394531 34.89830017089844 35.154998779296875 35.47570037841797 35.85860061645508 35.99800109863281 36.25510025024414 36.25910186767578 36.296600341796875 36.31480026245117 36.4900016784668  PSU	12 options
oxygen	= (ANY) 2.7699999809265137 2.869999885559082 2.890000104904175 3.2100000381469727 3.25 3.450000047683716 4.409999847412109 4.659999847412109 4.869999885559082 4.940000057220459 4.960000038146973 5.269999980926514  milliliters per liter	12 options
nitrite	= (ANY) 0.0 0.009999999776482582 0.029999999329447746 0.10000000149011612 0.10999999940395355  micromols	5 options
nitrate	= (ANY) 0.029999999329447746 0.07000000029802322 0.07999999821186066 0.11999999731779099 0.75 8.420000076293945 12.970000267028809 18.600000381469727 23.1299991607666 27.649999618530273 30.020000457763672  micromols	11 options
phosphate	= (ANY) 0.07000000029802322 0.09000000357627869 0.10000000149011612 0.12999999523162842 0.18000000715255737 0.5699999928474426 0.8399999737739563 1.2300000190734863 1.5800000429153442 1.9199999570846558 2.180000066757202  micromols	11 options
silicate	= (ANY) 0.2199999988079071 0.3499999940395355 0.6100000143051147 1.0199999809265137 1.6399999856948853 1.9500000476837158 2.619999885559082 4.019999980926514 6.989999771118164 10.300000190734863 14.880000114440918 23.190000534057617  micromols	12 options
salinity2	= (ANY) 28.187000274658203 32.619998931884766 34.89699935913086 35.15700149536133 35.481998443603516 35.88100051879883 35.99599838256836 36.2599983215332 36.26900100708008 36.30400085449219 36.31700134277344 36.459999084472656  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	29.423500061035156	28.162399291992188	4.869999885559082	0.009999999776482582	0.029999999329447746	0.07000000029802322	0.6100000143051147	28.187000274658203	0.0
13.0	29.081600189208984	32.76570129394531	4.659999847412109	0.009999999776482582	0.11999999731779099	0.09000000357627869	1.6399999856948853	32.619998931884766	0.0
29.0	27.073699951171875	35.99800109863281	4.940000057220459	0.009999999776482582	0.07999999821186066	0.09000000357627869	0.3499999940395355	35.99599838256836	0.0
48.0	23.132200241088867	36.25910186767578	5.269999980926514	0.0	0.07000000029802322	0.10000000149011612	0.2199999988079071	36.2599983215332	0.0
64.0	21.11079978942871	36.296600341796875	4.960000038146973	0.029999999329447746	0.07000000029802322	0.12999999523162842	1.0199999809265137	36.30400085449219	0.0
75.0	20.30120086669922	36.31480026245117	4.409999847412109	0.10999999940395355	0.75	0.18000000715255737	1.9500000476837158	36.31700134277344	0.0
95.0	19.132699966430664	36.4900016784668	3.450000047683716	0.10000000149011612	8.420000076293945	0.5699999928474426	2.619999885559082	36.459999084472656	0.0
137.0	16.874300003051758	36.25510025024414	3.2100000381469727	0.029999999329447746	12.970000267028809	0.8399999737739563	4.019999980926514	36.26900100708008	0.0
205.0	14.264800071716309	35.85860061645508	2.890000104904175	0.029999999329447746	18.600000381469727	1.2300000190734863	6.989999771118164	35.88100051879883	1.0
274.0	11.836899757385254	35.47570037841797	2.869999885559082	0.029999999329447746	23.1299991607666	1.5800000429153442	10.300000190734863	35.481998443603516	0.0
385.0	9.586700439453125	35.154998779296875	2.7699999809265137	0.029999999329447746	27.649999618530273	1.9199999570846558	14.880000114440918	35.15700149536133	0.0
652.0	6.375400066375732	34.89830017089844	3.25	0.029999999329447746	30.020000457763672	2.180000066757202	23.190000534057617	34.89699935913086	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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