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Dataset Title:	"Deepwater CTD - d94i163.bdo.nc - 27.54N, -95.91W - 1994-00-07"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94i163_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 14.0 28.0 43.0 60.0 71.0 81.0 101.0 133.0 190.0 218.0 269.0  m	12 options
temperature	= (ANY) 11.804300308227539 13.249099731445312 14.344200134277344 16.997800827026367 18.64579963684082 20.046199798583984 21.114099502563477 21.953899383544922 23.810800552368164 27.88129997253418 28.95870018005371 29.11680030822754  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 35.49150085449219 35.70819854736328 35.8765983581543 36.267601013183594 36.3135986328125 36.335201263427734 36.341400146484375 36.345401763916016 36.41109848022461 36.415199279785156 36.42179870605469 36.426300048828125  PSU	12 options
oxygen	= (ANY) 2.609999895095825 2.630000114440918 2.680000066757202 2.869999885559082 2.9000000953674316 3.759999990463257 4.489999771118164 4.53000020980835 4.619999885559082 4.800000190734863 4.809999942779541 5.239999771118164  milliliters per liter	12 options
nitrite	= (ANY) 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.05999999865889549 0.07000000029802322 0.11999999731779099 0.3700000047683716  micromols	8 options
nitrate	= (ANY) 0.11999999731779099 0.12999999523162842 0.1599999964237213 0.17000000178813934 0.2199999988079071 0.25 4.019999980926514 11.670000076293945 14.449999809265137 19.520000457763672 21.6200008392334 24.510000228881836  micromols	12 options
phosphate	= (ANY) 0.019999999552965164 0.029999999329447746 0.05999999865889549 0.1899999976158142 0.5600000023841858 0.7300000190734863 1.0800000429153442 1.190000057220459 1.399999976158142  micromols	9 options
silicate	= (ANY) 0.18000000715255737 0.23999999463558197 0.5 0.8999999761581421 1.3899999856948853 1.4199999570846558 1.4600000381469727 3.450000047683716 4.03000020980835 7.610000133514404 8.59000015258789 11.369999885559082  micromols	12 options
salinity2	= (ANY) 35.48899841308594 35.702999114990234 35.875999450683594 36.26599884033203 36.314998626708984 36.33700180053711 36.3380012512207 36.36399841308594 36.4109992980957 36.4119987487793 36.42399978637695 36.42900085449219  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	29.11680030822754	36.41109848022461	4.53000020980835	0.019999999552965164	0.2199999988079071	0.05999999865889549	1.4600000381469727	36.4109992980957	0.0
14.0	28.95870018005371	36.426300048828125	4.619999885559082	0.019999999552965164	0.17000000178813934	0.029999999329447746	1.3899999856948853	36.42900085449219	0.0
28.0	27.88129997253418	36.42179870605469	4.800000190734863	0.029999999329447746	0.1599999964237213	0.029999999329447746	0.8999999761581421	36.42399978637695	0.0
43.0	23.810800552368164	36.335201263427734	5.239999771118164	0.029999999329447746	0.11999999731779099	0.029999999329447746	0.23999999463558197	36.33700180053711	0.0
60.0	21.953899383544922	36.3135986328125	4.809999942779541	0.03999999910593033	0.12999999523162842	0.019999999552965164	0.18000000715255737	36.314998626708984	0.0
71.0	21.114099502563477	36.341400146484375	4.489999771118164	0.11999999731779099	0.25	0.029999999329447746	0.5	36.3380012512207	0.0
81.0	20.046199798583984	36.345401763916016	3.759999990463257	0.3700000047683716	4.019999980926514	0.1899999976158142	1.4199999570846558	36.36399841308594	0.0
101.0	18.64579963684082	36.415199279785156	2.9000000953674316	0.07000000029802322	11.670000076293945	0.5600000023841858	3.450000047683716	36.4119987487793	0.0
133.0	16.997800827026367	36.267601013183594	2.869999885559082	0.05999999865889549	14.449999809265137	0.7300000190734863	4.03000020980835	36.26599884033203	0.0
190.0	14.344200134277344	35.8765983581543	2.609999895095825	0.05000000074505806	19.520000457763672	1.0800000429153442	7.610000133514404	35.875999450683594	0.0
218.0	13.249099731445312	35.70819854736328	2.680000066757202	0.03999999910593033	21.6200008392334	1.190000057220459	8.59000015258789	35.702999114990234	0.0
269.0	11.804300308227539	35.49150085449219	2.630000114440918	0.029999999329447746	24.510000228881836	1.399999976158142	11.369999885559082	35.48899841308594	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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