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Dataset Title:	"Deepwater CTD - d93e198.bdo.nc - 26.01N, -96.24W - 1993-05-00"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93e198_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 8.0 24.0 38.0 47.0 60.0 73.0 98.0 148.0 246.0 345.0 475.0  m	12 options
temperature	= (ANY) 8.632800102233887 10.97350025177002 12.99899959564209 16.154199600219727 17.551700592041016 18.98509979248047 20.786300659179688 22.18709945678711 22.99329948425293 23.64539909362793 23.648000717163086 23.739900588989258  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 31.516000747680664 31.535999298095703 35.0724983215332 35.302398681640625 35.36869812011719 35.66699981689453 35.96889877319336 36.144500732421875 36.148399353027344 36.3114013671875 36.315799713134766 36.403499603271484  PSU	12 options
oxygen	= (ANY) 2.569999933242798 2.5999999046325684 2.630000114440918 2.7100000381469727 2.759999990463257 2.880000114440918 3.680000066757202 4.190000057220459 4.670000076293945 4.880000114440918 4.949999809265137 5.0  milliliters per liter	12 options
nitrite	= (ANY) 0.05000000074505806 0.05999999865889549 0.07000000029802322 0.07999999821186066 0.09000000357627869 0.10999999940395355 0.2199999988079071 0.33000001311302185  micromols	8 options
nitrate	= (ANY) 0.009999999776482582 0.029999999329447746 0.10000000149011612 1.9800000190734863 5.46999979019165 12.069999694824219 14.59000015258789 16.8799991607666 23.3700008392334 27.639999389648438 31.729999542236328  micromols	11 options
phosphate	= (ANY) 0.03999999910593033 0.05999999865889549 0.12999999523162842 0.30000001192092896 0.6100000143051147 0.7699999809265137 0.9100000262260437 1.3200000524520874 1.6399999856948853 1.9700000286102295  micromols	10 options
silicate	= (ANY) 2.0999999046325684 2.3499999046325684 2.559999942779541 3.2699999809265137 4.369999885559082 4.690000057220459 4.800000190734863 5.96999979019165 6.619999885559082 10.270000457763672 13.640000343322754 18.84000015258789  micromols	12 options
salinity2	= (ANY) 31.525999069213867 32.180999755859375 35.084999084472656 35.374000549316406 35.44599914550781 35.66699981689453 36.007999420166016 36.14899826049805 36.196998596191406 36.31700134277344 36.33000183105469 36.40700149536133  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	23.648000717163086	31.516000747680664	5.0	0.05000000074505806	0.029999999329447746	0.03999999910593033	4.800000190734863	31.525999069213867	0.0
8.0	23.64539909362793	31.535999298095703	4.949999809265137	0.05000000074505806	0.029999999329447746	0.03999999910593033	4.369999885559082	32.180999755859375	0.0
24.0	23.739900588989258	35.302398681640625	4.880000114440918	0.05000000074505806	0.009999999776482582	0.03999999910593033	2.3499999046325684	35.44599914550781	0.0
38.0	22.99329948425293	35.96889877319336	4.670000076293945	0.10999999940395355	0.10000000149011612	0.05999999865889549	2.0999999046325684	36.007999420166016	0.0
47.0	22.18709945678711	36.148399353027344	4.190000057220459	0.33000001311302185	1.9800000190734863	0.12999999523162842	2.559999942779541	36.196998596191406	0.0
60.0	20.786300659179688	36.315799713134766	3.680000066757202	0.2199999988079071	5.46999979019165	0.30000001192092896	3.2699999809265137	36.33000183105469	0.0
73.0	18.98509979248047	36.403499603271484	2.880000114440918	0.09000000357627869	12.069999694824219	0.6100000143051147	4.690000057220459	36.40700149536133	0.0
98.0	17.551700592041016	36.3114013671875	2.7100000381469727	0.07999999821186066	14.59000015258789	0.7699999809265137	5.96999979019165	36.31700134277344	0.0
148.0	16.154199600219727	36.144500732421875	2.759999990463257	0.07999999821186066	16.8799991607666	0.9100000262260437	6.619999885559082	36.14899826049805	0.0
246.0	12.99899959564209	35.66699981689453	2.5999999046325684	0.05999999865889549	23.3700008392334	1.3200000524520874	10.270000457763672	35.66699981689453	0.0
345.0	10.97350025177002	35.36869812011719	2.569999933242798	0.07000000029802322	27.639999389648438	1.6399999856948853	13.640000343322754	35.374000549316406	1.0
475.0	8.632800102233887	35.0724983215332	2.630000114440918	0.07000000029802322	31.729999542236328	1.9700000286102295	18.84000015258789	35.084999084472656	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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