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Dataset Title:	"Deepwater CTD - d93e203.bdo.nc - 26.93N, -96.44W - 1993-05-00"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93e203_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 12.0 18.0 38.0 49.0 58.0 72.0 98.0 122.0 148.0 204.0  m	12 options
temperature	= (ANY) 15.017600059509277 15.795100212097168 16.35650062561035 17.78420066833496 18.967100143432617 20.44860076904297 21.751399993896484 22.40180015563965 24.223499298095703 24.25860023498535 24.344200134277344 24.43779945373535  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 31.17729949951172 32.209999084472656 33.975101470947266 35.983699798583984 36.086299896240234 36.09590148925781 36.136600494384766 36.174598693847656 36.28820037841797 36.327999114990234 36.35369873046875 36.39670181274414  PSU	12 options
oxygen	= (ANY) 2.5999999046325684 2.630000114440918 2.740000009536743 2.759999990463257 2.869999885559082 3.2300000190734863 4.230000019073486 4.53000020980835 4.650000095367432 4.730000019073486 4.800000190734863 4.840000152587891  milliliters per liter	12 options
nitrite	= (ANY) 0.05000000074505806 0.05999999865889549 0.09000000357627869 0.10000000149011612 0.10999999940395355 0.12999999523162842 0.1899999976158142 0.25999999046325684  micromols	8 options
nitrate	= (ANY) 0.07000000029802322 0.07999999821186066 0.09000000357627869 0.10999999940395355 0.3799999952316284 1.7300000190734863 7.440000057220459 10.819999694824219 13.050000190734863 15.420000076293945 16.450000762939453 17.950000762939453  micromols	12 options
phosphate	= (ANY) 0.019999999552965164 0.029999999329447746 0.05000000074505806 0.14000000059604645 0.41999998688697815 0.6299999952316284 0.75 0.9100000262260437 1.0 1.090000033378601  micromols	10 options
silicate	= (ANY) 1.5499999523162842 1.8200000524520874 1.850000023841858 2.4100000858306885 2.5899999141693115 4.21999979019165 4.849999904632568 5.349999904632568 6.159999847412109 6.659999847412109 7.739999771118164  micromols	11 options
salinity2	= (ANY) 31.2450008392334 33.362998962402344 34.47100067138672 35.98899841308594 36.095001220703125 36.097999572753906 36.15700149536133 36.17399978637695 36.297000885009766 36.32400131225586 36.37099838256836 36.395999908447266  PSU	12 options
qualityFlag	= (ANY) 0.0	1 option: 0.0

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	24.223499298095703	31.17729949951172	4.840000152587891	0.05999999865889549	0.07999999821186066	0.05000000074505806	2.4100000858306885	31.2450008392334	0.0
6.0	24.25860023498535	32.209999084472656	4.800000190734863	0.05999999865889549	0.07000000029802322	0.029999999329447746	2.5899999141693115	33.362998962402344	0.0
12.0	24.344200134277344	33.975101470947266	4.730000019073486	0.05000000074505806	0.09000000357627869	0.029999999329447746	2.4100000858306885	34.47100067138672	0.0
18.0	24.43779945373535	36.086299896240234	4.650000095367432	0.05000000074505806	0.10999999940395355	0.019999999552965164	1.5499999523162842	36.095001220703125	0.0
38.0	22.40180015563965	36.136600494384766	4.53000020980835	0.1899999976158142	0.3799999952316284	0.05000000074505806	1.8200000524520874	36.15700149536133	0.0
49.0	21.751399993896484	36.28820037841797	4.230000019073486	0.25999999046325684	1.7300000190734863	0.14000000059604645	1.850000023841858	36.297000885009766	0.0
58.0	20.44860076904297	36.35369873046875	3.2300000190734863	0.10000000149011612	7.440000057220459	0.41999998688697815	4.21999979019165	36.37099838256836	0.0
72.0	18.967100143432617	36.39670181274414	2.869999885559082	0.12999999523162842	10.819999694824219	0.6299999952316284	4.849999904632568	36.395999908447266	0.0
98.0	17.78420066833496	36.327999114990234	2.759999990463257	0.10999999940395355	13.050000190734863	0.75	5.349999904632568	36.32400131225586	0.0
122.0	16.35650062561035	36.174598693847656	2.5999999046325684	0.10999999940395355	15.420000076293945	0.9100000262260437	6.159999847412109	36.17399978637695	0.0
148.0	15.795100212097168	36.09590148925781	2.740000009536743	0.10999999940395355	16.450000762939453	1.0	6.659999847412109	36.097999572753906	0.0
204.0	15.017600059509277	35.983699798583984	2.630000114440918	0.09000000357627869	17.950000762939453	1.090000033378601	7.739999771118164	35.98899841308594	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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