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Dataset Title:	"Deepwater CTD - d94i144.bdo.nc - 26.02N, -95.97W - 1994-00-05"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94i144_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) 1.0 18.0 32.0 44.0 74.0 87.0 101.0 125.0 182.0 306.0 390.0 1024.0  m	12 options
temperature	= (ANY) 4.701499938964844 9.777999877929688 11.364999771118164 14.481599807739258 18.711200714111328 20.092599868774414 21.489299774169922 22.414499282836914 24.0393009185791 25.04170036315918 28.862300872802734 29.425100326538086  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 34.94029998779297 35.20500183105469 35.42449951171875 35.89649963378906 36.31159973144531 36.3468017578125 36.35850143432617 36.37160110473633 36.37889862060547 36.42449951171875 36.42959976196289 36.430198669433594  PSU	12 options
oxygen	= (ANY) 2.5899999141693115 2.630000114440918 2.700000047683716 2.819999933242798 3.450000047683716 4.28000020980835 4.550000190734863 4.570000171661377 4.650000095367432 4.920000076293945 5.260000228881836 5.329999923706055  milliliters per liter	12 options
nitrite	= (ANY) 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.05000000074505806 0.1599999964237213 0.4000000059604645  micromols	6 options
nitrate	= (ANY) 0.05999999865889549 0.09000000357627869 0.10000000149011612 0.2199999988079071 4.760000228881836 12.1899995803833 19.3799991607666 25.809999465942383 26.65999984741211 28.229999542236328  micromols	10 options
phosphate	= (ANY) 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.23999999463558197 0.5799999833106995 1.0199999809265137 1.440000057220459 1.6200000047683716 1.6299999952316284  micromols	9 options
silicate	= (ANY) 0.4099999964237213 0.7599999904632568 0.8299999833106995 0.9399999976158142 2.009999990463257 2.0199999809265137 2.059999942779541 4.099999904632568 7.389999866485596 11.989999771118164 15.550000190734863 26.270000457763672  micromols	12 options
salinity2	= (ANY) 34.93899917602539 35.20500183105469 35.42599868774414 35.93000030517578 36.334999084472656 36.34700012207031 36.356998443603516 36.37699890136719 36.37900161743164 36.42599868774414 36.426998138427734 36.428001403808594  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
1.0	29.425100326538086	36.42959976196289	4.550000190734863	0.029999999329447746	0.10000000149011612	0.03999999910593033	2.0199999809265137	36.428001403808594	0.0
18.0	28.862300872802734	36.37160110473633	4.650000095367432	0.019999999552965164	0.10000000149011612	0.03999999910593033	2.009999990463257	36.37699890136719	0.0
32.0	25.04170036315918	36.31159973144531	5.260000228881836	0.019999999552965164	0.05999999865889549	0.03999999910593033	0.9399999976158142	36.334999084472656	0.0
44.0	24.0393009185791	36.37889862060547	5.329999923706055	0.019999999552965164	0.05999999865889549	0.029999999329447746	0.7599999904632568	36.37900161743164	0.0
74.0	22.414499282836914	36.35850143432617	4.920000076293945	0.029999999329447746	0.09000000357627869	0.029999999329447746	0.4099999964237213	36.356998443603516	0.0
87.0	21.489299774169922	36.3468017578125	4.570000171661377	0.1599999964237213	0.2199999988079071	0.019999999552965164	0.8299999833106995	36.34700012207031	0.0
101.0	20.092599868774414	36.42449951171875	3.450000047683716	0.4000000059604645	4.760000228881836	0.23999999463558197	2.059999942779541	36.42599868774414	0.0
125.0	18.711200714111328	36.430198669433594	2.819999933242798	0.05000000074505806	12.1899995803833	0.5799999833106995	4.099999904632568	36.426998138427734	0.0
182.0	14.481599807739258	35.89649963378906	2.700000047683716	0.029999999329447746	19.3799991607666	1.0199999809265137	7.389999866485596	35.93000030517578	1.0
306.0	11.364999771118164	35.42449951171875	2.630000114440918	0.019999999552965164	25.809999465942383	1.440000057220459	11.989999771118164	35.42599868774414	0.0
390.0	9.777999877929688	35.20500183105469	2.5899999141693115	0.009999999776482582	28.229999542236328	1.6299999952316284	15.550000190734863	35.20500183105469	0.0
1024.0	4.701499938964844	34.94029998779297	4.28000020980835	0.009999999776482582	26.65999984741211	1.6200000047683716	26.270000457763672	34.93899917602539	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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