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Dataset Title:	"Deepwater CTD - d94i159.bdo.nc - 26.93N, -96.44W - 1994-00-06"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94i159_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 15.0 28.0 43.0 55.0 65.0 75.0 87.0 96.0 138.0 185.0 205.0  m	12 options
temperature	= (ANY) 13.703700065612793 14.250900268554688 15.811300277709961 18.70400047302246 19.398300170898438 19.924699783325195 21.01729965209961 22.019800186157227 23.46299934387207 25.890300750732422 28.289400100708008 28.8572998046875  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 35.78150177001953 35.86520004272461 36.098899841308594 36.30270004272461 36.331298828125 36.3390998840332 36.354400634765625 36.35459899902344 36.374000549316406 36.374900817871094 36.436100006103516 36.44729995727539  PSU	12 options
oxygen	= (ANY) 2.7200000286102295 2.9000000953674316 2.9800000190734863 3.0899999141693115 3.25 3.890000104904175 4.619999885559082 5.050000190734863 5.059999942779541 5.079999923706055 5.46999979019165 5.639999866485596  milliliters per liter	12 options
nitrite	= (ANY) 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.09000000357627869 0.18000000715255737 0.2199999988079071 0.3100000023841858  micromols	8 options
nitrate	= (ANY) 0.019999999552965164 0.09000000357627869 0.11999999731779099 0.14000000059604645 0.38999998569488525 5.099999904632568 9.0600004196167 11.100000381469727 16.100000381469727 19.170000076293945 20.40999984741211  micromols	11 options
phosphate	= (ANY) 0.0 0.009999999776482582 0.019999999552965164 0.23000000417232513 0.4099999964237213 0.5199999809265137 0.8299999833106995 1.0299999713897705 1.1200000047683716  micromols	9 options
silicate	= (ANY) 0.14000000059604645 0.23000000417232513 0.27000001072883606 0.5699999928474426 0.6600000262260437 1.090000033378601 1.4700000286102295 2.4200000762939453 2.9800000190734863 5.230000019073486 7.130000114440918 8.350000381469727  micromols	12 options
salinity2	= (ANY) 35.77899932861328 35.867000579833984 36.11199951171875 36.30099868774414 36.32699966430664 36.34600067138672 36.354000091552734 36.35599899291992 36.37799835205078 36.391998291015625 36.446998596191406 36.45000076293945  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	28.8572998046875	36.374000549316406	5.050000190734863	0.009999999776482582	0.14000000059604645	0.009999999776482582	1.090000033378601	36.37799835205078	0.0
15.0	28.289400100708008	36.3390998840332	5.079999923706055	0.019999999552965164	0.09000000357627869	0.009999999776482582	0.6600000262260437	36.35599899291992	0.0
28.0	25.890300750732422	36.354400634765625	5.639999866485596	0.029999999329447746	0.11999999731779099	0.019999999552965164	0.27000001072883606	36.354000091552734	0.0
43.0	23.46299934387207	36.331298828125	5.46999979019165	0.019999999552965164	0.09000000357627869	0.009999999776482582	0.23000000417232513	36.32699966430664	0.0
55.0	22.019800186157227	36.30270004272461	5.059999942779541	0.019999999552965164	0.019999999552965164	0.0	0.14000000059604645	36.30099868774414	0.0
65.0	21.01729965209961	36.35459899902344	4.619999885559082	0.2199999988079071	0.38999998569488525	0.019999999552965164	0.5699999928474426	36.34600067138672	0.0
75.0	19.924699783325195	36.374900817871094	3.890000104904175	0.3100000023841858	5.099999904632568	0.23000000417232513	1.4700000286102295	36.391998291015625	0.0
87.0	19.398300170898438	36.44729995727539	3.25	0.18000000715255737	9.0600004196167	0.4099999964237213	2.4200000762939453	36.45000076293945	0.0
96.0	18.70400047302246	36.436100006103516	3.0899999141693115	0.09000000357627869	11.100000381469727	0.5199999809265137	2.9800000190734863	36.446998596191406	0.0
138.0	15.811300277709961	36.098899841308594	2.9000000953674316	0.029999999329447746	16.100000381469727	0.8299999833106995	5.230000019073486	36.11199951171875	0.0
185.0	14.250900268554688	35.86520004272461	2.9800000190734863	0.019999999552965164	19.170000076293945	1.0299999713897705	7.130000114440918	35.867000579833984	1.0
205.0	13.703700065612793	35.78150177001953	2.7200000286102295	0.03999999910593033	20.40999984741211	1.1200000047683716	8.350000381469727	35.77899932861328	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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