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Dataset Title:	"Deepwater CTD - d94i143.bdo.nc - 27.07N, -95.98W - 1994-00-05"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94i143_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 27.0 41.0 53.0 69.0 81.0 100.0 133.0 203.0 279.0 391.0 686.0  m	12 options
temperature	= (ANY) 6.254899978637695 9.874899864196777 12.02560043334961 14.248800277709961 17.27560043334961 18.893199920654297 20.282899856567383 20.817800521850586 22.440399169921875 24.056100845336914 25.950000762939453 28.479299545288086  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 34.90629959106445 35.21870040893555 35.52259826660156 35.86249923706055 36.30229949951172 36.35660171508789 36.360198974609375 36.37730026245117 36.382598876953125 36.39820098876953 36.422698974609375 36.46220016479492  PSU	12 options
oxygen	= (ANY) 2.559999942779541 2.609999895095825 2.7100000381469727 2.8499999046325684 2.890000104904175 3.25 3.5299999713897705 4.110000133514404 4.559999942779541 4.769999980926514 5.110000133514404 5.179999828338623  milliliters per liter	12 options
nitrite	= (ANY) 0.0 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.05000000074505806 0.15000000596046448 0.4699999988079071  micromols	7 options
nitrate	= (ANY) 0.07999999821186066 0.09000000357627869 0.14000000059604645 0.15000000596046448 0.1599999964237213 3.380000114440918 11.319999694824219 14.65999984741211 19.84000015258789 24.559999465942383 28.010000228881836 30.299999237060547  micromols	12 options
phosphate	= (ANY) 0.0 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.15000000596046448 0.46000000834465027 0.6399999856948853 0.9599999785423279 1.1399999856948853 1.4299999475479126 1.690000057220459  micromols	11 options
silicate	= (ANY) 0.8500000238418579 0.8899999856948853 1.0700000524520874 1.5800000429153442 2.140000104904175 2.1700000762939453 3.3499999046325684 4.650000095367432 7.860000133514404 11.3100004196167 15.550000190734863 24.3799991607666  micromols	12 options
salinity2	= (ANY) 34.90299987792969 35.21699905395508 35.52199935913086 35.86399841308594 36.30099868774414 36.36199951171875 36.36899948120117 36.380001068115234 36.38100051879883 36.400001525878906 36.42399978637695 36.465999603271484  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
1.0	28.479299545288086	36.39820098876953	4.559999942779541	0.0	0.1599999964237213	0.019999999552965164	2.1700000762939453	36.400001525878906	0.0
27.0	25.950000762939453	36.360198974609375	5.179999828338623	0.009999999776482582	0.15000000596046448	0.009999999776482582	1.0700000524520874	36.36899948120117	0.0
41.0	24.056100845336914	36.37730026245117	5.110000133514404	0.009999999776482582	0.14000000059604645	0.009999999776482582	0.8500000238418579	36.38100051879883	0.0
53.0	22.440399169921875	36.35660171508789	4.769999980926514	0.009999999776482582	0.07999999821186066	0.0	0.8899999856948853	36.36199951171875	0.0
69.0	20.817800521850586	36.382598876953125	4.110000133514404	0.4699999988079071	0.09000000357627869	0.029999999329447746	1.5800000429153442	36.380001068115234	0.0
81.0	20.282899856567383	36.422698974609375	3.5299999713897705	0.15000000596046448	3.380000114440918	0.15000000596046448	2.140000104904175	36.42399978637695	0.0
100.0	18.893199920654297	36.46220016479492	2.890000104904175	0.05000000074505806	11.319999694824219	0.46000000834465027	3.3499999046325684	36.465999603271484	0.0
133.0	17.27560043334961	36.30229949951172	2.8499999046325684	0.029999999329447746	14.65999984741211	0.6399999856948853	4.650000095367432	36.30099868774414	0.0
203.0	14.248800277709961	35.86249923706055	2.7100000381469727	0.019999999552965164	19.84000015258789	0.9599999785423279	7.860000133514404	35.86399841308594	0.0
279.0	12.02560043334961	35.52259826660156	2.609999895095825	0.019999999552965164	24.559999465942383	1.1399999856948853	11.3100004196167	35.52199935913086	0.0
391.0	9.874899864196777	35.21870040893555	2.559999942779541	0.019999999552965164	28.010000228881836	1.4299999475479126	15.550000190734863	35.21699905395508	0.0
686.0	6.254899978637695	34.90629959106445	3.25	0.019999999552965164	30.299999237060547	1.690000057220459	24.3799991607666	34.90299987792969	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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