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Dataset Title:	"Deepwater CTD - d94j146.bdo.nc - 26.01N, -96.19W - 1994-11-11"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94j146_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 48.0 61.0 74.0 83.0 98.0 110.0 132.0 198.0 286.0 377.0 648.0  m	12 options
temperature	= (ANY) 6.649400234222412 10.69480037689209 12.041799545288086 14.330100059509277 17.050800323486328 18.543500900268555 19.806299209594727 20.977100372314453 22.47920036315918 24.375200271606445 26.475099563598633 26.48069953918457  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 34.917701721191406 35.330299377441406 35.52579879760742 35.874900817871094 36.07379913330078 36.07440185546875 36.26959991455078 36.355899810791016 36.359901428222656 36.37329864501953 36.40660095214844 36.41279983520508  PSU	12 options
oxygen	= (ANY) 2.5799999237060547 2.640000104904175 2.7699999809265137 2.799999952316284 2.819999933242798 3.0999999046325684 3.240000009536743 3.809999942779541 4.420000076293945 4.610000133514404 4.619999885559082 5.03000020980835  milliliters per liter	12 options
nitrite	= (ANY) 0.0 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.09000000357627869  micromols	6 options
nitrate	= (ANY) 0.2199999988079071 0.25 0.33000001311302185 0.6299999952316284 3.069999933242798 7.489999771118164 12.239999771118164 14.59000015258789 19.299999237060547 23.790000915527344 26.329999923706055 29.940000534057617  micromols	12 options
phosphate	= (ANY) 0.03999999910593033 0.05999999865889549 0.07000000029802322 0.1599999964237213 0.36000001430511475 0.6100000143051147 0.7699999809265137 1.1399999856948853 1.409999966621399 1.559999942779541 1.899999976158142  micromols	11 options
silicate	= (ANY) 0.5199999809265137 0.9800000190734863 1.2699999809265137 1.2999999523162842 1.5099999904632568 2.25 3.380000114440918 4.079999923706055 6.690000057220459 9.760000228881836 12.319999694824219 21.579999923706055  micromols	12 options
salinity2	= (ANY) 34.915000915527344 35.323001861572266 35.52299880981445 35.869998931884766 36.06800079345703 36.07899856567383 36.25400161743164 36.349998474121094 36.354000091552734 36.36800003051758 36.404998779296875 36.40599822998047  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	26.48069953918457	36.07440185546875	4.619999885559082	0.0	0.33000001311302185	0.05999999865889549	1.5099999904632568	36.06800079345703	0.0
48.0	26.475099563598633	36.07379913330078	4.610000133514404	0.0	0.2199999988079071	0.03999999910593033	1.2699999809265137	36.07899856567383	0.0
61.0	24.375200271606445	36.359901428222656	5.03000020980835	0.0	0.25	0.03999999910593033	0.5199999809265137	36.349998474121094	0.0
74.0	22.47920036315918	36.355899810791016	4.420000076293945	0.09000000357627869	0.6299999952316284	0.07000000029802322	0.9800000190734863	36.354000091552734	0.0
83.0	20.977100372314453	36.37329864501953	3.809999942779541	0.03999999910593033	3.069999933242798	0.1599999964237213	1.2999999523162842	36.36800003051758	0.0
98.0	19.806299209594727	36.41279983520508	3.240000009536743	0.029999999329447746	7.489999771118164	0.36000001430511475	2.25	36.404998779296875	0.0
110.0	18.543500900268555	36.40660095214844	2.799999952316284	0.019999999552965164	12.239999771118164	0.6100000143051147	3.380000114440918	36.40599822998047	0.0
132.0	17.050800323486328	36.26959991455078	2.819999933242798	0.009999999776482582	14.59000015258789	0.7699999809265137	4.079999923706055	36.25400161743164	0.0
198.0	14.330100059509277	35.874900817871094	2.7699999809265137	0.009999999776482582	19.299999237060547	1.1399999856948853	6.690000057220459	35.869998931884766	0.0
286.0	12.041799545288086	35.52579879760742	2.640000104904175	0.009999999776482582	23.790000915527344	1.409999966621399	9.760000228881836	35.52299880981445	0.0
377.0	10.69480037689209	35.330299377441406	2.5799999237060547	0.009999999776482582	26.329999923706055	1.559999942779541	12.319999694824219	35.323001861572266	0.0
648.0	6.649400234222412	34.917701721191406	3.0999999046325684	0.019999999552965164	29.940000534057617	1.899999976158142	21.579999923706055	34.915000915527344	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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