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Dataset Title:	"Deepwater CTD - d93f045.bdo.nc - 27.94N, -91.55W - 1993-07-29"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93f045_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 5.0 8.0 19.0 29.0 48.0 69.0 90.0 118.0 148.0 187.0 224.0  m	12 options
temperature	= (ANY) 12.63860034942627 14.567099571228027 16.93269920349121 19.56049919128418 21.574199676513672 24.020200729370117 28.465299606323242 29.2189998626709 29.252599716186523 29.91990089416504 30.298799514770508 30.569499969482422  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 31.387300491333008 34.39070129394531 35.079498291015625 35.558101654052734 35.61869812011719 35.73929977416992 35.90489959716797 36.13019943237305 36.23440170288086 36.25619888305664 36.27090072631836 36.44139862060547  PSU	12 options
oxygen	= (ANY) 2.819999933242798 2.940000057220459 3.0299999713897705 3.559999942779541 4.599999904632568 4.619999885559082 4.630000114440918 4.639999866485596 4.659999847412109 4.78000020980835 5.139999866485596  milliliters per liter	11 options
nitrite	= (ANY) 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.09000000357627869 0.10000000149011612  micromols	6 options
nitrate	= (ANY) 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.09000000357627869 0.1899999976158142 0.3400000035762787 8.210000038146973 14.210000038146973 18.3700008392334 21.510000228881836  micromols	10 options
phosphate	= (ANY) 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.05999999865889549 0.44999998807907104 0.800000011920929 1.090000033378601 1.309999942779541  micromols	9 options
silicate	= (ANY) 1.6799999475479126 1.7999999523162842 2.0299999713897705 2.1700000762939453 2.2699999809265137 2.299999952316284 2.309999942779541 2.3299999237060547 3.569999933242798 5.650000095367432 7.920000076293945 10.199999809265137  micromols	12 options
salinity2	= (ANY) 33.042999267578125 34.48899841308594 35.119998931884766 35.62200164794922 35.625999450683594 35.75699996948242 35.8650016784668 36.15800094604492 36.20100021362305 36.25899887084961 36.28200149536133 36.46900177001953  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	30.569499969482422	31.387300491333008	4.659999847412109	0.019999999552965164	0.1899999976158142	0.05999999865889549	2.1700000762939453	33.042999267578125	0.0
5.0	30.298799514770508	34.39070129394531	4.630000114440918	0.009999999776482582	0.09000000357627869	0.029999999329447746	2.2699999809265137	34.48899841308594	0.0
8.0	29.91990089416504	35.079498291015625	4.639999866485596	0.009999999776482582	0.05000000074505806	0.019999999552965164	2.3299999237060547	35.119998931884766	0.0
19.0	29.252599716186523	35.558101654052734	4.599999904632568	0.009999999776482582	0.03999999910593033	0.009999999776482582	2.309999942779541	35.62200164794922	0.0
29.0	29.2189998626709	35.73929977416992	4.630000114440918	0.009999999776482582	0.03999999910593033	0.009999999776482582	2.299999952316284	35.75699996948242	0.0
48.0	28.465299606323242	36.13019943237305	4.78000020980835	0.019999999552965164	0.029999999329447746	0.019999999552965164	2.0299999713897705	36.15800094604492	0.0
69.0	24.020200729370117	36.27090072631836	5.139999866485596	0.019999999552965164	0.029999999329447746	0.009999999776482582	1.6799999475479126	36.28200149536133	0.0
90.0	21.574199676513672	36.23440170288086	4.619999885559082	0.10000000149011612	0.3400000035762787	0.03999999910593033	1.7999999523162842	36.25899887084961	0.0
118.0	19.56049919128418	36.44139862060547	3.559999942779541	0.09000000357627869	8.210000038146973	0.44999998807907104	3.569999933242798	36.46900177001953	0.0
148.0	16.93269920349121	36.25619888305664	3.0299999713897705	0.03999999910593033	14.210000038146973	0.800000011920929	5.650000095367432	36.20100021362305	0.0
187.0	14.567099571228027	35.90489959716797	2.940000057220459	0.029999999329447746	18.3700008392334	1.090000033378601	7.920000076293945	35.8650016784668	0.0
224.0	12.63860034942627	35.61869812011719	2.819999933242798	0.029999999329447746	21.510000228881836	1.309999942779541	10.199999809265137	35.625999450683594	1.0

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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