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Dataset Title:	"Deepwater CTD - d93f165.bdo.nc - 27.1N, -96.21W - 1993-00-04"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93f165_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 7.0 14.0 33.0 53.0 74.0 83.0 98.0 147.0 246.0 346.0 443.0  m	12 options
temperature	= (ANY) 8.727499961853027 11.373499870300293 14.034600257873535 15.952099800109863 16.758699417114258 17.177600860595703 19.520000457763672 22.75349998474121 24.145200729370117 28.168699264526367 28.923999786376953 28.925399780273438  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 35.08489990234375 35.43170166015625 35.833900451660156 36.12350082397461 36.21760177612305 36.219600677490234 36.22050094604492 36.23780059814453 36.24150085449219 36.273399353027344 36.28179931640625 36.29859924316406  PSU	12 options
oxygen	= (ANY) 2.569999933242798 2.619999885559082 2.6700000762939453 2.7899999618530273 2.880000114440918 2.9100000858306885 3.5899999141693115 4.570000171661377 4.579999923706055 4.650000095367432 4.699999809265137 5.019999980926514  milliliters per liter	12 options
nitrite	= (ANY) 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.1599999964237213 0.17000000178813934  micromols	6 options
nitrate	= (ANY) 0.009999999776482582 0.019999999552965164 0.03999999910593033 0.05999999865889549 7.260000228881836 7.730000019073486 13.800000190734863 14.539999961853027 16.139999389648438 19.829999923706055 25.079999923706055 29.530000686645508  micromols	12 options
phosphate	= (ANY) 0.0 0.009999999776482582 0.38999998569488525 0.41999998688697815 0.7300000190734863 0.800000011920929 0.8799999952316284 1.149999976158142 1.4900000095367432 1.840000033378601  micromols	10 options
silicate	= (ANY) 2.440000057220459 2.4800000190734863 2.5999999046325684 2.609999895095825 4.630000114440918 4.71999979019165 6.039999961853027 6.380000114440918 7.25 9.770000457763672 13.90999984741211 19.760000228881836  micromols	12 options
salinity2	= (ANY) 35.082000732421875 35.42399978637695 35.83100128173828 36.11899948120117 36.21200180053711 36.21799850463867 36.222999572753906 36.23699951171875 36.249000549316406 36.25199890136719 36.28300094604492 36.2859992980957  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	28.925399780273438	36.22050094604492	4.570000171661377	0.009999999776482582	0.05999999865889549	0.009999999776482582	2.5999999046325684	36.222999572753906	0.0
7.0	28.923999786376953	36.219600677490234	4.579999923706055	0.009999999776482582	0.03999999910593033	0.0	2.440000057220459	36.21799850463867	0.0
14.0	28.168699264526367	36.21760177612305	4.650000095367432	0.009999999776482582	0.009999999776482582	0.0	2.609999895095825	36.21200180053711	0.0
33.0	24.145200729370117	36.273399353027344	5.019999980926514	0.009999999776482582	0.019999999552965164	0.0	2.4800000190734863	36.28300094604492	0.0
53.0	22.75349998474121	36.28179931640625	4.699999809265137	0.17000000178813934	7.260000228881836	0.38999998569488525	4.630000114440918	36.249000549316406	0.0
74.0	19.520000457763672	36.23780059814453	3.5899999141693115	0.1599999964237213	7.730000019073486	0.41999998688697815	4.71999979019165	36.25199890136719	0.0
83.0	17.177600860595703	36.29859924316406	2.9100000858306885	0.03999999910593033	13.800000190734863	0.7300000190734863	6.039999961853027	36.2859992980957	0.0
98.0	16.758699417114258	36.24150085449219	2.880000114440918	0.029999999329447746	14.539999961853027	0.800000011920929	6.380000114440918	36.23699951171875	0.0
147.0	15.952099800109863	36.12350082397461	2.7899999618530273	0.019999999552965164	16.139999389648438	0.8799999952316284	7.25	36.11899948120117	0.0
246.0	14.034600257873535	35.833900451660156	2.6700000762939453	0.029999999329447746	19.829999923706055	1.149999976158142	9.770000457763672	35.83100128173828	0.0
346.0	11.373499870300293	35.43170166015625	2.569999933242798	0.019999999552965164	25.079999923706055	1.4900000095367432	13.90999984741211	35.42399978637695	0.0
443.0	8.727499961853027	35.08489990234375	2.619999885559082	0.019999999552965164	29.530000686645508	1.840000033378601	19.760000228881836	35.082000732421875	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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