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Dataset Title:	"Deepwater CTD - d93g067.bdo.nc - 27.97N, -91.32W - 1993-11-11"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93g067_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 13.0 29.0 43.0 57.0 68.0 87.0 117.0 147.0 177.0 217.0 261.0  m	12 options
temperature	= (ANY) 14.330400466918945 14.634900093078613 15.112099647521973 16.423799514770508 19.117000579833984 20.993799209594727 22.24329948425293 22.730100631713867 25.194400787353516 25.205900192260742 25.20599937438965 25.207700729370117  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 35.87260055541992 35.9192008972168 35.994300842285156 36.17720031738281 36.24700164794922 36.24879837036133 36.2494010925293 36.25080108642578 36.326499938964844 36.42390060424805 36.47650146484375 36.52939987182617  PSU	12 options
oxygen	= (ANY) 2.869999885559082 2.9100000858306885 2.940000057220459 2.9800000190734863 3.009999990463257 3.390000104904175 3.9100000858306885 4.400000095367432 4.71999979019165 4.739999771118164 4.809999942779541  milliliters per liter	11 options
nitrite	= (ANY) 0.0 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.12999999523162842 0.23999999463558197  micromols	7 options
nitrate	= (ANY) 0.14000000059604645 0.15000000596046448 0.1899999976158142 0.23999999463558197 1.3600000143051147 5.679999828338623 10.239999771118164 14.319999694824219 16.65999984741211 17.56999969482422 18.149999618530273  micromols	11 options
phosphate	= (ANY) 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.07999999821186066 0.2800000011920929 0.5400000214576721 0.8100000023841858 0.9800000190734863 1.0299999713897705 1.0800000429153442  micromols	10 options
silicate	= (ANY) 2.2699999809265137 2.2799999713897705 2.3399999141693115 2.5899999141693115 2.5999999046325684 2.740000009536743 3.190000057220459 4.420000076293945 6.150000095367432 7.420000076293945 8.029999732971191 10.329999923706055  micromols	12 options
salinity2	= (ANY) 35.87300109863281 35.917999267578125 35.99300003051758 36.18899917602539 36.25199890136719 36.25299835205078 36.255001068115234 36.33399963378906 36.44200134277344 36.483001708984375 36.534000396728516  PSU	11 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	25.194400787353516	36.25080108642578	4.739999771118164	0.0	0.14000000059604645	0.019999999552965164	2.5999999046325684	36.25199890136719	0.0
13.0	25.205900192260742	36.2494010925293	4.809999942779541	0.009999999776482582	0.14000000059604645	0.009999999776482582	2.3399999141693115	36.25199890136719	0.0
29.0	25.20599937438965	36.24879837036133	4.71999979019165	0.0	0.15000000596046448	0.009999999776482582	2.2799999713897705	36.25299835205078	0.0
43.0	25.207700729370117	36.24700164794922	4.809999942779541	0.009999999776482582	0.1899999976158142	0.009999999776482582	2.2699999809265137	36.255001068115234	0.0
57.0	22.730100631713867	36.326499938964844	4.400000095367432	0.23999999463558197	0.23999999463558197	0.029999999329447746	2.5899999141693115	36.33399963378906	0.0
68.0	22.24329948425293	36.42390060424805	3.9100000858306885	0.12999999523162842	1.3600000143051147	0.07999999821186066	2.740000009536743	36.44200134277344	0.0
87.0	20.993799209594727	36.52939987182617	3.390000104904175	0.03999999910593033	5.679999828338623	0.2800000011920929	3.190000057220459	36.534000396728516	0.0
117.0	19.117000579833984	36.47650146484375	3.009999990463257	0.029999999329447746	10.239999771118164	0.5400000214576721	4.420000076293945	36.483001708984375	0.0
147.0	16.423799514770508	36.17720031738281	2.9800000190734863	0.029999999329447746	14.319999694824219	0.8100000023841858	6.150000095367432	36.18899917602539	0.0
177.0	15.112099647521973	35.994300842285156	2.940000057220459	0.019999999552965164	16.65999984741211	0.9800000190734863	7.420000076293945	35.99300003051758	0.0
217.0	14.634900093078613	35.9192008972168	2.9100000858306885	0.019999999552965164	17.56999969482422	1.0299999713897705	8.029999732971191	35.917999267578125	0.0
261.0	14.330400466918945	35.87260055541992	2.869999885559082	0.029999999329447746	18.149999618530273	1.0800000429153442	10.329999923706055	35.87300109863281	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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