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Dataset Title:	"Deepwater CTD - d94h157.bdo.nc - 26.53N, -96.33W - 1994-05-06"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94h157_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 24.0 49.0 60.0 70.0 85.0 98.0 116.0 157.0 226.0 247.0 295.0  m	12 options
temperature	= (ANY) 12.881799697875977 13.765000343322754 14.392600059509277 16.850099563598633 18.547000885009766 19.15169906616211 19.564800262451172 20.040000915527344 20.362300872802734 20.653900146484375 22.194799423217773 24.162799835205078  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 29.896900177001953 35.64780044555664 35.78160095214844 35.87919998168945 36.235801696777344 36.24290084838867 36.277801513671875 36.28219985961914 36.28620147705078 36.28839874267578 36.38240051269531 36.38370132446289  PSU	12 options
oxygen	= (ANY) 2.6600000858306885 2.7200000286102295 2.7300000190734863 2.799999952316284 3.190000057220459 3.549999952316284 4.659999847412109 5.019999980926514 5.110000133514404 5.179999828338623 5.190000057220459 5.21999979019165  milliliters per liter	12 options
nitrite	= (ANY) 0.009999999776482582 0.019999999552965164 0.03999999910593033 0.05000000074505806 0.05999999865889549 0.07000000029802322 0.20999999344348907  micromols	7 options
nitrate	= (ANY) 0.029999999329447746 0.05000000074505806 0.05999999865889549 0.10000000149011612 0.12999999523162842 2.200000047683716 7.849999904632568 10.979999542236328 14.569999694824219 19.030000686645508 20.190000534057617 21.65999984741211  micromols	12 options
phosphate	= (ANY) 0.019999999552965164 0.029999999329447746 0.10999999940395355 0.4000000059604645 0.550000011920929 0.7799999713897705 1.100000023841858 1.1799999475479126 1.2999999523162842  micromols	9 options
silicate	= (ANY) 1.75 1.7599999904632568 1.7799999713897705 1.7999999523162842 1.809999942779541 2.440000057220459 4.03000020980835 5.090000152587891 6.980000019073486 9.640000343322754 10.350000381469727 11.720000267028809  micromols	12 options
salinity2	= (ANY) 30.26799964904785 35.652000427246094 35.78799819946289 35.8849983215332 36.24399948120117 36.25 36.28200149536133 36.28300094604492 36.28499984741211 36.28900146484375 36.39099884033203 36.40399932861328  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	24.162799835205078	29.896900177001953	5.019999980926514	0.019999999552965164	0.05000000074505806	0.029999999329447746	1.75	30.26799964904785	0.0
24.0	22.194799423217773	36.24290084838867	5.110000133514404	0.009999999776482582	0.029999999329447746	0.029999999329447746	1.809999942779541	36.25	0.0
49.0	20.653900146484375	36.28839874267578	5.190000057220459	0.009999999776482582	0.05999999865889549	0.019999999552965164	1.7599999904632568	36.28200149536133	0.0
60.0	20.362300872802734	36.28620147705078	5.21999979019165	0.009999999776482582	0.10000000149011612	0.019999999552965164	1.7799999713897705	36.28300094604492	0.0
70.0	20.040000915527344	36.277801513671875	5.179999828338623	0.20999999344348907	0.12999999523162842	0.019999999552965164	1.7999999523162842	36.28499984741211	0.0
85.0	19.564800262451172	36.28219985961914	4.659999847412109	0.07000000029802322	2.200000047683716	0.10999999940395355	2.440000057220459	36.28900146484375	0.0
98.0	19.15169906616211	36.38240051269531	3.549999952316284	0.03999999910593033	7.849999904632568	0.4000000059604645	4.03000020980835	36.40399932861328	0.0
116.0	18.547000885009766	36.38370132446289	3.190000057220459	0.03999999910593033	10.979999542236328	0.550000011920929	5.090000152587891	36.39099884033203	0.0
157.0	16.850099563598633	36.235801696777344	2.799999952316284	0.03999999910593033	14.569999694824219	0.7799999713897705	6.980000019073486	36.24399948120117	0.0
226.0	14.392600059509277	35.87919998168945	2.7300000190734863	0.03999999910593033	19.030000686645508	1.100000023841858	9.640000343322754	35.8849983215332	0.0
247.0	13.765000343322754	35.78160095214844	2.7200000286102295	0.05000000074505806	20.190000534057617	1.1799999475479126	10.350000381469727	35.78799819946289	0.0
295.0	12.881799697875977	35.64780044555664	2.6600000858306885	0.05999999865889549	21.65999984741211	1.2999999523162842	11.720000267028809	35.652000427246094	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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