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Dataset Title:	"Deepwater CTD - d94j164.bdo.nc - 27.65N, -95.71W - 1994-11-13"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94j164_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 12.0 34.0 49.0 63.0 70.0 75.0 84.0 93.0 136.0 173.0 239.0  m	12 options
temperature	= (ANY) -9.0 14.51039981842041 15.563899993896484 16.981700897216797 18.670499801635742 19.53190040588379 20.085399627685547 20.70789909362793 22.305999755859375 24.15690040588379 25.648799896240234 25.6658992767334  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) -9.0 35.02199935913086 35.024898529052734 35.905601501464844 36.0630989074707 36.2578010559082 36.36410140991211 36.367801666259766 36.372798919677734 36.39690017700195 36.39789962768555 36.4202995300293  PSU	12 options
oxygen	= (ANY) 2.75 2.7899999618530273 2.799999952316284 2.809999942779541 3.0899999141693115 3.4000000953674316 3.7200000286102295 4.260000228881836 4.460000038146973 4.690000057220459 4.699999809265137 4.840000152587891  milliliters per liter	12 options
nitrite	= (ANY) 0.009999999776482582 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.07000000029802322 0.09000000357627869 0.11999999731779099 0.1899999976158142 0.20999999344348907  micromols	9 options
nitrate	= (ANY) 0.019999999552965164 0.10000000149011612 0.1599999964237213 0.28999999165534973 1.899999976158142 4.730000019073486 8.489999771118164 12.199999809265137 15.329999923706055 17.270000457763672 19.40999984741211  micromols	11 options
phosphate	= (ANY) 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.1599999964237213 0.25999999046325684 0.4300000071525574 0.6600000262260437 0.8199999928474426 0.9700000286102295 1.1299999952316284  micromols	10 options
silicate	= (ANY) 0.800000011920929 0.8899999856948853 1.600000023841858 1.7200000286102295 1.9900000095367432 2.440000057220459 2.640000104904175 4.03000020980835 4.639999866485596 5.730000019073486 6.929999828338623  micromols	11 options
salinity2	= (ANY) 35.01599884033203 35.02000045776367 35.89799880981445 36.03799819946289 36.07099914550781 36.26100158691406 36.35100173950195 36.36399841308594 36.36600112915039 36.382999420166016 36.39799880981445 36.4109992980957  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
1.0	25.648799896240234	35.02199935913086	4.699999809265137	0.009999999776482582	0.28999999165534973	0.05000000074505806	1.7200000286102295	35.01599884033203	0.0
12.0	25.6658992767334	35.024898529052734	4.690000057220459	0.009999999776482582	0.10000000149011612	0.03999999910593033	1.600000023841858	35.02000045776367	0.0
34.0	-9.0	-9.0	4.260000228881836	0.11999999731779099	0.019999999552965164	0.05000000074505806	2.440000057220459	36.03799819946289	0.0
49.0	24.15690040588379	36.36410140991211	4.840000152587891	0.1899999976158142	0.019999999552965164	0.029999999329447746	0.8899999856948853	36.36399841308594	0.0
63.0	22.305999755859375	36.372798919677734	4.460000038146973	0.20999999344348907	0.1599999964237213	0.05000000074505806	0.800000011920929	36.36600112915039	0.0
70.0	20.70789909362793	36.367801666259766	3.7200000286102295	0.09000000357627869	1.899999976158142	0.1599999964237213	1.9900000095367432	36.35100173950195	0.0
75.0	20.085399627685547	36.39789962768555	3.4000000953674316	0.07000000029802322	4.730000019073486	0.25999999046325684	1.9900000095367432	36.382999420166016	0.0
84.0	19.53190040588379	36.4202995300293	3.0899999141693115	0.05000000074505806	8.489999771118164	0.4300000071525574	2.640000104904175	36.4109992980957	0.0
93.0	18.670499801635742	36.39690017700195	2.75	0.03999999910593033	12.199999809265137	0.6600000262260437	4.03000020980835	36.39799880981445	0.0
136.0	16.981700897216797	36.2578010559082	2.799999952316284	0.029999999329447746	15.329999923706055	0.8199999928474426	4.639999866485596	36.26100158691406	0.0
173.0	15.563899993896484	36.0630989074707	2.809999942779541	0.029999999329447746	17.270000457763672	0.9700000286102295	5.730000019073486	36.07099914550781	0.0
239.0	14.51039981842041	35.905601501464844	2.7899999618530273	0.029999999329447746	19.40999984741211	1.1299999952316284	6.929999828338623	35.89799880981445	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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