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Dataset Title:  "Deepwater CTD - 90g10102.bdo.nc - 28.36N, -89.64W - 1990-07-22" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_90g10102_bdo)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 11)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    depth ?  =  m   11 options
    temperature ?  =  degree_C   11 options
    salinity ?  =  PSU   11 options
    oxygen ?  =  milliliters per liter   11 options
    nitrite ?  =  micromols per liter   8 options
    nitrate ?  =  micromols   10 options
    phosphate ?  =  micromols per liter   11 options
    silicate ?  =  micromols per liter   11 options
    salinity2 ?  =  PSU   1 option:
    qualityFlag ?  =  1 option: 0.0

View:      Map of All Related Data ?      Distinct Data Counts ?     Distinct Data ?      Related Data Counts ?     Related Data ?

 
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.
 


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.

 


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 PSU milliliters per liter micromols per liter micromols micromols per liter micromols per liter PSU
1.0 28.59000015258789 32.10200119018555 4.558000087738037 0.05999999865889549 0.20000000298023224 0.05000000074505806 2.5999999046325684 0.0
27.0 26.489999771118164 35.9010009765625 4.645999908447266 0.07999999821186066 0.30000001192092896 0.10000000149011612 5.199999809265137 0.0
51.0 22.280000686645508 36.28499984741211 4.960999965667725 0.10000000149011612 0.30000001192092896 0.07999999821186066 3.700000047683716 0.0
74.0 20.25 36.38600158691406 4.2170000076293945 0.2199999988079071 2.799999952316284 0.1899999976158142 4.0 0.0
100.0 18.43000030517578 36.40999984741211 3.2039999961853027 0.11999999731779099 11.100000381469727 0.30000001192092896 6.0 0.0
147.0 16.350000381469727 36.20600128173828 3.2929999828338623 0.10000000149011612 12.5 0.800000011920929 7.0 0.0
194.0 14.449999809265137 35.87699890136719 3.187999963760376 0.11999999731779099 17.200000762939453 1.0399999618530273 9.100000381469727 0.0
247.0 12.949999809265137 35.64699935913086 2.884000062942505 0.14000000059604645 21.700000762939453 1.2899999618530273 12.600000381469727 0.0
299.0 11.420000076293945 35.417999267578125 2.7739999294281006 0.15000000596046448 26.600000381469727 1.4900000095367432 14.899999618530273 0.0
400.0 9.729999542236328 35.17499923706055 2.739000082015991 0.17000000178813934 30.0 1.7200000286102295 18.200000762939453 0.0
776.0 8.109999656677246 34.98099899291992 2.8499999046325684 0.17000000178813934 32.79999923706055 1.8799999952316284 21.799999237060547 0.0

In total, there are 11 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.
 


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.
 


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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