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Dataset Title:  "Deepwater CTD - 00419550.bdo.nc - 26.67N, -92.98W - 1964-02-28" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_00419550_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: 19)
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   19 options
    temperature ?  =  degree_C   18 options
    salinity ?  =  PSU   17 options
    oxygen ?  =  milliliters per liter   18 options
    nitrite ?  =  not-measured   1 option:
    nitrate ?  =  not-measured   1 option:
    phosphate ?  =  micromols   18 options
    silicate ?  =  not-measured   1 option:
    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 not-measured not-measured micromols not-measured PSU
0.0 19.209999084472656 36.56800079345703 4.579999923706055 0.0 0.0
23.0 18.8799991607666 36.56800079345703 4.630000114440918 0.0 0.0
46.0 18.829999923706055 36.564998626708984 4.440000057220459 0.029999999329447746 0.0
69.0 18.809999465942383 36.56100082397461 4.440000057220459 0.07000000029802322 0.0
92.0 18.760000228881836 36.55799865722656 4.570000171661377 0.05999999865889549 0.0
116.0 18.760000228881836 36.56100082397461 4.349999904632568 0.10000000149011612 0.0
139.0 18.700000762939453 36.54399871826172 4.510000228881836 0.11999999731779099 0.0
186.0 15.479999542236328 36.013999938964844 2.7100000381469727 1.0 0.0
233.0 13.850000381469727 35.775001525878906 2.630000114440918 1.0499999523162842 0.0
280.0 12.670000076293945 35.5890007019043 2.5399999618530273 1.100000023841858 0.0
376.0 10.140000343322754 35.22700119018555 2.559999942779541 1.5199999809265137 0.0
474.0 8.449999809265137 35.01499938964844 2.4600000381469727 1.7400000095367432 0.0
571.0 7.230000019073486 34.92300033569336 2.6700000762939453 1.7999999523162842 0.0
670.0 6.340000152587891 34.89400100708008 2.740000009536743 1.7799999713897705 0.0
770.0 5.650000095367432 34.89500045776367 3.299999952316284 1.8600000143051147 0.0
970.0 4.869999885559082 34.93299865722656 3.6600000858306885 1.4800000190734863 0.0
1170.0 4.360000133514404 34.96200180053711 4.28000020980835 1.4500000476837158 0.0
1370.0 4.199999809265137 34.9739990234375 4.170000076293945 1.3200000524520874 0.0
1570.0 4.179999828338623 34.97700119018555 3.9000000953674316 1.5299999713897705 0.0

In total, there are 19 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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