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ERDDAP > tabledap > Subset ?

Dataset Title:  "Deepwater CTD - 00830681.bdo.nc - 25.6N, -85.2W - 1983-03-20" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_00830681_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: 13)
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   13 options
    temperature ?  =  degree_C   13 options
    salinity ?  =  PSU   12 options
    oxygen ?  =  milliliters per liter   12 options
    nitrite ?  =  not-measured   1 option:
    nitrate ?  =  micromols   13 options
    phosphate ?  =  micromols   12 options
    silicate ?  =  micromols   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 not-measured micromols micromols micromols PSU
4.0 21.339000701904297 36.08000183105469 4.96999979019165 -99.98999786376953 -99.98999786376953 0.8999999761581421 0.0
50.0 20.719999313354492 36.130001068115234 4.949999809265137 0.20000000298023224 0.009999999776482582 0.8999999761581421 0.0
99.0 20.111000061035156 36.25 4.0 5.699999809265137 0.25 2.299999952316284 0.0
149.0 16.229000091552734 36.138999938964844 -99.98999786376953 15.800000190734863 0.6100000143051147 5.699999809265137 0.0
200.0 13.329999923706055 35.709999084472656 -99.98999786376953 21.700000762939453 0.8999999761581421 9.100000381469727 0.0
300.0 10.609999656677246 35.29999923706055 2.6500000953674316 27.200000762939453 1.6299999952316284 14.0 0.0
401.0 8.8100004196167 35.058998107910156 2.7200000286102295 30.399999618530273 1.8600000143051147 18.100000381469727 0.0
500.0 7.130000114440918 34.90999984741211 2.9000000953674316 32.20000076293945 2.0199999809265137 22.299999237060547 0.0
598.0 6.340000152587891 34.888999938964844 3.259999990463257 31.899999618530273 2.009999990463257 24.600000381469727 0.0
700.0 5.769999980926514 34.888999938964844 3.5 30.799999237060547 1.9800000190734863 26.700000762939453 0.0
800.0 5.258999824523926 34.91899871826172 3.7699999809265137 29.299999237060547 1.8600000143051147 26.600000381469727 0.0
900.0 4.940000057220459 34.92900085449219 4.199999809265137 27.700000762939453 1.850000023841858 26.799999237060547 0.0
1000.0 4.71999979019165 34.939998626708984 4.449999809265137 27.299999237060547 1.7300000190734863 18.100000381469727 0.0

In total, there are 13 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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