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ERDDAP > tabledap > Subset ?

Dataset Title:  "Deepwater CTD - 00830263.bdo.nc - 24.23N, -85.25W - 1983-03-13" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_00830263_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   13 options
    nitrite ?  =  not-measured   1 option:
    nitrate ?  =  micromols   12 options
    phosphate ?  =  micromols   12 options
    silicate ?  =  micromols   12 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
2.0 24.969999313354492 36.0890007019043 -99.98999786376953 -99.98999786376953 0.009999999776482582 1.100000023841858 0.0
51.0 24.698999404907227 36.11000061035156 4.860000133514404 -99.98999786376953 0.029999999329447746 1.100000023841858 0.0
100.0 24.110000610351562 36.308998107910156 4.949999809265137 0.6000000238418579 -99.98999786376953 0.6000000238418579 0.0
150.0 24.02899932861328 36.31999969482422 4.900000095367432 0.800000011920929 -99.98999786376953 0.699999988079071 0.0
200.0 22.75 36.77000045776367 4.25 5.300000190734863 0.2199999988079071 1.7000000476837158 0.0
300.0 19.111000061035156 36.54999923706055 3.7100000381469727 9.5 0.46000000834465027 2.9000000953674316 0.0
400.0 17.288999557495117 36.31999969482422 3.869999885559082 11.899999618530273 0.5600000023841858 3.9000000953674316 0.0
499.0 15.010000228881836 35.959999084472656 3.3299999237060547 18.200000762939453 0.7400000095367432 6.599999904632568 0.0
601.0 12.210000038146973 35.52899932861328 3.380000114440918 25.200000762939453 1.1100000143051147 11.199999809265137 0.0
800.0 8.109999656677246 34.9900016784668 3.8399999141693115 32.70000076293945 1.9800000190734863 19.899999618530273 0.0
1000.0 5.920000076293945 34.888999938964844 4.340000152587891 32.29999923706055 1.9900000095367432 25.299999237060547 0.0
1200.0 4.960999965667725 34.92900085449219 4.320000171661377 29.600000381469727 1.850000023841858 26.600000381469727 0.0
1498.0 4.36899995803833 34.970001220703125 3.1500000953674316 30.799999237060547 1.399999976158142 18.0 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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