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ERDDAP > tabledap > Subset ?

Dataset Title:  "Deepwater CTD - 00376095.bdo.nc - 21.88N, -85.1W - 1962-06-12" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_00376095_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: 18)
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   18 options
    temperature ?  =  degree_C   18 options
    salinity ?  =  PSU   18 options
    oxygen ?  =  milliliters per liter   16 options
    nitrite ?  =  not-measured   1 option:
    nitrate ?  =  not-measured   1 option:
    phosphate ?  =  micromols   14 options
    silicate ?  =  not-measured   1 option:
    salinity2 ?  =  PSU   1 option:
    qualityFlag ?  =  2 options

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
1.0 28.079999923706055 36.189998626708984 4.809999942779541 0.019999999552965164 0.0
10.0 28.06999969482422 36.24800109863281 4.760000228881836 0.03999999910593033 0.0
19.0 28.09000015258789 36.2140007019043 4.679999828338623 0.03999999910593033 0.0
29.0 27.600000381469727 36.231998443603516 4.739999771118164 0.019999999552965164 0.0
49.0 27.209999084472656 36.22700119018555 4.849999904632568 0.019999999552965164 0.0
73.0 26.790000915527344 36.255001068115234 4.869999885559082 0.019999999552965164 0.0
98.0 26.190000534057617 36.26599884033203 4.860000133514404 0.05000000074505806 0.0
146.0 24.469999313354492 36.65599822998047 3.9800000190734863 0.12999999523162842 0.0
195.0 20.93000030517578 36.696998596191406 3.7300000190734863 0.3499999940395355 0.0
243.0 19.239999771118164 36.58000183105469 3.869999885559082 0.36000001430511475 0.0
292.0 17.780000686645508 36.41699981689453 3.9800000190734863 0.44999998807907104 0.0
389.0 15.510000228881836 36.04999923706055 3.0399999618530273 0.75 0.0
486.0 12.850000381469727 35.61800003051758 3.119999885559082 1.2300000190734863 0.0
583.0 11.069999694824219 35.3489990234375 3.7100000381469727 1.5 0.0
680.0 9.140000343322754 35.08599853515625 3.059999942779541 1.8799999952316284 0.0
776.0 7.900000095367432 34.970001220703125 3.059999942779541 1.9600000381469727 0.0
970.0 5.25 34.95199966430664 4.21999979019165 1.7899999618530273 1.0
1269.0 4.289999961853027 34.965999603271484 5.210000038146973 1.5099999904632568 0.0

In total, there are 18 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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