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ERDDAP > tabledap > Subset ?

Dataset Title:  "Deepwater CTD - 00830254.bdo.nc - 24.4N, -84.92W - 1983-03-13" Subscribe RSS
Institution:  Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_00830254_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   11 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
2.0 25.270000457763672 36.04999923706055 4.900000095367432 0.10000000149011612 0.07000000029802322 1.399999976158142 0.0
50.0 25.288999557495117 36.04999923706055 4.800000190734863 -99.98999786376953 0.07000000029802322 1.2000000476837158 0.0
101.0 25.089000701904297 36.08000183105469 5.099999904632568 0.20000000298023224 -99.98999786376953 1.2000000476837158 0.0
150.0 24.618999481201172 36.439998626708984 4.340000152587891 2.299999952316284 0.05000000074505806 1.2000000476837158 0.0
200.0 22.388999938964844 36.77000045776367 3.890000104904175 5.900000095367432 0.1899999976158142 1.7999999523162842 0.0
300.0 18.270000457763672 36.459999084472656 3.690000057220459 10.399999618530273 0.41999998688697815 3.299999952316284 0.0
400.0 15.5600004196167 36.04999923706055 4.090000152587891 11.600000381469727 0.4300000071525574 3.799999952316284 0.0
503.0 12.710000038146973 35.61000061035156 3.180000066757202 23.200000762939453 1.0 9.699999809265137 0.0
602.0 10.039999961853027 35.220001220703125 3.0299999713897705 29.100000381469727 1.340000033378601 14.800000190734863 0.0
800.0 7.440000057220459 34.92900085449219 3.130000114440918 33.099998474121094 2.049999952316284 21.5 0.0
1001.0 5.71999979019165 34.89899826049805 3.890000104904175 31.600000381469727 2.0 25.399999618530273 0.0
1200.0 4.821000099182129 34.939998626708984 4.699999809265137 28.700000762939453 1.409999966621399 26.600000381469727 0.0
1489.0 4.339000225067139 34.970001220703125 3.430000066757202 33.0 1.5700000524520874 23.399999618530273 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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