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ERDDAP > tabledap > Subset ?

Dataset Title:  ALOHA Cabled Observatory (ACO): Bottom Pressure Recorder (BPR) Subscribe RSS
Institution:  University of Hawaii   (Dataset ID: hawaii_soest_d1bf_1535_741f)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 1)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    station ?  =  1 option: ACO
    longitude ?  =  degrees_east   1 option: -158.0062
    latitude ?  =  degrees_north   1 option: 22.7387
    depth ?  =  m   1 option: -4726.0

View:      Map of Distinct Data ?      Distinct Data Counts ?     Distinct Data ?      Related Data Counts ?     Related Data ?

 
Map of Distinct Data ?   (Refine the map and/or download the image)
Optional: Click on the map to select the closest data.
Map of Distinct 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)  

station longitude latitude depth
degrees_east degrees_north m
ACO -158.0062 22.7387 -4726.0

In total, there are 1 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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