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ERDDAP > tabledap > Subset ?

Dataset Title:  Sound Pressure Level time series at OBSEA seabed observatory (quality-
controlled)
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Institution:  UPC - Universitat Politècnica de Catalunya   (Dataset ID: OBSEA_seabed_station_SPL_L1b)
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: 56)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    platform_id ?  =  1 option: OBSEA
    sensor_id ?  =  1 option: NAXYS_SN0010
    depth ?  =  m   1 option: 20.0
    SPL_125_QC ?  =  5 options
    SPL_2000_QC ?  =  5 options
    SPL_63_QC ?  =  5 options
    SPL_all_QC ?  =  5 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)  

platform_id sensor_id depth SPL_125_QC SPL_2000_QC SPL_63_QC SPL_all_QC
m
OBSEA NAXYS_SN0010 20.0 1 1 1 1
OBSEA NAXYS_SN0010 20.0 1 1 1 2
OBSEA NAXYS_SN0010 20.0 1 1 1 3
OBSEA NAXYS_SN0010 20.0 1 1 1 4
OBSEA NAXYS_SN0010 20.0 1 1 1 9
OBSEA NAXYS_SN0010 20.0 1 1 3 1
OBSEA NAXYS_SN0010 20.0 1 1 3 2
OBSEA NAXYS_SN0010 20.0 1 1 3 3
OBSEA NAXYS_SN0010 20.0 1 1 9 2
OBSEA NAXYS_SN0010 20.0 1 1 9 9
OBSEA NAXYS_SN0010 20.0 1 3 1 1
OBSEA NAXYS_SN0010 20.0 1 3 1 2
OBSEA NAXYS_SN0010 20.0 1 3 1 3
OBSEA NAXYS_SN0010 20.0 1 3 3 1
OBSEA NAXYS_SN0010 20.0 1 3 3 2
OBSEA NAXYS_SN0010 20.0 1 3 3 3
OBSEA NAXYS_SN0010 20.0 1 9 1 1
OBSEA NAXYS_SN0010 20.0 1 9 1 2
OBSEA NAXYS_SN0010 20.0 2 2 2 2
OBSEA NAXYS_SN0010 20.0 3 1 1 1
OBSEA NAXYS_SN0010 20.0 3 1 1 2
OBSEA NAXYS_SN0010 20.0 3 1 1 3
OBSEA NAXYS_SN0010 20.0 3 1 3 1
OBSEA NAXYS_SN0010 20.0 3 1 3 2
OBSEA NAXYS_SN0010 20.0 3 1 3 3
OBSEA NAXYS_SN0010 20.0 3 1 4 2
OBSEA NAXYS_SN0010 20.0 3 1 4 3
OBSEA NAXYS_SN0010 20.0 3 3 1 1
OBSEA NAXYS_SN0010 20.0 3 3 1 2
OBSEA NAXYS_SN0010 20.0 3 3 1 3
OBSEA NAXYS_SN0010 20.0 3 3 3 1
OBSEA NAXYS_SN0010 20.0 3 3 3 2
OBSEA NAXYS_SN0010 20.0 3 3 3 3
OBSEA NAXYS_SN0010 20.0 3 3 4 2
OBSEA NAXYS_SN0010 20.0 3 3 4 3
OBSEA NAXYS_SN0010 20.0 3 3 4 4
OBSEA NAXYS_SN0010 20.0 3 4 3 2
OBSEA NAXYS_SN0010 20.0 3 4 3 3
OBSEA NAXYS_SN0010 20.0 4 1 3 2
OBSEA NAXYS_SN0010 20.0 4 1 3 3
OBSEA NAXYS_SN0010 20.0 4 1 4 2
OBSEA NAXYS_SN0010 20.0 4 1 4 3
OBSEA NAXYS_SN0010 20.0 4 3 3 2
OBSEA NAXYS_SN0010 20.0 4 3 3 3
OBSEA NAXYS_SN0010 20.0 4 3 4 2
OBSEA NAXYS_SN0010 20.0 4 3 4 3
OBSEA NAXYS_SN0010 20.0 4 3 4 4
OBSEA NAXYS_SN0010 20.0 4 4 4 2
OBSEA NAXYS_SN0010 20.0 9 1 1 2
OBSEA NAXYS_SN0010 20.0 9 1 9 1
OBSEA NAXYS_SN0010 20.0 9 1 9 2
OBSEA NAXYS_SN0010 20.0 9 1 9 9
OBSEA NAXYS_SN0010 20.0 9 9 1 1
OBSEA NAXYS_SN0010 20.0 9 9 1 2
OBSEA NAXYS_SN0010 20.0 9 9 9 1
OBSEA NAXYS_SN0010 20.0 9 9 9 2

In total, there are 56 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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