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ERDDAP > tabledap > Subset ?

Dataset Title:  Flow Cytometry : CHROME, PEACETIME, FUMSECK campains Subscribe RSS
Institution:  MIO UMR 7294 CNRS   (Dataset ID: CYTOBASE_CSV_9914_6de5_27d6)
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.

    nom_cruise ?  =  3 options
    sdn_ClusterName ?  =  7 options
    sdn_ClusterNameID ?  =  7 options
    Type ?  =  1 option: C
    sdn_local_cdi_id ?  =  3 options
    sdn_edmo_code ?  =  1 option: 3078
    COL_instrument ?  =  1 option: TOOL1209

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)  

nom_cruise sdn_ClusterName sdn_ClusterNameID Type sdn_local_cdi_id sdn_edmo_code COL_instrument
 
CHROME_Oct2016_FCMW Coccolithophores SDN:F02::F0200007 C FA35102016_CHROME_Oct2016_FCMW 3078 TOOL1209
CHROME_Oct2016_FCMW Cryptophytes SDN:F02::F0200006 C FA35102016_CHROME_Oct2016_FCMW 3078 TOOL1209
CHROME_Oct2016_FCMW Eukaryote nanophytoplankton SDN:F02::F0200005 C FA35102016_CHROME_Oct2016_FCMW 3078 TOOL1209
CHROME_Oct2016_FCMW Eukaryote picophytoplankton SDN:F02::F0200004 C FA35102016_CHROME_Oct2016_FCMW 3078 TOOL1209
CHROME_Oct2016_FCMW Microphytoplankton SDN:F02::F0200008 C FA35102016_CHROME_Oct2016_FCMW 3078 TOOL1209
CHROME_Oct2016_FCMW Prochlorococcus SDN:F02::F0200002 C FA35102016_CHROME_Oct2016_FCMW 3078 TOOL1209
FUMSECK_FCMW Cryptophytes SDN:F02::F0200006 C FA35042019_FUMSECK_FCMW 3078 TOOL1209
FUMSECK_FCMW Eukaryote nanophytoplankton SDN:F02::F0200005 C FA35042019_FUMSECK_FCMW 3078 TOOL1209
FUMSECK_FCMW Eukaryote picophytoplankton SDN:F02::F0200004 C FA35042019_FUMSECK_FCMW 3078 TOOL1209
FUMSECK_FCMW Microphytoplankton SDN:F02::F0200008 C FA35042019_FUMSECK_FCMW 3078 TOOL1209
FUMSECK_FCMW Prochlorococcus SDN:F02::F0200002 C FA35042019_FUMSECK_FCMW 3078 TOOL1209
PEACETIME_FCMW Coccolithophores SDN:F02::F0200007 C FA35052017_PEACETIME_FCMW 3078 TOOL1209
PEACETIME_FCMW Cryptophytes SDN:F02::F0200006 C FA35052017_PEACETIME_FCMW 3078 TOOL1209
PEACETIME_FCMW Eukaryote nanophytoplankton SDN:F02::F0200005 C FA35052017_PEACETIME_FCMW 3078 TOOL1209
PEACETIME_FCMW Eukaryote picophytoplankton SDN:F02::F0200004 C FA35052017_PEACETIME_FCMW 3078 TOOL1209
PEACETIME_FCMW Microphytoplankton SDN:F02::F0200008 C FA35052017_PEACETIME_FCMW 3078 TOOL1209
PEACETIME_FCMW Prochlorococcus SDN:F02::F0200002 C FA35052017_PEACETIME_FCMW 3078 TOOL1209
PEACETIME_FCMW Synechococcus SDN:F02::F0200003 C FA35052017_PEACETIME_FCMW 3078 TOOL1209

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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