ERDDAP > tabledap > Subset

Dataset Title:	AdriaClim Indicators | ARPAE | Monthly minimum, mean, and maximum values for dissolved oxygen: 2009-2016
Institution:	ARPAE   (Dataset ID: ARPAE_f099_1bf5_9110)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Data Access Form | Files | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 88)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

time	= (ANY) 2009-06-01 2009-07-01 2009-08-01 2009-09-01 2009-10-01 2009-11-01 2009-12-01 2010-01-01 2010-02-01 2010-03-01 2010-04-01 2010-05-01 2010-06-01 2010-07-01 2010-08-01 2010-09-01 2010-10-01 2010-11-01 2010-12-01 2011-01-01 2011-02-01 2011-03-01 2011-04-01 2011-05-01 2011-06-01 2011-07-01 2011-08-01 2011-09-01 2011-10-01 2011-11-01 2011-12-01 2012-01-01 2012-02-01 2012-03-01 2012-04-01 2012-05-01 2012-06-01 2012-07-01 2012-08-01 2012-09-01 2012-10-01 2012-11-01 2012-12-01 2013-01-01 2013-02-01 2013-03-01 2013-04-01 2013-05-01 2013-06-01 2013-07-01 2013-08-01 2013-09-01 2013-10-01 2013-11-01 2013-12-01 2014-01-01 2014-02-01 2014-03-01 2014-04-01 2014-05-01 2014-06-01 2014-07-01 2014-08-01 2014-09-01 2014-10-01 2014-11-01 2014-12-01 2015-01-01 2015-02-01 2015-03-01 2015-04-01 2015-05-01 2015-06-01 2015-07-01 2015-08-01 2015-09-01 2015-10-01 2015-11-01 2015-12-01 2016-01-01 2016-02-01 2016-03-01 2016-04-01 2016-05-01 2016-06-01 2016-07-01 2016-08-01 2016-09-01	88 options
longitude	= (ANY) 12.249444  degrees_east	1 option: 12.249444
latitude	= (ANY) 44.676667  degrees_north	1 option: 44.676667

View:      Map of Distinct Data      Distinct Data Counts     Distinct Data  0 10 100 1000 10000 100000      Related Data Counts     Related Data  0 10 100 1000 10000 100000

 

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

 

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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.
 

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Distinct Data   (Metadata)    (Refine the data subset and/or download the data)  

time	longitude	latitude
UTC	degrees_east	degrees_north
2009-06-01	12.249444	44.676667
2009-07-01	12.249444	44.676667
2009-08-01	12.249444	44.676667
2009-09-01	12.249444	44.676667
2009-10-01	12.249444	44.676667
2009-11-01	12.249444	44.676667
2009-12-01	12.249444	44.676667
2010-01-01	12.249444	44.676667
2010-02-01	12.249444	44.676667
2010-03-01	12.249444	44.676667
2010-04-01	12.249444	44.676667
2010-05-01	12.249444	44.676667
2010-06-01	12.249444	44.676667
2010-07-01	12.249444	44.676667
2010-08-01	12.249444	44.676667
2010-09-01	12.249444	44.676667
2010-10-01	12.249444	44.676667
2010-11-01	12.249444	44.676667
2010-12-01	12.249444	44.676667
2011-01-01	12.249444	44.676667
2011-02-01	12.249444	44.676667
2011-03-01	12.249444	44.676667
2011-04-01	12.249444	44.676667
2011-05-01	12.249444	44.676667
2011-06-01	12.249444	44.676667
2011-07-01	12.249444	44.676667
2011-08-01	12.249444	44.676667
2011-09-01	12.249444	44.676667
2011-10-01	12.249444	44.676667
2011-11-01	12.249444	44.676667
2011-12-01	12.249444	44.676667
2012-01-01	12.249444	44.676667
2012-02-01	12.249444	44.676667
2012-03-01	12.249444	44.676667
2012-04-01	12.249444	44.676667
2012-05-01	12.249444	44.676667
2012-06-01	12.249444	44.676667
2012-07-01	12.249444	44.676667
2012-08-01	12.249444	44.676667
2012-09-01	12.249444	44.676667
2012-10-01	12.249444	44.676667
2012-11-01	12.249444	44.676667
2012-12-01	12.249444	44.676667
2013-01-01	12.249444	44.676667
2013-02-01	12.249444	44.676667
2013-03-01	12.249444	44.676667
2013-04-01	12.249444	44.676667
2013-05-01	12.249444	44.676667
2013-06-01	12.249444	44.676667
2013-07-01	12.249444	44.676667
2013-08-01	12.249444	44.676667
2013-09-01	12.249444	44.676667
2013-10-01	12.249444	44.676667
2013-11-01	12.249444	44.676667
2013-12-01	12.249444	44.676667
2014-01-01	12.249444	44.676667
2014-02-01	12.249444	44.676667
2014-03-01	12.249444	44.676667
2014-04-01	12.249444	44.676667
2014-05-01	12.249444	44.676667
2014-06-01	12.249444	44.676667
2014-07-01	12.249444	44.676667
2014-08-01	12.249444	44.676667
2014-09-01	12.249444	44.676667
2014-10-01	12.249444	44.676667
2014-11-01	12.249444	44.676667
2014-12-01	12.249444	44.676667
2015-01-01	12.249444	44.676667
2015-02-01	12.249444	44.676667
2015-03-01	12.249444	44.676667
2015-04-01	12.249444	44.676667
2015-05-01	12.249444	44.676667
2015-06-01	12.249444	44.676667
2015-07-01	12.249444	44.676667
2015-08-01	12.249444	44.676667
2015-09-01	12.249444	44.676667
2015-10-01	12.249444	44.676667
2015-11-01	12.249444	44.676667
2015-12-01	12.249444	44.676667
2016-01-01	12.249444	44.676667
2016-02-01	12.249444	44.676667
2016-03-01	12.249444	44.676667
2016-04-01	12.249444	44.676667
2016-05-01	12.249444	44.676667
2016-06-01	12.249444	44.676667
2016-07-01	12.249444	44.676667
2016-08-01	12.249444	44.676667
2016-09-01	12.249444	44.676667

In total, there are 88 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.
 

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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.
 

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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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