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ERDDAP > tabledap > Subset ?

Dataset Title:  B01 Met - Meteorology   RSS
Institution:  Univ. of Maine   (Dataset ID: B01_met_all)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background | Data Access Form | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 80)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    air_temperature_qc ?  =  1   6 options
    barometric_pressure_qc ?  =  1   6 options
    wind_gust_qc ?  =  1   7 options
    wind_speed_qc ?  =  1   7 options
    wind_direction_qc ?  =  1   7 options
    visibility_qc ?  =  1   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)  

air_temperature_qc barometric_pressure_qc wind_gust_qc wind_speed_qc wind_direction_qc visibility_qc
1 1 1 1 1 1
0.0
0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 1.0
0.0 0.0 0.0 40.0 0.0
0.0 1.0 1.0 0.0 0.0
0.0 1.0 1.0 1.0 0.0
0.0 1.0 2.0 2.0 0.0
0.0 1.0 40.0 0.0 0.0
0.0 2.0 2.0 2.0 0.0
0.0 40.0 40.0 40.0 0.0
0.0 99.0 99.0 99.0 0.0
0.0 0 0.0 0.0 0.0 0.0
0.0 0 0.0 0.0 0.0 1.0
0.0 0 0.0 0.0 0.0 2.0
0.0 0 0.0 0.0 0.0 99.0
0.0 0 0.0 0.0 2.0 0.0
0.0 0 0.0 0.0 40.0 0.0
0.0 0 0.0 0.0 99.0 0.0
0.0 0 2.0 2.0 2.0 0.0
0.0 0 2.0 2.0 2.0 1.0
0.0 0 39.0 39.0 39.0 0.0
0.0 0 39.0 39.0 40.0 0.0
0.0 0 40.0 0.0 0.0 0.0
0.0 0 40.0 40.0 0.0 0.0
0.0 0 40.0 40.0 40.0 0.0
0.0 0 99.0 2.0 2.0 0.0
0.0 0 99.0 99.0 0.0 0.0
0.0 0 99.0 99.0 99.0 0.0
0.0 1 0.0 0.0 0.0 0.0
0.0 1 0.0 0.0 0.0 1.0
0.0 1 0.0 0.0 1.0 1.0
0.0 1 0.0 0.0 40.0 1.0
0.0 1 0.0 0.0 99.0 0.0
0.0 2 0.0 0.0 0.0 0.0
0.0 2 0.0 0.0 0.0 2.0
0.0 2 0.0 0.0 2.0 0.0
0.0 2 2.0 2.0 2.0 0.0
0.0 2 40.0 40.0 0.0 0.0
0.0 2 99.0 2.0 2.0 0.0
0.0 2 99.0 99.0 0.0 0.0
0.0 2 99.0 99.0 99.0 0.0
0.0 40 0.0 0.0 0.0 0.0
0.0 40 0.0 0.0 0.0 2.0
0.0 40 0.0 0.0 2.0 0.0
0.0 40 0.0 0.0 99.0 0.0
0.0 40 2.0 2.0 2.0 0.0
0.0 40 40.0 40.0 0.0 2.0
0.0 40 40.0 40.0 40.0 40.0
0.0 99 0.0 0.0 0.0 0.0
0.0 99 0.0 0.0 0.0 2.0
0.0 99 0.0 0.0 2.0 0.0
0.0 99 1.0 1.0 1.0 0.0
0.0 99 2.0 2.0 2.0 0.0
0.0 99 2.0 2.0 2.0 1.0
0.0 99 2.0 2.0 2.0 2.0
1.0 0.0 0.0 0.0 1.0
1.0 0 0.0 0.0 0.0 0.0
1.0 1 40.0 40.0 2.0 1.0
2.0 0 0.0 0.0 0.0 0.0
2.0 0 0.0 0.0 0.0 2.0
2.0 0 0.0 0.0 0.0 99.0
2.0 0 1.0 0.0 0.0 2.0
2.0 0 40.0 40.0 40.0 2.0
2.0 40 0.0 0.0 0.0 2.0
2.0 40 1.0 0.0 0.0 2.0
40.0 0 0.0 0.0 0.0 0.0
40.0 1 40.0 40.0 99.0 40.0
40.0 2 2.0 2.0 2.0 40.0
40.0 2 40.0 40.0 40.0 40.0
40.0 40 40.0 40.0 2.0 40.0
40.0 40 40.0 40.0 40.0 40.0
40.0 40 40.0 40.0 99.0 40.0
99.0 0 0.0 0.0 0.0 0.0
99.0 0 0.0 0.0 0.0 1.0
99.0 2 0.0 0.0 0.0 0.0
99.0 2 99.0 99.0 99.0 0.0
99.0 40 0.0 0.0 0.0 0.0
99.0 40 40.0 40.0 40.0 40.0
99.0 99 99.0 99.0 40.0 99.0

In total, there are 80 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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