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Dataset Title:	"Deepwater CTD - d93e211.bdo.nc - 27.84N, -94.59W - 1993-05-10"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d93e211_bdo)
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: 12)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

depth	= (ANY) 2.0 9.0 24.0 33.0 45.0 53.0 63.0 83.0 108.0 146.0 198.0 270.0  m	12 options
temperature	= (ANY) 13.20199966430664 15.06760025024414 17.380599975585938 19.029499053955078 19.097900390625 20.672199249267578 21.81839942932129 22.156299591064453 23.77720069885254 24.466299057006836 24.534900665283203 24.567699432373047  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 34.232200622558594 34.366798400878906 35.29970169067383 35.35499954223633 35.44879913330078 35.70389938354492 35.76969909667969 35.88359832763672 35.98780059814453 36.0452995300293 36.05659866333008 36.293701171875  PSU	12 options
oxygen	= (ANY) 2.6600000858306885 2.759999990463257 2.799999952316284 3.990000009536743 4.099999904632568 4.289999961853027 4.349999904632568 4.5 4.809999942779541 4.820000171661377 4.840000152587891 4.860000133514404  milliliters per liter	12 options
nitrite	= (ANY) 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.05999999865889549 0.20000000298023224 0.3799999952316284 0.44999998807907104 0.49000000953674316 0.7300000190734863  micromols	9 options
nitrate	= (ANY) 0.019999999552965164 0.05000000074505806 0.05999999865889549 0.09000000357627869 0.46000000834465027 1.4800000190734863 1.659999966621399 2.0 4.389999866485596 13.869999885559082 17.809999465942383 21.549999237060547  micromols	12 options
phosphate	= (ANY) 0.029999999329447746 0.09000000357627869 0.12999999523162842 0.1599999964237213 0.17000000178813934 0.2800000011920929 0.75 1.0099999904632568 1.2999999523162842  micromols	9 options
silicate	= (ANY) 1.7400000095367432 2.869999885559082 2.880000114440918 3.130000114440918 3.7899999618530273 4.440000057220459 4.53000020980835 4.659999847412109 5.53000020980835 7.159999847412109 7.820000171661377 9.960000038146973  micromols	12 options
salinity2	= (ANY) 34.25299835205078 34.369998931884766 34.935001373291016 35.36399841308594 35.61199951171875 35.70500183105469 35.7869987487793 35.9640007019043 35.97100067138672 35.98099899291992 35.987998962402344 36.29899978637695  PSU	12 options
qualityFlag	= (ANY) 0.0 1.0	2 options

View:      Map of All Related 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 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.
 

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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)  

depth	temperature	salinity	oxygen	nitrite	nitrate	phosphate	silicate	salinity2	qualityFlag
m	degree_C (potential temperature from ctd)	PSU	milliliters per liter	micromols	micromols	micromols	micromols	PSU
2.0	24.466299057006836	34.232200622558594	4.860000133514404	0.05000000074505806	0.05999999865889549	0.029999999329447746	2.880000114440918	34.25299835205078	0.0
9.0	24.534900665283203	34.366798400878906	4.809999942779541	0.029999999329447746	0.05000000074505806	0.029999999329447746	2.869999885559082	34.369998931884766	0.0
24.0	23.77720069885254	35.35499954223633	4.820000171661377	0.05000000074505806	0.09000000357627869	0.029999999329447746	3.130000114440918	34.935001373291016	0.0
33.0	24.567699432373047	36.0452995300293	4.840000152587891	0.05999999865889549	0.019999999552965164	0.029999999329447746	1.7400000095367432	35.97100067138672	0.0
45.0	22.156299591064453	35.44879913330078	4.5	0.44999998807907104	0.46000000834465027	0.09000000357627869	4.440000057220459	35.61199951171875	0.0
53.0	20.672199249267578	35.29970169067383	4.099999904632568	0.7300000190734863	1.659999966621399	0.1599999964237213	7.159999847412109	35.36399841308594	0.0
63.0	21.81839942932129	36.05659866333008	4.289999961853027	0.3799999952316284	1.4800000190734863	0.12999999523162842	3.7899999618530273	35.9640007019043	0.0
83.0	19.029499053955078	35.76969909667969	4.349999904632568	0.49000000953674316	2.0	0.17000000178813934	4.53000020980835	35.7869987487793	0.0
108.0	19.097900390625	35.88359832763672	3.990000009536743	0.20000000298023224	4.389999866485596	0.2800000011920929	4.659999847412109	35.98099899291992	0.0
146.0	17.380599975585938	36.293701171875	2.799999952316284	0.05000000074505806	13.869999885559082	0.75	5.53000020980835	36.29899978637695	0.0
198.0	15.06760025024414	35.98780059814453	2.759999990463257	0.03999999910593033	17.809999465942383	1.0099999904632568	7.820000171661377	35.987998962402344	0.0
270.0	13.20199966430664	35.70389938354492	2.6600000858306885	0.05000000074505806	21.549999237060547	1.2999999523162842	9.960000038146973	35.70500183105469	1.0

In total, there are 12 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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