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Dataset Title:	"Deepwater CTD - 00596643.bdo.nc - 22.0N, -85.18W - 1970-04-16"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_00596643_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: 28)
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) 0.0 25.0 50.0 75.0 100.0 120.0 140.0 160.0 180.0 200.0 230.0 260.0 300.0 350.0 400.0 450.0 500.0 550.0 646.0 746.0 846.0 946.0 1046.0 1146.0 1247.0 1347.0 1447.0 1497.0  m	28 options
temperature	= (ANY) 4.269999980926514 4.28000020980835 4.320000171661377 4.440000057220459 4.679999828338623 5.090000152587891 5.599999904632568 6.820000171661377 7.909999847412109 9.609999656677246 11.489999771118164 13.0600004196167 14.34000015258789 15.279999732971191 16.440000534057617 17.600000381469727 18.469999313354492 19.420000076293945 20.6200008392334 22.280000686645508 24.0 24.200000762939453 24.260000228881836 24.989999771118164 25.280000686645508 25.860000610351562 26.34000015258789 26.809999465942383  degree_C	28 options
salinity	= (ANY) -99.98999786376953 34.91400146484375 34.928001403808594 34.941001892089844 34.94900131225586 34.95899963378906 34.972999572753906 34.974998474121094 35.143001556396484 35.38399887084961 35.64099884033203 35.854000091552734 35.87699890136719 35.90800094604492 35.922000885009766 35.94900131225586 35.95399856567383 36.01100158691406 36.013999938964844 36.154998779296875 36.21200180053711 36.39699935913086 36.50899887084961 36.551998138427734 36.608001708984375 36.68199920654297 36.71500015258789  PSU	27 options
oxygen	= (ANY) -99.98999786376953 2.9000000953674316 3.1500000953674316 3.2699999809265137 3.4200000762939453 3.450000047683716 3.5999999046325684 3.6600000858306885 3.700000047683716 3.75 3.9800000190734863 4.0 4.289999961853027 4.349999904632568 4.449999809265137 4.789999961853027 4.809999942779541 4.840000152587891 4.860000133514404 4.900000095367432 5.050000190734863 5.110000133514404 5.300000190734863  milliliters per liter	23 options
nitrite	= (ANY)  not-measured	1 option:
nitrate	= (ANY)  not-measured	1 option:
phosphate	= (ANY)  not-measured	1 option:
silicate	= (ANY) 1.0 2.0 3.0 5.0 6.0 8.0 11.0 14.0 19.0 20.0 21.0 22.0 23.0  micromols	13 options
salinity2	= (ANY)  PSU	1 option:
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	PSU	milliliters per liter	not-measured	not-measured	not-measured	micromols	PSU
0.0	26.809999465942383	35.90800094604492	4.860000133514404				1.0		0.0
25.0	26.34000015258789	35.87699890136719	4.840000152587891				1.0		0.0
50.0	25.860000610351562	35.922000885009766	4.789999961853027				1.0		0.0
75.0	25.280000686645508	35.95399856567383	4.809999942779541				1.0		0.0
100.0	24.989999771118164	35.94900131225586	4.900000095367432				1.0		0.0
120.0	24.260000228881836	36.01100158691406	4.789999961853027				1.0		0.0
140.0	24.200000762939453	36.154998779296875	4.289999961853027				1.0		0.0
160.0	24.0	36.551998138427734	3.700000047683716				1.0		0.0
180.0	22.280000686645508	36.71500015258789	3.75				1.0		0.0
200.0	20.6200008392334	36.68199920654297	3.4200000762939453				2.0		0.0
230.0	19.420000076293945	36.608001708984375	3.700000047683716				2.0		0.0
260.0	18.469999313354492	36.50899887084961	3.75				2.0		0.0
300.0	17.600000381469727	36.39699935913086	3.9800000190734863				2.0		0.0
350.0	16.440000534057617	36.21200180053711	3.5999999046325684				3.0		0.0
400.0	15.279999732971191	36.013999938964844	3.6600000858306885				5.0		0.0
450.0	14.34000015258789	35.854000091552734	3.2699999809265137				6.0		0.0
500.0	13.0600004196167	35.64099884033203	-99.98999786376953				8.0		0.0
550.0	11.489999771118164	35.38399887084961	-99.98999786376953				11.0		0.0
646.0	9.609999656677246	35.143001556396484	3.1500000953674316				14.0		0.0
746.0	7.909999847412109	34.941001892089844	2.9000000953674316				19.0		0.0
846.0	6.820000171661377	-99.98999786376953	3.450000047683716				21.0		0.0
946.0	5.599999904632568	34.91400146484375	4.0				23.0		1.0
1046.0	5.090000152587891	34.928001403808594	4.349999904632568				22.0		0.0
1146.0	4.679999828338623	34.94900131225586	4.449999809265137				23.0		0.0
1247.0	4.440000057220459	34.95899963378906	4.789999961853027				22.0		0.0
1347.0	4.320000171661377	34.972999572753906	5.110000133514404				21.0		0.0
1447.0	4.28000020980835	34.974998474121094	5.050000190734863				20.0		0.0
1497.0	4.269999980926514	34.974998474121094	5.300000190734863				20.0		0.0

In total, there are 28 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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