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Dataset Title:	"Deepwater CTD - 00596891.bdo.nc - 21.82N, -85.65W - 1970-04-20"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_00596891_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 50.0 70.0 90.0 100.0 120.0 140.0 160.0 180.0 200.0 230.0 260.0 300.0 350.0 400.0 449.0 499.0 549.0 577.0 676.0 775.0 849.0 923.0 1123.0 1372.0 1621.0 1995.0 2045.0  m	28 options
temperature	= (ANY) 4.119999885559082 4.179999828338623 4.239999771118164 4.400000095367432 4.75 5.5 6.159999847412109 7.059999942779541 8.390000343322754 10.300000190734863 10.609999656677246 12.029999732971191 13.479999542236328 14.489999771118164 15.949999809265137 17.15999984741211 18.719999313354492 19.65999984741211 21.100000381469727 22.3799991607666 23.780000686645508 25.34000015258789 25.459999084472656 26.079999923706055 26.719999313354492 27.100000381469727 27.360000610351562  degree_C	27 options
salinity	= (ANY) 34.87099838256836 34.88999938964844 34.891998291015625 34.94200134277344 34.96200180053711 34.972999572753906 34.98500061035156 34.986000061035156 34.99800109863281 35.231998443603516 35.270999908447266 35.47700119018555 35.70199966430664 35.832000732421875 35.867000579833984 35.87099838256836 35.87300109863281 35.92900085449219 35.99399948120117 36.12099838256836 36.31399917602539 36.36000061035156 36.54499816894531 36.63999938964844 36.694000244140625 36.75 36.75699996948242  PSU	27 options
oxygen	= (ANY) 2.799999952316284 2.9200000762939453 3.059999942779541 3.190000057220459 3.25 3.299999952316284 3.3499999046325684 3.5399999618530273 3.5799999237060547 3.619999885559082 3.7100000381469727 3.7300000190734863 3.75 3.819999933242798 3.8299999237060547 4.269999980926514 4.300000190734863 4.659999847412109 4.699999809265137 4.710000038146973 4.75 4.820000171661377 4.900000095367432 5.03000020980835 5.639999866485596 5.949999809265137  milliliters per liter	26 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 4.0 5.0 7.0 9.0 12.0 15.0 17.0 20.0 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	27.360000610351562	35.832000732421875	5.03000020980835				1.0		0.0
50.0	27.360000610351562	35.832000732421875	4.900000095367432				1.0		0.0
70.0	27.100000381469727	35.87099838256836	4.75				1.0		0.0
90.0	26.719999313354492	35.92900085449219	4.699999809265137				1.0		0.0
100.0	26.079999923706055	35.867000579833984	4.820000171661377				1.0		0.0
120.0	25.459999084472656	35.99399948120117	4.659999847412109				1.0		0.0
140.0	25.34000015258789	36.36000061035156	4.269999980926514				1.0		0.0
160.0	23.780000686645508	36.694000244140625	3.619999885559082				1.0		0.0
180.0	22.3799991607666	36.75699996948242	3.819999933242798				1.0		0.0
200.0	21.100000381469727	36.75	3.5399999618530273				1.0		0.0
230.0	19.65999984741211	36.63999938964844	3.75				2.0		0.0
260.0	18.719999313354492	36.54499816894531	3.7100000381469727				2.0		0.0
300.0	17.15999984741211	36.31399917602539	3.7300000190734863				3.0		0.0
350.0	15.949999809265137	36.12099838256836	3.5799999237060547				4.0		0.0
400.0	14.489999771118164	35.87300109863281	3.7100000381469727				5.0		0.0
449.0	13.479999542236328	35.70199966430664	3.190000057220459				7.0		0.0
499.0	12.029999732971191	35.47700119018555	3.25				9.0		0.0
549.0	10.609999656677246	35.270999908447266	2.9200000762939453				12.0		0.0
577.0	10.300000190734863	35.231998443603516	3.059999942779541				12.0		0.0
676.0	8.390000343322754	34.99800109863281	2.799999952316284				17.0		0.0
775.0	7.059999942779541	34.891998291015625	3.299999952316284				20.0		0.0
849.0	6.159999847412109	34.87099838256836	3.3499999046325684				22.0		1.0
923.0	5.5	34.88999938964844	3.8299999237060547				22.0		0.0
1123.0	4.75	34.94200134277344	4.300000190734863				23.0		0.0
1372.0	4.400000095367432	34.96200180053711	4.820000171661377				22.0		0.0
1621.0	4.239999771118164	34.972999572753906	4.710000038146973				22.0		0.0
1995.0	4.179999828338623	34.986000061035156	5.949999809265137				17.0		0.0
2045.0	4.119999885559082	34.98500061035156	5.639999866485596				15.0		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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