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Dataset Title:	"Deepwater CTD - d94h144.bdo.nc - 26.02N, -95.97W - 1994-05-05"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94h144_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 16.0 34.0 57.0 69.0 89.0 120.0 154.0 225.0 305.0 415.0 1020.0  m	12 options
temperature	= (ANY) 4.796500205993652 9.891200065612793 12.068099975585938 14.507399559020996 17.0216007232666 18.989200592041016 20.72920036315918 22.92259979248047 23.272199630737305 23.431800842285156 24.100400924682617 25.144699096679688  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 32.212501525878906 34.93199920654297 35.21329879760742 35.52159881591797 35.893001556396484 36.265499114990234 36.415199279785156 36.417301177978516 36.435699462890625 36.43949890136719 36.490299224853516 36.54330062866211  PSU	12 options
oxygen	= (ANY) 2.5399999618530273 2.569999933242798 2.7100000381469727 2.9100000858306885 3.0199999809265137 3.319999933242798 4.21999979019165 4.630000114440918 4.880000114440918 4.909999847412109 4.920000076293945 4.929999828338623  milliliters per liter	12 options
nitrite	= (ANY) 0.03999999910593033 0.05000000074505806 0.05999999865889549 0.07000000029802322 0.07999999821186066 0.15000000596046448  micromols	6 options
nitrate	= (ANY) 0.6800000071525574 0.8100000023841858 0.9399999976158142 0.9700000286102295 1.3899999856948853 7.210000038146973 11.220000267028809 15.25 19.1299991607666 22.8799991607666 26.270000457763672 27.530000686645508  micromols	12 options
phosphate	= (ANY) 0.029999999329447746 0.05999999865889549 0.3499999940395355 0.5600000023841858 0.7799999713897705 1.1100000143051147 1.440000057220459 1.7400000095367432 1.7699999809265137  micromols	9 options
silicate	= (ANY) 0.029999999329447746 0.03999999910593033 0.09000000357627869 0.15000000596046448 1.2100000381469727 2.2100000381469727 3.859999895095825 6.610000133514404 10.050000190734863 14.479999542236328 25.479999542236328  micromols	11 options
salinity2	= (ANY) 32.3390007019043 34.93600082397461 35.220001220703125 35.52899932861328 35.89799880981445 36.27299880981445 36.422000885009766 36.428001403808594 36.44200134277344 36.44599914550781 36.500999450683594 36.555999755859375  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	25.144699096679688	32.212501525878906	4.920000076293945	0.05999999865889549	0.9700000286102295	0.029999999329447746	0.09000000357627869	32.3390007019043	0.0
16.0	24.100400924682617	36.415199279785156	4.929999828338623	0.05000000074505806	0.9399999976158142	0.029999999329447746	0.15000000596046448	36.422000885009766	0.0
34.0	23.431800842285156	36.43949890136719	4.880000114440918	0.07999999821186066	0.8100000023841858	0.029999999329447746	0.09000000357627869	36.44599914550781	0.0
57.0	23.272199630737305	36.435699462890625	4.909999847412109	0.15000000596046448	0.6800000071525574	0.029999999329447746	0.03999999910593033	36.44200134277344	0.0
69.0	22.92259979248047	36.417301177978516	4.630000114440918	0.07000000029802322	1.3899999856948853	0.05999999865889549	0.029999999329447746	36.428001403808594	0.0
89.0	20.72920036315918	36.54330062866211	3.319999933242798	0.05000000074505806	7.210000038146973	0.3499999940395355	1.2100000381469727	36.555999755859375	0.0
120.0	18.989200592041016	36.490299224853516	3.0199999809265137	0.03999999910593033	11.220000267028809	0.5600000023841858	2.2100000381469727	36.500999450683594	0.0
154.0	17.0216007232666	36.265499114990234	2.9100000858306885	0.03999999910593033	15.25	0.7799999713897705	3.859999895095825	36.27299880981445	0.0
225.0	14.507399559020996	35.893001556396484	2.7100000381469727	0.03999999910593033	19.1299991607666	1.1100000143051147	6.610000133514404	35.89799880981445	0.0
305.0	12.068099975585938	35.52159881591797	2.5399999618530273	0.03999999910593033	22.8799991607666	1.440000057220459	10.050000190734863	35.52899932861328	1.0
415.0	9.891200065612793	35.21329879760742	2.569999933242798	0.05000000074505806	27.530000686645508	1.7400000095367432	14.479999542236328	35.220001220703125	0.0
1020.0	4.796500205993652	34.93199920654297	4.21999979019165	0.03999999910593033	26.270000457763672	1.7699999809265137	25.479999542236328	34.93600082397461	0.0

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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