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Dataset Title:	"Deepwater CTD - d94j093.bdo.nc - 27.46N, -94.27W - 1994-11-00"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94j093_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) 0.0 29.0 54.0 63.0 74.0 102.0 119.0 144.0 207.0 329.0 434.0 986.0  m	12 options
temperature	= (ANY) 4.8582000732421875 9.826499938964844 11.892499923706055 14.383999824523926 17.03890037536621 18.479999542236328 19.70639991760254 22.725400924682617 23.5049991607666 26.02910041809082 26.730100631713867 26.731800079345703  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 34.93320083618164 35.20940017700195 35.50130081176758 35.88130187988281 36.17210006713867 36.17290115356445 36.26319885253906 36.28969955444336 36.33089828491211 36.3578987121582 36.39950180053711 36.40639877319336  PSU	12 options
oxygen	= (ANY) 2.5999999046325684 2.6600000858306885 2.740000009536743 2.869999885559082 2.9100000858306885 3.2799999713897705 4.150000095367432 4.610000133514404 4.619999885559082 4.630000114440918 4.75 4.840000152587891  milliliters per liter	12 options
nitrite	= (ANY) 0.009999999776482582 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.05999999865889549  micromols	6 options
nitrate	= (ANY) 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.10999999940395355 0.1599999964237213 7.050000190734863 11.880000114440918 14.420000076293945 19.670000076293945 24.540000915527344 27.6299991607666 28.860000610351562  micromols	12 options
phosphate	= (ANY) 0.029999999329447746 0.03999999910593033 0.36000001430511475 0.6299999952316284 0.7799999713897705 1.090000033378601 1.4199999570846558 1.6799999475479126 1.7200000286102295  micromols	9 options
silicate	= (ANY) 0.8299999833106995 0.8799999952316284 0.9100000262260437 1.1200000047683716 1.1799999475479126 2.2799999713897705 3.180000066757202 4.150000095367432 7.050000190734863 10.5600004196167 14.470000267028809 25.149999618530273  micromols	12 options
salinity2	= (ANY) 34.93000030517578 35.20500183105469 35.49300003051758 35.86800003051758 36.16699981689453 36.167999267578125 36.249000549316406 36.284000396728516 36.33300018310547 36.35499954223633 36.39699935913086  PSU	11 options
qualityFlag	= (ANY) 0.0	1 option: 0.0

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
0.0	26.730100631713867	36.17290115356445	4.610000133514404	0.009999999776482582	0.1599999964237213	0.03999999910593033	1.1200000047683716	36.16699981689453	0.0
29.0	26.731800079345703	36.17210006713867	4.630000114440918	0.009999999776482582	0.10999999940395355	0.029999999329447746	0.8799999952316284	36.167999267578125	0.0
54.0	26.02910041809082	36.28969955444336	4.840000152587891	0.009999999776482582	0.029999999329447746	0.03999999910593033	0.9100000262260437	36.284000396728516	0.0
63.0	23.5049991607666	36.33089828491211	4.75	0.05999999865889549	0.05000000074505806	0.03999999910593033	1.1799999475479126	36.33300018310547	0.0
74.0	22.725400924682617	36.3578987121582	4.619999885559082	0.05999999865889549	0.03999999910593033	0.029999999329447746	0.8299999833106995	36.35499954223633	0.0
102.0	19.70639991760254	36.39950180053711	3.2799999713897705	0.05000000074505806	7.050000190734863	0.36000001430511475	2.2799999713897705	36.39699935913086	0.0
119.0	18.479999542236328	36.40639877319336	2.9100000858306885	0.03999999910593033	11.880000114440918	0.6299999952316284	3.180000066757202	36.39699935913086	0.0
144.0	17.03890037536621	36.26319885253906	2.869999885559082	0.029999999329447746	14.420000076293945	0.7799999713897705	4.150000095367432	36.249000549316406	0.0
207.0	14.383999824523926	35.88130187988281	2.740000009536743	0.019999999552965164	19.670000076293945	1.090000033378601	7.050000190734863	35.86800003051758	0.0
329.0	11.892499923706055	35.50130081176758	2.6600000858306885	0.029999999329447746	24.540000915527344	1.4199999570846558	10.5600004196167	35.49300003051758	0.0
434.0	9.826499938964844	35.20940017700195	2.5999999046325684	0.019999999552965164	28.860000610351562	1.6799999475479126	14.470000267028809	35.20500183105469	0.0
986.0	4.8582000732421875	34.93320083618164	4.150000095367432	0.029999999329447746	27.6299991607666	1.7200000286102295	25.149999618530273	34.93000030517578	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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