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Dataset Title:	"Deepwater CTD - d94j168.bdo.nc - 27.84N, -94.81W - 1994-11-13"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94j168_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 14.0 23.0 38.0 49.0 56.0 66.0 76.0 89.0 100.0 128.0 229.0  m	12 options
temperature	= (ANY) 14.214500427246094 16.88089942932129 18.781099319458008 19.679899215698242 20.598600387573242 22.13010025024414 24.440500259399414 26.143800735473633 26.462600708007812 26.470699310302734 26.472700119018555 26.477399826049805  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 35.858299255371094 36.10639953613281 36.10749816894531 36.10940170288086 36.21540069580078 36.243900299072266 36.25090026855469 36.33409881591797 36.38140106201172 36.3921012878418 36.420501708984375  PSU	11 options
oxygen	= (ANY) 2.819999933242798 2.869999885559082 2.940000057220459 3.3399999141693115 3.700000047683716 4.25 4.460000038146973 4.579999923706055 4.610000133514404 4.630000114440918  milliliters per liter	10 options
nitrite	= (ANY) 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.05999999865889549 0.07000000029802322 0.1599999964237213 0.20000000298023224  micromols	8 options
nitrate	= (ANY) 0.029999999329447746 0.09000000357627869 0.12999999523162842 0.23999999463558197 0.2800000011920929 3.200000047683716 6.639999866485596 11.25 15.420000076293945 19.639999389648438  micromols	10 options
phosphate	= (ANY) 0.029999999329447746 0.03999999910593033 0.05000000074505806 0.09000000357627869 0.10000000149011612 0.20999999344348907 0.3499999940395355 0.550000011920929 0.800000011920929 1.0499999523162842  micromols	10 options
silicate	= (ANY) 1.0099999904632568 1.0499999523162842 1.090000033378601 1.1699999570846558 1.2799999713897705 1.5199999809265137 1.6200000047683716 2.2699999809265137 2.359999895095825 3.1500000953674316 4.369999885559082 6.829999923706055  micromols	12 options
salinity2	= (ANY) 35.854000091552734 36.099998474121094 36.10100173950195 36.10200119018555 36.11199951171875 36.189998626708984 36.24399948120117 36.2599983215332 36.332000732421875 36.37300109863281 36.38199996948242 36.40800094604492  PSU	12 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	26.462600708007812	36.10940170288086	4.579999923706055	0.019999999552965164	0.23999999463558197	0.029999999329447746	1.1699999570846558	36.10200119018555	0.0
14.0	26.472700119018555	36.10749816894531	4.610000133514404	0.019999999552965164	0.12999999523162842	0.029999999329447746	1.090000033378601	36.099998474121094	0.0
23.0	26.477399826049805	36.10749816894531	4.630000114440918	0.019999999552965164	0.09000000357627869	0.03999999910593033	1.0499999523162842	36.10100173950195	0.0
38.0	26.470699310302734	36.10639953613281	4.610000133514404	0.019999999552965164	0.09000000357627869	0.05000000074505806	1.0099999904632568	36.11199951171875	0.0
49.0	26.143800735473633	36.21540069580078	4.579999923706055	0.029999999329447746	0.09000000357627869	0.03999999910593033	1.2799999713897705	36.189998626708984	0.0
56.0	24.440500259399414	36.25090026855469	4.460000038146973	0.1599999964237213	0.029999999329447746	0.09000000357627869	2.359999895095825	36.2599983215332	0.0
66.0	22.13010025024414	36.33409881591797	4.25	0.20000000298023224	0.2800000011920929	0.10000000149011612	1.5199999809265137	36.332000732421875	0.0
76.0	20.598600387573242	36.38140106201172	3.700000047683716	0.07000000029802322	3.200000047683716	0.20999999344348907	1.6200000047683716	36.37300109863281	0.0
89.0	19.679899215698242	36.3921012878418	3.3399999141693115	0.07000000029802322	6.639999866485596	0.3499999940395355	2.2699999809265137	36.38199996948242	0.0
100.0	18.781099319458008	36.420501708984375	2.940000057220459	0.05999999865889549	11.25	0.550000011920929	3.1500000953674316	36.40800094604492	0.0
128.0	16.88089942932129	36.243900299072266	2.819999933242798	0.03999999910593033	19.639999389648438	1.0499999523162842	6.829999923706055	36.24399948120117	0.0
229.0	14.214500427246094	35.858299255371094	2.869999885559082	0.05000000074505806	15.420000076293945	0.800000011920929	4.369999885559082	35.854000091552734	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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