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Dataset Title:	"Deepwater CTD - d94h165.bdo.nc - 27.71N, -95.5W - 1994-05-07"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94h165_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) 1.0 14.0 33.0 43.0 53.0 66.0 89.0 109.0 126.0 170.0 244.0 307.0  m	12 options
temperature	= (ANY) 12.081399917602539 14.233099937438965 16.956300735473633 18.534900665283203 19.45490074157715 19.64310073852539 19.899999618530273 20.21660041809082 20.81049919128418 21.38450050354004 22.55739974975586 25.270099639892578  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 32.329200744628906 35.52629852294922 35.58409881591797 35.852699279785156 36.06449890136719 36.113399505615234 36.14440155029297 36.157798767089844 36.168701171875 36.24570083618164 36.301998138427734 36.35559844970703  PSU	12 options
oxygen	= (ANY) 2.6700000762939453 2.75 2.8299999237060547 3.180000066757202 4.320000171661377 4.409999847412109 4.730000019073486 4.800000190734863 4.920000076293945 4.980000019073486 5.03000020980835 5.070000171661377  milliliters per liter	12 options
nitrite	= (ANY) 0.019999999552965164 0.029999999329447746 0.03999999910593033 0.05999999865889549 0.09000000357627869 0.10999999940395355 0.15000000596046448 0.1899999976158142  micromols	8 options
nitrate	= (ANY) 0.1899999976158142 0.5099999904632568 0.6200000047683716 0.7200000286102295 1.1299999952316284 3.759999990463257 4.039999961853027 10.4399995803833 14.699999809265137 19.790000915527344 23.770000457763672  micromols	11 options
phosphate	= (ANY) 0.0 0.019999999552965164 0.03999999910593033 0.05000000074505806 0.1899999976158142 0.20000000298023224 0.550000011920929 0.8199999928474426 1.1399999856948853 1.4299999475479126  micromols	10 options
silicate	= (ANY) 1.3899999856948853 1.7799999713897705 1.7899999618530273 1.9700000286102295 2.299999952316284 2.509999990463257 3.259999990463257 5.139999866485596 6.460000038146973 8.819999694824219 12.109999656677246  micromols	11 options
salinity2	= (ANY) 32.36000061035156 35.54600143432617 35.80400085449219 35.867000579833984 36.104000091552734 36.124000549316406 36.159000396728516 36.16299819946289 36.19499969482422 36.25199890136719 36.301998138427734 36.36199951171875  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
1.0	25.270099639892578	32.329200744628906	4.920000076293945	0.029999999329447746	0.1899999976158142	0.0	1.3899999856948853	32.36000061035156	0.0
14.0	22.55739974975586	35.58409881591797	5.070000171661377	0.019999999552965164	0.1899999976158142	0.0	1.9700000286102295	35.80400085449219	0.0
33.0	21.38450050354004	36.06449890136719	4.730000019073486	0.10999999940395355	0.6200000047683716	0.03999999910593033	2.509999990463257	36.104000091552734	0.0
43.0	20.81049919128418	36.157798767089844	4.800000190734863	0.1899999976158142	1.1299999952316284	0.05000000074505806	2.299999952316284	36.19499969482422	0.0
53.0	20.21660041809082	36.14440155029297	5.03000020980835	0.15000000596046448	0.5099999904632568	0.019999999552965164	1.7899999618530273	36.159000396728516	0.0
66.0	19.899999618530273	36.113399505615234	4.980000019073486	0.15000000596046448	0.7200000286102295	0.03999999910593033	1.7799999713897705	36.124000549316406	0.0
89.0	19.64310073852539	36.168701171875	4.320000171661377	0.09000000357627869	3.759999990463257	0.1899999976158142	3.259999990463257	36.16299819946289	0.0
109.0	19.45490074157715	36.301998138427734	4.409999847412109	0.05999999865889549	4.039999961853027	0.20000000298023224	3.259999990463257	36.301998138427734	0.0
126.0	18.534900665283203	36.35559844970703	3.180000066757202	0.05999999865889549	10.4399995803833	0.550000011920929	5.139999866485596	36.36199951171875	0.0
170.0	16.956300735473633	36.24570083618164	2.8299999237060547	0.05999999865889549	14.699999809265137	0.8199999928474426	6.460000038146973	36.25199890136719	0.0
244.0	14.233099937438965	35.852699279785156	2.75	0.029999999329447746	19.790000915527344	1.1399999856948853	8.819999694824219	35.867000579833984	1.0
307.0	12.081399917602539	35.52629852294922	2.6700000762939453	0.03999999910593033	23.770000457763672	1.4299999475479126	12.109999656677246	35.54600143432617	1.0

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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