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Dataset Title:	"Deepwater CTD - d94i018.bdo.nc - 27.66N, -90.5W - 1994-07-28"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_d94i018_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 19.0 43.0 64.0 75.0 96.0 125.0 207.0 294.0 407.0 597.0 908.0  m	12 options
temperature	= (ANY) 5.115900039672852 6.894400119781494 9.543000221252441 11.928099632263184 14.257399559020996 16.8705997467041 18.586000442504883 20.382600784301758 21.491600036621094 24.463899612426758 29.10260009765625 29.582700729370117  degree_C (potential temperature from ctd)	12 options
salinity	= (ANY) 28.796499252319336 34.906898498535156 34.91830062866211 35.15019989013672 35.48910140991211 35.85660171508789 35.9640007019043 36.26070022583008 36.44089889526367 36.511199951171875 36.52389907836914 36.53179931640625  PSU	12 options
oxygen	= (ANY) 2.7699999809265137 2.9100000858306885 3.0399999618530273 3.069999933242798 3.25 3.3399999141693115 3.7300000190734863 4.039999961853027 4.269999980926514 4.730000019073486 4.760000228881836 5.010000228881836  milliliters per liter	12 options
nitrite	= (ANY) 0.009999999776482582 0.029999999329447746 0.03999999910593033 0.09000000357627869 0.1599999964237213 0.4300000071525574  micromols	6 options
nitrate	= (ANY) 0.009999999776482582 0.019999999552965164 0.07999999821186066 0.47999998927116394 3.890000104904175 9.479999542236328 11.75 17.420000076293945 22.489999771118164 27.290000915527344 27.6299991607666 30.690000534057617  micromols	12 options
phosphate	= (ANY) 0.09000000357627869 0.10000000149011612 0.12999999523162842 0.6499999761581421 0.7900000214576721 1.1799999475479126 1.5199999809265137 1.8799999952316284 1.9500000476837158 2.119999885559082  micromols	10 options
silicate	= (ANY) 0.11999999731779099 0.5400000214576721 0.6899999976158142 1.059999942779541 1.659999966621399 3.180000066757202 4.119999885559082 6.829999923706055 10.319999694824219 15.40999984741211 22.200000762939453 25.510000228881836  micromols	12 options
salinity2	= (ANY) 28.849000930786133 34.90800094604492 34.917999267578125 35.15299987792969 35.492000579833984 35.861000061035156 35.9379997253418 36.26599884033203 36.44900131225586 36.51599884033203 36.52899932861328 36.53799819946289  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	29.582700729370117	28.796499252319336	4.760000228881836	0.009999999776482582	0.019999999552965164	0.09000000357627869	0.5400000214576721	28.849000930786133	0.0
19.0	29.10260009765625	35.9640007019043	4.730000019073486	0.009999999776482582	0.009999999776482582	0.10000000149011612	0.6899999976158142	35.9379997253418	0.0
43.0	24.463899612426758	36.511199951171875	5.010000228881836	0.009999999776482582	0.07999999821186066	0.09000000357627869	0.11999999731779099	36.51599884033203	0.0
64.0	21.491600036621094	36.52389907836914	4.269999980926514	0.1599999964237213	0.47999998927116394	0.12999999523162842	1.059999942779541	36.52899932861328	0.0
75.0	20.382600784301758	36.53179931640625	3.7300000190734863	0.4300000071525574	3.890000104904175	0.12999999523162842	1.659999966621399	36.53799819946289	0.0
96.0	18.586000442504883	36.44089889526367	3.25	0.09000000357627869	9.479999542236328	0.6499999761581421	3.180000066757202	36.44900131225586	0.0
125.0	16.8705997467041	36.26070022583008	3.3399999141693115	0.03999999910593033	11.75	0.7900000214576721	4.119999885559082	36.26599884033203	0.0
207.0	14.257399559020996	35.85660171508789	3.0399999618530273	0.029999999329447746	17.420000076293945	1.1799999475479126	6.829999923706055	35.861000061035156	0.0
294.0	11.928099632263184	35.48910140991211	2.9100000858306885	0.029999999329447746	22.489999771118164	1.5199999809265137	10.319999694824219	35.492000579833984	0.0
407.0	9.543000221252441	35.15019989013672	2.7699999809265137	0.029999999329447746	27.6299991607666	1.8799999952316284	15.40999984741211	35.15299987792969	0.0
597.0	6.894400119781494	34.906898498535156	3.069999933242798	0.029999999329447746	30.690000534057617	2.119999885559082	22.200000762939453	34.90800094604492	0.0
908.0	5.115900039672852	34.91830062866211	4.039999961853027	0.029999999329447746	27.290000915527344	1.9500000476837158	25.510000228881836	34.917999267578125	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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