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Dataset Title:	"Deepwater CTD - 00596556.bdo.nc - 23.77N, -83.57W - 1970-04-15"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_00596556_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: 27)
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 30.0 50.0 80.0 100.0 120.0 140.0 160.0 180.0 200.0 230.0 260.0 300.0 350.0 400.0 450.0 500.0 550.0 626.0 726.0 826.0 926.0 1026.0 1127.0 1227.0 1327.0 1377.0  m	27 options
temperature	= (ANY) 4.230000019073486 4.239999771118164 4.300000190734863 4.440000057220459 4.599999904632568 4.960000038146973 5.440000057220459 6.059999942779541 6.519999980926514 6.840000152587891 7.369999885559082 7.960000038146973 8.680000305175781 9.5600004196167 10.789999961853027 11.520000457763672 12.680000305175781 13.350000381469727 14.8100004196167 16.1200008392334 17.239999771118164 17.790000915527344 18.889999389648438 20.34000015258789 21.209999084472656 24.309999465942383  degree_C	26 options
salinity	= (ANY) 34.86899948120117 34.87200164794922 34.87699890136719 34.891998291015625 34.90599822998047 34.92100143432617 34.939998626708984 34.94900131225586 34.959999084472656 34.96099853515625 34.96799850463867 35.027000427246094 35.13600158691406 35.305999755859375 35.41899871826172 35.59299850463867 35.70000076293945 35.91899871826172 36.07400131225586 36.09400177001953 36.178001403808594 36.198001861572266 36.22999954223633 36.25 36.262001037597656  PSU	25 options
oxygen	= (ANY) -99.98999786376953 2.799999952316284 2.819999933242798 2.9000000953674316 2.930000066757202 2.950000047683716 2.990000009536743 3.2200000286102295 3.240000009536743 3.259999990463257 3.2899999618530273 3.309999942779541 3.509999990463257 3.5799999237060547 3.619999885559082 3.740000009536743 3.9700000286102295 4.239999771118164 4.679999828338623 4.849999904632568 4.960000038146973 4.96999979019165 5.010000228881836 5.059999942779541 5.179999828338623 5.260000228881836  milliliters per liter	26 options
nitrite	= (ANY)  not-measured	1 option:
nitrate	= (ANY)  not-measured	1 option:
phosphate	= (ANY)  not-measured	1 option:
silicate	= (ANY) 1.0 2.0 3.0 4.0 5.0 6.0 8.0 9.0 11.0 12.0 15.0 17.0 18.0 20.0 21.0 22.0 23.0 24.0  micromols	18 options
salinity2	= (ANY)  PSU	1 option:
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	PSU	milliliters per liter	not-measured	not-measured	not-measured	micromols	PSU
0.0	24.309999465942383	36.07400131225586	4.960000038146973				1.0		0.0
30.0	21.209999084472656	36.178001403808594	5.059999942779541				1.0		0.0
50.0	20.34000015258789	36.25	5.260000228881836				1.0		0.0
80.0	18.889999389648438	36.262001037597656	-99.98999786376953				2.0		0.0
100.0	17.790000915527344	36.22999954223633	3.9700000286102295				3.0		0.0
120.0	17.239999771118164	36.198001861572266	3.509999990463257				4.0		0.0
140.0	16.1200008392334	36.09400177001953	3.5799999237060547				5.0		0.0
160.0	14.8100004196167	35.91899871826172	3.259999990463257				6.0		0.0
180.0	13.350000381469727	35.70000076293945	3.2899999618530273				8.0		0.0
200.0	12.680000305175781	35.59299850463867	2.950000047683716				9.0		0.0
230.0	11.520000457763672	35.41899871826172	2.9000000953674316				11.0		0.0
260.0	10.789999961853027	35.305999755859375	2.990000009536743				12.0		0.0
300.0	9.5600004196167	35.13600158691406	2.819999933242798				15.0		0.0
350.0	8.680000305175781	35.027000427246094	2.799999952316284				17.0		0.0
400.0	7.960000038146973	34.94900131225586	3.2200000286102295				18.0		0.0
450.0	7.369999885559082	34.90599822998047	2.930000066757202				20.0		0.0
500.0	6.840000152587891	34.87699890136719	3.309999942779541				21.0		0.0
550.0	6.519999980926514	34.86899948120117	3.240000009536743				22.0		0.0
626.0	6.059999942779541	34.87200164794922	3.619999885559082				23.0		0.0
726.0	5.440000057220459	34.891998291015625	3.740000009536743				24.0		0.0
826.0	4.960000038146973	34.92100143432617	4.239999771118164				24.0		0.0
926.0	4.599999904632568	34.939998626708984	4.679999828338623				24.0		0.0
1026.0	4.440000057220459	34.94900131225586	4.96999979019165				24.0		0.0
1127.0	4.300000190734863	34.96099853515625	4.960000038146973				23.0		0.0
1227.0	4.239999771118164	34.96799850463867	5.010000228881836				23.0		0.0
1327.0	4.230000019073486	34.959999084472656	4.849999904632568				22.0		0.0
1377.0	4.239999771118164	34.959999084472656	5.179999828338623				23.0		0.0

In total, there are 27 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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