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Dataset Title:	"Deepwater CTD - 87g1003.bdo.nc - 26.01N, -94.94W - 1987-10-27"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_87g1003_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: 24)
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) 7.0 11.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 91.0 100.0 109.0 118.0 141.0 160.0 178.0 199.0 249.0 300.0 396.0 496.0 597.0 993.0  m	23 options
temperature	= (ANY) 5.139999866485596 7.710000038146973 9.069999694824219 10.800000190734863 13.220000267028809 14.949999809265137 16.770000457763672 17.8799991607666 19.6299991607666 20.489999771118164 20.8700008392334 21.040000915527344 21.389999389648438 22.040000915527344 22.65999984741211 23.25 24.170000076293945 26.850000381469727 26.989999771118164 27.0 27.020000457763672  degree_C	22 options
salinity	= (ANY) 34.92499923706055 34.928001403808594 34.959999084472656 35.11000061035156 35.34000015258789 35.70000076293945 35.959999084472656 36.22999954223633 36.310001373291016 36.31999969482422 36.33000183105469 36.349998474121094 36.41999816894531 36.43000030517578 36.439998626708984 36.45000076293945 36.459999084472656 36.470001220703125  PSU	18 options
oxygen	= (ANY) 3.9040000438690186 4.2729997634887695 4.692999839782715 4.744999885559082 4.922999858856201 5.0960001945495605  milliliters per liter	7 options
nitrite	= (ANY)  micromols per liter	1 option:
nitrate	= (ANY) 0.47999998927116394 0.5 0.5099999904632568 0.550000011920929 0.5699999928474426 0.6299999952316284 0.6399999856948853 0.6700000166893005 0.7099999785423279 1.8700000047683716 3.109999895095825 3.890000104904175 5.230000019073486 9.130000114440918 12.600000381469727 14.0 21.399999618530273 25.799999237060547 27.399999618530273 28.899999618530273 30.600000381469727  micromols	22 options
phosphate	= (ANY)  micromols per liter	1 option:
silicate	= (ANY) 0.0 0.30000001192092896 0.8999999761581421 1.399999976158142 1.5 1.600000023841858 1.7000000476837158 1.7999999523162842 1.899999976158142 2.5999999046325684 3.200000047683716 3.799999952316284 7.099999904632568 10.800000190734863 14.800000190734863 18.299999237060547 21.399999618530273  micromols per liter	18 options
salinity2	= (ANY)  PSU	1 option:
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	PSU	milliliters per liter	micromols per liter	micromols	micromols per liter	micromols per liter	PSU
7.0	26.989999771118164	36.31999969482422			0.550000011920929		0.0		0.0
11.0	27.0	36.310001373291016			0.5699999928474426		0.30000001192092896		0.0
20.0	27.0	36.310001373291016	4.744999885559082		0.6299999952316284		0.8999999761581421		0.0
30.0	27.0	36.31999969482422			0.6399999856948853		1.600000023841858		0.0
40.0	27.020000457763672	36.33000183105469	4.922999858856201		0.7099999785423279		1.7999999523162842		0.0
50.0	26.850000381469727	36.439998626708984			0.47999998927116394		1.600000023841858		0.0
60.0	24.170000076293945	36.45000076293945	5.0960001945495605		0.5		1.600000023841858		0.0
70.0	23.25	36.459999084472656			0.5099999904632568		1.5		0.0
80.0	22.65999984741211	36.459999084472656	4.692999839782715		0.6700000166893005		1.399999976158142		0.0
91.0	22.040000915527344	36.43000030517578			1.8700000047683716		1.399999976158142		0.0
100.0	21.389999389648438	36.41999816894531	4.2729997634887695		3.109999895095825		1.600000023841858		0.0
109.0	21.040000915527344	36.41999816894531			3.890000104904175		1.7000000476837158		0.0
118.0	20.8700008392334	36.41999816894531	3.9040000438690186		5.230000019073486		1.899999976158142		0.0
141.0	20.489999771118164	36.45000076293945			9.130000114440918		2.5999999046325684		0.0
160.0	19.6299991607666	36.470001220703125			12.600000381469727		3.200000047683716		0.0
178.0	17.8799991607666	36.349998474121094			14.0		3.799999952316284		0.0
199.0	16.770000457763672	36.22999954223633							0.0
249.0	14.949999809265137	35.959999084472656			21.399999618530273		7.099999904632568		0.0
300.0	13.220000267028809	35.70000076293945			25.799999237060547		10.800000190734863		1.0
396.0	10.800000190734863	35.34000015258789			28.899999618530273		14.800000190734863		0.0
496.0	9.069999694824219	35.11000061035156			30.600000381469727		18.299999237060547		0.0
597.0	7.710000038146973	34.959999084472656			30.600000381469727		21.399999618530273		0.0
993.0		34.928001403808594			27.399999618530273				0.0
993.0	5.139999866485596	34.92499923706055			27.399999618530273				0.0

In total, there are 24 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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