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Dataset Title:	"Deepwater CTD - 93g0112.ctd.nc - 27.73N, -95.69W - 1993-01-14"
Institution:	Texas A&M University, Department of Oceanography   (Dataset ID: deepwater_93g0112_ctd)
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: 72)
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) 3.0 4.0 5.0 7.0 8.0 9.0 11.0 12.0 13.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 27.0 28.0 29.0 30.0 31.0 32.0 33.0 34.0 35.0 36.0 37.0 38.0 39.0 40.0 41.0 42.0 43.0 45.0 46.0 47.0 49.0 50.0 51.0 52.0 53.0 54.0 55.0 56.0 57.0 58.0 59.0 60.0 61.0 62.0 63.0 64.0 65.0 66.0 67.0 68.0 69.0 70.0 71.0 72.0 73.0 75.0 77.0 78.0 79.0 80.0 81.0 82.0  m	72 options
temperature	= (ANY) 21.458499908447266 21.466100692749023 21.604299545288086 21.829999923706055 22.44659996032715 22.569299697875977 22.708099365234375 22.839399337768555 22.930999755859375 22.986799240112305 22.98710060119629 22.987499237060547 22.988800048828125 22.98900032043457 22.989200592041016 22.990299224853516 22.99049949645996 22.991100311279297 22.991600036621094 22.992300033569336 22.992700576782227 22.993000030517578 22.99850082397461 22.998600006103516 22.999099731445312 22.99970054626465 23.00040054321289 23.000499725341797 23.000600814819336 23.00079917907715 23.000900268554688 23.000999450683594 23.00119972229004 23.001699447631836 23.00200080871582 23.002300262451172 23.00429916381836 23.00480079650879 23.0049991607666 23.005399703979492 23.005800247192383 23.007099151611328 23.00749969482422 23.007699966430664 23.00779914855957 23.009000778198242 23.009300231933594 23.0093994140625 23.00950050354004 23.009599685668945 23.009700775146484 23.00979995727539 23.009899139404297 23.010000228881836 23.010099411010742 23.01020050048828 23.010299682617188 23.01059913635254  degree_C	58 options
salinity	= (ANY) 35.957298278808594 35.95869827270508 35.96739959716797 35.9822998046875 36.05659866333008 36.11069869995117 36.125999450683594 36.149600982666016 36.16429901123047 36.1796989440918 36.1797981262207 36.179901123046875 36.18000030517578 36.18009948730469 36.180198669433594 36.18050003051758 36.180599212646484 36.18069839477539 36.18080139160156 36.18090057373047 36.180999755859375 36.18109893798828 36.18119812011719 36.18130111694336 36.181400299072266 36.18149948120117 36.18159866333008 36.18170166015625 36.181800842285156 36.183998107910156 36.18429946899414  PSU	31 options
oxygen	= (ANY) 2.5829999446868896 2.6389999389648438 2.697000026702881 2.8269999027252197 2.941999912261963 3.5190000534057617 4.27400016784668 4.801000118255615 4.84499979019165 4.8470001220703125 4.855000019073486 4.877999782562256  milliliters per liter	13 options
nitrite	= (ANY) 0.009999999776482582 0.019999999552965164 0.03999999910593033 0.05000000074505806 0.05999999865889549  micromols per liter	6 options
nitrate	= (ANY) 0.0 0.10000000149011612 1.2000000476837158 5.800000190734863 12.300000190734863 17.5 23.600000381469727 28.799999237060547 30.899999618530273  micromols	10 options
phosphate	= (ANY) 0.019999999552965164 0.029999999329447746 0.05999999865889549 0.07999999821186066 0.2800000011920929 0.6600000262260437 1.0199999809265137 1.4700000286102295 1.8700000047683716 2.059999942779541  micromols per liter	11 options
silicate	= (ANY) 0.8999999761581421 1.0 1.2999999523162842 1.399999976158142 1.7000000476837158 1.899999976158142 2.4000000953674316 4.599999904632568 8.399999618530273 13.300000190734863 17.299999237060547  micromols per liter	12 options
salinity2	= (ANY) -99.0  PSU	2 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	PSU	milliliters per liter	micromols per liter	micromols	micromols per liter	micromols per liter	PSU
3.0	22.988800048828125	36.180999755859375	4.8470001220703125	0.05000000074505806	0.10000000149011612	0.029999999329447746	1.899999976158142	-99.0	0.0
4.0	22.990299224853516	36.180599212646484	4.877999782562256	0.05000000074505806	0.0	0.05999999865889549	1.7000000476837158	-99.0	0.0
5.0	22.991100311279297	36.180999755859375	4.855000019073486	0.05000000074505806	0.0	0.019999999552965164	1.399999976158142	-99.0	0.0
7.0	22.991600036621094	36.180999755859375	4.84499979019165	0.05000000074505806	0.0	0.019999999552965164	1.2999999523162842	-99.0	0.0
8.0	22.99049949645996	36.18119812011719	4.801000118255615	0.05999999865889549	0.10000000149011612	0.019999999552965164	1.0	-99.0	0.0
9.0	22.987499237060547	36.18149948120117	4.27400016784668	0.03999999910593033	1.2000000476837158	0.07999999821186066	0.8999999761581421	-99.0	0.0
11.0	22.986799240112305	36.18159866333008	3.5190000534057617	0.019999999552965164	5.800000190734863	0.2800000011920929	1.2999999523162842	-99.0	0.0
12.0	22.98710060119629	36.18130111694336	2.941999912261963	0.009999999776482582	12.300000190734863	0.6600000262260437	2.4000000953674316	-99.0	0.0
13.0	22.98900032043457	36.181400299072266	2.8269999027252197	0.009999999776482582	17.5	1.0199999809265137	4.599999904632568	-99.0	0.0
15.0	22.989200592041016	36.18170166015625	2.6389999389648438	0.019999999552965164	23.600000381469727	1.4700000286102295	8.399999618530273	-99.0	0.0
16.0	22.993000030517578	36.181400299072266	2.5829999446868896	0.009999999776482582	28.799999237060547	1.8700000047683716	13.300000190734863	-99.0	0.0
17.0	22.992300033569336	36.18119812011719	2.697000026702881	0.009999999776482582	30.899999618530273	2.059999942779541	17.299999237060547	-99.0	0.0
18.0	22.992700576782227	36.18119812011719							0.0
19.0	22.998600006103516	36.18080139160156							0.0
20.0	22.999099731445312	36.180999755859375							0.0
21.0	22.99970054626465	36.18130111694336							0.0
22.0	23.000600814819336	36.18109893798828							0.0
23.0	23.000600814819336	36.18080139160156							0.0
24.0	23.000900268554688	36.18090057373047							0.0
25.0	23.00119972229004	36.18090057373047							0.0
27.0	23.001699447631836	36.18119812011719							0.0
28.0	23.00200080871582	36.180599212646484							0.0
29.0	23.000900268554688	36.180198669433594							0.0
30.0	22.99850082397461	36.1796989440918							0.0
31.0	22.998600006103516	36.1797981262207							0.0
32.0	22.99970054626465	36.180198669433594							0.0
33.0	23.00040054321289	36.179901123046875							0.0
34.0	23.000600814819336	36.18000030517578							0.0
35.0	23.000999450683594	36.18009948730469							0.0
36.0	23.000499725341797	36.179901123046875							0.0
37.0	23.00079917907715	36.18009948730469							0.0
38.0	23.001699447631836	36.18009948730469							0.0
39.0	23.002300262451172	36.18000030517578							0.0
40.0	23.00480079650879	36.18050003051758							0.0
41.0	23.0049991607666	36.18080139160156							0.0
42.0	23.005399703979492	36.18069839477539							0.0
43.0	23.00429916381836	36.18429946899414							0.0
45.0	23.0049991607666	36.180599212646484							0.0
46.0	23.005399703979492	36.18080139160156							0.0
47.0	23.005800247192383	36.18109893798828							0.0
49.0	23.007099151611328	36.181400299072266							0.0
50.0	23.00749969482422	36.18130111694336							0.0
51.0	23.007699966430664	36.18109893798828							0.0
52.0	23.00779914855957	36.18130111694336							0.0
53.0	23.009000778198242	36.180999755859375							0.0
54.0	23.009300231933594	36.18130111694336							0.0
55.0	23.009700775146484	36.183998107910156							0.0
56.0	23.010299682617188	36.181800842285156							0.0
57.0	23.010000228881836	36.18119812011719							0.0
58.0	23.009700775146484	36.18130111694336							0.0
59.0	23.0093994140625	36.181400299072266							0.0
60.0	23.009899139404297	36.18119812011719							0.0
61.0	23.009700775146484	36.18130111694336							0.0
62.0	23.00950050354004	36.181400299072266							0.0
63.0	23.009599685668945	36.18149948120117							0.0
64.0	23.00979995727539	36.18130111694336							0.0
65.0	23.00979995727539	36.181400299072266							0.0
66.0	23.010099411010742	36.181400299072266							0.0
67.0	23.010299682617188	36.181400299072266							0.0
68.0	23.01020050048828	36.181400299072266							0.0
69.0	23.010099411010742	36.18149948120117							0.0
70.0	23.01059913635254	36.18149948120117							0.0
71.0	23.009599685668945	36.18119812011719							0.0
72.0	22.930999755859375	36.16429901123047							0.0
73.0	22.839399337768555	36.149600982666016							0.0
75.0	22.708099365234375	36.125999450683594							0.0
77.0	22.569299697875977	36.11069869995117							0.0
78.0	22.44659996032715	36.05659866333008							0.0
79.0	21.829999923706055	35.95869827270508							0.0
80.0	21.604299545288086	35.957298278808594							0.0
81.0	21.466100692749023	35.9822998046875							0.0
82.0	21.458499908447266	35.96739959716797							0.0

In total, there are 72 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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