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ERDDAP > tabledap > Subset ?

Dataset Title:  "CREMP - Florida Keys Revisited OBIS_Occurrence v2.2 - 2004" Subscribe RSS
Institution:  FWC-FWRI   (Dataset ID: fk_CREMP_Rev_OBIS_Occurrence_v2_2_2004)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background | Data Access Form | Make a graph

Select a subset:      (Current number of distinct combinations of matching data: 1098)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

    latitude ?  =  degrees_north   48 options
    longitude ?  =  degrees_east   51 options
    organismQuantity ?  =  1023 options

View:      Map of Distinct Data ?      Distinct Data Counts ?     Distinct Data ?      Related Data Counts ?     Related Data ?

 
Map of Distinct Data ?   (Refine the map and/or download the image)
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Map of Distinct Data
 

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.

 


Distinct Data ?   (Metadata)    (Refine the data subset and/or download the data)  

latitude longitude organismQuantity
degrees_north degrees_east
24.4517 -81.8798 0.0
24.4517 -81.8798 4.81464E-4
24.4517 -81.8798 4.88043E-4
24.4517 -81.8798 9.43841E-4
24.4517 -81.8798 9.76086E-4
24.4517 -81.8798 0.001415762
24.4517 -81.8798 0.001887683
24.4517 -81.8798 0.001952172
24.4517 -81.8798 0.002407318
24.4517 -81.8798 0.002888782
24.4517 -81.8798 0.003370246
24.4517 -81.8798 0.003416301
24.4517 -81.8798 0.003775366
24.4517 -81.8798 0.004247286
24.4517 -81.8798 0.006134969
24.4517 -81.8798 0.006344558
24.4517 -81.8798 0.007221955
24.4517 -81.8798 0.007703418
24.4517 -81.8798 0.0105922
24.4517 -81.8798 0.012201074
24.4517 -81.8798 0.020292591
24.4517 -81.8798 0.023914104
24.4517 -81.8798 0.029259084
24.4517 -81.8798 0.080698443
24.4517 -81.8798 0.082811748
24.4517 -81.8798 0.100536847
24.4517 -81.8798 0.120058565
24.4517 -81.8798 0.170438132
24.4517 -81.8798 0.711603274
24.4517 -81.8798 0.724255735
24.4517 -81.8798 0.843794243
24.452 -81.8775 0.0
24.452 -81.8775 5.19481E-4
24.452 -81.8775 5.40833E-4
24.452 -81.8775 0.001038961
24.452 -81.8775 0.001081666
24.452 -81.8775 0.001558442
24.452 -81.8775 0.001622499
24.452 -81.8775 0.002077922
24.452 -81.8775 0.002163332
24.452 -81.8775 0.002597403
24.452 -81.8775 0.002704164
24.452 -81.8775 0.00378583
24.452 -81.8775 0.004155844
24.452 -81.8775 0.005194805
24.452 -81.8775 0.005949162
24.452 -81.8775 0.006233766
24.452 -81.8775 0.007272727
24.452 -81.8775 0.007792208
24.452 -81.8775 0.008311688
24.452 -81.8775 0.011898323
24.452 -81.8775 0.012467532
24.452 -81.8775 0.015584416
24.452 -81.8775 0.018701299
24.452 -81.8775 0.026493506
24.452 -81.8775 0.028571429
24.452 -81.8775 0.03190914
24.452 -81.8775 0.045429962
24.452 -81.8775 0.076883117
24.452 -81.8775 0.841038961
24.452 -81.8775 0.874805195
24.452 -81.8775 0.890751758
24.4532 -81.8568 0.0
24.4532 -81.8568 4.30478E-4
24.4532 -81.8568 4.84496E-4
24.4532 -81.8568 8.60956E-4
24.4532 -81.8568 9.68992E-4
24.4532 -81.8568 0.001937984
24.4532 -81.8568 0.002422481
24.4532 -81.8568 0.002582867
24.4532 -81.8568 0.003391473
24.4532 -81.8568 0.003443823
24.4532 -81.8568 0.005329457
24.4532 -81.8568 0.005813953
24.4532 -81.8568 0.007318123
24.4532 -81.8568 0.007751938
24.4532 -81.8568 0.008609557
24.4532 -81.8568 0.016788635
24.4532 -81.8568 0.022771318
24.4532 -81.8568 0.04748062
24.4532 -81.8568 0.094274645
24.4532 -81.8568 0.121394748
24.4532 -81.8568 0.146317829
24.4532 -81.8568 0.737839001
24.4532 -81.8568 0.754360465
24.4545 -81.8589 0.0
24.4545 -81.8589 4.68604E-4
24.4545 -81.8589 4.95295E-4
24.4545 -81.8589 5.16796E-4
24.4545 -81.8589 9.37207E-4
24.4545 -81.8589 9.90589E-4
24.4545 -81.8589 0.001033592
24.4545 -81.8589 0.001405811
24.4545 -81.8589 0.001981179
24.4545 -81.8589 0.002476474
24.4545 -81.8589 0.002583979
24.4545 -81.8589 0.003748828
24.4545 -81.8589 0.005154639
24.4545 -81.8589 0.005684755
24.4545 -81.8589 0.005943536
24.4545 -81.8589 0.00656045
24.4545 -81.8589 0.006934126
24.4545 -81.8589 0.009905894
24.4545 -81.8589 0.015463918
24.4545 -81.8589 0.03368004
24.4545 -81.8589 0.037726098
24.4545 -81.8589 0.03875969
24.4545 -81.8589 0.041343669
24.4545 -81.8589 0.044517338
24.4545 -81.8589 0.051015354
24.4545 -81.8589 0.055763824
24.4545 -81.8589 0.141085271
24.4545 -81.8589 0.726098191
24.4545 -81.8589 0.864573571
24.4545 -81.8589 0.885586924
24.4548 -81.857 0.0
24.4548 -81.857 4.88281E-4
24.4548 -81.857 0.001953125
24.4548 -81.857 0.002441406
24.4548 -81.857 0.003417969
24.4548 -81.857 0.005371094
24.4548 -81.857 0.028808594
24.4548 -81.857 0.043457031
24.4548 -81.857 0.067382813
24.4548 -81.857 0.09765625
24.4548 -81.857 0.739746094
24.478 -81.7171 0.0
24.478 -81.7171 4.78469E-4
24.478 -81.7171 5.24384E-4
24.478 -81.7171 9.56938E-4
24.478 -81.7171 0.001435407
24.478 -81.7171 0.001573152
24.478 -81.7171 0.002097535
24.478 -81.7171 0.002392344
24.478 -81.7171 0.002621919
24.478 -81.7171 0.003349282
24.478 -81.7171 0.004195071
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24.478 -81.7171 0.011012061
24.478 -81.7171 0.011483254
24.478 -81.7171 0.013109596
24.478 -81.7171 0.05453592
24.478 -81.7171 0.0784689
24.478 -81.7171 0.271291866
24.478 -81.7171 0.28474043
24.478 -81.7171 0.619617225
24.478 -81.7171 0.623492396
24.4796 -81.7176 0.0
24.4796 -81.7176 4.47027E-4
24.4796 -81.7176 4.75737E-4
24.4796 -81.7176 8.94055E-4
24.4796 -81.7176 9.51475E-4
24.4796 -81.7176 0.001788109
24.4796 -81.7176 0.002682164
24.4796 -81.7176 0.003129191
24.4796 -81.7176 0.007152436
24.4796 -81.7176 0.010466223
24.4796 -81.7176 0.023692445
24.4796 -81.7176 0.027117031
24.4796 -81.7176 0.027715691
24.4796 -81.7176 0.035680304
24.4796 -81.7176 0.044702727
24.4796 -81.7176 0.098001903
24.4796 -81.7176 0.120250335
24.4796 -81.7176 0.240247383
24.4796 -81.7176 0.584205519
24.4796 -81.7176 0.766651766
24.4796 -81.7142 0.0
24.4796 -81.7142 9.30233E-4
24.4796 -81.7142 0.001395349
24.4796 -81.7142 0.001860465
24.4796 -81.7142 0.00372093
24.4796 -81.7142 0.005116279
24.4796 -81.7142 0.00744186
24.4796 -81.7142 0.093488372
24.4796 -81.7142 0.265116279
24.4796 -81.7142 0.614883721
24.4798 -81.7158 0.0
24.4798 -81.7158 4.83092E-4
24.4798 -81.7158 9.66184E-4
24.4798 -81.7158 0.001449275
24.4798 -81.7158 0.001932367
24.4798 -81.7158 0.009661836
24.4798 -81.7158 0.011111111
24.4798 -81.7158 0.019323671
24.4798 -81.7158 0.030434783
24.4798 -81.7158 0.033333333
24.4798 -81.7158 0.044444444
24.4798 -81.7158 0.166183575
24.4798 -81.7158 0.676811594
24.4884 -81.6659 0.0
24.4884 -81.6659 4.6729E-4
24.4884 -81.6659 4.77099E-4
24.4884 -81.6659 5.5991E-4
24.4884 -81.6659 9.34579E-4
24.4884 -81.6659 0.001869159
24.4884 -81.6659 0.004672897
24.4884 -81.6659 0.004770992
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24.4884 -81.6659 0.009541985
24.4884 -81.6659 0.011198208
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24.4884 -81.6659 0.022429907
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24.4884 -81.6659 0.13549832
24.4884 -81.6659 0.185981308
24.4884 -81.6659 0.231870229
24.4884 -81.6659 0.381298992
24.4884 -81.6659 0.429451288
24.4884 -81.6659 0.616889313
24.4884 -81.6659 0.677570093
24.4917 -81.663565 0.0
24.4917 -81.663565 4.40723E-4
24.4917 -81.663565 4.72144E-4
24.4917 -81.663565 4.83325E-4
24.4917 -81.663565 9.44287E-4
24.4917 -81.663565 0.001416431
24.4917 -81.663565 0.001449976
24.4917 -81.663565 0.002360718
24.4917 -81.663565 0.002832861
24.4917 -81.663565 0.003966505
24.4917 -81.663565 0.012340238
24.4917 -81.663565 0.014636449
24.4917 -81.663565 0.015466409
24.4917 -81.663565 0.019832525
24.4917 -81.663565 0.022232963
24.4917 -81.663565 0.033994334
24.4917 -81.663565 0.041082649
24.4917 -81.663565 0.043909348
24.4917 -81.663565 0.045797923
24.4917 -81.663565 0.072498792
24.4917 -81.663565 0.13098115
24.4917 -81.663565 0.151608638
24.4917 -81.663565 0.153371529
24.4917 -81.663565 0.174220963
24.4917 -81.663565 0.657558396
24.4917 -81.663565 0.678470255
24.4917 -81.663565 0.714354761
24.4977 -81.8056 0.0
24.4977 -81.8056 4.87805E-4
24.4977 -81.8056 5.05561E-4
24.4977 -81.8056 5.26039E-4
24.4977 -81.8056 0.001011122
24.4977 -81.8056 0.001052078
24.4977 -81.8056 0.001463415
24.4977 -81.8056 0.001578117
24.4977 -81.8056 0.00195122
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24.5036 -81.7677 0.0
24.5036 -81.7677 5.00751E-4
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24.5421 -81.4153 0.0
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24.5426 -81.4128 0.0
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24.5452 -81.4071 0.0
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24.5475 -81.5866 0.0
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24.6253 -81.1116 0.0
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25.1032 -80.3243 0.059457131
25.1032 -80.3243 0.061611374
25.1032 -80.3243 0.112882378
25.1032 -80.3243 0.17724388
25.1032 -80.3243 0.206472197
25.1032 -80.3243 0.23118767
25.1032 -80.3243 0.255241568
25.1032 -80.3243 0.470829535
25.1032 -80.3243 0.540344515
25.1032 -80.3243 0.723395088
25.1075 -80.3069 0.0
25.1075 -80.3069 4.87329E-4
25.1075 -80.3069 5.09944E-4
25.1075 -80.3069 0.001019888
25.1075 -80.3069 0.001949318
25.1075 -80.3069 0.00254972
25.1075 -80.3069 0.002923977
25.1075 -80.3069 0.003059663
25.1075 -80.3069 0.003411306
25.1075 -80.3069 0.003569607
25.1075 -80.3069 0.005847953
25.1075 -80.3069 0.006629271
25.1075 -80.3069 0.007649159
25.1075 -80.3069 0.011695906
25.1075 -80.3069 0.015107212
25.1075 -80.3069 0.024477307
25.1075 -80.3069 0.036206017
25.1075 -80.3069 0.06871345
25.1075 -80.3069 0.155022947
25.1075 -80.3069 0.159356725
25.1075 -80.3069 0.185109638
25.1075 -80.3069 0.33625731
25.1075 -80.3069 0.394249513
25.1075 -80.3069 0.565017848
25.1075 -80.3068 0.0
25.1075 -80.3068 5.19751E-4
25.1075 -80.3068 9.71345E-4
25.1075 -80.3068 0.002428363
25.1075 -80.3068 0.002598753
25.1075 -80.3068 0.002914036
25.1075 -80.3068 0.004371054
25.1075 -80.3068 0.006756757
25.1075 -80.3068 0.011656144

In total, there are 1098 rows of distinct combinations of the variables listed above.
The first 1000 rows are shown above. The remaining 98 rows aren't being shown.
To change the maximum number of rows displayed, change View : Distinct Data above.
 


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.
 


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.


 
ERDDAP, Version 2.02
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