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ERDDAP > tabledap > Subset ?

Dataset Title:  "CREMP - Dry Tortugas Revisited OBIS_Measure v2.2 - 2008" Subscribe RSS
Institution:  FWC-FWRI   (Dataset ID: dt_CREMP_Rev_OBIS_Measure_v2_2_2008)
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: 380)
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   9 options
    longitude ?  =  degrees_east   9 options
    measurementValue ?  =  353 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)
Optional: Click on the map to select the closest data.
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 measurementValue
degrees_north degrees_east
24.608 -82.944 0.0
24.608 -82.944 3.38639E-4
24.608 -82.944 3.49528E-4
24.608 -82.944 3.61402E-4
24.608 -82.944 6.73174E-4
24.608 -82.944 6.77277E-4
24.608 -82.944 7.22804E-4
24.608 -82.944 0.001009761
24.608 -82.944 0.001015916
24.608 -82.944 0.001048584
24.608 -82.944 0.001084207
24.608 -82.944 0.001354555
24.608 -82.944 0.001398113
24.608 -82.944 0.001682935
24.608 -82.944 0.001747641
24.608 -82.944 0.001807011
24.608 -82.944 0.002097169
24.608 -82.944 0.002370471
24.608 -82.944 0.002446697
24.608 -82.944 0.002692696
24.608 -82.944 0.002709109
24.608 -82.944 0.002796225
24.608 -82.944 0.003047748
24.608 -82.944 0.003614022
24.608 -82.944 0.003702457
24.608 -82.944 0.004336827
24.608 -82.944 0.005048805
24.608 -82.944 0.005059631
24.608 -82.944 0.005941978
24.608 -82.944 0.006866643
24.608 -82.944 0.007741501
24.608 -82.944 0.008738203
24.608 -82.944 0.01009761
24.608 -82.944 0.010136316
24.608 -82.944 0.010836438
24.608 -82.944 0.011443958
24.608 -82.944 0.014473241
24.608 -82.944 0.022350152
24.608 -82.944 0.026590374
24.608 -82.944 0.032164799
24.608 -82.944 0.035005049
24.608 -82.944 0.039496679
24.608 -82.944 0.04192266
24.608 -82.944 0.044739602
24.608 -82.944 0.064313177
24.608 -82.944 0.072130037
24.608 -82.944 0.144395826
24.608 -82.944 0.151032848
24.608 -82.944 0.160462595
24.608 -82.944 0.194337644
24.608 -82.944 0.618664803
24.608 -82.944 0.730104978
24.608 -82.944 0.733759677
24.608 -82.944 0.73545356
24.608 -82.944 19.0
24.608 -82.944 21.0
24.608 -82.944 22.0
24.608 -82.944 29.0
24.608 -82.944 30.0
24.608 -82.944 31.0
24.608 -82.944 32.0
24.608 -82.944 2767.0
24.608 -82.944 2861.0
24.608 -82.944 2953.0
24.608 -82.944 2971.0
24.6117 -82.8702 0.0
24.6117 -82.8702 3.17259E-4
24.6117 -82.8702 3.56125E-4
24.6117 -82.8702 6.30716E-4
24.6117 -82.8702 7.12251E-4
24.6117 -82.8702 0.001068376
24.6117 -82.8702 0.001261432
24.6117 -82.8702 0.001803101
24.6117 -82.8702 0.001903553
24.6117 -82.8702 0.002163722
24.6117 -82.8702 0.002207506
24.6117 -82.8702 0.002492877
24.6117 -82.8702 0.002522863
24.6117 -82.8702 0.002849003
24.6117 -82.8702 0.003561254
24.6117 -82.8702 0.003606203
24.6117 -82.8702 0.003784295
24.6117 -82.8702 0.004124365
24.6117 -82.8702 0.00462963
24.6117 -82.8702 0.004758883
24.6117 -82.8702 0.005698006
24.6117 -82.8702 0.005991801
24.6117 -82.8702 0.006130545
24.6117 -82.8702 0.008830022
24.6117 -82.8702 0.009615385
24.6117 -82.8702 0.010152284
24.6117 -82.8702 0.011738579
24.6117 -82.8702 0.016227912
24.6117 -82.8702 0.016737892
24.6117 -82.8702 0.020939086
24.6117 -82.8702 0.022705771
24.6117 -82.8702 0.026332487
24.6117 -82.8702 0.033312183
24.6117 -82.8702 0.05373242
24.6117 -82.8702 0.069063387
24.6117 -82.8702 0.079059829
24.6117 -82.8702 0.084401709
24.6117 -82.8702 0.086188244
24.6117 -82.8702 0.094607379
24.6117 -82.8702 0.094729345
24.6117 -82.8702 0.122461929
24.6117 -82.8702 0.213126578
24.6117 -82.8702 0.263323873
24.6117 -82.8702 0.340418782
24.6117 -82.8702 0.420685279
24.6117 -82.8702 0.520655944
24.6117 -82.8702 0.617021277
24.6117 -82.8702 0.689814815
24.6117 -82.8702 22.0
24.6117 -82.8702 23.0
24.6117 -82.8702 25.0
24.6117 -82.8702 40.0
24.6117 -82.8702 43.0
24.6117 -82.8702 45.0
24.6117 -82.8702 2773.0
24.6117 -82.8702 2808.0
24.6117 -82.8702 3152.0
24.6117 -82.8702 3171.0
24.6206 -82.8696 0.0
24.6206 -82.8696 3.13578E-4
24.6206 -82.8696 3.96825E-4
24.6206 -82.8696 7.10732E-4
24.6206 -82.8696 7.93651E-4
24.6206 -82.8696 0.001066098
24.6206 -82.8696 0.001587302
24.6206 -82.8696 0.001881468
24.6206 -82.8696 0.002132196
24.6206 -82.8696 0.003135779
24.6206 -82.8696 0.003909026
24.6206 -82.8696 0.005017247
24.6206 -82.8696 0.007107321
24.6206 -82.8696 0.008173419
24.6206 -82.8696 0.008528785
24.6206 -82.8696 0.012698413
24.6206 -82.8696 0.014111007
24.6206 -82.8696 0.017063492
24.6206 -82.8696 0.024772656
24.6206 -82.8696 0.037698413
24.6206 -82.8696 0.041705864
24.6206 -82.8696 0.05188344
24.6206 -82.8696 0.082470994
24.6206 -82.8696 0.159920635
24.6206 -82.8696 0.164179104
24.6206 -82.8696 0.752309879
24.6206 -82.8696 0.769444444
24.6206 -82.8696 0.821260583
24.6206 -82.8696 5.0
24.6206 -82.8696 7.0
24.6206 -82.8696 18.0
24.6206 -82.8696 21.0
24.6206 -82.8696 22.0
24.6206 -82.8696 2520.0
24.6206 -82.8696 2814.0
24.6206 -82.8696 3189.0
24.6207 -82.8673 0.0
24.6207 -82.8673 3.427E-4
24.6207 -82.8673 6.51466E-4
24.6207 -82.8673 6.85401E-4
24.6207 -82.8673 9.77199E-4
24.6207 -82.8673 0.001028101
24.6207 -82.8673 0.001628664
24.6207 -82.8673 0.002741604
24.6207 -82.8673 0.003257329
24.6207 -82.8673 0.003583062
24.6207 -82.8673 0.004234528
24.6207 -82.8673 0.004560261
24.6207 -82.8673 0.004885993
24.6207 -82.8673 0.006168609
24.6207 -82.8673 0.007539411
24.6207 -82.8673 0.026710098
24.6207 -82.8673 0.029814942
24.6207 -82.8673 0.029967427
24.6207 -82.8673 0.045276873
24.6207 -82.8673 0.874267101
24.6207 -82.8673 0.95030843
24.6207 -82.8673 9.0
24.6207 -82.8673 20.0
24.6207 -82.8673 25.0
24.6207 -82.8673 2918.0
24.6207 -82.8673 3070.0
24.635 -82.9163 0.0
24.635 -82.9163 3.16156E-4
24.635 -82.9163 3.17259E-4
24.635 -82.9163 6.32311E-4
24.635 -82.9163 6.34518E-4
24.635 -82.9163 9.51777E-4
24.635 -82.9163 0.001264622
24.635 -82.9163 0.003793867
24.635 -82.9163 0.005393401
24.635 -82.9163 0.008883249
24.635 -82.9163 0.011697755
24.635 -82.9163 0.012646222
24.635 -82.9163 0.012690355
24.635 -82.9163 0.014543155
24.635 -82.9163 0.019285488
24.635 -82.9163 0.935188113
24.635 -82.9163 0.970812183
24.635 -82.9163 6.0
24.635 -82.9163 7.0
24.635 -82.9163 22.0
24.635 -82.9163 3152.0
24.635 -82.9163 3163.0
24.6414 -82.8962 0.0
24.6414 -82.8962 2.97442E-4
24.6414 -82.8962 3.02755E-4
24.6414 -82.8962 3.04971E-4
24.6414 -82.8962 6.0551E-4
24.6414 -82.8962 6.09942E-4
24.6414 -82.8962 8.92326E-4
24.6414 -82.8962 9.08265E-4
24.6414 -82.8962 9.14913E-4
24.6414 -82.8962 0.00121102
24.6414 -82.8962 0.001219884
24.6414 -82.8962 0.00148721
24.6414 -82.8962 0.001513775
24.6414 -82.8962 0.001524855
24.6414 -82.8962 0.001784652
24.6414 -82.8962 0.002082094
24.6414 -82.8962 0.002119285
24.6414 -82.8962 0.002134797
24.6414 -82.8962 0.002422041
24.6414 -82.8962 0.009220702
24.6414 -82.8962 0.009518144
24.6414 -82.8962 0.010673986
24.6414 -82.8962 0.010707912
24.6414 -82.8962 0.046995836
24.6414 -82.8962 0.053242118
24.6414 -82.8962 0.087496216
24.6414 -82.8962 0.10094541
24.6414 -82.8962 0.160460188
24.6414 -82.8962 0.233912778
24.6414 -82.8962 0.639829216
24.6414 -82.8962 0.740538904
24.6414 -82.8962 0.853361095
24.6414 -82.8962 18.0
24.6414 -82.8962 22.0
24.6414 -82.8962 23.0
24.6414 -82.8962 24.0
24.6414 -82.8962 29.0
24.6414 -82.8962 3279.0
24.6414 -82.8962 3303.0
24.6414 -82.8962 3362.0
24.6423 -82.8971 0.0
24.6423 -82.8971 3.20616E-4
24.6423 -82.8971 6.41231E-4
24.6423 -82.8971 0.001603078
24.6423 -82.8971 0.001923693
24.6423 -82.8971 0.002244309
24.6423 -82.8971 0.009297852
24.6423 -82.8971 0.011862777
24.6423 -82.8971 0.096825906
24.6423 -82.8971 0.117986534
24.6423 -82.8971 0.756652773
24.6423 -82.8971 15.0
24.6423 -82.8971 23.0
24.6423 -82.8971 3119.0
24.6431 -82.9307 0.0
24.6431 -82.9307 3.33111E-4
24.6431 -82.9307 3.40252E-4
24.6431 -82.9307 3.50754E-4
24.6431 -82.9307 3.58809E-4
24.6431 -82.9307 6.80504E-4
24.6431 -82.9307 7.17618E-4
24.6431 -82.9307 9.99334E-4
24.6431 -82.9307 0.001052262
24.6431 -82.9307 0.001361007
24.6431 -82.9307 0.001998668
24.6431 -82.9307 0.002104525
24.6431 -82.9307 0.002381763
24.6431 -82.9307 0.00266489
24.6431 -82.9307 0.002722014
24.6431 -82.9307 0.002806033
24.6431 -82.9307 0.003507541
24.6431 -82.9307 0.004423273
24.6431 -82.9307 0.004664514
24.6431 -82.9307 0.004910558
24.6431 -82.9307 0.005103777
24.6431 -82.9307 0.01065956
24.6431 -82.9307 0.010764263
24.6431 -82.9307 0.01148188
24.6431 -82.9307 0.012991339
24.6431 -82.9307 0.014290575
24.6431 -82.9307 0.017537706
24.6431 -82.9307 0.019016864
24.6431 -82.9307 0.026879891
24.6431 -82.9307 0.056295803
24.6431 -82.9307 0.072479368
24.6431 -82.9307 0.08727515
24.6431 -82.9307 0.104117047
24.6431 -82.9307 0.105576991
24.6431 -82.9307 0.128094726
24.6431 -82.9307 0.129077517
24.6431 -82.9307 0.162899175
24.6431 -82.9307 0.164681865
24.6431 -82.9307 0.172884744
24.6431 -82.9307 0.195644777
24.6431 -82.9307 0.324096808
24.6431 -82.9307 0.408277797
24.6431 -82.9307 0.476352501
24.6431 -82.9307 0.589522784
24.6431 -82.9307 0.649566955
24.6431 -82.9307 20.0
24.6431 -82.9307 21.0
24.6431 -82.9307 22.0
24.6431 -82.9307 23.0
24.6431 -82.9307 28.0
24.6431 -82.9307 2787.0
24.6431 -82.9307 2851.0
24.6431 -82.9307 2939.0
24.6431 -82.9307 3002.0
24.6993 -83.0022 0.0
24.6993 -83.0022 3.64299E-4
24.6993 -83.0022 3.84911E-4
24.6993 -83.0022 4.28633E-4
24.6993 -83.0022 4.3611E-4
24.6993 -83.0022 7.28597E-4
24.6993 -83.0022 7.69823E-4
24.6993 -83.0022 8.57265E-4
24.6993 -83.0022 8.7222E-4
24.6993 -83.0022 0.001092896
24.6993 -83.0022 0.001285898
24.6993 -83.0022 0.001457195
24.6993 -83.0022 0.001539646
24.6993 -83.0022 0.001821494
24.6993 -83.0022 0.002550091
24.6993 -83.0022 0.003052769
24.6993 -83.0022 0.003924989
24.6993 -83.0022 0.004361099
24.6993 -83.0022 0.005003849
24.6993 -83.0022 0.005773672
24.6993 -83.0022 0.006000857
24.6993 -83.0022 0.006158584
24.6993 -83.0022 0.00642949
24.6993 -83.0022 0.006543495
24.6993 -83.0022 0.006858123
24.6993 -83.0022 0.006921676
24.6993 -83.0022 0.008144021
24.6993 -83.0022 0.009158308
24.6993 -83.0022 0.009594418
24.6993 -83.0022 0.010030528
24.6993 -83.0022 0.011657559
24.6993 -83.0022 0.013471901
24.6993 -83.0022 0.014144878
24.6993 -83.0022 0.014391627
24.6993 -83.0022 0.017486339
24.6993 -83.0022 0.018214936
24.6993 -83.0022 0.026575225
24.6993 -83.0022 0.028098537
24.6993 -83.0022 0.030792918
24.6993 -83.0022 0.031290184
24.6993 -83.0022 0.037069341
24.6993 -83.0022 0.039708561
24.6993 -83.0022 0.04317488
24.6993 -83.0022 0.048498845
24.6993 -83.0022 0.053551913
24.6993 -83.0022 0.055722246
24.6993 -83.0022 0.058891455
24.6993 -83.0022 0.064480874
24.6993 -83.0022 0.074138683
24.6993 -83.0022 0.08765809
24.6993 -83.0022 0.091224018
24.6993 -83.0022 0.100728676
24.6993 -83.0022 0.120874411
24.6993 -83.0022 0.620660094
24.6993 -83.0022 0.70169361
24.6993 -83.0022 0.701700829
24.6993 -83.0022 0.777413479
24.6993 -83.0022 19.0
24.6993 -83.0022 20.0
24.6993 -83.0022 70.0
24.6993 -83.0022 71.0
24.6993 -83.0022 2293.0
24.6993 -83.0022 2333.0
24.6993 -83.0022 2598.0
24.6993 -83.0022 2745.0

In total, there are 380 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.
 


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.


 
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