Extract sightings and associated information from processed DAS data
Arguments
- x
an object of class
das_df, or a data frame that can be coerced to classdas_df- ...
ignored
- return.format
character; can be one of "default", "wide", "complete", or any partial match thereof (case sensitive). Formats described below
- return.events
character; event codes included in the output. Must be one or more of: "S", "K", "M", "G", "s", "k", "m", "g", "t", "p", "F" (case-sensitive). The default is all of these event codes
Value
Data frame with 1) the columns from x, excluding the 'Data#' columns,
and 2) columns with sighting information extracted from 'Data#' columns.
See das_format_pdf for more information the sighting information.
If return.format is "default", then there is one row for each species of each sighting event;
if return.format is "wide", then there is one row for each sighting event;
if return.format is "complete", then there is one row for every
group size estimate for each sighting event (excluding sperm whale "C" events - see the Details section).
The format-specific columns are described in their respective sections. The following sighting information columns are included in all return formats:
| Sighting information | Column name | Notes |
| Sighting number | SightNo | Character |
| Subgroup code | Subgroup | Character |
| Daily sighting number | SightNoDaily | See below |
| Observer that made the sighting | Obs | |
| Standard observer | ObsStd | Logical; TRUE if Obs is one of ObsL, Rec or ObsR, and FALSE otherwise |
| Bearing to the sighting | Bearing | Numeric; degrees, expected range 0 to 360 |
| Number of reticle marks | Reticle | Numeric |
| Distance (nautical miles) | DistNm | Numeric |
| Sighting cue | Cue | |
| Sighting method | Method | |
| Photos of school? | Photos | |
| Birds present with school? | Birds | |
| Calibration school? | CalibSchool | |
| Aerial photos taken? | PhotosAerial | |
| Biopsy taken? | Biopsy | |
| Probable sighting | Prob | Logical indicating if sighting has associated ? event; NA for non-S/K/M/G events |
| Number of species in sighting | nSp | NA for non-S/K/M/G events |
| Mixed species sighting | Mixed | Logical; TRUE if nSp > 1 |
| Group size of school - best estimate | GsSchoolBest | See below |
| Group size of school - high estimate | GsSchoolHigh | See below |
| Group size of school - low estimate | GsSchoolLow | See below |
| Course (true heading) of school at resight | CourseSchool | NA for non-s/k/m events |
| Presence of associated JFR | TurtleJFR | NA for non-"t" events; JFR = jellyfish, floating debris, or red tide |
| Estimated turtle maturity | TurtleAge | NA for non-"t" events |
| Perpendicular distance (km) to sighting | PerpDistKm | Calculated via (abs(sin(Bearing*pi/180) * DistNm) * 1.852) |
SightNoDaily is a running count of the number of S/K/M/G sightings that occurred on each day. It is formatted as 'YYYYMMDD'_'running count', e.g. "20050101_1".
The GsSchoolBest, GsSchoolHigh, and GsSchoolLow columns are either:
1) the arithmetic mean across observer estimates, for the "default" and "wide" formats, or
2) the individual observer estimates, for the "complete" format.
Note that for non-"complete" formats, na.rm = TRUE is used when calculating the mean,
and thus blank elements of estimates (but not the whole incomplete estimate) are ignored.
To convert the perpendicular distance back to nautical miles, one would divide PerpDistKm by 1.852
Details
DAS events contain specific information in the 'Data#' columns,
with the information depending on the event code for that row.
The output data frame contains columns with this specific information
extracted to dedicated columns as described below.
This function recognizes the following types of sightings:
marine mammal sightings (event codes "S", "K", or "M"),
marine mammal resights (codes "s", "k", "m"),
marine mammal subgroup sightings (code "G"),
marine mammal subgroup resights (code "g"),
turtle sightings (code "t"),
pinniped sightings (code "p"),
and fishing vessel sightings (code "F").
Warnings are printed if all S, K, M, and G events (and only these events) are not
followed by an A event and at least one numeric event.
See das_format_pdf for more information about events and event formats.
Of specific note - sperm whale sightings (species code 046) often contain additional estimates
recorded as "C" events immediately following the S, A, and numeric events.
Because these estimates are recorded as"C" events, they are NOT included in the
das_sight calculations or output for any return.format
The return.events argument simply provides a shortcut for
filtering the output of das_sight by event codes
Abbreviations used in output column names: Gs = group size, Sp = species, Nm = nautical mile, Perc = percentage, Prob = probable, GsSchool = school-level group size info
This function makes the following assumptions, and alterations to the raw DAS data:
"A" events immediately following an S/K/M/G event have the same sighting number (Data1 value) as the S/K/M/G event
The 'nSp' column is equivalent to the number of non-
NAvalues across the 'Data5', 'Data6', 'Data7', and 'Data8' columns for the pertinent "A" eventThe following data are coerced to a numeric using
as.numeric: Bearing, Reticle, DistNm, Cue, Method, species percentages, and group sizes (including for t, p, and F events). Note that if there are any formatting errors and these data are not numeric, the function will likely print a warning messageThe values for the following columns are capitalized using
toupper: 'Birds', 'Photos', 'CalibSchool', 'PhotosAerial', 'Biopsy', 'TurtleAge', and 'TurtleCapt'
The "default" format output
This output data frame contains 'long' sighting data, meaning there is one row for each species of each sighting event.
The GsSp... columns are calculated as follows:
for each species and for each observer estimate, the best/high/low school size estimate is multiplied by the applicable species percent estimate.
The values are grouped by species and then averaged to get single GsSpBest, GsSpHigh, and GsSpLow values for each species.
(using mean with na.rm = TRUE)
Sighting information columns/formats present specifically in the "default" format output:
| Sighting information | Column name | Notes |
| Species code | SpCode | Boat type or mammal, turtle, or pinniped species codes |
| Probable species code | SpCodeProb | Probable mammal species codes; NA if none or not applicable |
| Group size of species - best estimate | GsSpBest | The product of the arithmetic means of GsSchoolBest and the corresponding species percentage |
| Group size of species - high estimate | GsSpHigh | The product of the arithmetic means of GsSchoolHigh and the corresponding species percentage |
| Group size of species - low estimate | GsSpLow | The product of the arithmetic means of GsSchoolLow and the corresponding species percentage |
Note that for the above calculations,
the GsSchoolX value and corresponding species percentages were each
averaged across observers, using na.rm = TRUE,
before being multiplied to calculate GsSpX. For example, in the workflow:
GsSpBest1 = mean(.data$Data2, na.rm = TRUE) * mean(.data$Data5, na.rm = TRUE)
The "wide" and "complete" format outputs
The "wide" and "complete" options have very similar columns in their output date frames.
There are two main differences: 1) the "wide" format has one row for each sighting event,
while the complete format has a row for every observer estimate for each sightings, and thus
2) in the "wide" format, all numeric information for which there are multiple observer estimates
(school group size, species percentage, etc.) are averaged across estimated via
an arithmetic mean (using mean with na.rm = TRUE)
With these formats, note that the species/type code and group size for turtle, pinniped, and boat sightings are in their own column
Sighting information columns present in the "wide" and "complete" format outputs:
| Sighting information | Column name | Notes |
| Observer code - estimate | ObsEstimate | See below |
| Species 1 code | SpCode1 | |
| Species 2 code | SpCode2 | |
| Species 3 code | SpCode3 | |
| Species 4 code | SpCode4 | |
| Species 1 probable code | SpCodeProb1 | Extracted from '?' event |
| Species 2 probable code | SpCodeProb2 | Extracted from '?' event |
| Species 3 probable code | SpCodeProb3 | Extracted from '?' event |
| Species 4 probable code | SpCodeProb4 | Extracted from '?' event |
| Percentage of Sp 1 in school | SpPerc1 | |
| Percentage of Sp 2 in school | SpPerc2 | |
| Percentage of Sp 3 in school | SpPerc3 | |
| Percentage of Sp 4 in school | SpPerc4 | |
| Group size of species 1 | GsSpBest1 | Present in "wide" output only; see below |
| Group size of species 2 | GsSpBest2 | Present in "wide" output only; see below |
| Group size of species 3 | GsSpBest3 | Present in "wide" output only; see below |
| Group size of species 4 | GsSpBest4 | Present in "wide" output only; see below |
| Turtle species | TurtleSp | NA for non-"t" events |
| Turtle group size | TurtleGs | NA for non-"t" events |
| Was turtle captured? | TurtleCapt | NA for non-"t" events |
| Pinniped species | PinnipedSp | NA for non-"p" events |
| Pinniped group size | PinnipedGs | NA for non-"p" events |
| Boat or gear type | BoatType | NA for non-"F" events |
| Number of boats | BoatGs | NA for non-"F" events |
ObsEstimate refers to the code of the observer that made the corresponding estimate. For the "wide" format, ObsEstimate is a list-column of all of the observer codes that provided an estimate. Also in the "wide" format, the GsSpBest# columns are the product of the means of GsSchoolBest and the corresponding species percentage (see the Default section for calculation details). These numbers, 1 to 4, correspond to the order of the data as it appears in the DAS file
Examples
y <- system.file("das_sample.das", package = "swfscDAS")
y.proc <- das_process(y)
das_sight(y.proc)
#> Event DateTime Lat Lon OnEffort Cruise Mode OffsetGMT
#> 1 S 2013-01-13 06:46:02 39.36617 -137.5820 TRUE 1000 C 5
#> 2 S 2013-01-13 07:56:22 39.51767 -137.5285 TRUE 1000 C 5
#> 3 s 2013-01-13 08:06:00 39.54217 -137.5263 FALSE 1000 C 5
#> 4 s 2013-01-13 08:08:58 39.55000 -137.5255 FALSE 1000 C 5
#> 5 s 2013-01-13 08:15:32 39.56000 -137.5218 FALSE 1000 C 5
#> 6 s 2013-01-13 08:17:28 39.56233 -137.5210 FALSE 1000 C 5
#> 7 s 2013-01-13 08:19:39 39.56483 -137.5197 FALSE 1000 C 5
#> 8 s 2013-01-13 08:26:45 39.56400 -137.5140 FALSE 1000 C 5
#> 9 t 2013-01-13 09:34:27 39.59733 -137.4400 TRUE 1000 C 5
#> 10 t 2013-01-13 13:35:18 40.14000 -137.2048 FALSE 1000 C 5
#> 11 t 2013-01-13 14:02:55 40.18283 -137.1622 TRUE 1000 C 5
#> 12 S 2013-01-13 14:37:56 40.26567 -137.1350 TRUE 1000 C 5
#> 13 t 2013-01-13 15:36:47 40.36050 -137.0978 TRUE 1000 C 5
#> 14 S 2013-01-13 16:29:50 40.45133 -137.0628 TRUE 1000 C 5
#> 15 s 2013-01-13 16:36:34 40.46667 -137.0570 FALSE 1000 C 5
#> 16 S 2013-01-13 17:00:45 40.52400 -137.0522 TRUE 1000 C 5
#> 17 S 2013-01-13 17:00:45 40.52400 -137.0522 TRUE 1000 C 5
#> 18 t 2013-01-13 17:08:11 40.52083 -137.0383 FALSE 1000 C 5
#> 19 t 2013-01-13 17:45:10 40.50450 -137.0437 FALSE 1000 C 5
#> 20 S 2013-01-14 09:17:21 40.75183 -135.7748 FALSE 1000 <NA> 5
#> 21 F 2013-01-14 11:25:32 40.98950 -135.5965 TRUE 1000 C 5
#> 22 S 2013-01-14 11:47:51 41.04017 -135.5635 TRUE 1000 C 5
#> 23 S 2013-01-14 11:47:51 41.04017 -135.5635 TRUE 1000 C 5
#> 24 S 2013-01-14 11:49:14 41.04333 -135.5615 TRUE 1000 C 5
#> 25 S 2013-01-14 11:49:14 41.04333 -135.5615 TRUE 1000 C 5
#> EffType ESWsides Course SpdKt Bft SwellHght WindSpdKt RainFog HorizSun
#> 1 S 2 25 10.2 3 3 10 1 NA
#> 2 S 2 26 9.7 3 3 10 3 2
#> 3 S 2 26 9.7 3 3 10 3 2
#> 4 S 2 26 9.7 3 3 10 3 2
#> 5 S 2 26 9.7 3 3 10 3 2
#> 6 S 2 26 9.7 3 3 10 3 2
#> 7 S 2 26 9.7 3 3 10 3 2
#> 8 S 2 26 9.7 3 3 10 3 2
#> 9 S 2 27 9.0 3 3 10 1 2
#> 10 S 2 35 9.2 3 3 9 1 12
#> 11 S 2 20 9.3 3 3 6 1 8
#> 12 S 2 20 9.3 3 3 6 1 8
#> 13 S 2 16 8.9 2 3 6 1 9
#> 14 S 2 25 8.9 2 3 6 1 8
#> 15 S 2 25 8.9 2 3 6 1 8
#> 16 S 2 30 9.5 2 3 6 1 8
#> 17 S 2 30 9.5 2 3 6 1 8
#> 18 S 2 30 9.5 2 3 6 1 8
#> 19 S 2 30 9.5 2 3 6 1 8
#> 20 <NA> NA NA NA NA NA NA NA NA
#> 21 S 2 35 9.5 2 1 5 3 NA
#> 22 S 2 23 9.6 2 1 5 3 NA
#> 23 S 2 23 9.6 2 1 5 3 NA
#> 24 S 2 23 9.6 2 1 5 3 NA
#> 25 S 2 23 9.6 2 1 5 3 NA
#> VertSun Glare Vis ObsL Rec ObsR ObsInd EffortDot EventNum file_das
#> 1 NA NA 6.0 208 280 001 <NA> TRUE 15 das_sample.das
#> 2 2 FALSE 5.5 125 208 280 <NA> TRUE 35 das_sample.das
#> 3 2 FALSE 5.5 125 208 280 <NA> FALSE 39 das_sample.das
#> 4 2 FALSE 5.5 125 208 280 <NA> FALSE 41 das_sample.das
#> 5 2 FALSE 5.5 125 208 280 <NA> FALSE 42 das_sample.das
#> 6 2 FALSE 5.5 125 208 280 <NA> FALSE 44 das_sample.das
#> 7 2 FALSE 5.5 125 208 280 <NA> FALSE 45 das_sample.das
#> 8 2 FALSE 5.5 125 208 280 <NA> FALSE 46 das_sample.das
#> 9 2 FALSE 5.5 001 126 149 <NA> TRUE 59 das_sample.das
#> 10 12 FALSE 6.0 126 149 125 <NA> FALSE 118 das_sample.das
#> 11 1 FALSE 6.0 280 001 126 <NA> TRUE 131 das_sample.das
#> 12 1 FALSE 6.0 280 001 126 <NA> TRUE 136 das_sample.das
#> 13 1 FALSE 6.0 125 208 280 <NA> TRUE 153 das_sample.das
#> 14 2 FALSE 6.0 149 125 208 <NA> TRUE 167 das_sample.das
#> 15 2 FALSE 6.0 149 125 208 <NA> FALSE 170 das_sample.das
#> 16 2 FALSE 6.0 126 149 125 <NA> TRUE 181 das_sample.das
#> 17 2 FALSE 6.0 126 149 125 <NA> TRUE 181 das_sample.das
#> 18 2 FALSE 6.0 126 149 125 <NA> FALSE 186 das_sample.das
#> 19 2 FALSE 6.0 126 149 125 <NA> FALSE 190 das_sample.das
#> 20 NA NA NA <NA> <NA> <NA> <NA> FALSE 199 das_sample.das
#> 21 NA NA 4.0 149 125 208 <NA> TRUE 8 das_sample.das
#> 22 NA NA 4.0 149 125 208 <NA> TRUE 18 das_sample.das
#> 23 NA NA 4.0 149 125 208 <NA> TRUE 18 das_sample.das
#> 24 NA NA 4.0 149 125 208 <NA> TRUE 20 das_sample.das
#> 25 NA NA 4.0 149 125 208 <NA> TRUE 20 das_sample.das
#> line_num SightNo Subgroup SightNoDaily Obs ObsStd Bearing Reticle DistNm
#> 1 15 1406 <NA> 20130113_1 208 TRUE 309 2.8 1.06
#> 2 38 1407 <NA> 20130113_2 125 TRUE 326 0.4 2.97
#> 3 45 1407 <NA> <NA> <NA> FALSE 11 2.0 1.30
#> 4 47 1407 <NA> <NA> <NA> FALSE 5 3.5 0.90
#> 5 48 1407 <NA> <NA> <NA> FALSE 50 NA 0.50
#> 6 50 1407 <NA> <NA> <NA> FALSE 71 4.5 0.70
#> 7 51 1407 <NA> <NA> <NA> FALSE 104 4.5 0.70
#> 8 52 1407 <NA> <NA> <NA> FALSE 2 2.2 1.30
#> 9 65 <NA> <NA> <NA> 280 FALSE 120 NA 0.03
#> 10 124 <NA> <NA> <NA> 149 TRUE 270 NA 0.03
#> 11 137 <NA> <NA> <NA> 228 FALSE 300 NA 0.02
#> 12 142 1408 <NA> 20130113_3 280 TRUE 270 14.0 0.28
#> 13 162 <NA> <NA> <NA> 231 FALSE 45 NA 0.05
#> 14 176 1409 <NA> 20130113_4 149 TRUE 344 0.2 3.68
#> 15 182 1409 <NA> <NA> <NA> FALSE 356 0.4 3.00
#> 16 193 1410 <NA> 20130113_5 125 TRUE 70 1.4 1.66
#> 17 193 1410 <NA> 20130113_5 125 TRUE 70 1.4 1.66
#> 18 202 <NA> <NA> <NA> 280 FALSE 42 17.0 0.23
#> 19 206 <NA> <NA> <NA> 099 FALSE 180 NA 0.01
#> 20 215 1411 <NA> 20130114_1 280 FALSE 0 NA 0.00
#> 21 238 <NA> <NA> <NA> 149 TRUE 309 1.7 1.47
#> 22 248 1412 <NA> 20130114_2 149 TRUE 359 0.3 3.28
#> 23 248 1412 <NA> 20130114_2 149 TRUE 359 0.3 3.28
#> 24 252 1413 <NA> 20130114_3 208 TRUE 38 0.8 2.23
#> 25 252 1413 <NA> 20130114_3 208 TRUE 38 0.8 2.23
#> Cue Method Photos Birds CalibSchool PhotosAerial Biopsy Prob nSp Mixed
#> 1 3 4 N N <NA> <NA> <NA> FALSE 1 FALSE
#> 2 3 4 Y N <NA> <NA> <NA> FALSE 1 FALSE
#> 3 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 4 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 5 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 6 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 7 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 8 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 9 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 10 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 11 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 12 3 4 N N <NA> <NA> <NA> FALSE 1 FALSE
#> 13 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 14 3 4 Y Y <NA> <NA> <NA> FALSE 1 FALSE
#> 15 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 16 3 4 Y N <NA> <NA> <NA> FALSE 2 TRUE
#> 17 3 4 Y N <NA> <NA> <NA> FALSE 2 TRUE
#> 18 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 19 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 20 3 1 N N <NA> <NA> <NA> FALSE 1 FALSE
#> 21 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 22 2 4 Y N <NA> <NA> <NA> FALSE 2 TRUE
#> 23 2 4 Y N <NA> <NA> <NA> FALSE 2 TRUE
#> 24 3 4 Y N <NA> <NA> <NA> TRUE 2 TRUE
#> 25 3 4 Y N <NA> <NA> <NA> TRUE 2 TRUE
#> SpCode SpCodeProb GsSchoolBest GsSchoolHigh GsSchoolLow GsSpBest GsSpHigh
#> 1 018 <NA> NA NA 42.333333 NA NA
#> 2 076 <NA> 8.00000 14.00 5.666667 8.00000 14.0000
#> 3 <NA> <NA> NA NA NA NA NA
#> 4 <NA> <NA> NA NA NA NA NA
#> 5 <NA> <NA> NA NA NA NA NA
#> 6 <NA> <NA> NA NA NA NA NA
#> 7 <NA> <NA> NA NA NA NA NA
#> 8 <NA> <NA> NA NA NA NA NA
#> 9 LV <NA> 1.00000 NA NA 1.00000 NA
#> 10 DC <NA> 2.00000 NA NA 2.00000 NA
#> 11 DC <NA> 1.00000 NA NA 1.00000 NA
#> 12 037 <NA> 10.66667 20.00 10.666667 10.66667 20.0000
#> 13 DC <NA> 1.00000 NA NA 1.00000 NA
#> 14 016 <NA> 46.66667 79.00 46.666667 46.66667 79.0000
#> 15 <NA> <NA> NA NA NA NA NA
#> 16 013 <NA> 41.75000 72.75 41.750000 30.06000 52.3800
#> 17 016 <NA> 41.75000 72.75 41.750000 11.69000 20.3700
#> 18 DC <NA> 2.00000 NA NA 2.00000 NA
#> 19 LV <NA> 1.00000 NA NA 1.00000 NA
#> 20 075 <NA> NA NA NA NA NA
#> 21 <NA> <NA> NA NA NA NA NA
#> 22 018 <NA> 151.50000 249.00 151.500000 128.77500 211.6500
#> 23 277 <NA> 151.50000 249.00 151.500000 22.72500 37.3500
#> 24 016 016 21.25000 37.75 21.250000 15.08750 26.8025
#> 25 277 016 21.25000 37.75 21.250000 6.16250 10.9475
#> GsSpLow CourseSchool TurtleJFR TurtleAge TurtleCapt PerpDistKm
#> 1 42.333333 NA <NA> <NA> <NA> 1.525631e+00
#> 2 5.666667 NA <NA> <NA> <NA> 3.075807e+00
#> 3 NA NA <NA> <NA> <NA> 4.593917e-01
#> 4 NA NA <NA> <NA> <NA> 1.452712e-01
#> 5 NA NA <NA> <NA> <NA> 7.093572e-01
#> 6 NA 100 <NA> <NA> <NA> 1.225770e+00
#> 7 NA 100 <NA> <NA> <NA> 1.257891e+00
#> 8 NA NA <NA> <NA> <NA> 8.402403e-02
#> 9 NA NA <NA> A N 4.811637e-02
#> 10 NA NA <NA> A N 5.556000e-02
#> 11 NA NA <NA> J N 3.207758e-02
#> 12 10.666667 NA <NA> <NA> <NA> 5.185600e-01
#> 13 NA NA <NA> A <NA> 6.547809e-02
#> 14 46.666667 NA <NA> <NA> <NA> 1.878568e+00
#> 15 NA NA <NA> <NA> <NA> 3.875670e-01
#> 16 30.060000 NA <NA> <NA> <NA> 2.888916e+00
#> 17 11.690000 NA <NA> <NA> <NA> 2.888916e+00
#> 18 NA NA F A Y 2.850229e-01
#> 19 NA NA <NA> A N 2.268046e-18
#> 20 NA NA <NA> <NA> <NA> 0.000000e+00
#> 21 NA NA <NA> <NA> <NA> 2.115733e+00
#> 22 128.775000 NA <NA> <NA> <NA> 1.060157e-01
#> 23 22.725000 NA <NA> <NA> <NA> 1.060157e-01
#> 24 15.087500 NA <NA> <NA> <NA> 2.542657e+00
#> 25 6.162500 NA <NA> <NA> <NA> 2.542657e+00
das_sight(y.proc, return.format = "complete")
#> Event DateTime Lat Lon OnEffort Cruise Mode OffsetGMT
#> 1 S 2013-01-13 06:46:02 39.36617 -137.5820 TRUE 1000 C 5
#> 2 S 2013-01-13 06:46:02 39.36617 -137.5820 TRUE 1000 C 5
#> 3 S 2013-01-13 06:46:02 39.36617 -137.5820 TRUE 1000 C 5
#> 4 S 2013-01-13 07:56:22 39.51767 -137.5285 TRUE 1000 C 5
#> 5 S 2013-01-13 07:56:22 39.51767 -137.5285 TRUE 1000 C 5
#> 6 S 2013-01-13 07:56:22 39.51767 -137.5285 TRUE 1000 C 5
#> 7 s 2013-01-13 08:06:00 39.54217 -137.5263 FALSE 1000 C 5
#> 8 s 2013-01-13 08:08:58 39.55000 -137.5255 FALSE 1000 C 5
#> 9 s 2013-01-13 08:15:32 39.56000 -137.5218 FALSE 1000 C 5
#> 10 s 2013-01-13 08:17:28 39.56233 -137.5210 FALSE 1000 C 5
#> 11 s 2013-01-13 08:19:39 39.56483 -137.5197 FALSE 1000 C 5
#> 12 s 2013-01-13 08:26:45 39.56400 -137.5140 FALSE 1000 C 5
#> 13 t 2013-01-13 09:34:27 39.59733 -137.4400 TRUE 1000 C 5
#> 14 t 2013-01-13 13:35:18 40.14000 -137.2048 FALSE 1000 C 5
#> 15 t 2013-01-13 14:02:55 40.18283 -137.1622 TRUE 1000 C 5
#> 16 S 2013-01-13 14:37:56 40.26567 -137.1350 TRUE 1000 C 5
#> 17 S 2013-01-13 14:37:56 40.26567 -137.1350 TRUE 1000 C 5
#> 18 S 2013-01-13 14:37:56 40.26567 -137.1350 TRUE 1000 C 5
#> 19 t 2013-01-13 15:36:47 40.36050 -137.0978 TRUE 1000 C 5
#> 20 S 2013-01-13 16:29:50 40.45133 -137.0628 TRUE 1000 C 5
#> 21 S 2013-01-13 16:29:50 40.45133 -137.0628 TRUE 1000 C 5
#> 22 S 2013-01-13 16:29:50 40.45133 -137.0628 TRUE 1000 C 5
#> 23 s 2013-01-13 16:36:34 40.46667 -137.0570 FALSE 1000 C 5
#> 24 S 2013-01-13 17:00:45 40.52400 -137.0522 TRUE 1000 C 5
#> 25 S 2013-01-13 17:00:45 40.52400 -137.0522 TRUE 1000 C 5
#> 26 S 2013-01-13 17:00:45 40.52400 -137.0522 TRUE 1000 C 5
#> 27 S 2013-01-13 17:00:45 40.52400 -137.0522 TRUE 1000 C 5
#> 28 t 2013-01-13 17:08:11 40.52083 -137.0383 FALSE 1000 C 5
#> 29 t 2013-01-13 17:45:10 40.50450 -137.0437 FALSE 1000 C 5
#> 30 S 2013-01-14 09:17:21 40.75183 -135.7748 FALSE 1000 <NA> 5
#> 31 F 2013-01-14 11:25:32 40.98950 -135.5965 TRUE 1000 C 5
#> 32 S 2013-01-14 11:47:51 41.04017 -135.5635 TRUE 1000 C 5
#> 33 S 2013-01-14 11:47:51 41.04017 -135.5635 TRUE 1000 C 5
#> 34 S 2013-01-14 11:49:14 41.04333 -135.5615 TRUE 1000 C 5
#> 35 S 2013-01-14 11:49:14 41.04333 -135.5615 TRUE 1000 C 5
#> 36 S 2013-01-14 11:49:14 41.04333 -135.5615 TRUE 1000 C 5
#> 37 S 2013-01-14 11:49:14 41.04333 -135.5615 TRUE 1000 C 5
#> EffType ESWsides Course SpdKt Bft SwellHght WindSpdKt RainFog HorizSun
#> 1 S 2 25 10.2 3 3 10 1 NA
#> 2 S 2 25 10.2 3 3 10 1 NA
#> 3 S 2 25 10.2 3 3 10 1 NA
#> 4 S 2 26 9.7 3 3 10 3 2
#> 5 S 2 26 9.7 3 3 10 3 2
#> 6 S 2 26 9.7 3 3 10 3 2
#> 7 S 2 26 9.7 3 3 10 3 2
#> 8 S 2 26 9.7 3 3 10 3 2
#> 9 S 2 26 9.7 3 3 10 3 2
#> 10 S 2 26 9.7 3 3 10 3 2
#> 11 S 2 26 9.7 3 3 10 3 2
#> 12 S 2 26 9.7 3 3 10 3 2
#> 13 S 2 27 9.0 3 3 10 1 2
#> 14 S 2 35 9.2 3 3 9 1 12
#> 15 S 2 20 9.3 3 3 6 1 8
#> 16 S 2 20 9.3 3 3 6 1 8
#> 17 S 2 20 9.3 3 3 6 1 8
#> 18 S 2 20 9.3 3 3 6 1 8
#> 19 S 2 16 8.9 2 3 6 1 9
#> 20 S 2 25 8.9 2 3 6 1 8
#> 21 S 2 25 8.9 2 3 6 1 8
#> 22 S 2 25 8.9 2 3 6 1 8
#> 23 S 2 25 8.9 2 3 6 1 8
#> 24 S 2 30 9.5 2 3 6 1 8
#> 25 S 2 30 9.5 2 3 6 1 8
#> 26 S 2 30 9.5 2 3 6 1 8
#> 27 S 2 30 9.5 2 3 6 1 8
#> 28 S 2 30 9.5 2 3 6 1 8
#> 29 S 2 30 9.5 2 3 6 1 8
#> 30 <NA> NA NA NA NA NA NA NA NA
#> 31 S 2 35 9.5 2 1 5 3 NA
#> 32 S 2 23 9.6 2 1 5 3 NA
#> 33 S 2 23 9.6 2 1 5 3 NA
#> 34 S 2 23 9.6 2 1 5 3 NA
#> 35 S 2 23 9.6 2 1 5 3 NA
#> 36 S 2 23 9.6 2 1 5 3 NA
#> 37 S 2 23 9.6 2 1 5 3 NA
#> VertSun Glare Vis ObsL Rec ObsR ObsInd EffortDot EventNum file_das
#> 1 NA NA 6.0 208 280 001 <NA> TRUE 15 das_sample.das
#> 2 NA NA 6.0 208 280 001 <NA> TRUE 15 das_sample.das
#> 3 NA NA 6.0 208 280 001 <NA> TRUE 15 das_sample.das
#> 4 2 FALSE 5.5 125 208 280 <NA> TRUE 35 das_sample.das
#> 5 2 FALSE 5.5 125 208 280 <NA> TRUE 35 das_sample.das
#> 6 2 FALSE 5.5 125 208 280 <NA> TRUE 35 das_sample.das
#> 7 2 FALSE 5.5 125 208 280 <NA> FALSE 39 das_sample.das
#> 8 2 FALSE 5.5 125 208 280 <NA> FALSE 41 das_sample.das
#> 9 2 FALSE 5.5 125 208 280 <NA> FALSE 42 das_sample.das
#> 10 2 FALSE 5.5 125 208 280 <NA> FALSE 44 das_sample.das
#> 11 2 FALSE 5.5 125 208 280 <NA> FALSE 45 das_sample.das
#> 12 2 FALSE 5.5 125 208 280 <NA> FALSE 46 das_sample.das
#> 13 2 FALSE 5.5 001 126 149 <NA> TRUE 59 das_sample.das
#> 14 12 FALSE 6.0 126 149 125 <NA> FALSE 118 das_sample.das
#> 15 1 FALSE 6.0 280 001 126 <NA> TRUE 131 das_sample.das
#> 16 1 FALSE 6.0 280 001 126 <NA> TRUE 136 das_sample.das
#> 17 1 FALSE 6.0 280 001 126 <NA> TRUE 136 das_sample.das
#> 18 1 FALSE 6.0 280 001 126 <NA> TRUE 136 das_sample.das
#> 19 1 FALSE 6.0 125 208 280 <NA> TRUE 153 das_sample.das
#> 20 2 FALSE 6.0 149 125 208 <NA> TRUE 167 das_sample.das
#> 21 2 FALSE 6.0 149 125 208 <NA> TRUE 167 das_sample.das
#> 22 2 FALSE 6.0 149 125 208 <NA> TRUE 167 das_sample.das
#> 23 2 FALSE 6.0 149 125 208 <NA> FALSE 170 das_sample.das
#> 24 2 FALSE 6.0 126 149 125 <NA> TRUE 181 das_sample.das
#> 25 2 FALSE 6.0 126 149 125 <NA> TRUE 181 das_sample.das
#> 26 2 FALSE 6.0 126 149 125 <NA> TRUE 181 das_sample.das
#> 27 2 FALSE 6.0 126 149 125 <NA> TRUE 181 das_sample.das
#> 28 2 FALSE 6.0 126 149 125 <NA> FALSE 186 das_sample.das
#> 29 2 FALSE 6.0 126 149 125 <NA> FALSE 190 das_sample.das
#> 30 NA NA NA <NA> <NA> <NA> <NA> FALSE 199 das_sample.das
#> 31 NA NA 4.0 149 125 208 <NA> TRUE 8 das_sample.das
#> 32 NA NA 4.0 149 125 208 <NA> TRUE 18 das_sample.das
#> 33 NA NA 4.0 149 125 208 <NA> TRUE 18 das_sample.das
#> 34 NA NA 4.0 149 125 208 <NA> TRUE 20 das_sample.das
#> 35 NA NA 4.0 149 125 208 <NA> TRUE 20 das_sample.das
#> 36 NA NA 4.0 149 125 208 <NA> TRUE 20 das_sample.das
#> 37 NA NA 4.0 149 125 208 <NA> TRUE 20 das_sample.das
#> line_num SightNo Subgroup SightNoDaily Obs ObsStd Bearing Reticle DistNm
#> 1 15 1406 <NA> 20130113_1 208 TRUE 309 2.8 1.06
#> 2 15 1406 <NA> 20130113_1 208 TRUE 309 2.8 1.06
#> 3 15 1406 <NA> 20130113_1 208 TRUE 309 2.8 1.06
#> 4 38 1407 <NA> 20130113_2 125 TRUE 326 0.4 2.97
#> 5 38 1407 <NA> 20130113_2 125 TRUE 326 0.4 2.97
#> 6 38 1407 <NA> 20130113_2 125 TRUE 326 0.4 2.97
#> 7 45 1407 <NA> <NA> <NA> FALSE 11 2.0 1.30
#> 8 47 1407 <NA> <NA> <NA> FALSE 5 3.5 0.90
#> 9 48 1407 <NA> <NA> <NA> FALSE 50 NA 0.50
#> 10 50 1407 <NA> <NA> <NA> FALSE 71 4.5 0.70
#> 11 51 1407 <NA> <NA> <NA> FALSE 104 4.5 0.70
#> 12 52 1407 <NA> <NA> <NA> FALSE 2 2.2 1.30
#> 13 65 <NA> <NA> <NA> 280 FALSE 120 NA 0.03
#> 14 124 <NA> <NA> <NA> 149 TRUE 270 NA 0.03
#> 15 137 <NA> <NA> <NA> 228 FALSE 300 NA 0.02
#> 16 142 1408 <NA> 20130113_3 280 TRUE 270 14.0 0.28
#> 17 142 1408 <NA> 20130113_3 280 TRUE 270 14.0 0.28
#> 18 142 1408 <NA> 20130113_3 280 TRUE 270 14.0 0.28
#> 19 162 <NA> <NA> <NA> 231 FALSE 45 NA 0.05
#> 20 176 1409 <NA> 20130113_4 149 TRUE 344 0.2 3.68
#> 21 176 1409 <NA> 20130113_4 149 TRUE 344 0.2 3.68
#> 22 176 1409 <NA> 20130113_4 149 TRUE 344 0.2 3.68
#> 23 182 1409 <NA> <NA> <NA> FALSE 356 0.4 3.00
#> 24 193 1410 <NA> 20130113_5 125 TRUE 70 1.4 1.66
#> 25 193 1410 <NA> 20130113_5 125 TRUE 70 1.4 1.66
#> 26 193 1410 <NA> 20130113_5 125 TRUE 70 1.4 1.66
#> 27 193 1410 <NA> 20130113_5 125 TRUE 70 1.4 1.66
#> 28 202 <NA> <NA> <NA> 280 FALSE 42 17.0 0.23
#> 29 206 <NA> <NA> <NA> 099 FALSE 180 NA 0.01
#> 30 215 1411 <NA> 20130114_1 280 FALSE 0 NA 0.00
#> 31 238 <NA> <NA> <NA> 149 TRUE 309 1.7 1.47
#> 32 248 1412 <NA> 20130114_2 149 TRUE 359 0.3 3.28
#> 33 248 1412 <NA> 20130114_2 149 TRUE 359 0.3 3.28
#> 34 252 1413 <NA> 20130114_3 208 TRUE 38 0.8 2.23
#> 35 252 1413 <NA> 20130114_3 208 TRUE 38 0.8 2.23
#> 36 252 1413 <NA> 20130114_3 208 TRUE 38 0.8 2.23
#> 37 252 1413 <NA> 20130114_3 208 TRUE 38 0.8 2.23
#> Cue Method Photos Birds CalibSchool PhotosAerial Biopsy Prob nSp Mixed
#> 1 3 4 N N <NA> <NA> <NA> FALSE 1 FALSE
#> 2 3 4 N N <NA> <NA> <NA> FALSE 1 FALSE
#> 3 3 4 N N <NA> <NA> <NA> FALSE 1 FALSE
#> 4 3 4 Y N <NA> <NA> <NA> FALSE 1 FALSE
#> 5 3 4 Y N <NA> <NA> <NA> FALSE 1 FALSE
#> 6 3 4 Y N <NA> <NA> <NA> FALSE 1 FALSE
#> 7 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 8 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 9 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 10 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 11 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 12 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 13 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 14 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 15 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 16 3 4 N N <NA> <NA> <NA> FALSE 1 FALSE
#> 17 3 4 N N <NA> <NA> <NA> FALSE 1 FALSE
#> 18 3 4 N N <NA> <NA> <NA> FALSE 1 FALSE
#> 19 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 20 3 4 Y Y <NA> <NA> <NA> FALSE 1 FALSE
#> 21 3 4 Y Y <NA> <NA> <NA> FALSE 1 FALSE
#> 22 3 4 Y Y <NA> <NA> <NA> FALSE 1 FALSE
#> 23 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 24 3 4 Y N <NA> <NA> <NA> FALSE 2 TRUE
#> 25 3 4 Y N <NA> <NA> <NA> FALSE 2 TRUE
#> 26 3 4 Y N <NA> <NA> <NA> FALSE 2 TRUE
#> 27 3 4 Y N <NA> <NA> <NA> FALSE 2 TRUE
#> 28 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 29 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 30 3 1 N N <NA> <NA> <NA> FALSE 1 FALSE
#> 31 NA NA <NA> <NA> <NA> <NA> <NA> NA NA NA
#> 32 2 4 Y N <NA> <NA> <NA> FALSE 2 TRUE
#> 33 2 4 Y N <NA> <NA> <NA> FALSE 2 TRUE
#> 34 3 4 Y N <NA> <NA> <NA> TRUE 2 TRUE
#> 35 3 4 Y N <NA> <NA> <NA> TRUE 2 TRUE
#> 36 3 4 Y N <NA> <NA> <NA> TRUE 2 TRUE
#> 37 3 4 Y N <NA> <NA> <NA> TRUE 2 TRUE
#> ObsEstimate SpCode1 SpCode2 SpCode3 SpCode4 SpCodeProb1 SpCodeProb2
#> 1 280 018 <NA> <NA> <NA> <NA> <NA>
#> 2 001 018 <NA> <NA> <NA> <NA> <NA>
#> 3 208 018 <NA> <NA> <NA> <NA> <NA>
#> 4 280 076 <NA> <NA> <NA> <NA> <NA>
#> 5 001 076 <NA> <NA> <NA> <NA> <NA>
#> 6 125 076 <NA> <NA> <NA> <NA> <NA>
#> 7 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 8 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 9 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 10 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 11 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 12 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 13 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 14 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 15 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 16 280 037 <NA> <NA> <NA> <NA> <NA>
#> 17 001 037 <NA> <NA> <NA> <NA> <NA>
#> 18 126 037 <NA> <NA> <NA> <NA> <NA>
#> 19 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 20 125 016 <NA> <NA> <NA> <NA> <NA>
#> 21 149 016 <NA> <NA> <NA> <NA> <NA>
#> 22 208 016 <NA> <NA> <NA> <NA> <NA>
#> 23 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 24 280 013 016 <NA> <NA> <NA> <NA>
#> 25 125 013 016 <NA> <NA> <NA> <NA>
#> 26 149 013 016 <NA> <NA> <NA> <NA>
#> 27 126 013 016 <NA> <NA> <NA> <NA>
#> 28 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 29 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 30 280 075 <NA> <NA> <NA> <NA> <NA>
#> 31 <NA> <NA> <NA> <NA> <NA> <NA> <NA>
#> 32 149 018 277 <NA> <NA> <NA> <NA>
#> 33 126 018 277 <NA> <NA> <NA> <NA>
#> 34 125 016 277 <NA> <NA> 016 016
#> 35 208 016 277 <NA> <NA> 016 016
#> 36 149 016 277 <NA> <NA> 016 016
#> 37 126 016 277 <NA> <NA> 016 016
#> SpCodeProb3 SpCodeProb4 SpPerc1 SpPerc2 SpPerc3 SpPerc4 GsSchoolBest
#> 1 <NA> <NA> 100 NA NA NA NA
#> 2 <NA> <NA> 100 NA NA NA NA
#> 3 <NA> <NA> 100 NA NA NA NA
#> 4 <NA> <NA> 100 NA NA NA 6
#> 5 <NA> <NA> 100 NA NA NA 9
#> 6 <NA> <NA> 100 NA NA NA 9
#> 7 <NA> <NA> NA NA NA NA NA
#> 8 <NA> <NA> NA NA NA NA NA
#> 9 <NA> <NA> NA NA NA NA NA
#> 10 <NA> <NA> NA NA NA NA NA
#> 11 <NA> <NA> NA NA NA NA NA
#> 12 <NA> <NA> NA NA NA NA NA
#> 13 <NA> <NA> NA NA NA NA NA
#> 14 <NA> <NA> NA NA NA NA NA
#> 15 <NA> <NA> NA NA NA NA NA
#> 16 <NA> <NA> 100 NA NA NA 11
#> 17 <NA> <NA> 100 NA NA NA 12
#> 18 <NA> <NA> 100 NA NA NA 9
#> 19 <NA> <NA> NA NA NA NA NA
#> 20 <NA> <NA> 100 NA NA NA 46
#> 21 <NA> <NA> 100 NA NA NA 28
#> 22 <NA> <NA> 100 NA NA NA 66
#> 23 <NA> <NA> NA NA NA NA NA
#> 24 <NA> <NA> 68 32 NA NA 37
#> 25 <NA> <NA> 75 25 NA NA 35
#> 26 <NA> <NA> 65 35 NA NA 29
#> 27 <NA> <NA> 80 20 NA NA 66
#> 28 <NA> <NA> NA NA NA NA NA
#> 29 <NA> <NA> NA NA NA NA NA
#> 30 <NA> <NA> 100 NA NA NA NA
#> 31 <NA> <NA> NA NA NA NA NA
#> 32 <NA> <NA> 80 20 NA NA 183
#> 33 <NA> <NA> 90 10 NA NA 120
#> 34 <NA> <NA> 60 40 NA NA 21
#> 35 <NA> <NA> 56 44 NA NA 16
#> 36 <NA> <NA> 70 30 NA NA 12
#> 37 <NA> <NA> 98 2 NA NA 36
#> GsSchoolHigh GsSchoolLow CourseSchool TurtleSp TurtleGs TurtleJFR TurtleAge
#> 1 NA 43 NA <NA> NA <NA> <NA>
#> 2 NA 36 NA <NA> NA <NA> <NA>
#> 3 NA 48 NA <NA> NA <NA> <NA>
#> 4 10 6 NA <NA> NA <NA> <NA>
#> 5 10 2 NA <NA> NA <NA> <NA>
#> 6 22 9 NA <NA> NA <NA> <NA>
#> 7 NA NA NA <NA> NA <NA> <NA>
#> 8 NA NA NA <NA> NA <NA> <NA>
#> 9 NA NA NA <NA> NA <NA> <NA>
#> 10 NA NA 100 <NA> NA <NA> <NA>
#> 11 NA NA 100 <NA> NA <NA> <NA>
#> 12 NA NA NA <NA> NA <NA> <NA>
#> 13 NA NA NA LV 1 <NA> A
#> 14 NA NA NA DC 2 <NA> A
#> 15 NA NA NA DC 1 <NA> J
#> 16 24 11 NA <NA> NA <NA> <NA>
#> 17 23 12 NA <NA> NA <NA> <NA>
#> 18 13 9 NA <NA> NA <NA> <NA>
#> 19 NA NA NA DC 1 <NA> A
#> 20 90 46 NA <NA> NA <NA> <NA>
#> 21 65 28 NA <NA> NA <NA> <NA>
#> 22 82 66 NA <NA> NA <NA> <NA>
#> 23 NA NA NA <NA> NA <NA> <NA>
#> 24 72 37 NA <NA> NA <NA> <NA>
#> 25 74 35 NA <NA> NA <NA> <NA>
#> 26 52 29 NA <NA> NA <NA> <NA>
#> 27 93 66 NA <NA> NA <NA> <NA>
#> 28 NA NA NA DC 2 F A
#> 29 NA NA NA LV 1 <NA> A
#> 30 NA NA NA <NA> NA <NA> <NA>
#> 31 NA NA NA <NA> NA <NA> <NA>
#> 32 328 183 NA <NA> NA <NA> <NA>
#> 33 170 120 NA <NA> NA <NA> <NA>
#> 34 60 21 NA <NA> NA <NA> <NA>
#> 35 20 16 NA <NA> NA <NA> <NA>
#> 36 18 12 NA <NA> NA <NA> <NA>
#> 37 53 36 NA <NA> NA <NA> <NA>
#> TurtleCapt PinnipedSp PinnipedGs BoatType BoatGs PerpDistKm
#> 1 <NA> <NA> NA <NA> NA 1.525631e+00
#> 2 <NA> <NA> NA <NA> NA 1.525631e+00
#> 3 <NA> <NA> NA <NA> NA 1.525631e+00
#> 4 <NA> <NA> NA <NA> NA 3.075807e+00
#> 5 <NA> <NA> NA <NA> NA 3.075807e+00
#> 6 <NA> <NA> NA <NA> NA 3.075807e+00
#> 7 <NA> <NA> NA <NA> NA 4.593917e-01
#> 8 <NA> <NA> NA <NA> NA 1.452712e-01
#> 9 <NA> <NA> NA <NA> NA 7.093572e-01
#> 10 <NA> <NA> NA <NA> NA 1.225770e+00
#> 11 <NA> <NA> NA <NA> NA 1.257891e+00
#> 12 <NA> <NA> NA <NA> NA 8.402403e-02
#> 13 N <NA> NA <NA> NA 4.811637e-02
#> 14 N <NA> NA <NA> NA 5.556000e-02
#> 15 N <NA> NA <NA> NA 3.207758e-02
#> 16 <NA> <NA> NA <NA> NA 5.185600e-01
#> 17 <NA> <NA> NA <NA> NA 5.185600e-01
#> 18 <NA> <NA> NA <NA> NA 5.185600e-01
#> 19 <NA> <NA> NA <NA> NA 6.547809e-02
#> 20 <NA> <NA> NA <NA> NA 1.878568e+00
#> 21 <NA> <NA> NA <NA> NA 1.878568e+00
#> 22 <NA> <NA> NA <NA> NA 1.878568e+00
#> 23 <NA> <NA> NA <NA> NA 3.875670e-01
#> 24 <NA> <NA> NA <NA> NA 2.888916e+00
#> 25 <NA> <NA> NA <NA> NA 2.888916e+00
#> 26 <NA> <NA> NA <NA> NA 2.888916e+00
#> 27 <NA> <NA> NA <NA> NA 2.888916e+00
#> 28 Y <NA> NA <NA> NA 2.850229e-01
#> 29 N <NA> NA <NA> NA 2.268046e-18
#> 30 <NA> <NA> NA <NA> NA 0.000000e+00
#> 31 <NA> <NA> NA <NA> NA 2.115733e+00
#> 32 <NA> <NA> NA <NA> NA 1.060157e-01
#> 33 <NA> <NA> NA <NA> NA 1.060157e-01
#> 34 <NA> <NA> NA <NA> NA 2.542657e+00
#> 35 <NA> <NA> NA <NA> NA 2.542657e+00
#> 36 <NA> <NA> NA <NA> NA 2.542657e+00
#> 37 <NA> <NA> NA <NA> NA 2.542657e+00