* using log directory ‘/Users/ripley/R/packages/tests-devel/tiledb.Rcheck’ * using R Under development (unstable) (2026-02-09 r89390) * using platform: aarch64-apple-darwin25.2.0 * R was compiled by Apple clang version 17.0.0 (clang-1700.6.4.2) GNU Fortran (GCC) 14.2.0 * running under: macOS Tahoe 26.2 * using session charset: UTF-8 * current time: 2026-02-10 09:36:17 UTC * using option ‘--no-stop-on-test-error’ * checking for file ‘tiledb/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘tiledb’ version ‘0.33.0’ * package encoding: UTF-8 * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for executable files ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK * checking whether package ‘tiledb’ can be installed ... [33s/38s] OK * used C compiler: ‘Apple clang version 17.0.0 (clang-1700.6.4.2)’ * used C++ compiler: ‘Apple clang version 17.0.0 (clang-1700.6.4.2)’ * used SDK: ‘MacOSX26.2.sdk’ * checking C++ specification ... INFO specified C++17 * checking installed package size ... INFO installed size is 42.6Mb sub-directories of 1Mb or more: libs 2.0Mb tiledb 38.1Mb * checking package directory ... OK * checking ‘build’ directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the namespace can be loaded with stated dependencies ... OK * checking whether the namespace can be unloaded cleanly ... OK * checking loading without being on the library search path ... OK * checking whether startup messages can be suppressed ... OK * checking use of S3 registration ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... OK * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking line endings in shell scripts ... OK * checking line endings in C/C++/Fortran sources/headers ... OK * checking line endings in Makefiles ... OK * checking compilation flags in Makevars ... OK * checking for GNU extensions in Makefiles ... OK * checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK * checking use of PKG_*FLAGS in Makefiles ... OK * checking pragmas in C/C++ headers and code ... OK * checking compilation flags used ... OK * checking compiled code ... OK * checking installed files from ‘inst/doc’ ... OK * checking files in ‘vignettes’ ... OK * checking examples ...sh: line 1: 79311 Segmentation fault: 11 LANGUAGE=en _R_CHECK_INTERNALS2_=1 '/Users/ripley/R/R-devel/bin/R' --vanilla > 'tiledb-Ex.Rout' 2>&1 < 'tiledb-Ex.R' ERROR Running examples in ‘tiledb-Ex.R’ failed The error most likely occurred in: > ### Name: fromDataFrame > ### Title: Create a TileDB dense or sparse array from a given 'data.frame' > ### Object > ### Aliases: fromDataFrame > > ### ** Examples > > ## Don't show: > ctx <- tiledb_ctx(limitTileDBCores()) > ## End(Don't show) > uri <- tempfile() > fromDataFrame(iris, uri) *** caught segfault *** address 0x1, cause 'invalid permissions' Traceback: 1: RcppSpdlog::formatter(s, v) 2: fmt(s, ...) 3: RcppSpdlog::log_debug(fmt(s, ...)) 4: spdl::debug("[tiledb_array] '[<-' alloc buf {} '{}': {}, rows: {} null: {} asint64: {}", k, colnam, alltypes[k], nr, allnullable[k], asint64) 5: `[<-`(`*tmp*`, , value = list(`__tiledb_rows` = 1:150, Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6, 5, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1, 5.4, 5.1, 4.6, 5.1, 4.8, 5, 5, 5.2, 5.2, 4.7, 4.8, 5.4, 5.2, 5.5, 4.9, 5, 5.5, 4.9, 4.4, 5.1, 5, 4.5, 4.4, 5, 5.1, 4.8, 5.1, 4.6, 5.3, 5, 7, 6.4, 6.9, 5.5, 6.5, 5.7, 6.3, 4.9, 6.6, 5.2, 5, 5.9, 6, 6.1, 5.6, 6.7, 5.6, 5.8, 6.2, 5.6, 5.9, 6.1, 6.3, 6.1, 6.4, 6.6, 6.8, 6.7, 6, 5.7, 5.5, 5.5, 5.8, 6, 5.4, 6, 6.7, 6.3, 5.6, 5.5, 5.5, 6.1, 5.8, 5, 5.6, 5.7, 5.7, 6.2, 5.1, 5.7, 6.3, 5.8, 7.1, 6.3, 6.5, 7.6, 4.9, 7.3, 6.7, 7.2, 6.5, 6.4, 6.8, 5.7, 5.8, 6.4, 6.5, 7.7, 7.7, 6, 6.9, 5.6, 7.7, 6.3, 6.7, 7.2, 6.2, 6.1, 6.4, 7.2, 7.4, 7.9, 6.4, 6.3, 6.1, 7.7, 6.3, 6.4, 6, 6.9, 6.7, 6.9, 5.8, 6.8, 6.7, 6.7, 6.3, 6.5, 6.2, 5.9), Sepal.Width = c(3.5, 3, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.4, 3, 3, 4, 4.4, 3.9, 3.5, 3.8, 3.8, 3.4, 3.7, 3.6, 3.3, 3.4, 3, 3.4, 3.5, 3.4, 3.2, 3.1, 3.4, 4.1, 4.2, 3.1, 3.2, 3.5, 3.6, 3, 3.4, 3.5, 2.3, 3.2, 3.5, 3.8, 3, 3.8, 3.2, 3.7, 3.3, 3.2, 3.2, 3.1, 2.3, 2.8, 2.8, 3.3, 2.4, 2.9, 2.7, 2, 3, 2.2, 2.9, 2.9, 3.1, 3, 2.7, 2.2, 2.5, 3.2, 2.8, 2.5, 2.8, 2.9, 3, 2.8, 3, 2.9, 2.6, 2.4, 2.4, 2.7, 2.7, 3, 3.4, 3.1, 2.3, 3, 2.5, 2.6, 3, 2.6, 2.3, 2.7, 3, 2.9, 2.9, 2.5, 2.8, 3.3, 2.7, 3, 2.9, 3, 3, 2.5, 2.9, 2.5, 3.6, 3.2, 2.7, 3, 2.5, 2.8, 3.2, 3, 3.8, 2.6, 2.2, 3.2, 2.8, 2.8, 2.7, 3.3, 3.2, 2.8, 3, 2.8, 3, 2.8, 3.8, 2.8, 2.8, 2.6, 3, 3.4, 3.1, 3, 3.1, 3.1, 3.1, 2.7, 3.2, 3.3, 3, 2.5, 3, 3.4, 3), Petal.Length = c(1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.6, 1.4, 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5, 1.7, 1.5, 1, 1.7, 1.9, 1.6, 1.6, 1.5, 1.4, 1.6, 1.6, 1.5, 1.5, 1.4, 1.5, 1.2, 1.3, 1.4, 1.3, 1.5, 1.3, 1.3, 1.3, 1.6, 1.9, 1.4, 1.6, 1.4, 1.5, 1.4, 4.7, 4.5, 4.9, 4, 4.6, 4.5, 4.7, 3.3, 4.6, 3.9, 3.5, 4.2, 4, 4.7, 3.6, 4.4, 4.5, 4.1, 4.5, 3.9, 4.8, 4, 4.9, 4.7, 4.3, 4.4, 4.8, 5, 4.5, 3.5, 3.8, 3.7, 3.9, 5.1, 4.5, 4.5, 4.7, 4.4, 4.1, 4, 4.4, 4.6, 4, 3.3, 4.2, 4.2, 4.2, 4.3, 3, 4.1, 6, 5.1, 5.9, 5.6, 5.8, 6.6, 4.5, 6.3, 5.8, 6.1, 5.1, 5.3, 5.5, 5, 5.1, 5.3, 5.5, 6.7, 6.9, 5, 5.7, 4.9, 6.7, 4.9, 5.7, 6, 4.8, 4.9, 5.6, 5.8, 6.1, 6.4, 5.6, 5.1, 5.6, 6.1, 5.6, 5.5, 4.8, 5.4, 5.6, 5.1, 5.1, 5.9, 5.7, 5.2, 5, 5.2, 5.4, 5.1), Petal.Width = c(0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.2, 0.1, 0.1, 0.2, 0.4, 0.4, 0.3, 0.3, 0.3, 0.2, 0.4, 0.2, 0.5, 0.2, 0.2, 0.4, 0.2, 0.2, 0.2, 0.2, 0.4, 0.1, 0.2, 0.2, 0.2, 0.2, 0.1, 0.2, 0.2, 0.3, 0.3, 0.2, 0.6, 0.4, 0.3, 0.2, 0.2, 0.2, 0.2, 1.4, 1.5, 1.5, 1.3, 1.5, 1.3, 1.6, 1, 1.3, 1.4, 1, 1.5, 1, 1.4, 1.3, 1.4, 1.5, 1, 1.5, 1.1, 1.8, 1.3, 1.5, 1.2, 1.3, 1.4, 1.4, 1.7, 1.5, 1, 1.1, 1, 1.2, 1.6, 1.5, 1.6, 1.5, 1.3, 1.3, 1.3, 1.2, 1.4, 1.2, 1, 1.3, 1.2, 1.3, 1.3, 1.1, 1.3, 2.5, 1.9, 2.1, 1.8, 2.2, 2.1, 1.7, 1.8, 1.8, 2.5, 2, 1.9, 2.1, 2, 2.4, 2.3, 1.8, 2.2, 2.3, 1.5, 2.3, 2, 2, 1.8, 2.1, 1.8, 1.8, 1.8, 2.1, 1.6, 1.9, 2, 2.2, 1.5, 1.4, 2.3, 2.4, 1.8, 1.8, 2.1, 2.4, 2.3, 1.9, 2.3, 2.5, 2.3, 1.9, 2, 2.3, 1.8), Species = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L))) 6: `[<-`(`*tmp*`, , value = list(`__tiledb_rows` = 1:150, Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6, 5, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1, 5.4, 5.1, 4.6, 5.1, 4.8, 5, 5, 5.2, 5.2, 4.7, 4.8, 5.4, 5.2, 5.5, 4.9, 5, 5.5, 4.9, 4.4, 5.1, 5, 4.5, 4.4, 5, 5.1, 4.8, 5.1, 4.6, 5.3, 5, 7, 6.4, 6.9, 5.5, 6.5, 5.7, 6.3, 4.9, 6.6, 5.2, 5, 5.9, 6, 6.1, 5.6, 6.7, 5.6, 5.8, 6.2, 5.6, 5.9, 6.1, 6.3, 6.1, 6.4, 6.6, 6.8, 6.7, 6, 5.7, 5.5, 5.5, 5.8, 6, 5.4, 6, 6.7, 6.3, 5.6, 5.5, 5.5, 6.1, 5.8, 5, 5.6, 5.7, 5.7, 6.2, 5.1, 5.7, 6.3, 5.8, 7.1, 6.3, 6.5, 7.6, 4.9, 7.3, 6.7, 7.2, 6.5, 6.4, 6.8, 5.7, 5.8, 6.4, 6.5, 7.7, 7.7, 6, 6.9, 5.6, 7.7, 6.3, 6.7, 7.2, 6.2, 6.1, 6.4, 7.2, 7.4, 7.9, 6.4, 6.3, 6.1, 7.7, 6.3, 6.4, 6, 6.9, 6.7, 6.9, 5.8, 6.8, 6.7, 6.7, 6.3, 6.5, 6.2, 5.9), Sepal.Width = c(3.5, 3, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.4, 3, 3, 4, 4.4, 3.9, 3.5, 3.8, 3.8, 3.4, 3.7, 3.6, 3.3, 3.4, 3, 3.4, 3.5, 3.4, 3.2, 3.1, 3.4, 4.1, 4.2, 3.1, 3.2, 3.5, 3.6, 3, 3.4, 3.5, 2.3, 3.2, 3.5, 3.8, 3, 3.8, 3.2, 3.7, 3.3, 3.2, 3.2, 3.1, 2.3, 2.8, 2.8, 3.3, 2.4, 2.9, 2.7, 2, 3, 2.2, 2.9, 2.9, 3.1, 3, 2.7, 2.2, 2.5, 3.2, 2.8, 2.5, 2.8, 2.9, 3, 2.8, 3, 2.9, 2.6, 2.4, 2.4, 2.7, 2.7, 3, 3.4, 3.1, 2.3, 3, 2.5, 2.6, 3, 2.6, 2.3, 2.7, 3, 2.9, 2.9, 2.5, 2.8, 3.3, 2.7, 3, 2.9, 3, 3, 2.5, 2.9, 2.5, 3.6, 3.2, 2.7, 3, 2.5, 2.8, 3.2, 3, 3.8, 2.6, 2.2, 3.2, 2.8, 2.8, 2.7, 3.3, 3.2, 2.8, 3, 2.8, 3, 2.8, 3.8, 2.8, 2.8, 2.6, 3, 3.4, 3.1, 3, 3.1, 3.1, 3.1, 2.7, 3.2, 3.3, 3, 2.5, 3, 3.4, 3), Petal.Length = c(1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.6, 1.4, 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5, 1.7, 1.5, 1, 1.7, 1.9, 1.6, 1.6, 1.5, 1.4, 1.6, 1.6, 1.5, 1.5, 1.4, 1.5, 1.2, 1.3, 1.4, 1.3, 1.5, 1.3, 1.3, 1.3, 1.6, 1.9, 1.4, 1.6, 1.4, 1.5, 1.4, 4.7, 4.5, 4.9, 4, 4.6, 4.5, 4.7, 3.3, 4.6, 3.9, 3.5, 4.2, 4, 4.7, 3.6, 4.4, 4.5, 4.1, 4.5, 3.9, 4.8, 4, 4.9, 4.7, 4.3, 4.4, 4.8, 5, 4.5, 3.5, 3.8, 3.7, 3.9, 5.1, 4.5, 4.5, 4.7, 4.4, 4.1, 4, 4.4, 4.6, 4, 3.3, 4.2, 4.2, 4.2, 4.3, 3, 4.1, 6, 5.1, 5.9, 5.6, 5.8, 6.6, 4.5, 6.3, 5.8, 6.1, 5.1, 5.3, 5.5, 5, 5.1, 5.3, 5.5, 6.7, 6.9, 5, 5.7, 4.9, 6.7, 4.9, 5.7, 6, 4.8, 4.9, 5.6, 5.8, 6.1, 6.4, 5.6, 5.1, 5.6, 6.1, 5.6, 5.5, 4.8, 5.4, 5.6, 5.1, 5.1, 5.9, 5.7, 5.2, 5, 5.2, 5.4, 5.1), Petal.Width = c(0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.2, 0.1, 0.1, 0.2, 0.4, 0.4, 0.3, 0.3, 0.3, 0.2, 0.4, 0.2, 0.5, 0.2, 0.2, 0.4, 0.2, 0.2, 0.2, 0.2, 0.4, 0.1, 0.2, 0.2, 0.2, 0.2, 0.1, 0.2, 0.2, 0.3, 0.3, 0.2, 0.6, 0.4, 0.3, 0.2, 0.2, 0.2, 0.2, 1.4, 1.5, 1.5, 1.3, 1.5, 1.3, 1.6, 1, 1.3, 1.4, 1, 1.5, 1, 1.4, 1.3, 1.4, 1.5, 1, 1.5, 1.1, 1.8, 1.3, 1.5, 1.2, 1.3, 1.4, 1.4, 1.7, 1.5, 1, 1.1, 1, 1.2, 1.6, 1.5, 1.6, 1.5, 1.3, 1.3, 1.3, 1.2, 1.4, 1.2, 1, 1.3, 1.2, 1.3, 1.3, 1.1, 1.3, 2.5, 1.9, 2.1, 1.8, 2.2, 2.1, 1.7, 1.8, 1.8, 2.5, 2, 1.9, 2.1, 2, 2.4, 2.3, 1.8, 2.2, 2.3, 1.5, 2.3, 2, 2, 1.8, 2.1, 1.8, 1.8, 1.8, 2.1, 1.6, 1.9, 2, 2.2, 1.5, 1.4, 2.3, 2.4, 1.8, 1.8, 2.1, 2.4, 2.3, 1.9, 2.3, 2.5, 2.3, 1.9, 2, 2.3, 1.8), Species = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L))) 7: fromDataFrame(iris, uri) An irrecoverable exception occurred. R is aborting now ... * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘pkgconfig-test.R’ Running ‘tinytest.R’/Users/ripley/R/R-devel/bin/BATCH: line 60: 79459 Segmentation fault: 11 ${R_HOME}/bin/R -f ${in} ${opts} ${R_BATCH_OPTIONS} > ${out} 2>&1 ERROR Running the tests in ‘tests/tinytest.R’ failed. Complete output: > if (requireNamespace("tinytest", quietly = TRUE)) { + if (R.Version()$minor >= "2.0" && Sys.getenv("MY_UNIVERSE", "") == "") { + tinytest::test_package("tiledb") + } + } test_aggregates.R............. 0 tests test_aggregates.R............. 0 tests test_aggregates.R............. 0 tests test_aggregates.R............. 0 tests test_aggregates.R............. 0 tests Attaching package: 'palmerpenguins' The following objects are masked from 'package:datasets': penguins, penguins_raw test_aggregates.R............. 0 tests test_aggregates.R............. 0 tests *** caught segfault *** address 0x1, cause 'invalid permissions' Traceback: 1: RcppSpdlog::formatter(s, v) 2: fmt(s, ...) 3: RcppSpdlog::log_debug(fmt(s, ...)) 4: spdl::debug("[tiledb_array] '[<-' alloc buf {} '{}': {}, rows: {} null: {} asint64: {}", k, colnam, alltypes[k], nr, allnullable[k], asint64) 5: `[<-`(`*tmp*`, , value = list(`__tiledb_rows` = 1:344, species = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), island = c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), bill_length_mm = c(39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39.2, 34.1, 42, 37.8, 37.8, 41.1, 38.6, 34.6, 36.6, 38.7, 42.5, 34.4, 46, 37.8, 37.7, 35.9, 38.2, 38.8, 35.3, 40.6, 40.5, 37.9, 40.5, 39.5, 37.2, 39.5, 40.9, 36.4, 39.2, 38.8, 42.2, 37.6, 39.8, 36.5, 40.8, 36, 44.1, 37, 39.6, 41.1, 37.5, 36, 42.3, 39.6, 40.1, 35, 42, 34.5, 41.4, 39, 40.6, 36.5, 37.6, 35.7, 41.3, 37.6, 41.1, 36.4, 41.6, 35.5, 41.1, 35.9, 41.8, 33.5, 39.7, 39.6, 45.8, 35.5, 42.8, 40.9, 37.2, 36.2, 42.1, 34.6, 42.9, 36.7, 35.1, 37.3, 41.3, 36.3, 36.9, 38.3, 38.9, 35.7, 41.1, 34, 39.6, 36.2, 40.8, 38.1, 40.3, 33.1, 43.2, 35, 41, 37.7, 37.8, 37.9, 39.7, 38.6, 38.2, 38.1, 43.2, 38.1, 45.6, 39.7, 42.2, 39.6, 42.7, 38.6, 37.3, 35.7, 41.1, 36.2, 37.7, 40.2, 41.4, 35.2, 40.6, 38.8, 41.5, 39, 44.1, 38.5, 43.1, 36.8, 37.5, 38.1, 41.1, 35.6, 40.2, 37, 39.7, 40.2, 40.6, 32.1, 40.7, 37.3, 39, 39.2, 36.6, 36, 37.8, 36, 41.5, 46.1, 50, 48.7, 50, 47.6, 46.5, 45.4, 46.7, 43.3, 46.8, 40.9, 49, 45.5, 48.4, 45.8, 49.3, 42, 49.2, 46.2, 48.7, 50.2, 45.1, 46.5, 46.3, 42.9, 46.1, 44.5, 47.8, 48.2, 50, 47.3, 42.8, 45.1, 59.6, 49.1, 48.4, 42.6, 44.4, 44, 48.7, 42.7, 49.6, 45.3, 49.6, 50.5, 43.6, 45.5, 50.5, 44.9, 45.2, 46.6, 48.5, 45.1, 50.1, 46.5, 45, 43.8, 45.5, 43.2, 50.4, 45.3, 46.2, 45.7, 54.3, 45.8, 49.8, 46.2, 49.5, 43.5, 50.7, 47.7, 46.4, 48.2, 46.5, 46.4, 48.6, 47.5, 51.1, 45.2, 45.2, 49.1, 52.5, 47.4, 50, 44.9, 50.8, 43.4, 51.3, 47.5, 52.1, 47.5, 52.2, 45.5, 49.5, 44.5, 50.8, 49.4, 46.9, 48.4, 51.1, 48.5, 55.9, 47.2, 49.1, 47.3, 46.8, 41.7, 53.4, 43.3, 48.1, 50.5, 49.8, 43.5, 51.5, 46.2, 55.1, 44.5, 48.8, 47.2, NA, 46.8, 50.4, 45.2, 49.9, 46.5, 50, 51.3, 45.4, 52.7, 45.2, 46.1, 51.3, 46, 51.3, 46.6, 51.7, 47, 52, 45.9, 50.5, 50.3, 58, 46.4, 49.2, 42.4, 48.5, 43.2, 50.6, 46.7, 52, 50.5, 49.5, 46.4, 52.8, 40.9, 54.2, 42.5, 51, 49.7, 47.5, 47.6, 52, 46.9, 53.5, 49, 46.2, 50.9, 45.5, 50.9, 50.8, 50.1, 49, 51.5, 49.8, 48.1, 51.4, 45.7, 50.7, 42.5, 52.2, 45.2, 49.3, 50.2, 45.6, 51.9, 46.8, 45.7, 55.8, 43.5, 49.6, 50.8, 50.2), bill_depth_mm = c(18.7, 17.4, 18, NA, 19.3, 20.6, 17.8, 19.6, 18.1, 20.2, 17.1, 17.3, 17.6, 21.2, 21.1, 17.8, 19, 20.7, 18.4, 21.5, 18.3, 18.7, 19.2, 18.1, 17.2, 18.9, 18.6, 17.9, 18.6, 18.9, 16.7, 18.1, 17.8, 18.9, 17, 21.1, 20, 18.5, 19.3, 19.1, 18, 18.4, 18.5, 19.7, 16.9, 18.8, 19, 18.9, 17.9, 21.2, 17.7, 18.9, 17.9, 19.5, 18.1, 18.6, 17.5, 18.8, 16.6, 19.1, 16.9, 21.1, 17, 18.2, 17.1, 18, 16.2, 19.1, 16.6, 19.4, 19, 18.4, 17.2, 18.9, 17.5, 18.5, 16.8, 19.4, 16.1, 19.1, 17.2, 17.6, 18.8, 19.4, 17.8, 20.3, 19.5, 18.6, 19.2, 18.8, 18, 18.1, 17.1, 18.1, 17.3, 18.9, 18.6, 18.5, 16.1, 18.5, 17.9, 20, 16, 20, 18.6, 18.9, 17.2, 20, 17, 19, 16.5, 20.3, 17.7, 19.5, 20.7, 18.3, 17, 20.5, 17, 18.6, 17.2, 19.8, 17, 18.5, 15.9, 19, 17.6, 18.3, 17.1, 18, 17.9, 19.2, 18.5, 18.5, 17.6, 17.5, 17.5, 20.1, 16.5, 17.9, 17.1, 17.2, 15.5, 17, 16.8, 18.7, 18.6, 18.4, 17.8, 18.1, 17.1, 18.5, 13.2, 16.3, 14.1, 15.2, 14.5, 13.5, 14.6, 15.3, 13.4, 15.4, 13.7, 16.1, 13.7, 14.6, 14.6, 15.7, 13.5, 15.2, 14.5, 15.1, 14.3, 14.5, 14.5, 15.8, 13.1, 15.1, 14.3, 15, 14.3, 15.3, 15.3, 14.2, 14.5, 17, 14.8, 16.3, 13.7, 17.3, 13.6, 15.7, 13.7, 16, 13.7, 15, 15.9, 13.9, 13.9, 15.9, 13.3, 15.8, 14.2, 14.1, 14.4, 15, 14.4, 15.4, 13.9, 15, 14.5, 15.3, 13.8, 14.9, 13.9, 15.7, 14.2, 16.8, 14.4, 16.2, 14.2, 15, 15, 15.6, 15.6, 14.8, 15, 16, 14.2, 16.3, 13.8, 16.4, 14.5, 15.6, 14.6, 15.9, 13.8, 17.3, 14.4, 14.2, 14, 17, 15, 17.1, 14.5, 16.1, 14.7, 15.7, 15.8, 14.6, 14.4, 16.5, 15, 17, 15.5, 15, 13.8, 16.1, 14.7, 15.8, 14, 15.1, 15.2, 15.9, 15.2, 16.3, 14.1, 16, 15.7, 16.2, 13.7, NA, 14.3, 15.7, 14.8, 16.1, 17.9, 19.5, 19.2, 18.7, 19.8, 17.8, 18.2, 18.2, 18.9, 19.9, 17.8, 20.3, 17.3, 18.1, 17.1, 19.6, 20, 17.8, 18.6, 18.2, 17.3, 17.5, 16.6, 19.4, 17.9, 19, 18.4, 19, 17.8, 20, 16.6, 20.8, 16.7, 18.8, 18.6, 16.8, 18.3, 20.7, 16.6, 19.9, 19.5, 17.5, 19.1, 17, 17.9, 18.5, 17.9, 19.6, 18.7, 17.3, 16.4, 19, 17.3, 19.7, 17.3, 18.8, 16.6, 19.9, 18.8, 19.4, 19.5, 16.5, 17, 19.8, 18.1, 18.2, 19, 18.7), flipper_length_mm = c(181L, 186L, 195L, NA, 193L, 190L, 181L, 195L, 193L, 190L, 186L, 180L, 182L, 191L, 198L, 185L, 195L, 197L, 184L, 194L, 174L, 180L, 189L, 185L, 180L, 187L, 183L, 187L, 172L, 180L, 178L, 178L, 188L, 184L, 195L, 196L, 190L, 180L, 181L, 184L, 182L, 195L, 186L, 196L, 185L, 190L, 182L, 179L, 190L, 191L, 186L, 188L, 190L, 200L, 187L, 191L, 186L, 193L, 181L, 194L, 185L, 195L, 185L, 192L, 184L, 192L, 195L, 188L, 190L, 198L, 190L, 190L, 196L, 197L, 190L, 195L, 191L, 184L, 187L, 195L, 189L, 196L, 187L, 193L, 191L, 194L, 190L, 189L, 189L, 190L, 202L, 205L, 185L, 186L, 187L, 208L, 190L, 196L, 178L, 192L, 192L, 203L, 183L, 190L, 193L, 184L, 199L, 190L, 181L, 197L, 198L, 191L, 193L, 197L, 191L, 196L, 188L, 199L, 189L, 189L, 187L, 198L, 176L, 202L, 186L, 199L, 191L, 195L, 191L, 210L, 190L, 197L, 193L, 199L, 187L, 190L, 191L, 200L, 185L, 193L, 193L, 187L, 188L, 190L, 192L, 185L, 190L, 184L, 195L, 193L, 187L, 201L, 211L, 230L, 210L, 218L, 215L, 210L, 211L, 219L, 209L, 215L, 214L, 216L, 214L, 213L, 210L, 217L, 210L, 221L, 209L, 222L, 218L, 215L, 213L, 215L, 215L, 215L, 216L, 215L, 210L, 220L, 222L, 209L, 207L, 230L, 220L, 220L, 213L, 219L, 208L, 208L, 208L, 225L, 210L, 216L, 222L, 217L, 210L, 225L, 213L, 215L, 210L, 220L, 210L, 225L, 217L, 220L, 208L, 220L, 208L, 224L, 208L, 221L, 214L, 231L, 219L, 230L, 214L, 229L, 220L, 223L, 216L, 221L, 221L, 217L, 216L, 230L, 209L, 220L, 215L, 223L, 212L, 221L, 212L, 224L, 212L, 228L, 218L, 218L, 212L, 230L, 218L, 228L, 212L, 224L, 214L, 226L, 216L, 222L, 203L, 225L, 219L, 228L, 215L, 228L, 216L, 215L, 210L, 219L, 208L, 209L, 216L, 229L, 213L, 230L, 217L, 230L, 217L, 222L, 214L, NA, 215L, 222L, 212L, 213L, 192L, 196L, 193L, 188L, 197L, 198L, 178L, 197L, 195L, 198L, 193L, 194L, 185L, 201L, 190L, 201L, 197L, 181L, 190L, 195L, 181L, 191L, 187L, 193L, 195L, 197L, 200L, 200L, 191L, 205L, 187L, 201L, 187L, 203L, 195L, 199L, 195L, 210L, 192L, 205L, 210L, 187L, 196L, 196L, 196L, 201L, 190L, 212L, 187L, 198L, 199L, 201L, 193L, 203L, 187L, 197L, 191L, 203L, 202L, 194L, 206L, 189L, 195L, 207L, 202L, 193L, 210L, 198L), body_mass_g = c(3750L, 3800L, 3250L, NA, 3450L, 3650L, 3625L, 4675L, 3475L, 4250L, 3300L, 3700L, 3200L, 3800L, 4400L, 3700L, 3450L, 4500L, 3325L, 4200L, 3400L, 3600L, 3800L, 3950L, 3800L, 3800L, 3550L, 3200L, 3150L, 3950L, 3250L, 3900L, 3300L, 3900L, 3325L, 4150L, 3950L, 3550L, 3300L, 4650L, 3150L, 3900L, 3100L, 4400L, 3000L, 4600L, 3425L, 2975L, 3450L, 4150L, 3500L, 4300L, 3450L, 4050L, 2900L, 3700L, 3550L, 3800L, 2850L, 3750L, 3150L, 4400L, 3600L, 4050L, 2850L, 3950L, 3350L, 4100L, 3050L, 4450L, 3600L, 3900L, 3550L, 4150L, 3700L, 4250L, 3700L, 3900L, 3550L, 4000L, 3200L, 4700L, 3800L, 4200L, 3350L, 3550L, 3800L, 3500L, 3950L, 3600L, 3550L, 4300L, 3400L, 4450L, 3300L, 4300L, 3700L, 4350L, 2900L, 4100L, 3725L, 4725L, 3075L, 4250L, 2925L, 3550L, 3750L, 3900L, 3175L, 4775L, 3825L, 4600L, 3200L, 4275L, 3900L, 4075L, 2900L, 3775L, 3350L, 3325L, 3150L, 3500L, 3450L, 3875L, 3050L, 4000L, 3275L, 4300L, 3050L, 4000L, 3325L, 3500L, 3500L, 4475L, 3425L, 3900L, 3175L, 3975L, 3400L, 4250L, 3400L, 3475L, 3050L, 3725L, 3000L, 3650L, 4250L, 3475L, 3450L, 3750L, 3700L, 4000L, 4500L, 5700L, 4450L, 5700L, 5400L, 4550L, 4800L, 5200L, 4400L, 5150L, 4650L, 5550L, 4650L, 5850L, 4200L, 5850L, 4150L, 6300L, 4800L, 5350L, 5700L, 5000L, 4400L, 5050L, 5000L, 5100L, 4100L, 5650L, 4600L, 5550L, 5250L, 4700L, 5050L, 6050L, 5150L, 5400L, 4950L, 5250L, 4350L, 5350L, 3950L, 5700L, 4300L, 4750L, 5550L, 4900L, 4200L, 5400L, 5100L, 5300L, 4850L, 5300L, 4400L, 5000L, 4900L, 5050L, 4300L, 5000L, 4450L, 5550L, 4200L, 5300L, 4400L, 5650L, 4700L, 5700L, 4650L, 5800L, 4700L, 5550L, 4750L, 5000L, 5100L, 5200L, 4700L, 5800L, 4600L, 6000L, 4750L, 5950L, 4625L, 5450L, 4725L, 5350L, 4750L, 5600L, 4600L, 5300L, 4875L, 5550L, 4950L, 5400L, 4750L, 5650L, 4850L, 5200L, 4925L, 4875L, 4625L, 5250L, 4850L, 5600L, 4975L, 5500L, 4725L, 5500L, 4700L, 5500L, 4575L, 5500L, 5000L, 5950L, 4650L, 5500L, 4375L, 5850L, 4875L, 6000L, 4925L, NA, 4850L, 5750L, 5200L, 5400L, 3500L, 3900L, 3650L, 3525L, 3725L, 3950L, 3250L, 3750L, 4150L, 3700L, 3800L, 3775L, 3700L, 4050L, 3575L, 4050L, 3300L, 3700L, 3450L, 4400L, 3600L, 3400L, 2900L, 3800L, 3300L, 4150L, 3400L, 3800L, 3700L, 4550L, 3200L, 4300L, 3350L, 4100L, 3600L, 3900L, 3850L, 4800L, 2700L, 4500L, 3950L, 3650L, 3550L, 3500L, 3675L, 4450L, 3400L, 4300L, 3250L, 3675L, 3325L, 3950L, 3600L, 4050L, 3350L, 3450L, 3250L, 4050L, 3800L, 3525L, 3950L, 3650L, 3650L, 4000L, 3400L, 3775L, 4100L, 3775L), sex = c(2L, 1L, 1L, NA, 1L, 2L, 1L, 2L, NA, NA, NA, NA, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, NA, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, NA, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, NA, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, NA, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, NA, 2L, 1L, NA, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L), year = c(2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L))) 6: `[<-`(`*tmp*`, , value = list(`__tiledb_rows` = 1:344, species = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), island = c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), bill_length_mm = c(39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39.2, 34.1, 42, 37.8, 37.8, 41.1, 38.6, 34.6, 36.6, 38.7, 42.5, 34.4, 46, 37.8, 37.7, 35.9, 38.2, 38.8, 35.3, 40.6, 40.5, 37.9, 40.5, 39.5, 37.2, 39.5, 40.9, 36.4, 39.2, 38.8, 42.2, 37.6, 39.8, 36.5, 40.8, 36, 44.1, 37, 39.6, 41.1, 37.5, 36, 42.3, 39.6, 40.1, 35, 42, 34.5, 41.4, 39, 40.6, 36.5, 37.6, 35.7, 41.3, 37.6, 41.1, 36.4, 41.6, 35.5, 41.1, 35.9, 41.8, 33.5, 39.7, 39.6, 45.8, 35.5, 42.8, 40.9, 37.2, 36.2, 42.1, 34.6, 42.9, 36.7, 35.1, 37.3, 41.3, 36.3, 36.9, 38.3, 38.9, 35.7, 41.1, 34, 39.6, 36.2, 40.8, 38.1, 40.3, 33.1, 43.2, 35, 41, 37.7, 37.8, 37.9, 39.7, 38.6, 38.2, 38.1, 43.2, 38.1, 45.6, 39.7, 42.2, 39.6, 42.7, 38.6, 37.3, 35.7, 41.1, 36.2, 37.7, 40.2, 41.4, 35.2, 40.6, 38.8, 41.5, 39, 44.1, 38.5, 43.1, 36.8, 37.5, 38.1, 41.1, 35.6, 40.2, 37, 39.7, 40.2, 40.6, 32.1, 40.7, 37.3, 39, 39.2, 36.6, 36, 37.8, 36, 41.5, 46.1, 50, 48.7, 50, 47.6, 46.5, 45.4, 46.7, 43.3, 46.8, 40.9, 49, 45.5, 48.4, 45.8, 49.3, 42, 49.2, 46.2, 48.7, 50.2, 45.1, 46.5, 46.3, 42.9, 46.1, 44.5, 47.8, 48.2, 50, 47.3, 42.8, 45.1, 59.6, 49.1, 48.4, 42.6, 44.4, 44, 48.7, 42.7, 49.6, 45.3, 49.6, 50.5, 43.6, 45.5, 50.5, 44.9, 45.2, 46.6, 48.5, 45.1, 50.1, 46.5, 45, 43.8, 45.5, 43.2, 50.4, 45.3, 46.2, 45.7, 54.3, 45.8, 49.8, 46.2, 49.5, 43.5, 50.7, 47.7, 46.4, 48.2, 46.5, 46.4, 48.6, 47.5, 51.1, 45.2, 45.2, 49.1, 52.5, 47.4, 50, 44.9, 50.8, 43.4, 51.3, 47.5, 52.1, 47.5, 52.2, 45.5, 49.5, 44.5, 50.8, 49.4, 46.9, 48.4, 51.1, 48.5, 55.9, 47.2, 49.1, 47.3, 46.8, 41.7, 53.4, 43.3, 48.1, 50.5, 49.8, 43.5, 51.5, 46.2, 55.1, 44.5, 48.8, 47.2, NA, 46.8, 50.4, 45.2, 49.9, 46.5, 50, 51.3, 45.4, 52.7, 45.2, 46.1, 51.3, 46, 51.3, 46.6, 51.7, 47, 52, 45.9, 50.5, 50.3, 58, 46.4, 49.2, 42.4, 48.5, 43.2, 50.6, 46.7, 52, 50.5, 49.5, 46.4, 52.8, 40.9, 54.2, 42.5, 51, 49.7, 47.5, 47.6, 52, 46.9, 53.5, 49, 46.2, 50.9, 45.5, 50.9, 50.8, 50.1, 49, 51.5, 49.8, 48.1, 51.4, 45.7, 50.7, 42.5, 52.2, 45.2, 49.3, 50.2, 45.6, 51.9, 46.8, 45.7, 55.8, 43.5, 49.6, 50.8, 50.2), bill_depth_mm = c(18.7, 17.4, 18, NA, 19.3, 20.6, 17.8, 19.6, 18.1, 20.2, 17.1, 17.3, 17.6, 21.2, 21.1, 17.8, 19, 20.7, 18.4, 21.5, 18.3, 18.7, 19.2, 18.1, 17.2, 18.9, 18.6, 17.9, 18.6, 18.9, 16.7, 18.1, 17.8, 18.9, 17, 21.1, 20, 18.5, 19.3, 19.1, 18, 18.4, 18.5, 19.7, 16.9, 18.8, 19, 18.9, 17.9, 21.2, 17.7, 18.9, 17.9, 19.5, 18.1, 18.6, 17.5, 18.8, 16.6, 19.1, 16.9, 21.1, 17, 18.2, 17.1, 18, 16.2, 19.1, 16.6, 19.4, 19, 18.4, 17.2, 18.9, 17.5, 18.5, 16.8, 19.4, 16.1, 19.1, 17.2, 17.6, 18.8, 19.4, 17.8, 20.3, 19.5, 18.6, 19.2, 18.8, 18, 18.1, 17.1, 18.1, 17.3, 18.9, 18.6, 18.5, 16.1, 18.5, 17.9, 20, 16, 20, 18.6, 18.9, 17.2, 20, 17, 19, 16.5, 20.3, 17.7, 19.5, 20.7, 18.3, 17, 20.5, 17, 18.6, 17.2, 19.8, 17, 18.5, 15.9, 19, 17.6, 18.3, 17.1, 18, 17.9, 19.2, 18.5, 18.5, 17.6, 17.5, 17.5, 20.1, 16.5, 17.9, 17.1, 17.2, 15.5, 17, 16.8, 18.7, 18.6, 18.4, 17.8, 18.1, 17.1, 18.5, 13.2, 16.3, 14.1, 15.2, 14.5, 13.5, 14.6, 15.3, 13.4, 15.4, 13.7, 16.1, 13.7, 14.6, 14.6, 15.7, 13.5, 15.2, 14.5, 15.1, 14.3, 14.5, 14.5, 15.8, 13.1, 15.1, 14.3, 15, 14.3, 15.3, 15.3, 14.2, 14.5, 17, 14.8, 16.3, 13.7, 17.3, 13.6, 15.7, 13.7, 16, 13.7, 15, 15.9, 13.9, 13.9, 15.9, 13.3, 15.8, 14.2, 14.1, 14.4, 15, 14.4, 15.4, 13.9, 15, 14.5, 15.3, 13.8, 14.9, 13.9, 15.7, 14.2, 16.8, 14.4, 16.2, 14.2, 15, 15, 15.6, 15.6, 14.8, 15, 16, 14.2, 16.3, 13.8, 16.4, 14.5, 15.6, 14.6, 15.9, 13.8, 17.3, 14.4, 14.2, 14, 17, 15, 17.1, 14.5, 16.1, 14.7, 15.7, 15.8, 14.6, 14.4, 16.5, 15, 17, 15.5, 15, 13.8, 16.1, 14.7, 15.8, 14, 15.1, 15.2, 15.9, 15.2, 16.3, 14.1, 16, 15.7, 16.2, 13.7, NA, 14.3, 15.7, 14.8, 16.1, 17.9, 19.5, 19.2, 18.7, 19.8, 17.8, 18.2, 18.2, 18.9, 19.9, 17.8, 20.3, 17.3, 18.1, 17.1, 19.6, 20, 17.8, 18.6, 18.2, 17.3, 17.5, 16.6, 19.4, 17.9, 19, 18.4, 19, 17.8, 20, 16.6, 20.8, 16.7, 18.8, 18.6, 16.8, 18.3, 20.7, 16.6, 19.9, 19.5, 17.5, 19.1, 17, 17.9, 18.5, 17.9, 19.6, 18.7, 17.3, 16.4, 19, 17.3, 19.7, 17.3, 18.8, 16.6, 19.9, 18.8, 19.4, 19.5, 16.5, 17, 19.8, 18.1, 18.2, 19, 18.7), flipper_length_mm = c(181L, 186L, 195L, NA, 193L, 190L, 181L, 195L, 193L, 190L, 186L, 180L, 182L, 191L, 198L, 185L, 195L, 197L, 184L, 194L, 174L, 180L, 189L, 185L, 180L, 187L, 183L, 187L, 172L, 180L, 178L, 178L, 188L, 184L, 195L, 196L, 190L, 180L, 181L, 184L, 182L, 195L, 186L, 196L, 185L, 190L, 182L, 179L, 190L, 191L, 186L, 188L, 190L, 200L, 187L, 191L, 186L, 193L, 181L, 194L, 185L, 195L, 185L, 192L, 184L, 192L, 195L, 188L, 190L, 198L, 190L, 190L, 196L, 197L, 190L, 195L, 191L, 184L, 187L, 195L, 189L, 196L, 187L, 193L, 191L, 194L, 190L, 189L, 189L, 190L, 202L, 205L, 185L, 186L, 187L, 208L, 190L, 196L, 178L, 192L, 192L, 203L, 183L, 190L, 193L, 184L, 199L, 190L, 181L, 197L, 198L, 191L, 193L, 197L, 191L, 196L, 188L, 199L, 189L, 189L, 187L, 198L, 176L, 202L, 186L, 199L, 191L, 195L, 191L, 210L, 190L, 197L, 193L, 199L, 187L, 190L, 191L, 200L, 185L, 193L, 193L, 187L, 188L, 190L, 192L, 185L, 190L, 184L, 195L, 193L, 187L, 201L, 211L, 230L, 210L, 218L, 215L, 210L, 211L, 219L, 209L, 215L, 214L, 216L, 214L, 213L, 210L, 217L, 210L, 221L, 209L, 222L, 218L, 215L, 213L, 215L, 215L, 215L, 216L, 215L, 210L, 220L, 222L, 209L, 207L, 230L, 220L, 220L, 213L, 219L, 208L, 208L, 208L, 225L, 210L, 216L, 222L, 217L, 210L, 225L, 213L, 215L, 210L, 220L, 210L, 225L, 217L, 220L, 208L, 220L, 208L, 224L, 208L, 221L, 214L, 231L, 219L, 230L, 214L, 229L, 220L, 223L, 216L, 221L, 221L, 217L, 216L, 230L, 209L, 220L, 215L, 223L, 212L, 221L, 212L, 224L, 212L, 228L, 218L, 218L, 212L, 230L, 218L, 228L, 212L, 224L, 214L, 226L, 216L, 222L, 203L, 225L, 219L, 228L, 215L, 228L, 216L, 215L, 210L, 219L, 208L, 209L, 216L, 229L, 213L, 230L, 217L, 230L, 217L, 222L, 214L, NA, 215L, 222L, 212L, 213L, 192L, 196L, 193L, 188L, 197L, 198L, 178L, 197L, 195L, 198L, 193L, 194L, 185L, 201L, 190L, 201L, 197L, 181L, 190L, 195L, 181L, 191L, 187L, 193L, 195L, 197L, 200L, 200L, 191L, 205L, 187L, 201L, 187L, 203L, 195L, 199L, 195L, 210L, 192L, 205L, 210L, 187L, 196L, 196L, 196L, 201L, 190L, 212L, 187L, 198L, 199L, 201L, 193L, 203L, 187L, 197L, 191L, 203L, 202L, 194L, 206L, 189L, 195L, 207L, 202L, 193L, 210L, 198L), body_mass_g = c(3750L, 3800L, 3250L, NA, 3450L, 3650L, 3625L, 4675L, 3475L, 4250L, 3300L, 3700L, 3200L, 3800L, 4400L, 3700L, 3450L, 4500L, 3325L, 4200L, 3400L, 3600L, 3800L, 3950L, 3800L, 3800L, 3550L, 3200L, 3150L, 3950L, 3250L, 3900L, 3300L, 3900L, 3325L, 4150L, 3950L, 3550L, 3300L, 4650L, 3150L, 3900L, 3100L, 4400L, 3000L, 4600L, 3425L, 2975L, 3450L, 4150L, 3500L, 4300L, 3450L, 4050L, 2900L, 3700L, 3550L, 3800L, 2850L, 3750L, 3150L, 4400L, 3600L, 4050L, 2850L, 3950L, 3350L, 4100L, 3050L, 4450L, 3600L, 3900L, 3550L, 4150L, 3700L, 4250L, 3700L, 3900L, 3550L, 4000L, 3200L, 4700L, 3800L, 4200L, 3350L, 3550L, 3800L, 3500L, 3950L, 3600L, 3550L, 4300L, 3400L, 4450L, 3300L, 4300L, 3700L, 4350L, 2900L, 4100L, 3725L, 4725L, 3075L, 4250L, 2925L, 3550L, 3750L, 3900L, 3175L, 4775L, 3825L, 4600L, 3200L, 4275L, 3900L, 4075L, 2900L, 3775L, 3350L, 3325L, 3150L, 3500L, 3450L, 3875L, 3050L, 4000L, 3275L, 4300L, 3050L, 4000L, 3325L, 3500L, 3500L, 4475L, 3425L, 3900L, 3175L, 3975L, 3400L, 4250L, 3400L, 3475L, 3050L, 3725L, 3000L, 3650L, 4250L, 3475L, 3450L, 3750L, 3700L, 4000L, 4500L, 5700L, 4450L, 5700L, 5400L, 4550L, 4800L, 5200L, 4400L, 5150L, 4650L, 5550L, 4650L, 5850L, 4200L, 5850L, 4150L, 6300L, 4800L, 5350L, 5700L, 5000L, 4400L, 5050L, 5000L, 5100L, 4100L, 5650L, 4600L, 5550L, 5250L, 4700L, 5050L, 6050L, 5150L, 5400L, 4950L, 5250L, 4350L, 5350L, 3950L, 5700L, 4300L, 4750L, 5550L, 4900L, 4200L, 5400L, 5100L, 5300L, 4850L, 5300L, 4400L, 5000L, 4900L, 5050L, 4300L, 5000L, 4450L, 5550L, 4200L, 5300L, 4400L, 5650L, 4700L, 5700L, 4650L, 5800L, 4700L, 5550L, 4750L, 5000L, 5100L, 5200L, 4700L, 5800L, 4600L, 6000L, 4750L, 5950L, 4625L, 5450L, 4725L, 5350L, 4750L, 5600L, 4600L, 5300L, 4875L, 5550L, 4950L, 5400L, 4750L, 5650L, 4850L, 5200L, 4925L, 4875L, 4625L, 5250L, 4850L, 5600L, 4975L, 5500L, 4725L, 5500L, 4700L, 5500L, 4575L, 5500L, 5000L, 5950L, 4650L, 5500L, 4375L, 5850L, 4875L, 6000L, 4925L, NA, 4850L, 5750L, 5200L, 5400L, 3500L, 3900L, 3650L, 3525L, 3725L, 3950L, 3250L, 3750L, 4150L, 3700L, 3800L, 3775L, 3700L, 4050L, 3575L, 4050L, 3300L, 3700L, 3450L, 4400L, 3600L, 3400L, 2900L, 3800L, 3300L, 4150L, 3400L, 3800L, 3700L, 4550L, 3200L, 4300L, 3350L, 4100L, 3600L, 3900L, 3850L, 4800L, 2700L, 4500L, 3950L, 3650L, 3550L, 3500L, 3675L, 4450L, 3400L, 4300L, 3250L, 3675L, 3325L, 3950L, 3600L, 4050L, 3350L, 3450L, 3250L, 4050L, 3800L, 3525L, 3950L, 3650L, 3650L, 4000L, 3400L, 3775L, 4100L, 3775L), sex = c(2L, 1L, 1L, NA, 1L, 2L, 1L, 2L, NA, NA, NA, NA, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, NA, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, NA, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, NA, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, NA, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, NA, 2L, 1L, NA, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L), year = c(2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2007L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2008L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L, 2009L))) 7: fromDataFrame(penguins, uri, sparse = TRUE) 8: doTryCatch(return(expr), name, parentenv, handler) 9: tryCatchOne(expr, names, parentenv, handlers[[1L]]) 10: tryCatchList(expr, names[-nh], parentenv, handlers[-nh]) 11: doTryCatch(return(expr), name, parentenv, handler) 12: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]), names[nh], parentenv, handlers[[nh]]) 13: tryCatchList(expr, classes, parentenv, handlers) 14: tryCatch(current, error = function(e) { result <<- FALSE msg <<- e$message type <<- "An error"}, warning = function(w) { result <<- FALSE msg <<- w$message type <<- "A warning"}) 15: fun(...) 16: expect_silent(fromDataFrame(penguins, uri, sparse = TRUE)) 17: eval(expr, envir = e) 18: eval(expr, envir = e) 19: FUN(X[[i]], ...) 20: lapply(basename(testfiles), run_test_file, at_home = at_home, verbose = verbose, color = color, remove_side_effects = remove_side_effects, ...) 21: run_test_dir(testdir, at_home = at_home, cluster = cluster, ...) 22: tinytest::test_package("tiledb") An irrecoverable exception occurred. R is aborting now ... * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking re-building of vignette outputs ... [7s/10s] OK * checking PDF version of manual ... OK * checking HTML version of manual ... OK * checking for detritus in the temp directory ... OK * DONE Status: 2 ERRORs See ‘/Users/ripley/R/packages/tests-devel/tiledb.Rcheck/00check.log’ for details. 88.86 real 66.42 user 13.22 sys