ggplot2 functions not inheriting? - r

After updating to ggplot2 2.0 some of my visualisation code broke and in trying to figure out why, this behaviour concerned me. Running an internal ggplot2 function such as geom_point after the base call of ggplot(), it appears as if geom_point doesn't inherit the data structures from the original ggplot() call.
Example:
test <- data.frame(a = 1:100, b = 801:900)
ggplot(test, aes(x=a, y=b)) + geom_point()
Error: geom_point requires the following missing aesthetics: x, y
Is this explicit defining of aesthetics in each internal ggplot2 call now the default behaviour?
session info:
R version 3.2.3 (2015-12-10)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.11.2 (El Capitan)
locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
attached base packages:
[1] grid stats4 parallel stats graphics grDevices utils datasets
[9] methods base
other attached packages:
[1] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.2.1
[2] biomaRt_2.26.1
[3] GenomicFeatures_1.22.7
[4] AnnotationDbi_1.32.3
[5] biovizBase_1.18.0
[6] ggbio_1.18.1
[7] cowplot_0.6.0
[8] gridExtra_2.0.0
[9] doParallel_1.0.10
[10] IlluminaHumanMethylation450kmanifest_0.4.0
[11] scales_0.3.0
[12] reshape2_1.4.1
[13] ggplot2_2.0.0
[14] limma_3.26.4
[15] lumi_2.22.0
[16] minfi_1.16.0
[17] bumphunter_1.10.0
[18] locfit_1.5-9.1
[19] iterators_1.0.8
[20] foreach_1.4.3
[21] Biostrings_2.38.3
[22] XVector_0.10.0
[23] SummarizedExperiment_1.0.2
[24] GenomicRanges_1.22.3
[25] GenomeInfoDb_1.6.1
[26] IRanges_2.4.6
[27] S4Vectors_0.8.7
[28] lattice_0.20-33
[29] Biobase_2.30.0
[30] BiocGenerics_0.16.1
loaded via a namespace (and not attached):
[1] nlme_3.1-122 bitops_1.0-6 matrixStats_0.50.1
[4] RColorBrewer_1.1-2 tools_3.2.3 doRNG_1.6
[7] nor1mix_1.2-1 affyio_1.40.0 rpart_4.1-10
[10] KernSmooth_2.23-15 Hmisc_3.17-1 DBI_0.3.1
[13] mgcv_1.8-10 colorspace_1.2-6 nnet_7.3-11
[16] methylumi_2.16.0 GGally_1.0.0 base64_1.1
[19] preprocessCore_1.32.0 graph_1.48.0 pkgmaker_0.22
[22] labeling_0.3 rtracklayer_1.30.1 genefilter_1.52.0
[25] quadprog_1.5-5 affy_1.48.0 RBGL_1.46.0
[28] stringr_1.0.0 digest_0.6.8 Rsamtools_1.22.0
[31] foreign_0.8-66 illuminaio_0.12.0 siggenes_1.44.0
[34] GEOquery_2.36.0 dichromat_2.0-0 BSgenome_1.38.0
[37] RSQLite_1.0.0 BiocInstaller_1.20.1 mclust_5.1
[40] BiocParallel_1.4.3 acepack_1.3-3.3 VariantAnnotation_1.16.4
[43] RCurl_1.95-4.7 magrittr_1.5 Formula_1.2-1
[46] futile.logger_1.4.1 Matrix_1.2-3 Rcpp_0.12.2
[49] munsell_0.4.2 stringi_1.0-1 nleqslv_2.9.1
[52] MASS_7.3-45 zlibbioc_1.16.0 plyr_1.8.3
[55] splines_3.2.3 multtest_2.26.0 annotate_1.48.0
[58] beanplot_1.2 igraph_1.0.1 rngtools_1.2.4
[61] corpcor_1.6.8 codetools_0.2-14 mixOmics_5.2.0
[64] futile.options_1.0.0 XML_3.98-1.3 latticeExtra_0.6-26
[67] lambda.r_1.1.7 gtable_0.1.2 reshape_0.8.5
[70] xtable_1.8-0 survival_2.38-3 OrganismDbi_1.12.1
[73] GenomicAlignments_1.6.3 registry_0.3 ellipse_0.3-8
[76] cluster_2.0.3 rgl_0.95.1441

Related

Error when using ggplot2: can't find `stat` called "identity"

I didn't find any results on my internet calls. How to fix this error is caused?
library(ggplot2)
ggplot(data = mtcars, aes(x=disp , y=wt)) +
geom_point(stat = "identity")
result;
Error: Can't find stat called "identity"
My sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.1 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1
locale:
[1] LC_CTYPE=tr_TR.UTF-8 LC_NUMERIC=C
[3] LC_TIME=tr_TR.UTF-8 LC_COLLATE=tr_TR.UTF-8
[5] LC_MONETARY=tr_TR.UTF-8 LC_MESSAGES=tr_TR.UTF-8
[7] LC_PAPER=tr_TR.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=tr_TR.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ggplot2_3.1.0 shiny_1.2.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.0 pillar_1.3.0 compiler_3.5.1
[4] cellranger_1.1.0 RColorBrewer_1.1-2 later_0.7.5
[7] plyr_1.8.4 bindr_0.1.1 forcats_0.3.0
[10] tools_3.5.1 digest_0.6.18 viridisLite_0.3.0
[13] jsonlite_1.5 tibble_1.4.2 gtable_0.2.0
[16] pkgconfig_2.0.2 rlang_0.3.0.1 ggplotgui_1.0.0
[19] rstudioapi_0.8 yaml_2.2.0 haven_1.1.2
[22] bindrcpp_0.2.2 withr_2.1.2 stringr_1.3.1
[25] httr_1.3.1 dplyr_0.7.8 htmlwidgets_1.3
[28] hms_0.4.2 grid_3.5.1 tidyselect_0.2.5
[31] data.table_1.11.8 glue_1.3.0 R6_2.3.0
[34] plotly_4.8.0 readxl_1.1.0 readr_1.1.1
[37] tidyr_0.8.2 purrr_0.2.5 magrittr_1.5
[40] scales_1.0.0 promises_1.0.1 htmltools_0.3.6
[43] assertthat_0.2.0 xtable_1.8-3 mime_0.6
[46] colorspace_1.3-2 httpuv_1.4.5 stringi_1.2.4
[49] lazyeval_0.2.1 munsell_0.5.0 crayon_1.3.4

How to split incrementally part of dataframe that in memory to R

I have a bigdata dataset (dat1)
require (data.table)
dat1 <- fread('https://archive.ics.uci.edu/ml/machine-learning-databases/poker/poker-hand-testing.data')
I split it into 1000 subdatasets:
chunk <- 1000 ## No. of rows per chunk
n <- nrow(dat1)
r <- rep(1:floor(n/chunk),each=chunk)[1:n]
d <- split(dat1,r)
I would like to create a new list of accumulative subdatasets. So that each member in the list will include the lines of the former member and a delta of d[i+1]:
e<-list()
e[[1]]<-d[[1]]
for (i in 1:997 ) {e[[i+1]]<-bind_rows(e[[i]],d[[i+1]])}
After running a while I get the following:
Error: cannot allocate vector of size 1.8 Mb in R
Error: cannot allocate vector of size 2.0 Mb
> sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1
locale:
[1] LC_COLLATE=Hebrew_Israel.1255 LC_CTYPE=Hebrew_Israel.1255 LC_MONETARY=Hebrew_Israel.1255
[4] LC_NUMERIC=C LC_TIME=Hebrew_Israel.1255
attached base packages:
[1] grid stats graphics grDevices utils datasets methods base
other attached packages:
[1] dplyr_0.5.0 rpart_4.1-10 partykit_1.1-1 plyr_1.8.4 caret_6.0-76
[6] ggplot2_2.2.1 lattice_0.20-34 data.table_1.10.4 arulesSequences_0.2-17 arules_1.5-0
[11] Matrix_1.2-7.1
loaded via a namespace (and not attached):
[1] Rcpp_0.12.11 RWeka_0.4-34 visNetwork_1.0.3 assertthat_0.2.0 digest_0.6.12 foreach_1.4.3
[7] R6_2.2.1 MatrixModels_0.4-1 stats4_3.3.2 RWekajars_3.9.1-3 rlang_0.1.1 lazyeval_0.2.0
[13] curl_2.6 SparseM_1.77 rstudioapi_0.6 minqa_1.2.4 car_2.1-4 nloptr_1.0.4
[19] DiagrammeR_0.9.0 splines_3.3.2 lme4_1.1-13 stringr_1.2.0 htmlwidgets_0.8 igraph_1.0.1
[25] munsell_0.4.3 influenceR_0.1.0 rgexf_0.15.3 mgcv_1.8-15 htmltools_0.3.6 nnet_7.3-12
[31] tibble_1.3.3 gridExtra_2.2.1 codetools_0.2-15 XML_3.98-1.7 viridisLite_0.2.0 MASS_7.3-45
[37] ModelMetrics_1.1.0 nlme_3.1-128 jsonlite_1.5 gtable_0.2.0 DBI_0.6-1 magrittr_1.5
[43] RMOAjars_1.0 scales_0.4.1 stringi_1.1.5 reshape2_1.4.2 viridis_0.4.0 RMOA_1.1
[49] brew_1.0-6 Formula_1.2-1 data.tree_0.7.0 RColorBrewer_1.1-2 iterators_1.0.8 tools_3.3.2
[55] Rook_1.1-1 survival_2.39-5 pbkrtest_0.4-7 parallel_3.3.2 colorspace_1.3-2 rJava_0.9-9
[61] quantreg_5.33

How do I know which packages are interfering with the others?

I am putting some files together using the following code:
data_path <- "daymet"
files <- dir(data_path, pattern = "*.csv")
daymet <- data_frame(filename = files) %>%
mutate(file_contents = map(filename, ~ read_csv(file.path(data_path, .),
skip=7)))%>%
unnest()%>%
mutate(site = str_sub(filename, 1, 3))
At first I had some problems with the error "'GAJPCSR1_2003_2011.csvMapEnv' is not an exported object from 'namespace:maps'". I reinstalled purrr. Error gone, everything worked!
I went to put this back with the rest of my analysis, cleared my environment, and when R got to this chunk, the same error message came back.
I've got all these other packages going, so it seems like one of them is not working well with purrr. Or maybe not. Even if I don't load all the packages, I still get the same error message.
Session Info:
R version 3.3.2 (2016-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] reprex_0.1.1 mapdata_2.2-6 maps_3.2.0 ggmap_2.6.1 soilDB_1.8.5 aqp_1.10
[7] stringr_1.1.0 modelr_0.1.0 lubridate_1.6.0 dplyr_0.5.0 purrr_0.2.3 readr_1.0.0
[13] tidyr_0.6.1 tibble_1.2 ggplot2_2.2.1 tidyverse_1.1.1
loaded via a namespace (and not attached):
[1] httr_1.2.1 jsonlite_1.5 splines_3.3.2 Formula_1.2-1
[5] assertthat_0.2.0 sp_1.2-5 latticeExtra_0.6-28 backports_1.0.5
[9] lattice_0.20-34 digest_0.6.12 RColorBrewer_1.1-2 checkmate_1.8.2
[13] rvest_0.3.2 colorspace_1.3-2 htmltools_0.3.5 Matrix_1.2-7.1
[17] plyr_1.8.4 psych_1.6.12 devtools_1.12.0 clipr_0.3.3
[21] XML_3.98-1.8 broom_0.4.2 raster_2.5-8 haven_1.0.0
[25] scales_0.4.1 whisker_0.3-2 jpeg_0.1-8 htmlTable_1.9
[29] withr_1.0.2 nnet_7.3-12 lazyeval_0.2.0 mnormt_1.5-5
[33] proto_1.0.0 survival_2.41-3 magrittr_1.5 readxl_0.1.1
[37] evaluate_0.10 memoise_1.0.0 nlme_3.1-131 MASS_7.3-45
[41] forcats_0.2.0 xml2_1.1.1 foreign_0.8-67 tools_3.3.2
[45] data.table_1.10.4 hms_0.3 geosphere_1.5-5 RgoogleMaps_1.4.1
[49] munsell_0.4.3 cluster_2.0.5 plotrix_3.6-4 callr_1.0.0
[53] rlang_0.1.2 grid_3.3.2 rjson_0.2.15 htmlwidgets_0.8
[57] rmarkdown_1.5 labeling_0.3 base64enc_0.1-3 gtable_0.2.0
[61] DBI_0.5-1 reshape_0.8.6 reshape2_1.4.2 R6_2.2.0
[65] gridExtra_2.2.1 knitr_1.17 rprojroot_1.2 Hmisc_4.0-3
[69] stringi_1.1.2 parallel_3.3.2 Rcpp_0.12.10 mapproj_1.2-4
[73] rpart_4.1-10 acepack_1.4.1 png_0.1-7
You can see everything that is masking or being masked with
conflicts(detail = TRUE)
For example, in my current R session you can see below that I've been answering questions on SO because of all the generic data names in the Global Environment, df, dt, and t masking the base functions of the same name. And you can see data table's first and last masking the dplyr versions, because I loaded data.table after dplyr:
> conflicts(detail = T)
$.GlobalEnv
[1] "n" "df" "dt" "gamma" "t"
$`package:stringr`
[1] "%>%"
$`package:data.table`
[1] "between" "first" "last"
$`package:dplyr`
[1] "%>%" "between" "first" "last" "n" "filter" "lag"
[8] "intersect" "setdiff" "setequal" "union"
$`package:ggplot2`
[1] "Position"
$`package:stats`
[1] "df" "dt" "filter" "lag"
$`package:methods`
[1] "body<-" "kronecker"
$`package:base`
[1] "body<-" "gamma" "intersect" "kronecker" "Position" "setdiff" "setequal"
[8] "t" "union"

Error in lm(Sales ~ Discount, data = dtsample2) : unused argument (data = dtsample2)

While executing the following for linear regression the following error is thrown. The variables are numeric in the dataset.
dtsample2 <- read.csv("dtsample2.csv")
gt <- lm(Sales ~ Discount, data = dtsample2)
Error in lm(Sales ~ Discount, data = dtsample2) : unused argument
(data = dtsample2)
Please find the session info below.
sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: i386-w64-mingw32/i386 (32-bit)
Running under: Windows 7 (build 7601) Service Pack 1
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] tcltk stats4 grid splines stats graphics grDevices utils datasets methods
[11] base
other attached packages:
[1] RcmdrPlugin.FuzzyClust_1.1 FactoMineR_1.36 RcmdrPlugin.EZR_1.35
[4] Hmisc_4.0-3 Formula_1.2-2 xtable_1.8-2
[7] forecast_8.1 xts_0.10-0 zoo_1.8-0
[10] tseries_0.10-42 TeachingDemos_2.10 RcmdrPlugin.EcoVirtual_1.0
[13] EcoVirtual_1.0 RcmdrPlugin.EBM_1.0-10 epiR_0.9-87
[16] RcmdrPlugin.EACSPIR_0.2-2 reshape_0.8.6 nortest_1.0-4
[19] ez_4.4-0 abind_1.4-5 R2HTML_2.3.2
[22] RcmdrPlugin.doex_0.2.0 RcmdrPlugin.DoE_0.12-3 relimp_1.0-5
[25] DoE.wrapper_0.8-10 rsm_2.8 FrF2_1.7-2
[28] DoE.base_0.30 conf.design_2.0.0 RcmdrPlugin.depthTools_1.3
[31] depthTools_0.4 RcmdrPlugin.coin_1.0-22 multcomp_1.4-6
[34] TH.data_1.0-8 mvtnorm_1.0-6 coin_1.2-0
[37] survival_2.41-3 biclust_1.2.0 colorspace_1.3-2
[40] MASS_7.3-47 RcmdrPlugin.BCA_0.9-8 flexclust_1.3-4
[43] modeltools_0.2-21 lattice_0.20-35 BCA_0.9-3
[46] Rcmdr_2.3-2 RcmdrMisc_1.0-5 sandwich_2.3-4
[49] car_2.1-5 ggthemes_3.4.0 ggplot2_2.2.1
[52] e1071_1.6-8 dplyr_0.7.1 rJava_0.9-8
[55] ModelMetrics_1.1.0 lme4_1.1-13 arules_1.5-2
[58] Matrix_1.2-10 ROCR_1.0-7 gplots_3.0.1
[61] RSQLite_2.0
loaded via a namespace (and not attached):
[1] stringr_1.2.0 gdata_2.18.0 gtools_3.5.0
[4] bindrcpp_0.2 rlang_0.1.1 htmlTable_1.9
[7] iterators_1.0.8 mgcv_1.8-17 blob_1.1.0
[10] bitops_1.0-6 base64enc_0.1-3 quantreg_5.33
[13] reshape2_1.4.2 R6_2.2.2 bit_1.1-12
[16] clue_0.3-53 plyr_1.8.4 tkrplot_0.0-23
[19] stringi_1.1.5 tcltk2_1.2-11 BsMD_2013.0718
[22] rpart.plot_2.1.2 munsell_0.4.3 vcd_1.4-3
[25] MatrixModels_0.4-1 ggthemr_1.1.0 htmlwidgets_0.9
[28] leaps_3.0 quadprog_1.5-5 quantmod_0.4-10
[31] pbkrtest_0.4-7 DBI_0.7 memoise_1.1.0
[34] bindr_0.1 foreign_0.8-69 pkgconfig_2.0.1
[37] BiasedUrn_1.07 tools_3.4.1 acepack_1.4.1
[40] SparseM_1.77 clv_0.3-2.1 cluster_2.0.6
[43] compiler_3.4.1 assertthat_0.2.0 caTools_1.17.1
[46] igraph_1.0.1 gtable_0.2.0 RcmdrPlugin.epack_1.2.5
[49] glue_1.1.1 readxl_1.0.0 digest_0.6.12
[52] RColorBrewer_1.1-2 knitr_1.16 doParallel_1.0.10
[55] htmltools_0.3.6 KernSmooth_2.23-15 DiceDesign_1.7
[58] data.table_1.10.4 lmtest_0.9-35 foreach_1.4.3
[61] sfsmisc_1.1-1 flashClust_1.01-2 RcmdrPlugin.FactoMineR_1.6-0
[64] fracdiff_1.4-2 backports_1.1.0 lazyeval_0.2.0
[67] magrittr_1.5 AlgDesign_1.1-7.3 checkmate_1.8.3
[70] estimability_1.2 minqa_1.2.4 timeDate_3012.100
[73] Rcpp_0.12.12 coda_0.19-1 bit64_0.9-7
[76] scales_0.4.1 TTR_0.23-2 lsmeans_2.26-3
[79] nloptr_1.0.4 combinat_0.0-8 tibble_1.3.3
[82] latticeExtra_0.6-28 RcmdrPlugin.Export_0.3-1 cellranger_1.1.0
[85] nnet_7.3-12 codetools_0.2-15 curl_2.7
[88] gridExtra_2.2.1 nlme_3.1-131 class_7.3-14
[91] parallel_3.4.1 lhs_0.14 rpart_4.1-11
[94] scatterplot3d_0.3-40
It may happen because you defined yearlier custom lm function by yourself and/or some package with specific lm definition had overriden base::lm.
You can call rm(list = ls()) as well restart your R session to
avoid this kind of behaviour.
Or you can call gt <- base::lm(Sales ~ Discount, data = dtsample2) to call lm from base package with desired functionality.
Please see the example how it happens:
lm <- function(x) {
0
}
lm(x ~ y, data = df)
# Error in lm(x ~ y, data = df) : unused argument (data = df)

Shiny Apps Error in R Studio

My Shiny apps had been running fine until last week.
I am trying to run the apps today and getting errors in most of them :
Below is the error and my sessionInfo.
I am using Shinydashboard and other shiny libraries to render an app.
Error in withReactiveDomain(shinysession, { :
No handler registered for for type file1:shiny.file
sessionInfo()
R version 3.3.1 (2016-06-21)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: OS X 10.10.1 (Yosemite)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] parallel stats4 grid stats graphics grDevices utils datasets methods base
other attached packages:
[1] locfit_1.5-9.1 ggbiplot_0.55 scales_0.4.0
[4] chimera_1.14.0 Homo.sapiens_1.3.1 org.Hs.eg.db_3.3.0
[7] GO.db_3.3.0 OrganismDbi_1.14.1 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[10] GenomicFeatures_1.24.5 BSgenome.Hsapiens.UCSC.hg19_1.4.0 BSgenome_1.40.1
[13] rtracklayer_1.32.2 AnnotationDbi_1.34.4 GenomicAlignments_1.8.4
[16] Rsamtools_1.24.0 Biostrings_2.40.2 XVector_0.12.1
[19] BiocInstaller_1.22.3 gTrack_0.1.0 gUtils_0.2.0
[22] data.table_1.9.6 stringr_1.1.0 devtools_1.12.0
[25] reshape_0.8.5 DESeq2_1.12.4 SummarizedExperiment_1.2.3
[28] Biobase_2.32.0 GenomicRanges_1.24.3 GenomeInfoDb_1.8.7
[31] IRanges_2.6.1 S4Vectors_0.10.3 BiocGenerics_0.18.0
[34] xlsx_0.5.7 xlsxjars_0.6.1 rJava_0.9-8
[37] shinydashboard_0.5.3 DT_0.2 shiny_0.14.1
[40] ggplot2_2.1.0 sva_3.20.0 genefilter_1.54.2
[43] mgcv_1.8-15 nlme_3.1-128 matrixStats_0.51.0
[46] pvclust_2.0-0 gplots_3.0.1 reshape2_1.4.1
[49] plyr_1.8.4 ComplexHeatmap_1.11.7
loaded via a namespace (and not attached):
[1] colorspace_1.2-7 rjson_0.2.15 class_7.3-14 modeltools_0.2-21 mclust_5.2
[6] circlize_0.3.9 GlobalOptions_0.0.10 flexmix_2.3-13 mvtnorm_1.0-5 splines_3.3.1
[11] robustbase_0.92-6 geneplotter_1.50.0 Formula_1.2-1 jsonlite_1.1 annotate_1.50.1
[16] cluster_2.0.5 kernlab_0.9-25 graph_1.50.0 httr_1.2.1 Matrix_1.2-7.1
[21] acepack_1.3-3.3 htmltools_0.3.5 tools_3.3.1 gtable_0.2.0 Rcpp_0.12.7
[26] trimcluster_0.1-2 gdata_2.17.0 fpc_2.1-10 mime_0.5 gtools_3.5.0
[31] XML_3.98-1.4 dendextend_1.3.0 DEoptimR_1.0-6 zlibbioc_1.18.0 MASS_7.3-45
[36] RBGL_1.48.1 RColorBrewer_1.1-2 yaml_2.1.13 curl_2.1 memoise_1.0.0
[41] gridExtra_2.2.1 biomaRt_2.28.0 rpart_4.1-10 latticeExtra_0.6-28 stringi_1.1.2
[46] RSQLite_1.0.0 caTools_1.17.1 BiocParallel_1.6.6 shape_1.4.2 chron_2.3-47
[51] prabclus_2.2-6 bitops_1.0-6 lattice_0.20-34 htmlwidgets_0.7 labeling_0.3
[56] magrittr_1.5 R6_2.2.0 Hmisc_3.17-4 DBI_0.5-1 whisker_0.3-2
[61] foreign_0.8-67 withr_1.0.2 survival_2.39-5 RCurl_1.95-4.8 nnet_7.3-12
[66] KernSmooth_2.23-15 GetoptLong_0.1.5 git2r_0.15.0 digest_0.6.10 diptest_0.75-7
[71] xtable_1.8-2 httpuv_1.3.3 munsell_0.4.3
Any idea,what this could be?
Thanks,
Ron
Shiny version 0.14.2 was published last week (along with new versions of R and RStudio). Maybe this broke something in your code. One way to protect against this is to use something like packrat package that locks in a certain version of an R package so that your code is not changed by a new package. You can then test your code against an upgrade and troubleshoot before using that new version.
Restarting R studio worked.There was no need to update any packages.

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