ggplotly throws error when called with a ggplot object containing a violin plot that did not have enough data to produce a distribution curve.
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Descripción
ggplot is called to produce a violin plot. The data set contains very little data so that the distribution plot is not able to be created. ggplot returns (what I believe to be) a valid ggplot object.
when ggplotly() is called with this object, it throws an error. I would have expected ggplotly() to return without an error as ggplot() did.
library(ggplot2)
library(plotly)
dat <- data.frame(Axis = c("A", "A", "B", "B", "C", "C"),
Value = c("0.815724727",
"0.727678445",
"0.579208876",
"0.880850014",
"0.999999999",
"0.999888945"
))
gg <- ggplot(dat, aes(x = Axis, y = Value))
gg <- gg + geom_jitter()
gg <- gg + geom_violin()
# print(gg)
ggplotly(gg)
ggplotly.ggplot() calls gg2list()
Then gg2list() calls layers2traces() at line 216: traces <- layers2traces(data, prestats_data, layout, plot)
layers2traces() is in a loop at line 67. The 2nd list element of data[[i]] is a dataframe with no rows or columns.
What happened is the violin plot did not have enough data for ggplot to create any of the density plots
so the violin plot structure is empty. When I replace the call to ggplotly(gg) with print(gg), violin plots are not produced, only the points from the geom_jitter() call.
ggplotly() is unfortunately, crashing here with the message:
Browse[6]> c
Error in order(data[["y"]], decreasing = TRUE) :
argument 1 is not a vector
>
Browse[6]> str(data)
List of 2
$ :Classes ‘GeomPoint’ and 'data.frame': 6 obs. of 13 variables:
..$ x : num [1:6] 0.733 0.897 2.355 1.677 3.377 ...
..$ y : num [1:6] 0.816 0.728 0.579 0.881 1 ...
..$ PANEL : Factor w/ 1 level "1": 1 1 1 1 1 1
..$ group : int [1:6] 1 1 2 2 3 3
.. ..- attr(*, "n")= int 3
..$ x_plotlyDomain: chr [1:6] "A" "A" "B" "B" ...
..$ y_plotlyDomain: num [1:6] 0.816 0.728 0.579 0.881 1 ...
..$ shape : num [1:6] 19 19 19 19 19 19
..$ colour : chr [1:6] "black" "black" "black" "black" ...
..$ size : num [1:6] 1.5 1.5 1.5 1.5 1.5 1.5
..$ fill : logi [1:6] NA NA NA NA NA NA
..$ alpha : logi [1:6] NA NA NA NA NA NA
..$ stroke : num [1:6] 0.5 0.5 0.5 0.5 0.5 0.5
$ :Classes ‘GeomViolin’ and 'data.frame': 0 obs. of 0 variables
Browse[6]>
> sessionInfo()
R version 3.5.0 (2018-04-23)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Red Hat Enterprise Linux
Matrix products: default
BLAS: /opt/R/R-3.5.0/lib64/R/lib/libRblas.so
LAPACK: /opt/R/R-3.5.0/lib64/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8
[4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] viridis_0.5.1 viridisLite_0.3.0 colourpicker_1.0
[4] tidyr_0.8.1 openxlsx_4.0.17 shinyFiles_0.7.0.9000
[7] DT_0.4 readxl_1.1.0 htmltools_0.3.6
[10] bindrcpp_0.2.2 stringr_1.3.1 markdown_0.8
[13] dplyr_0.7.6 XML_3.98-1.11 visNetwork_2.0.3
[16] shinyTree_0.3.0.9000 usagelogr_0.1.5 httr_1.3.1
[19] plyr_1.8.4 knitr_1.20 plotly_4.8.0.9000
[22] ggplot2_3.0.0.9000 rmarkdown_1.10 shinyjs_1.0
[25] shinyBS_0.61 shiny_1.0.5
loaded via a namespace (and not attached):
[1] tidyselect_0.2.4 reshape2_1.4.3 purrr_0.2.5 V8_1.5
[5] colorspace_1.3-2 miniUI_0.1.1 yaml_2.1.19 rlang_0.2.2
[9] later_0.7.2 pillar_1.2.2 glue_1.3.0 withr_2.1.2
[13] bindr_0.1.1 cellranger_1.1.0 munsell_0.5.0 gtable_0.2.0
[17] htmlwidgets_1.2 evaluate_0.10.1 labeling_0.3 Cairo_1.5-9
[21] httpuv_1.4.2 crosstalk_1.0.0 curl_3.2 Rcpp_0.12.16
[25] xtable_1.8-2 promises_1.0.1 scales_1.0.0 backports_1.1.2
[29] jsonlite_1.5 mime_0.5 gridExtra_2.3 digest_0.6.15
[33] stringi_1.2.4 grid_3.5.0 rprojroot_1.3-2 tools_3.5.0
[37] magrittr_1.5 lazyeval_0.2.1 tibble_1.4.2 pkgconfig_2.0.2
[41] rsconnect_0.8.8 data.table_1.11.4 assertthat_0.2.0 R6_2.2.2
[45] compiler_3.5.0
>
`
Guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
Línea de trabajo
Comienza ejecutando la reproducción mínima en R con ggplotly() y, a continuación, sigue ggplotly.ggplot() hasta gg2list() y layers2traces(), especialmente el bucle que gestiona los datos vacíos de GeomViolin. Confirma que la capa de violín vacía ya no provoca el error de order() y que los puntos de jitter siguen disponibles en el gráfico resultante.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- r
- Área
- data-visualization
- Tipo de issue
- Error
- Dificultad
- 3/5
- Tiempo estimado
- 1-2 días
- Estado de actividad
- Estancado
- Claridad
- Bastante claro
- Aptitud para principiantes
- 45/100