legendrank scrambled by fillcolor with type='scatter'
Nadie ha tomado este issue todavía.
- Lenguaje dominante
- R
- Estrellas
- 2.7k
- Forks
- 641
- Métricas de merge de PR
- Sin PR fusionados en 30 d
Descripción
Expected behavior
When making a stacked area chart, the ordering of the legend values follows the ordering of the legendrank argument.
Actual behavior
When making a stacked area chart, the ordering of the legend values depends on the legendrank argument in combination with the alphabetical ordering of the fillcolor argument. Somehow the fillcolors seem to be scrambling the order.
Here's an example:
# The goal is to make a stacked area chart, where each fill color is a severity
# level. Then, the legend should be ordered by severity
library(plotly)
severities = c('Mild', 'Moderate', 'Severe')
severity_colors = c('#FF0000', '#440000', '#AA0000')
# ^ colors chosen specifically to be out of alphabetical order
severity_color_dict = setNames(severity_colors, severities)
timeline = data.frame(Time = rep(1:15, 3),
coverage = rep(1, 45),
Severity = factor(rep(severities, each = 15)))
timeline$fill = severity_color_dict[timeline$Severity]
# default order
plot_ly(timeline, x = ~Time, y = ~coverage, name = ~Severity, type = 'scatter',
mode = 'none', stackgroup = 'one', groupnorm = '')
# add fillcolor-- now the legend is in alphabetical order of fillcolor
plot_ly(timeline, x = ~Time, y = ~coverage, name = ~Severity, type = 'scatter',
mode = 'none', stackgroup = 'one', groupnorm = '', fillcolor = ~fill)
# this should be ordered by Severity, but it's still in alphabetical order of
# fillcolor
plot_ly(timeline, x = ~Time, y = ~coverage, name = ~Severity, type = 'scatter',
mode = 'none', stackgroup = 'one', groupnorm = '', fillcolor = ~fill,
legendrank = ~as.integer(Severity))
# The intended order can only be acheived by using the alphabetical ordering of
# the fill colors to "unscramble" the legendrank
unscramble_dict = order(severity_colors)
plot_ly(timeline, x = ~Time, y = ~coverage, name = ~Severity, type = 'scatter',
mode = 'none', stackgroup = 'one', groupnorm = '', fillcolor = ~fill,
legendrank = ~unscramble_dict[as.integer(Severity)])
Session info
R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.2 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8
[6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] plotly_4.10.2 ggplot2_3.4.2
loaded via a namespace (and not attached):
[1] magrittr_2.0.3 tidyselect_1.2.0 munsell_0.5.0 viridisLite_0.4.2 colorspace_2.1-0 R6_2.5.1 rlang_1.1.1
[8] fastmap_1.1.1 fansi_1.0.4 httr_1.4.6 dplyr_1.1.2 tools_4.1.2 parallel_4.1.2 grid_4.1.2
[15] data.table_1.14.8 gtable_0.3.3 utf8_1.2.3 cli_3.6.1 withr_2.5.0 ellipsis_0.3.2 crosstalk_1.2.0
[22] htmltools_0.5.5 yaml_2.3.7 lazyeval_0.2.2 digest_0.6.31 tibble_3.2.1 lifecycle_1.0.3 tidyr_1.3.0
[29] purrr_1.0.1 htmlwidgets_1.6.2 vctrs_0.6.2 glue_1.6.2 compiler_4.1.2 pillar_1.9.0 generics_0.1.3
[36] scales_1.2.1 jsonlite_1.8.5 pkgconfig_2.0.3
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 los ejemplos reproducibles de R usando plot_ly con type='scatter', stackgroup, fillcolor y legendrank. Rastrea cómo responde el orden de la leyenda de las áreas apiladas a esos argumentos; se considera terminado cuando el orden de la leyenda sigue de forma consistente a legendrank, independientemente del orden de fillcolor, preservando al mismo tiempo el comportamiento informado.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- r
- Área
- data-visualization
- Tipo de issue
- Error
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Estado de actividad
- Estancado
- Claridad
- Bastante claro
- Aptitud para principiantes
- 35/100