如何更改每个面图的颜色？

问题描述 投票：0回答：1

我正在使用 ggplot 绘制有关政党偏好的调查数据 (ESS)，并为每一方创建一个单独的方面图。我希望每个图都有它所显示的政党的颜色，其中较深的颜色意味着更多的选票。

这是我的数据的样子

head(party_votes_summary)

# A tibble: 5 × 7
# Groups:   NUTS_NAME [5]
  NUTS_NAME   all_votes    total_votes                  geometry percentage_votes                geometry.y
  <chr>       <fct>              <int>        <MULTIPOLYGON [m]>            <dbl>        <MULTIPOLYGON [m]>
1 Centro (IT) Forza Italia          18 (((4358646 2346312, 4371…          0.0111  (((4358646 2346312, 4371…
2 Isole       Fratelli d'…           0 (((4787072 1652570, 4774…         NA                           EMPTY
3 Nord-Est    Altro                 34 (((4510729 2621661, 4527…          0.0209  (((4510729 2621661, 4527…
4 Nord-Ovest  Forza Italia          37 (((4386364 2524813, 4371…          0.0228  (((4386364 2524813, 4371…
5 Sud         Fratelli d'…          16 (((4945372 2007501, 4997…          0.00984 (((4945372 2007501, 4997…
# ℹ 1 more variable: NUTS_ID <chr>

目前，我有这个代码

ggplot(party_votes_summary) +
  geom_sf(aes(fill = total_votes, geometry = geometry), color = "black") +
  facet_wrap(~ all_votes, labeller = labeller(all_votes = c(
    "Partido Democratico (PD)" = "Partido Democratico",
    "Sinistra Ecologia e Libertà (SEL)" = "Sinistra Ecologia e Libertà",
    "Popolo delle Libertà (PdL)" = "Popolo delle Libertà"
    ))) +
  labs(title = "Summary of Votes per Party per Region",
       fill = "Party") +
  theme(axis.text.x = element_blank(),  
        axis.text.y = element_blank(),  
        axis.ticks = element_blank())+
  scale_fill_distiller(palette = "Blues", direction = 1)

这产生了这个情节：

My current plot

正如我所提到的，我希望每个面都有不同的颜色，颜色越深代表投票越多，颜色越浅代表投票越少。

这是我的情节的代码

ggplot(party_votes_summary) +
  geom_sf(aes(fill = total_votes, geometry = geometry), color = "black") +
  facet_wrap(~ all_votes, labeller = labeller(all_votes = c(
    "Partido Democratico (PD)" = "Partido Democratico",
    "Sinistra Ecologia e Libertà (SEL)" = "Sinistra Ecologia e Libertà",
    "Popolo delle Libertà (PdL)" = "Popolo delle Libertà"
    ))) +
  labs(title = "Summary of Votes per Party per Region",
       fill = "Party") +
  theme(axis.text.x = element_blank(),  
        axis.text.y = element_blank(),  
        axis.ticks = element_blank())+
  scale_fill_manual(values = party_palette)

我得到的错误是：

scale_fill_manual()
中的错误： ！提供给离散尺度的连续值。 ℹ 示例值：261、261、261、261 和 261

我尝试过这两种颜色向量：

party_colours <- c("Movimento 5 Stelle" = "#EED924",
"Lega" = "#008000",
"Partido Democratico (PD)" = "#DC143C",
"Forza Italia" = "#0087DC",
"Fratelli d'Italia" = "darkblue",
"SVP-PATT"="#8a8a8a",
"+ Europa" = "darkgreen",
"Altro"="whitesmoke",
"Sinistra Ecologia e Libertà (SEL)"="palegreen2",
"Liberi e Uguali" = "darkred",
"Popolo delle Libertà (PdL)" = "#0099DC",
"La Destra" = "royalblue")

party_palette <- c(
"Movimento 5 Stelle" = scale_fill_brewer(palette = "OrRd"),
"Lega" = scale_fill_brewer(palette = "Greens"),
"Partido Democratico (PD)" = scale_fill_brewer(palette = "Reds"),
"Forza Italia" = scale_fill_brewer(palette = "Blues"),
"Fratelli d'Italia" = scale_fill_brewer(palette = "Blues"),
"SVP-PATT" = scale_fill_brewer(palette = "Greys"),
"+ Europa" = scale_fill_brewer(palette = "Greens"),
"Altro" = scale_fill_brewer(palette = "Greys"),
"Sinistra Ecologia e Libertà (SEL)" = scale_fill_brewer(palette = "Greens"),
"Liberi e Uguali" = scale_fill_brewer(palette = "Reds"),
"Popolo delle Libertà (PdL)" = scale_fill_brewer(palette = "Blues"),
"La Destra" = scale_fill_brewer(palette = "Blues"))

非常感谢任何帮助！如果您需要其他任何信息来更好地理解我的数据/代码，请告诉我:) 会议信息：

R version 4.3.2 (2023-10-31) Platform: aarch64-apple-darwin20 (64-bit) Running under: macOS Ventura 13.3 Matrix products: default BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0 locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 time zone: Europe/London tzcode source: internal attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] ISCO08ConveRsions_0.2.0 nuts_1.0.0 leaflet_2.2.1 [4] cowplot_1.1.3 stargazer_5.2.3 knitr_1.45 [7] huxtable_5.5.6 data.table_1.15.2 countrycode_1.5.0 [10] profvis_0.3.8 RColorBrewer_1.1-3 ggspatial_1.1.9 [13] ggrepel_0.9.5 viridis_0.6.5 viridisLite_0.4.2 [16] reshape2_1.4.4 see_0.8.2 MASS_7.3-60.0.1 [19] nnet_7.3-19 tictoc_1.2 vdemdata_13.0 [22] readxl_1.4.3 haven_2.5.4 raster_3.6-26 [25] sp_2.1-3 modelsummary_1.4.5 tidytext_0.4.1 [28] themis_1.0.2 textrecipes_1.0.6 rpart.plot_3.1.2 [31] rattle_5.5.1 bitops_1.0-7 ranger_0.16.0 [34] parttree_0.0.1.9004 plotly_4.10.4 pscl_1.5.9 [37] texreg_1.39.3 rpart_4.1.23 sjPlot_2.8.15 [40] randomForest_4.7-1.1 gghighlight_0.4.1 ggeffects_1.5.0 [43] ggiraphExtra_0.3.0 sf_1.0-15 yardstick_1.3.0 [46] workflowsets_1.0.1 workflows_1.1.4 tune_1.1.2 [49] rsample_1.2.0 recipes_1.0.10 parsnip_1.2.0 [52] modeldata_1.3.0 infer_1.0.6 dials_1.2.1 [55] scales_1.3.0 broom_1.0.5 tidymodels_1.1.1 [58] patchwork_1.2.0 readstata13_0.10.1 brant_0.3-0 [61] janitor_2.2.0 gtsummary_1.7.2 gt_0.10.1 [64] vip_0.4.1 lubridate_1.9.3 forcats_1.0.0 [67] stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2 [70] readr_2.1.5 tidyr_1.3.1 tibble_3.2.1 [73] ggplot2_3.5.0 tidyverse_2.0.0 loaded via a namespace (and not attached): [1] splines_4.3.2 cellranger_1.1.0 datawizard_0.9.1 hardhat_1.3.1 [5] lifecycle_1.0.4 globals_0.16.2 lattice_0.22-5 insight_0.19.8 [9] crosstalk_1.2.1 SnowballC_0.7.1 backports_1.4.1 magrittr_2.0.3 [13] sass_0.4.8 rmarkdown_2.26 jquerylib_0.1.4 yaml_2.3.8 [17] DBI_1.2.2 minqa_1.2.6 ipred_0.9-14 lava_1.8.0 [21] tokenizers_0.3.0 listenv_0.9.1 terra_1.7-71 units_0.8-5 [25] performance_0.10.9 parallelly_1.37.1 svglite_2.1.3 codetools_0.2-19 [29] xml2_1.3.6 tidyselect_1.2.0 farver_2.1.1 effectsize_0.8.6 [33] lme4_1.1-35.1 broom.helpers_1.14.0 jsonlite_1.8.8 e1071_1.7-14 [37] survival_3.5-8 iterators_1.0.14 emmeans_1.10.0 systemfonts_1.0.5 [41] foreach_1.5.2 tools_4.3.2 Rcpp_1.0.12 glue_1.7.0 [45] gridExtra_2.3 prodlim_2023.08.28 xfun_0.42 mgcv_1.9-1 [49] withr_3.0.0 ROSE_0.0-4 fastmap_1.1.1 boot_1.3-30 [53] fansi_1.0.6 digest_0.6.34 timechange_0.3.0 R6_2.5.1 [57] estimability_1.5 colorspace_2.1-0 utf8_1.2.4 generics_0.1.3 [61] class_7.3-22 httr_1.4.7 htmlwidgets_1.6.4 parameters_0.21.5 [65] pkgconfig_2.0.3 gtable_0.3.4 timeDate_4032.109 lmtest_0.9-40 [69] GPfit_1.0-8 furrr_0.3.1 janeaustenr_1.0.0 htmltools_0.5.7 [73] mycor_0.1.1 kableExtra_1.4.0 gower_1.0.1 snakecase_0.11.1 [77] rstudioapi_0.15.0 tzdb_0.4.0 uuid_1.2-0 checkmate_2.3.1 [81] nlme_3.1-164 nloptr_2.0.3 cachem_1.0.8 zoo_1.8-12 [85] proxy_0.4-27 sjlabelled_1.2.0 KernSmooth_2.23-22 parallel_4.3.2 [89] pillar_1.9.0 grid_4.3.2 vctrs_0.6.5 xtable_1.8-4 [93] lhs_1.1.6 evaluate_0.23 mvtnorm_1.2-4 cli_3.6.2 [97] compiler_4.3.2 crayon_1.5.2 rlang_1.1.3 ppcor_1.1 [101] future.apply_1.11.1 labeling_0.4.3 modelr_0.1.11 classInt_0.4-10 [105] plyr_1.8.9 sjmisc_2.8.9 ggiraph_0.8.9 stringi_1.8.3 [109] assertthat_0.2.1 tables_0.9.17 munsell_0.5.0 lazyeval_0.2.2 [113] bayestestR_0.13.2 pacman_0.5.1 Matrix_1.6-5 sjstats_0.18.2 [117] hms_1.1.3 future_1.33.1 highr_0.10 bslib_0.6.1 [121] DiceDesign_1.10 




    
    r
    
    ggplot2
    
    colors
    
    facet
    
    colorbrewer
    
    
1个回答

    

      
      
      

        

          

            

              
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# Define custom color gradients for each party
party_palette <- list(
  "Movimento 5 Stelle" = colorRampPalette(c("#FF4500", "#FFE4B5"))(10),  # Orange gradient
  "Lega" = colorRampPalette(c("#006400", "#98FB98"))(10),                # Green gradient
  "Partido Democratico (PD)" = colorRampPalette(c("#8B0000", "#FFC0CB"))(10),  # Red gradient
  "Forza Italia" = colorRampPalette(c("#87CEFA", "#00008B"))(10),         # Blue gradient
  "Fratelli d'Italia" = colorRampPalette(c("#87CEFA", "#00008B"))(10),    # Blue gradient
  "SVP-PATT" = colorRampPalette(c("#DCDCDC", "#A9A9A9"))(10),             # Grey gradient
  "Altro" = colorRampPalette(c("#DCDCDC", "#A9A9A9"))(10),                 # Grey gradient
  "Sinistra Ecologia e Libertà (SEL)" = colorRampPalette(c("#006400", "#98FB98"))(10),  # Green gradient
  "Liberi e Uguali" = colorRampPalette(c("#8B0000", "#FFC0CB"))(10),      # Red gradient
  "Popolo delle Libertà (PdL)" = colorRampPalette(c("#87CEFA", "#00008B"))(10),         # Blue gradient
  "La destra" = colorRampPalette(c("#87CEFA", "#00008B"))(10)              # Blue gradient
)


# Function to create gradient plots for each party
create_party_plot <- function(party_name, party_palette) {
  ggplot(party_votes_summary[party_votes_summary$all_votes == party_name, ]) +
    geom_sf(aes(fill = total_votes, geometry = geometry), color = "darkgrey") +
    scale_fill_gradientn(colors = party_palette[[party_name]], name = "Votes") +
    labs(title = paste(party_name),
         fill = "Votes") +
    theme(axis.text.x = element_blank(),  
          axis.text.y = element_blank(),  
          axis.ticks = element_blank(),
          plot.title = element_text(hjust = 0.5),
          legend.position = "none") +
    coord_sf(crs = st_crs(3035))  
}

# Create separate plots for each party
party_plots <- lapply(names(party_palette), function(party_name) {
  create_party_plot(party_name, party_palette)
})

grid.arrange(
  grobs = lapply(party_plots, function(plot) {
    plot + coord_sf(lims_method = "geometry_bbox")
  }),
  ncol = 4,  # Adjust the number of columns as needed
  top = "Party Votes by Region"
)



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