ggplot与aes（group = ...）问题

抽动休克

使用我的简单数据框

> str(dta)
Classes 'tbl_df', 'tbl' and 'data.frame':   54 obs. of  4 variables:
 $ year   : num  2016 2016 2017 2017 2018 ...
 $ severef: num  0.112 0.465 0.11 0.457 0.114 ...
 $ package: Factor w/ 3 levels "Baseline","HSS",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ run_nb : int  1 2 1 2 1 2 1 2 1 2 ...

跑步时

library(ggplot2)
ggplot(dta, aes(x = year, y = severef, color = package, group = run_nb)) +
    geom_line()

我期待的是几个不同的行会因为绘制aes(..., group = run_nb)按重叠线条在GGPLOT2

而是，输出被卡住。我已经尝试了几种变量类型的转换，但是没有用。我究竟做错了什么？

dta <- structure(list(year = c(2016, 2016, 2017, 2017, 2018, 2018, 2019, 
2019, 2020, 2020, 2021, 2021, 2022, 2022, 2023, 2023, 2024, 2024, 
2016, 2016, 2017, 2017, 2018, 2018, 2019, 2019, 2020, 2020, 2021, 
2021, 2022, 2022, 2023, 2023, 2024, 2024, 2016, 2016, 2017, 2017, 
2018, 2018, 2019, 2019, 2020, 2020, 2021, 2021, 2022, 2022, 2023, 
2023, 2024, 2024), severef = c(0.111823385630219, 0.465018440108279, 
0.109918488465996, 0.457096910073382, 0.11417253918809, 0.474787413895822, 
0.124623038552219, 0.518245898767047, 0.138076553592572, 0.574192448254701, 
0.133435431355833, 0.554892304454577, 0.139052739728505, 0.57825192607885, 
0.150916617717648, 0.627587957223443, 0.144179084276974, 0.599569870728368, 
0.112252179138183, 0.466801581327609, 0.109674033567054, 0.456080342428412, 
0.111055456891102, 0.461825002328107, 0.120224868167075, 0.499956072177523, 
0.125299916066184, 0.521060699301965, 0.0855819441772642, 0.355893196744622, 
0.0495125747278424, 0.205898436502569, 0.030746318019459, 0.12785880845856, 
0.0284200221496644, 0.118184888549004, 0.111823385630219, 0.465018440108279, 
0.109918488465996, 0.457096910073382, 0.11417253918809, 0.474787413895822, 
0.113843419896702, 0.473418768700291, 0.097003856181354, 0.403391308818959, 
0.0628228996117884, 0.261249528583923, 0.0389240209844475, 0.161865851395205, 
0.0297564629438263, 0.123742488239764, 0.0276489857179591, 0.114978527404441
), package = structure(c(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, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("Baseline", 
"HSS", "VMW+ HSS"), class = "factor"), run_nb = c(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)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-54L))

理查德·特尔福德

您的问题是，group美学超越了美学的通常行为colour，后者会使每种颜色仅占一行。使用linetype美学代替group少数群体会很好。

对于大量的组，您可以interaction用来创建唯一的run_nb / package组合，并将其用作分组变量。现在，每一行都有一个唯一的分组变量。

library(ggplot2)

dta <- structure(list(year = c(2016, 2016, 2017, 2017, 2018, 2018, 2019, 2019, 2020, 2020, 2021, 2021, 2022, 2022, 2023, 2023, 2024, 2024, 2016, 2016, 2017, 2017, 2018, 2018, 2019, 2019, 2020, 2020, 2021, 2021, 2022, 2022, 2023, 2023, 2024, 2024, 2016, 2016, 2017, 2017, 2018, 2018, 2019, 2019, 2020, 2020, 2021, 2021, 2022, 2022, 2023, 2023, 2024, 2024), severef = c(0.111823385630219, 0.465018440108279, 0.109918488465996, 0.457096910073382, 0.11417253918809, 0.474787413895822, 0.124623038552219, 0.518245898767047, 0.138076553592572, 0.574192448254701, 0.133435431355833, 0.554892304454577, 0.139052739728505, 0.57825192607885, 0.150916617717648, 0.627587957223443, 0.144179084276974, 0.599569870728368, 0.112252179138183, 0.466801581327609, 0.109674033567054, 0.456080342428412, 0.111055456891102, 0.461825002328107, 0.120224868167075, 0.499956072177523, 0.125299916066184, 0.521060699301965, 0.0855819441772642, 0.355893196744622, 
 0.0495125747278424, 0.205898436502569, 0.030746318019459, 0.12785880845856, 0.0284200221496644, 0.118184888549004, 0.111823385630219, 0.465018440108279, 0.109918488465996, 0.457096910073382, 0.11417253918809, 0.474787413895822, 0.113843419896702, 0.473418768700291, 0.097003856181354, 0.403391308818959, 0.0628228996117884, 0.261249528583923, 0.0389240209844475, 0.161865851395205, 0.0297564629438263, 0.123742488239764, 0.0276489857179591, 0.114978527404441 ), package = structure(c(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, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("Baseline", "HSS", "VMW+ HSS"), class = "factor"), run_nb = c(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)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, -54L))

ggplot(dta, aes(x = year, y = severef, color = package, 
                group = interaction(run_nb, package))) +
 geom_line()

^{由reprex软件包（v0.3.0）创建于2020-01-15}

您的问题与ggplot2中的重叠行不同，因为该示例中的分组变量已经是唯一的-每行一个。

本文收集自互联网，转载请注明来源。

如有侵权，请联系 [email protected] 删除。

编辑于 2021-01-22

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