R语言 为什么我的ggplot生成幻影数据？

y4ekin9u  于 2023-10-13  发布在  其他
关注(0)|答案(1)|浏览(111)

我的情节似乎是插入数据不在我的df。
我的情节代码：

X <- ggplot(methods_per_CONSM_majors |> mutate(Majors = factor(Majors) |> fct_inorder(),
                    Measures = factor(Measures) |> fct_rev()), 
       aes(Majors, Measures, label = LCOs, color = Years)) + geom_text(size = 2.5) + geom_text_repel(box.padding = 1, max.overlaps = 5) +
  scale_y_discrete(guide = guide_axis(n.dodge = 8)) +
  labs(title = "TEMP:",
         subtitle = "TEMP") +
  xlab(label = "") +
  ylab(label = "") +
  scale_y_discrete(labels = function(x) str_wrap(x, width = 10)) +
  theme_minimal() +
  theme(panel.grid = element_line(
      size = (0.1), colour =
        "lightgrey")) +
  theme(legend.position = "top") + 
  guides(color = guide_legend(nrow = 1)) +
  theme(axis.text.x=element_text(angle=90, hjust=1)) +
  geom_text_repel()

X + labs(color=NULL) +
  scale_color_manual(values=c("gold3", "firebrick2", "blue", 'orchid', 'black'))

问题来了：例如，Engineering在Rubric中有一个数据点，它是2.1。但是当我绘图时，2.1对于Engineering出现了 * 三次 *：
[

]
我意识到这个图实际上并没有将数据插入到我的df中，但是是什么导致了这些额外的、虚幻的数据标签的出现呢？

数据

methods_per_CONSM_majors <- data.frame(
  'Majors'=c('Science (Pre-Nursing)', 'Science (Pre-Nursing)', 'Science (Pre-Nursing)', 
             'Science (Pre-Nursing)', 'Science (Pre-Nursing)', 'Science (Pre-Nursing)', 'Science (Pre-Nursing)', 
             'Science (Pre-Nursing)', 'Science (Pre-Nursing)', 'Science (Pre-Nursing)', 'Engineering', 
             'Engineering', 'Biology', 'Biology', 'Biology', 'Biology', 'Biology', 'Biology', 'Biology', 
             'Biology', 'Biology', 'Biology', 'Cell Biology', 'Cell Biology', 'Cell Biology', 'Cell Biology', 
             'Cell Biology', 'Cell Biology', 'Cell Biology', 'Cell Biology', 'Cell Biology', 'Cell Biology', 
             'Macrobiology', 'Macrobiology', 'Macrobiology', 'Macrobiology', 'Macrobiology', 'Macrobiology', 
             'Macrobiology', 'Macrobiology', 'Macrobiology', 'Macrobiology',  'Computer Information Science',  
             'Computer Information Science',  'Computer Information Science',  'Computer Information Science',  
             'Computer Information Science',  'Computer Information Science',  'Computer Information Science',  
             'Computer Information Science',  'Computer Information Science',  'Computer Information Science', 
             'Computer Science', 'Computer Science', 'Computer Science', 'Computer Science', 'Computer Science', 
             'Computer Science', 'Computer Science', 'Computer Science', 'Computer Science', 'Computer Science', 
             'Environmental Science', 'Environmental Science', 'Environmental Science', 'Environmental Science', 
             'Environmental Science', 'Environmental Science', 'Environmental Science', 'Environmental Science', 
             'Environmental Science', 'Environmental Science', 'Health Sciences', 'Health Sciences', 'Health Sciences', 
             'Health Sciences', 'Kinesiology', 'Kinesiology', 'Kinesiology', 'Kinesiology', 'Kinesiology', 
             'Kinesiology', 'Kinesiology', 'Kinesiology', 'Kinesiology', 'Kinesiology', 'Mathematics', 'Mathematics', 
             'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics', 
             'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics', 
             'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics', 'Mathematics',  
             'Natural Sciences', 'Natural Sciences', 'Natural Sciences', 'Natural Sciences', 'Natural Sciences', 
             'Natural Sciences', 'Natural Sciences', 'Natural Sciences', 'Natural Sciences', 'Natural Sciences', 
             'Natural Sciences', 'Natural Sciences', 'Natural Sciences'), 
  'Measures'=c('Research Project/Essay', 
               'Pre/Post', 'Rubric', 'Pre/Post', 'Rubric', 'Rubric', 'Pre/Post', 'Ill-Defined', 'Rubric', 'Rubric', 
               'Rubric', 'Exam', 'Exit Exam', 'Pre/Post', 'Quiz', 'Pre/Post', 'Pre/Post', 'Rubric', 'Exit Exam', 
               'Pre/Post', 'Rubric', 'Rubric', 'Exit Exam', 'Pre/Post', 'Quiz', 'Pre/Post', 'Pre/Post', 'Rubric', 
               'Exit Exam', 'Pre/Post', 'Rubric', 'Rubric', 'Exit Exam', 'Pre/Post', 'Quiz', 'Pre/Post', 'Pre/Post', 
               'Rubric', 'Exit Exam', 'Pre/Post', 'Rubric', 'Rubric', 'Rubric', 'Rubric', 'Exam', 'Rubric', 'Rubric', 
               'Rubric', 'Exam', 'Rubric', 'Evaluator Observation/ Assessment', 'Evaluator Observation/ Assessment', 
               'Rubric', 'Exams & Projects', 'Exam', 'Rubric', 'Exam', 'Rubric', 'Exam', 'Rubric', 'Evaluator Observation/ Assessment', 
               'Evaluator Observation/ Assessment', 'Observation/ Other', 'Ill-Defined', 'Rubric', 'Rubric', 'Rubric',
               'Rubric', 'Exams (Multiple)', 'Rubric', 'Exams (Multiple)', 'Rubric', 'Rubric', 'Exam', 'Rubric', 'Exam',
               'Pre/Post', 'Pre/Post', 'Rubric', 'Pre/Post', 'Rubric', 'Exam', 'Rubric', 'Rubric', 'Pre/Post', 'Rubric',
               'Exam', 'Ill-Defined', 'Exam', 'Exam', 'Exam', 'Rubric', 'Rubric', 'Rubric', 'Alumni Survey', 
               'Journal/ Reflection', 'Rubric', 'Rubric', 'Rubric', 'Rubric', 'Rubric', 'Exam', 'Exam', 'Exam', 'Exam', 
               'Exam', 'Exam', 'Rubric', 'Rubric', 'Exam', 'Ill-Defined', 'Ill-Defined', 'Rubric', 'Rubric', 'Exam', 
               'Quiz', 'Quiz', 'Rubric', 'Exam', 'Exam', 'Quiz', 'Rubric'), 
  'LCOs'=c('1.1', '2.1', '1.1', '2.1', '1.2', 
           '3.1', '2.1', '3.1', '1.2', '3.1', '2.1', '2.2', '1.1', '2.1', '1.2', '2.1', '1.2', '2.2', '1.1', '2.1', 
           '2.2', '3.2', '1.1', '2.1', '1.2', '2.1', '1.2', '2.2', '1.1', '2.1', '2.2', '3.2', '1.1', '2.1', '1.2', 
           '2.1', '1.2', '2.2', '1.1', '2.1', '2.2', '3.2', '2', '4', '1.1', '3.1', '2.2', '4.2', '2.1', '4.1', '3.1', 
           '4.2', '2', '4', '1.1', '3.1', '1.1', '2.2', '2.1', '4.1', '3.1', '4.2', '1.2', '3.1', '1.1', '2.1', '1.2', 
           '2.1', '1.2', '2.1', '1.2', '2.1', '1.1', '2.1', '1.2', '2.2', '2.2', '5.1', '1.1', '5.1', '3.1', '6.1', '4.1', 
           '7.1', '2.1', '5.1', '3.1', '4.1', '4.2', '3.2', '3.3', '5.1', '5.3', '5.2', '1.1', '1.2', '5.3', '5.2', '5.1', 
           '2.1', '2.2', '3.1', '3.2', '3.3', '3.1', '3.2', '3.3', '4.1', '4.2', '1.1', '1.2', '1.3', '4.1', '4.2', '2.1', 
           '3.6', '3.1', '4.1', '1.1', '2.1', '3', '5'), 
  'Years'=c('2017-2018', '2017-2018', '2018-2019', '2018-2019', 
            '2019-2020', '2019-2020', '2020-2021', '2020-2021', '2021-2022', '2021-2022', '2021-2022', '2021-2022', 
            '2017-2018', '2017-2018', '2018-2019', '2018-2019', '2019-2020', '2019-2020', '2020-2021', '2020-2021', 
            '2021-2022', '2021-2022', '2017-2018', '2017-2018', '2018-2019', '2018-2019', '2019-2020', '2019-2020', 
            '2020-2021', '2020-2021', '2021-2022', '2021-2022', '2017-2018', '2017-2018', '2018-2019', '2018-2019', 
            '2019-2020', '2019-2020', '2020-2021', '2020-2021', '2021-2022', '2021-2022', '2017-2018', '2017-2018', 
            '2018-2019', '2018-2019', '2019-2020', '2019-2020', '2020-2021', '2020-2021', '2021-2022', '2021-2022', 
            '2017-2018', '2017-2018', '2018-2019', '2018-2019', '2019-2020', '2019-2020', '2020-2021', '2020-2021', 
            '2021-2022', '2021-2022', '2017-2018', '2017-2018', '2018-2019', '2018-2019', '2019-2020', '2019-2020', 
            '2020-2021', '2020-2021', '2021-2022', '2021-2022', '2020-2021', '2020-2021', '2021-2022', '2021-2022', 
            '2017-2018', '2017-2018', '2018-2019', '2018-2019', '2019-2020', '2019-2020', '2020-2021', '2020-2021', 
            '2021-2022', '2021-2022', '2017-2018',  '2017-2018',  '2017-2018', '2018-2019', '2018-2019', '2018-2019',
            '2018-2019', '2018-2019', '2019-2020', '2019-2020', '2019-2020', '2019-2020', '2019-2020', '2020-2021', 
            '2020-2021', '2020-2021', '2020-2021', '2020-2021', '2021-2022', '2021-2022', '2021-2022', '2021-2022', 
            '2021-2022', '2017-2018', '2017-2018',  '2017-2018', '2017-2018',  '2017-2018', '2018-2019', '2018-2019', 
            '2019-2020', '2019-2020', '2020-2021', '2020-2021', '2021-2022', '2021-2022'))

创建于2023-10-07附带reprex v2.0.2

r

1条答案

按热度按时间
busg9geu

busg9geu1#

发布的代码中有几个错误。
主要错误是有重复的层，geom_text_repel和scale_y_discrete。也有重复的labs，x/ylabs和theme的。
数据转换是在绘图之前进行的，而不是在data参数中进行的。
在下面的代码中，我首先定义了一个自定义的theme，这样下面的图就更简单，可读性更强。

suppressPackageStartupMessages({
  library(dplyr)
  library(forcats)
  library(stringr)
  library(ggplot2)
  library(ggrepel)
})

theme_so_q77248246 <- function() {
  theme_minimal() %+replace%    #
    theme(
      panel.grid = element_line(linewidth = 0.1, colour = "lightgrey"),
      legend.position = "top",
      axis.text.x=element_text(angle = 90, hjust = 1),
      axis.text.y = element_text(size = 5, color = "black")
    )
}

methods_per_CONSM_majors |> 
  mutate(Majors = factor(Majors) |> fct_inorder(),
         Measures = factor(Measures) |> fct_rev()) |>
  ggplot(aes(Majors, Measures, label = LCOs, color = Years)) + 
  geom_point(alpha = 0) + 
  geom_text(size = 2.5, show.legend = FALSE) +
  geom_text_repel(box.padding = 1, max.overlaps = 5, show.legend = FALSE) +
  scale_y_discrete(labels = function(x) str_wrap(x, width = 10)) +
  labs(title = "TEMP:", subtitle = "TEMP", x = "", y = "") +
  guides(color = guide_legend(
    nrow = 1, 
    override.aes = list(alpha = 1, size = 5)
  )) +
  theme_so_q77248246() -> X

X + labs(color = NULL) +
  scale_color_manual(values=c("gold3", "firebrick2", "blue", 'orchid', 'black'))
#> Warning: ggrepel: 117 unlabeled data points (too many overlaps). Consider
#> increasing max.overlaps

创建于2023-10-07附带reprex v2.0.2

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