RKeithL's questions

我正在尝试构建我的第一个斜率图，以在线指南为模型。

df1 <- dplyr::data_frame('tests' = c("2023","2024"),
                         'Pre-season Avg.' = c(42.35,51.38),
                         'Post-season Avg.' = c(90.4,86.56))

colnames(df1) <- c("tests", "Pre-season Avg.", "Post-season Avg.")
left_label <- paste(df1$'tests', df1$'Pre-season Avg.')
right_label <- paste(df1$'tests', df1$'Post-season Avg.')
df1$class <- ifelse((df1$'Post-season Avg.' - df1$'Pre-season Avg.') < 0, "red", "dodgerblue")

plot <- ggplot(df1) +
  geom_segment(aes(x=1, xend=2, y="Pre-season Avg.", yend="Post-season Avg.", col=class), size=0.75,
  show.legend=F) +
  geom_vline(xintercept=1, linetype="dashed", size=0.1) +
  geom_vline(xintercept=2, linetype="dashed", size=0.1) +
  scale_color_manual(labels = c("Up","Down"),
                     values=c("red", "dodgerblue")) +
  labs(x="", y="Scores by Average") +
  xlim(0.5,2.5) + ylim(0, (1.1*(max(df1$'Pre-season Avg.', df1$'Post-season Avg.'))))     

plot <- plot + geom_text(label=left_label, y=df1$'Pre-season Avg.', x=rep(1, NROW(
  df1)), hjust=1.1, size=3.5)
plot <- plot + geom_text(label=right_label, y=df1$'Post-season Avg.', x=rep(2, NROW(
  df1)), hjust=-0.1, size=3.5)
plot <- plot + geom_text(label="Pre-season", x=1, y=1.1*(max(df1$'Pre-season Avg.', df1$'Post-season Avg.')),
  hjust=1.2, size=5)
plot <- plot + geom_text(label="Post-season", x=2, y=1.1*(max(df1$'Pre-season Avg.', df1$'Post-season Avg.')),
  hjust=-0.1, size=5)

plot + theme(panel.background = element_blank(), 
          panel.grid = element_blank(),
          axis.ticks = element_blank(),
          axis.text.x = element_blank(),
          panel.border = element_blank(),
          plot.margin = unit(c(1,2,1,2), "cm"))
plot

和df1$'Pre-season Avg.'都是，df1$'Pre-season Avg.'但double我收到了警告：

Error in `ylim()`:
! Discrete values supplied to continuous scale.
ℹ Example values: "Pre-season Avg." and "Pre-season Avg."

但我不明白为什么会收到警告，因为我（至少我认为）在连续尺度上使用连续值。我显然犯了一个错误，但我无法确定它是什么。

dplyr我查看了许多“根据条件执行 X ”的 SO 问题，我相信只有这个问题接近我正在做的事情。我尝试过但无法适应 @divibisan 的答案。

我的数据如下：

df <- tibble(
  Group_ID = c(1,2,3,4,5,6),
  statusA = c("NEW", "NEW", "OLD","NEW", "OLD","OLD"),
  statusB = c("BONUS", NA, "BONUS", NA, NA,"ROLLBACK"),
  someVar = c("Thanks", "for", "your", "help","!","!"))

当statusB是任何非 NA 值时，我想“拆分”（就像拆分）该行，使得和Group_ID存在不同的行。当行被“拆分”时， 的非 NA 值的行应显示 的 NA ， 的非 NA 值的行应显示 的 NA 。所有剩余变量（即和以外的变量）应按每行显示。statusAstatusBstatusAstatusBstatusBstatusAstatusAstatusBGroup_ID

desired_df <- tibble(
  Group_ID = c(1,1,2,3,3,4,5,6,6),
  statusA = c("NEW",NA,"NEW","OLD",NA,"NEW","OLD","OLD",NA),
  statusB = c(NA,"BONUS",NA,NA,"BONUS",NA,NA,NA,"ROLLBACK"),
  someVar = c("Thanks","Thanks", "for", "your","your","help","!","!","!"))

我强烈希望避免使用循环。可以使用 dplyr 来实现吗？

我正在尝试绘制一个涉及两个 geom_textlines 和一个 geom_bar 的图。我认为我的问题与告诉 ggplot 在哪里使用 df 的哪些部分有关。我最接近的方法是过滤longdf以使 geom_textline 图工作，但这会阻止绘制 geom_bar（我认为）通过阻止filter(vars == "New Wins")。如您所见，我正在尝试使用完成任务dplyr。

先谢谢各位的指导和指正！

library(dplyr)
library(tidyverse)
library(geomtextpath)

dummydf <- data.frame(vars=c('Roster','Alumni', 'New Wins'),SP22=c(34,5,4),
FA22=c(31,5,7), SP23=c(31,5,4), FA23=c(37,3,15),SP24=c(29,7,3),FA24=c(NA,NA,11))

longdf <- dummydf %>% pivot_longer(cols=c('SP22','FA22','SP23','FA23','SP24','FA24'),
names_to='semesters', values_to='value')

myplot <-longdf %>%
  filter(vars != "New Wins") %>%
  ggplot(aes(x=semesters, y=value, group=vars, color=vars)) + 
  geom_textline(aes(label = vars, hjust = vars), spacing = 100) +
  scale_hjust_manual(values = c(0.1, 0.6)) +
  scale_y_continuous(n.breaks = 16, limits = c(0, 44)) +
  scale_x_discrete(limit = c('SP22','FA22','SP23','FA23','SP24'), expand = c(0,.2)) +
  scale_color_manual(values = c("darkorchid2", "steelblue"), guide = "none") %>%
#filter(vars == "New Wins") %>%
  ggplot(aes(x=semesters, y=value, color=vars)) + 
geom_bar(aes(x = semesters, fill = 'gold1')) 
myplot

我有这样的数据：

DF <- data.frame(Majors = c('Sam', 'Bob', 'Henry', 'John', 'Ted', 'Carl', 
                          'Robert', 'Matt', 'Jared', 'Jack', 'Greg', 
                          'Arthur', 'Glenn'), 
                 MEASURES = c('A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 
                              'I', 'J', 'K', 'L', 'M'), 
                 LCOs = c(1.1, 2.1, 3.3, 4.1, 1.2, 1.1,
                          2.4, 3.3, 2.3, 1.1, 2.1, 1.4, 7), 
                 Years=c('2017-2018', '2017-2018', '2017-2018', 
                         '2018-2019', '2018-2019', '2018-2019',
                         '2018-2019', '2019-2020', '2020-2021', 
                         '2020-2021', '2020-2021', '2020-2021', 
                         '2021-2022'))

我的目标是绘制（或表格？），以便Majorsx 轴/底部，Measuresy 轴/侧面，LCOs相应地绘制，并Years通过对绘制的值进行着色来表示LCOs。根据我迄今为止的尝试，我认为ggplot2选择可能不是最好的。但kable似乎不想“策划”（因为缺乏更好的术语）它们。

我非常感谢任何帮助！

编辑以包括预期结果的可怜草图