Question

我有这些数据（前20行的样本）：

编码变量值
1 Z1 Week.0 0
2 Z2 Week.0 0
3 Z3 Week.0 0
4 Z4 Week.0 0
5 Z5 Week.0 0
6 Z6 Week.0 0
7 Z7 Week.0 0
8 Z8 Week.0 0
9 Z9 Week.0 0
10 Z101 Week.0 NA
11 Z102 Week.0 NA
12 Z1 Week.1 0
13 Z2 Week.1 0
14 Z3 Week.1 0
15 Z4 Week.1 0
16 Z5 Week.1 0
17 Z6 Week.1 0
18 Z7 Week.1 0
19 Z8 Week.1 0

我用它绘图：

pZ <- ggplot(zmeltdata,aes(x=variable,y=value,color=Codering,group=Codering)) + 
  geom_line()+
  geom_point()+
  theme_few()+
  theme(legend.position="right")+
  scale_color_hue(name = "Treatment group:")+
  scale_y_continuous(labels = percent)+
  ylab("Germination percentage")+
  xlab("Week number")+
  labs(title = "Z. monophyllum germination data")
pZ

图表显示正常：

enter image description here

然而，当我想将它导出到Plot.ly时，我收到以下错误：

> py <- plotly()
> response<-py$ggplotly(pZ)
Error in if (all(xcomp) && all(ycomp)) { : 
  missing value where TRUE/FALSE needed
In addition: Warning message:
In trace.list[[lind[1]]]$y == trace.list[[lind[2]]]$y :
  longer object length is not a multiple of shorter object length

我已经搜索过这些错误，但解释却让我感到困惑。＆＃34;需要TRUE / FALSE的缺失值。＆＃34;如果你在你的过程中使用逻辑术语作为IF / ELSE / TRUE / FALSE就应该发生，我根本不会这样做！即使在检查图表值中的任何NA时，我也会得到：

> is.na(pZ)
       data      layers      scales     mapping       theme coordinates       facet    plot_env      labels 
      FALSE       FALSE       FALSE       FALSE       FALSE       FALSE       FALSE       FALSE       FALSE

并且较长的对象长度不是较短对象长度的倍数＆＃39;当你有不同长度的对象时应该弹出，但我只使用1个具有3行长度完全相同的对象。当我使用时，图形的值确实给了NULL请求那些行，但这应该发生..

> nrow(zmeltdata)
[1] 143
> nrow(test)
NULL

总而言之，我非常困惑，并且不知道如何正确处理这些错误，有人可以详细说明吗？

感谢您的时间。

编辑：我尝试使用1：100的随机样本将不同的图形导出到Plot.ly并且工作得很好，我很确定错误在我的数据中，我可以＆＃39 ;弄清楚如何解决它。

EDIT2：回应@Gregor：

> dput(head(zmeltdata, 20))
structure(list(Codering = structure(c(16L, 19L, 20L, 21L, 22L, 
23L, 24L, 25L, 26L, 17L, 18L, 16L, 19L, 20L, 21L, 22L, 23L, 24L, 
25L, 26L), .Label = c("B1", "C2", "C3", "C8", "M1", "M101", "M102", 
"M2", "M3", "M4", "M5", "M6", "M7", "M8", "M9", "Z1", "Z101", 
"Z102", "Z2", "Z3", "Z4", "Z5", "Z6", "Z7", "Z8", "Z9"), class = "factor"), 
    variable = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("Week.0", 
    "Week.1", "Week.2", "Week.3", "Week.4", "Week.5", "Week.6", 
    "Week.7", "Week.8", "Week.9", "Week.10", "Week.11", "Week.12"
    ), class = "factor"), value = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 
    NA, NA, 0, 0, 0, 0, 0, 0, 0, 0, 0)), .Names = c("Codering", 
"variable", "value"), row.names = c(NA, 20L), class = "data.frame")

尾巴：

> dput(tail(zmeltdata, 43))
structure(list(Codering = structure(c(19L, 20L, 21L, 22L, 23L, 
24L, 25L, 26L, 17L, 18L, 16L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 
26L, 17L, 18L, 16L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 17L, 
18L, 16L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 17L, 18L), .Label = c("B1", 
"C2", "C3", "C8", "M1", "M101", "M102", "M2", "M3", "M4", "M5", 
"M6", "M7", "M8", "M9", "Z1", "Z101", "Z102", "Z2", "Z3", "Z4", 
"Z5", "Z6", "Z7", "Z8", "Z9"), class = "factor"), variable = structure(c(10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
13L, 13L, 13L), .Label = c("Week.0", "Week.1", "Week.2", "Week.3", 
"Week.4", "Week.5", "Week.6", "Week.7", "Week.8", "Week.9", "Week.10", 
"Week.11", "Week.12"), class = "factor"), value = c(0.1, 0.06, 
0.05, 0.09, 0.04, 0.08, 0.05, 0.08, 0, 0, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)), .Names = c("Codering", 
"variable", "value"), row.names = 101:143, class = "data.frame")

我对这些并不感到惊讶，数据集中有相当多的NA，但它们不应该被证明是一个问题，因为我之前使用过类似（更大）的数据集。 / p>

如果您愿意，我还可以使用.csv文件：https://www.mediafire.com/?jij1vlp14a29ntt

Answer 1

问题在于处理NA ......我通过运行以下代码得到了https://plot.ly/~marianne2/417/z-monophyllum-germination-data/：

pZ <- ggplot(na.omit(zmeltdata), aes(x=variable, y=value, color=Codering,
                                 group=Codering)) +
  geom_line() +
  geom_point() +
  # theme_few() +
  theme(legend.position="right") +
  scale_color_hue(name="Treatment group:") +
  # scale_y_continuous(labels = percent) +
  ylab("Germination percentage") +
  xlab("Week number") +
  labs(title="Z. monophyllum germination data")

py$ggplotly(pZ, kwargs=list(fileopt="overwrite", filename="test_zdata"))

请注意，我必须对theme_few()和scale_y_continuous(labels = percent)发表评论，因为仅加载＆＃34; ggplot2＆＃34;，我会收到以下错误：

Error: could not find function "theme_few"

和

Error in structure(list(call = match.call(), aesthetics = aesthetics,  : 
object 'percent' not found

分别。我想这些都是依赖性问题（也许你正在使用＆＃34; ggthemes＆＃34;？）的版本。

我不知道theme_few()有什么样的魔法，但如果我不在na.omit()上使用zmeltdata，我的pZ情节看起来很像像这样： enter image description here

Eww，＆＃34;第10周和第34周;在＆＃34;第1周和第34周之后来到而不是在＆＃34;第9周和第34周之后......所以你无论如何都不想把它发送到剧情！所以我无法完全重现你的ggplot示例。但是我想知道你是否真的想保留这些NA（CSV本身读取＆＃34; NA＆＃34;，我期待空白＆＃34;细胞＆＃34;）。你不想要预先处理这些吗？

请注意，当我在na.omit()上使用zmeltdata时，会收到以下警告消息：

Warning messages:
1: Removed 20 rows containing missing values (geom_path).
2: Removed 47 rows containing missing values (geom_point).

同样，除了纯粹的显示/绘图考虑因素之外，由于这看起来像科学数据，你不想用实际数字来表示周数，或者如果你真的想要一个字符串，请填上数字？（＆＃34;第01周＆＃34;，＆＃34;第02周和＃34;等）而且看起来缺失的数据全都落后...... 10周以上的数据（还没有），对吧？

感谢您举报，

玛丽安

将绘图导出到Plot.ly时出错

1 个答案: