我是R new的新手，只是通过实现以下代码链接“用流动数据和警报通知可视化”来尝试在R闪亮中进行实时数据可视化
https://datascienceplus.com/visualizing-streaming-data-with-shiny/
我正在使用两个R会话
R-session1
我正在使用以下代码
setwd("G:\\MY Project\\Jigsaw\\Deep learning\\shinyreal")
library(ggplot2)
library(dplyr)
data(diamonds)
这里使用了钻石数据集 .
head(diamonds)
# A tibble: 6 x 10
carat cut color clarity depth table price x y z
<dbl> <ord> <ord> <ord> <dbl> <dbl> <int> <dbl> <dbl> <dbl>
1 0.23 Ideal E SI2 61.5 55 326 3.95 3.98 2.43
2 0.21 Premium E SI1 59.8 61 326 3.89 3.84 2.31
3 0.23 Good E VS1 56.9 65 327 4.05 4.07 2.31
4 0.290 Premium I VS2 62.4 58 334 4.2 4.23 2.63
5 0.31 Good J SI2 63.3 58 335 4.34 4.35 2.75
6 0.24 Very Good J VVS2 62.8 57 336 3.94 3.96 2.48
str(diamonds)
Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 53940 obs. of 10 variables:
$ carat : num 0.23 0.21 0.23 0.29 0.31 0.24 0.24 0.26 0.22 0.23 ...
$ cut : Ord.factor w/ 5 levels "Fair"<"Good"<..: 5 4 2 4 2 3 3 3 1 3 ...
$ color : Ord.factor w/ 7 levels "D"<"E"<"F"<"G"<..: 2 2 2 6 7 7 6 5 2 5 ...
$ clarity: Ord.factor w/ 8 levels "I1"<"SI2"<"SI1"<..: 2 3 5 4 2 6 7 3 4 5 ...
$ depth : num 61.5 59.8 56.9 62.4 63.3 62.8 62.3 61.9 65.1 59.4 ...
$ table : num 55 61 65 58 58 57 57 55 61 61 ...
$ price : int 326 326 327 334 335 336 336 337 337 338 ...
$ x : num 3.95 3.89 4.05 4.2 4.34 3.94 3.95 4.07 3.87 4 ...
$ y : num 3.98 3.84 4.07 4.23 4.35 3.96 3.98 4.11 3.78 4.05 ...
$ z : num 2.43 2.31 2.31 2.63 2.75 2.48 2.47 2.53 2.49 2.39 ...
这是将连续生成“.csv”文件的代码，并将保存在上面的文件夹中 .
while(TRUE){
temp=sample_frac(diamonds, 0.1)
write.csv(temp, paste0("sampled", gsub("[^0-9]","", Sys.time()), ".csv"), row.names = FALSE)
Sys.sleep(10) # Suspend execution of R expressions. The time interval to suspend execution for, in seconds.
}
R会话1非常好，因为“.csv”不断生成并保存在目标文件夹上 .
现在的问题是UI.R和Server.R程序 .
R session 2
我复制了以下代码
setwd("G:\\MY Project\\Jigsaw\\Deep learning\\shinyreal")
library(shiny)
ui<-fluidPage(
tags$h2("Visualizing Streaming Data with Shiny", style = "color:blue; text-aligh: center"),
plotOutput("plot1", height = "600px")
)
library(rsconnect)
library(shiny)
library(data.table)
library(ggplot2)
library(gridExtra)
library(readr)
IsThereNewFile=function(){ # cheap function whose values over time will be tested for equality;
# inequality indicates that the underlying value has changed and needs to be
# invalidated and re-read using valueFunc
filenames <- list.files(pattern="*.csv", full.names=TRUE)
length(filenames)
}
ReadAllData=function(){ # A function that calculates the underlying value
filenames <- list.files(pattern="*.csv", full.names=TRUE)
read_csv(filenames[length(filenames)])
}
server<-function(input, output, session) {
sampled_data <- reactivePoll(10, session,IsThereNewFile, ReadAllData)
# 10: number of milliseconds to wait between calls to checkFunc
output$plot1<-renderPlot({
sampled_data= sampled_data()
g1= ggplot(sampled_data, aes(depth, fill = cut, colour = cut)) +
geom_density(alpha = 0.1) +xlim(55, 70)+ggtitle("Distribution of Depth by Cut")+
theme(plot.title = element_text(color="darkred",size=18,hjust = 0.5),
axis.text.y = element_text(color="blue",size=12,hjust=1),
axis.text.x = element_text(color="darkred",size=12,hjust=.5,vjust=.5),
axis.title.x = element_text(color="red", size=14),
axis.title.y = element_text(size=14))
g2=ggplot(sampled_data, aes(carat, ..count.., fill = cut)) +
geom_density(position = "stack")+ggtitle("Total Carat by Count")+
theme(plot.title = element_text(color="purple",size=18,hjust = 0.5),
axis.text.y = element_text(color="blue",size=12,hjust=1),
axis.text.x = element_text(color="darkred",size=12,hjust=.5,vjust=.5),
axis.title.x = element_text(color="red", size=14),
axis.title.y = element_text(size=14))
g3=ggplot(sampled_data, aes(carat, ..count.., fill = cut)) +
geom_density(position = "fill")+ggtitle("Conditional Density Estimate")+
theme(plot.title = element_text(color="black",size=18,hjust = 0.5),
axis.text.y = element_text(color="blue",size=12,hjust=1),
axis.text.x = element_text(color="darkred",size=12,hjust=.5,vjust=.5),
axis.title.x = element_text(color="red", size=14),
axis.title.y = element_text(size=14))
g4=ggplot(sampled_data,aes(carat,price))+geom_boxplot()+facet_grid(.~cut)+
ggtitle("Price by Carat for each cut")+
theme(plot.title = element_text(color="darkblue",size=18,hjust = 0.5),
axis.text.y = element_text(color="blue",size=12,hjust=1),
axis.text.x = element_text(color="darkred",size=12,hjust=.5,vjust=.5),
axis.title.x = element_text(color="red", size=14),
axis.title.y = element_text(size=14))
grid.arrange(g1,g2,g3,g4)
})
}
shinyApp(ui, server)
在运行R session 1代码时，它会生成.csv文件（这部分没问题）
在运行R session 2代码或shinyapp时，它创建了4个静态图像，但我的动态绘图没有显示 . 我认为它无法自动从更新文件中读取数据 .
我无法找到实际问题 .
显示以下错误 .
shinyApp(ui, server)
Listening on http://127.0.0.1:5341
Parsed with column specification:
cols(
carat = col_double(),
cut = col_character(),
color = col_character(),
clarity = col_character(),
depth = col_double(),
table = col_double(),
price = col_integer(),
x = col_double(),
y = col_double(),
z = col_double()
)
Warning: Removed 2 rows containing non-finite values (stat_density).
Warning: Continuous x aesthetic -- did you forget aes(group=...)?
Don't know how to automatically pick scale for object of type function. Defaulting to continuous.
Don't know how to automatically pick scale for object of type function. Defaulting to continuous.
Warning: Error in FUN: object 'depth' not found
[No stack trace available]
什么时候出现这种错误？ ggplot2中的任何问题？
建议总是受到赞赏 .