r - 我无法让 DT 包在 Rshiny 上正常工作
问题描述
我目前正在开发一个 Rshiny webapp，用于一些简单的分类。目前，我一直在努力创建一个表，其中包含 CART 和 LDA 数据方法的 CCR 和 MCR。然后，我的目标是突出显示最佳方法的 MCR 和 CCR 列（具有最高 CCR 的方法......或最低 MCR）。我已经运行了代码并查看它使用查看器窗格可以正常工作。但是，当我加载应用程序时，我得到错误'data' must be 2-dimensional (eg data frame or matrix)。
这是我的代码：
data <- read.csv("Fatality-task2.csv")
data$Rate <- as.factor(data$Rate)
library(shiny)
library(dplyr)
library(ggplot2)
library(markdown)
library(gtsummary)
library(ggdendro)
library(factoextra)
library(mclust)
library(cluster)
library(rpart)
library(rpart.plot)
library(DT)
#library(MASS)
glimpse(data)
#################################################################
ui <- fluidPage(
navbarPage("",
tabPanel("Data Exploration",
sidebarLayout(
sidebarPanel(
selectInput("variable",
"Variable",
colnames(data)),
selectInput("rate",
"Rate",
levels(data$Rate))
),
mainPanel(
tableOutput("table"),
plotOutput("plot")
)
)
),
tabPanel("Classification tools",
sidebarLayout(
sidebarPanel(
sliderInput("train.prop",
"Training data proportion",
min = 0.4,
max = 0.8,
step = 0.1,
value = 0.6),
radioButtons("prune",
"Pruning option",
choices = c("view pruned tree",
"view unpruned tree"))
),
mainPanel(
DTOutput("table2"),
plotOutput("plot2")
)
)
)
)
)
#################################################################
server <- function(input, output) {
output$table <- renderTable({
req(input$variable,input$rate)
data <- data %>%
filter(Rate == input$rate) %>%
dplyr::select(input$variable) %>%
summary() %>%
as.data.frame() %>%
tidyr::separate(Freq, c("Stat", "Value"), sep=":") %>%
tidyr::pivot_wider(names_from =Stat, values_from = Value)
data <- data[, -c(1,2)]
})
output$plot <- renderPlot({
req(input$variable)
if (input$variable == "jaild" | input$variable == "Rate"){
ggplot(data, aes(x = Rate, fill = .data[[as.name(input$variable)]])) +
geom_bar(position = "dodge", width = 0.7) +
if (input$variable == "Rate"){
theme(legend.position = "none")
}
} else {
ggplot(data, aes(x = Rate, y = .data[[as.name(input$variable)]], fill = Rate)) +
geom_boxplot() +
theme(legend.position = "none")
}
})
output$plot2 <- renderPlot({
req(input$train.prop,input$prune)
set.seed(1234)
n <- nrow(data)
ind1 <- sample(c(1:n), round(n*as.numeric(input$train.prop)))
ind2 <- sample(c(1:n)[-ind1], length(c(1:n)[-ind1]))
train.data <- data[ind1,]
valid.data <- data[ind2,]
fit.tree <- rpart(Rate~., data = train.data, method = "class")
ptree <- prune(fit.tree, cp = fit.tree$cptable[which.min(fit.tree$cptable[,"xerror"]),"CP"])
if (input$prune == "view pruned tree"){
rpart.plot(ptree, uniform =TRUE)
} else {
rpart.plot(fit.tree)
}
})
output$table2 <- DT::renderDT({
library(MASS)
set.seed(1234)
n <- nrow(data)
ind1 <- sample(c(1:n), round(n*0.6))
#ind2 <- sample(c(1:n)[-ind1], length(c(1:n)[-ind1]))
ind2 <- setdiff(c(1:n), ind1)
train.data <- data[ind1,]
valid.data <- data[ind2,]
#################################
### fit cart model
fit.tree <- rpart(Rate~., data = train.data, method = "class")
### prune the tree
ptree <- prune(fit.tree, cp = fit.tree$cptable[which.min(fit.tree$cptable[,"xerror"]),"CP"])
### predict using the validation data on the pruned tree
pred <- predict(ptree, newdata = valid.data[,-6], type = "class")
### lda
#lda.model <- lda(train.data[,-6], train.data[,6])
lda.model <- lda(Rate~., data = train.data)
lda.pred <- predict(lda.model, newdata = valid.data[,-6])
### create a classification table
length(lda.model)
x <- pred == valid.data[,6]
CCR <- length(x[x == TRUE])/nrow(valid.data)
MCR <- 1 - CCR
CR <- c(CCR, MCR)
z <- lda.pred$class == valid.data[,6]
lda.CCR <- length(z[z == TRUE])/nrow(valid.data)
lda.MCR <- 1 - lda.CCR
lda.CR <- c(lda.CCR, lda.MCR)
y <- cbind(CR, lda.CR)
y <- as.data.frame(y)
colnames(y) <- c("CART", "LDA")
rownames(y) <- c("CCR", "MCR")
#y
DT::datatable(y, options=list(dom = "t")) %>%
formatRound(columns = c(1,2), digits = 6) %>%
formatStyle(columns = colnames(y[which.max(y[1,])]), background = "green")
#colnames(y[1])
#colnames(y[which.max(y[1,])])
},
rownames = TRUE)
}
?formatStyle
?formatRound()
#################################################################
shinyApp(ui, server)
这是我的一些数据：
"beertax","jaild","vmiles","unrate","perinc","Rate"
1.53937947750092,"no",7.23388720703125,14.3999996185303,10544.15234375,1
1.78899073600769,"no",7.83634765625,13.6999998092651,10732.7978515625,1
1.71428561210632,"no",8.262990234375,11.1000003814697,11108.791015625,1
1.65254235267639,"no",8.7269169921875,8.89999961853027,11332.626953125,1
1.60990703105927,"no",8.952853515625,9.80000019073486,11661.5068359375,1
1.55999994277954,"no",9.1663017578125,7.80000019073486,11944,1
1.50144362449646,"no",9.6743232421875,7.19999980926514,12368.6240234375,1
0.214797139167786,"yes",6.81015673828125,9.89999961853027,12309.0693359375,1
0.206422030925751,"yes",6.58749462890625,9.10000038146973,12693.8076171875,1
0.296703308820724,"yes",6.70997021484375,5,13265.93359375,1
0.381355941295624,"yes",6.7712626953125,6.5,13726.6953125,1
0.371517032384872,"yes",8.1290078125,6.90000009536743,14107.3271484375,1
0.360000014305115,"yes",9.370654296875,6.19999980926514,14241,1
0.346487015485764,"yes",9.815720703125,6.30000019073486,14408.0849609375,1
0.650358021259308,"no",7.20850048828125,9.80000019073486,10267.302734375,1
0.67545872926712,"no",7.1759169921875,10.1000003814697,10433.486328125,1
0.598901093006134,"no",7.08481982421875,8.89999961853027,10916.4833984375,1
0.577330529689789,"no",7.25391796875,8.69999980926514,11149.3642578125,1
0.562435507774353,"no",7.4689990234375,8.69999980926514,11399.380859375,1
0.545000016689301,"no",7.66583056640625,8.10000038146973,11537,1
0.52454286813736,"no",8.02462548828125,7.69999980926514,11760.3466796875,1
0.107398569583893,"no",6.8586767578125,9.89999961853027,15797.1357421875,0
0.103211015462875,"no",7.21629150390625,9.69999980926514,15970.18359375,0
0.0989011004567146,"no",7.61917578125,7.80000019073486,16590.109375,0
0.0953389853239059,"no",7.87406689453125,7.19999980926514,16985.169921875,0
0.0928792580962181,"no",8.03491015625,6.69999980926514,17356.037109375,0
0.0900000035762787,"no",8.18063330078125,5.80000019073486,17846,0
0.0866217538714409,"no",8.531990234375,5.30000019073486,18049.0859375,0
0.214797139167786,"no",7.742841796875,7.69999980926514,15082.3388671875,1
0.206422030925751,"no",7.65606298828125,6.59999990463257,15131.880859375,1
0.197802200913429,"no",7.7078525390625,5.59999990463257,15486.8134765625,0
0.190677970647812,"no",8.09220947265625,5.90000009536743,15569.9150390625,0
0.185758516192436,"no",8.13137451171875,7.40000009536743,15616.0986328125,0
0.180000007152557,"no",8.18202783203125,7.69999980926514,15605,0
0.173243507742882,"no",8.3807685546875,6.40000009536743,15845.04296875,0
0.224343672394753,"no",6.4400537109375,6.90000009536743,17255.369140625,0
0.233563080430031,"no",6.57004296875,6,17744.265625,0
0.248010993003845,"no",6.68019287109375,4.59999990463257,18760.439453125,0
0.239078402519226,"yes",6.97921484375,4.90000009536743,19312.5,0
我知道代码可以正常工作 - 我只是希望它能够在应用程序上正常运行。请帮忙！
解决方案
推荐阅读
- reactjs - 无法读取未定义 React 的属性“toLowerCase”
- python-3.x - 如何返回指向对象属性的链接而不是 Python3 中的值？
- amazon-web-services - AWS 访问用户组的 S3 存储桶文件夹
- swift - Mapsdk 没有出现在我的故事板中
- ios - 为不兼容的目标 x86_64-apple-ios13.0 创建了模块“Swift”
- maven - 如何在集群模式下运行 spark-submit 命令时覆盖 spark jar？（好的http3）
- linux - 推送时出现“远程：Gogs：内部错误”错误
- python - 使用 curses 库无法阻止箭头键回显到 Python 中的控制台
- javascript - 在 THREE.js 中使用四元数设置矢量的全局旋转
- c++ - 如何将 QListView 中的每个元素添加到向量中？