R中的反应数据帧子集
您好,我想找到我的数据集的两列的相关系数。如果我使用R中的反应数据帧子集,r,shiny,subset,R,Shiny,Subset,您好,我想找到我的数据集的两列的相关系数。如果我使用cor(子集(虹膜,select=c(“萼片长度”)),子集(虹膜,select=c(“萼片宽度”)) 正在找到相关性,但我无法使用作为CSV文件输入的实际数据集子集,该数据集位于反应式表达式中 cor(subset(rt(), select=c("Sepal.Length")),subset(rt(), select=c("Sepal.Width")))` 那么,我怎样才能将这个被动表单的数据帧子集呢 rt<-reactive({
cor(子集(虹膜,select=c(“萼片长度”)),子集(虹膜,select=c(“萼片宽度”))
正在找到相关性,但我无法使用作为CSV文件输入的实际数据集子集,该数据集位于反应式表达式中
cor(subset(rt(), select=c("Sepal.Length")),subset(rt(), select=c("Sepal.Width")))`
那么,我怎样才能将这个被动表单的数据帧子集呢
rt<-reactive({
req(input$file1)
csvdata <- read.csv(input$file1$datapath,
header = input$header
)
csvdata
})
rt有两种解决方法:
将数据帧存储在reactiveValues
对象中(参见:了解非常类似的问题)
通过rt.df将反应式表达式强制为正则R变量什么是反应式形式?我的意思是我使用反应式()创建了它。我编辑了它。@TimBiegeleisen它来自shiny,添加了一个tag@MichaelChirico我太老了,太过时了,不知道这一点:-)@TimBiegeleisen fret不,我是最近才知道的。非常有用:)实际上问题不同,我的数据集包括NAs,我用x替换了NAs
#ui.r
library(shiny)
library(ggplot2)
library(plotly)
library(extrafont)
fluidPage(
# App title ----
titlePanel(div("CROSS CORRELATION",style = "color:blue")),
# Sidebar layout with input and output definitions ----
sidebarLayout(
# Sidebar panel for inputs ----
sidebarPanel(
# Input: Select a file ----
fileInput("file1", "Input CSV-File",
multiple = TRUE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
# Horizontal line ----
tags$hr(),
# Input: Checkbox if file has header ----
checkboxInput("header", "Header", TRUE),
# Input: Select separator ----
radioButtons("sep", "Separator",
choices = c(Comma = ",",
Semicolon = ";",
Tab = "\t"),
selected = ","),
# Horizontal line ----
tags$hr(),
# Input: Select number of rows to display ----
radioButtons("disp", "Display",
choices = c(Head = "head",
All = "all"),
selected = "head")
),
# Main panel for displaying outputs ----
mainPanel(
tabsetPanel(type = "tabs",
tabPanel("Table",
shiny::dataTableOutput("contents")),
tabPanel("Correlation Plot",
fluidRow(
column(3, uiOutput("lx1")),
column(3,uiOutput("lx2"))),
hr(),
fluidRow(
tags$style(type="text/css",
".shiny-output-error { visibility: hidden; }",
".shiny-output-error:before { visibility: hidden; }"
),
column(3,uiOutput("td")),
column(3,uiOutput("an"))),
plotlyOutput("sc"))
))
))
#server.r
function(input, output) {
rt<-reactive({
req(input$file1)
csvdata <- read.csv(input$file1$datapath,
header = input$header
)
csvdata
})
output$contents <- shiny::renderDataTable({
rt()
})
output$lx1<-renderUI({
selectInput("lx1", label = h4("Select 1st Expression Profile"),
choices = colnames(rt()[,4:15]),
selected = "Lex1")
})
output$lx2<-renderUI({
selectInput("lx2", label = h4("Select 2nd Expression Profile"),
choices = colnames(rt()[,4:15]),
selected = "Lex2")
})
output$td<-renderUI({
radioButtons("td", label = h3("Trendline"),
choices = list("Add Trendline" = "lm", "Remove Trendline" = ""),
selected = "")
})
output$an<-renderUI({
radioButtons("an", label = h3("Correlation Coefficient"),
choices = list("Add R^2" = cor(subset(rt(), select=c(input$lx1)),subset(rt(), select=c(input$lx2))), "Remove R^2" = ""),
selected = "")
})
output$sc<-renderPlotly({
p1 <- ggplot(rt(), aes_string(x = input$lx1, y = input$lx2))+
# Change the point options in geom_point
geom_point(color = "darkblue") +
# Change the title of the plot (can change axis titles
# in this option as well and add subtitle)
labs(title = "Cross Correlation") +
# Change where the tick marks are
scale_x_continuous(breaks = seq(0, 80000, 10000)) +
scale_y_continuous(breaks = seq(0, 120000, 20000)) +
# Change how the text looks for each element
theme(title = element_text(family = "Calibri",
size = 10,
face = "bold"),
axis.title = element_text(family = "Calibri Light",
size = 16,
face = "bold",
color = "darkgrey"),
axis.text = element_text(family = "Calibri",
size = 11))+
theme_bw()+
geom_smooth(method = input$td)+
annotate("text", x = 50000, y = 50000, label = as.character(input$an))
ggplotly(p1) %>%
layout(hoverlabel = list(bgcolor = "white",
font = list(family = "Calibri",
size = 9,
color = "black")))
})
}