根据输入的日期更改传单图上的数据（R，S）
我正在尝试使用R创建一个闪亮的应用程序，通过传单在地图上绘制坐标数据。数据也有日期戳，我希望能够根据用户的选择绘制特定日期的坐标。我对R和Shinny都是全新的，所以非常感谢大家的帮助。这里是数据帧的一个片段根据输入的日期更改传单图上的数据（R，S）,r,shiny,leaflet,R,Shiny,Leaflet,我正在尝试使用R创建一个闪亮的应用程序，通过传单在地图上绘制坐标数据。数据也有日期戳，我希望能够根据用户的选择绘制特定日期的坐标。我对R和Shinny都是全新的，所以非常感谢大家的帮助。这里是数据帧的一个片段 Date | InitialLat | InitialLong | NewLat | NewLong | 13/05/16 | 53.477403 | -2.230932 | 51.527953 | -0.13216 | 13/05/16 |
Date | InitialLat | InitialLong | NewLat | NewLong |
13/05/16 | 53.477403 | -2.230932 | 51.527953 | -0.13216 |
13/05/16 | 53.490599 | -2.312568 | 53.485655 | -2.237405 |
14/05/16 | 53.371535 | -2.23148 | 53.32803 | -2.246991 |
14/05/16 | 53.371535 | -2.23148 | 53.32803 | -2.246991 |
15/05/16 | 53.371535 | -2.23148 | 53.32803 | -2.246991 |
15/05/16 | 53.371535 | -2.23148 | 53.32803 | -2.246991 |
16/05/16 | 53.478316 | -2.23270 | 53.42814 | -2.17458 |
16/05/16 | 53.48868 | -2.21839 | 53.47737 | -2.23091 |
library(shiny)
library(leaflet)
cleanData <- read.csv(file="CleanedJourneyData.csv", header=TRUE, sep=",")
cleanData$X <- NULL
ui <- fluidPage(
dateInput(inputId = "n_date", label="Select a date", value = "2016-05-13", min = "2016-05-13", max = "2016-10-24",
format = "dd-mm-yyyy", startview = "month",
language = "en", width = NULL),
leafletOutput("map")
)
server <- function(input, output, session) {
dailyData <- reactive(cleanData[cleanData$Date == format(input$n_date, '%d/%m/%y')] )
output$map <- renderLeaflet({ leaflet(dailyData) %>% addTiles() %>%
addMarkers(~InitialLong, ~InitialLat, popup = "Start") })
}
shinyApp(ui, server)
- 用户选择一个日期
- 日期的格式已更改为“%d/%m/%y”
- 然后使用输入的日期搜索数据框（cleanData），以创建一个新的数据框（dailyData），该数据框仅包含所选日期的横向/纵向坐标
- 修剪后的数据框被输入传单地图并显示
日期输入工作正常，我可以以正确的格式获取日期，但当我尝试使用它搜索cleanData以创建dailyData时，它不起作用，我无法找到它。我做错了什么？作为记录，我能够让它在Shiny之外工作-我手动更改了代码中的日期，并通过传单绘制了相应的坐标。我修改了您的代码。看看这是不是你真正想要的
library(shiny)
library(leaflet)
cleanData <- read.csv(file="D:/CleanedJourneyData.csv", header=TRUE, sep=",")
cleanData$X <- NULL
ui <- fluidPage(
dateInput(inputId = "n_date", label="Select a date", value = "2016-05-13", min = "2016-05-13", max = "2016-10-24",
format = "dd-mm-yyyy", startview = "month",
language = "en", width = NULL),
leafletOutput("map")
)
server <- function(input, output, session) {
dailyData <- reactive(cleanData[cleanData$Date == format(input$n_date, '%d/%m/%y'), ] )
# I have implemented the change here, instead of using dailyData, I've used isolate(dailyData())
output$map <- renderLeaflet({ leaflet(isolate(dailyData())) %>% addTiles() %>%
addMarkers(~InitialLong, ~InitialLat, popup = "Start") })
}
shinyApp(ui, server)
库（闪亮）
图书馆（单张）
cleanData在一位精通R的同事的帮助下，我找到了问题的答案
cleanData <- read.csv(file="/Users/CharlesPowell/R/CleanedJourneyData.csv", header=TRUE, sep=",")
cleanData$X <- NULL
r_colors <- rgb(t(col2rgb(colors()) / 255))
names(r_colors) <- colors()
ui <- fluidPage(
dateInput(inputId = "n_date", label="Select a date", value = "2016-05-13", min = "2016-05-13", max = "2016-10-24",
format = "dd-mm-yyyy", startview = "month",
language = "en", width = NULL),
leafletOutput("map")
)
server <- function(input, output, session) {
numrow <- reactive({cleanData$Date == format(input$n_date, '%d/%m/%y')})
dailyData <- reactive({cbind(cleanData[numrow(),], Observation = seq(1:sum(numrow())))})
z <- reactive({as.data.frame(gather(data=dailyData()[, 2:dim(dailyData())[2]], measure, val, -Observation) %>% group_by(Observation) %>%
do(data.frame( lat=c(.[["val"]][.[["measure"]]=="InitialLat"],
.[["val"]][.[["measure"]]=="NewLat"]),
long = c(.[["val"]][.[["measure"]]=="InitialLong"],
.[["val"]][.[["measure"]]=="NewLong"]))))})
y <- reactive({points_to_line(z(), "long", "lat", "Observation")})
output$map <- renderLeaflet({ leaflet(dailyData()) %>% addTiles() %>%
addMarkers(~InitialLong, ~InitialLat, popup = "Start") %>%
addPolylines(data = y()) })
}
shinyApp(ui, server)
cleanData嗨，我实现了你的修改，但很抱歉，我不明白它们是做什么的。你能解释一下吗？@Calastar我添加了一些评论。希望你能理解。关于更多的细节，你可以按照这个抱歉@SBista，但我完全被难住了。我无法理解反应性功能。我在Shinny RStudio网站和Youtube上观看了该教程，并阅读了大量相关文档。我感谢你的帮助，但我觉得我离我需要的解决方案还有一段距离。你的反应功能有一个错误。它应该是被动的（{}）…缺少大括号被动是一个返回数据的函数，而不是数据本身。要获取数据，请像下面这样调用它传单（dailyData（））
library(shiny)
library(leaflet)
cleanData <- read.csv(file="D:/CleanedJourneyData.csv", header=TRUE, sep=",")
cleanData$X <- NULL
ui <- fluidPage(
dateInput(inputId = "n_date", label="Select a date", value = "2016-05-13", min = "2016-05-13", max = "2016-10-24",
format = "dd-mm-yyyy", startview = "month",
language = "en", width = NULL),
leafletOutput("map")
)
server <- function(input, output, session) {
dailyData <- reactive(cleanData[cleanData$Date == format(input$n_date, '%d/%m/%y'), ] )
# I have implemented the change here, instead of using dailyData, I've used isolate(dailyData())
output$map <- renderLeaflet({ leaflet(isolate(dailyData())) %>% addTiles() %>%
addMarkers(~InitialLong, ~InitialLat, popup = "Start") })
}
shinyApp(ui, server)
cleanData <- read.csv(file="/Users/CharlesPowell/R/CleanedJourneyData.csv", header=TRUE, sep=",")
cleanData$X <- NULL
r_colors <- rgb(t(col2rgb(colors()) / 255))
names(r_colors) <- colors()
ui <- fluidPage(
dateInput(inputId = "n_date", label="Select a date", value = "2016-05-13", min = "2016-05-13", max = "2016-10-24",
format = "dd-mm-yyyy", startview = "month",
language = "en", width = NULL),
leafletOutput("map")
)
server <- function(input, output, session) {
numrow <- reactive({cleanData$Date == format(input$n_date, '%d/%m/%y')})
dailyData <- reactive({cbind(cleanData[numrow(),], Observation = seq(1:sum(numrow())))})
z <- reactive({as.data.frame(gather(data=dailyData()[, 2:dim(dailyData())[2]], measure, val, -Observation) %>% group_by(Observation) %>%
do(data.frame( lat=c(.[["val"]][.[["measure"]]=="InitialLat"],
.[["val"]][.[["measure"]]=="NewLat"]),
long = c(.[["val"]][.[["measure"]]=="InitialLong"],
.[["val"]][.[["measure"]]=="NewLong"]))))})
y <- reactive({points_to_line(z(), "long", "lat", "Observation")})
output$map <- renderLeaflet({ leaflet(dailyData()) %>% addTiles() %>%
addMarkers(~InitialLong, ~InitialLat, popup = "Start") %>%
addPolylines(data = y()) })
}
shinyApp(ui, server)