# Generate a plot of the data. Also uses the inputs to build
# the plot label. Note that the dependencies on both the inputs
# and the data reactive expression are both tracked, and
# all expressions are called in the sequence implied by the
# dependency graph
# d4 <- read.csv(paste(path,"/Data_day4.csv",sep=""))
# d51 <- read.csv(paste(path,"/Day_5_1.csv",sep=""))
# d52 <- read.csv("~/R/shiny-examples/006-tabsets/Day_5_2.csv")
# d53 <- read.csv("~/R/shiny-examples/006-tabsets/Day_5_3.csv")
# d6 <- read.csv("~/R/shiny-examples/006-tabsets/Day_6.csv")
# g1 <- rHighcharts ::: Chart$new()
#
# g1$data(x = c("Fog","Darkness","Twilight"),
# y = c(mean(df$humidity, na.rm = TRUE),mean(df$temperature, na.rm = TRUE),
# mean(df$windspeed, na.rm = TRUE)),
# type = "pie")
#
# g1$legend("Mysterious")
# g1$chart(height = 300, width = 500)
# g1
#g1 <- rHighcharts ::: Chart$new()
#g1$title("Appropriateness of weather")
#g1$data(x = bardata$Conditions, y = bardata$Contribution, type = "bar")
# g1$data(x = c("Fog","Cold","Cluttered"),
# y = c(mean(df$humidity, na.rm = TRUE),mean(df$temperature, na.rm = TRUE),
# mean(df$distance, na.rm = TRUE)),
# type = "bar",col = "")
#g1$xAxis(c("Fog","Cold","Cluttered"))
#g1$chart(height = 200, width = 400)
#dygraph(humidity, main = )
#tags$br()
#dygraph(humidity,main = "Variation of Humidity over time", ylab = "Humidity (%)")
#g2 <- ggplot
# gvisColumnChart(df, xvar = colnames(df)[2], yvar = colnames(df)[3:5lib],
# options=list(title="Variation of atmospheric conditions over time",
# titlePosition='out',
# hAxis="{slantedText:'true',slantedTextAngle:45}",
# titleTextStyle="{color:'black',fontName:'Courier',fontSize:14}",
# height=500, width=800))
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