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When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:
library(readxl)
kumos <- read_excel("./kumos_.xlsx")
str(kumos)
## Classes 'tbl_df', 'tbl' and 'data.frame': 26876 obs. of 28 variables:
## $ Cruise_ID : chr "HI-16-01" "HI-16-01" "HI-16-01" "HI-16-01" ...
## $ Year : num 2016 2016 2016 2016 2016 ...
## $ Month : num 8 8 8 8 8 8 8 8 8 8 ...
## $ Day : num 5 5 5 5 5 5 5 5 5 5 ...
## $ Hour : num 5 5 5 5 5 5 5 5 5 5 ...
## $ Min : num 17 19 20 21 22 23 24 25 27 28 ...
## $ SEC : num 59 59 59 59 59 59 59 59 59 59 ...
## $ Latitude : num 35 35 35 35 35 ...
## $ Lat_hem : chr "N" "N" "N" "N" ...
## $ Longitude : num 129 129 129 129 129 ...
## $ Longitude_hem: chr "E" "E" "E" "E" ...
## $ Course : num 275.47 19.43 12.16 7.75 8.6 ...
## $ Speed : num 2.1 0.2 1.7 1.8 1.9 3 4 5.9 7.8 7.7 ...
## $ Heading : num 93.1 40.3 15.4 13.1 14.7 ...
## $ App_WS : num 1.73 3.27 5.09 3.99 3.85 ...
## $ App_WD : num 355.2 22.3 47.1 77.8 49.3 ...
## $ True_WS : num 1.72 3.26 4.92 3.96 3.35 ...
## $ True_WD : num 101.3 91.2 86.8 106.5 76.2 ...
## $ Air_Temp : num 29.1 29.3 29.4 29.4 29.4 ...
## $ Atmos_Press : num 1008 1008 1008 1008 1007 ...
## $ Humidity : num 69 69.4 69.9 68.7 68.8 ...
## $ Solar_R : num NA NA 696 NA 820 ...
## $ Conductivity : num 48.5 48.5 48.5 48.5 48.5 ...
## $ Seawater_T1 : num NA NA NA NA NA NA NA NA NA NA ...
## $ Seawater_T2 : num 24.1 24.1 24.1 24.1 24.1 ...
## $ Salinity : num NA NA NA NA NA NA NA NA NA NA ...
## $ Depth : num NA 4.62 4.44 4.26 4.58 5.11 5.08 5.49 NA NA ...
## $ Datetime : POSIXct, format: NA NA ...
kumos$Cruise_ID <- factor(kumos$Cruise_ID)
str(kumos)
## Classes 'tbl_df', 'tbl' and 'data.frame': 26876 obs. of 28 variables:
## $ Cruise_ID : Factor w/ 5 levels "HI-16-00","HI-16-01",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ Year : num 2016 2016 2016 2016 2016 ...
## $ Month : num 8 8 8 8 8 8 8 8 8 8 ...
## $ Day : num 5 5 5 5 5 5 5 5 5 5 ...
## $ Hour : num 5 5 5 5 5 5 5 5 5 5 ...
## $ Min : num 17 19 20 21 22 23 24 25 27 28 ...
## $ SEC : num 59 59 59 59 59 59 59 59 59 59 ...
## $ Latitude : num 35 35 35 35 35 ...
## $ Lat_hem : chr "N" "N" "N" "N" ...
## $ Longitude : num 129 129 129 129 129 ...
## $ Longitude_hem: chr "E" "E" "E" "E" ...
## $ Course : num 275.47 19.43 12.16 7.75 8.6 ...
## $ Speed : num 2.1 0.2 1.7 1.8 1.9 3 4 5.9 7.8 7.7 ...
## $ Heading : num 93.1 40.3 15.4 13.1 14.7 ...
## $ App_WS : num 1.73 3.27 5.09 3.99 3.85 ...
## $ App_WD : num 355.2 22.3 47.1 77.8 49.3 ...
## $ True_WS : num 1.72 3.26 4.92 3.96 3.35 ...
## $ True_WD : num 101.3 91.2 86.8 106.5 76.2 ...
## $ Air_Temp : num 29.1 29.3 29.4 29.4 29.4 ...
## $ Atmos_Press : num 1008 1008 1008 1008 1007 ...
## $ Humidity : num 69 69.4 69.9 68.7 68.8 ...
## $ Solar_R : num NA NA 696 NA 820 ...
## $ Conductivity : num 48.5 48.5 48.5 48.5 48.5 ...
## $ Seawater_T1 : num NA NA NA NA NA NA NA NA NA NA ...
## $ Seawater_T2 : num 24.1 24.1 24.1 24.1 24.1 ...
## $ Salinity : num NA NA NA NA NA NA NA NA NA NA ...
## $ Depth : num NA 4.62 4.44 4.26 4.58 5.11 5.08 5.49 NA NA ...
## $ Datetime : POSIXct, format: NA NA ...
dim(kumos)
## [1] 26876 28
You can also embed plots, for example:
hangcha <- kumos[,1]
Month <- kumos[,3]
Hour <- kumos[,5]
spd <- kumos[,17]
dir <- kumos[,18]
df <- data.frame(hangcha, Month, Hour, spd, dir)
names(df)[1]<-"hangcha"
str(df)
## 'data.frame': 26876 obs. of 5 variables:
## $ hangcha: Factor w/ 5 levels "HI-16-00","HI-16-01",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ Month : num 8 8 8 8 8 8 8 8 8 8 ...
## $ Hour : num 5 5 5 5 5 5 5 5 5 5 ...
## $ spd : num 1.72 3.26 4.92 3.96 3.35 ...
## $ dir : num 101.3 91.2 86.8 106.5 76.2 ...
head(df)
## hangcha Month Hour spd dir
## 1 HI-16-01 8 5 1.723796 101.30310
## 2 HI-16-01 8 5 3.256355 91.23310
## 3 HI-16-01 8 5 4.920528 86.76074
## 4 HI-16-01 8 5 3.963347 106.45040
## 5 HI-16-01 8 5 3.349347 76.16217
## 6 HI-16-01 8 5 4.109369 101.18940
library(DT)
datatable(df)
## Warning in instance$preRenderHook(instance): It seems your data is too
## big for client-side DataTables. You may consider server-side processing:
## http://rstudio.github.io/DT/server.html
# WindRose.R
require(ggplot2)
## Loading required package: ggplot2
require(RColorBrewer)
## Loading required package: RColorBrewer
plot.windrose <- function(data,
spd,
dir,
spdres = 2,
dirres = 30,
spdmin = 2,
spdmax = 20,
spdseq = NULL,
palette = "YlGnBu",
countmax = NA,
debug = 0){
# Look to see what data was passed in to the function
if (is.numeric(spd) & is.numeric(dir)){
# assume that we've been given vectors of the speed and direction vectors
data <- data.frame(spd = spd,
dir = dir)
spd = "spd"
dir = "dir"
} else if (exists("data")){
# Assume that we've been given a data frame, and the name of the speed
# and direction columns. This is the format we want for later use.
}
# Tidy up input data ----
n.in <- NROW(data)
dnu <- (is.na(data[[spd]]) | is.na(data[[dir]]))
data[[spd]][dnu] <- NA
data[[dir]][dnu] <- NA
# figure out the wind speed bins ----
if (missing(spdseq)){
spdseq <- seq(spdmin,spdmax,spdres)
} else {
if (debug >0){
cat("Using custom speed bins \n")
}
}
# get some information about the number of bins, etc.
n.spd.seq <- length(spdseq)
n.colors.in.range <- n.spd.seq - 1
# create the color map
spd.colors <- colorRampPalette(brewer.pal(min(max(3,
n.colors.in.range),
min(9,
n.colors.in.range)),
palette))(n.colors.in.range)
if (max(data[[spd]],na.rm = TRUE) > spdmax){
spd.breaks <- c(spdseq,
max(data[[spd]],na.rm = TRUE))
spd.labels <- c(paste(c(spdseq[1:n.spd.seq-1]),
'-',
c(spdseq[2:n.spd.seq])),
paste(spdmax,
"-",
max(data[[spd]],na.rm = TRUE)))
spd.colors <- c(spd.colors, "grey50")
} else{
spd.breaks <- spdseq
spd.labels <- paste(c(spdseq[1:n.spd.seq-1]),
'-',
c(spdseq[2:n.spd.seq]))
}
data$spd.binned <- cut(x = data[[spd]],
breaks = spd.breaks,
labels = spd.labels,
ordered_result = TRUE)
# clean up the data
data. <- na.omit(data)
# figure out the wind direction bins
dir.breaks <- c(-dirres/2,
seq(dirres/2, 360-dirres/2, by = dirres),
360+dirres/2)
dir.labels <- c(paste(360-dirres/2,"-",dirres/2),
paste(seq(dirres/2, 360-3*dirres/2, by = dirres),
"-",
seq(3*dirres/2, 360-dirres/2, by = dirres)),
paste(360-dirres/2,"-",dirres/2))
# assign each wind direction to a bin
dir.binned <- cut(data[[dir]],
breaks = dir.breaks,
ordered_result = TRUE)
levels(dir.binned) <- dir.labels
data$dir.binned <- dir.binned
# Run debug if required ----
if (debug>0){
cat(dir.breaks,"\n")
cat(dir.labels,"\n")
cat(levels(dir.binned),"\n")
}
# deal with change in ordering introduced somewhere around version 2.2
if(packageVersion("ggplot2") > "2.2"){
cat("Hadley broke my code\n")
data$spd.binned = with(data, factor(spd.binned, levels = rev(levels(spd.binned))))
spd.colors = rev(spd.colors)
}
# create the plot ----
p.windrose <- ggplot(data = data,
aes(x = dir.binned,
fill = spd.binned)) +
geom_bar() +
scale_x_discrete(drop = FALSE,
labels = waiver()) +
coord_polar(start = -((dirres/2)/360) * 2*pi) +
scale_fill_manual(name = "Wind Speed (m/s)",
values = spd.colors,
drop = FALSE) +
#theme_bw() +
theme(axis.title.x = element_blank(),
#panel.border = element_rect(colour = "blank"),
panel.grid.major = element_line(colour="grey65"))
# adjust axes if required
if (!is.na(countmax)){
p.windrose <- p.windrose +
ylim(c(0,countmax))
}
# print the plot
print(p.windrose)
# return the handle to the wind rose
return(p.windrose)
}
# try the default settings
p1 <- plot.windrose(spd = spd,
dir = dir)
## Hadley broke my code
p2 <- plot.windrose(data=df, spd = spd,
dir = dir,
spdseq = c(0,3,6,12,20))
## Hadley broke my code
p_f1 <- p2 + facet_wrap(~df$hangcha, ncol=3)
p_f1
p_f2 <- p2 + facet_grid(df$Month~df$hangcha)
p_f2