绘制作物日历

时间:2013-07-23 09:50:01

标签: r calendar plot ggplot2

我有一个csv文件(crop_calendar.csv),其中包含特定地区作物发育阶段的信息。基本上每行都有以下结构:

crop_name   sowing_dat    emergence_date  flowering_date  maturity_date  harvest_date

例如:

Winter_wheat    18.08   28.08   24.06   30.07   3.08
Winter_rye      18.08   28.08   15.06   23.07   29.07
Spring_wheat    27.04   10.05   1.07    4.08    7.08
Spring_barley   27.04   12.05   27.06   1.08    5.08

现在,我想将这些信息放在一个看起来像这样的图形中: crop calendar example

知道如何使用大量裁剪(行)和不同位置吗?

4 个答案:

答案 0 :(得分:5)

这是一个例子,假设你有播种的day.of.year()和每个作物和每个国家的三个时期的持续时间(以天为单位)。

The crop calendar

#making random numbers reproducible
set.seed(12345)
rawdata <- expand.grid(
  Crop = paste("Crop", LETTERS[1:8]), 
  Country = paste("Country", letters[10:13])
)
#day.of.year of sowing
rawdata$Sowing <- runif(nrow(rawdata), min = 0, max = 365)
#number of days until mid season
rawdata$Midseason <- runif(nrow(rawdata), min = 10, max = 30)
#number of days until harvest
rawdata$Harvest <- runif(nrow(rawdata), min = 20, max = 150)
#number of days until end of harvest
rawdata$Harvest.end <- runif(nrow(rawdata), min = 10, max = 40)

dataset <- data.frame(Crop = character(0), Country = character(0), Period = character(0), Duration = numeric(0))

#sowing around new year
last.day <- rowSums(rawdata[, c("Sowing", "Midseason")])
if(any(last.day >= 365)){
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Sowing",
      Duration = last.day[last.day >= 365] - 365
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Mid-season",
      Duration = rawdata$Harvest[last.day >= 365]
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Harvest",
      Duration = rawdata$Harvest.end[last.day >= 365]
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = NA,
      Duration = 365 - rowSums(rawdata[last.day >= 365, c("Midseason", "Harvest", "Harvest.end")])
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Sowing",
      Duration = 365 - rawdata$Sowing[last.day >= 365]
    )
  )
  rawdata <- rawdata[last.day < 365, ]
}

#mid-season around new year
last.day <- rowSums(rawdata[, c("Sowing", "Midseason", "Harvest")])
if(any(last.day >= 365)){
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Mid-season",
      Duration = last.day[last.day >= 365] - 365
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Harvest",
      Duration = rawdata$Harvest.end[last.day >= 365]
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = NA,
      Duration = 365 - rowSums(rawdata[last.day >= 365, c("Midseason", "Harvest", "Harvest.end")])
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Sowing",
      Duration = rawdata$Midseason[last.day >= 365]
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Mid-season",
      Duration = 365 - rowSums(rawdata[last.day >= 365, c("Sowing", "Midseason")])
    )
  )
  rawdata <- rawdata[last.day < 365, ]
}


#harvest around new year
last.day <- rowSums(rawdata[, c("Sowing", "Midseason", "Harvest", "Harvest.end")])
if(any(last.day >= 365)){
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Harvest",
      Duration = last.day[last.day >= 365] - 365
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = NA,
      Duration = 365 - rowSums(rawdata[last.day >= 365, c("Midseason", "Harvest", "Harvest.end")])
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Sowing",
      Duration = rawdata$Midseason[last.day >= 365]
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Mid-season",
      Duration = rawdata$Harvest[last.day >= 365]
    )
  )
  dataset <- rbind(
    dataset,
    cbind(
      rawdata[last.day >= 365, c("Crop", "Country")],
      Period = "Harvest",
      Duration = 365 - rowSums(rawdata[last.day >= 365, c("Sowing", "Midseason", "Harvest")])
    )
  )
  rawdata <- rawdata[last.day < 365, ]
}


#no crop around new year
dataset <- rbind(
  dataset,
  cbind(
    rawdata[, c("Crop", "Country")],
    Period = NA,
    Duration = rawdata$Sowing
  )
)
dataset <- rbind(
  dataset,
  cbind(
    rawdata[, c("Crop", "Country")],
    Period = "Sowing",
    Duration = rawdata$Midseason
  )
)
dataset <- rbind(
  dataset,
  cbind(
    rawdata[, c("Crop", "Country")],
    Period = "Mid-season",
    Duration = rawdata$Harvest
  )
)
dataset <- rbind(
  dataset,
  cbind(
    rawdata[, c("Crop", "Country")],
    Period = "Harvest",
    Duration = rawdata$Harvest.end
  )
)
dataset <- rbind(
  dataset,
  cbind(
    rawdata[, c("Crop", "Country")],
    Period = NA,
    Duration = 365 - rowSums(rawdata[, c("Sowing", "Midseason", "Harvest")])
  )
)

Labels <- c("", "Jan.", "Feb.", "Mar.", "Apr.", "May", "Jun.", "Jul.", "Aug.", "Sep.", "Okt.", "Nov.", "Dec.")
Breaks <- cumsum(c(0, 31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31))
ggplot(dataset, aes(x = Crop, y = Duration, colour = Period, fill = Period)) + geom_bar(stat = "identity") + facet_wrap(~Country) + coord_flip() + scale_fill_manual(values = c("Sowing" = "darkgreen", "Mid-season" = "grey", "Harvest" = "yellow")) + scale_colour_manual(values = c("Sowing" = "black", "Mid-season" = "black", "Harvest" = "black"), guide = "none") + scale_y_continuous("", breaks = Breaks, labels = Labels, limits = c(0, 365)) + theme_bw() + theme(axis.text.x = element_text(hjust = 1))

答案 1 :(得分:2)

要在每个"color=.."的{​​{1}}来电中添加图例广告aes(),然后使用参数geom_linerange()添加scale_color_identity() - 这将使用颜色名称作为实际颜色。使用guide="legend",您可以更改图例中的标签。要删除月份之间的行,请在labels=内添加minor_breaks=NULL

scale_y_date()

enter image description here

答案 2 :(得分:1)

猜测你想做什么有点困难。只有3个日期,您无法重现您显示的图表(每个作物需要4个日期)。目前还不清楚这些数字代表什么(大概是几周?)。如果这只是一个关于绘图的问题,这将让你开始。否则,请澄清问题。

df <- read.table(text="crop_name   emergence_date  maturity_date  harvest_date
                 wheat        13.04           25.05          30.06
                 corn         12.02           21.30          23.11", header=TRUE)
require(ggplot2)
ggplot(df, aes(x=crop_name)) +
  geom_linerange(aes(ymin=emergence_date, ymax=maturity_date), color="green3", size=5) +
  geom_linerange(aes(ymin=maturity_date, ymax=harvest_date), color="yellow", size=5) +
  coord_flip() + ylim(0, 52)

答案 3 :(得分:1)

好的编译答案和其他研究,这是我最终得到的解决方案:

inDf <- read.table(text="crop     sowing  emergence  flowering   maturity harvesting
                         Spring barley 27/04/2013 12/05/2013 27/06/2013  1/08/2013  5/08/2013
                         Oats 27/04/2013 10/05/2013 29/06/2013  6/08/2013  8/08/2013
                         Maize 25/05/2013  6/06/2013 18/08/2013 10/09/2013 12/09/2013", header=TRUE)

inDf[, "sowing"]     <- as.Date(inDf[, "sowing"], format = '%d/%m/%Y')
inDf[, "emergence"]  <- as.Date(inDf[, "emergence"], format = '%d/%m/%Y')
inDf[, "flowering"]  <- as.Date(inDf[, "flowering"], format = '%d/%m/%Y')
inDf[, "maturity"]   <- as.Date(inDf[, "maturity"], format = '%d/%m/%Y')
inDf[, "harvesting"] <- as.Date(inDf[, "harvesting"], format = '%d/%m/%Y')

ggplot(inDf, aes(x=crop)) +
geom_linerange(aes(ymin=sowing, ymax=emergence), color="green", size=5) +
geom_linerange(aes(ymin=emergence, ymax=flowering), color="green3", size=5) +
geom_linerange(aes(ymin=flowering, ymax=maturity), color="yellow", size=5) +
geom_linerange(aes(ymin=maturity, ymax=harvesting), color="red", size=5) +
coord_flip() +  scale_y_date(lim = c(as.Date("2012-08-15"), as.Date("2013-09-01")),breaks=date_breaks(width = "1 month"), labels = date_format("%b"))+
ggtitle('Crop Calendar')+ xlab("")+ylab("")

给出: enter image description here

BUT

我现在要添加图例并删除每个月之间的所有白线。有任何想法吗?感谢