本文介绍了绘制作物日历的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一个csv文件( crop_calendar.csv
),其中包含有关特定区域中作物生长阶段的信息。基本上,每行都具有以下结构:
I have a csv file (crop_calendar.csv
) containing information on development stages of crop in a particular region. Basically each row has the following structure:
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,我想将该信息放置在如下所示的图形中:
Now, I'd like to put that information in a graphic that looks like that:
有人知道如何在很多地方(不同行)种植大量作物(行)吗?
Any idea how to do it with lots of crop (rows) and at different locations?
推荐答案
下面是一个示例,假设您具有播种的day.of.year()和每个周期三个时期的持续时间(以天为单位)作物和每个国家。
Here is an example assuming you have the day.of.year() of sowing and the duration (in days) of the three periods for each crop and each country.
#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))
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