用dcast在R中重塑EPA风速和风向数据

Question

我正在尝试将长格式的风数据转换为宽格式。风速和风向都列在Parameter.Name柱内。这些值需要同时由Local.Site.Name和Date.Local变量进行转换。

如果每个唯一的Local.Site.Name + Date.Local行有多个观测值，那么我想要这些观测值的平均值。内置的参数'fun.aggregate = mean‘对于风速来说工作得很好，但是平均风向不能这样计算，因为数值是以度为单位的。例如，北(350，10)附近两个风向的平均值将输出为南方(180)。例如：(350+ 10)/2 =180，尽管极地平均值是360或0。

“圆形”软件包将允许我们计算平均风向，而不必执行任何三角学，但我很难在“fun.aggregate”参数中嵌套这个附加函数。我认为简单的如果语句可以做到这一点的话，但是我遇到了以下错误：

Error in vaggregate(.value = value, .group = overall, .fun = fun.aggregate, : could not find function ".fun"
In addition: Warning messages:
1: In if (wind$Parameter.Name == "Wind Direction - Resultant") { :
    the condition has length > 1 and only the first element will be used
2: In if (wind$Parameter.Name == "Wind Speed - Resultant") { :
    the condition has length > 1 and only the first element will be used     
3: In mean.default(wind$"Wind Speed - Resultant") :
    argument is not numeric or logical: returning NA

我们的目标是能够将fun.aggregate = mean用于风速，而mean(circular(Wind Direction, units = 'degrees')用于风向。

以下是原始数据(>100‘s)：bZ8CGwuUUhGdk9ONTgtT0E

下面是数据的子集(第1 100行)：bZ8CGwucVZGT0pBQlFzT2M

这是我的剧本：

library(reshape2)
library(dplyr)
library(circular)

#read in the long format data:
wind <- read.csv("<INSERT_FILE_PATH_HERE>", header = TRUE)

#cast into wide format:
wind.w <- dcast(wind, 
            Local.Site.Name + Date.Local ~ Parameter.Name,
            value.var = "Arithmetic.Mean", 
            fun.aggregate = (
              if (wind$Parameter.Name == "Wind Direction - Resultant") {
                mean(circular(wind$"Wind Direction - Resultant", units = 'degrees'))
              }
              else if (wind$Parameter.Name == "Wind Speed - Resultant") {
                mean(wind$"Wind Speed - Resultant")
              }),
            na.rm = TRUE)

任何帮助都将不胜感激！

-spacedSparking

编辑:这是解决方案：

library(reshape2)
library(SDMTools)
library(dplyr)
#read in the EPA wind data:
#This data is publicly accessible, and can be found here: https://aqsdr1.epa.gov/aqsweb/aqstmp/airdata/download_files.html    
wind <- read.csv("daily_WIND_2016.csv", sep = ',', header = TRUE, stringsAsFactors = FALSE)

#convert long format wind speed data by date and site id:
wind_speed <- dcast(wind, 
                    Local.Site.Name + Date.Local ~ Parameter.Name,
                    value.var = "Arithmetic.Mean",
                    fun.aggregate = function(x) {
                      mean(x, na.rm=TRUE)
                    },
                    subset = .(Parameter.Name == "Wind Speed - Resultant")
)

#convert long format wind direction data into wide format by date and local site id:
wind_direction <- dcast(wind, 
                        Local.Site.Name + Date.Local ~ Parameter.Name,
                        value.var = "Arithmetic.Mean",
                        fun.aggregate = function(x) {
                          if(length(x) > 0) 
                            circular.averaging(x, deg = TRUE)
                          else
                            -1
                        },
                        subset= .(Parameter.Name == "Wind Direction - Resultant")
)

#join the wide format split wind_speed and wind_direction dataframes
wind.w <- merge(wind_speed, wind_direction)

Answer 1

您可以使用dcast中的子集来应用这两个函数，并将它们分开，然后合并它们。

library(reshape2)
library(dplyr)
library(circular)

#cast into wide format:
wind_speed <- dcast(wind, 
                Local.Site.Name + Date.Local ~ Parameter.Name,
                value.var = "Arithmetic.Mean",
                fun.aggregate = function(x) {
                  mean(x, na.rm=TRUE)
                },
                subset=.(Parameter.Name == "Wind Speed - Resultant")
)

wind_direction <- dcast(wind, 
                    Local.Site.Name + Date.Local ~ Parameter.Name,
                    value.var = "Arithmetic.Mean",
                    fun.aggregate = function(x) {
                      if(length(x) > 0) 
                        mean(circular(c(x), units="degrees"), na.rm=TRUE)
                      else
                        -1
                    },
                    subset=.(Parameter.Name == "Wind Direction - Resultant")
)


wind.w <- merge(wind_speed, wind_direction)

Answer 2

在定义wind.w的代码中使用wind.w --这是行不通的！

您还使用了角引号(`)而不是直引号(')。应使用直引号来描绘字符串。

Answer 3

好吧，感谢你的帮助，我设法解决了这个讨厌的风向问题。有时候，解决问题只是知道该问的问题。在我的例子中，学习“向量平均”这个术语是我所需要的！有一个名为circular.averaging()的内置矢量平均函数，它来自于SDMTools包，它平均风向，并产生一个仍然在0-359度之间的输出！我最后做的是附上tjjjohnson的脚本。我将fun.aggregate参数从mean(circular(c(x), units = "degrees"), na.rm = TRUE)更改为circular.averaging(x, deg = TRUE)，这里是原始和聚合数据的直方图！一切看起来都很好，谢谢大家！