使用 R 中的 dcast 重塑 EPA 风速和风向数据

Question

我正在尝试将长格式风数据转换为宽格式。 Parameter.Name 列中列出了风速和风向。这些值需要由 Local.Site.Name 和 Date.Local 变量转换。

如果每个唯一 Local.Site.Name + Date.Local 行有多个观察值，那么我需要这些观察值的平均值。内置参数 'fun.aggregate = mean' 适用于风速，但不能以这种方式计算平均风向，因为值以度为单位。例如，靠近北 (350, 10) 的两个风向的平均值将输出为南 (180)。例如：((350 + 10)/2 = 180)，尽管极平均值为 360 或 0。

'circular' 包将允许我们计算平均风向而无需执行任何三角函数，但我无法尝试将此附加函数嵌套在 'fun.aggregate' 参数中。我认为一个简单的 else if 语句就可以解决问题，但我运行遇到以下错误：

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

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

这是原始数据（>100MB）： https://drive.google.com/open?id=0By6o_bZ8CGwuUUhGdk9ONTgtT0E

这是数据的一个子集（前 100 行）： https://drive.google.com/open?id=0By6o_bZ8CGwucVZGT0pBQlFzT2M

这是我的脚本：

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)

如有任何帮助，我们将不胜感激！

-间隔火花

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

您在定义 wind.w 的代码中使用了 wind.w - 这是行不通的！

您还使用了斜引号 (`) 而不是直引号 (')。应该使用直引号来划定字符串。

Answer 2

您可以在 dcast 中使用子集来应用这两个函数并获得单独的数据帧然后合并它们

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 3

好的，感谢您的帮助，我设法解决了这个讨厌的风向问题。有时解决问题只是知道要问正确的问题。就我而言，学习术语 'vector-averaging' 就是我所需要的！ SDMTools 包中有一个名为 circular.averaging() 的 built-in vector-averaging 函数，它平均风向并产生仍在 0-359 度之间的输出！我最后做的是附加 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) 这是 raw and aggregated 数据的直方图！一切看起来都很好，谢谢大家！

使用 R 中的 dcast 重塑 EPA 风速和风向数据

Reshaping EPA wind speed & direction data with dcast in R

average

r

degrees

reshape2

dcast