Question

我正在尝试执行以下操作，我的数据集看起来像这样，它包含POSIXct格式的日期，每小时风速和每小时风向（df称为wind_DNSeason）。我的目标是根据季节和日光的大小来获得风速的频率计数。

  date                     wspd_havg10m_kn avg_wdir
1 2013-12-06 00:25:00        9.835853       50
2 2013-12-06 01:25:00       10.506479       56
3 2013-12-06 02:25:00       11.847732       55
4 2013-12-06 03:25:00        8.494600       53
5 2013-12-06 04:25:00       13.188985       47
6 2013-12-06 05:25:00       13.188985       60

根据日期添加季节：

wind_DNSeason$season<-time2season(wind_DNSeason$date, out.fmt="seasons", type="default")

然后我使用openair包将数据切割成白天和夜晚：

wind_DNSeason$daylight <- cutData(wind, type = "daylight", local.hour.offset = -8, latitude = 54.312519, longitude = -130.305405, local.tz= "Canada/Pacific")

我知道函数聚合但我怀疑我是否正确使用它：

aggregate(wspd_havg10m_kn ~ season + daylight, wind_DNSeason, length)

这给了我发生的次数，但这不是我想要的。我试图一步到位吗？

我需要知道每个季节分组的白天和晚上发生的风速分组（见下文）。因为我想创建具有不同频率的条形图。 break = c（0,1,3,6,10,16,21,27,33,40,47）

我可以得到一些看起来像这样的东西，然后我可以轻松地计算出在条形图中绘制它的百分比：

  season  daylight            total_count  wspd<=1 wspd>1,<=3 wspd>3,<=6 etc

1 autumm  daylight             854            151      34         56   
2 spring  daylight            2580            456      56         98
3 summer  daylight            1722            34       344        09
4 winter  daylight             852            545      55         55
5 autumm nighttime            1030            55        6         777
6 spring nighttime            1825            89       89         344
7 summer nighttime             827            344      55         66
8 winter nighttime            1533            34       66         777

任何想法？感谢任何帮助！

我尝试使用dplyr并且我认为我非常接近，但不知何故它似乎没有正确地加上频率。这就是我应用建议代码的方式：

a<-wind_DNSeason %>% group_by(season,daylight) %>% 
  mutate(count=n(),"wspd<=1" = sum(wspd_havg10m_kn<=1),
     "wspd>1,<=3" = sum(wspd_havg10m_kn > 1 & wspd_havg10m_kn <= 3, na.rm=TRUE), 
     "wspd>3,<=6" = sum(wspd_havg10m_kn > 3 & wspd_havg10m_kn <= 6,na.rm=TRUE),
     "wspd>6,<=10" = sum(wspd_havg10m_kn > 6 & wspd_havg10m_kn <= 10,na.rm=TRUE),
     "wspd>10,<=16" = sum(wspd_havg10m_kn > 10 & wspd_havg10m_kn <= 16,na.rm=TRUE),
     "wspd>16,<=21" = sum(wspd_havg10m_kn > 16 & wspd_havg10m_kn <= 21,na.rm=TRUE),
     "wspd>21,<=27" = sum(wspd_havg10m_kn > 21 & wspd_havg10m_kn <= 27,na.rm=TRUE),
     "wspd>27,<=33" = sum(wspd_havg10m_kn > 27 & wspd_havg10m_kn <= 33,na.rm=TRUE),
     "wspd>33,<=40" = sum(wspd_havg10m_kn > 33 & wspd_havg10m_kn <= 40,na.rm=TRUE),
     "wspd>40,<=47" = sum(wspd_havg10m_kn > 33 & wspd_havg10m_kn <= 47,na.rm=TRUE))

输出看起来像这样，我选择了一些独特的行，因为它在整个df中复制它（例如冬天和夜晚）：

date    wspd_havg10m_kn avg_wdir    daylight    season  count   wspd<=1 wspd>1,<=3  wspd>3,<=6  wspd>6,<=10 wspd>10,<=16    wspd>16,<=21    wspd>21,<=27    wspd>27,<=33    wspd>33,<=40    wspd>40,<=47
1   2013-12-06 00:25:00 9.8358531   50  nighttime   winter  2751    NA  59  185 315 551 260 106 47  6   6
2   2013-12-06 12:25:00 7.3768898   57  daylight    winter  1449    NA  13  73  251 322 133 46  13  0   0

不同组的频率是否应该与总计数相加？总df包含13368个时间步长，如果我将每个组的频率相加，我只得到11165.没有比最大组更大的风速。我错过了什么？

Answer 1

这是一个dplyr解决方案：

library(dplyr)
wind_DNSeason %>% group_by(season,daylight) %>% 
    summarise(count=n(),"wspd<=1" = sum(wspd_havg10m_kn<=1),
           "wspd>1,<=3" = sum(wspd_havg10m_kn > 1 & wspd_havg10m_kn <= 3),
           "wspd>3,<=6" = sum(wspd_havg10m_kn > 3 & wspd_havg10m_kn <= 6)
    )

您可以根据需要添加任意数量的风力强度列，并填写名称和要求。

Answer 2

您在评论中提到plyr，因此您可以执行以下操作：

library("plyr")

ddply(wind_DNSeason, .(season, daylight), summarize, n = length(wspd_havg10m_kn),
     "wspd<=1" = sum(wspd_havg10m_kn <= 1))

此外，如果要自动创建这些计算值，您可以执行以下操作：

calc = function(x) {
   cuts = c(1, 3, 6, 10)
   res = data.frame(n = nrow(x))
   for(i in 1:(length(cuts) - 1)) {
       nm = sprintf("wspd>%d, <=%d", cuts[i], cuts[i + 1])
       val = sum(x$wspd_havg10m_kn > cuts[i] & x$wspd_havg10m_kn < cuts[i + 1], na.rm = T)
       res[, nm] = val
   }
   return(res)
}

ddply(wind_DNSeason, .(season, daylight), "calc")

根据列和组结果聚合df

2 个答案: