在R中构建气候数据

Question

我对编程非常陌生，最近开始尝试使用R进行数据分析。我目前正在尝试根据来自另一个列的值在我的df上生成一个新的列，并将每个列的总降雨量相加。我从PRISM气候组站点获得了我的气候数据，并添加了以下代码来将(1980-01)获取的日期字段分成年和月

climate <- tidyr::separate(climate,date, c("year", "month"), sep = "-") 

我的问题是，我如何开始添加一个新的列，以添加基于月份的文本？

我目前的伪代码方法是

if climate$month == 1,2,3 then climate$season == winter

else climate$month == 4,5,6 then climate$season == spring

else climate$month == 7,8,9 then climate$season == summer

else climate$month == 10,11,12 climate$season == fall

我的目标是用计算出的每年每个季节的降雨量总和生成一个新的df，同时避免使用Excel

谢谢你的建议！

已解决，以下是最终的工作输出，以供将来参考：

#Read in PRSIM data
prism <- read.csv('PRISM.csv')

#Seperate Date into Year - Month
prism <- tidyr::separate(prism,date, c("year", "month"), sep = "-")

#Convert factor variable into numeric
library(dplyr)
prism <- prism %>% mutate(month= as.numeric(as.character(month)))

#Generate new season column based on month
prism <- prism %>% mutate(season = case_when(
  month < 4 ~ "winter",
  month < 7 ~ "spring",
  month < 10 ~ "summer",
  month < 13 ~ "fall",
  TRUE ~ NA_character_
))

#Generate new data frame with Year and sum of each seasons value
clima <-  prism %>% 
          group_by(year, season) %>% 
          summarise(ppt_mm = sum(ppt_mm), tmin_c = sum(tmin_c), tmean_c = sum(tmean_c), tmax_c = sum(tmax_c), vdpmin_hpa = sum(vdpmin_hpa), vdpmax_hpa = sum(vdpmax_hpa))

#By Season
spring <- clima[clima$season=="spring", ]
summer <- clima[clima$season=="summer", ] 
fall <- clima[clima$season=="fall", ] 
winter <- clima[clima$season=="winter", ]

Answer 1

您可以使用dplyr::case_when。它比链式条件更好：

library(dplyr)

df %>% mutate(season = case_when(
  month < 3 ~ "winter",
  month < 7 ~ "spring",
  month < 10 ~ "summer",
  month < 13 ~ "fall",
  TRUE ~ NA_character_
))

month season
1      1 winter
2      2 winter
3      3 spring
4      4 spring
5      5 spring
6      6 spring
7      7 summer
8      8 summer
9      9 summer
10    10   fall
11    11   fall
12    12   fall
13    13   <NA>