我正在尝试将每日天气信息添加到R上的数据框,因此df1 + df2 = df3是客观的。我认为在df1上按日期对df2进行分段,将df2和rbind.fill折叠为df1将会是这样,但我遇到了麻烦。
date2 <- c('2014-06-03','2017-05-20')
date <- c('2014-06-01','2017-05-15')
df1 <- data.frame(date,date2)
date
#> df1
# date date2
#1 2014-06-01 2014-06-03
#2 2017-05-15 2017-05-20
date3 <- c('2014-06-01','2014-06-02','2014-06-03','2017-05-15','2017-05-16','2017-05-17','2017-05-18','2017-05-19','2017-05-20')
rain <- c(3, 4, 3, 5, 5, 6, 7, 6 ,6)
sun <- c ( 10,10,10, 15,15,15,16,15,15)
df2 <- data.frame(date3,rain,sun)
#> df2
# date3 rain sun
#1 2014-06-01 3 10
#2 2014-06-02 4 10
#3 2014-06-03 3 10
#4 2017-05-15 5 15
#5 2017-05-16 5 15
#6 2017-05-17 6 15
#7 2017-05-18 7 16
#8 2017-05-19 6 15
#9 2017-05-20 6 15
rain_day1 <- c(3,5)
rain_day2 <- c(4,5)
rain_day3 <- c(3,6)
rain_day4 <- c(NA,7)
rain_day5 <- c(NA,6)
rain_day6 <- c(NA,6)
sun_day1 <- c(10,15)
sun_day2 <- c(10,15)
sun_day3 <- c(10,15)
sun_day4 <- c(NA,15)
sun_day5 <- c(NA,16)
sun_day6 <- c(NA,15)
date5 <- c('2014-06-03','2017-05-20')
date4 <- c('2014-06-01','2017-05-15')
df3 <- data.frame(date4,date5,rain_day1,sun_day1,rain_day2,sun_day2,rain_day3,sun_day3,rain_day4,sun_day4,rain_day5,sun_day5,rain_day6,sun_day6)
#> df3
# date4 date5 rain_day1 sun_day1 rain_day2 sun_day2 rain_day3 sun_day3 rain_day4 sun_day4
#1 2014-06-01 2014-06-03 3 10 4 10 3 10 NA NA
#2 2017-05-15 2017-05-20 5 15 5 15 6 15 7 15
# rain_day5 sun_day5 rain_day6 sun_day6
#1 NA NA NA NA
#2 6 16 6 15
任何帮助将不胜感激。提前致谢
答案 0 :(得分:0)
试试这个。我欢迎任何改进我的管道散文,我正在努力。
library(magrittr)
df1$date <- as.Date(df1$date)
df1$date2 <- as.Date(df1$date2)
df2$date3 <- as.Date(df2$date3)
df2 %<>% setNames(c("date3","rain_day","sun_day"))
row_list <- df1 %>% apply(1,function(x){ df2 %>%
subset(date3 >= x["date"] & date3 <= x["date2"]) %>% # subsetting
"["(2:3) %>% # selecting relevant column
unlist}) %>% # spearding all data into a vector
sapply(.,function(x){x[rep(c(0,length(x)/2),length(x)/2)+rep(1:(length(x)/2),each=2)]}) # reordering
row_names <- row_list %>% sapply(length) %>% which.max %>% "[["(row_list,.) %>% names() # taking the names from longest list
row_list %>% sapply(function(x){c(x,rep(NA,max(sapply(.,length))-length(x)))}) %>% # complete with NAs
t %>% as.data.frame %>% setNames(row_names) %>% cbind(df1,.) # transpose, convert, set names and append to df1
# date date2 rain_day1 sun_day1 rain_day2 sun_day2 rain_day3 sun_day3 rain_day4 sun_day4 rain_day5 sun_day5 rain_day6 sun_day6
# 1 2014-06-01 2014-06-03 3 10 4 10 3 10 NA NA NA NA NA NA
# 2 2017-05-15 2017-05-20 5 15 5 15 6 15 7 16 6 15 6 15
答案 1 :(得分:0)
&#34;我认为在df1上按日期对df2进行分段,将df2和rbind.fill折叠为df1将是方式&#34; ....它花费的时间比想要的长,但我做到了!
lapply(df1, class)
df1$date <- sapply( df1$date , function(x) as.character(x) )
df1$date2 <- sapply( df1$date2 , function(x) as.character(x) )
lapply(df2, class)
df2$date3 <- sapply( df2$date3 , function(x) as.character(x) )
lapply(df3, class)
df3$date4 <- sapply( df3$date4 , function(x) as.character(x) )
df3$date5 <- sapply( df3$date5 , function(x) as.character(x) )
tryCatch(library("plyr") ,
error = function(e) {
install.packages("plyr")
library("plyr")
}
)
df4 <- df1
for (i in 1:nrow(df1)){
dff <- df2[ which( df2$date3 <= df1$date2[i] ) , ]
dff <- dff[ which( dff$date3 >= df1$date[i] ) , ]
dff <- as.data.frame(t(unlist(dff)))
colnames(dff)[1] <- "date"
df5 <- merge(x = df1, y = dff, by = "date")
df5 <- rbind.fill(df4,df5)
df5<-df5[-1,]
df4 <- df5
}
df5 <- df5[, -grep("^date3", colnames(df5))]