根据“df1”的一个变量（“df1$var1”）在“df1”中创建一个变量，并根据“df1$var1”创建一个可更改的“df2”变量

我有数据框df1总结了一段时间内鱼的深度。df1$Site告诉你鱼所在的地点，df1$Ind告诉你个人和df1$Depth告诉您鱼在特定位置的深度df1$Datetime.

另一方面，我有df2总结了一段时间内（每三小时）从表面到 39 米深度、每隔 8 米的水流强度（m0-7, m8-15, m16-23, m24-31 and m32-39）。举个例子：

df1<-data.frame(Datetime=c("2016-08-01 15:34:07","2016-08-01 16:25:16","2016-08-01 17:29:16","2016-08-01 18:33:16","2016-08-01 20:54:16","2016-08-01 22:48:16"),Site=c("BD","HG","BD","BD","BD","BD"),Ind=c(16,17,19,16,17,16), Depth=c(5.3,24,36.4,42,NA,22.1))
df1$Datetime<-as.POSIXct(df1$Datetime, format="%Y-%m-%d %H:%M:%S",tz="UTC")


> df1
             Datetime Site Ind Depth
1 2016-08-01 15:34:07   BD  16   5.3
2 2016-08-01 16:25:16   HG  17  24.0
3 2016-08-01 17:29:16   BD  19  36.4
4 2016-08-01 18:33:16   BD  16  42.0
5 2016-08-01 20:54:16   BD  17    NA
6 2016-08-01 22:48:16   BD  16  22.1

df2<-data.frame(Datetime=c("2016-08-01 12:00:00","2016-08-01 15:00:00","2016-08-01 18:00:00","2016-08-01 21:00:00","2016-08-02 00:00:00"), Site=c("BD","BD","BD","BD","BD"),var1=c(2.75,4,6.75,2.25,4.3),var2=c(3,4,4.75,3,2.1),var3=c(2.75,4,5.75,2.25,1.4),var4=c(3.25,3,6.5,2.75,3.4),var5=c(3,4,4.75,3,1.7))
df2$Datetime<-as.POSIXct(df2$Datetime, format="%Y-%m-%d %H:%M:%S",tz="UTC")
colnames(df2)<-c("Datetime","Site","m0-7","m8-15","m16-23","m24-31","m32-39")

> df2
             Datetime Site m0-7 m8-15 m16-23 m24-31 m32-39
1 2016-08-01 12:00:00   BD 2.75  3.00   2.75   3.25   3.00
2 2016-08-01 15:00:00   BD 4.00  4.00   4.00   3.00   4.00
3 2016-08-01 18:00:00   BD 6.75  4.75   5.75   6.50   4.75
4 2016-08-01 21:00:00   BD 2.25  3.00   2.25   2.75   3.00
5 2016-08-02 00:00:00   BD 4.30  2.10   1.40   3.40   1.70

我想创建一个新专栏df1 called df1$Current.Int总结了鱼所在深度的当前强度，根据什么时间和地点df2说的是电流。

我想得到这个：

> df1
             Datetime Site Ind Depth Current.Int
1 2016-08-01 15:34:07   BD  16   5.3        4.00
2 2016-08-01 16:25:16   HG  17  24.0          NA # Currents of this site are not included in df2
3 2016-08-01 17:29:16   BD  19  36.4        4.75
4 2016-08-01 18:33:16   BD  16  42.0        4.75
5 2016-08-01 20:54:16   BD  17    NA          NA
6 2016-08-01 22:48:16   BD  16  22.1        1.40

只是指出，由于当前的记录是每三个小时一次，因此每小时显示一次df2$Datetime代表多一个半小时，少一个半小时。也就是说，中指出的电流强度df2 at 21:00:00反映了之间的电流19:30:00 and 22:30:00。其余时间也一样。

有谁知道该怎么做？

日期不匹配，因此针对示例进行了更改。通过这种方法，您可以准确检查比赛的进行情况并确保其符合您的要求。

df1<-data.frame(Datetime=c("2016-08-18 15:34:07","2016-08-18 16:25:16","2016-08-18 17:29:16","2016-08-18 18:33:16","2016-08-18 20:54:16","2016-08-18 22:48:16"),Site=c("BD","HG","BD","BD","BD","BD"),Ind=c(16,17,19,16,17,16), Depth=c(5.3,24,36.4,42,NA,22.1))
df1$Datetime<-as.POSIXct(df1$Datetime, format="%Y-%m-%d %H:%M:%S",tz="UTC")

df2<-data.frame(Datetime=c("2016-08-18 12:00:00","2016-08-18 15:00:00","2016-08-18 18:00:00","2016-08-18 21:00:00","2016-08-19 00:00:00"), Site=c("BD","BD","BD","BD","BD"),var1=c(2.75,4,6.75,2.25,4.3),var2=c(3,4,4.75,3,2.1),var3=c(2.75,4,5.75,2.25,1.4),var4=c(3.25,3,6.5,2.75,3.4),var5=c(3,4,4.75,3,1.7))
df2$Datetime<-as.POSIXct(df2$Datetime, format="%Y-%m-%d %H:%M:%S",tz="UTC")
colnames(df2)<-c("Datetime","Site","m0-7","m8-15","m16-23","m24-31","m32-39")

library(dplyr)
library(lubridate)

# Round the date and convert the depth to match the look-up. 
df1 = df1 %>% 
  mutate(
    Datetime_rounded = round_date(Datetime, "3 hour"),
    Depth_ind = ifelse(Depth < 8, "m0-7", 
                  ifelse(Depth > 7 & Depth < 16, "m8-15", 
                    ifelse(Depth > 15 & Depth < 24, "m16-23",
                      ifelse(Depth > 23 & Depth < 32, "m24-31",
                        ifelse(Depth > 31 & Depth < 40, "m32-39", NA)
                      )
                    )
                  )
                )
  )

# Wide to long on the intensity columns. 
df2 = df2 %>% 
  tidyr::gather("Depth_ind", "Intensity", 3:7)

# Join
df1 %>% 
  left_join(df2, by = c("Datetime_rounded" = "Datetime", 
                        "Site",
                        "Depth_ind"))

             Datetime Site Ind Depth    Datetime_rounded Depth_ind Intensity
1 2016-08-18 15:34:07   BD  16   5.3 2016-08-18 15:00:00      m0-7      4.00
2 2016-08-18 16:25:16   HG  17  24.0 2016-08-18 15:00:00    m24-31        NA
3 2016-08-18 17:29:16   BD  19  36.4 2016-08-18 18:00:00    m32-39      4.75
4 2016-08-18 18:33:16   BD  16  42.0 2016-08-18 18:00:00      <NA>        NA
5 2016-08-18 20:54:16   BD  17    NA 2016-08-18 21:00:00      <NA>        NA
6 2016-08-18 22:48:16   BD  16  22.1 2016-08-19 00:00:00    m16-23      1.40

# EDIT ----
## As per the request, the width of the final depth range can be adjusted as you wish, e.g. to a max depth of 60 m.

# Round the date and convert the depth to match the look-up. 
df1 = df1 %>% 
  mutate(
    Datetime_rounded = round_date(Datetime, "3 hour"),
    Depth_ind = ifelse(Depth < 8, "m0-7", 
                  ifelse(Depth > 7 & Depth < 16, "m8-15", 
                    ifelse(Depth > 15 & Depth < 24, "m16-23",
                      ifelse(Depth > 23 & Depth < 32, "m24-31",
                        ifelse(Depth > 31 & Depth < 60, "m32-39", NA)
                      )
                    )
                  )
                )
  )