我正在试图弄清楚如何合并两个不同频率的时间序列。第一个时间序列是1分钟间隔
time1<-seq(from=as.POSIXct("2010-03-01 13:02"),to=as.POSIXct("2010-03-01 13:10"),by="1 min")
value<-round(matrix(runif(90,1,10),9,10),2)
data<-data.frame(time1,value)
data
time1 X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
1 2010-03-01 13:02:00 2.03 9.06 6.93 8.78 1.62 6.79 7.30 8.58 7.17 5.71
2 2010-03-01 13:03:00 6.68 6.36 1.32 1.32 7.40 6.46 5.86 9.22 7.48 2.56
3 2010-03-01 13:04:00 2.68 1.26 7.54 9.32 2.20 5.83 2.58 2.33 9.13 6.77
4 2010-03-01 13:05:00 9.82 9.78 2.73 6.68 8.59 8.18 4.59 3.84 6.65 9.28
5 2010-03-01 13:06:00 9.47 5.97 5.18 7.32 2.66 2.62 9.14 2.81 1.60 3.29
6 2010-03-01 13:07:00 9.11 4.92 2.03 3.10 3.77 9.96 7.30 8.19 6.06 6.32
7 2010-03-01 13:08:00 4.46 1.42 9.97 8.96 7.16 2.21 1.72 9.08 3.45 6.27
8 2010-03-01 13:09:00 7.43 8.99 9.47 5.66 1.43 4.34 9.94 7.62 1.34 8.55
9 2010-03-01 13:10:00 6.10 2.09 6.47 3.83 7.05 9.65 4.84 1.34 6.14 6.63
第二个时间序列是间隔5分钟
time2<-seq(from=as.POSIXct("2010-03-01 13:00"),to=as.POSIXct("2010-03-01 13:10"),by="5 min")
value2<-round(matrix(runif(6,1,10),3,2),2)
data2<-data.frame(time2,value2)
data2
time2 X1 X2
1 2010-03-01 13:00:00 4.55 3.93
2 2010-03-01 13:05:00 4.05 8.04
3 2010-03-01 13:10:00 6.87 7.93
优先输出将在5分钟的间隔内组合两个时间序列，因此我将有一个新的数据框：
1 2010-03-01 13:05:00 4.05 8.04 9.82 9.78 2.73 6.68 8.59 8.18 4.59 3.84 6.65 9.28
2 2010-03-01 13:10:00 6.87 7.93 6.10 2.09 6.47 3.83 7.05 9.65 4.84 1.34 6.14 6.63
肯定有简单的功能，但我找不到它。
答案 0 :(得分：2)
如果用于合并的列具有不同的名称，则需要使用by.x（第一个表）和by.y（第二个表）指定它们。请查看?merge了解详情。
merge(data2, data, by.x = "time2", by.y = "time1")
<强>输出
time2 X1.x X2.x X1.y X2.y X3 X4 X5 X6 X7 X8 X9 X10
1 2010-03-01 13:05:00 1.53 8.01 9.17 7.18 2.91 5.34 4.70 7.59 5.67 5.31 9.03 7.81
2 2010-03-01 13:10:00 6.78 8.18 6.66 9.93 1.12 7.02 5.77 3.20 5.13 8.55 4.91 2.29
数据
set.seed(1)
time1<-seq(from=as.POSIXct("2010-03-01 13:02"),to=as.POSIXct("2010-03-01 13:10"),by="1 min")
value<-round(matrix(runif(90,1,10),9,10),2)
data<-data.frame(time1,value)
data
time1 X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
1 2010-03-01 13:02:00 3.39 1.56 4.42 4.44 8.15 8.10 1.64 3.99 4.12 7.41
2 2010-03-01 13:03:00 4.35 2.85 8.00 8.83 1.97 1.21 1.90 6.86 4.00 4.60
3 2010-03-01 13:04:00 6.16 2.59 9.41 4.06 7.51 5.30 3.85 3.32 5.29 3.93
4 2010-03-01 13:05:00 9.17 7.18 2.91 5.34 4.70 7.59 5.67 5.31 9.03 7.81
5 2010-03-01 13:06:00 2.82 4.46 6.87 6.40 8.39 7.23 6.96 7.90 8.78 2.82
6 2010-03-01 13:07:00 9.09 7.93 2.13 5.44 6.82 5.30 4.66 1.76 4.51 7.40
7 2010-03-01 13:08:00 9.50 5.48 3.40 2.68 8.05 8.75 9.22 8.88 8.00 2.10
8 2010-03-01 13:09:00 6.95 7.46 4.48 8.45 5.98 4.94 3.64 4.05 9.65 3.21
9 2010-03-01 13:10:00 6.66 9.93 1.12 7.02 5.77 3.20 5.13 8.55 4.91 2.29
time2<-seq(from=as.POSIXct("2010-03-01 13:00"),to=as.POSIXct("2010-03-01 13:10"),by="5 min")
value2<-round(matrix(runif(6,1,10),3,2),2)
data2<-data.frame(time2,value2)
data2
time2 X1 X2
1 2010-03-01 13:00:00 3.16 8.89
2 2010-03-01 13:05:00 1.53 8.01
3 2010-03-01 13:10:00 6.78 8.18
答案 1 :(得分：1)
# MERGE DATA SETS IF ELEMENTS ARE THE SAME IN COLUMN A
require(reshape2)
# Set WD
setwd("C:\\your_path_here\\")
# Load data from all CSV files
NumOne <- c("Book1.csv")
NumOneData <- as.matrix((read.csv(NumOne,header=T,sep=",",check.names = F)))
NumTwo = c("Book2.csv")
NumTwoData <- as.matrix((read.csv(NumTwo,header=T,sep=",",check.names = F)))
myfulldata1 = merge(NumOneData, NumTwoData)
write.table(myfulldata1, file = "C:\\your_path_here\\foo1.csv", sep = ",", col.names = NA, qmethod = "double")
NumOneData$CONTRIBUTING_GROUP <- match(NumOneData$CONTRIBUTING_GROUP, NumTwoData$CONTRIBUTING_GROUP, nomatch=0)
write.table(nomatch, file = "C:\\your_path_here\\foo2.csv", sep = ",", col.names = NA, qmethod = "double")
merged.data.all3 <- merge(NumOneData, NumTwoData, by="CONTRIBUTING_GROUP", all=TRUE)
write.table(merged.data.all3, file = "C:\\your_path_here\\foo3.csv", sep = ",", col.names = NA, qmethod = "double")
# mydata <- merge(df1, df2, by=c("country","year"))
# When common ids have different names use by.x and by.y to match them. R will keep the name of the first dataset (by.x)
# When different variables from two different dataset have the same name, R will assign a suffix .x or .y to make them unique and to identify which dataset they are coming from.
# mydata <- merge(mydata1, mydata2, by.x=c("country","year"), by.y=c("nations","time"))
# Note: The default setting of the merge() function drops all unmatched cases. If you want to keep all cases in the new data set, include the option all=TRUE in the merge() function:
# merged.data.all <- merge(dataset1, dataset2, by="countryID", all=TRUE)
你也应该将它们保存在安全的地方。
Inner join: merge(df1, df2) will work for these examples because R automatically joins the frames by common variable names, but you would most likely want to specify merge(df1, df2, by = "CustomerId") to make sure that you were matching on only the fields you desired. You can also use the by.x and by.y parameters if the matching variables have different names in the different data frames.
Outer join: merge(x = df1, y = df2, by = "CustomerId", all = TRUE)
Left outer: merge(x = df1, y = df2, by = "CustomerId", all.x = TRUE)
Right outer: merge(x = df1, y = df2, by = "CustomerId", all.y = TRUE)
Cross join: merge(x = df1, y = df2, by = NULL)
所有这些概念都来自这里。
How to join (merge) data frames (inner, outer, left, right)?
答案 2 :(得分：0)
一个简单的合并就可以了
time1<-seq(from=as.POSIXct("2010-03-01 13:02"),to=as.POSIXct("2010-03-01 13:10"),by="1 min")
value<-round(matrix(runif(90,1,10),9,10),2)
data<-data.frame(time=time1,value)
time2<-seq(from=as.POSIXct("2010-03-01 13:00"),to=as.POSIXct("2010-03-01 13:10"),by="5 min")
value2<-round(matrix(runif(6,1,10),3,2),2)
data2<-data.frame(time=time2,value2)
merge(data2,data,by="time")