合并两个时间序列答案

【问题标题】：Merge two time series合并两个时间序列
【发布时间】：2018-07-03 09:57:55
【问题描述】：

我试图弄清楚如何合并两个不同频率的时间序列。第一个时间序列间隔 1 分钟

 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

首选输出将结合 5 分钟间隔的两个时间序列，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

肯定有这个简单的功能，但我找不到它。

【问题讨论】：

标签： r time-series

【解决方案1】：

如果用于合并的列名称不同，则需要使用by.x（第一个表）和by.y（第二个表）指定它们。更多详情请查看?merge。

merge(data2, data,  by.x = "time2", by.y = "time1")

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

【讨论】：

【解决方案2】：

# 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)

您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)?

【讨论】：

【解决方案3】：

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")

【讨论】：