合并R中的聚合数据 [英] Merging aggregate data in R

问题描述

关于将小时数据汇总成日常数据的上一个问题，我想继续（a）每月总计，（b）将每月汇总合并为原始数据框。

我的原始数据框如下所示：

 行<  - 日期，户外，室内
 01/01/2000 01：00,30,25 
 01 / 01/2000 02：00,31,26 
 01/01/2000 03：00,33,24 
 02/01/2000 01：00,29,25 
 02/01 / 2000 02：00,27,26 
 02/01/2000 03：00,39,24 
 12/01/2000 02：00,27,26 
 12/01/2000 03：00,39.24 
 12/31/2000 23：00,28,25
  

在我的上一个问题中回答了每日汇总，然后我可以找到我的方式来生成从那里的每月总数，到这样的事情：

 行s - 日期，月，OutdoorAVE 
 01/01/2000，Jan，31.33 
 02/01/2000，Feb，31.67 
 12/01/2000，Dec，31.33 
  

OutdoorAVE是每日最低和最高室外温度的平均值。我想要的结局是这样的：

 行<  - 日期，户外，室内， OutdoorAVE 
 01/01/2000 01：00,30,25，Jan，31.33 
 01/01/2000 02：00,31,26，Jan，31.33 
 01/01/2000 03：00,33,24，Jan，31.33 
 02/01/2000 01：00,29,25，Feb，31.67 
 02/01/2000 02：00,27,26，Feb， 31.67 
 02/01/2000 03：00,39,24，Feb，31.67 
 12/01/2000 02：00,27,26，Dec，31.33 
 12/01/2000 03：00,39,24，Dec，31.33 
 12/31/2000 23：00,28,25，Dec，31.33
  

我不知道如何做到这一点。非常感谢任何帮助。

解决方案

尝试 ave ，例如 POSIXlt 提取月份：

  zz<  -  textConnection（Lines）
数据<  -  read.table（zz，header = T，sep =，，stringsAsFactors = F）
 close（zz）
 
数据$ Month<  -  strftime （
 as.POSIXlt（Data $ Date，format =％m /％d /％Y％H：％M），
 format ='％b'）
数据$ outdoor_ave <  -  ave（Data $ Outdoor，Data $ Month，FUN = mean）
  

p>

 >数据
日期户外室内月户外_ave 
 1 01/01/2000 01:00 30 25 Jan 31.33333 
 2 01/01/2000 02:00 31 26 Jan 31.33333 
 3 01 / 01/2000 03:00 33 24 Jan 31.33333 
 4 02/01/2000 01:00 29 25 Feb 31.66667 
 5 02/01/2000 02:00 27 26 Feb 31.66667 
 6 02/01/2000 03:00 39 24 Feb 31.66667 
 7 12/01/2000 02:00 27 26 Dec 31.33333 
 8 12/01/2000 03:00 39 24 Dec 31.33333 
 9 12/31/2000 23:00 28 25 Dec 31.33333 
  

---

编辑：然后只是calcualte Month数据如上所示，并使用合并：

  zz<  -  textConnection（Lines2） ＃Lines2是汇总数据
 Data2<  -  read.table（zz，header = T，sep =，，stringsAsFactors = F）
 close（zz）
 
 >合并（数据，数据2 [-1]，全= T）
月日期户外室外AVE 
 1 Dec 12/01/2000 02:00 27 26 31.33 
 2 Dec 12/01 / 2000 03:00 39 24 31.33 
 3 Dec 12/31/2000 23:00 28 25 31.33 
 4 Feb 02/01/2000 01:00 29 25 31.67 
 5 Feb 02/01 / 2000 02:00 27 26 31.67 
 6 Feb 02/01/2000 03:00 39 24 31.67 
 7 Jan 01/01/2000 01:00 30 25 31.33 
 8 Jan 01 / 01/2000 02:00 31 26 31.33 
 9一月01/01/2000 03:00 33 24 31.33 
  

Following up my previous question about aggregating hourly data into daily data, I want to continue with (a) monthly aggregate and (b) merging the monthly aggregate into the original dataframe.

My original dataframe looks like this:

Lines <- "Date,Outdoor,Indoor
01/01/2000 01:00,30,25
01/01/2000 02:00,31,26
01/01/2000 03:00,33,24
02/01/2000 01:00,29,25
02/01/2000 02:00,27,26
02/01/2000 03:00,39,24
12/01/2000 02:00,27,26
12/01/2000 03:00,39,24
12/31/2000 23:00,28,25"

The daily aggregates have been answered in my previous question, and then I can find my way to produce the monthly aggregates from there, to something like this:

Lines <- "Date,Month,OutdoorAVE
01/01/2000,Jan,31.33
02/01/2000,Feb,31.67
12/01/2000,Dec,31.33"

Where the OutdoorAVE is the monthly average of the daily minimum and maximum outdoor temperature. What I want to have in the end is something like this:

Lines <- "Date,Outdoor,Indoor,Month,OutdoorAVE
01/01/2000 01:00,30,25,Jan,31.33
01/01/2000 02:00,31,26,Jan,31.33
01/01/2000 03:00,33,24,Jan,31.33
02/01/2000 01:00,29,25,Feb,31.67
02/01/2000 02:00,27,26,Feb,31.67
02/01/2000 03:00,39,24,Feb,31.67
12/01/2000 02:00,27,26,Dec,31.33
12/01/2000 03:00,39,24,Dec,31.33
12/31/2000 23:00,28,25,Dec,31.33"

I do not know enough R on how to do that. Any help is greatly appreciated.

解决方案

Try ave and eg POSIXlt to extract the month:

zz <- textConnection(Lines)
Data <- read.table(zz,header=T,sep=",",stringsAsFactors=F)
close(zz)

Data$Month <- strftime(
     as.POSIXlt(Data$Date,format="%m/%d/%Y %H:%M"),
     format='%b')
Data$outdoor_ave <- ave(Data$Outdoor,Data$Month,FUN=mean)

Gives :

> Data
              Date Outdoor Indoor Month outdoor_ave
1 01/01/2000 01:00      30     25   Jan    31.33333
2 01/01/2000 02:00      31     26   Jan    31.33333
3 01/01/2000 03:00      33     24   Jan    31.33333
4 02/01/2000 01:00      29     25   Feb    31.66667
5 02/01/2000 02:00      27     26   Feb    31.66667
6 02/01/2000 03:00      39     24   Feb    31.66667
7 12/01/2000 02:00      27     26   Dec    31.33333
8 12/01/2000 03:00      39     24   Dec    31.33333
9 12/31/2000 23:00      28     25   Dec    31.33333

---

Edit : Then just calcualte Month in Data as shown above and use merge :

zz <- textConnection(Lines2) # Lines2 is the aggregated data
Data2 <- read.table(zz,header=T,sep=",",stringsAsFactors=F)
close(zz)

> merge(Data,Data2[-1],all=T)
  Month             Date Outdoor Indoor OutdoorAVE
1   Dec 12/01/2000 02:00      27     26      31.33
2   Dec 12/01/2000 03:00      39     24      31.33
3   Dec 12/31/2000 23:00      28     25      31.33
4   Feb 02/01/2000 01:00      29     25      31.67
5   Feb 02/01/2000 02:00      27     26      31.67
6   Feb 02/01/2000 03:00      39     24      31.67
7   Jan 01/01/2000 01:00      30     25      31.33
8   Jan 01/01/2000 02:00      31     26      31.33
9   Jan 01/01/2000 03:00      33     24      31.33

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