将数据帧转换为 R 中的时间序列 [英] convert data frame to time series in R
问题描述
我有过去两年半的月度数据.我想将我的数据框转换为时间序列.所以我应该有
开始 :: 2015-01-01结束 :: 2017-06-01频率 : 1我试过了
ts (df [, -1], start = df [1, 1], end = df [29, 1])但我从中得到了真正的有线输出.
时间序列:开始 = 16436结束 = 17287频率 = 1日期流入1 2015-01-01 64342 2015-02-01 55953 2015-03-01 31014 2015-04-01 34755 2015-05-01 65196 2015-06-01 72517 2015-07-01 42008 2015-08-01 36229 2015-09-01 478210 2015-10-01 650311 2015-11-01 946012 2015-12-01 1562313 2016-01-01 1839314 2016-02-01 1441015 2016-03-01 1121016 2016-04-01 1058217 2016-05-01 1431618 2016-06-01 1187619 2016-07-01 1367620 2016-08-01 1246621 2016-09-01 1732622 2016-10-01 1584523 2016-11-01 1556924 2016-12-01 2493325 2017-01-01 3505026 2017-02-01 2600827 2017-03-01 2576728 2017-04-01 1785829 2017-05-01 21089输出(df)结构(列表(日期 = 结构(c(16436、16467、16495、16526，16556、16587、16617、16648、16679、16709、16740、16770、16801、16832, 16861, 16892, 16922, 16953, 16983, 17014, 17045, 17075,17106, 17136, 17167, 17198, 17226, 17257, 17287, 17318), class = "Date"),流入量 = c(6434L、5595L、3101L、3475L、6519L、7251L、4200L、3622L、4782L、6503L、9460L、15623L、18393L、14410L、11210L、10582L、14316L、11876L、13676L、12466L、17326L、15845L、15569L、24933L、35050L、26008L、25767L、17858L、21089L、13570L))，row.names = c(NA,-30L), class = "data.frame", .Names = c("date", "inflow"))非常感谢！
1) zoo 可能最简单的方法是将其转换为 "zoo" 类，然后从该类转换为"ts" 类."yearmon" 类是zoo 包中提供的一个类，用于表示月度数据，与ts 中的频率12 数据紧密对应.结果是一个 "ts" 类系列，其长度与 df 中的行数相同.
图书馆(动物园)as.ts(read.zoo(df, FUN = as.yearmon))## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec## 2015 6434 5595 3101 3475 6519 7251 4200 3622 4782 6503 9460 15623## 2016 18393 14410 11210 10582 14316 11876 13676 12466 17326 15845 15569 24933## 2017 35050 26008 25767 17858 21089 13570根据您想要做什么，您可能更愿意将其保留为 "zoo" 类时间序列，在这种情况下省略 as.ts .
1a) 使用动物园的另一种方法是:
ts(df$inflow, start = as.yearmon(df$date[1]), freq = 12)2) base 这是更长的但不使用任何包:
mo <- as.numeric(format(df$date[1], "%m"))yr <- as.numeric(format(df$date[1], "%Y"))ts(df$inflow, start = c(yr, mo), freq = 12)如果知道系列总是在一月份开始，那么我们可以省略mo的定义并写成:
ts(df$inflow, start = yr, freq = 12)注意:问题的输入df是:
df <-结构(列表(日期 = 结构(c(16436、16467、16495、16526，16556、16587、16617、16648、16679、16709、16740、16770、16801、16832, 16861, 16892, 16922, 16953, 16983, 17014, 17045, 17075,17106, 17136, 17167, 17198, 17226, 17257, 17287, 17318), class = "Date"),流入量 = c(6434L、5595L、3101L、3475L、6519L、7251L、4200L、3622L、4782L、6503L、9460L、15623L、18393L、14410L、11210L、10582L、14316L、11876L、13676L、12466L、17326L、15845L、15569L、24933L、35050L、26008L、25767L、17858L、21089L、13570L)), row.names =c(NA, 30L), class = "data.frame", .Names = c("date", "inflow"))I have monthly data fro last two and half year. I want to convert my data frame to time series. So that I should have
Start :: 2015-01-01
End :: 2017-06-01
Frequency : 1
I have tried
ts (df [, -1], start = df [1, 1], end = df [29, 1])
But I get this really wired output from this.
Time Series:
Start = 16436
End = 17287
Frequency = 1
date inflow
1 2015-01-01 6434
2 2015-02-01 5595
3 2015-03-01 3101
4 2015-04-01 3475
5 2015-05-01 6519
6 2015-06-01 7251
7 2015-07-01 4200
8 2015-08-01 3622
9 2015-09-01 4782
10 2015-10-01 6503
11 2015-11-01 9460
12 2015-12-01 15623
13 2016-01-01 18393
14 2016-02-01 14410
15 2016-03-01 11210
16 2016-04-01 10582
17 2016-05-01 14316
18 2016-06-01 11876
19 2016-07-01 13676
20 2016-08-01 12466
21 2016-09-01 17326
22 2016-10-01 15845
23 2016-11-01 15569
24 2016-12-01 24933
25 2017-01-01 35050
26 2017-02-01 26008
27 2017-03-01 25767
28 2017-04-01 17858
29 2017-05-01 21089
dput(df)
structure(list(date = structure(c(16436, 16467, 16495, 16526,
16556, 16587, 16617, 16648, 16679, 16709, 16740, 16770, 16801,
16832, 16861, 16892, 16922, 16953, 16983, 17014, 17045, 17075,
17106, 17136, 17167, 17198, 17226, 17257, 17287, 17318), class = "Date"),
inflow = c(6434L, 5595L, 3101L, 3475L, 6519L, 7251L, 4200L,
3622L, 4782L, 6503L, 9460L, 15623L, 18393L, 14410L, 11210L,
10582L, 14316L, 11876L, 13676L, 12466L, 17326L, 15845L, 15569L,
24933L, 35050L, 26008L, 25767L, 17858L, 21089L, 13570L)), row.names = c(NA,
-30L), class = "data.frame", .Names = c("date", "inflow"))
Many thanks in advance!!
1) zoo Probably the easiest is to convert it to "zoo" class and from that to "ts" class. "yearmon" class is a class provided in the zoo package for representing monthly data and closely corresponds to frequency 12 data in ts. The result is a "ts" class series having the same length as the number of rows in df.
library(zoo)
as.ts(read.zoo(df, FUN = as.yearmon))
## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
## 2015 6434 5595 3101 3475 6519 7251 4200 3622 4782 6503 9460 15623
## 2016 18393 14410 11210 10582 14316 11876 13676 12466 17326 15845 15569 24933
## 2017 35050 26008 25767 17858 21089 13570
Depending on what you want to do you may prefer to just leave it as a "zoo" class time series in which case omit the as.ts .
1a) An alternative way to use zoo would be:
ts(df$inflow, start = as.yearmon(df$date[1]), freq = 12)
2) base This is longer but does not use any packages:
mo <- as.numeric(format(df$date[1], "%m"))
yr <- as.numeric(format(df$date[1], "%Y"))
ts(df$inflow, start = c(yr, mo), freq = 12)
If it were known that the series always starts in January then we could omit the definition of mo and write:
ts(df$inflow, start = yr, freq = 12)
Note: The input df from the question is:
df <-
structure(list(date = structure(c(16436, 16467, 16495, 16526,
16556, 16587, 16617, 16648, 16679, 16709, 16740, 16770, 16801,
16832, 16861, 16892, 16922, 16953, 16983, 17014, 17045, 17075,
17106, 17136, 17167, 17198, 17226, 17257, 17287, 17318), class = "Date"),
inflow = c(6434L, 5595L, 3101L, 3475L, 6519L, 7251L, 4200L,
3622L, 4782L, 6503L, 9460L, 15623L, 18393L, 14410L, 11210L,
10582L, 14316L, 11876L, 13676L, 12466L, 17326L, 15845L, 15569L,
24933L, 35050L, 26008L, 25767L, 17858L, 21089L, 13570L)), row.names =
c(NA, 30L), class = "data.frame", .Names = c("date", "inflow"))
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