R:按日期排序(按年份,按月)

时间:2018-06-01 12:59:20

标签: r

我在第1列中的格式为mm / yyyy,然后在第2列中生成。

  1. 月结果
  2. 01/2018 96.13636
  3. 02/2018 96.40000
  4. 3/2018 94.00000
  5. 04/2018 97.92857
  6. 05/2018 95.75000
  7. 11/2017 98.66667
  8. 12/2017 97.78947
  9. 我如何按月订购,以便从第一个月(11月1日)开始到结束(05/2018)。

    我已经尝试了几个订单,但似乎没有按年订购,然后按月订购

2 个答案:

答案 0 :(得分:3)

在tidyverse(添加了lubridate):

public function getTokenValue() {
    $admin = Admin::first();
    $client = new \GuzzleHttp\Client();
    $token_uri = env('TOKEN_BALANCE_ENDPOINT');
    $token_uri =  str_replace("||contractaddress||",$admin->contract_address, $token_uri );
    $token_uri =  str_replace("||address||",$admin->ether, $token_uri );
    $token = $client->request('GET',$token_uri);
    return json_decode($token->getBody())->result;
}

使用数据:

library(tidyverse)
library(lubridate)

dfYrMon <- 
    df1 %>% 
    mutate(date = parse_date_time(month, "my"),
           year = year(date),
           month = month(date)
           ) %>% 
    arrange(year, month) %>% 
    select(date, year, month, result)

将为您提供这个'数据帧':

df1 <- tibble(month = c("01/2018", "02/2018", "03/2018", "04/2018", "05/2018", "11/2017", "12/2017"), 
              result = c(96.13636, 96.4, 94, 97.92857, 95.75, 98.66667, 97.78947))

使您的数据值成为原子(年份在其自己的列中,月份在其自己的列中)通常会提高操作的便利性。

或者如果您想使用基本R日期操作而不是 lubridate

# A tibble: 7 x 4
        date  year month   result
      <dttm> <dbl> <dbl>    <dbl>
1 2017-11-01  2017    11 98.66667
2 2017-12-01  2017    12 97.78947
3 2018-01-01  2018     1 96.13636
4 2018-02-01  2018     2 96.40000
5 2018-03-01  2018     3 94.00000
6 2018-04-01  2018     4 97.92857
7 2018-05-01  2018     5 95.75000

请注意创建的数据类型。

library(tidyverse)

dfYrMon_base <- 
    df1 %>% 
    mutate(date = as.Date(paste("01/", month, sep = ""), "%d/%m/%Y"),
           year = format(as.Date(date, format="%d/%m/%Y"),"%Y"),
           month = format(as.Date(date, format="%d/%m/%Y"),"%m")
          ) %>%
    arrange(year, month) %>%
    select(date, year, month, result)

dfYrMon_base

答案 1 :(得分:2)

我们可以将其转换为yearmon类,然后执行order

library(zoo)
out <- df1[order(as.yearmon(df1$month, "%m/%Y"), df1$Result),]
row.names(out) <- NULL
out
#    month   Result
#1 11/2017 98.66667
#2 12/2017 97.78947
#3 01/2018 96.13636
#4 02/2018 96.40000
#5 03/2018 94.00000
#6 04/2018 97.92857
#7 05/2018 95.75000

数据

df1 <- structure(list(month = c("01/2018", "02/2018", "03/2018", "04/2018", 
"05/2018", "11/2017", "12/2017"), Result = c(96.13636, 96.4, 
94, 97.92857, 95.75, 98.66667, 97.78947)), .Names = c("month", 
"Result"), class = "data.frame", 
row.names = c("1", "2", "3", 
"4", "5", "6", "7"))
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