如何在R中找到固定日期范围内多年的平均值

Question

我的数据集有1967年至2022年一年中每天的河流流量测量值。我想找到从4月开始和结束的年度平均流量(例如，1967年4月至1969年4月、1968年4月-1969年4月份、1969年4月至1970年4月等的平均流量(。

以下是我的数据示例：

A tibble: 20,100 x 7
river year  season month   date       flow_rate quality
<chr> <fct> <fct>  <fct>   <date>         <dbl> <chr>  
1 wylye 1967  Winter January 1967-01-01      6.67 Good   
2 wylye 1967  Winter January 1967-01-02      6.39 Good   
3 wylye 1967  Winter January 1967-01-03      6.32 Good   
4 wylye 1967  Winter January 1967-01-04      6.34 Good   
5 wylye 1967  Winter January 1967-01-05      6.37 Good   
6 wylye 1967  Winter January 1967-01-06      6.45 Good   
7 wylye 1967  Winter January 1967-01-07      6.65 Good   
8 wylye 1967  Winter January 1967-01-08      6.54 Good   
9 wylye 1967  Winter January 1967-01-09      6.53 Good   
10 wylye 1967  Winter January 1967-01-10      6.62 Good   
# ... with 20,090 more rows

我看到过人们在同一年(7月至10月(的某些月份找到平均值的代码

例如

df %>%
mutate(date = as.Date(date), 
day = day(date), 
month = month(date), 
year = year(date)) %>%
filter(between(month, 7, 10) | 
day >= 7  & month == 6 | 
day <= 9 & month == 11) %>%
group_by(year) %>%
summarise(tmax = mean(tmax, na.rm = TRUE))

但不是一个允许我查看多年平均年周期的代码(1967-1968/1968-1969/1969-1970等(。如有任何帮助，我们将不胜感激：(

Answer 1

这里有一种使用lubridate的方法，通过改变年份来匹配您的间隔

df<-tibble::tribble(
~date, ~flow_rate,
"1967-01-01",      1,
"1967-04-01",      2,
"1968-01-01",      3,
"1968-04-01",      4      )
library(dplyr)
library(lubridate)

df_new<-df %>%
mutate(date=ymd(date),
year_shift=year(date-days(90)),
label=paste("April",year_shift,"-","March",year_shift+1)) %>%
group_by(label) %>%
summarize(flow_rate = mean(flow_rate)) %>%
ungroup() 
df_new
#> # A tibble: 3 × 2
#>   label                   flow_rate
#>   <chr>                       <dbl>
#> 1 April 1966 - March 1967       1  
#> 2 April 1967 - March 1968       2.5
#> 3 April 1968 - March 1969       4

^{创建于2022-01-25由reprex包(v2.0.1(}