我有一個隨機的、有時是不常見的事件的資料集，我想把它們算作每周的總和。由于隨機性，它們不是線性的，所以到目前為止我嘗試過的其他示例不適用。
資料與此類似：
df_date <- data.frame( Name = c("Jim","Jim","Jim","Jim","Jim","Jim","Jim","Jim","Jim","Jim",
"Sue","Sue","Sue","Sue","Sue","Sue","Sue","Sue","Sue","Sue"),
Dates = c("2010-1-1", "2010-1-2", "2010-01-5","2010-01-17","2010-01-20",
"2010-01-29","2010-02-6","2010-02-9","2010-02-16","2010-02-28",
"2010-1-1", "2010-1-2", "2010-01-5","2010-01-17","2010-01-20",
"2010-01-29","2010-02-6","2010-02-9","2010-02-16","2010-02-28"),
Event = c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1) )
我要做的是創建一個新表，其中包含日歷年每周事件的總和。
在這種情況下產生這樣的東西：
Name Week Events
Jim 1 3
Sue 1 3
Jim 2 0
Sue x ... x
and so on...
uj5u.com熱心網友回復：
更新多年的 OP 請求：
我們也可以使用isoweekfromlubridate而不是week
或者：
我們可以按如下方式添加年份：
df_date %>%
as_tibble() %>%
mutate(Week = week(ymd(Dates))) %>%
mutate(Year = year(ymd(Dates))) %>%
count(Name, Year, Week)
在使用s函式將字符轉換為日期格式后，我們可以使用lubridates函式。然后我們可以使用which 的縮寫
：WeekDateslubridateymdcount group_by(Name, Week) %>% summarise(Count = n())
library(dplyr)
library(lubridate)
df_date %>%
as_tibble() %>%
mutate(Week = week(ymd(Dates))) %>%
count(Name, Week)
Name Week n
<chr> <dbl> <int>
1 Jim 1 3
2 Jim 3 2
3 Jim 5 1
4 Jim 6 2
5 Jim 7 1
6 Jim 9 1
7 Sue 1 3
8 Sue 3 2
9 Sue 5 1
10 Sue 6 2
11 Sue 7 1
12 Sue 9 1
uj5u.com熱心網友回復：
這是一種方法，可讓您在每個 ISO 周為每個人獲取，當該周沒有針對該人的事件時為零：
get_dates_df <- function(d) {
data.frame(date = seq(min(d, na.rm=T),max(d,na.rm=T),1)) %>%
mutate(Year=year(date), Week=week(date)) %>%
distinct(Year, Week)
}
df_date = df_date %>% mutate(Dates=lubridate::ymd(Dates))
left_join(
full_join(distinct(df_date %>% select(Name)), get_dates_df(df_date$Dates), by=character()),
df_date %>%
group_by(Name,Year=year(Dates), Week=week(Dates)) %>%
summarize(Events = sum(Event), .groups="drop")
) %>%
mutate(Events=if_else(is.na(Events),0,Events))
輸出：
Name Year Week Events
1 Jim 2010 1 3
2 Jim 2010 2 0
3 Jim 2010 3 2
4 Jim 2010 4 0
5 Jim 2010 5 1
6 Jim 2010 6 2
7 Jim 2010 7 1
8 Jim 2010 8 0
9 Jim 2010 9 1
10 Sue 2010 1 3
11 Sue 2010 2 0
12 Sue 2010 3 2
13 Sue 2010 4 0
14 Sue 2010 5 1
15 Sue 2010 6 2
16 Sue 2010 7 1
17 Sue 2010 8 0
18 Sue 2010 9 1
轉載請註明出處，本文鏈接：https://www.uj5u.com/qukuanlian/470826.html
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