ℕʘʘ*_*ḆḽḘ 11 r xts lubridate dplyr
请考虑以下示例
library(tidyverse)
library(lubridate)
time <- seq(from =ymd("2014-02-24"),to= ymd("2014-03-20"), by="days")
set.seed(123)
values <- sample(seq(from = 20, to = 50, by = 5), size = length(time), replace = TRUE)
df2 <- data_frame(time, values)
df2 <- df2 %>% mutate(day_of_week = wday(time, label = TRUE))
Source: local data frame [25 x 3]
time values day_of_week
<date> <dbl> <fctr>
1 2014-02-24 30 Mon
2 2014-02-25 45 Tues
3 2014-02-26 30 Wed
4 2014-02-27 50 Thurs
5 2014-02-28 50 Fri
6 2014-03-01 20 Sat
7 2014-03-02 35 Sun
8 2014-03-03 50 Mon
9 2014-03-04 35 Tues
10 2014-03-05 35 Wed
我希望按周汇总这个数据框.
也就是说,假设我将一周定义为从星期一早上开始到星期日晚上结束,我们将其称为Monday to Monday循环.(重要的是,我希望能够选择其他约定,例如周五到周五).
然后,我只想计算values每周的平均值.
例如,在上面的示例中,可以计算values2月24日星期一到3月2日星期日之间的平均值,依此类推.
我怎样才能做到这一点？
谢谢!
编辑:感谢所有提出想法的人.有点不寻常,我认为我的后期解决方案可能更合适.再次感谢!
ali*_*ire 23
在tidyverse,
df2 %>% group_by(week = week(time)) %>% summarise(value = mean(values))
## # A tibble: 5 × 2
## week value
## <dbl> <dbl>
## 1 8 37.50000
## 2 9 38.57143
## 3 10 38.57143
## 4 11 36.42857
## 5 12 45.00000
或者isoweek改为使用:
df2 %>% group_by(week = isoweek(time)) %>% summarise(value = mean(values))
## # A tibble: 4 × 2
## week value
## <int> <dbl>
## 1 9 37.14286
## 2 10 40.71429
## 3 11 35.00000
## 4 12 42.50000
或者cut.Date:
df2 %>% group_by(week = cut(time, "week")) %>% summarise(value = mean(values))
## # A tibble: 4 × 2
## week value
## <fctr> <dbl>
## 1 2014-02-24 37.14286
## 2 2014-03-03 40.71429
## 3 2014-03-10 35.00000
## 4 2014-03-17 42.50000
如果您愿意,可以告诉您在星期天开始:
df2 %>% group_by(week = cut(time, "week", start.on.monday = FALSE)) %>%
summarise(value = mean(values))
## # A tibble: 4 × 2
## week value
## <fctr> <dbl>
## 1 2014-02-23 37.50000
## 2 2014-03-02 40.00000
## 3 2014-03-09 33.57143
## 4 2014-03-16 44.00000
如果您想转到星期二开始,请在您的日期添加一个:
df2 %>% group_by(week = cut(time + 1, "week")) %>% summarise(value = mean(values))
## # A tibble: 4 × 2
## week value
## <fctr> <dbl>
## 1 2014-02-24 37.50000
## 2 2014-03-03 40.00000
## 3 2014-03-10 33.57143
## 4 2014-03-17 44.00000
不过,标签将会关闭.如果使用cut,请考虑其include.lowest和right参数的含义,记录在?cut.
为什么不直接使用floor_date和整数来调整一周的开始日期？
library(lubridate)
time <- seq(from =ymd("2014-02-24"),to= ymd("2014-03-20"), by="days")
set.seed(123)
values <- sample(seq(from = 20, to = 50, by = 5), size = length(time), replace = TRUE)
df2 <- data_frame(time, values)
df2 <- df2 %>% mutate(day_of_week = weekdays(time))
# week wednesday to tuesday
df2 %>% group_by(Week = floor_date(time-3, unit="week")) %>%
summarize(WeeklyAveDist=mean(values), mean(values), min_date = min(time), max_date = max(time)) %>% mutate(weekdays(min_date), weekdays(max_date)))
Week WeeklyAveDist mean.values. min_date max_date
1 2014-02-16 37.50000 37.50000 2014-02-24 2014-02-25
2 2014-02-23 38.57143 38.57143 2014-02-26 2014-03-04
3 2014-03-02 38.57143 38.57143 2014-03-05 2014-03-11
4 2014-03-09 36.42857 36.42857 2014-03-12 2014-03-18
5 2014-03-16 45.00000 45.00000 2014-03-19 2014-03-20
weekdays.min_date. weekdays.max_date.
1 Monday Tuesday
2 Wednesday Tuesday
3 Wednesday Tuesday
4 Wednesday Tuesday
5 Wednesday Thursday
# Week Thursday to Wednesday
df2 %>% group_by(Week = floor_date(time-4, unit="week")) %>%
summarize(WeeklyAveDist=mean(values), mean(values), min_date = min(time), max_date = max(time)) %>% mutate(weekdays(min_date), weekdays(max_date)))
Week WeeklyAveDist mean.values. min_date max_date
1 2014-02-16 35.00000 35.00000 2014-02-24 2014-02-26
2 2014-02-23 39.28571 39.28571 2014-02-27 2014-03-05
3 2014-03-02 37.14286 37.14286 2014-03-06 2014-03-12
4 2014-03-09 40.00000 40.00000 2014-03-13 2014-03-19
5 2014-03-16 40.00000 40.00000 2014-03-20 2014-03-20
weekdays.min_date. weekdays.max_date.
1 Monday Wednesday
2 Thursday Wednesday
3 Thursday Wednesday
4 Thursday Wednesday
5 Thursday Thursday
就这一次，经过一些研究，我实际上认为我想出了一个更好的解决方案
\n\n下面的示例是从星期四开始的几周。这些周将按照给定周期的第一天进行标记。
\n\nlibrary(tidyverse)\nlibrary(lubridate)\noptions(tibble.print_min = 30)\n\ntime <- seq(from =ymd("2014-02-24"),to= ymd("2014-03-20"), by="days")\nset.seed(123)\nvalues <- sample(seq(from = 20, to = 50, by = 5), size = length(time), replace = TRUE)\ndf2 <- data_frame(time, values)\n\ndf2 <- df2 %>% mutate(day_of_week_label = wday(time, label = TRUE),\n day_of_week = wday(time, label = FALSE))\n\ndf2 <- df2 %>% mutate(thursday_cycle = time - ((as.integer(day_of_week) - 5) %% 7),\n tmp_1 = (as.integer(day_of_week) - 5),\n tmp_2 = ((as.integer(day_of_week) - 5) %% 7))\n这使
\n\n> df2\n# A tibble: 25 \xc3\x97 7\n time values day_of_week_label day_of_week thursday_cycle tmp_1 tmp_2\n <date> <dbl> <ord> <dbl> <date> <dbl> <dbl>\n1 2014-02-24 30 Mon 2 2014-02-20 -3 4\n2 2014-02-25 45 Tues 3 2014-02-20 -2 5\n3 2014-02-26 30 Wed 4 2014-02-20 -1 6\n4 2014-02-27 50 Thurs 5 2014-02-27 0 0\n5 2014-02-28 50 Fri 6 2014-02-27 1 1\n6 2014-03-01 20 Sat 7 2014-02-27 2 2\n7 2014-03-02 35 Sun 1 2014-02-27 -4 3\n8 2014-03-03 50 Mon 2 2014-02-27 -3 4\n9 2014-03-04 35 Tues 3 2014-02-27 -2 5\n10 2014-03-05 35 Wed 4 2014-02-27 -1 6\n11 2014-03-06 50 Thurs 5 2014-03-06 0 0\n12 2014-03-07 35 Fri 6 2014-03-06 1 1\n13 2014-03-08 40 Sat 7 2014-03-06 2 2\n14 2014-03-09 40 Sun 1 2014-03-06 -4 3\n15 2014-03-10 20 Mon 2 2014-03-06 -3 4\n16 2014-03-11 50 Tues 3 2014-03-06 -2 5\n17 2014-03-12 25 Wed 4 2014-03-06 -1 6\n18 2014-03-13 20 Thurs 5 2014-03-13 0 0\n19 2014-03-14 30 Fri 6 2014-03-13 1 1\n20 2014-03-15 50 Sat 7 2014-03-13 2 2\n21 2014-03-16 50 Sun 1 2014-03-13 -4 3\n22 2014-03-17 40 Mon 2 2014-03-13 -3 4\n23 2014-03-18 40 Tues 3 2014-03-13 -2 5\n24 2014-03-19 50 Wed 4 2014-03-13 -1 6\n25 2014-03-20 40 Thurs 5 2014-03-20 0 0\n