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R:加权加总

aggregate r

Helen · 技术社区 · 6 年前

我在这张表上有一个数据集:

set.seed(4561)    # Make the results reproducible

df=data.frame(
colour=rep(c("green","red","blue"),each=3),
year=rep("2017",9),
month=rep(c(1,2,3),3),
price=c(200,254,188,450,434,490,100,99,97),
work=ceiling(runif(9,30,60)),
gain=ceiling(runif(9,1,10)),
work_weighed_price=NA,
gain_weighed_price=NA
)

对于每种颜色,年,月,我有一个价格(输出变量)和两个输入变量,称为收益和工作。实际上,我有更多的输入变量,但这足以表明我想用我的数据帧做什么。

> df
  colour year month price work gain work_weighed_price gain_weighed_price
1  green 2017     1   200   33    9                 NA                 NA
2  green 2017     2   254   56    5                 NA                 NA
3  green 2017     3   188   42    8                 NA                 NA
4    red 2017     1   450   39    3                 NA                 NA
5    red 2017     2   434   45    2                 NA                 NA
6    red 2017     3   490   36    8                 NA                 NA
7   blue 2017     1   100   50    8                 NA                 NA
8   blue 2017     2    99   45    8                 NA                 NA
9   blue 2017     3    97   56    4                 NA                 NA

我想计算加权增益和功(以及加权价格),其中权重是该月和该年的价格除以各颜色的价格之和:

 desired_output=data.frame(
  year=rep("2017",3),
  month=rep(c(1,2,3),1),
  price=c(200*(200/(200+450+100))+450*(450/(200+450+100))+100*(100/(200+450+100)),
          254*(254/(254+434+99))+434*(434/(254+434+99))+99*(99/(254+434+99)),
          188*(188/(188+490+97))+490*(490/(188+490+97))+97*(97/(188+490+97))),
  work_weighed_price=c(47*(200/(200+450+100))+44*(450/(200+450+100))+52*(100/(200+450+100)),
                       44*(254/(254+434+99))+42*(434/(254+434+99))+32*(99/(254+434+99)),
                       38*(188/(188+490+97))+52*(490/(188+490+97))+52*(97/(188+490+97))) ,                                      
  gain_weighed_price=c(5*(200/(200+450+100))+8*(450/(200+450+100))+10*(100/(200+450+100)),
                       3*(254/(254+434+99))+7*(434/(254+434+99))+9*(99/(254+434+99)),
                       2*(188/(188+490+97))+4*(490/(188+490+97))+9*(97/(188+490+97)))
)

> desired_output
  year month    price work_weighed_price gain_weighed_price
1 2017     1 336.6667           45.86667           7.466667
2 2017     2 333.7649           41.38755           5.960610
3 2017     3 367.5523           48.60387           4.140645

我该如何在R中攻击它?

3 回复 | 直到 6 年前

IceCreamToucan 6 年前

你可以使用 weighted.mean 功能

df %>% 
  group_by(year, month) %>% 
  summarise_at(vars(price, work, gain), 
               funs(price_weighted = weighted.mean(., price)))
# # A tibble: 3 x 5
# # Groups:   year [?]
#    year month price_price_weighted work_price_weighted gain_price_weighted
#    <int> <int>                <dbl>               <dbl>               <dbl>
# 1  2017     1                  337                45.9                7.47
# 2  2017     2                  334                41.4                5.96
# 3  2017     3                  368                48.6                4.14

或者,在 data.table

library(data.table)
setDT(df)

df[, lapply(.SD, weighted.mean, price)
   , .SDcols = c('price', 'work', 'gain')
   , by = .(year, month)]

#    year month    price     work     gain
# 1: 2017     1 336.6667 45.86667 7.466667
# 2: 2017     2 333.7649 41.38755 5.960610
# 3: 2017     3 367.5523 48.60387 4.140645

Weihuang Wong 6 年前

使用 dplyr . 你的使用 runif 在你的例子中 df 如果没有设定种子,而且它与您想要的输出不一致,就会造成一些混乱。在下面的代码中,我使用 东风 这和你想要的结果是一致的。

library(dplyr)
df %>%
  group_by(year, month) %>%
  mutate(weight = price / sum(price)) %>%
  mutate_at(vars(price, work, gain), funs(weighed_price = . * weight)) %>%
  summarise_at(vars(ends_with("weighed_price")), sum)
# # A tibble: 3 x 5
# # Groups:   year [?]
#    year month work_weighed_price gain_weighed_price price_weighed_price
#   <int> <int>              <dbl>              <dbl>               <dbl>
# 1  2017     1               45.9               7.47                337.
# 2  2017     2               41.4               5.96                334.
# 3  2017     3               48.6               4.14                368.

东风 :

structure(list(colour = c("green", "green", "green", "red", "red", 
"red", "blue", "blue", "blue"), year = c(2017L, 2017L, 2017L, 
2017L, 2017L, 2017L, 2017L, 2017L, 2017L), month = c(1L, 2L, 
3L, 1L, 2L, 3L, 1L, 2L, 3L), price = c(200L, 254L, 188L, 450L, 
434L, 490L, 100L, 99L, 97L), work = c(47L, 44L, 38L, 44L, 42L, 
52L, 52L, 32L, 52L), gain = c(5L, 3L, 2L, 8L, 7L, 4L, 10L, 9L, 
9L), work_weighed_price = c(NA, NA, NA, NA, NA, NA, NA, NA, NA
), gain_weighed_price = c(NA, NA, NA, NA, NA, NA, NA, NA, NA)), .Names = c("colour", 
"year", "month", "price", "work", "gain", "work_weighed_price", 
"gain_weighed_price"), class = "data.frame", row.names = c(NA, 
-9L))

Rui Barradas 6 年前

碱基R溶液可以是 tapply 说明。

fun_price <- function(x){
    s <- sum(x)
    sum(x*(x/s))
}

fun_weighted <- function(x, w){
    s <- sum(w)
    sum(x*(w/s))
}

desired <- data.frame(year = unique(df$year), month = sort(unique(df$month)))

desired$price <- with(df, tapply(price, month, FUN = fun_price))
desired$work_weighed_price <- with(df, tapply(work, month, FUN = fun_weighted, w = price))
desired$gain_weighed_price <- with(df, tapply(gain, month, FUN = fun_weighted, w = price))

desired
#  year month    price work_weighed_price gain_weighed_price
#1 2017     1 336.6667           40.74092           6.622405
#2 2017     2 333.7649           48.56834           4.984429
#3 2017     3 367.5523           44.65052           6.659170