对列中的特定值应用weighted.mean

Question

我有一个名为df的数据框架，有五列：

age <- c(10,11,12,12,10,11,11,12,10,11,12)
time <- c(20,26,41,60,29,28,54,24,59,70,25)
weight <- c(123,330,445,145,67,167,190,104,209,146,201)
gender <- c(1,1,2,2,2,2,1,2,2,2,1)
Q2 <- c(112,119,114,120,121,117,116,114,121,122,124)
df <- data_frame(age, w, time, gender, Q2)

我想要的是使用两个条件将基于每个年龄的weighted.mean应用于我的数据帧：1)gender = 2 and 2) Q2 >=114 & Q2 <= 121

通过下面的代码，我可以简单地应用weighted.mean，但我不知道如何使用我的两个条件。

df1<-
  df %>% 
  group_by(age) %>% 
  summarise(weighted_time = weighted.mean(time, weight))

Answer 1

下面是你要找的东西吗？

library(tidyverse)

age <- c(10,11,12,12,10,11,11,12,10,11,12)
time <- c(20,26,41,60,29,28,54,24,59,70,25)
weight <- c(123,330,445,145,67,167,190,104,209,146,201)
gender <- c(1,1,2,2,2,2,1,2,2,2,1)
Q2 <- c(112,119,114,120,121,117,116,114,121,122,124)
df <- data.frame(age, weight, time, gender, Q2)

df %>% 
  group_by(age) %>% 
  filter(gender == 2 & Q2 >=114 &  Q2 <= 121) %>% 
  summarise(weighted_time = weighted.mean(time, weight), .groups = "drop")

#> # A tibble: 3 × 2
#>     age weighted_time
#>   <dbl>         <dbl>
#> 1    10          51.7
#> 2    11          28  
#> 3    12          42.4

Answer 2

您可以为这2 (3)条件添加一个过滤器：

df %>% filter(gender == 2 & Q2 >= 114 & Q2 <= 121) %>% group_by(age) %>% summarise(weighted_time = weighted.mean(time, weight))

这给了我们

# A tibble: 3 x 2
    age weighted_time
  <dbl>         <dbl>
1    10          51.7
2    11          28  
3    12          42.4