Question

我想在每个组（年）中重复该值，该值等于第一类“ A”的值。

例如。我的数据框是：

data = expand.grid(
category = LETTERS[1:3],
year = 2000:2005)
data$value = runif(nrow(data))

我尝试执行以下操作，但是，该值不会重复三次

test<-data %>% group_by(year) %>% mutate(value2 =value[category == "A"])
test
# A tibble: 18 x 4
# Groups:   year [6]
category  year  value value2
<fct>    <int>  <dbl>  <dbl>
1 A         2000 0.783   0.783
2 B         2000 0.351   0.467
3 C         2000 0.296   0.895
4 A         2001 0.467   0.102
5 B         2001 0.168   0.546
6 C         2001 0.459   0.447
7 A         2002 0.895   0.783

我需要以下结果：

1 A         2000 0.783   0.783
2 B         2000 0.351   0.783
3 C         2000 0.296   0.783
4 A         2001 0.467   0.467
5 B         2001 0.168   0.467
6 C         2001 0.459   0.467

编辑：在评论可能与软件包冲突有关之后，我添加了之前加载的软件包列表：

# install packages if not installed already
 list.of.packages <- c("stringr", "timeDate", "bizdays", 
                  "lubridate", "readxl", "dplyr","plyr",
                  "rootSolve", "RODBC", "glue", 
                  "ggplot2","gridExtra","bdscale", "gtools", "scales", "shiny", "leaflet", "data.table", "plotly")
 new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
 if(length(new.packages)) install.packages(new.packages)


  #========== Libraries to be loaded ===============
  lapply(list.of.packages, require, character.only = TRUE)
  #------

Answer 1

这有点R怪胎

> data %>% group_by(year) %>% 
+   mutate(value_tmp = if_else(category == "A", value, NA_real_),
+          value2 = mean(value_tmp, na.rm = TRUE))
# A tibble: 18 x 5
# Groups:   year [6]
   category  year      value   value_tmp     value2
   <fct>    <int>      <dbl>       <dbl>      <dbl>
 1 A         2000 0.01818495  0.01818495 0.01818495
 2 B         2000 0.5649932  NA          0.01818495
 3 C         2000 0.5483291  NA          0.01818495
 4 A         2001 0.9175864   0.9175864  0.9175864 
 5 B         2001 0.2415837  NA          0.9175864 
 6 C         2001 0.2250608  NA          0.9175864 
 7 A         2002 0.6037224   0.6037224  0.6037224 
 8 B         2002 0.8712926  NA          0.6037224 
 9 C         2002 0.6293625  NA          0.6037224 
10 A         2003 0.8126948   0.8126948  0.8126948 
11 B         2003 0.7540445  NA          0.8126948 
12 C         2003 0.02220114 NA          0.8126948 
13 A         2004 0.3961279   0.3961279  0.3961279 
14 B         2004 0.3638186  NA          0.3961279 
15 C         2004 0.8682010  NA          0.3961279 
16 A         2005 0.04196315  0.04196315 0.04196315
17 B         2005 0.4879482  NA          0.04196315
18 C         2005 0.8605212  NA          0.04196315

Answer 2

通过稍微修改Noobie的响应并使用tidyverse的填充，我获得了预期的结果：

   test <- data %>% group_by(year) %>%
   mutate(value_tmp = if_else(category == "A", value, NA_real_))%>%
   fill(value_tmp)

按dplyr组重复该值

2 个答案: