R语言 Tidy eval在函数中失败

disbfnqx  于 2023-10-13  发布在  其他
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我试图自动化.tex表的生成，我想在stargazer的add.lines部分添加一个名为mean_outcome的值，但我在生成这个值时遇到了麻烦，我想我处理tidy eval时出错了。我已经试过了！”““但是什么都不起作用。

  1. df <- tibble::tribble(~hhid, ~treatment_arm, ~round_pooled, ~tot_lstock_count, ~tot_animal_tlu,
  2.                       "1020201023",1,1,10,1,
  3.                       "1020201023",1,11,6,0.600000023841858,
  4.                       "1020201036",1,1,10,0.100000001490116,
  5.                       "1020201036",1,11,4,0.400000005960464,
  6.                       "1020201039",1,1,9,0.0900000035762787,
  7.                       "1020201057",1,1,12,0.480000019073486,
  8.                       "1020201068",1,1,2,0.200000002980232,
  9.                       "1020201095",1,1,6,0.330000013113022,
  10.                       "1020201095",1,11,7,0.400000005960464,
  11.                       "1020201103",1,1,2,0.200000002980232,
  12.                       "1020201116",1,1,7,0.0599999986588955,
  13.                       "1020201116",1,11,2,0.0199999995529652,
  14.                       "1020201139",1,11,12,0.480000019073486,
  15.                       "1020201144",1,1,5,0.5,
  16.                       "1020201144",1,11,8,0.800000011920929,
  17.                       "1020201146",1,1,6,0.0599999986588955,
  18.                       "1020201146",1,11,6,0.0599999986588955,
  19.                       "1020201159",1,11,15,1.5,
  20.                       "1020201180",1,11,11,0.560000002384186,
  21.                       "1020201205",1,1,2,0.0199999995529652)
  23. reg_coef_tables <- function(df, y) {
  24.   
  25.   outcome = eval(`i`)  
  26.   
  27.   mean_outcome  <- df %>% 
  28.     
  29.     filter(round_pooled == 11 & treatment_arm == 1) %>% 
  30.     
  31.     summarise(mean = mean(!!outcome, na.rm = T)) %>% 
  32.     
  33.     pull(mean)
  34.   
  35.   reg1 <- felm(outcome ~ treatment_arm, data = df)
  37. stargazer(reg1,
  38.           align = TRUE, 
  39.           dep.var.labels = c("(1)"),
  40.           omit.stat = c("f", "adj.rsq", "ser"),
  41.           no.space = TRUE,
  42.           digits = 3, # number of decimals
  43.           add.lines = list(c('Mean outcome', rep(`mean_outcome`, 1)),
  44.                            dep.var.caption = "", # remove dep var header
  45.                            out = paste0(outcome, ".tex"))
  46. }          
  47.           
  48. liv_vars  = c("tot_lstock_count", "tot_animal_tlu")
  49. liv_out_list = vector("list", 2)
  50. for(i in liv_vars) {
  51.             liv_out_list[[i]] <- reg_coef_tables(df, i)
  52. }
r

1条答案

按热度按时间
vuktfyat

vuktfyat1#

撇开stargazer（因为，恕我直言，它很可怕）和felm（因为我不知道它来自哪个包），因为这两个都与tidyverse的问题无关，试试这个

  1. reg_coef_tables <- function(df, y) {
  2.   outcome = as.name(y) 
  3.   mean_outcome  <- df %>% 
  4.     filter(round_pooled == 11 & treatment_arm == 1) %>% 
  5.     summarise(mean = mean(!!outcome, na.rm = T)) %>% 
  6.     pull(mean)
  7. }
  8. liv_vars  = c("tot_lstock_count", "tot_animal_tlu")
  9. liv_out_list = list()
  10. for(i in liv_vars) {
  11.   liv_out_list[[i]] <- reg_coef_tables(df, i)
  12. }  
  13. liv_out_list
  14. $tot_lstock_count
  15. [1] 7.888889
  17. $tot_animal_tlu
  18. [1] 0.5355556

或者，更简洁地说：

  1. mean_outcome <- df %>% 
  2.   filter(round_pooled == 11 & treatment_arm == 1) %>% 
  3.   summarise(
  4.     across(
  5.       c(tot_lstock_count, tot_animal_tlu), 
  6.       \(x) mean(x, na.rm = TRUE)
  7.     )
  8.   )
  9. mean_outcome
  10. # A tibble: 1 × 2
  11.   tot_lstock_count tot_animal_tlu
  12.              <dbl>          <dbl>
  13. 1             7.89          0.536

你可以在NSE here上找到一个有用的引物。

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