我有一个字符列表，其中包含天气变量，后跟＆＃34; mean _＃＆＃34;其中＃是5到10之间的数字。我想将列表子集化为仅具有天气变量名称。平均天气变量如下所示：
> mean_vars
[1] "dew_mean_10" "dew_mean_5" "dew_mean_6" "dew_mean_7"
[5] "dew_mean_8" "dew_mean_9" "humid_mean_10" "humid_mean_5"
[9] "humid_mean_6" "humid_mean_7" "humid_mean_8" "humid_mean_9"
[13] "rain_mean_10" "rain_mean_5" "rain_mean_6" "rain_mean_7"
[17] "rain_mean_8" "rain_mean_9" "soil_moist_mean_10" "soil_moist_mean_5"
[21] "soil_moist_mean_6" "soil_moist_mean_7" "soil_moist_mean_8" "soil_moist_mean_9"
[25] "soil_temp_mean_10" "soil_temp_mean_5" "soil_temp_mean_6" "soil_temp_mean_7"
[29] "soil_temp_mean_8" "soil_temp_mean_9" "solar_mean_10" "solar_mean_5"
[33] "solar_mean_6" "solar_mean_7" "solar_mean_8" "solar_mean_9"
[37] "temp_mean_10" "temp_mean_5" "temp_mean_6" "temp_mean_7"
[41] "temp_mean_8" "temp_mean_9" "wind_dir_mean_10" "wind_dir_mean_5"
[45] "wind_dir_mean_6" "wind_dir_mean_7" "wind_dir_mean_8" "wind_dir_mean_9"
[49] "wind_gust_mean_10" "wind_gust_mean_5" "wind_gust_mean_6" "wind_gust_mean_7"
[53] "wind_gust_mean_8" "wind_gust_mean_9" "wind_spd_mean_10" "wind_spd_mean_5"
[57] "wind_spd_mean_6" "wind_spd_mean_7" "wind_spd_mean_8" "wind_spd_mean_9"
这就是我想要的结果：
> var_names
"dew" "humid" "rain" "solar" "temp" "soil_moist" "soil_temp" "wind_dir" "wind_gust" "wind_spd"
现在我想出了如何做到这一点，但由于缺乏正则表达式的能力，我填写我的方法是无关紧要的。我也将不得不重复我的过程20次代替＆＃34;意思是＆＃34;换句话说。
var_names <- unique(str_split_fixed(mean_vars, "_", n = 3)[c(1:18,31:42),1])
var_names <- unlist(c(var_names, unique(unite(as_tibble(str_split_fixed(mean_vars, "_", n = 3)[c(19:30,43:60), 1:2])))))
我一直试图尽可能地保持在tidyverse软件包的范围内，所以我使用了stringr :: str_split_fixed。
如果你有一个使用同样功能的解决方案，那将是理想的，因为我可以继续相同的编程风格，但我对所有建议持开放态度。
感谢。
答案 0 :(得分：1)
使用sub和unique。这个更短，没有包依赖（或者使用unique(str_replace(mean_vars, "_mean.*", ""))和stringr）：
unique(sub("_mean.*", "", mean_vars))
，并提供：
[1] "dew" "humid" "rain" "soil_moist" "soil_temp"
[6] "solar" "temp" "wind_dir" "wind_gust" "wind_spd"
如果由于某种原因你真的想使用str_split，那么：
rmMean <- function(x) paste(head(x, -2), collapse = "_")
unique(sapply(str_split(mean_vars, "_"), rmMean))
mean_vars <- c("dew_mean_10", "dew_mean_5", "dew_mean_6", "dew_mean_7", "dew_mean_8",
"dew_mean_9", "humid_mean_10", "humid_mean_5", "humid_mean_6",
"humid_mean_7", "humid_mean_8", "humid_mean_9", "rain_mean_10",
"rain_mean_5", "rain_mean_6", "rain_mean_7", "rain_mean_8", "rain_mean_9",
"soil_moist_mean_10", "soil_moist_mean_5", "soil_moist_mean_6",
"soil_moist_mean_7", "soil_moist_mean_8", "soil_moist_mean_9",
"soil_temp_mean_10", "soil_temp_mean_5", "soil_temp_mean_6",
"soil_temp_mean_7", "soil_temp_mean_8", "soil_temp_mean_9", "solar_mean_10",
"solar_mean_5", "solar_mean_6", "solar_mean_7", "solar_mean_8",
"solar_mean_9", "temp_mean_10", "temp_mean_5", "temp_mean_6",
"temp_mean_7", "temp_mean_8", "temp_mean_9", "wind_dir_mean_10",
"wind_dir_mean_5", "wind_dir_mean_6", "wind_dir_mean_7", "wind_dir_mean_8",
"wind_dir_mean_9", "wind_gust_mean_10", "wind_gust_mean_5", "wind_gust_mean_6",
"wind_gust_mean_7", "wind_gust_mean_8", "wind_gust_mean_9", "wind_spd_mean_10",
"wind_spd_mean_5", "wind_spd_mean_6", "wind_spd_mean_7", "wind_spd_mean_8",
"wind_spd_mean_9")